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JMIR Preprints
A preprint server for pre-publication/pre-peer-review preprints intended for community review as well as ahead-of-print (accepted) manuscripts
Background: AI technologies are being increasingly integrated into medical practice. Among them, AI-assisted diagnosis has been a technology with promising perspectives, yet its acceptance (compared to human-only procedures) among patients is still understudied, especially after the release of ChatGPT. Objective: The current research is interested in the extent to which people would prefer doctors using AI assistance over traditional doctors relying solely on human expertise. Also, it studies the demographic, social, and experiential determinants of preferences over AI-assisted diagnosis. Methods: We conducted a four-group randomized survey experiment among a national sample representative of the US population on several demographic benchmarks (n = 1,762). In all four groups, participants saw the same doctor's information. The control group did not mention AI-related content. The "No AI" group explicated mentioned the doctor does not use AI. The "Moderate AI" group noted the doctor used AI moderately and the “Extensive AI” group noted that the doctor used AI extensively. Next, respondents reported their tendency to seek help, trust in the doctor as a person and a professional, knowledge of AI, frequency of using AI in their daily lives, demographics, and partisan identification. We analyzed the results with ordinary least squares regression (controlling for socio-demographic factors), mediation analysis, and moderation analysis. We also explored the effect of past AI experience. Results: Mentioning that the doctor uses AI to assist in diagnosis uniformly decreases trust and intention to seek help, regardless of age, gender, education, and party identification. Trust in the doctor and intention to seek help were highest when participants were explicitly told that the doctor does not use AI in their diagnosis. The trust and intention to seek help were similarly low when participants were told that the doctor uses AI assistance moderately or extensively. The largest "intention gap" was observed among those with the highest self-reported AI knowledge but the least AI experience, signaling that more AI experiences make people more open to AI-assisted diagnosis, but higher self-reported AI familiarity has the opposite effect. Conclusions: Our findings suggest that despite the increasing integration of AI in medical practice, there remains a strong preference for human-only expertise, underscoring the need for strategies to build trust in AI technologies in healthcare. Clinical Trial: https://osf.io/v8kzs/
Journal Description
JMIR Preprintscontains pre-publication/pre-peer-review preprints intended for community review (FAQ: What are Preprints?). For a list of all preprints under public review click here. The NIH and other organizations and societies encourage investigators to use interim research products, such as preprints, to speed the dissemination and enhance the rigor of their work. JMIR Publications facilitates this by allowing its authors to expose submitted manuscripts on its preprint server with a simple checkbox when submitting an article, and the preprint server is also open for non-JMIR authors.
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For pathway 2, if authors do not wish to have the preprint considered in a partner journal (or a specific journal), this should be noted in the cover letter. Also, note if you want to have the paper only considered/forwarded to specific journals, e.g. JMIR, PLOS, PEERJ, BMJ Open, Nature Communications etc), please specify this in the cover letter.
Manuscripts can be in any format. However, an abstract is required in all cases. We highly recommend to have the references in JMIR format (include a PMID) as then our system will automatically assign reviewers based on the references.
Background: AI technologies are being increasingly integrated into medical practice. Among them, AI-assisted diagnosis has been a technology with promising perspectives, yet its acceptance (compared t...
Background: AI technologies are being increasingly integrated into medical practice. Among them, AI-assisted diagnosis has been a technology with promising perspectives, yet its acceptance (compared to human-only procedures) among patients is still understudied, especially after the release of ChatGPT. Objective: The current research is interested in the extent to which people would prefer doctors using AI assistance over traditional doctors relying solely on human expertise. Also, it studies the demographic, social, and experiential determinants of preferences over AI-assisted diagnosis. Methods: We conducted a four-group randomized survey experiment among a national sample representative of the US population on several demographic benchmarks (n = 1,762). In all four groups, participants saw the same doctor's information. The control group did not mention AI-related content. The "No AI" group explicated mentioned the doctor does not use AI. The "Moderate AI" group noted the doctor used AI moderately and the “Extensive AI” group noted that the doctor used AI extensively. Next, respondents reported their tendency to seek help, trust in the doctor as a person and a professional, knowledge of AI, frequency of using AI in their daily lives, demographics, and partisan identification. We analyzed the results with ordinary least squares regression (controlling for socio-demographic factors), mediation analysis, and moderation analysis. We also explored the effect of past AI experience. Results: Mentioning that the doctor uses AI to assist in diagnosis uniformly decreases trust and intention to seek help, regardless of age, gender, education, and party identification. Trust in the doctor and intention to seek help were highest when participants were explicitly told that the doctor does not use AI in their diagnosis. The trust and intention to seek help were similarly low when participants were told that the doctor uses AI assistance moderately or extensively. The largest "intention gap" was observed among those with the highest self-reported AI knowledge but the least AI experience, signaling that more AI experiences make people more open to AI-assisted diagnosis, but higher self-reported AI familiarity has the opposite effect. Conclusions: Our findings suggest that despite the increasing integration of AI in medical practice, there remains a strong preference for human-only expertise, underscoring the need for strategies to build trust in AI technologies in healthcare. Clinical Trial: https://osf.io/v8kzs/
Background: Cognitive tasks are essential tools in psychology and neuroscience research, offering insights into various mental processes such as attention, perception, and memory. These tasks often in...
Background: Cognitive tasks are essential tools in psychology and neuroscience research, offering insights into various mental processes such as attention, perception, and memory. These tasks often involve simple stimuli, such as alphanumeric characters and shapes, and a large number of trials, a deliberate design choice aimed at controlling for extraneous variables and ensuring the reliability of the results. While this methodological approach is crucial for maintaining experimental rigor and validity, it may inadvertently lead to issues regarding participant engagement. Objective: The main objective of the present empirical study was to investigate whether gamified versions of 3 established cognitive tasks, namely the Visual Search, the Whack-the-Mole, and the Corsi block tasks yield the same patterns of results as their traditional counterparts. These three tasks were chosen because they are commonly used to assess attention and visual short-term memory, which are crucial for many everyday tasks. Methods: Participants executed our gamified versions of the Visual Search, the Whack-the-Mole, and the Corsi Block in one of three conditions: in Immersive Virtual Reality (VR-Lab), in a desktop VR environment presented in the lab (Desktop-Lab), and in a desktop VR environment experienced at home (Desktop-Remote). Results: The pattern of results from these gamified tasks replicated those reported in the literature about their traditional counterparts that typically employ simple stimuli and are longer in duration. Notably, some differences in findings were observed across the three administration conditions (VR-Lab, Desktop-Lab, and Desktop-Remote). In the Visual Search and the Whack-the-Mole tasks participants were 250ms and 70ms faster to respond in the VR-Lab than in the Desktop-Lab condition. Moreover, in the Whack-the-Mole task, participants were 160ms faster when carrying out the task in the Desktop-Lab than in the Desktop-Remote condition. Conclusions: Despite these differences, overall, the findings of the study confirm the potential of VR technology as a tool for assessing cognitive performance with tasks that can potentially increase participant engagement.
Background: : In healthcare settings, especially in high-pressure environments like Emergency situations, the ability to document and communicate patient information rapidly and accurately is crucial....
Background: : In healthcare settings, especially in high-pressure environments like Emergency situations, the ability to document and communicate patient information rapidly and accurately is crucial. Traditional methods for manual documentation are often time-consuming and prone to errors, which can adversely affect patient outcomes. To address these challenges, there is growing interest in integrating advanced technologies, especially Large Language Models (LLMs), into medical communication systems. However, deploying LLMs in clinical environments presents unique challenges, including the need to ensure the accuracy of medical content and to mitigate the risk of generating irrelevant or misleading information. Objective: This paper aims to address these challenges by developing a Natural Language Processing (NLP) pipeline for the extraction of text from German rescue services treatment dialogues. The objectives are twofold: (1) to generate realistic, medically relevant dialogues where the ground truth is known, and (2) to accurately extract essential information from these dialogues to populate emergency protocols. Methods: This study utilizes the MIMIC-IV-ED dataset, a de-identified, publicly available resource, to generate synthetic dialogue data for emergency department scenarios. By selecting and anonymizing data from 100 patients, we created a baseline for generating realistic dialogues and evaluating an NLP pipeline. We applied the Post Randomization Method (PRAM) for non-mechanical data perturbation, ensuring patient privacy and data utility. Dialogue generation was conducted in two stages: initial generation using the "Zephyr-7b-beta" model, followed by refinement and translation into German using GPT-4 Turbo. A Retrieval-Augmented Generation (RAG) approach was developed for extracting relevant information from these dialogues, involving chunking, embedding, and dynamic prompt templates. The model's performance was evaluated through manual review and sentiment analysis, ensuring that the generated dialogues maintained clinical relevance and emotional accuracy. Results: The data generation pipeline produced 100 dialogues, with initial English dialogues averaging 2,000 tokens and German dialogues 4,000 tokens. Manual evaluation identified certain redundancies and formal language in the German dialogues. Sentiment analysis revealed a reduction in negative sentiment from 67% to 59% and an increase in positive sentiment from 27% to 38%, which may negatively impact text extraction, as positive sentiments may not align well with identifying critical topics such as suicidal thoughts. The RAG-based extraction system achieved high precision and recall in both nominal and numerical features in the initial dialogues, with F1-scores ranging from 86.21% to 100%. However, performance declined in the refined dialogues, with notable drops in precision, particularly for "Diagnosis" (60.82%) and "Pain Score" (57.61%). Conclusions: The results of the study underscore the system's robust capabilities in processing structured data efficiently, demonstrating its strength in managing well-defined, quantitative information. However, the findings also reveal limitations in the system’s ability to handle nuanced clinical language, particularly when it comes to non-English and non-Chinese languages.
Background: Diabetic retinopathy (DR), a leading cause of preventable blindness among working-aged adults.
Black, Latine, and individuals living in poverty are screened less for DR, diagnosed later,...
Background: Diabetic retinopathy (DR), a leading cause of preventable blindness among working-aged adults.
Black, Latine, and individuals living in poverty are screened less for DR, diagnosed later, treated
less often, and go blind more than wealthy white individuals. Objective: Through a community-led research approach, this project engaged community members directly
to co-design a digital health tool that is accessible, user-friendly, and culturally relevant. Methods: Using a qualitative approach, we conducted 4 semi-structured focus groups with 19 individuals
from the Greater New Haven area, aged 18 years or older, and diagnosed with diabetes. We
transcribed and coded contextual interviews and categorized them into themes using affinity
mapping. The study has two specific aims: (1) to complete a comprehensive needs assessment
aimed at (2) developing a community-responsive digital health tool to increase access to and
knowledge of diabetic retinopathy (DR) screening in high-risk populations. We transcribed the
focus group interviews, used rapid qualitative analysis to generate themes, and completed
affinity mapping to identify content and features for a digital health tool for preventing blindness
from diabetic retinopathy. Results: We interviewed 19 individuals (68% female, 47% Black, 26% Hispanic,11% indigenous) in 4
focus groups. Over 80% had access to smart devices. Participants’ self-reported mean [SD] A1c
was 6.77 [1.93]. Age mean [SD] was 58.79 [19.54]. Almost half (48%) of participants completed
some college. The principal themes obtained from coding contextual interviews were desired app
attributes, mental impact, informal support, content knowledge related to diabetes, barriers, diet-related topics, and receiving notifications. Conclusions: DR is one of the leading causes of blindness, and many treatments exist. Despite the existence of
treatments, historically marginalized populations experience poor health outcomes, including
blindness. Our community-based approach empowers the creation of a culturally sensitive digital
health tool that will engage more of the patient population with DR.
Background: Fetal circulation differs from the extrauterine circulatory mode by the anatomical and functional way it occurs. Understanding the flow of this circulation is fundamental for medical stude...
Background: Fetal circulation differs from the extrauterine circulatory mode by the anatomical and functional way it occurs. Understanding the flow of this circulation is fundamental for medical students. However, the anatomy and physiology of the fetal circulation process are complex, making understanding it difficult. Objective: We aimed to describe the study of gamification applied to the anatomy and physiology of fetal circulation, especially establishing a relationship with the treatment of fetal diseases, for the computer game "Fetal Circulation." Methods: We developed descriptive research on the topic of fetal circulation. We created a prototype of a computational game using the C# language, the Unity 3D platform, with graphic libraries, and the use of free software components. Results: We developed the first phase of the game prototype about fetal circulation. Further advances must be provided in a second phase. Conclusions: Thus, the first phase describes the basic diagram of the screen and graphic layers and the fundamental paths for the gamification. These preliminary results are disposed of in the manuscript. We are programming and designing the subsequent phases of the game, which will include the application of the simulated fetal circulation diseases. Machine learning, Gamification, Fetal circulation
This cross-sectional study reveals enrichment of women oncology physicians on X (formerly Twitter) from typically male-dominated fields, as well as higher time-adjusted levels of self-engagement, sugg...
This cross-sectional study reveals enrichment of women oncology physicians on X (formerly Twitter) from typically male-dominated fields, as well as higher time-adjusted levels of self-engagement, suggestive of an inherent desire for women to engage on social media for professional use, though the longitudinal impact of these behavioral differences on existing gender disparities is worthy of further study.
With the exponential growth in the number of research papers and the proliferation of preprint servers, ensuring high-quality peer review has become a significant challenge, especially in the medical...
With the exponential growth in the number of research papers and the proliferation of preprint servers, ensuring high-quality peer review has become a significant challenge, especially in the medical field. The surge in submissions has led to a shortage of qualified reviewers, slowing down the peer review process. The repeated review of rejected manuscripts not only increases costs but may also stifle research innovation, raising concerns about the efficiency, fairness, and effectiveness of the review process. Therefore, innovative solutions are urgently needed. Recent advancements in generative artificial intelligence (GenAI), such as ChatGPT, have demonstrated exceptional capabilities in feature learning and textual expression, allowing them to identify complex relationships within data without relying on pre-existing assumptions. GenAI present an opportunity to enhance semi-automated peer review systems, potentially addressing the current limitations in the peer review process and improving the efficiency and quality of medical publications. This viewpoint highlights the potential benefits and challenges of integrating GenAI into the peer review and identifies the key issues that need to be addressed.
Background: Post-stroke spasticity (PSS) is a frequent sequela in patients who have suffered a stroke. This form of paralysis is more prevalent compared to other post-stroke sequelae and is among the...
Background: Post-stroke spasticity (PSS) is a frequent sequela in patients who have suffered a stroke. This form of paralysis is more prevalent compared to other post-stroke sequelae and is among the most challenging and complex symptoms to manage. Surface electromyography (sEMG) can reflect the physiological information of muscles in real time and is highly beneficial in diagnosing neuromuscular diseases in clinical medicine. This study aimed to investigate the timing of post-stroke limb spasms using a nested case-control study combined with sEMG and to identify and predict factors of PSS at an early stage. Objective: This clinical study aimed to improve the prognosis of patients with PSS by exploring the time of PSS occurrence through a nested case-control study, early identification, and prediction of PSS factors. Methods: This was a nested case-control study. Participants were assessed within 24 h of the onset of hospitalization using a standardized case report form to evaluate general patient information and clinical data related to cerebral infarction and imaging. Upon inclusion, patients were assessed after 1, 2, 4, 8, and 12 weeks, using the Modified Ashworth Scale (MAS) for spasticity severity, root mean square (RMS) values from (sEMG) for limb spasm severity, and the simplified Fugl-Meyer Assessment (S-FM) for limb motor function. Patients who experienced spasticity within 12 weeks were assigned to the spasticity group, whereas those who did not experience spasticity were assigned to the control group. Unmatched case grouping was implemented. Data with normal distribution was analyzed using the t-test, while data with non-normal distribution was analyzed using the rank-sum test; categorical data was analyzed using the chi-square test, rank-sum test, or Fisher's exact test. Logistic regression analysis was used to investigate factors affecting treatment outcomes. Data processing, analysis, and visualization were conducted using Statistical Package for the Social Sciences software (version 26.0). Results: The patient is still being recruited Conclusions: The patient is still being recruited Clinical Trial: Ethics and dissemination: The study has been approved by the Ethics Committee of the Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine (approval number: [202371]). All patients were required to provide a written informed consent before enrollment. The findings of this investigation were mandated for publication in peer-reviewed journals.
Clinical trial registration: ClinicalTrials.gov ChiCTR2300077121.
Background: Mobile health (mHealth) applications represent a promising tool to bridge the healthcare
gaps by enhancing knowledge and facilitating early detection practices like breast self-examinatio...
Background: Mobile health (mHealth) applications represent a promising tool to bridge the healthcare
gaps by enhancing knowledge and facilitating early detection practices like breast self-examination
(BSE). Objective: This study aimed to evaluate the effectiveness and usability of BreMo in increasing breast cancer
knowledge and practice of BSE among nurses in Nepal. Methods: We conducted a quasi-experimental study involving 92 nurses at Nepalgunj Medical College,
utilizing the BreMo application over a three-month period. Pre- and post-intervention assessments were
conducted to measure changes in knowledge and usability, employing the use of a self-administered
BCAMAQ questionnaire. Change in mean knowledge scores and shift in first quantile of scores, Q1 after
the intervention were evaluated. Using the Likert scale, BreMo’s user experience was also assessed in
terms of usability, content, privacy, acceptability and satisfaction. Results: We found a significant increase in mean knowledge score (shift from 20.86 to 21.72, p<0.001) of
participants between pre-intervention and post-intervention phases. Similarly, a significant shift in first
quartile (Q1) mean knowledge score (shift from 20.68 to 21.52, p<0.001) was observed between pre-
intervention and post-intervention phases. Highest scores were obtained in BSE knowledge (9.1%
increase) and practice (14.3% increase). BreMo was rated highly (more than 90% rated at higher than 4,
out of 7) in all categories: usability, privacy, content clarity, acceptability and satisfaction except privacy
where 51% participants were found to be unsure. Conclusions: We showed the valuable potential of mHealth application to enhance breast cancer
knowledge and BSE practices among nurses in Nepal given that women are educated enough to read
and use the application. The higher usability ratings of the application underscore its feasibility as a health
education tool.
Background: High blood pressure is a leading risk factor for cardiovascular, brain, and kidney diseases. In Japan, a significant number of individuals are undergoing treatment for hypertension. High b...
Background: High blood pressure is a leading risk factor for cardiovascular, brain, and kidney diseases. In Japan, a significant number of individuals are undergoing treatment for hypertension. High blood pressure is linked to unhealthy lifestyles, and its treatment includes medications and lifestyle interventions such as exercise. Objective: We aimed to investigate the effect of regular dance therapy interventions with videos on blood pressure in hypertensive patients to provide a reference for prescription studies on dance exercise therapy in these patients. Methods: This non-blind, double-arm, randomized trial was conducted at Juntendo University, Tokyo, from April to December 2023. 40 hypertensive patients were randomly assigned to either an intervention group (dance) or a control group (self-selected exercise), with each group comprising 20 participants. The intervention group performed daily dance exercises using modern dance videos (10 minutes per video) uploaded to YouTube. The control group performed non-dance exercises for 10 min daily. The activity levels of the participants were monitored using a triaxial accelerometer. Blood pressure and body composition were measured at baseline and after 2 months. Results: 34 patients were included in the study (16 in the intervention group and 18 in the control group). The exclusion criteria were lack of blood pressure data, medication changes, or withdrawal from the study. Overall, 18 (52.9%) patients were female, aged 56±10. The basic characteristics did not differ between the 2 groups. The intervention group showed a significant reduction in both systolic BP (SBP) and diastolic BP (DBP) compared with the control group. Multivariable analysis showed that SBP was -9.7±3.3 (P = 0.0064) and DBP was 12.8±6.1 (P = 0.0047). Conclusions: Unsupervised YouTube dance exercise was more effective in lowering blood pressure than conventional exercise prescriptions. We hope that these results will contribute to exercise therapy for patients with lifestyle-related diseases.
Background: Virtual reality (VR) is a rapidly developing technology that has gained significant traction in the medical domain, particularly in the treatment and rehabilitation of individuals with str...
Background: Virtual reality (VR) is a rapidly developing technology that has gained significant traction in the medical domain, particularly in the treatment and rehabilitation of individuals with stroke. The growing use of VR in stroke management has led to a notable increase in clinical investigations. Objective: The aim of this study is to present a bibliometric analysis of VR for stroke studies to identify prevailing research trends and guide future scientific research. Methods: Articles and reviews on the topic of virtual reality for stroke were retrieved from the Science Citation Index Expanded of Web of Science Core Collection database. The data related to publications, countries, institutions, authors, journals, citations, and keywords in the studies were systematically analyzed using VOSviewer 1.6.20 and Citespace 6.3.1 software. Results: A total of 1171 papers on the topic of VR for stroke between 1999 and 2023 were analyzed and visualized to identify research hotspots and trends in the field. The number of annual publications in this field of study has increased gradually over the past 20 years, with the number of annual publications peaking in 2022 (n=154). In terms of publications and total citations, countries, institutions, and authors from North America and Western Europe were found to make significant contributions to the field. The current hotspot is concentrated on evaluating the effectiveness of VR for improving upper limb and balance functions in stroke patients. The keyword analysis indicates that the latest research is oriented to investigate the effectiveness of VR in combination with rehabilitation techniques such as physiotherapy and occupational therapy for the treatment of stroke, and the advancements in VR technology are increasingly gaining focus. Conclusions: Our study offers insights into the current hotspots and emerging trends of VR in the treatment of stroke. These findings may serve as a guide for future research and the application of VR for stroke.
Background: Medical Marijuana (MMJ) is available in Pennsylvania and participation in the state-regulated program requires a patient to register and receive a certification by an approved physician....
Background: Medical Marijuana (MMJ) is available in Pennsylvania and participation in the state-regulated program requires a patient to register and receive a certification by an approved physician. There is currently no integration of MMJ certification data in Pennsylvania into health records that would allow for physicians to rapidly identify patients that are using MMJ, as there are with other scheduled drugs. This absence of a formal data sharing structure necessitates tools that aid in consistent documentation practices to enable comprehensive patient care. Objective: Customized smart data elements (SDE) were made available to clinicians at an integrated health system, Geisinger, following MMJ legalization in Pennsylvania. The purpose of this project was to examine and contextualize the use of MMJ SDEs in the Geisinger population. We accomplished this goal by developing a systematic chart review protocol, with the goal of creating a tool that resulted in consistent human data extraction. Methods: We developed a chart review protocol for extracting MMJ-related information. The protocol was developed between August to December of 2022 and focused on a patient group that received one of several MMJ SDE between 1/25/2019 and 5/26/2022. Characteristics were first identified on a small pilot sample of patients (N=5), which were then iteratively reviewed to optimize for consistency. Following the pilot, two reviewers were assigned 200 patient charts, selected randomly from the larger cohort, with a third reviewer examining a subsample to determine reliability. We then summarized the clinician-level and patient-level features from n=156 charts with a table-format SDE that best captured MMJ information. Results: We found the chart review protocol was feasible for those with minimal medical background to complete, with high inter-rater reliability (Kappa = 0.966 (p <0.001), 95% CI (0.954 - 0.978)). MMJ certification was largely documented by nurses and medical assistants (87.2%) and typically within primary care settings (68.6%). The SDE has 6 pre-set field prompts, including certifying provider, authorized dispensary, certifying conditions, dosage, product, and active ingredient. We found preset fields were overall well-recorded (76.6% across all fields). Individual fields were more heterogeneous in terms of completion, with dispensary specified in 87.8% of documentation, certifying provider specified in 61.5% of documentation, and product dose specified in only 30.8% of documentation. Conclusions: This method of chart review yields high quality data extraction that can serve as a model for other health record inquiries. Our evaluation showed relatively high completeness of SDE fields, primarily by clinical staff responsible for rooming patients. Improving adoption and fidelity of SDE data collection may present a valuable data source for future research on patient MMJ use and treatment efficacy and outcomes. Clinical Trial: N/A
Background: Recent advancements in artificial intelligence, particularly with large language models (LLMs), have shown potential in the automated generation of synthetic clinical electronic health rec...
Background: Recent advancements in artificial intelligence, particularly with large language models (LLMs), have shown potential in the automated generation of synthetic clinical electronic health records (EHRs). However, concerns regarding the performance of these models and the manifestation of gender and racial biases in their outputs necessitate a thorough examination, especially as these models are increasingly applied in healthcare settings. Objective: This study aims to systematically assess the performance of various LLMs in generating synthetic EHRs and to critically evaluate the presence of gender and racial biases in the generated outputs. The study introduces the Electronic Health Record Performance Score (EPS) as a novel metric for comparing the efficacy of different LLMs, particularly focusing on bilingual English-Chinese models versus predominantly English models. Methods: We evaluated seven open-source LLMs across 20 diseases, analyzing the completeness and bias of the generated EHRs. Gender and racial biases were quantified using statistical methods, including chi-square tests. The study involved the generation of 140,000 synthetic patient cases, which were assessed using the EPS and attribute-specific EPS (EPSgender and EPSrace). Model performance was analyzed in relation to model size, cultural background, and training data diversity. Results: The findings revealed significant differences in the accuracy of synthetic EHRs generated by different models, with larger models generally performing better but also exhibiting more pronounced biases. Gender biases were found to increase with model size, particularly aligning with the gender prevalence of specific diseases. Racial biases were more complex, with a consistent overrepresentation of white patients across most diseases. The study highlighted that increasing the diversity of training data did not necessarily reduce racial biases. Conclusions: This study underscores the critical need for ongoing interdisciplinary research to enhance the fairness and reliability of LLMs in healthcare. The pervasive gender and racial biases identified in LLM-generated EHRs emphasize the importance of developing methods for bias detection and mitigation to ensure equitable healthcare delivery and education. Future research should focus on refining these models to better represent diverse patient populations while maintaining high performance in EHR generation.
Background: Chronic pain is a frequent problem in society, having an enormous impact. Tools that enhance the assessment to understand better people with pain experiences are essential to provide the c...
Background: Chronic pain is a frequent problem in society, having an enormous impact. Tools that enhance the assessment to understand better people with pain experiences are essential to provide the care people need. In this line, a qualitative approach based in written narratives (WNs) from the people suffering chronic pain can be quite useful as supported in different studies. However, the assessment from this perspective can be time-consuming. Objective: This study explores the feasibility of employing LLMs to assess WNs of people with chronic pain. At the end, we want to evaluate the potential of applying this LLMs to assist clinicians in assessing patients’ pain. Methods: We performed an experiment based on a list of pain narratives made by people with fibromyalgia and qualitatively evaluated in Serrat et al.[17]. Focusing on pain severity and disability, we prompt GPT-4 to assign scores and scores' explanations, to these narratives. Then we quantitatively compare GPT-4 scores with experts' scores of the same narratives, employing statistical measures such as Pearson correlations, Root Mean Squared Error (RMSE), Gwet's AC2 and Krippendorff's α. Additionally, experts specialized in chronic pain conducted a qualitative analysis of the scores' explanation to assess their accuracy and potential applicability of GPT's analysis for future pain narrative evaluations. Results: Our analysis reveals that GPT-4's performance in assessing pain narratives yielded promising results. GPT-4 was comparable in terms of agreement with experts, correlations with standardized measurements, and error rates. Moreover, experts generally deemed the ratings provided by GPT-4, as well as the scores' explanation, to be adequate. Conclusions: These findings underline the potential of LLMs in facilitating the assessment of pain narratives, offering a novel approach to understanding and evaluating patient pain experiences. The integration of automated assessments through LLMs presents opportunities for streamlining and enhancing the evaluation process, paving the way for improved patient care and tailored interventions in the realm of chronic pain management.
Background: The growth of studies evaluating ChatGPT's performance in exams swamped the medical education community. However, it has been proved from low to high-stakes examination, affecting the reli...
Background: The growth of studies evaluating ChatGPT's performance in exams swamped the medical education community. However, it has been proved from low to high-stakes examination, affecting the reliability and validity of findings. To ensure reliability and bring a final consensus, we opted to synthesize the evidence of ChatGPT's performance under high-stakes examinations, namely, National Licensing Medical Examinations (NLME). Objective: To evaluate ChatGPT’s NLMEs performance and assess whether it could achieve a license to practice in various countries. Methods: We searched the Pubmed and Scopus databases for studies that evaluated ChatGPT's performance in NLMEs. In addition to the reference list and in Google Scholar. Studies were screened, and the accuracy rate (performance) of ChatGPT was extracted, as well as other study characteristics. Results: We identified 37 studies that evaluated ChatGPT's performance across 18 NLMEs. Most studies evaluated the performance of ChatGPT in the NLME of the United States, China, and Japan. While the majority of studies used official datasets, others used unofficial ones from third parties, and a scarce number of studies used prompting techniques. GPT-4 was superior to GPT-3.5 in all NLMEs and could pass all of them. GPT-4 overperformed the average performance of examinees' in most studies, except the Japan NLME. Conclusions: Current evidence suggests that ChatGPT can pass 18 NLMEs, surpassing almost all candidates, and, if possible, receive a "global medical license." Further research should move towards using ChatGPT as GPT-4o in performance assessment and exploring the potential of ChatGPT for NLMEs development and validation. Moreover, our findings represent a call for reimagining assessment in medical education. Clinical Trial: Not applicable
Background: It is imperative to maintain precise dosing records in repeated-dose pharmacokinetic studies involving healthy volunteers to ensure data validity. Conventional techniques, such as direct o...
Background: It is imperative to maintain precise dosing records in repeated-dose pharmacokinetic studies involving healthy volunteers to ensure data validity. Conventional techniques, such as direct observation, self-reporting, and pill counts, often prove inadequate in terms of accuracy and practicality. Video-based monitoring systems have emerged as a promising alternative, offering enhanced accuracy and reduced burden on stakeholders. This study assesses the efficacy of an asynchronous video-based Self-Administration of the Investigational Product (SAI) monitoring system (VSMS) in ensuring accurate dosing in clinical trials with healthy volunteers in Korea. Objective: The primary objectives of this study were to evaluate the usefulness of an asynchronous VSMS in validating subject SAI in a repeated-dose pharmacokinetic study and to explore patterns of subject compliance with planned dosing times, suggesting possible applications for such a system. Methods: A retrospective analysis was conducted using data from 17,619 SAI events in repeated-dose clinical trials employing the VSMS between February 2020 and March 2023. The SAI events were classified into four categories: Verified On-time Dosing, Verified Deviated Dosing, Unverified Dosing, and Missed Dosing. Analysis methods included calculating the success rate for verified SAI events and analyzing trends in deviation between planned and actual dosing times (PADEV) over the dosing period and by push notification type. The mean PADEV for each subsequent dosing period was compared with the initial period using either a paired t-test or a Wilcoxon signed-rank test to assess any differences. Results: The VSMS achieved a high success rate of 97%, with 99% of the classified as Verified On-time Dosing. An analysis of trends in dosing time deviations revealed a tendency towards delayed dosing in cohorts 1, 2, 6, 8, 12, and 14, while cohorts 3, 4, 5, 7, 9, 10, 11, and 13 exhibited a tendency to dose earlier than the planned time. A comparison of the initial and subsequent dosing periods revealed no significant differences in dosing time deviations for most cohorts. However, significant differences (P < .05) were observed on only 16% (13 out of 79 days). The analysis of the impact of push notification types revealed a trend towards the highest compliance with planned dosing times when both Dosing Notifications and Dosing Reminders were provided (average PADEV: -3.5 ± 31.3 minutes). Conclusions: The VSMS effectively enabled real-time remote monitoring and verification of SAI events in early clinical trials. Additionally, the system facilitated control over subject SAI behavior through targeted push notifications and communication. Its utility is expected to grow with more data and experience.
Technology-assisted physical activity interventions for older adults in their home-based environment have been used to promote physical activity. While previous reviews focused on health-related outco...
Technology-assisted physical activity interventions for older adults in their home-based environment have been used to promote physical activity. While previous reviews focused on health-related outcomes of such interventions, this scoping review explores the characteristics of the technology in relation to the characteristics of populations, exercise types and usability in terms of adverse events, drop-outs, adherence and user experience.
We identified 8496 sources. After title and abstract screening, 455 full texts were assessed, and 148 were included, representing 12,717 participants aged 74 (SD 6) years. In total, 93 (63%) sources reported on the population’s health status. The main purpose of the interventions was balance (51%), and strength and power (43%) and intervention purposes were not related to embedded technology. In studies where the participant’s health status was reported as healthy, 53% implemented exergames compared to only 27% in studies with participants with a clinical condition. Mobile apps (20%) and trackers (11%) were implemented likewise in both groups. The technology was embedded to provide continuous exercise information (27%) and exercise feedback (27%) or to record real-time movement data (26%).
Adverse events were reported in 68 (46%) of the sources with three quarters (49 sources) reporting no adverse events. Only 2 mild events were related to technology. Dropout rates were reported in 100 (68%) studies, with no differences between intervention (16±16%) and control (14±12%) groups. Dropout reasons related to technology in 3%. Adherence was reported in 78 studies (53%) and was slightly higher in the intervention group (80±18%) compared to the control group (71±25%). A significantly higher adherence was found between interventions that were tailored (83 ± 15%) versus those that were not (75±21%). General enjoyment of the technology was captured in 55 studies (37%) and was rated positive (91%), neutral (7%) or negative (2%). Occasionally reported wishes were related to goal setting, feedback, technical support, exercise variation, and social setting.
In conclusion, various technologies were successfully used in healthy and clinical older populations. The embedded technology was not a reason for additional dropouts, lead to slightly better adherence, and adverse events were rarely related to technology. When assessed, the technology was well accepted and positively enjoyed.
Background: Stress-related disorders, such as adjustment disorder and exhaustion disorder, are prevalent and associated with significant personal suffering and societal costs. While cognitive behavior...
Background: Stress-related disorders, such as adjustment disorder and exhaustion disorder, are prevalent and associated with significant personal suffering and societal costs. While cognitive behavioral therapy has shown efficacy in treating these conditions, knowledge about factors contributing to treatment response is limited. Improved identification of such factors could enhance assessment procedures and treatment strategies. Objective: This study aims to (1) evaluate putative predictors of treatment outcome in patients with stress-related disorders using traditional prediction methods and (2) model treatment outcomes utilizing a machine learning approach. The primary outcome of interest is responder status on the Perceived Stress Scale-10, evaluated based on the reliable change index post-treatment. Methods: Data from a randomized controlled trial comparing two internet-delivered treatments for patients diagnosed with adjustment disorder or exhaustion disorder (N = 300) will be analyzed. Putative predictors include sociodemographic and clinical information, clinician-assessed data, self-rated symptoms, and cognitive test scores. For the traditional approach, univariate logistic regressions will be conducted for each predictor, followed by an ablation study for significant predictors. For the machine learning approach, four classifiers (logistic regression with Elastic Net, random forest, support vector machine, and AdaBoost) will be trained and evaluated. The dataset will be split into training (70%) and testing (30%) sets. Hyperparameter tuning will be conducted using 5-fold cross-validation with randomized search. Model performance will be assessed using balanced accuracy, precision, recall, and area under the curve. Results: All data to be used in the present study was collected between April 2021 and July 2022. We hypothesize that key predictors will include younger age, education level, baseline symptom severity, treatment credibility, and history of sickness absence. We anticipate that the machine learning models will outperform a dummy model predicting the majority class and achieve a balanced accuracy of 67% or higher, thus being considered clinically useful. Conclusions: This study will contribute to the limited research on predictors of treatment outcome in stress-related disorders. By comparing traditional and machine learning approaches, it aims to enhance our understanding of factors influencing treatment response. The findings could support the development of more personalized and effective treatments for individuals diagnosed with adjustment disorder or exhaustion disorder, potentially improving clinical practice and patient outcomes. If successful, this approach may encourage future studies with larger datasets and the implementation of machine learning models in clinical settings, ultimately enhancing precision in mental health care. Clinical Trial: ClinicalTrials ID: NCT04797273. Trial registration date 15 March 2021.
Background: Objectives: To explore the influencing factors and path of health information avoidance behavior of cancer patients in the age of smart media, and to construct a theoretical model of influ...
Background: Objectives: To explore the influencing factors and path of health information avoidance behavior of cancer patients in the age of smart media, and to construct a theoretical model of influencing factors. Methods: Face-to-face interviews were used to collect primary data, following the steps of the rooted theory research method. NVivo 12 software was applied to code and analyze the data, and a theoretical model of the factors influencing the health information avoidance behaviors of cancer patients was constructed by combining with the Stimulus-Human Body-Response (SOR) theory. Results: This study proposed six research hypotheses by analyzing the content of the interviews, which showed a causal relationship between psychological factors and health information avoidance behavior; personal, informational, and environmental factors, while indirectly influencing the health information avoidance behavior of cancer patients through the mediating role of psychological factors; capacity factors moderated the chain of factors from information factors and environmental factors to psychological factors to health information avoidance behaviors, respectively. Conclusions: In this study, we proposed a theoretical model of the factors influencing cancer patients' health information avoidance behavior in the smart media era. This model can summarize the influencing factors of cancer patients' occurrence of health information avoidance behaviors in the environment of the Smart Media Era, and provides research hypotheses and theoretical frameworks for further explaining the role path relationships between the influencing factors.
Background: With the rapid development and iteration of generative artificial intelligence, the growing popularity of such groundbreaking tools among nurse researchers, represented by ChatGPT, is rece...
Background: With the rapid development and iteration of generative artificial intelligence, the growing popularity of such groundbreaking tools among nurse researchers, represented by ChatGPT, is receiving passionate debate and intrigue. Although there has been qualitative research on generative artificial intelligence in other fields, little is known about the experiences and perceptions of nurse researchers, and this study seeks to report on the subject. Objective: This study aimed to describe the experiences and perceptions of generative artificial intelligence among Chinese nurse researchers. Provide a reference for the application of generative artificial intelligence in nursing research in the future. Methods: Semi-structured interviews were used to collect data in this qualitative study. Data were analyzed employing inductive content analysis. Results: Five themes and twelve sub-themes were categorized from 27 original interview documents as follows: (1) Diverse reflections on human-machine symbiosis, which includes the interplay between substitution, researchers shaping the potential space of generative artificial intelligence, and researchers accepting generative artificial intelligence with alacrity; (2) Heterogeneity of groups and experiences, including diversity in experiences of using and heterogeneity in the perception and use among different groups; (3) Research paradigm reshaping in the infancy stage, which involves a groundbreaking auxiliary tool in nursing research and the incubation of innovative research paths; (4) Ethical concerns and application challenges, considering insight into the public opinion around generative artificial intelligence, academic integrity and medical ethical challenges, and limitations on application in nursing research; (5) Future development and capacity reinforcement, which concerns reinforcement needs for utilization competency and collaboration and exploration in future nursing research. In this context, the first four themes form the rocket of the human-machine symbiosis journey. Only when humans fully leverage the advantages of machines (generative artificial intelligence) and overcome the shortcomings of them, can this human-machine symbiosis journey reach towards the correct future direction (fifth theme). Conclusions: This study explored the experiences and perceptions of nurse researchers interacting with generative artificial intelligence, which was a "symbiotic journey" full of windings. The human-machine interaction process relentlessly moves nurse researchers to improve scientific literacy, digital literacy, and prompt skills. Meanwhile, the potential hazards and concerns of this topic for nurse researchers became apparent, with an emphasis on academic integrity, drafting relevant specifications, and the accuracy of generated content. Collaboration with interdisciplinary professionals, utilizing supervised fine-tuning, knowledge graphs, and retrieval augmented generation techniques, to develop nursing research-specific multimodal artificial general intelligence was expected to meet the individual needs of nurse researchers.
Background: Globally, 10% of pregnant women and 13% of postpartum women experience mental disorders. In Bangladesh, nearly half of all mothers face common mental disorders, but mental health services...
Background: Globally, 10% of pregnant women and 13% of postpartum women experience mental disorders. In Bangladesh, nearly half of all mothers face common mental disorders, but mental health services and trained professionals are scarce to serve this need. To address this, the Government of Bangladesh's NCDC Programme initiated the "Wellbeing Centre," a tele-mental health service in selected public hospitals. Objective: This study examines the implementation outcomes of the Wellbeing Centre, with a particular focus on antepartum and postpartum women. Methods: Between January 2023 and August 2024, we interviewed 911 antepartum and postpartum women receiving mental health services, along with 168 healthcare providers, at six Wellbeing Centres in four districts in Bangladesh. Data collection involved both quantitative and qualitative methods. Implementation outcomes were measured following the World Health Organization’s implementation research framework. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) questionnaires. Descriptive statistics and adjusted odds ratios (aOR) with 95% confidence intervals (CI) were used to evaluate the implementation outcomes. Qualitative information was obtained through in-depth interviews (IDIs) and key informant interviews (KIIs). Results: Among 168 health care providers, almost everyone (99%) reported that the Wellbeing Centre is feasible to implement in their health facilities, however, about half (50%) felt the lack of sufficient trained staff to operate. Almost all women agreed that Wellbeing Centre is acceptable (99.9%) and useful (99.9%), and its enhanced accessibility to mental healthcare (99%). Patients visiting district-level hospitals had higher odds of accessibility (aOR:1.5; 95% CI: 1.1-2.0) to Wellbeing Centres. Besides, 77.3% women experienced depressive and 76.7% women experienced anxiety symptoms. About 52% experienced tiredness or lack of energy, 51% felt nervous, anxious, or on edge, and 57% felt worries and 4% had suicidal ideation almost every day. Patient visiting the district hospitals had higher odds (aOR: 2.6; 95% CI: 1.8-3.78) of both depression and anxiety symptoms compared to the patients visiting sub-district level hospitals. The decreasing trend of average PHQ-9 score (from 14.2 to 12.7) and GAD-7 score (from 12.9 to 12.0) between two counselling sessions indicated an improved mental health in antepartum and postpartum women. The Wellbeing Centres’ services are appreciated for their health providers, free and accessible treatment, and privacy. However, stigma, postpartum illness, and long waiting times prevented some women from utilising these services. Conclusions: To our knowledge, this is the first implementation research assessing tele-mental health in public health facilities involving a pool of trained psychologists and psychiatrists. Our study highlighted the increased accessibility, feasibility, acceptability, and utility of Wellbeing Centres for antepartum and postpartum women in Bangladesh. This supports evidence-based decisions for introducing and scaling up Wellbeing Centres in Bangladesh and other low- and middle-income countries.
Background: Bronchiectasis is characterized by intractable dyspnea, decreased functional capacity, restricted airflow, acute exacerbation episodes, and irreversible blockage. A common symptom is a pro...
Background: Bronchiectasis is characterized by intractable dyspnea, decreased functional capacity, restricted airflow, acute exacerbation episodes, and irreversible blockage. A common symptom is a productive cough due to mucus hypersecretion. Clearing the lungs can prevent infections, enhance energy conservation, improve breathing, and lung function. Oscillating positive expiratory pressure (OPEP) devices, such as the RC Cornet Plus and Aerobika, are non-pharmacological interventions that facilitate sputum clearance by combining airway oscillations and positive pressure to keep airways open. These devices are safe compared to pharmacological therapies. Objective: The Aerobika device has five resistance settings adjustable by the patient. Similarly, the RC Cornet Plus allows patients to determine optimal pressure and flow by turning the mouthpiece. Both are flow-dependent devices. However, the comparative effectiveness of these devices in bronchiectasis patient`s needs further exploration. To address this gap, comparative research is needed on Symptomatic and clinical outcomes. Methods: A single-center, 18-month experimental comparative study with thirty participants will be selected based on inclusion and exclusion criteria, provided with study information, and asked for informed consent. They will be divided into two groups of 15 each: Group A (RC Cornet Plus with conventional chest physiotherapy) and Group B (Aerobika with conventional chest physiotherapy). Sputum volume and lung functions (FEV1, FVC, and FEV1/FVC) will be assessed on day 1 and reassessed on day 7 after a week of intervention with twice-daily physiotherapist visits. Results: As of November 2023, we enrolled 30 participants, and the data collection process started from November 2023- November 2024. The expected results are that the significance of RC cornet will be more than that of the Aerobika device, and the expected results to be published in the end week of November 2024. Conclusions: The study will conclude that is RC Cornet device is effective than Aerobika Device on pulmonary function and sputum volume. Clinical Trial: This study is registered under CTRI Number- CTRI/2024/07/071083, registered on 23/07/2024.
Background: Standardized patients (SPs) prepare medical students (MSs) for difficult conversations with patients, such as discussions about life-changing diagnostic results. Despite their value, SP tr...
Background: Standardized patients (SPs) prepare medical students (MSs) for difficult conversations with patients, such as discussions about life-changing diagnostic results. Despite their value, SP training is constrained by available resources and competing clinical demands. Researchers are turning to generative pre-trained transformers (GPTs) and other large language models (LLMs) to create communication skills simulations that incorporate computer-generated (virtual) SPs (VSPs). GPT-4 is a major LLM advance that makes it practical for developers to use text-based prompts instead of Branching Path Simulations (BPS) that rely on pre-scripted conversations. These nascent developmental practices have yet to take root in the literature to guide other researchers in developing their own simulations. Objective: This study aims to describe our developmental process and lessons learned for a GPT-4-driven VSP. We designed the VSP to help MS learners rehearse discussing abnormal mammography results with a patient as a primary care physician (PCP). Methods: We conducted in-depth interviews with 5 MSs, 5 PCPs, and 5 breast cancer survivors to inform development of the scenario and VSP. We then used Hyperskill, simulation authoring software, to develop a VSP. Initially, GPT-4 was not available. We started development using BPS. Aided by GPT-4, we used a prompt to instruct the VSP regarding the scenario, its emotional state, and expectations for how the learner should converse with it. We iteratively refined the prompt after multiple rounds of testing. As an exploratory feature, we programmed the simulation to display written feedback on the learner’s performance in communicating with the VSP. Results: In-depth interviews helped us create a realistic scenario by establishing when a conversation between a PCP and patient would likely first take place in the breast cancer screening process and the mode of communication. The scenario simulates a telephone call between the learner and patient to discuss the results of an abnormal diagnostic mammogram that requires a biopsy. Interviews informed programming of prompts for the VSP to expect learner communication based on the SPIKES protocol for delivering bad news. The simulation also evaluated the learner’s performance based on the SPIKES protocol. Preliminary testing was promising. The VSP asked sensible questions about their mammography results and responded to learner inquiries using a realistic voice replete with appropriate emotional inflections based on the conversation. Feedback was useful to highlight major SPIKES deviations but less so when clinical judgement was warranted to balance VSP responses with appropriate next steps (e.g., not pressuring the VSP to schedule a biopsy while displaying agitation). Conclusions: GPT-4 streamlined development and provided a better and more natural user experience than what we were able to provide using BPS. As next steps, we will continue to develop the simulation to improve feedback and pilot test the VSP with MSs to evaluate its feasibility.
Background: Acute pancreatitis (AP) is one of the most prevalent gastrointestinal diseases in clinical practice. In addition to essential medication therapy, a nutritional diet also plays a vital part...
Background: Acute pancreatitis (AP) is one of the most prevalent gastrointestinal diseases in clinical practice. In addition to essential medication therapy, a nutritional diet also plays a vital part in the treatment. People are increasingly using online short video platforms to look up health-related information with the widespread use of smartphones. However, the quality and reliability of health content on these platforms remain unknown. Objective: This study aimed to assess the quality and reliability of the information in AP diet–related videos on Chinese short-video-sharing platforms. Methods: A total of 147 videos were included to analyze from three of the most widely used short-video sharing platforms in China, TikTok, BiliBili, and WeChat channels. Each video was assessed by two physicians separately for content (by content score), quality (by Global Quality Score), and reliability (by an adjusted DISCERN tool). Poisson regression and correlation analysis were used to explore the variables that might affect the quality of the video. Results: videos from TikTok had the most likes and comments than videos from TikTok and WeChat channels, and videos from BiliBili were longer in duration and in days since published than other videos (all p<.001). However, there was no significant difference in the GQS, content score and the DISCERN score among videos from TikTok, BiliBili, and WeChat channels (p>.05). The overall quality of the videos was poor. videos from medical professionals had a relatively greater advice value than those from non-medical professionals in the field of content trustworthiness, quality, and comprehensiveness. The subsequent variables were correlated positively: likes and shares (r=0.326, p<.001), likes and comments (r=0.439, p<.001), comments and shares (r=0.337, p<0.001). DISCERN scores and days since published were found to be negatively correlated (r=-0.259, p<.001). Conclusions: The findings showed that these videos’ quality was inadequate and varied greatly based on the kind of source. In general, videos uploaded by medical professionals were proved to be more reliable, comprehensive, and high-quality than non-medical professionals' videos in content quality. these platforms were not a suitable source of information for patient education. But given the rise in popularity of video-sharing platforms, necessary regulations and restrictions should be taken.
Background: Root canal treatment (RCT) being one of the most common interventions provided by general dentists in clinical practice and the preferred treatment method for treating endodontic diseases....
Background: Root canal treatment (RCT) being one of the most common interventions provided by general dentists in clinical practice and the preferred treatment method for treating endodontic diseases.However, China exhibits certain differences from other countries, both in the content and discipline orientation of endodontic education.Past research on endodontic teaching primarily focused on undergraduate and postgraduate students, leading to the limitations of research not addressing specialized students and lacking feedback from clinical practitioners.This study aims to identify issues related to the differences between clinical practices and classroom education, the effectiveness of teaching content, difficulties in practical components, and the bias in educational training. Objective: This study aimed to investigate the subjective appraisals of Chinese dental practitioners concerning the congruence between classroom education and clinical practice of root canal treatment. Methods: A total of 90 questionnaires were distributed via the Internet to dental practitioners in the eastern coastal areas of China using random sampling. The questionnaire segmented the root canal treatment process into 9 distinct phases (including preoperative preparation, intraoperative procedures, postoperative cleaning, and relevant doctor-patient communication), and gauged the respondents' sensitivity to the posed queries by using 7-point Likert scales. Results: A total of 83 valid responses were collated. Notable disparities were perceived by junior practitioners between classroom teachings and clinical requisites in both root canal treatment procedures and doctor-patient communication (p<0.05). In the phase of root canal disinfection and temporary sealing, respondents under the age of 29 perceived there were significant differences between classroom education and clinical requirements (p<0.05). Dental professionals in Shanghai indicated relatively minor discrepancies between academic instruction and clinical demands across multiple procedural steps (p<0.05). The collective assessment of the clinical complexity of root canal treatment exhibited a convergent trend, albeit with an overall difficulty rating surpassing those of individual procedural stages. More than half of the respondents believed that there is a need to improve and increase the proportion of teaching on indications for root canal treatment and doctor-patient communication.Over half of the participants advocated for enhancements and augmentation in the curricular emphasis on endodontic indications and doctor-patient communication skills. Only 3.7% of the respondents had encountered VR/AR applications during their school studies. In addition, in the free comments received, respondents mentioned the importance of lecturers in the instructional process. Conclusions: Prevalent structural variances exist in the preclinical root canal treatment pedagogy within China, attributable to factors such as experiential deficiencies, abbreviated academic durations, and regional developmental disparities. Teaching content related to periodontal disease is relatively minimal, leading to increased difficulty in judging the indications for root canal treatment. This investigation, focusing on the experiential insights of dental practitioners, offers a novel vantage point for the ongoing refinement of dental educational paradigms. Clinical Trial: This study was approved by the Ethics Committee of Shanghai University of Engineering Science (Approval No. EST-2024-027).
Background: In recent years the prevalence of cardiometabolic disease (CMD) in women has drastically risen and the risk increases with age in comparison to men. Evidence demonstrates that stressful li...
Background: In recent years the prevalence of cardiometabolic disease (CMD) in women has drastically risen and the risk increases with age in comparison to men. Evidence demonstrates that stressful life events, including racism and perceived discrimination, contribute substantially to inflammatory diseases, such as CMD. Despite this evidence, few evidence-based interventions are available to assist minorities in coping with the chronic stress related to being a minority. Objective: Our proposed randomized controlled trial (RCT) will test a novel, race-based intervention tailored to AA women, called Resilience, Stress, and Ethnicity (RiSE) Methods: In this randomized controlled trial, we will randomize participants 1:1 to the 8-week, group–based Resilience, Stress, and Ethnicity (RiSE) program (intervention) or a health education program (HEP-attention control group). The primary endpoint will be stress at 6 months post-intervention, and the efficacy of RiSE will be evaluated for improving stress-related symptoms (chronic stress, racism, discrimination, and subjective social status), reducing inflammatory burden, and improving coping strategies in African American (AA) women at risk for CMD. Validated survey measures and biomarkers will be assessed at baseline, mid-intervention, completion of intervention, and 6 months post-intervention, and differences over time by intervention will be evaluated using mixed effects models. Results: Racism is a dangerous, pervasive, and unfortunately, growing problem in the U.S. It is essential to find a way to reduce the impact of racism on psychological and physical health at the individual level. RiSE reduces stress and has the potential to reduce the psychobiological consequences of racism and discrimination. Conclusions: Despite evidence that racism and perceived discrimination heighten the inflammatory response and CMD, few evidence-based interventions are available to help minorities cope with unique stressors associated with being a minority. This study will be one of the first to examine a race-based stress reduction intervention in the AA woman population and has the potential to improve the health of minorities faced with the chronic stress associated with racism and discrimination. Clinical Trial: ClinicalTrials.gov NCT05902741
Background: The National Essential Public Health Service Package was launched in 2009 to tackle poor blood pressure control of Chinese people with hypertension. However, effect of The National Essenti...
Background: The National Essential Public Health Service Package was launched in 2009 to tackle poor blood pressure control of Chinese people with hypertension. However, effect of The National Essential Public Health Service Package on blood pressure control is still unclear. Objective: In a retrospective population-based retrospective longitudinal study, we aimed to evaluate effect of the National Essential Public Health Service Package on blood pressure control. Methods: A total of 516777 patients registered in the National Essential Public Health Service Package were included in this study. The blood pressure control data was assessed based on the Residence Health Record System dataset. We longitudinally evaluated effects of the NEPHSP on blood pressure control by analyzing changes of blood pressures measured via regular follow-ups that were quarterly conducted. Both of level and trend (slope) of the blood pressure outcome changes were analyzed. We conducted stratified analysis to explore blood pressure control effects of the NEPHSP among subgroup participants with specific characteristics. Results: The baseline mean (SD) values of SBP and DBP were 147.12(19.88) mm/Hg and 85.11(11.79) mm/Hg. The control rates of baseline SBP and DBP were 39.79% and 69.21%. SBP mean values quarterly decreased by 5.06 mm Hg (95% CI, -5.11 to -5.00, P<0.001), 6.69 mm Hg (95% CI, -6.74 to -6.63, P<0.001), 10.30 mm Hg (95% CI, -10.34 to -10.23, P<0.001), 6.63 mm Hg (95% CI, -6.68 to -6.57, P<0.001). SBP control rates quarterly increased to 53.12% (0.60, 95% CI, 0.59 to 0.61, P<0.001), 56.61% (0.76, 95% CI, 0.75 to 0.77, P<0.001), 63.40% (1.08, 95% CI, 1.07 to 1.09, P<0.001), 55.09% (0.69, 95% CI, 0.68 to 0.70, P<0.001). DBP mean value quarterly decreased by 1.75 mm Hg (95% CI, -1.79 to -1.72, P<0.001), 2.64 mm Hg (95% CI, -2.68 to -2.61, P<0.001), 4.20 mm Hg (95% CI, -4.23 to -4.16, P<0.001), 2.64 mm Hg (95% CI, -2.68 to -2.61, P<0.001). DBP control rates quarterly increased to 78.11% (0.52, 95% CI, 0.51 to 0.53, P<0.001), 80.32% (0.67, 95% CI, 0.66 to 0.68, P<0.001), 83.17% (0.89, 95% CI, 0.88 to 0.90, P<0.001), 79.47% (0.61, 95% CI, 0.60 to 0.62, P<0.001). Older age group a larger decrease in SBP mean values (0.87, 95% CI, 0.85 to 0. 90, P<0.001) and a larger increase in SBP control rates (0.054, 95% CI, 0.051 to 0.058, P<0.001). The participants with CVD had smaller decrease in SBP mean values (-0.38, 95% CI, -0.41 to -0.35, P<0.001) and smaller increase in SBP control rates (-0.041, 95% CI, -0.045 to -0.037, P<0.001) than the blood pressures outcomes of participants without CVD. Conclusions: The NEPHSP was effective on improving blood pressure control of Chinese people with hypertension. Blood pressure control of the older and participants with CVD need to be intensified.
Background: Amidst a growing need for improved surgical training, the conventional "see one, do one, teach one" model falls short, particularly for complex procedures like pedicle screw placement. Thi...
Background: Amidst a growing need for improved surgical training, the conventional "see one, do one, teach one" model falls short, particularly for complex procedures like pedicle screw placement. This study introduces an Immersive Mixed Reality Training Framework (IMR-STF) designed to bridge this gap by integrating advanced mixed reality technologies with traditional surgical training to provide comprehensive, hands-on experience without the logistical constraints and ethical concerns of traditional methods. Objective: With the increasing constraints in surgical training, this study aimed to propose a novel Immersive Mixed Reality Surgical Training Framework(IMR-STF) to facilitate surgical skill development among medical students and evaluate its efficacy. Under IMR-STF, the authors developed the Immersive Mixed Reality Surgical Self-Training System(IMR-SS) for pedicle screw placement, seeking to overcome the limitations of traditional training by providing an immersive, interactive, and high-fidelity training environment Methods: A conceptual Immersive Mixed Reality Surgical Training Framework (IMR-STF) was proposed, under which a self-training system was prototyped as IMR-SS for pedicle screw placement for validation. The system integrates 3D-printed models, real surgical instruments, and IMR technology to provide an immersive learning experience and high-fidelity haptic feedback. A randomized controlled trial was conducted with 32 undergraduate medical students from two centers. Participants were randomly assigned to either the IMR Group(using IMR-SS) or the Control Group (using a digital textbook). Both groups underwent theoretical and practical training, followed by identical assessments. Results: The IMR Group demonstrated significantly higher completion rates (0.99±0.02 vs. 0.87±0.11, p=0.000) and fewer errors(0.06±0.25 vs. 2.13±1.54, p=0.000) compared to the Control Group. Additionally, the IMR Group showed better performance in screw placement angles(13.88°±6.98° vs. 20.89°±11.59°, p=0.049) and more stable performance with smaller variances. No cortical bone breaches were observed in the IMR Group, while the Control Group had breaches in 4 out of 16 cases during the exercise session (p=0.051). The theoretical assessment showed no significant difference between the groups, indicating equivalent baseline knowledge. The IMR Group reported higher satisfaction and confidence in learning outcomes. Conclusions: The IMR-SS is a feasible and effective method for enhancing surgical education for novice medical students, providing superior hands-on training experiences, and improving practical skills. Future research should focus on long-term learning curve validation, skill transferability, and developing curricula for more surgeries for generalizability validation. Clinical Trial: This study was deemed exempt by the Peking Union Medical College Hospital(K5533-K24C0630) and The First Affiliated Hospital of Xi'an Jiaotong University(XJTU1AF2024LSYY-097).
Background: Isotretinoin, a common treatment for severe cystic nodular acne, provides anti-inflammatory effects and alleviates symptoms. Despite its efficacy, the medication has been linked to many we...
Background: Isotretinoin, a common treatment for severe cystic nodular acne, provides anti-inflammatory effects and alleviates symptoms. Despite its efficacy, the medication has been linked to many well-documented side effects, including arthralgias, xerosis, and birth defects; however, it also introduces new contributions to sexual dysfunction, presenting opportunity for further research and patient education. Objective: To elucidate the prevalence of sexual dysfunction symptoms among patients taking isotretinoin and examine the extent to which these patients received counseling on potential sexual dysfunction from their dermatologist. Methods: Research was conducted through patient completion of a survey study assessing patients’ adverse reactions to isotretinoin and the education provided by their dermatologist. Results: 144 participants completed the survey. Of the female respondents (N=118), 33% experienced vaginal dryness with isotretinoin use, and of the male respondents (N=23), 34.7% experienced erectile dysfunction while using isotretinoin. 6.8% of female participants reported discussing vaginal dryness as a potential side effect with their prescribing dermatologist prior to starting isotretinoin while 4.3% of male respondents reported discussing erectile dysfunction, ejaculatory failure, and delayed ejaculation. Conclusions: This study demonstrates the opportunity for improved awareness and counseling on isotretinoin’s impact on sexual health.
Background: In Nakhon Pathom Province, residents who recovered from COVID-19 over the past 3-4 years have not been monitored for post-COVID-19 symptoms (Long COVID), resulting in a lack of necessary s...
Background: In Nakhon Pathom Province, residents who recovered from COVID-19 over the past 3-4 years have not been monitored for post-COVID-19 symptoms (Long COVID), resulting in a lack of necessary services. Objective: 1)To study the issues, needs, and systems of nursing and continuous care for people living with post-COVID-19 in Nakhon Pathom Province.
2)To design and develop a database system for continuous monitoring and care of individuals with post-COVID-19 in Nakhon Pathom Province.
3)To develop guidelines for the continuous care of patients recovering from post-COVID-19 in the community at Nakhon Pathom Province.
4)To evaluate the effectiveness of the database system for continuous monitoring and care of individuals with post-COVID-19 in Nakhon Pathom Province Methods: Participatory action research. Results: Post-COVID-19 symptoms persist for approximately six months, with common symptoms including persistent cough and easy fatigue. Patients with post-COVID symptoms have reduced access to services, relying on symptomatic treatment at local healthcare facilities and utilizing telehealth nursing systems. They expressed a need for continuous care from professional nurses and village health volunteers. Consequently, healthcare guidelines for post-COVID-19 recovery were developed, consisting of five approaches: 1) self-care through digital information retrieval, 2) care via telehealth nursing systems, 3) physical healthcare services post-recovery, 4) mental health services post-recovery, and 5) continuous care for referral in case of post-recovery incidents. These guidelines were used to design a database system for continuous monitoring and care, which was evaluated as highly effective. Conclusions: This research highlights the critical need for a proactive and comprehensive approach to managing post-COVID-19 care in Nakhon Pathom Province. By developing and implementing a database system for continuous monitoring and care, along with clear guidelines, the study effectively addresses the ongoing needs of individuals recovering from COVID-19. The integration of technology, along with continuous care provided by professional nurses and village health volunteers, is highly effective in improving the quality of care. The findings suggest that adopting these strategies and implementing supportive policies on data management and communication systems focused on home visits will significantly enhance health service management and better prepare the region for future public health challenges.
Background: Coronavirus disease 2019 (COVID-19) was declared a global pandemic by WHO on 11th March 2020. Witnessing the pattern of relapse of cases, varying severity of cases and persistence of sympt...
Background: Coronavirus disease 2019 (COVID-19) was declared a global pandemic by WHO on 11th March 2020. Witnessing the pattern of relapse of cases, varying severity of cases and persistence of symptoms through different waves of pandemic has emerged as the reason for the studies targeting post-covid status of individuals. Objective: The objective of this survey was to assess the long-term effectiveness of homoeopathic medicines when used as an adjunct therapy along with the conventional therapy during covid infection in oxygen-dependent, moderate and severe patients. Methods: The survey was carried out from 1st April 2022 to 29 May 2022 via telephonic conversation among 219 participants who were discharged from AIIMS, Jhajjar, Haryana and St. George Hospital, Mumbai, India and had participated in two different placebo-controlled, randomized trials held at these two hospitals where individualized homoeopathic medicines were given to the experimental groups in addition to the conventional treatment. The post-COVID-19 Functional Status (PCFS) Scale was employed to evaluate the functional status of the surviving survey participants and to compare the status between the add-on Homoeopathy (AoH) group and the add-on placebo (AoP) group. Results: The mean score of PCFS Scale between the groups were compared using the chi-square test, which was presumed to be statistically significant at P<0.05. In total, 93 participants of AoH group showed more functional ability with mean difference of 0.83±1.47 (mean ± SD), as opposed to 1.33±1.63 (mean ± SD) among the AoP group participants (P=.04). Percentage of participants who developed post-COVID diabetes mellitus or hypertension, or shortness of breath on exertion and was found to be 17.20%, 8.60% and 6.45%, respectively in the AoH group, as compared to 17.57%, 9.68% and 10.81%, respectively in the AoP group. No incidence of post covid anxiety, pneumonia and chronic/acute kidney disease was reported in the AoH group while it was 1.35%, 1.35% and 4.05% respectively in the AoP group. The ability to perform daily chores was observed to be in 57% of the participants of AoH group, as against 43% of those in the AoP group. Conclusions: Homoeopathy, when given as an add-on therapy in COVID-19, helps in faster recovery from acute infections such as COVID19, witha higher proportion of participants being able to perform daily chores, along with an improvement in their general weakness, even after the meidicine was discontinued., This proved the long term effectiveness of homoeopathic treatment when used as an adjunct therapy along with the conventional therapy in the oxygen-dependent, moderate or severe patients of COVID-19. Clinical Trial: As it was a survey, the trial registration was not mandatory.
Displaced populations face complex dermatologic challenges. Contributing factors include low immunization rates, poor sanitation, crowded living conditions, and physical abuse. Chronic inflammatory co...
Displaced populations face complex dermatologic challenges. Contributing factors include low immunization rates, poor sanitation, crowded living conditions, and physical abuse. Chronic inflammatory conditions and infectious diseases, including fungal infections and scabies, are prevalent. Research is crucial to reduce the spread of disease and improve care in these populations; the paucity of dermatologist support in this field exacerbates the issue. Ethical considerations include non-maleficence and culturally sensitive practices, and proposed solutions include trauma-informed care training, advocacy for equitable research funding, teledermatology, and the development of shared international screening guidelines. Further research is essential to enhance dermatologic care for displaced populations.
Introduction: Diabetic Nephropathy (DN), severe complications of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal...
Introduction: Diabetic Nephropathy (DN), severe complications of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal disease (ESRD). DN's pathogenesis involves high glucose levels, oxidative stress, inflammation, and fibrosis, resulting in kidney changes such as glomerular basement membrane thickening and glomerulosclerosis. The International Diabetes Federation projects that by 2045, 783 million people will have diabetes, with 30%-40% of them developing DN. Early detection and intervention are crucial for preserving renal function, improving quality of life, eliminating cardiovascular complications, and reducing healthcare costs.
Methods: This study utilized machine learning (ML) techniques to develop and validate a predictive model for DN, focusing on both high predictive accuracy and model interpretability. Data from 1,000 Type-2 diabetes patients, including 444 with DN and 556 without, were analyzed. Various ML algorithms, including decision trees, random forests, Extra Trees, AdaBoost, XGBoost, and LightGBM, were employed. Multiple imputation was used for handling missing data, and the Synthetic Minority Over-sampling Technique (SMOTE) addressed data imbalance. Model performance was evaluated with metrics such as accuracy, precision, recall, F1 score, specificity, and area under the curve (AUC). Explainable Machine Learning (XML) techniques like LIME and SHAP were used to enhance model transparency and interpretability.
Results: XGBoost and LightGBM demonstrated superior performance, with XGBoost achieving the highest accuracy of 86.87%, a precision of 88.90%, a recall of 84.40%, an F1 score of 86.44%, and a specificity of 89.12%. LIME and SHAP analyses provided insights into the contribution of individual features to the prediction outcomes, identifying serum creatinine, C-peptide, albumin, and lipoproteins as significant predictors.
Conclusion: The developed ML model not only provides a robust predictive tool for early diagnosis and risk assessment of DN but also ensures transparency and interpretability, crucial for clinical integration. By enabling early intervention and personalized treatment strategies, this model has the potential to improve patient outcomes and optimize healthcare resource utilization.
Background: Implementation frameworks like the EPIS model emphasize the importance of the “fit” between an intervention and its context, which includes the needs of its target population, as well...
Background: Implementation frameworks like the EPIS model emphasize the importance of the “fit” between an intervention and its context, which includes the needs of its target population, as well as the culture, resources, and capabilities of the implementing organization. Even though lack of fit is a major barrier to implementation, fit has not often been a focus of implementation research. Objective: This paper uses fit as a lens to examine the implementation of Tula, an mHealth app aimed at reducing risky drinking days among individuals meeting the criteria for mild to moderate alcohol use disorder, in a 3-arm (app alone; app plus peer mentoring; app plus health coaching) RCT. Methods: Semi-structured interviews with 18 trial participants and 7 Tula implementers were conducted. Trial participants were pulled equally from each arm of the trial, and represented participants who demonstrated both high and low engagement with the application. Implementers consisted of a project manager, 4 peer mentors, and 2 health coaches. Interviews with participants focused on their motivations, opinions, and experiences of the intervention and their perception of their drinking behavior following the intervention, including how their use of the app worked to change that behavior. Interviews with implementers were centered on their roles, theories of change, perceptions of intervention, and areas for improvement. All interviews were analyzed using rapid qualitative analysis with both deductive and inductive components. Results: We identified areas of both fit and misfit. For example, there was a good fit between implementers’ theories of change and participants’ description of how change occurred. Fit was improved by the versatility of the app, which allowed participants to customize their experiences. Conversely, misfit was noted in the app’s inability to cultivate connection for many participants and a disjunction between the role of peer mentors in the intervention and their broader professional ethos. Conclusions: Focusing on fit provides a useful guide to enhance future iterations of the Tula app that lead to better sustainment of the intervention. Clinical Trial: NCT04011644 (ClinicalTrials.gov). Registered 08 July 2019. Available at: https://clinicaltrials.gov/study/NCT04011644
Background: The increasing number of older adults who are living alone poses challenges for maintaining their well-being, as they often need support with daily tasks, healthcare services, and social c...
Background: The increasing number of older adults who are living alone poses challenges for maintaining their well-being, as they often need support with daily tasks, healthcare services, and social connections. However, advancements in artificial intelligence (AI) technologies have revolutionized healthcare and caregiving via their capacity to monitor health, provide medication and appointment reminders, and companionship to older adults. Nevertheless, the adaptability of these technologies for older adults are stymied by useability issues. This study explores how older adults use and adapt to AI technologies, highlighting both the persistent barriers and opportunities for potential enhancements. Objective: The study purpose was to provide deeper insights into older adults' engagement with technology and AI. The technologies currently used, potential technologies desired for daily life integration, personal technology concerns faced, and overall attitudes towards technology and AI are explored. Methods: Using mixed-methods, participants (N = 28) completed both a semi-structured interview and surveys consisting of health and well-being measures. Participants then participated in a research team facilitated interaction with an AI chatbot, Amazon Alexa. Interview transcripts were analyzed using thematic analysis, and surveys were evaluated using descriptive statistics. Results: Participants ranged in age from 65 to 84 years. Digital devices were most commonly used for entertainment, health management, professional productivity, and social connectivity. Participants were most interested in integrating technology in their personal life for scheduling reminders, chore assistance, and for providing care to others. Challenges in using new technology included commitment to learning, a lack of privacy, and a worry about future technology dependence. Overall, their attitudes coalesced towards early adapters, those wary, and those who were resisters of technology and AI. Conclusions: To ensure that AI technologies effectively support older adults, it's essential to foster ongoing dialogue among developers, older adults, families, and their caregivers, focusing on inclusive designs to meet older adults’ needs.
Background: The integration of artificial intelligence (AI) into medicine has ushered an era of unprecedented innovation, with substantial impacts on healthcare delivery and patient outcomes. Objectiv...
Background: The integration of artificial intelligence (AI) into medicine has ushered an era of unprecedented innovation, with substantial impacts on healthcare delivery and patient outcomes. Objective: it is essential to comprehend the current state of development, primary research focal points, and to identify key contributors and their relationships in the application of AI in medicine through bibliometric analysis. Methods: We employed the Web of Science Core Collection as our primary database and conducted a literature search spanning from January 2019 to December 2023.VOSviewer and R-bibliometrix were performed to conduct bibliometric analysis and network visualization, including the number of publications, countries, journals, citations, authors and keywords. Results: A total of 1811 publications on research for artificial intelligence in medicine were released across 565 journals by 12376 authors affiliated with 3583 institutions from 97 countries. The United States emerged as the leading producer of scholarly works, exerting significant influence in this domain. Harvard Medical School exhibited the highest publication count among all institutions. The JOURNAL OF MEDICAL INTERNET RESEARCH attained the highest H-index (H-index=19), the most significant publication count (NP=76), and total citations (NC=1495). Among the keywords, four clusters were identified, encompassing the application of AI in digital health, COVID-19 and ChatGPT, precision medicine, epidemiology, and public health. "Outcomes" and "Risk" demonstrated a notable upward trend, indicating the utilization of AI in engaging with clinicians and patients to discuss patients' health condition risks, foreshadowing future research focal points. Conclusions: Our bibliometric analysis delved into the advancements, focal points, and cutting-edge areas within the field of artificial intelligence in medicine, revealing potential future research opportunities. Research on artificial intelligence in medicine is rapidly progressing, as evidenced by a consistent increase in publications on the topic since 2019. Simultaneously, we identified leading countries, institutions, and scholars in the field and conducted an analysis of journals and representative literature. This study equips researchers with the necessary information to comprehend the current state, collaborative networks, and primary research focal points within the field. Furthermore, our findings propose a set of recommendations for future research.
Background: Health and social care models worldwide are facing perpetual crisis where the informal (family) caring role is becoming increasingly pivotal. Despite unparalleled societal and economic val...
Background: Health and social care models worldwide are facing perpetual crisis where the informal (family) caring role is becoming increasingly pivotal. Despite unparalleled societal and economic value, many informal carers face poor mental and physical health with limited opportunities for physical activity. There remains an urgent need to understand and support informal carers to stay well, including evidence based physical activity approaches. Objective: To codesign, adapt and explore the feasibility of a novel cross-platform approach to support physical activity in carers of people with dementia. Methods: This was a mixed-methods codesign, development and evaluation study of a smartphone app (CareFit) to support physical activity for unpaid dementia carers. We explored implementation of CareFit for carers, guided by both ‘RE-AIM’ and MRC Complex Intervention Frameworks in two stages: (i) codesign; (ii) feasibility study findings (i.e. recruitment, intervention and outcome selection). The codesign sessions for adaptation and expansion involved 3 development sprints gaining feedback and identifying priority areas from a range of stakeholders (e.g. carers, support professionals, charities, researchers and developers). This was followed by an 8-week feasibility study with participants recruited from local and national networks alongside Join Dementia Research (JDR) using a closed-testing release app on Google and Apple app stores. Results: We successfully codesigned, developed and user tested the CareFit app. Codesign resulted in an expanded and adapted CareFit suitable for 8-weeks of use. Final app design included a simplified navigation system, increased video content alongside more personalised delivery of content. Feasibility study results highlighted the challenges of recruiting carers of people with dementia. In total 41 carers of people with dementia were recruited with 21 completing the 8-week study. Study retention was considerably lower for those carers undertaking high levels of physical activity at baseline opposed to those who were not (36% retention vs 58% respectively) providing useful information on the target group of future interventions. CareFit rated well on the System Usability Scale and we observed common user patterns of behaviour (e.g. an initial focus on ‘learn’ section). Most outcome measures were largely suitable for future use in this group- this included novel measures introduced by the research team around the number of sedentary breakers and muscle and balance activities. Conclusions: Physical activity in carers of people with dementia remains a largely unmet need. We conclude that our approach fits largely within the context of preventative medicine where presentation to carers at the ‘right’ time in their trajectory (i.e. early) is critical for adoption and long-term use. A major challenge remains around recruitment. Despite value recognised by stakeholders including carers, we cannot currently recommend progression to randomised control trial. Of future interest would be to build upon this work further to accumulate evidence on optimising the active ingredients of the intervention.
Background: Social isolation at the onset of the 2020 Covid-19 pandemic conditioned increased use of online formats in counseling. The demands counselors face in online counseling focus primarily on c...
Background: Social isolation at the onset of the 2020 Covid-19 pandemic conditioned increased use of online formats in counseling. The demands counselors face in online counseling focus primarily on changes concerning the organization of work and the establishment of therapeutic relationships. These include the decrease of access to facial expressions and gestures and potential problems with special technical features. Objective: The aim of the study is to identify risk factors for an increased stress experience in online counseling and to develop and validate an instrument that allows to assess stressors. Methods: The stressors arising from online counseling were surveyed by means of a self-developed questionnaire. The questionnaire was examined by means of an explorative factor analysis. Linear regression was used to analyze how the variables can predict distress. Results: The sample consisted of 174 social counselors and psychotherapists from various social counseling fields. The results indicated that the QueStrOn had acceptable validity and internal consistency (Cronbach's alpha exceeded 0.87 for the overall scale). Explorative factor analysis identified four underlying factors: 'online work organization’, ‘online framework’, ‘online communication’ and 'online work content'. Further the regression model showed that the identified factors are predictors of stress level. Conclusions: The results suggest that the QueStrOn instrument is a practical tool for assessing stressors in the profes-sional use of online counseling.
Background: Many mobile health (mHealth) apps focus on promoting physical activity (PA) and healthy eating (HE). However, there is limited empirical evidence regarding their effectiveness in initiatin...
Background: Many mobile health (mHealth) apps focus on promoting physical activity (PA) and healthy eating (HE). However, there is limited empirical evidence regarding their effectiveness in initiating and sustaining behavior change, particularly among children and adolescents. Considering that behavior is influenced by social contexts, it is essential to take core settings like family dynamics into account when designing mHealth apps. Objective: The purpose of this study was to further develop and refine the SMARTFAMILY app targeting PA and HE in a collective family-based setting by enhancing design and usability, as well as by adding gamification aspects, health literacy, and just-in-time adaptive interventions (JITAI) to the first version of the app. Methods: The SMARTFAMILY2.0 app, based on behavior change theories and techniques, was developed, implemented, and evaluated. The app was used in a collective family setting, with family members using it individually and cooperatively. In a cluster-randomized controlled trial, the intervention group (IG) used the app for three consecutive weeks, while the control group (CG) received no treatment. Primary outcomes included physical activity (PA) measured through self-reports and accelerometry, as well as self-reported fruit and vegetable intake (FVI) for health eating (HE). Secondary outcomes included intrinsic motivation, behavior-specific self-efficacy, and the Family Health Climate (FHC). A follow-up assessment (T2) was conducted four weeks after the post-measurement (T1) to assess intervention effects. Multilevel analyses were performed in R, considering the hierarchical structure of individuals (level 1) within families (level 2). Results: Overall, 55 families (28 CG, n = 105; 27 IG, n = 104 participants) were recruited for the study. Three families (3 KG, n = 12) chose to drop out of the study due to personal reasons before T0. Overall, no evidence for meaningful and statistically significant increases in PA was observed in favour of the IG our physically active sample. However, the app elucidated positive effects in favor of the intervention group for FVI diary (T0-T1; p = .031), joint PA (T0-T1 and T0-T2; p <.026), and joint family meals (T0-T1; p =.004). Conclusions: The SMARTFAMILY2.0 trial evaluated a mHealth intervention designed to promote PA and HE within families. Despite incorporating a theoretical foundation, several behavior change techniques based on family life and gamification and JITAI features, the intervention did not significantly increase PA levels among physically active participants. FVI intake, joint PA, and joint meals were improved within the intervention group. Previous studies on digital health interventions have produced mixed results, and family-based mHealth interventions remain rare, with limited focus on whole-family behavior and randomized controlled trials. To enhance intervention effectiveness, future app development could consider incorporating even more advanced features and should focus on inactive participants. Further research is needed to better understand intervention engagement and tailor mHealth approaches for primary prevention efforts. Clinical Trial: The study is registered with the German Clinical Trials Register under the registration number DRKS00010415.
Background: Obesity remains a critical global public health issue, contributing to severe health conditions such as type 2 diabetes and cardiovascular diseases. In Maidstone, United Kingdom the obesit...
Background: Obesity remains a critical global public health issue, contributing to severe health conditions such as type 2 diabetes and cardiovascular diseases. In Maidstone, United Kingdom the obesity rate stands at 16.3% higher than the national average of 15.8%. Objective: This study evaluates the demographics and outcomes of a face-to-face weight management program implemented in Maidstone, a region with varying levels of deprivation, who self-referred to a Tier 2 Weight Management program. Methods: This study employed a single-arm intervention design, where adults who were overweight or obese self-referred to an in-person weight management service. The service focuses on accessible behavior change self-management through weekly evidence-based structured education, guided behavioral change activities, and community support. Participant characteristics and health data were collected at baseline, 12 and 26-weeks. Results: A total of 50 participants self-referred and completed the initial registration process, all of whom (100%) were deemed eligible for the program. The first 40 participants (80%) enrolled in the face-to-face weight management service, and of these, 15 (38%) also downloaded an app for additional support. The average age of participants was 42.4 years, with mean BMI of 35.7 kg/m², predominantly female (68%) and 73% identified as white.
At the 26-week follow-up, 75% of participants reported outcomes, with an average weight loss of 3.46% ± 4.2% (from 98.3 ± 23.0 kg at Week 0 to 94.9 ± 21.7 kg at Week 26) and an average BMI reduction of 3.34% ± 3.9 kg/m² (from 35.7 ± 8.7 kg/m² at Week 0 to 34.5 ± 8.3 kg/m² at Week 26). Participants expressed high levels of engagement and acceptance of the service, and those who utilized the digital app experienced greater weight loss. Conclusions: The face-to-face service was well-received and facilitated significant weight loss. Integration of digital technology contributed to greater weight reduction among participants.
Background: Real-world data (RWD) from sources like administrative claims, electronic health records, and cancer registries offer insights into patient populations beyond the tightly regulated environ...
Background: Real-world data (RWD) from sources like administrative claims, electronic health records, and cancer registries offer insights into patient populations beyond the tightly regulated environment of randomized controlled trials. To leverage this and to advance cancer research, six university hospitals in Bavaria have established a joint research IT infrastructure. Objective: This article aims to outline the design, implementation, and deployment of a modular data transformation pipeline that transforms oncological RWD into HL7 (Health Level 7) FHIR (Fast Healthcare Interoperability Resources) format and then into a tabular format in preparation for a federated analysis (FA) across the six BZKF university hospitals. Methods: To harness RWD effectively, we designed a pipeline to convert the oncological basic dataset (oBDS) into HL7 FHIR format and prepare it for federated analysis. The pipeline handles diverse IT infrastructures and systems while maintaining privacy by keeping data decentralized for analysis. To assess the functionality and validity of our implementation, we defined a cohort to address two specific medical research questions. We evaluated our findings by comparing the results of the FA with reports from the Bavarian Cancer Registry and the original data from local tumor documentation systems. Results: We conducted a federated analysis of 17,885 cancer cases from 2021/2022. Breast cancer was the most common diagnosis at three sites, prostate cancer ranked in the top two at four sites, and malignant melanoma was notably prevalent. Gender-specific trends showed larynx and esophagus cancers were more common in males, while breast and thyroid cancers were more frequent in females. Discrepancies between the Bavarian Cancer Registry and our data, such as higher rates of malignant melanoma (5 % vs. 11 %) and lower representation of colorectal cancers (13 % vs. 7 %) likely result from differences in the time periods analyzed (2019 vs. 2021/2022) and the scope of data sources used. The Bavarian Cancer Registry reports approximately three times more cancer cases than the six university hospitals alone. Conclusions: The modular pipeline successfully transformed oncological RWD across six hospitals, and the federated approach preserved privacy while enabling comprehensive analysis. Future work will add support for recent oBDS versions, automate data quality checks, and integrate additional clinical data. Our findings highlight the potential of federated health data networks and lay the groundwork for future research that can leverage high-quality RWD, aiming to contribute valuable knowledge to the field of cancer research.
Background: The rapid shift to video consultation services during the COVID-19 pandemic has raised concerns about exacerbating existing health inequities, particularly for disadvantaged populations. I...
Background: The rapid shift to video consultation services during the COVID-19 pandemic has raised concerns about exacerbating existing health inequities, particularly for disadvantaged populations. Intersectionality theory provides a valuable framework for understanding how multiple dimensions of disadvantage interact to shape health experiences and outcomes. Objective: To explore how multiple dimensions of disadvantage - specifically older age, limited English proficiency, and low socioeconomic status - intersect to shape experiences with digital health services, focusing on video consultations. Methods: Guided by intersectionality theory and digital capital concepts, semi-structured narrative interviews were conducted with 17 participants aged 65 or older from diverse ethnic backgrounds in the Redbridge borough of London. Interviews explored participants' experiences accessing healthcare virtually. Intersectional narrative analysis was used to identify key themes and examine how different forms of disadvantage interact. Theoretically-informed narrative portraits and user personas were developed to synthesize findings. Results: Analysis revealed that digitalisation of healthcare can exacerbate existing inequities, erode trust, compound oppression, and reduce patient agency for multiply-disadvantaged patient populations. Examining intersectionality illuminated how age, language proficiency, and socioeconomic status interact to create unique barriers and experiences. Key themes included: weakened presence in digital interactions, erosion of therapeutic relationships, shift from relational to distributed continuity, increased complexity leading to disorientation, engagement shaped by prior experiences of discrimination, and reduced patient agency. Conclusions: This study provides critical insights into how the digitalisation of healthcare can deepen disparities for older, low-income, limited English speaking patients. By applying intersectionality theory to digital health disparities, our findings underscore the urgent need for multifaceted approaches to digital health equity that address the complex interplay of disadvantage. Recommendations include co-designing inclusive digital services, strengthening relational continuity, and developing targeted support to preserve agency and trust for marginalized groups in an increasingly digital healthcare landscape.
Background: Over the past two decades, the gut microbiota has emerged as a key player in human health, being involved in many different clinical contexts. Yet, many aspects of the relationship with it...
Background: Over the past two decades, the gut microbiota has emerged as a key player in human health, being involved in many different clinical contexts. Yet, many aspects of the relationship with its host are poorly documented. One obstacle is the substantial variability in wet-lab procedures and data processing implemented during gut microbiota studies, which poses a challenge of comparability and potential meta-analysis. Objective: In order to better understand the relationship between health, dietary habits, and the observed heterogeneity of gut microbiota composition in the general population, « Le French Gut – Le microbiote français » aims to collect, sequence, and analyze 100,000 fecal samples from French residents using a high-quality shotgun metagenomic pipeline, complemented with comprehensive health, lifestyle, and dietary metadata. Methods: “Le French Gut – Le microbiote français” is a prospective, non-interventional French national study involving individuals , the creation of a biological collection (feces) and the exploitation of data from questionnaires and the National Health Data System (SNDS, Système National des Données de Santé). This national study is open to all metropolitan French adult residents, excluding those who have undergone a colectomy or digestive stoma, or who have had a colonoscopy or taken antibiotics in the last 3 months. This is a home-based trial in which volunteers complete a questionnaire with insights about their health, lifestyle, and dietary habits, and in which stool samples are self-collected. Results: Recruitment has started in September 2022 and is still on going. As of July 2024, we enrolled 14160 participants. Conclusions: “Le French Gut” will provide a reference database and new ecosystem tools for understanding the relationship between the gut microbiota, its host and diet. It aims to find new signatures or targets and promote the design of innovative preventive strategies, personalized nutrition, and precision medicine. Clinical Trial: ClinicalTrials.gov NCT05758961. Registered on 8 March 2023. The trial was prospectively registered.
Background: Multiple Correspondence Analysis (MCA) is an unsupervised data science methodology that aims to identify and represent associations between categorical variables. Gliomas are an aggressive...
Background: Multiple Correspondence Analysis (MCA) is an unsupervised data science methodology that aims to identify and represent associations between categorical variables. Gliomas are an aggressive type of cancer characterized by diverse molecular and clinical features that serve as key prognostic factors. Thus, advanced computational approaches are essential to enhance analysis and interpretation of the associations between clinical and molecular features in gliomas. Objective: This study aims to apply MCA to identify associations between glioma prognostic factors and also explore their associations with stemness phenotype. Methods: Clinical and molecular data from 448 brain tumor patients were obtained from The Cancer Genome Atlas (TCGA). The mDNA stemness index, derived from DNA methylation patterns, was built using a one-class logistic regression (OCLR). Associations between variables were evaluated using the chi-square test with k degrees of freedom, followed by analysis of the adjusted standardized residuals. MCA was employed to uncover associations between glioma prognostic factors and stemness. Results: Our analysis revealed significant associations among molecular and clinical characteristics in gliomas. Additionally, we demonstrated the capability of MCA to identify associations between stemness and these prognostic factors. Our results exhibited a strong association between higher mDNA stemness index and features related to poorer prognosis, demonstrating the utility of MCA as an analytical tool for elucidating potential prognostic factors. Conclusions: MCA proves to be a valuable tool for understanding the complex interdependence of prognostic markers in gliomas. MCA facilitates the exploration of large-scale datasets and enhances the identification of significant associations.
Background: Insulin therapy is crucial for diabetes management, and its effectiveness is well-established. With better access to health services, adherence to guidelines, and the availability of insul...
Background: Insulin therapy is crucial for diabetes management, and its effectiveness is well-established. With better access to health services, adherence to guidelines, and the availability of insulin, its usage in Indonesia may rise. However, prescribing insulin poses challenges such as storage issues, patient preparation, and proper injection techniques, all of which can impact insulin's effectiveness.
Patient education is vital for successful diabetes management, especially for those on insulin. Indonesia has guidelines for insulin injection techniques, adapted from the Forum for Injection Technique and Therapy Experts (FITTER), but proper insulin use remains insufficient. A preliminary study at a Jakarta hospital revealed that only 6.1% of diabetes patients received education during outpatient treatment. Objective: This study seeks to investigate physicians' knowledge and practice in providing education on insulin use to diabetes patients in Indonesia, as no previous research has addressed this issue. Methods: This study recruited potential participants (all physicians in Indonesia) through the internet using convenience sampling method. Participants gave their informed consent before completing the questionnaire. The online questionnaire was created by the research team and pretested on 30 individuals before distributed to participants. The survey lasted from February to March 2021. Results: A total of 823 participants were included in the analysis. More than 80% of the participants had given insulin education to patients at least once during the last 30 days. However, only 58.20% used specific guidelines in their practice, with only 34.02% aware of the Indonesian guideline. Almost all (99.03%) participants agreed that insulin injection techniques would affect clinical results. The median score of knowledge about insulin injection techniques were 7 (IQR 2) among the study participants. Conclusions: Most physicians in this study had given education to their patients. However, there was still a gap between the guideline and practice of insulin education, as shown by the lack of awareness and the fair level of knowledge about the Indonesian guideline.
Background: Numerous barriers to moderate and vigorous physical activity (MVPA) exist for youth with type 1 diabetes (T1D). The virtual exercise games for youth with T1D (ExerT1D) intervention impleme...
Background: Numerous barriers to moderate and vigorous physical activity (MVPA) exist for youth with type 1 diabetes (T1D). The virtual exercise games for youth with T1D (ExerT1D) intervention implements synchronous support of MVPA including T1D peers and role models. Objective: To understand the acceptability of this intervention to participants. Methods: We conducted post-program, semi-structured, televideo interviews with participating youth to elicit perspectives on acceptability of the intervention and experience with the program. Two coders independently reviewed and analyzed each transcript using a coding scheme developed inductively by senior researchers. Discrepancies were resolved by team discussion, and multiple codes were grouped together to produce four main thematic areas. Results: All 15 participants provided interviews [14-19 years old; 2 non-binary, 6 females; 7.8% median HbA1c, 5 with HbA1c≥10.0%]. Qualitative data revealed four themes. (1) Motivation to engage in PA: Improving their physical capabilities and/or stabilizing glucose levels were cited as motivation for PA. Challenges of living with T1D were cited as PA barriers. (2) Experience with and motivation to manage diabetes while engaging in PA: Participants provided details of accommodating the inherent uncertainty or limitations of PA with diabetes. Sometimes preparing for PA involved psychological and motivational adjustments. Some relayed feelings of avoidance. (3) Peer support encouraged engagement with the intervention: Participants appreciated the peer aspects of components of ExerT1D. Participants’ reflections of the facilitated group experience highlight many benefits of a small-group virtual program. (4) Improvements in PA and diabetes self-management efficacy: All participants credited the program with improving and/or raising awareness of T1D management skills. Conclusions: Our virtual PA intervention using an active video game and discussion component provided adolescents with T1D the confidence and peer support to engage in PA, improve awareness of diabetes-specific tasks to prepare for exercise, and improved understanding of the effect of PA on glucose levels. Engaging youth with a virtual videogame intervention is a viable approach to overcome barriers to PA for adolescents with T1D. Clinical Trial: Interviewed participants of clinical trial NCT05163912
Background: Emotional support plays a crucial role in enhancing social interactions, facilitating psychological interventions, and improving customer service outcomes by addressing individuals' emotio...
Background: Emotional support plays a crucial role in enhancing social interactions, facilitating psychological interventions, and improving customer service outcomes by addressing individuals' emotional needs. The emergence of large language models (LLMs) holds promise for delivering emotional support on a large scale, but their effectiveness compared to human counselors is still not well understood. Evaluating and enhancing the emotional support capabilities of LLMs through targeted user-centered strategies is crucial for their successful real-world integration. Objective: This study aims to evaluate the emotional support capabilities of large language models (LLMs), specifically GPT-4o, and to introduce an integrative automatic evaluation framework centered on user-perceived feedback. The framework is designed to enhance LLM performance in emotional support conversations (ESCs) by identifying psycholinguistic clues as intrinsic evaluation metrics and leveraging a customized Chain-of-Thought (CoT) prompting framework. Methods: The study used a dataset of emotional support conversations from human counselors. An explanatory predictive model was developed using explainable artificial intelligence methods, following an integrative modeling paradigm rooted in computational social science. The model evaluated and interpreted user-perceived feedback scores for GPT-4o. Additionally, the study integrated Hill’s three-stage model of helping into a manually customized chain of thought prompting framework to systematically evaluate GPT-4o's performance in ESCs. Results: GPT-4o achieved high user-perceived feedback scores, demonstrating relative stability in its performance, but it still significantly trails behind human counselors overall (Cliff's Delta = 0.087, p < 0.001). The evaluation framework, which identified 41 distinct linguistic clues related to emotional expression, social dynamics, cognitive processes, linguistic style, and decision-making stages, enhanced the understanding of both processes and outcomes in ESCs. Notably, GPT-4o's user-perceived feedback scores significantly improved with the use of manually customized Chain of Thought prompts (p < 0.001, Cohen's d: 0.378), but showing no significant difference from the average performance of human counselors overall (p-adj: 0.47, Cliff's Delta: -0.014). However, thought prompts demonstrate a significant advantage in specific emotion categories such as fear (p: 0.002, Cliff's Delta: -0.23), sadness (p: 0.012, Cliff's Delta: -0.105), and break up with partner issues (p: 0.254, Cliff's Delta: -0.06). However, GPT-4o exhibited weaknesses in emotional understanding, cognitive complexity, language fluency, and handling extreme scenarios. Conclusions: This study provides preliminary evidence of GPT-4o's emotional support capabilities and proposes a user-perceived feedback-centered integrative evaluation framework for ESCs. The findings suggest a cautiously optimistic outlook for the application of advanced large language models (LLMs) in emotional support services, although significant challenges remain, particularly in enhancing the depth of exploration in conversations and the personalization of language. The proposed framework encourages the integration of human expertise into LLMs, enhancing their efficacy and advancing the development of trustworthy AI-based emotional support services.
Background: The Automated Heart-Health Assessment (AH-HA) tool is a novel electronic health record clinical decision support tool based on the American Heart Association’s Life’s Simple 7 cardiova...
Background: The Automated Heart-Health Assessment (AH-HA) tool is a novel electronic health record clinical decision support tool based on the American Heart Association’s Life’s Simple 7 cardiovascular health (CVH) metrics to promote CVH assessment and discussion in outpatient oncology. Before proceeding to future implementation trials, it is critical to establish the acceptability of the tool among providers and survivors. Objective: We assessed provider and survivor acceptability of the AH-HA tool and provider training at practices randomized to the AH-HA tool arm within WF-1804CD. Methods: Providers (physicians, nurse practitioners, physician assistants) completed a survey to assess acceptability of the AH-HA training, immediately following training. Providers also completed surveys to assess AH-HA tool acceptability and potential sustainability. Tool acceptability was assessed after 30 patients were enrolled at the practice with both a survey developed for the study as well as with domains from the Unified Theory of Acceptance and Use of Technology (UTAUT) survey (Performance Expectancy, Effort Expectancy, Attitude Toward using Technology, and Facilitating Conditions). Semi-structured interviews at the end of the study captured additional provider perceptions of the AH-HA tool. Post-treatment survivors (breast, prostate, colorectal, endometrial, and lymphomas) completed a survey to assess acceptability of the AH-HA tool immediately after the designated study appointment. Results: Providers (n=15) reported high overall acceptability of the AH-HA training (mean=5.8, SD=1.0) and tool (mean=5.5, SD =1.4); provider acceptability was also supported by UTAUT scores (e.g., Effort Expectancy mean=5.6, SD=1.5). Qualitative data also supported provider acceptability of different aspects of the AH-HA tool (e.g., It helps focus the conversation and give the patient a visual of continuum of progress). Providers were more favorable about using the AH-HA tool for post-treatment survivorship care. Enrolled survivors (n=245) were an average of 4.4 years post-treatment (SD =3.7). Most survivors reported that they strongly agreed/agreed that they liked the AH-HA tool (94.3%, n=231). A larger proportion of survivors with high health literacy strongly agreed/agreed that it was helpful to see their heart health score (98.2%, n=161) compared to survivors with lower health literacy scores (89.5%, n=68; p=0.005). Conclusions: Quantitative surveys and qualitative interview data both demonstrate high acceptability of the AH-HA tool among both providers and survivors. Although most survivors found it helpful to see their heart health score, there may be room for improving communication with survivors who have lower health literacy. Clinical Trial: Assessing Effectiveness and Implementation of an EHR Tool to Assess Heart Health Among Survivors (AH-HA)
NCT03935282
https://clinicaltrials.gov/study/NCT03935282?term=NCT03935282&rank=1
Background: Prevalence of obesity and overweight has steadily increased over the past decade, urging the development, and refinement of methods of intervention to combat the epidemic. Various formulat...
Background: Prevalence of obesity and overweight has steadily increased over the past decade, urging the development, and refinement of methods of intervention to combat the epidemic. Various formulations have been marketed to help tackle obesity via decreasing appetite and stimulating metabolism. Objective: In this study, we aim to explore the effect of Slimbiome® - a formulation containing glucomannan, chromium picolinate and fructo-oligosaccharides, on post-prandial blood glucose modulation, and hunger and satiation in healthy adults. Methods: This was a single-group, prospective, open-label pilot study, included 17 adults (Mean ± SD: age 26.35 ± 5.18 years; height 171 ± 11.22 cm; body weight 73.24 ± 13.23 kg; BMI 24.89 ± 2.72 kg/m2). Blood glucose concentration and subjective perceptions of satiety was measured in participants after ingesting a test solution containing a combination of dextrose, agglomerated glucomannan, fructo-oligosaccharides and chromium picolinate, over a 150-minute period. Results: Consumption of both control and test solutions resulted in a significant difference in post prandial blood glucose concentration, by an average of 172% and 168% from baseline to peak in control and test solutions respectively. There was statistically significant difference between baseline and peak glucose concentration, but not between baseline and post-trial when observing the control solution (P = .001 and .072 respectively). A similar result was also produced for the test solution, however, the difference between peak concentration and post-trial was even less statistically significant (baseline – peak, P = .001; baseline – post-trial, P = .460).
No statistically significant differences were observed in the response scores for the level of hunger felt and feeling of fullness at 75 minutes post consumption of the test solution, however there was a significant difference between these response scores at 150 minutes after consumption (P = .001)
A strong positive correlation between desire to eat and feelings of hunger increased further at 150 minutes after test solution consumption, which was statistically significant (r = .895**, P = <.001). The desire to eat and the amount of food believed could be eaten were moderately, negatively correlated, with statistical significance (r = .752**, P = <0.001). There were no significant associations between levels of thirst and any other variable. Conclusions: The data revealed that though Slimbiome® resulted in a peak glucose concentration that was comparatively, on average, lower than the control solution, the positive effect was not statistically significant. The more substantial impacts of the test drug appeared to be related to aspects of hunger, satiety, and cravings. It was observed that the test group on average had lower response scores for how hungry they felt, and how strong their desire to eat was, at both mid-trial and post-trial time points. Not only does Slimbiome® show positive effect on reducing levels of hunger, but it may potentially play a role in delaying the onset of hunger.
Introduction: Cardiovascular disease (CVD) is the leading cause of death among females in America. Hypertensive disorders of pregnancy (HDP) negatively impact acute and long-term cardiovascular health...
Introduction: Cardiovascular disease (CVD) is the leading cause of death among females in America. Hypertensive disorders of pregnancy (HDP) negatively impact acute and long-term cardiovascular health, with approximately 16% of all pregnancies affected. With CVD 2-4 times more likely after HDP compared to normotensive pregnancies, effective interventions to promote cardiovascular health are imperative. Given that physical activity (PA) is associated with decreased CVD risk, promotion of this behavior may be a promising approach in a postpartum population affected by HDP.
Methods: A remotely delivered 14-week health coaching intervention was designed, based on formative work, to promote PA during the postpartum period. Feasibility, acceptability, and preliminary efficacy to increase PA was tested via a single arm proof-of-concept study involving 19 women who were 3-6 months postpartum HDP. PA behavior (steps/day) was measured with an activPAL4 micro.
Results: A total of 140 of 152 possible health coaching sessions were attended by those who started the intervention (n = 19; 92.1%). Intervention completers (n=17) indicated they were satisfied with the program (100%) and would recommend it to others (100%). No significant changes in activPAL measured steps were observed from pre- to post-testing (+138.40±1294.00 steps/day; P = 0.75).
Conclusions: While PA behaviors did not change, the intervention was found to be feasible and acceptable among this sample of at-risk women. After additional refinement, the intervention should be retested among a larger, more diverse, and less active sample.
Background: Digital phenotyping (DP), the process of using data from digital devices, like smartphones and wearable technology to understand and monitor people's behaviour, health, and daily activitie...
Background: Digital phenotyping (DP), the process of using data from digital devices, like smartphones and wearable technology to understand and monitor people's behaviour, health, and daily activities, has shown significant promise in mental health care within high-income countries (HICs). However, its application in lower and middle-income countries (LMICs) is limited, particularly among impoverished populations such as slum residents. Objective: This study investigates the awareness, knowledge, acceptance, and implementation of DP, including willingness to share data, and concerns regarding privacy and data security, among residents of Dhaka's Korail slum, one of Bangladesh's largest and most densely populated informal settlements. Methods: We conducted eight focus group discussions (FGDs) with 38 participants with individuals diagnosed with serious mental disorders (SMDs) and their caregivers. The FGDs also included a section explaining what DP is. Results: There was a general lack of awareness about DP among the participants. Most had no prior knowledge of DP, but after receiving an explanation, they acknowledged its potential applications and benefits. Participants recognized the utility of DP for health monitoring, particularly in managing mental health conditions. They expressed their interest in sharing data, if the content of their activities was not accessed. Despite these perceived benefits, significant concerns about privacy and data security emerged. Participants expressed fears about the potential misuse of their personal information, with some feeling resigned to the idea of already being constantly monitored. This highlights a critical barrier to the adoption of DP tools: the need for robust data protection measures and transparent communication to build trust among users. Participants stressed the need for DP to reflect local customs and practices. Conclusions: To implement DP effectively in LMICs, educational initiatives are necessary to raise awareness and understanding of the technology. Additionally, robust data protection measures must be in place, and clear communication about these measures can help alleviate fears and build trust. DP tools should be adapted to fit the cultural context of the target population, possibly involving modifications to the types of data collected or the way data is interpreted. In conclusion, while DP holds potential to improve mental health care in underserved communities, addressing barriers related to awareness, privacy, culture and usability is crucial. Focusing on educational initiatives, robust data protection, cultural adaptation, user-friendly design, and community engagement, DP can become a valuable tool in bridging the mental health care gap in LMICs.
Background: The purpose of this study was to conduct a systematic review of Internet-based teleinterventions for patients with hypertension and to evaluate the cost-effectiveness of Internet-based tel...
Background: The purpose of this study was to conduct a systematic review of Internet-based teleinterventions for patients with hypertension and to evaluate the cost-effectiveness of Internet-based teleinterventions for the management of hypertension. Objective: The purpose of this study was to conduct a systematic review of Internet-based teleinterventions for patients with hypertension and to evaluate the cost-effectiveness of Internet-based teleinterventions for the management of hypertension. Methods: A computerized search of the literature on health economics studies of remote interventions for hypertensive patients via the Internet in national and international databases was conducted from database construction to March 2023, and a qualitative systematic evaluation was performed by 2 researchers after independently screening the literature, extracting information, and evaluating the risk of bias of included studies. The risk of bias evaluation referred to the entries in the Consensus of Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) list that addressed the risk of bias. Results: The final 14 included literature on Internet-based remote blood pressure monitoring systems, mobile applications, and e-mail blood pressure management;7 literature underwent cost-benefit analysis, 3 literature underwent cost-utility analysis, 1 literature underwent cost-effectiveness analysis, and 1 literature underwent both cost-effectiveness analysis and cost-utility analysis; 2 literature conducted both cost effectiveness and cost-utility analysis; A total of 8 studies modeled health economics. all studies used quality-adjusted life-years as the primary output outcome indicator and 88% of the studies considered the intervention cost-effective and concluded that the teleintervention increased Quality-adjusted life years（QALY）; there were also cost-effectiveness analysis studies that included systolic blood pressure and blood pressure control rates, new cardiovascular events as health output indicators.An assessment of the included literature based on CHEERS 2022 found that the quality of included studies was high. Conclusions: The current study allows to conclude that Internet-based remote intervention for hypertensive patients may be economical and effective in controlling blood pressure levels and improving the quality of life of hypertensive patients. The number of studies on the economics of Internet-based remote interventions for hypertension is high, but the quality of some of them needs to be improved, and there is still a need for higher quality, larger samples, and more standardized health economics evaluation studies to provide evidence for policy makers in the future.
Background: Understanding the dementia disease trajectory and clinical practice patterns in outpatient settings is vital for effective management. Knowledge about the path from initial memory loss com...
Background: Understanding the dementia disease trajectory and clinical practice patterns in outpatient settings is vital for effective management. Knowledge about the path from initial memory loss complaints to dementia diagnosis remains limited Objective: This study aims to 1) determine the time intervals between initial memory loss complaints and dementia diagnosis in outpatient care, 2) assess the proportion of patients receiving cognition-enhancing medication prior to dementia diagnosis, and 3) identify patient and provider characteristics that influence the time between memory complaints and diagnosis, and the prescription of cognition-enhancing medication. Methods: This retrospective cohort study utilized a large outpatient EHR database from the University of Connecticut Health Center, covering 2010-2018, with a cohort of 581 outpatients. We employed a customized deep learning-based natural language processing (NLP) pipeline to extract clinical information from electronic health record (EHR) data, focusing on cognition-related symptoms, primary caregiver relation, and medication usage. We applied descriptive statistics, linear, and logistic regression for analysis. Results: The NLP pipeline showed precision, recall, and F1 scores of 0.97, 0.93, and 0.95, respectively. The median time from the first memory loss complaint to dementia diagnosis was 342 days. Factors such as the location of initial complaints and diagnosis, and primary caregiver relationships significantly affected this interval. Around 25% of patients were prescribed cognition-enhancing medication before diagnosis, with the number of complaints influencing medication usage Conclusions: Our NLP-guided analysis provided insights into the clinical pathways from memory complaints to dementia diagnosis and medication practices, which can enhance patient care and decision-making in outpatient settings.
Background: With obesity posing an increasing public health challenge, the demand for personalized weight loss and fitness solutions has intensified. Given advancements in artificial intelligence, lik...
Background: With obesity posing an increasing public health challenge, the demand for personalized weight loss and fitness solutions has intensified. Given advancements in artificial intelligence, like GPT-4, this study evaluates its effectiveness as a virtual fitness coach for creating personalized plans.
Method: We selected a 24-year-old female from Chongqing, China, providing detailed personal information. Using this, both GPT-4 and three local professional coaches formulated 16-week fitness plans. Senior health science experts evaluated these plans across four dimensions: personalization, effectiveness, comprehensiveness, and safety. Descriptive and inferential statistics were employed for analysis.
Results: GPT-4 excelled in personalization (M=12.80, SD=0.84) compared to coaches (M=11.53, SD=0.46). However, coaches slightly outperformed in effectiveness (GPT-4: M=12.60; Coaches: M=12.80), safety (GPT-4: M=12.20; Coaches: M=12.33), and comprehensiveness (GPT-4: M=12.00; Coaches: M=12.13), with no significant differences (P > .05). These findings highlight comparable performance but suggest potential for GPT-4 in personalized exercise prescriptions.
Conclusions: GPT-4 shows promise as a virtual fitness coach for personalized weight loss and fitness guidance. Yet, due to technological constraints, it cannot fully replace human coaches. Future research should explore enhancing AI models' applicability in sports and their collaboration with coaches for optimal personalized fitness solutions.
Background: The use of virtual mental healthcare increased rapidly in 2020 as a critical response to the COVID-19 pandemic, effectively serving as a contact-free alternative to receiving treatment. Wh...
Background: The use of virtual mental healthcare increased rapidly in 2020 as a critical response to the COVID-19 pandemic, effectively serving as a contact-free alternative to receiving treatment. While virtual care remains a viable option for individuals with geographic and physical barriers to treatment, there are several perceived therapeutic disadvantages (e.g., missing nonverbal signals, handling crises, confidentiality, weakened social connection in group therapy). Objective: The present study sought to develop and validate a survey designed to measure effectiveness of virtual therapy versus in-person treatment across key therapeutic factors (i.e., therapeutic alliance, engagement, rapport, confidentiality). Methods: An exploratory factor analysis (EFA) was conducted to understand factor structure, and Cronbach’s alpha was utilized to determine internal consistency. Incremental validity was demonstrated through a hierarchical linear regression. Results: The EFA revealed a three-dimensional factor structure. Three factors accounted for 61% of the variance and preliminary Cronbach’s alpha (α =0.71) indicates a satisfactory level of internal consistency. Hierarchical linear regression indicated that the Client Satisfaction Questionnaire (CSQ) accounts for additional variance in the Therapy Mode Preference Scale (TMPS). Conclusions: Continual research is warranted to expand the current findings, by validating this standardized tool for assessing the therapeutic impact of virtual versus in-person care in a generalizable population.
Background: Social media platforms offer valuable insights into the patient’s experience, revealing organic conversations that reflect their immediate concerns and needs. Through active listening to...
Background: Social media platforms offer valuable insights into the patient’s experience, revealing organic conversations that reflect their immediate concerns and needs. Through active listening to lived experiences, we can identify unmet needs and discover real-world challenges patients and caregivers face. Objective: This study aimed to develop a reusable framework to collect and analyze evolving social media data, capturing insights into the experiences of individuals with MDS and higher-risk myelodysplastic syndromes (HR-MDS) and their caregivers. The findings can inform the development of appropriate patient support interventions. Methods: We conducted an extensive Google search to identify social posts of interest using validated URLs and keywords on English-language websites relevant to MDS. The search covered the period from 1/1/2008 to 12/31/2022. We utilized scraping algorithms to collect, clean, and standardize pertinent information. To classify the perspective of each experience as either that of a patient or caregiver, we employed classification algorithms. This involved contextualizing and summarizing all user posts, followed by decision tree tagging to assign them to the patient or caregiver category. Advanced algorithms were employed to analyze the semantic and temporal structure of the data. Patients or caregivers were categorized as HR-MDS based on contextual mentions of high-risk in their posts or specific factors aligned with NCCN guidelines (e.g., blast percentage, transplantation, use of high-intensity chemotherapy or hypomethylating agents, or disease progression). Each post was assigned major themes and sentiments using a supervised classification machine learning model. Additionally, we employed a semi-supervised machine learning approach for the identification of latent themes in the data corpus. Results: The data collected comprised approximately 5.5 million words from 42,000 posts across 5,500 threads, involving about 4,000 users predominantly from the US, UK, and Canada. Out of the 1,249 users classified as HR-MDS, 588 (47%) were patients and 661 (53%) were caregivers. Among the HR-MDS users, the predominant sentiments included concern (78%), anxiety (60%), frustration (58%), fear (58%), and confusion (49%). Concern was the predominant sentiment expressed by caregivers (n=971, 59%), and anxiety by patients (n=752, 55%). Common concerns were specifically related to blood counts (n=677, 54%), burden of the disease (43%), QoL (36%), available treatment options and effectiveness (31%), and disease progression and prognosis (31%). Anxiety related to health and disease (48%), treatment (26%), and the diagnostic process (20%) were also common. The most common sentiments related to fear were the potential development of health complications and the manifestation of symptoms (19%) and the progression and exacerbation of MDS (19%). Additionally, confusion was pervasive among participants, with 295 (24%) individuals finding it challenging to comprehend the nuances of MDS and its diagnosis. A systematic analysis of the principal domains for which information is being sought about HR-MDS revealed frequent mention amongst users of acquiring information on therapeutic intervention (19%), and an interest in ongoing research associated with the disease (17%) Conclusions: The application of sophisticated NLP techniques demonstrates promise in effectively identifying the emerging complex themes and sentiments experienced by HR-MDS users, thereby highlighting the unmet needs, barriers, and facilitators associated with the disease. Clinical Trial: NA
Background: Large Artificial Intelligence (AI) language models have been increasingly applied in the medical field for disease prediction, diagnosis, and evaluation. However, research on AI-assisted e...
Background: Large Artificial Intelligence (AI) language models have been increasingly applied in the medical field for disease prediction, diagnosis, and evaluation. However, research on AI-assisted early sepsis identification and screening remains scarce. Here, we conduct a retrospective study to evaluate the diagnostic efficacy of a novel medical large language model-MedGo developed by our collaborating team and us in early sepsis in emergency department (ED). Objective: This study aims to evaluate the performance of a novel medical artificial intelligence large language model, MedGo, in supporting clinical decision-making for emergency department patients with suspected sepsis, specifically focusing on its diagnostic accuracy, comprehensiveness, readability, and analytical capabilities compared to physicians with varying levels of experience. Methods: We retrospectively collected medical history data from 203 eligible patients treated at a tertiary teaching hospital between January 1, 2023 and January 1, 2024. MedGo’s performance was compared to that of junior and senior ED physicians across nine assessment tasks related to the diagnosis and management of sepsis . A five-point Likert scale was used to assess the four dimensions of accuracy, comprehensiveness, readability and case analysis skills. Results: MedGo exhibited diagnostic performance comparable to senior doctors, scoring 4 on the Likert Scale for accuracy, comprehensiveness, readability, and analytical capability, significantly surpassing junior doctors. Furthermore, MedGo's decision support enhanced both junior and senior doctors' diagnostic abilities, with junior doctors' performance equal that of seniors. Notably, MedGo consistently delivered exceptional results in diagnosing early sepsis cases of varying severity. Conclusions: MedGo demonstrates remarkable diagnostic efficacy in early sepsis, effectively supporting clinicians of diverse experience levels in making informed decisions in the time-urgent ED. Although we acknowledge its limitations and emphasize the importance of comprehensive, standardized, systematic, and visualized medical history data in future research endeavors, the results underscore the potential of MedGo as a supportive tool in ED settings, thereby laying the groundwork for future developing specialized sepsis models.
Background: Atrial fibrillation (AF) is the most common arrhythmia in clinical practice, yet interpretation concerns among healthcare providers persist. Confounding factors contribute to false-positiv...
Background: Atrial fibrillation (AF) is the most common arrhythmia in clinical practice, yet interpretation concerns among healthcare providers persist. Confounding factors contribute to false-positive and false-negative AF diagnoses, leading to potential omissions. Artificial intelligence advancements show promise in electrocardiogram (ECG) interpretation. Objective: We sought to examine the diagnostic accuracy of ChatGPT-4omni (GPT-4o), equipped with image evaluation capabilities, in interpreting ECGs with confounding factors and compare its performance to that of physicians. Methods: Twenty ECG cases, divided into Group A (10 cases of AF or atrial flutter) and Group B (10 cases of sinus or another atrial rhythm), were crafted into multiple-choice questions. Total of 100 practitioners (25 from each: emergency medicine, internal medicine, primary care, and cardiology) were tasked to identify the underlying rhythm. Next, GPT-4o was prompted in five separate sessions. Results: GPT-4o performed inadequately, averaging 3 (±2) in Group A questions and 5.40 (±1.34) in Group B questions. Upon examining the accuracy of the total ECG questions, no significant difference was found between GPT-4o, internists, and primary care physicians (p = 0.952 and = 0.852, respectively). Cardiologists outperformed other medical disciplines and GPT-4o (p < 0.001), while emergency physicians followed in accuracy, though comparison to GPT-4o only indicated a trend (p = 0.068). Conclusions: GPT-4o demonstrated suboptimal accuracy with significant under- and over-recognition of AF in ECGs with confounding factors. Despite its potential as a supportive tool for ECG interpretation, its performance did not surpass that of medical practitioners, underscoring the continued importance of human expertise in complex diagnostics.
Background: To understand the acceptance of healthcare technology for older adults, the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) is commonly...
Background: To understand the acceptance of healthcare technology for older adults, the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) is commonly used. However, the divergence in the current literature makes it difficult to predict acceptance and understand how various factors affect older adults’ behavior. Objective: This study aims to 1) determine the influence of perceived usefulness (PU), perceived ease of use (PEOU), and social influence (SI) on the behavioral intention (BI) to use healthcare technology among older adults and 2) and assess the moderating effects of age, gender, geographic region, type of healthcare technology, and the presence of visual demonstrations on these three pairwise relationships. Methods: Google Scholar, Web of Science, Scopus, IEEE Xplore, and ProQuest electronic databases were searched from inception to February 2024. Two independent reviewers screened the titles, abstracts, full texts, and performed data extraction and risk of bias assessments with the Newcastle-Ottawa Quality Assessment Scale. The "meta" package in R was used for data synthesis, conducting random-effects meta-analyses, meta-regression and subgroup analysis. Results: 41 studies with a total of 11,574 participants were included. Random-effects meta-analyses showed significant positive correlations for PU-BI (r = 0.607, 95% CI 0.543 - 0.665, P < .001), PEOU-BI (r = 0.525, 95% CI 0.462 - 0.583, P < .001), and SI-BI (r = 0.551, 95% CI 0.468 - 0.624, P < .001). Moderator analyses indicated significant differences in effect sizes based on geographic region for PEOU-BI (Q-test, P = .04), type of technology for PU-BI (Q-test, P = .04) and SI-BI (Q-test, P = .002), and presence of visual demonstrations for PU-BI (Q-test, P = .03) and SI-BI (Q-test, P = .04). Conclusions: The findings indicate that PU, PEOU, SI significantly impact the acceptance of healthcare technology among older adults, with heterogeneity influenced by geographic region, type of technology, and presence of visual demonstrations. Researchers should account for these variables when interpreting previous research and embarking on new studies with the TAM or UTAUT model for older adults. Clinical Trial: Current paper is not RCT
Background: Dementia poses a significant global health challenge, characterized by progressive cognitive decline and functional impairment. With the aging global population, dementia prevalence is pro...
Background: Dementia poses a significant global health challenge, characterized by progressive cognitive decline and functional impairment. With the aging global population, dementia prevalence is projected to surge, reaching an estimated 153 million cases by 2050. While the impact of traditional social isolation on dementia risk has been extensively studied, the influence of digital isolation—a phenomenon unique to the digital age—remains underexplored. Objective: This study investigates the association between digital isolation and dementia risk among older adults, hypothesizing that higher levels of digital isolation significantly increase the risk of developing dementia. Methods: We conducted a longitudinal cohort study using data from the National Health and Aging Trends Study (NHATS), analyzing 8,189 participants aged 65 and older from the third (2013) to the twelfth wave (2022). Digital isolation was quantified using a composite Digital Isolation Index, derived from participants' usage of digital devices, electronic communication, internet access, and engagement in online activities. Participants were stratified into low isolation and moderate to high isolation groups. Dementia incidence was assessed using cognitive tests and proxy reports. Cox proportional hazards models were employed to estimate the association between digital isolation and dementia risk, adjusting for potential confounders including sociodemographic factors, baseline health conditions, and lifestyle variables. Results: The moderate to high isolation group demonstrated a significantly elevated risk of dementia compared to the low isolation group. In the discovery cohort, the adjusted hazard ratio (HR) was 1.25 (95% CI: 1.03-1.52, P=0.023), while the validation cohort showed an HR of 1.68 (95% CI: 1.30-2.16, P<0.001). The pooled analysis across both cohorts revealed an adjusted HR of 1.40 (95% CI: 1.20-1.64, P<0.001). Kaplan-Meier curves corroborated a higher incidence of dementia in the moderate to high isolation group. Conclusions: Our findings indicate that digital isolation is a significant risk factor for dementia among older adults. This study underscores the importance of digital engagement in mitigating dementia risk and suggests that promoting digital literacy and access to digital resources should be integral components of public health strategies aimed at dementia prevention.
Background: The coronavirus disease 2019 (COVID-19) pandemic is among the greatest global public health challenges of this century.The WHO and the Johns Hopkins University Center for Systems Science a...
Background: The coronavirus disease 2019 (COVID-19) pandemic is among the greatest global public health challenges of this century.The WHO and the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) were two open-access data sources which were widely used in research and decision-making about the COVID-19 epidemic.High-quality data is one key aspect of public health crisis and pandemic preparedness for decision-making, practice, and research about prevention and control. To better respond to pandemics and other health crises in the future, it is necessary to evaluate the quality of pandemic data to improve rapid response to outbreaks. Objective: To evaluate consistency of daily reported Coronavirus disease 2019 (COVID-19) cases in 191 countries from the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) and the World Health Organization (WHO) dashboards during 2020-2022. Methods: We retrieved data concerning new daily COVID-19 cases in 191 countries covered by both data sources from January 22, 2020, to December 31, 2022. The ratio of numbers of daily reported cases from the two sources were calculated to measure data consistency. We performed simple linear regression to examine significant changes in the ratio of numbers of daily reported cases during the study period. Results: Of 191 WHO member countries, only 60 displayed excellent data consistency in the number of daily reported COVID-19 cases between the WHO and JHU CSSE dashboards (case number ratio: 0.9-1.1). Data consistency changed greatly across the 191 countries from 2020 to 2022 and differed across four types of countries, defined by income. Data inconsistency between the two data sources generally decreased slightly over time, both for the 191 countries combined and within the four types of income-defined countries. The absolute relative difference between two data sources increased in 84 countries (particularly for Malta, Montenegro, and United States, R2=0.29) but decreased in 40 countries (P<0.05). Conclusions: The inconsistency between the two data sources warrants further research. Construction of public health surveillance and data collection systems for public health emergencies like the COVID-19 pandemic should be strengthened in the future.
Background: Social media is currently serving as a tool for increased digital interconnectedness and has resulted in playing an instrumental role in sharing health-related information with a wide audi...
Background: Social media is currently serving as a tool for increased digital interconnectedness and has resulted in playing an instrumental role in sharing health-related information with a wide audience. In conjunction with the vast availability of information, there has been a rapid spread of misinformation, leading to public mistrust, safety concerns, and discrimination. The COVID-19 pandemic has amplified the threat of misinformation resulting in detrimental health outcomes due to individuals becoming fatigued with COVID-19 health guidance. Although vaccinations are the key to combating COVID-19, the overwhelming amount of misinformation has resulted in diminished vaccine acceptance. Objective: (1) Train and deploy a group of healthcare workers and student volunteers to address anti-vaccine sentiment on Facebook; and, (2) Evaluate the intervention through semi-structured interviews to determine lessons learned and suggestions for future initiatives to address misinformation online Methods: The project utilized volunteers to address vaccine-hesitant comments on Facebook (Met Platforms Inc., Menlo Park, California), with the overall goal of empowering healthcare professionals to engage with vaccine-hesitant individuals online to counteract the spread of vaccine misinformation. Eligible participants included healthcare workers and students in healthcare-related disciplines were recruited through social media and email advertising campaigns by the University of Calgary, School of Nursing contact list. Informational training sessions on Zoom with a duration of 30-minutes followed, to better equip volunteers with the ability to utilize their working knowledge of health communication and behaviour change to correct online misinformation. During the deployment of volunteers, they were provided a file containing Facebook posts that discussed COVID-19 vaccines to act as a starting point for leaving or responding to comments that spread vaccine misinformation. Participants in the project were provided with working knowledge of health communication, behaviour change, and correct misinformation through the informational training sessions. Qualitative evaluation in the form of interviews were used to examine participant experiences, where it was found that volunteers felt that they were adequately equipped to engage in vaccine conversations both online and in healthcare settings. Overall, the project has addressed vaccine hesitancy and valuable insights into the relationship between public engagement and communication in the era of digital interconnectedness. Results: Following the evaluative interview discussions, three main themes emerged regarding the project’s format and training model, the factors motivating volunteers to participate, and overall experiences tackling misinformation on an online platform. The first theme showcased that the training format was effective due to its use of interactive components and overall flexibility, resulting in it being well-received by volunteers. The second identified theme highlighted that a main driving factor for participation included a balance of professional development and societal good. Finally, the third theme revealed that the volunteers' experiences in interacting with the public revealed a rich tapestry of emotions and perspectives, where vaccine hesitancy is interconnected with emotional responses and personal beliefs. Conclusions: The Informed Choice Project provided an opportunity to increase self-efficacy and confidence for more than a dozen healthcare professionals and students while engaging in vaccine-related conversations online. Immediate challenges associated with the COVID-19 pandemic, including combating misinformation and promotion of vaccination were addressed, which has resulted in a more reliable groundwork for shaping future public health communication strategies. To enhance both participant satisfaction and compliance, future interventions should consider utilizing a self-paced format, flexible hours, and highlight the vitality of healthcare professionals as key advocates for trusted sources of information for the public.
Background: Since November 2022, with the debut of OpenAI’s ChatGPT, there has been growing interest in the use of generative artificial intelligence (AI), including in healthcare. However, there is...
Background: Since November 2022, with the debut of OpenAI’s ChatGPT, there has been growing interest in the use of generative artificial intelligence (AI), including in healthcare. However, there is only limited research into doctors’ adoption of these tools and their opinions about their application in clinical practice. Objective: This study aimed to explore the opinions of general practitioners (GPs) in the United Kingdom (UK) about the use of generative AI tools (ChatGPT/Bard/Bing AI) in primary care. Methods: Between February 2nd-24th 2024, using a convenience sample, we administered a web-based mixed methods survey of 1000 GPs in the UK to explore their experiences and opinions about the impact of generative AI on clinical practice. Participants were recruited from registered GPs currently working in the UK using the clinician marketing service Doctors.net.uk. Quantitative data were analyzed using descriptive statistics and nonparametric tests. We used thematic content analysis to investigate free-text responses and conducted a qualitative descriptive analysis of written responses (“comments”) to 2 open-ended questions embedded in the web-based questionnaire. Results: A total of 1006 GPs responded, with 53% being male and 54% aged 46 years and older. Most GPs (80%) expressed a need for more support and training in understanding these tools. GPs at least somewhat agreed AI would improve documentation (59%), patient information gathering (56%), treatment plans (41%), diagnostic accuracy (40%), and prognostic accuracy (38%). Additionally, 62% believed patients might rely more on AI, 55% felt it could increase inequities, and 54% saw potential for patient harm, but 47% believed it would enhance healthcare efficiency. GPs who used these tools were significantly more optimistic about the scope for generative AI in improving clinical tasks compared with those who did not report using them. Elaborating on the quantitative component of the survey, 31% (307/1006) left comments that were classified into 4 major themes in relation to generative AI in medicine: (1) lack of familiarity and understanding, (2) a role in clinical practice, (3) concerns, and (4) thoughts on future of healthcare. Conclusions: This study highlights UK GPs' perspectives on generative AI in clinical practice, emphasizing the need for more training. Many GPs reported a lack of knowledge and experience with this technology and a significant proportion used non-medical grade technology for clinical tasks, with the risks that this entails. Medical organizations must urgently invest in educating and guiding physicians on AI use and limitations.
Background: Digital health interventions, such as electronic immunization registries (eIR) and electronic Logistic Management Information Systems (eLMIS), have the potential to significantly improve i...
Background: Digital health interventions, such as electronic immunization registries (eIR) and electronic Logistic Management Information Systems (eLMIS), have the potential to significantly improve immunization data management and vaccine logistics in low- and middle-income countries (LMICs). Despite their growing adoption, there is limited evidence on the financial and economic costs associated with their implementation compared to traditional paper-based systems. Objective: We aimed to measure the costs of implementing and maintaining eIR and eLMIS systems in LMICs, and to estimate the affordability of their implementation as compared to the previous paper-based registries. Methods: The study was conducted across four countries: Guinea, Honduras, Rwanda, and Tanzania. A combination of primary and secondary data sources was used for the analysis. Expenditure information regarding the design, development and implementation of the tools was directly obtained from implementers and National Immunization Program offices in all countries. Primary survey data was collected to gauge the operational expenses of immunization information systems, both with and without electronic tools using an Activity Based Costing approach. The cost of immunization information system to the national level was then extrapolated and compared to national spending on immunization as a measure for affordability. Results: The total costs of designing, developing and deploying eIR and/or eLMIS were I$ 1.7, 5.4, 4.7 and 33 million in Guinea, Honduras, Rwanda and Tanzania respectively. Design costs were greatly affected by the degree of customization of the tool, whereas roll out costs were mostly driven by the costs of purchasing hardware and training of health workers. Overall, the implementation of the electronic systems was associated with higher costs in Honduras (I$ 535 per facility, 95% CI 441; 702) and Rwanda (I$ 278, 95%CI 75; 482), a cost reduction in Tanzania (I$ -1,770, 95%CI -2,990; -550) and no significant cost difference in Guinea. The percentage weight of the cost of managing data with the electronic systems over the total national immunization budgets was estimated at 8.6%, 1.1%, 3.7% and 1.8% for Honduras, Rwanda, Tanzania and Guinea, respectively Conclusions: Digital health interventions such as eIR and eLMIS can potentially reduce costs and improve the efficiency of immunization data management and vaccine logistics in LMICs. However, the extent of cost savings is contingent upon the degree to which these digital systems replace traditional paper-based methods. Our study suggests that the economic impact of digital health solutions greatly depends on factors such as infrastructure, implementation, and the extent to which these technologies are integrated into existing healthcare systems. Careful planning and investment are essential to realizing the full economic potential of digital health in LMICs.
Background: Qualitative experience data can inform healthcare providers how to best support families during pediatric postoperative recovery. Patient experience data can also provide actionable inform...
Background: Qualitative experience data can inform healthcare providers how to best support families during pediatric postoperative recovery. Patient experience data can also provide actionable information to guide healthcare quality improvement: positive feedback can confirm the efficacy of current practices and systems, while negative comments can identify areas for improvement. Objective: To understand families’ perspectives regarding their child’s surgical recovery using qualitative patient experience data (free-text comments) from a prospective cohort study conducted within a larger study developing postoperative outcomes risk stratification model. Methods: Participants were parents/guardians of children aged 0-18 who underwent surgery at a pediatric tertiary care facility; children undergoing either outpatient or inpatient procedures were eligible to be enrolled. English second language participants were offered translational services during the consent process and were included if any family member could translate the surveys to their preferred language. Participants were ineligible if they and their families could not understand English or their child had a neurodevelopmental disability. Perioperative survey data were collected from families using the Research Electronic Data Capture tool, including one preoperative survey and follow-up surveys sent on postoperative day (POD) 1, 2, 3, 7, 15, 30, and 90. Surveys were completed until the family indicated the child was fully recovered or until POD 90 was reached. Follow-up surveys included opportunities to leave free-text comments on their child’s surgical experience. Thematic content analysis of free-text comments was completed using NVivo, and quantitative analysis was performed using R. Results: In total, 454/500 (91%) enrolled families completed at least one postoperative survey; 242/454 (53%) provided at least one free-text comment and were included in the presented analysis, based on a total of 485 comments. The patient's age distribution was bimodal (modes at 2-3 and 14-15 years), with 160 (66%) being male. Patients underwent orthopedic (24%), urology (16%), general (15%), otolaryngology (13%), ophthalmology (13%), dental (11%), and plastic (7%) surgeries. Largely positive comments (398/485; 82%) were made on the recovery and clinical care experience. A key theme for improvement included “communication,” with subthemes highlighting parental concerns regarding the “preoperative discussions,” “clarity of discharge instructions,” and “continuity of care.” Other themes included “length of stay” and “recovery experience.” Feedback also suggested survey design amendments for future iterations of this instrument. Conclusions: Collecting parental recovery feedback is feasible and valued by families. Findings underscored the significance of enhancing communication strategies between healthcare providers and parents to align expectations and support proactive family-centred care. Our postoperative surveys allowed families to provide actionable suggestions for improving their experience, which may not have been considered during their hospital encounter. Our longitudinal survey protocol may be expanded to support continuous QI initiatives involving near-real-time patient feedback to improve the healthcare experience of patients and families.
Background: Emotion recognition bias in depression is well documented and is proposed to play a causal role in depression. A Cognitive Bias Modification (CBM) intervention targeting the bias in emotio...
Background: Emotion recognition bias in depression is well documented and is proposed to play a causal role in depression. A Cognitive Bias Modification (CBM) intervention targeting the bias in emotional expression perception was developed, but despite robust training effects on emotion perception, the effect on mood was unreliable and weak. We propose a new gamified version of CBM (GCBM) to address potential limitations that may attenuate therapeutic effects. Objective: This study aims to test the effectiveness of GCBM in altering the perception of emotional facial expressions and improving the immediate mood of healthy participants.
Study 1 aimed to investigate the effectiveness of a single session of GCBM on emotion perception and to assess whether the gamified version of the task would produce the same robust training effects on the interpretation of emotional expressions as the original CBM.
Study 2 aimed to compare the effectiveness of a single session of CBM training, CBM (no training) control, and GCBM training on immediate mood. Methods: We reported two between-subjects online experimental studies that recruited participants from the general population. Study 1 (N = 58) tested the effectiveness of GCBM in changing participants' responses to ambiguous facial expressions. The primary outcome was emotion recognition bias, measured by increased identification of happy faces. Study 2 (N = 916) compared the effects of a single session of GCBM training, CBM training and CBM control conditions on immediate mood. The primary outcome was immediate mood after the training, measured by the Immediate Mood Scaler (IMS). Results: Study 1 showed that participants in the intervention condition classified more ambiguous faces as 'happy' after the training compared to controls, indicating an increased perception of happiness in ambiguous faces. (B = 1.73, P < .001). Study 2 provided evidence that GCBM training produced more positive changes in immediate mood compared to the CBM control condition (B = -3.64, P = .003) and compared to the CBM training condition (B = 1.73, P = .044). Conclusions: These studies showed that GCBM may change participants' emotion recognition bias to ambiguous facial expressions and enhance mood compared to both CBM and control conditions. These results suggest that GCBM might be an effective intervention for addressing mood-related cognitive biases. Further exploration of GCBM's long-term effects on mood and its clinical application is needed.
Background: Hypertrophic scarring is a condition where excessive connective tissue growth occurs after deep skin injuries such as burns, frostbite, and surgery. This condition not only affects a patie...
Background: Hypertrophic scarring is a condition where excessive connective tissue growth occurs after deep skin injuries such as burns, frostbite, and surgery. This condition not only affects a patient's physical appearance but also causes symptoms like itching, pain, and limited limb function, significantly impacting their quality of life. TikTok, a popular platform for sharing short videos, has shown potential in spreading health information, particularly in educating people about hypertrophic scarring. Objective: This study aims to analyze the content and quality of short videos related to hypertrophic scarring on TikTok, providing valuable insights for health information dissemination. Methods: This study examined 153 short TikTok videos focusing on hypertrophic scarring. The videos were found by searching for the keywords 'scar hyperplasia' and 'hypertrophic scars' (Language: Chinese). The sources of the videos were thoroughly verified, and the content's comprehensiveness was assessed using a six-core question framework covering definition, signs and symptoms, risk factors, evaluation, management, and outcomes. The reliability and quality of the videos were evaluated using standardized tools such as DISCERN, JAMA benchmarks, the Global Quality Scale (GQS), and HON code. In the comprehensive evaluation of video reliability and quality, we calculated the average scores of four assessment methods (labeled as R) to indicate the overall reliability and quality of the videos. The study also explored the potential relationship between video quality and characteristics. Results: The analysis showed that healthcare professionals uploaded all videos about treating hypertrophic scarring, which matches the hexagonal radar model analysis findings. The quality assessment scores for JAMA, GQS, DISCERN, and HON code had median values of 1 (IQR 1-2), 2 (IQR 2-3), 2 (IQR 2-3), and 3 (IQR 3-4) respectively, indicating a need to improve the quality and reliability of videos on hypertrophic scarring. Additionally, high-quality videos were more popular, based on metrics such as likes, comments, favorites, and shares (P<.001). Interestingly, the time when the videos were uploaded positively correlated with GQS and DISCERN scores (r=0.374, P<.001; r=0.281, P<.001), while the video length did not significantly correlate with evaluation scores. Conclusions: This study emphasizes the need for improved quality and comprehensiveness of short TikTok videos addressing hypertrophic scarring. The information presented should be more reliable and scientifically accurate. When watching videos related to hypertrophic scars, we strongly recommend that viewers prefer content published by healthcare professionals from the Burn Department and Burn Plastic Surgery Department, as well as those from first-tier and emerging first-tier cities. As social media platforms like TikTok increasingly influence health information, viewers should evaluate short videos' scientific validity and reliability before making medical decisions. Moreover, creators of such videos should prioritize scientific accuracy and precision in their content to improve video quality and effectively meet the needs of their audience.
Background: TikTok is regarded as one of the major social media platforms for sharing health-related information, including teaching TikTok users about pregnancy prevention strategies. Adolescent lear...
Background: TikTok is regarded as one of the major social media platforms for sharing health-related information, including teaching TikTok users about pregnancy prevention strategies. Adolescent learners are also using this social media to learn about various types of contraceptives that can be used to prevent pregnancy due to a lack of information on the subject from parents, teachers, and clinic staff, as well as a fear of being judged when discussing such sensitive health topics. However, pregnancy prevention material shared on TikTok can be either accurate or misleading. Objective: The study sought to explore and describe adolescent learners' perspectives on the influence of TikTok in pregnancy prevention in Vhembe District Methods: This study was conducted using a cooperative inquiry qualitative research design. This study stems from the study umbrella study, which aimed to develop strategies for the prevention of adolescent learner pregnancy. Data was collected using the Lekgotla data discussion method. This study's data was analyzed using NVIVO version 14 following the six Tesch thematic phases. Results: Four themes emerged from the data analysis: home-based concoctions recipes used for pregnancy prevention methods, other home-based recipes used for pregnancy prevention methods, home-based pregnancy test recipes, and different types of modern contraceptives used for pregnancy prevention. Conclusions: Adolescent TikTok users learn pregnancy prevention methods that are myth-based and misleading. Regulating content on TikTok is crucial to avoid harm to teenagers using home remedies for pregnancy prevention.
Background: White spot lesions (WSLs) are white marks that can form on teeth during orthodontic treatment with fixed appliances (FA) and become apparent once they are removed. About half of people who...
Background: White spot lesions (WSLs) are white marks that can form on teeth during orthodontic treatment with fixed appliances (FA) and become apparent once they are removed. About half of people who have FA treatment get WSLs. They are usually caused by poor tooth-brushing around the brace.
Several studies explore the prevention and/or treatment of WSL. However, there remain uncertainties about what young people and their parents/guardians know or feel about WSL. A Cochrane review concluded that patient-reported outcomes have been overlooked in WSL prevention studies. Objective: This protocol describes a mixed-methods study that aims to explore young people’s and their parents/ guardians’ perceptions, attitudes, and feelings towards WSLs. Methods: Participants will be recruited from children aged 11-15, undergoing orthodontic treatment at Liverpool University Dental Hospital and their parents/guardians. Part 1 (quantitative) will use a questionnaire and images of pre-treatment malocclusions and post-orthodontic WSLs of varying severity (mild, moderate, severe). Part 2 (qualitative) will involve one-to-one, semi-structured interviews, using open-ended questions with young people and their parents/ guardians.
A sample size of 200 survey respondents for Part 1 and 30 interviewees for Part 2 will be undertaken. The responses for the questionnaire use a Likert scale with the option of free text comments. The qualitative research will be analysed using a modified framework analysis approach; the outcomes will be presented as themes. Results: As of September 2024, we have secured funding from the Royal College of Surgeons, England and British Orthodontic Society. We have also completed sponsor approval with the University of Liverpool. We received an outcome of favourable opinion, pending minor issues from the Health Research Authority regarding our ethics application; we are awaiting the outcome of the submitted response to this. Conclusions: WSLs can be highly visible when smiling or speaking. Aesthetic defects, caused by WSLs, may expose young people to oral health related stigma and discrimination e.g., bullying or teasing and impact on self-esteem. WSLs may also have cost consequences for patients and NHS dental services, for example, the costs of professionally applied fluoride, restorations, and their maintenance. This study is important for understanding the impact WSLs have on oral health-related quality of life and the decision making of young people and their parents/ guardians.
Objective: This study conducts a comprehensive bibliometric analysis to explore the landscape of research on smart hospitals, highlighting significant research trends, challenges, and future direction...
Objective: This study conducts a comprehensive bibliometric analysis to explore the landscape of research on smart hospitals, highlighting significant research trends, challenges, and future directions.
Methods: We analyzed 5,190 publications from the Web of Science and PubMed databases spanning January 2014 to October 2023, employing text mining and Latent Dirichlet Allocation (LDA) for data categorization into four domains: technological application in healthcare ("Function"), implementation challenges ("Barrier"), operational impacts ("Supply"), and patient outcomes ("Demand").
Results: Our findings show a surge in smart hospital publications post-2016 and following the onset of the COVID-19 pandemic. Sixty topics were defined by LDA analysis, and the "Function" domain was the most researched, indicating strong interest in leveraging technology for improved healthcare delivery. However, there was a significant gap in the "Demand" domain, suggesting a need for more patient-centric research. Thematic mapping and co-occurrence analysis highlighted key technological progress and important challenges, including the need for better interoperability and stronger data security. Additionally, a thorough review of key articles emphasized the practical use of these technologies, underlining the importance of increasing patient engagement and tailoring healthcare services to individual needs.
Conclusion: This study reveals a focus on digital technology applications in hospitals but highlights a critical gap in evaluating their effectiveness and developing management-oriented frameworks for smart hospital analysis. It underscores the need for further exploration of the effect of advanced digital technologies and increased managerial research to enhance hospital services and efficiency.
Background: Non-communicable diseases resulting from sedentary behaviour (SB) are adding further strain on the South African health system, which is already struggling to manage infectious diseases. S...
Background: Non-communicable diseases resulting from sedentary behaviour (SB) are adding further strain on the South African health system, which is already struggling to manage infectious diseases. Some countries have enabled children to reduce SB at school by substituting traditional furniture with sit-stand classroom furniture. Alternating between sitting and standing benefits spinal health, but no such intervention exists in South Africa. It is therefore essential to consider several contextual factors, such as the acceptability of the intervention, its impact on teachers' practices, and the logistical and pragmatic considerations of data collection. This study therefore aimed to assess the feasibility of implementing a classroom-based intervention to reduce SB and improve spinal health in primary school learners. Objective: The study objectives were to assess the pragmatics of delivering and adherence to a classroom-based intervention and assess the pragmatics of measuring physical activity and postural dynamism data with activPAL and Noraxon Myomotion inertial measurement units (IMUs), respectively. Methods: We used a stratified, closed-cohort, randomised, two-cluster, stepped-wedge design with a pragmatic approach. One grade 5 and 6 class each were recruited from contrasting socio-economically categorised, publicly funded primary schools in the Western Cape Province, South Africa. Classroom furniture was substituted with sit-stand desks and health and movement videos were shown during class time. Skin-mounted activPAL physical activity monitors and Noraxon Myomotion Inertial measurement units were used to measure SB and spinal movement respectively. The study was evaluated for feasibility by tracking school retention, successful delivery of the videos and use of the desks, compliance with the wearable sensors, and data accuracy. We deductively analysed teacher interviews and learners' focus groups using Atlas.ti 9 software. Descriptive analysis of quantitative data was done using Microsoft Excel. Results: All feasibility outcomes were met in cluster two. Cluster one withdrew from the study before follow-up SB, postural topography and spinal movements were measured. The study found that it is feasible to conduct a larger trial with minor modifications to the methodology. Conclusions: We recommend a whole-school approach to support the intervention and a monitoring strategy to track the impact of the intervention on the classroom. Furthermore, we recommend contextualised teacher training on how sit-stand desks and health education videos can be utilised as classroom management tools. Clinical Trial: Pan African Trials Registry PACTR201811799476016; Registered 22 November 2018 – retrospectively registered; https://tinyurl.com/y4upoys8
Background: Background
The global shortage of healthcare workers has exacerbated the challenges faced by health systems worldwide. The World Health Organization (WHO) projects a deficit of 10 million...
Background: Background
The global shortage of healthcare workers has exacerbated the challenges faced by health systems worldwide. The World Health Organization (WHO) projects a deficit of 10 million healthcare workers by 2030. While low- and lower-middle income countries will be the most affected, all countries will face significant challenges [1]. In the UK, the National Health Service (NHS) is already under considerable strain [2], with significant effects on the quality of care and health outcomes of patients [3].
At the same time, there is a growing demand for health information and increasing consumer empowerment [4]. In this context, the reliance on digital health tools has surged, particularly decision support tools including online symptom checkers (OSCs) [5, 6]. The ubiquitous access to the internet supports this trend, with 96% of households in the UK having internet access in 2020 [7], which accelerated following the advent of the COVID-19 pandemic given the need of health services to avoid face-to-face contact and preserve urgent care capacity [8].
Symptom checkers are available as websites or applications and can generate a prioritised list of potential diagnoses based on the entered symptoms and suggest suitable actions, such as self-care, consulting a general practitioner (GP), or seeking urgent medical care [9]. By providing preliminary diagnostic guidance and triage recommendations, these tools could potentially alleviate some of the burdens on healthcare systems with the potential to reduce unnecessary healthcare visits by providing timely medical advice and empowering individuals to make informed decisions about their health [10, 11]. The diagnostic and triage accuracy have been found to vary greatly among OSCs, thus raising concerns and calling for caution [12, 13].
The use of OSCs globally varies as: users tend to be young [12, 13], women [6, 14, 15] and more highly educated [6, 14-16]. Having a chronic health condition has also been associated with greater use in one study [16]. A 2022 systematic review on user experience of symptom checkers identified eight relevant aspects of user experience that have been explored in the literature, including motivation, trust, acceptability, satisfaction, accuracy, usability, safety/security and functionality [17]. Of the 31 included studies only 3 were carried among the UK population [18-20] and focused either on cancer symptom checking [19], users with inflammatory arthritis [20] or the use of one specific OSC [18].
Data on the experience and perspectives of potential users living in the UK on the use of OSCs remains scarce and no study has yet quantified or ranked the various factors associated with the use of OSCs. Objective: The aim of this study was to identify, characterise and quantify the factors associated with the use of OSCs among community-dwelling adults in the UK. Specifically, we sought to (i) assess the demographic characteristics of OSC users, (ii) evaluate user perceptions of the usability and effectiveness of OSCs, (iii) identify concerns related to the privacy, security and accuracy of OSCs, and (iv) quantify the weight of these various factors on the adoption and utilisation of OSCs. Methods: Study design
This cross-sectional study aimed to explore factors influencing the use of OSCs among community-dwelling adults in the UK. The study employed a quantitative methodology using an electronic survey tool (eSurvey).
Data collection
This was an open eSurvey, accessible to anyone with the survey link, and required less than 10 minutes to complete. The eSurvey was developed and tested to ensure clarity, usability and technical functionality before fielding. The link to the eSurvey was active on the Imperial College Qualtrics platform between 23 February and 25 March 2024. Study information was disseminated including the Participant Information Sheet (PIS) and link to the survey. Participants were recruited through convenience sampling. The researcher’s personal and professional networks were mobilised to respond and further disseminate the eSurvey among potentially eligible participants. Most participants were recruited via Prolific Academic’s panel [21]. The PIS included information regarding the study’s aims, the protection of participants’ personal data, their right to withdraw from the study at any time, which data were stored, where and for how long, who the investigator was, the purpose of the study and survey length.
Participants were informed that this was a voluntary survey. Informed consent was obtained from all participants. Data collected were stored on a secure database at Imperial College London and only accessible to the researcher team. All responses were pseudo-anonymised to ensure confidentiality.
The selection of factors which may affect the use of OSCs to be included in the survey was guided by a review of existing literature of the topic. Demographic factors including age and gender, as well as perceptions such as perceived usability, effectiveness, reliability, accuracy, safety and privacy have been identified as influential factors from prior studies [6, 16-18, 20, 22].
Before publication, the survey was tested, piloted and revised internally by the study team. In its final version, the survey comprised a total of 25 questions displayed across four screens and gathered data regarding respondents’ awareness, use and perspectives regarding OSCs, as well as basic demographic information (Table 1).
Data analysis
Only questionnaires fully completed were included in the analysis. Duplicate entries from the same IP address within a 24-hour period were also eliminated before analysis. Participant characteristics and responses were summarised using total (n) and relative (%) frequencies. For inferential analyses, 'strongly agree' and 'somewhat agree' were categorised into 'agree,' and 'strongly disagree' and 'somewhat disagree' were categorised into 'disagree, to create binary variables for logistic regression analysis. Relationships between (i) demographic factors, (ii) usability and effectiveness, (iii) reliability and accuracy, (iv) risks and concerns and the use of OSC were assessed using univariable and multivariable logistic regression models, adjusting for age, gender, ethnicity, education level, parenting status, disability and long-term health conditions. Results were deemed statistically significant at a p-value <0.05. The odds ratios for these relationships were quantified to understand the influence of each factor on the use of OSCs and compare them.
All analyses were performed using STATA, version 17 (StataCorp LP, College Station, TX, USA). The Checklist for Reporting Results of Internet E Surveys (CHERRIES) was used to guide reporting [23] (Supplementary file 1). Results: Participants characteristics
A total of 641 individuals took part in the survey with complete responses obtained from 634 respondents. A full description of participants according to age, gender, ethnicity and educational background is provided in Table 2. The largest proportion were between 26 and 35 years old (32.7%), followed by participants aged 36-45 (24.6%). Gender distribution showed a slight predominance of females (46.5%) over males (41.8%), with a smaller percentage identifying as "other" (10.3%). Ethnicity predominantly comprised individuals identifying as White (84.2%), followed by Asian/Asian British (7.1%) and Black/African, Caribbean/Black, British (3.9%). The majority held a college or university degree (71.5%), nearly a third (31.5%) had children under 16 years, 15.1% of respondents reported having disabilities, and 22.9% had one or more long-term health conditions.
Main survey findings
Use of OSC
The majority (85.7%) of participants had used an OSC, while 14.4% reported never having used one. The reasons for non-use of OSC reported by the largest proportion (45.1%) was preference of consulting a healthcare professional directly rather than using OSC, followed by having never heard of them (39.6%); 24.2% of respondents did not trust them. However, two-thirds of the non-users (64.8%) expressed a likelihood of using a symptom checker in the future (Supplementary Table 1).
The most utilised OSC was NHS 111, with 78.6% of respondents indicating that they had used this tool, followed by Healthline (22%). Participants predominantly used symptom checkers before seeking medical advice (94.5%), primarily to better understand symptoms (79.0%) and to determine the need for medical care (77.4%).
Most respondents (77.9%) indicated that symptom checkers offered recommendations for action or triage. Among those who received such recommendations, a significant proportion (79.7%) were directed to seek a consultation with a healthcare professional. Regarding adherence, most participants (59.8%) reported following the recommendations most of the time, 27.7% stated they always adhered to the suggestions provided by the symptom checker, while a smaller proportion (12.3%) admitted to rarely doing so.
Association between demographics and use of OSC
An increase in age was associated with a decrease in OSC use. Specifically, individuals aged 46-55, 56-65 and >65 showed significantly decreased odds of using OSC (adjusted odds ratio (aOR)=0.29, 95%CI 0.11 - 0.72), (aOR=0.27, 95%CI 0.10 - 0.71) and (aOR=0.22, 95%CI 0.06 - 0.78) respectively, compared to the younger (18-25) age group. Similarly, females exhibited higher odds of using OSC compared to males (aOR=1.79, 95%CI 1.05 – 3.06). Having children under 16 years of age also showed significantly higher odds of using OSC (aOR= 3.19, 95%CI 1.56 - 6.51) compared to those who do not have children under 16 years of age. In contrast, neither ethnicity nor educational background exhibited any statistically significant association with the use of OSC. Similarly, disability and long-term health conditions did not contribute to the outcome of using OSC; Table 3.
Associations between OSC use & users’ perceptions of OSCs
The main survey findings are shown in Supplementary Table 1. The segment below highlights key associations between perceived usability and effectiveness, reliability and accuracy, and risks and concerns with using OSCs
Perceived usability and usefulness and use of OSCs
Most of the participants found OSCs easy to use (89.3%), believed they could help with medical decisions (86.0%) and to support their health literacy and self-care (84.7%). A great proportion also (94.6%) agreed that OSCs are useful tools in scenarios with limited access to healthcare professionals, such as rural settings or out-of-hours situations.
Participants who found the symptom checkers easy to use were more than eight times more likely to utilise them compared to those who did not (aOR=8.17, 95% CI 4.25-15.71). Similarly, individuals who found these tools helpful in making better medical care choices were almost three times more likely to use them than those who did not (aOR=2.96, 95% CI 1.62-5.42). Moreover, those who agreed that the symptom checkers improved health literacy and supported self-care showed a heightened likelihood of use (aOR=2.36, 95% CI 1.30-4.28). Participants who perceived the OSC as useful in scenarios with limited access to healthcare professionals were twice as likely to utilise them compared to those who disagreed (aOR=2.15, 95% CI 1.01-4.59); Table 3.
Perceived reliability and accuracy and use of OSCs
Just over half of the respondents expressed confidence and trust in OSCs’ information (57.3%). The perceived accuracy of OSCs’ diagnosis was slightly higher (63.0%) while 79.2% of respondents said they trusted the triage provided by the tools. 69.2% of respondents found using a symptom checker reassuring and made them feel less anxious about their health.
Participants who trusted the suggested diagnosis to be accurate were over twice as likely to use the symptom checkers compared to those who disagreed (aOR=2.24, 95%CI 1.32-3.79). Similarly, individuals who trusted the triage recommendation provided by these tools showed a heightened likelihood of use (aOR=2.33, 95% CI 1.33-4.06). Participants who found using symptom checkers reassuring and anxiety-reducing were significantly more likely to utilise them (aOR=3.85, 95% CI 2.28-6.50). Additionally, the encouragement from family and friends to use symptom checkers significantly influenced their use (aOR=2.05, 95%CI 1.24-3.41). However, encouragement from GPs was not significantly associated with the use of symptom checkers (aOR=1.34, 95%CI 0.79-2.24); Table 4.
Perceived risks and concerns and use of OSCs
Reported concerns included safety (75.9%), privacy (41.7%) and exacerbating inequalities (41.6%). More than half of the respondents (65.9%) worried about replacing traditional consultations and more than a quarter (26.9%) would not feel confident discussing the outcomes of their symptom checker consultation with their GP.
Participants who agreed that symptom checkers are not yet safe enough to rely solely on them and may put their health at risk did not show a significant association with use compared to those who disagreed (aOR=0.59, 95% CI 0.30-1.17). However, concerns regarding privacy and health information security were significantly inversely associated with use, with individuals expressing such worries being less likely to utilise symptom checkers (aOR=0.58, 95% CI 0.35-0.97). Similarly, those who believed that symptom checkers might increase inequalities between patients were less likely to use them (aOR=0.47, 95% CI 0.28-0.79). Concern about OSCs replacing face-to-face or phone consultations was significantly associated with decreased use (aOR=0.47, 95% CI 0.26-0.87); Table 5.
Figure 1 represents the weight of each factor on the use of OSCs. The main factor that significantly increased the probability of using OSCs was the tools’ ease of use (aOR=8.17, 95% CI 4.25-15.71). This was followed by feeling reassured by using the tool and having children. Users of OSCs also usually thought of OSCs as improving their healthcare choices, their health literacy and self-care capacity. Encouragement from friends and family limited healthcare access, better. being female. and trust in the triage and diagnostic accuracy.
Demographic factors associated with a decreased odd of using OSCs included male gender and older age. Concerns regarding privacy and data security, as well as the risk of increased inequalities and loss of face-to-face consultations due to OSCs were also identified as reducing the likelihood of using these tools. Conclusions: Principal results
This study investigated the factors influencing the use of OSC in the UK through a cross-sectional survey of community dwelling adults. Among the key findings, we observed that most participants (86%) had used a symptom checker at some point, with the NHS 111 platform being the most widely used (79%), followed by Healthline (22%). These tools were predominantly employed before seeking medical advice (95%) primarily to better understand symptoms and to determine the need for care. Interestingly, while most OSC non-users expressed a strong likelihood of future use, we observed varying concerns regarding the accuracy of information, safety, privacy and potential increase of inequalities.
Older individuals (aged between 46-55, 56-65 and older than 65) showed significantly decreased odds of using OSC compared to the 18-25 age group independently from other variables. However, females exhibited higher odds of utilising these tools compared to males, and individuals with children under 16 years of age were more than three times more likely to use OSC compared to those who did not have children. Further, although trust in the accuracy of diagnoses and triage recommendations, as well as encouragement from family and friends, positively influenced use, concerns regarding privacy, health information security, inequalities and the potential displacement of traditional consultations were significantly associated with decreased use (Figure 1). No significant associations were found between the use of OSCs and encouragement from GPs to use these tools, concerns about the safety of relying solely on symptom checkers nor potential health risks.
Study strengths and limitations
This study examined a wide range of variables, including demographics, motivations, perceived effectiveness, reliability and concerns regarding OSC and associations with their use providing valuable insights into the complexities surrounding the wide scale adoption and diffusion of these tools in the contemporary setting. While supporting existing evidence on this topic, we identified additional factors associated with the use of OSCs, including the perceived family and friends support as well as having children. By employing regression models, we were also able to quantify the associations between the use of OSCs and a variety of factors, including both demographic factors and respondents’ perceptions regarding the usability, safety, accuracy and concerns associated with OSCs. Crucially, we identified significant predictors of use while controlling for potential confounders and enhancing the internal validity.
This study's large, diverse and representative sample closely reflects the ethnic distribution of the UK population [24], which enhances the generalisability of the findings.
However, this study is also has several limitations. Firstly, cross-sectional studies cannot establish causality and temporal relationships between the factors examined. Secondly, since the survey was only accessible online, it is likely that potentially eligible participants with limited access to internet and / or those less confident with digital technology were excluded and their views absent or at least under-reported. Lastly, this study relies on self-reported data, which may be subject to recall and social desirability biases. Participants' responses regarding their use patterns, preferences and adherence to recommendations may therefore not fully reflect their actual behaviours. Longitudinal studies are indicated to follow-up users over a longer time horizon to better understand how their interactions with OSC evolve and how it influences their health behaviours, healthcare utilisation and health outcomes.
Comparison with existing literature
The findings of this study are in line with prior research, including primary studies and reviews reporting on the socio-demographics of OSC users who tend to be young [6, 14, 15], women [6, 14-16] and with higher education levels [6, 14, 16]. Although having a chronic health condition or a disability was associated with greater use in a study by Meyer et al. [16], we did not find this association in this study’s sample. Regarding the motivations for using OSCs, a better understanding of the causes of symptoms has also been found to be the primary motivation among US users of the Isabel Symptom Checker [16], followed by support for deciding whether to seek care.
The finding that users of OSCs tend to find these tools easy to use and helpful was corroborated by Meyer et al. [16] and Pairon et al. [6]. The strong correlation identified in this study highlights the importance of user-friendly interfaces in promoting the adoption of OSCs. The review by Pairon et al. [6] also emphasized that users value OSCs for their ability to support health-related decisions, especially in determining whether to seek medical care. The results of this study reinforce this by showing that individuals who perceived OSCs as helpful in making better medical care choices were nearly three times more likely to use them.
Compliance with OSC recommendations has also been a point of focus in the literature. Previous studies reported varying levels of adherence to OSC advice, with compliance rates ranging from 57% to 67% [6], whereas this study reports a higher compliance rate, with 87.5% of participants following OSC recommendations most or all of the time. This higher rate of adherence may reflect an increasing reliance on digital health tools, particularly in the context of the COVID-19 pandemic which has accelerated the adoption of telemedicine and online health resources. Further research is needed to continue monitoring these trends and to explore the long-term impact of OSC use on healthcare outcomes.
Finally, issues relating to perceived accessibility, accuracy, security and privacy of OSCs were also identified by Aboueid et al. [22] in their qualitative study exploring young adults’ perspectives on the use of OSCs. Most of their respondents thought of OSCs as more useful to self-triage than self-diagnosis, which reflects the fact that only 63% of the respondents in this study trusted the diagnosis provided by the OSC, compared to 79.2% for the triage suggestion.
Implications for research
Although this study identified demographic disparities in the use of OSCs, further research is warranted to understand the underlying reasons for these disparities. Research focusing on the socio-cultural factors, digital literacy and healthcare-seeking behaviours among different demographic groups could provide valuable insights into addressing disparities and promoting equitable access to OSC. In addition, this study’s findings highlight the importance of usability, effectiveness and trust in driving the adoption and utilisation of OSCs. Future research could investigate deeper into the specific features and functionalities of these tools, such as user interface design and decision support algorithms that contribute to their perceived usability, effectiveness and adherence to the recommendations.
This study highlighted concerns regarding the privacy and health information security of OSC, which could impact their acceptance and use, necessitating the development of robust frameworks, regulatory standards and guidelines for OSC platforms to ensure transparency, accuracy and user privacy. Additionally, studies investigating the potential implications of OSC on healthcare inequalities and the doctor-patient relationship are essential for informing policy and practice, whereas research exploring effective strategies for educating users about the capabilities and limitations of these tools, as well as enhancing communication and collaboration between users and healthcare providers, could help build trust and confidence in OSC.
Future research should focus on understanding the socio-cultural factors influencing OSC use and developing strategies to address privacy and security concerns. Additionally, efforts to improve the usability and reliability of OSCs, alongside targeted interventions to promote equitable access, are essential for integrating these tools effectively into the healthcare system. By addressing these issues, OSCs can play a key role in supporting self-care and improving healthcare accessibility and efficiency in the UK.
Conclusion
This study provides insights into the factors influencing the use of OSCs in the UK, highlighting both their increasing and widespread adoption and some of the concerns associated with these digital health tools. The findings indicate that most adults have used OSCs, particularly the NHS 111 service, primarily for understanding symptoms and determining the need for medical care, and that younger individuals, females and those with children are more likely to use OSCs overall. Ease of use, perceived helpfulness in medical decision-making, and trust in the accuracy of diagnoses and triage recommendations are key factors driving OSC use, but these are coupled to concerns about privacy, health information security and the potential for OSCs to exacerbate healthcare inequalities, posing significant barriers to their adoption. The fear of OSCs replacing traditional consultations with healthcare professionals remains common among users, and these concerns must be addressed to enhance user trust and maximize the benefits of OSCs in healthcare delivery.
Background: Many healthcare systems confront considerable strain attributable to an escalating prevalence of older adults living longer leading to an increased number of people with chronic conditions...
Background: Many healthcare systems confront considerable strain attributable to an escalating prevalence of older adults living longer leading to an increased number of people with chronic conditions. Concomitantly the numbers of trained professionals in the healthcare workforce is not keeping up with the increased numbers of people with chronic conditions. In this context, increased digitalization is considered one way to mitigate many of the challenges, but it remains to be documented whether this is of benefit to COPD patients. The Epital Care Model (ECM) constitutes a proactive and data-centric treatment paradigm that leverages patient-reported outcome data and 24/7 telehealth service to facilitate early detection of deteriorating conditions among patients with chronic diseases (1). This approach aims to reduce and address exacerbations early, thereby averting the need for extensive and resource-intensive interventions. It is noteworthy that the Epital frontline service is delivered by trained and certified staff consisting of students from health educations and not by health care professionals. Objective: This clinical controlled trial was conducted to investigate the impact of the virtual component of the ECM framework in COPD on healthcare resource utilization and participants mental wellbeing and social activities. Methods: A pragmatic step-wedged design was employed, involving the random allocation of 184 patients into either an intervention group (n=92) or a control group (n=92), with equitable distribution across four general practice clinics in Denmark. Participants were examined at an 8-month (T1) follow-up and 12-month (T2) follow-up. Healthcare service utilisation and participants’ social activity were assessed and compared using Poisson regression. Mental wellbeing was assessed by comparing the scores on the WHO-5 wellbeing index using an unpaired t-test. Results: A significant reduction of healthcare utilization associated with COPD was found in the intervention group at T2, with reduced hospital admissions (56%), general practitioner visits (78%), on-call doctor consultations (73%), emergency room visits (49% reduction), and outpatient attendances (60% reduction) compared to the control group. Further, there was a significant increase in social activities (p< 0.01) and travel activities abroad (p< 0.01) at T2 in the intervention group, but no difference was found in well-being (WHO-5 index) between the two groups Conclusions: The study highlights the value of the ECM virtual care model in COPD management, offering a potential solution to healthcare workforce shortages and resource constraints as it leads to both a significantly reduced use of healthcare services and at the same time introduces a new kind of workforce to complement the existing workforce. Further research using this model in other chronic conditions and other healthcare systems is warranted based on these findings. Clinical Trial: No trial registration has been performed. The protocol is available from: https://epital.com/temokap-protokol-2/
Background: Health anxiety (HA) by proxy is characterized by ruminations about severe illness in one's child. Although HA by proxy can cause severe distress in affected parents, no targeted treatment...
Background: Health anxiety (HA) by proxy is characterized by ruminations about severe illness in one's child. Although HA by proxy can cause severe distress in affected parents, no targeted treatment has previously been evaluated. Objective: The aim of this study was to investigate the feasibility and effect of the internet-delivered treatment PROXY for parents with HA by proxy. Methods: Four participants with HA by proxy entered a replicated randomized single-case experimental design. They were randomly allocated to a baseline period of 7-26 days before entering the eight-week treatment. The primary outcome was daily measures of anxiety, impact of anxiety and value-based actions analyzed using visual analysis, and supplemented with statistical analyses. Secondary outcomes were measures of anxiety-related symptoms, experience of the treatment and negative events. Results: Visual analysis indicated that PROXY could be an effective treatment for two participants. All par-ticipants were happy about the treatment but two participants experienced that HA for their own health deteriorated during treatment, and two participants thought the treatment was too short. Conclusions: could hold potential as a treatment for HA by proxy. However, more work is required in relation to when and how PROXY should be introduced to parents with HA by proxy. Clinical Trial: ClinicalTrials.gov NCT04830605
Background: The rise of e-health systems, including electronic health records (EHRs), telemedicine platforms, and mobile health applications, has revolutionized healthcare delivery by improving access...
Background: The rise of e-health systems, including electronic health records (EHRs), telemedicine platforms, and mobile health applications, has revolutionized healthcare delivery by improving access, efficiency, and quality of care. However, the increasing reliance on digital platforms has raised significant concerns regarding the privacy and security of personal health information. Objective: This study aims to provide a thorough examination of the privacy issues associated with e-health systems. It seeks to identify and analyze key privacy risks, evaluate current privacy protection measures, discuss their limitations, and suggest potential areas for future research. Methods: We conducted a comprehensive review of the literature on privacy issues in e-health systems. The review included an analysis of current data protection methods, privacy regulations, informed consent practices, and emerging technologies such as blockchain and privacy-preserving algorithms. We also evaluated recent studies on privacy breaches and their impacts on individuals and healthcare systems. Results: Our review identified several critical privacy concerns, including unauthorized data access, data breaches, and inadequate encryption. Current solutions, such as encryption and access controls, have limitations, including insufficient protection and challenges in balancing data utility with privacy. We also observed gaps in compliance with privacy regulations and the need for more robust privacy-preserving technologies. Conclusions: Ensuring the privacy of personal health information in e-health systems is crucial for maintaining public trust and enabling the effective use of digital health technologies. While current measures offer some protection, there is a need for improved privacy solutions and stronger compliance with regulations. Future research should focus on developing advanced privacy-preserving technologies, exploring federated learning models, and addressing ethical concerns related to AI in healthcare. Collaborative efforts among stakeholders are essential for advancing privacy protections and optimizing the benefits of e-health systems.
Background: Patient-Generated Health Data (PGHD) has been recognized as a potential tool in transforming healthcare from clinician-centered to more patient-centered approaches. This transformation is...
Background: Patient-Generated Health Data (PGHD) has been recognized as a potential tool in transforming healthcare from clinician-centered to more patient-centered approaches. This transformation is driven by the potential of PGHD to provide deeper insights into patients' conditions, facilitate personalized care, improve patient quality of life, reduce inefficiencies in data collection, and empower patients. Yet, actual implementation within clinical settings is still at early stages, and therefore impacts on clinical care remain limited. Objective: This study sought to explore the benefits, challenges, and opportunities of integrating PGHD into orthopaedic care by analyzing the reflections of early adopter surgeons and physiotherapists, who have used a digital care management platform. Methods: This qualitative study employed thematic analysis of interviews conducted with surgeons and physiotherapists (n=9) from an early adopter unit using "mymobility" an industry produced software platform. The participants were recruited using snowball sampling, and interviews were conducted from June to July 2022. The interviews focused on current work practices, use of digital tools, experiences with PGHD, and experiences with the mymobility software. Thematic analysis was conducted using NVivo software, focusing on identifying key themes and insights Results: The study identified several benefits of integrating PGHD into orthopaedic care, including improved patient education, enhanced communication and assessment, and increased patient motivation and adherence. However, several challenges were also noted, such as increased clinician workload, questionable data utility, lack of patient centricity, and inability to tailor software to clinical contexts. Suggested opportunities included improving dashboard design, personalizing physiotherapy, and using collected data for improving clinical care. Conclusions: The integration of PGHD into orthopaedic care shows promise, largely in areas suggested by literature. However, significant challenges remain. Future research should focus on addressing solvable challenges such as improving software user interface design and functionality, while embracing the possibility that some challenges lack clear solutions and will likely require careful balancing of design tensions. The findings highlight the need for ongoing development and refinement of PGHD-inclusive systems to better support clinical practice and patient outcomes.
Background: Individuals of childbearing age enter pregnancy less healthy than previous generations, placing them at increased risk for pregnancy complications. One approach to ensuring effective monit...
Background: Individuals of childbearing age enter pregnancy less healthy than previous generations, placing them at increased risk for pregnancy complications. One approach to ensuring effective monitoring and treatment of at-risk pregnant/birthing people is designing technology-based interventions that prevent maternal morbidities and treat perinatal conditions. Objective: This scoping review evaluates what informatics interventions have been designed and tested to prevent and treat maternal morbidity. Methods: MEDLINE, EMBASE, and Cochrane Library were searched to identify relevant studies. Inclusion criteria were: (a) tested a medical or clinical informatics intervention; (b) enrolled pregnant/birthing people; and (c) addressed preeclampsia, gestational diabetes mellitus (GDM), preterm birth, CDC-defined severe maternal morbidity, or perinatal mental health conditions. Demographic, population, and intervention data were extracted to characterize the technologies, conditions, and populations addressed. Results: 80 studies were identified that met inclusion criteria. Of these, 73% tested technologies for either GDM or perinatal mental health conditions, and 15% tested technologies for preeclampsia. For technology, 32% of the technologies tested were smartphone or tablet application, 26% were telehealth interventions, and 15% were remote monitoring technologies. Most (79%) studies assessed patient physical or mental health outcomes. Conclusions: Per this scoping review, most informatics interventions address three conditions: GDM, preeclampsia, and mental health. There may be opportunities to treat other potentially lethal conditions like postpartum hemorrhage using proven technologies such as mobile applications. Ample gaps in the literature exist concerning the use of informatics technologies aimed at maternal morbidity. There may therefore be opportunities to use informatics for lesser-targeted conditions and populations.
Background: Disease-modifying therapies ameliorate disease severity of sickle cell disease (SCD), but hematopoietic cell transplantation (HCT) and more recently autologous gene therapy are the only tr...
Background: Disease-modifying therapies ameliorate disease severity of sickle cell disease (SCD), but hematopoietic cell transplantation (HCT) and more recently autologous gene therapy are the only treatments that have curative potential for sickle cell disease (SCD). While registry-based studies provide population-level estimates they do not address the uncertainty regarding individual outcomes of HCT. Computational machine learning (ML) has the potential to identify generalizable predictive patterns and quantify uncertainty in estimates thereby improving clinical decision-making. There is no existing ML Model for SCD and ML models for HCT for other diseases focus on single outcomes rather than all relevant outcomes. Objective: Address the existing knowledge gap by developing, and validating an individualized ML-prediction model, sickle cell predicting outcomes of hematopoietic cell transplantation (SPRIGHT), incorporating multiple relevant pre-HCT features to make predictions of key post-HCT clinical outcomes. Methods: We applied a supervised random forest ML model to clinical parameters in a de-identified CIBMTR dataset of 1641 patients who underwent HCT 1991-2021 and followed for a median of 47.8 months (0.3-312.9). We applied forward and reverse feature selection methods to optimize a set of predictive variables. To counter the imbalance bias towards predicting positive outcomes due to the small number of negative outcomes we constructed a training dataset taking each outcome variable of interest, and performed a two-times repeated 10-fold Cross-Validation. SPRIGHT a web-based individualized prediction tool accessible by smartphone, tablet, or personal computer. It incorporates predictive variables of age, age group, Karnofsky/Lansky score, co-morbidity index, recipient CMV seropositivity, history of ACS, need for exchange transfusion, occurrence and frequency of vasocclusive crisis (VOC) before HCT, and either a published or custom chemotherapy/radiation conditioning, serotherapy, and GVHD prophylaxis. SPRIGHT makes individualized predictions of overall survival (OS), Event Free Survival (EFS), Graft Failure (GF), acute graft versus host disease (AGVHD), chronic graft versus host disease (CGVHD), occurrence of VOC or stroke post-HCT. Results: A web-based ML- prediction tool predicts key outcomes of HCT for SCD based on multiple clinically relevant predictors and has potential use in shared decision-making. Conclusions: A web-based ML- -prediction tool predicts key outcomes of HCT for SCD based on multiple clinically relevant predictors and has potential use in shared decision-making. Clinical Trial: Not Applicable. This is not a clinical trial
Background: Medication non-adherence is a serious problem in cancer with potential impact on patients’ health outcomes and healthcare costs. Technology-based medication adherence (MA) interventions...
Background: Medication non-adherence is a serious problem in cancer with potential impact on patients’ health outcomes and healthcare costs. Technology-based medication adherence (MA) interventions are increasingly introduced, yet their evidence of quality and effectiveness is poor. Objective: This study aimed to test the acceptability, feasibility, and potential effects of SAMSON, a digital solution designed to support MA and self-management in cancer. Methods: This was a two-arm, unblinded, 12-week, pragmatic pilot randomized controlled trial (RCT). Adults who started oral cancer medicines for haematological malignancies within the last 12 months were recruited from a metropolitan specialised hospital. Participants were randomized 1:1 to either the SAMSON solution or the control arm to receive usual care. The SAMSON solution included a smartphone app which allows prompting individually tailored phone alerts and real-time self-care advice, a web-based dashboard for healthcare professionals (HCPs) to monitor patients’ adherence and symptoms, alongside motivational interviewing (MI) teleconsultations delivered by oncology nurses and pharmacists scheduled after recruitment and at weeks 1, 4, 8 and 12, to support patient adherence and side-effect self-management. Primary outcomes were the patients’ acceptance of SAMSON, measured by the Unified Theory of Acceptance and Use of Technology at 12 weeks, and study feasibility, measured by predefined rates of recruitment, randomization, retention, intervention adherence and outcome assessment completion. Secondary outcomes were comparison of MA and clinical self-assessments through online questionnaires, including adherence, toxicity self-management, anxiety-depression-and symptoms, and quality of life, measured at baseline and 12 weeks between the two arms. Data retrieved from the SAMSON app on the tasks completed by patients were used for analysis. Results: Thirty-three patients (78.6% of those who were approached) consented to participate in the trial. Of those, 31 (93.7%) completed baseline surveys and were randomised to SAMSON (n=15) and control arms (n=16). Twenty-eight patients (90.3%) completed week-12 surveys (12 SAMSON and 16 control). Overall, patients rated SAMSON solution as highly acceptable (13/15; 86.7% app usage and 14/15; 93.3% MI teleconsultation delivery). They reported that SAMSON was easy-to-use (10/12; 83.3%) and helpful in improving their MA (6/12; 50%). All study HCPs reported the SAMSON solution was helpful in supporting patients’ MA. Patients completed an average of 99 tasks over the 12-week study period (70.7% of scheduled tasks). Most patients (10/12; 83.3%) completed all five scheduled consultations. All study feasibility measures were higher than the predefined upper thresholds, except the rate of patients’ responses to medication reminders. Conclusions: The results demonstrated that the SAMSON solution is acceptable, usable, and useful for oncology HCPs and patients with cancer. The SAMSON solution is feasible in real-life oncology settings. Our next steps involve refining SAMSON solution based on participants’ feedback, conducting a large-scale RCT to evaluate its clinical and economic effectiveness, and exploring potential commercialisation. Clinical Trial: ACTRN12623000472673
Background: In Quebec, the shortage of nurses during night shifts compromises the safety and quality of resident care, especially in small residential and long-term care centres (CHSLDs) located in se...
Background: In Quebec, the shortage of nurses during night shifts compromises the safety and quality of resident care, especially in small residential and long-term care centres (CHSLDs) located in semi-remote or remote areas. This situation, which is exacerbated by the current overall shortage, exacerbates nurse staffing problems in these facilities. The need to ensure the continuous presence of nurses 24 hours a day in CHSLDs has become more pressing, forcing some facilities to implement exceptional measures such as on-call telephone services to ensure access to a nurse. In light of these challenging circumstances, the Direction nationale des soins et des services infirmiers (DNSSI) of Quebec’s Ministère de la Santé et des Services sociaux (MSSS) has rolled out a teleconsultation pilot project. Objective: This study aimed to explore nurses’ and nursing assistants’ lived experience of the integration of teleconsultation during night shifts in rural CHSLDs with fewer than 50 residents. Methods: The six-month pilot project was rolled out sequentially in three rural CHSLDs located in two administrative regions of Quebec, between July 2022 and March 2023. A total of 16 semi-structured interviews were conducted with eight nurses and nursing assistants between February and July 2023. Results: Participants’ testimonials revealed that teleconsultation provided significant added value by improving clinical, administrative, and organizational practices. Some practices remained unchanged, indicating stable workflows. Workflow optimization through an expanded scope of practice ensured efficient and safe continuity of care. Enhanced collaboration between nurses and nursing assistants led to improved care coordination and communication. Leadership played a significant role in clarifying professionals’ roles and in supporting effective adaptation to teleconsultation. Conclusions: This pilot project represents a significant step forward in improving care for CHSLD residents in Quebec. Teleconsultation not only makes it possible to overcome recruitment challenges and ensure the continuous presence of nurses during night shifts, it also optimizes professional practices while ensuring the safety and quality of care provided to residents.
Background: Smartphone applications (apps) can be used to monitor chronic conditions and offer opportunities for self-assessment conveniently at home. However, few digital studies include older adults...
Background: Smartphone applications (apps) can be used to monitor chronic conditions and offer opportunities for self-assessment conveniently at home. However, few digital studies include older adults. Objective: To describe a new electronic cohort (eCohort) of older adults embedded in the Framingham Heart Study (FHS) including baseline smartphone survey return rates and survey completion rates by smartphone type (iPhone and Android users). To report survey results for selected baseline surveys and participant experience with the study app. Methods: FHS Offspring and Omni (multi-ethnic cohort) participants who owned a smartphone were invited to download the study app that contained a range of survey types to report on different aspects of health including self-reported measures from the Patient-Reported Outcomes Measurement Information System (PROMIS). iPhone users also completed four cognitive and physical function testing tasks. Baseline survey return and completion rates were calculated for 12 surveys and compared between iPhone and Android users. We calculated standardized scores for the PROMIS surveys. The Mobile App Rating Survey (MARS) was deployed 30 days after enrollment to obtain participant feedback on app functionality and aesthetics. Results: We enrolled 611 smartphone users (average age 73.6±6.3 years, 56.6% women, 14.4% Omni participants, 77% iPhone users) and 596 (97.5%) returned at least one baseline survey. iPhone users had higher app survey return rates than Android users for each survey (range 85.5 to 98.3% vs 73.8 to 95.2% respectively), but survey completion rates did not differ in the two smartphone groups. The return rate for the four iPhone tasks ranged from 80.9% for the Gait task to 88.9% for the Trail Making Test task. The eFHS participants had better standardized T-scores in six of seven PROMIS surveys compared to the general population mean (T-score =50) including higher cognitive function (55.6) and lower fatigue (45.5). Among 469 participants who returned the MARS survey, app functionality and aesthetics was rated high (total MARS score = 8.6 on a 1-10 scale). Conclusions: We effectively engaged community-dwelling older adults to use a smartphone app designed to collect health information relevant to older adults. High app survey return rates and very high app survey completion rates were observed along with high participant rating of the study app.
Background: People living with dementia are at risk of getting lost and going missing due to memory loss, confusion, and disorientation. Missing incidents involving people living with dementia are inc...
Background: People living with dementia are at risk of getting lost and going missing due to memory loss, confusion, and disorientation. Missing incidents involving people living with dementia are increasing. Alert systems such as Community ASAP can promote community engagement in locating missing persons with dementia and aid search and rescue efforts. However, implications of public disclosure of personal information such as name, age, sex, and physical descriptions within such alert systems have yet to be explored. Objective: This study aimed to identify and discuss the implications of public disclosure of personal information in Community ASAP for people living with dementia at risk of going missing. Methods: This study used a qualitative descriptive research design drawing from naturalistic inquiry. Nineteen participants including people living with dementia, care partners, and service providers were recruited from Ontario, Alberta, and British Columbia, Canada. Semi-structured interviews were used to explore participants’ perspectives on the perceived implications of the release of personal information when using Community ASAP. NVivo 12 was used to manage data and conventional content analysis conducted to identify key themes of the implications of public disclosure of personal information in Community ASAP. Results: Participants were 10 females and 9 males. Three were people living with dementia, five were care partners, four were first responders, and seven were service providers. Four key themes were identified as implications of public disclosure of personal information in Community ASAP: Right to autonomy, safety versus privacy, informed and knowledgeable consent, and stigmatization. Participants discussed how the public disclosure of personal information in Community ASAP could undermine a person’s choice not to be found and contribute to stigmatization. Participants emphasized a need to balance safety and privacy concerns. Informed and knowledgeable consent is important when using an alert system to locate missing persons with dementia. Conclusions: Community ASAP can promote community engagement in locating missing persons with dementia. However, the public disclosure of personal information in alert systems has implications. Users’ right to autonomy, a balance between safety and privacy, informed and knowledgeable consent, and risks for stigmatization are perceived impacts of disclosure of personal information in alert systems.
Background: Mobile Health (mHealth), which refers to health care facilitated by mobile devices, offers a promising strategy for enhancing disease management and treatment for patients with chronic con...
Background: Mobile Health (mHealth), which refers to health care facilitated by mobile devices, offers a promising strategy for enhancing disease management and treatment for patients with chronic conditions. However, there is limited information on how patients with inflammatory bowel disease (IBD) utilize mHealth and their digital preferences. Objective: The aim of the study was to investigate the utilization of mHealth, as well as the preferences, obstacles, and eHealth literacy as reported by patients with IBD in Germany. Methods: From April to May 2023, we sequentially enrolled patients diagnosed with inflammatory bowel disease, such as Crohn´s disease and ulcerative colitis, to participate in a paper-based survey. The survey encompassed inquiries covering sociodemographic details, health characteristics, mHealth utilization, internet usage, eHealth literacy measured through the eHealth Literacy Scale (eHEALS), and preferences related to communication and information. Results: Out of the 200 surveyed participants, almost all individuals (197/200, 98.5%) reported regular smartphone usage, and more than half indicated regular engagement with social media (139/200, 69.5%). Most respondents (168/200, 84.0%) expressed the belief that incorporating medical apps into their routine could positively impact their health. However, only 25 out of 200 patients (12.5%) acknowledged using medical apps, amongst which only two apps were IBD-specific, used by 3 out of 25 participants (12.0%). Furthermore, awareness of useful websites or mobile applications specifically tailored for IBD was limited (45/200, 22.5%). An overwhelming majority of participants (196/200, 98.0%) affirmed their willingness to share data from mobile apps for research purposes. Consent to the transmission of app data to treating physicians was also high (171/200, 85.5%). Most patients (175/200, 87.5%) conveyed a readiness to regularly input data through an application with a preferred duration of up to 5 minutes (109/200, 54.5%) and a frequency of weekly input (76/200, 38.0%). Regarding functions for an IBD-specific app, participants’ most frequent requests were related to electronic prescription (55.0%) and a newsletter about new scientific work and clinical studies (47.0%). Favored key attributes of an app were usability and security. When seeking health-related information, the internet emerged as the predominant source (180/200, 90%). The average eHealth literacy was reported to be high (28.9/40), with a positive correlation observed between higher eHealth literacy and factors such as younger age and more frequent internet usage to receive health information. Conclusions: Patients with IBD are well-qualified and motivated to use mHealth technologies to better understand their chronic condition and optimize their treatment. However, their enthusiasm is curbed by the low actual adoption of mHealth. To fully harness the potential of mHealth in IBD treatment, effective and tailored mHealth solutions, implementation recommendations, and patient education are needed.
Background: Reducing greenhouse gas emissions is a priority that must be addressed to prevent the negative impacts of climate change. Inhalational anesthetic agents are a major source of potent greenh...
Background: Reducing greenhouse gas emissions is a priority that must be addressed to prevent the negative impacts of climate change. Inhalational anesthetic agents are a major source of potent greenhouse gases, and reducing their emissions is a goal that can be readily addressed. Nitrous oxide (N2O) has a prolonged environmental half-life combined with a low clinical potency, leading to relatively large amounts of N2O being stored in cryogenic tanks and H cylinders for use, thus increasing the chance of pollution through leaks. Building on the results of previous studies, Stanford Health Care (SHC) N2O emissions were analyzed at two campuses and targeted for waste reduction as a precursor to system wide reductions. Objective: To determine the extent of N2O pollution at SHC. Subsequently, to determine if using E-cylinders for storage and delivery of N2O at the point of care in its ambulatory surgery centers could reduce emissions within SHC’s system. Methods: Phase 1: Total Palo Alto, CA SHC N2O purchase data for CY2022 was collected and compared (volume and cost) to total Palo Alto clinical delivery data using Epic electronic health record.
Phase 2: A pilot study was conducted in the 8 operating rooms of SHC campus A (Redwood City). The central N2O pipelines were disconnected, and E-cylinders were used in each operating room. E-cylinders were weighed before and after use on a weekly basis for comparison to Epic N2O delivery data over a 5-week period.
Phase 3: After successful implementation, the same methodology was applied to Campus B, one of three facilities in Palo Alto. Results: Phase 1: Total N2O purchased in 2022 was 8,217,449 liters (33,201.8 lbs.), at a total cost of $63,298. Of this, only 780,882.2 liters (9.5%) of N2O was delivered to patients, with 7,436,566.8 liters (90.5%) or $57,285 worth lost or wasted.
Phase 2: Total weight of N2O use from E-cylinders was 7.4 lbs (1lb N2O = 247.5L) or 1,831.5 liters at campus A. Epic data showed total N2O volume delivered was 1,839.3 liters (7.4 lbs).
Phase 3: Total weight of N2O use from E-cylinders was 10.4 lbs or 2,574 Liters at campus B (confirming reliability within error propagation margins). Epic data showed total N2O volume delivered was 2840.3 liters (11.5 lbs).
Over Phase 2 and 3, total use for campuses A and B was less than the volume of 3 E-cylinders (1 E-cylinder = 1590 liters). Conclusions: Converting N2O delivery from centralized storage to point-of-care E-cylinders dramatically reduced waste and expense with no detriment to patient care. The results of this study provide strong evidence for analyzing N2O storage in healthcare systems that rely on centralized storage as well as consideration of E-cylinder implementation to reduce emissions. The reduction in N2O waste will help meet SHC’s goal of Scope 1 and 2 emissions reduction by 50% before 2030.
Background: Virtual reality (VR) is increasingly utilized in healthcare training and assessment, offering immersive experiences through head-mounted displays. Compared to traditional Objective Structu...
Background: Virtual reality (VR) is increasingly utilized in healthcare training and assessment, offering immersive experiences through head-mounted displays. Compared to traditional Objective Structured Clinical Examinations (OSCEs), which are costly and may be burdensome, VR could provide an attractive alternative by recreating scenarios and presenting pathological findings through virtual patients (VPs). VR also enables scalability, standardization, and potential automation of checklist completion, alleviating the cognitive load on examiners. Objective: The study aims to explore the use of a VR OSCE station and compare it to a traditional on-campus OSCE station in undergraduate medical education. It investigates how students perceive workload, fairness, and realism, and compares student performance between the two types of stations. Additionally, the study examines the item and scale analysis of checklist items, the VR-related side effects experienced by students, and their evaluation of the VR station's usability and acceptance. Finally, it identifies the technical challenges involved in conducting and evaluating a VR OSCE station. Methods: This quasi-experimental comparison study is conducted at the University of Bern, comparing a traditional OSCE case with a corresponding VR OSCE case. To assess workload, fairness, realism, VR-related side effects, technology acceptance, and usability, we use validated questionnaires. The official exam checklist is used to compare student performance in both the VR and traditional cases. Additionally, technical challenges encountered during the VR OSCE are documented. Results: Study recruitment and data collection on the traditional OSCE began in April 2024. The VR OSCE will be conducted in the summer of 2024. Conclusions: This study will compare a traditional OSCE with a VR OSCE to assess feasibility, workload, performance, realism, and fairness, ultimately providing insights for the potential integration of VR OSCE into high stakes assessments.
Background: Involving people with lived experience (PLE) in medical education, which may occur with varying levels of patient and caregiver involvement, can be beneficial for patients, their caregiver...
Background: Involving people with lived experience (PLE) in medical education, which may occur with varying levels of patient and caregiver involvement, can be beneficial for patients, their caregivers, and medical students. Benefits have been demonstrated across both patient populations and learner level of training. Including PLE may be particularly impactful in medical education related to children who require comprehensive, individualized, and multidisciplinary care, such as children with medical complexity or developmental disabilities. Despite this, there is no summary of how children with medical complexities or developmental disabilities or their families/caregivers have been included in medical education for medical students, residents, and fellows. In order to advance the effective inclusion of lived experience in medical education related to this patient population, a synthesis of existing literature is needed. Objective: The purpose of this scoping review is to identify and synthesize the literature related to including the lived experiences of children with medical complexity or developmental disabilities, their families, and their caregivers in medical education and the level of engagement of people with lived experience in the process. Methods: To complete the proposed scoping review, MEDLINE, Scopus, PsycINFO, ERIC, Academic Search Premier, and Google Scholar will be searched for studies investigating patient and caregiver involvement in medical education related to children with medical complexity or developmental disabilities. Data will be extracted from studies that meet the inclusion criteria. Studies involving continuing professional development or patients that are not children with medical complexity or developmental disabilities will be excluded. Data will be extracted to identify the stage of curriculum development in which lived experience is included based on Kern’s 6-step approach. Data will also be extracted to examine the level of engagement in medical education of children with medical complexity or developmental disabilities, their families, or their caregivers. Results: Descriptive analysis will be performed to identify the findings from the included sources pertaining to the research objective. Findings will be presented in tables, diagrams, or matrices to demonstrate how lived experience has been incorporated into the six steps of curriculum development and characterize the level of engagement of people with lived experience in this process. Conclusions: Results from this scoping review may identify areas of improvement for medical education, especially pertaining to the care of children with medical complexity and developmental disabilities. The findings could contribute to the development of medical school curricula that lead to improved patient outcomes.
Background: Major Depressive Disorder (MDD) is a psychiatric condition that globally ranks as the 24th leading cause of Disability-adjusted Life Years. Pakistan, a developing nation, grapples with pov...
Background: Major Depressive Disorder (MDD) is a psychiatric condition that globally ranks as the 24th leading cause of Disability-adjusted Life Years. Pakistan, a developing nation, grapples with poverty, resource inequality, population growth, and political instability, which may probable cause MDD among general population. Resultantly high prevalence of MDD in Pakistan in evident from the existing literature. Currently, evidence-based psychotherapies such as Eye Movement Desensitization and Reprocessing(EMDR) are widely available. However, EMDR originated in the United States, it might not be consistent with requirements of non-western countries, so it may require cross-cultural and methodological adaptations. Moreover, therapists have long practiced face-to-face EMDR, but recently, online EMDR modalities have emerged. Nonetheless, it is surprising that there is a dearth of research on both the adaptations of EMDR in Pakistan and its clinical efficacy, particularly its online modes have never been scientifically validated in Pakistan. Objective: Considering lack of research on adaptations and clinical efficacy EMDR in Pakistan, the present study aims to develop a culturally and methodologically adapted EMDR therapy protocol for MDD in Pakistan, determine its treatment fidelity, and then clinically test its efficacy by administering it through the face-to-face and online modalities of EMDR therapy. Methods: This study adopted a mixed-mode exploratory sequential Randomized Controlled Trial design in two phases. In the first phase, qualitative exploratory data will be collected, followed by quantitative data, to accomplish the adaptation process of the EMDR therapy protocol. In the second phase, a consecutive sample of 80 patients will be randomly allocated in a 1:1 ratio to face-to-face and online groups to determine the clinical efficacy of the adapted EMDR therapy protocol in both modalities. Symptoms related data will be collected through clinician administered scales during start, mid, end and follow-up stages of therapy. Data will be analyzed using a variety of qualitative and quantitative statistical techniques. Results: This study has been approved by the Ethics Review Committees of Khushal Khan Khattak University Karak, Pakistan, and University Malaysia Sarawak, Malaysia. It is registered at ClinicalTrials.gov. The process of adapting the DeprEnd-EMDR Depression Protocol has already begun. Recruitment of patients for psychotherapy sessions will start in September 2024. Conclusions: In conclusion, this study addresses significant research gaps concerning the adaptation and clinical efficacy of EMDR therapy in the Asian region, with a particular focus on its online modalities. By employing a rigorous research methodology, the results are likely to make substantial contributions by providing insights into both the adaptation and clinical efficacy of EMDR therapy. This study will extend our understanding of the comparative effectiveness of EMDR therapy in the Asian region, offering valuable information on its applicability and impact in diverse, particularly non-Western, settings. Clinical Trial: ClinicalTrials.gov ID NCT06439043
Background: Background Acute pancreatitis is a primarily sterile inflammation caused by premature intracellular protease activation, which has caught the attention of social media platforms such as Bi...
Background: Background Acute pancreatitis is a primarily sterile inflammation caused by premature intracellular protease activation, which has caught the attention of social media platforms such as Bilibili, TikTok, and YouTube. However, the content and quality of medical information on social media exists unclear and indeterminate. Objective: The purpose of the study is to evaluate the content and quality of online videos about acute pancreatitis from Bilibili, TikTok, and YouTube Methods: Methods A video search using acute pancreatic-related keywords was conducted on three video-sharing platforms: Bilibili, TikTok, and YouTube. We recorded basic information presented in the videos and identified the source and content type of each video. The educational content and quality of each video were evaluated using the Global Quality Scale (GQS), Journal of the American Medical Association (JAMA), and Modified DISCERN. A comparative analysis was conducted on the videos obtained from these three sources. Results: Results 300 videos were considered for assessment. Most videos were provided by health professionals (50.7%, 152/300), followed by nonprofit organizations (27.7%, 83/300). Additionally, 13.2% of videos (36/300) were offered by science communicators, and 5.7% (17/300) were provided by general users. The remaining videos were uploaded by news agencies (3.3%, 10/300) and two for-profit organizations (0.7%, 2/300). The content types of the 300 videos were classified into five categories: clinical diagnosis (25%, 75/300), prognosis (5%, 15/300), etiologies and causations (6.7%, 20/300), scientific introductions (51%, 153/300), and treatment methods (12.3%, 37/300). The overall quality of the videos, as evaluated by GQS, JAMA, and Modified DISCERN, was found to be moderate, with scores of 2.67/5, 2.22/4, and 2.63/5 points, respectively. Conclusions: Conclusions Video-sharing platforms have become easily accessible sources for patients seeking information about their diseases. This innovative study demonstrates that social media videos can facilitate public learning about clinical diagnosis, prognosis, treatment methods, etiologies and causations, and scientific introductions of acute pancreatitis. However, both the content and quality of uploaded videos are currently inadequate. In the future, greater efforts should be made to enhance the content and quality of videos on acute pancreatitis and increase public awareness.
Background: Kidney diseases encompass a variety of conditions, including chronic kidney disease, acute kidney injury, glomerulonephritis, and polycystic kidney disease. These diseases significantly im...
Background: Kidney diseases encompass a variety of conditions, including chronic kidney disease, acute kidney injury, glomerulonephritis, and polycystic kidney disease. These diseases significantly impact patients' quality of life and healthcare costs, often necessitating substantial lifestyle changes, especially regarding dietary management. However, patients frequently receive ambiguous or conflicting dietary advice from healthcare providers, leading them to seek information and support from online health communities. Objective: This study aims to analyze social media data to better understand the experiences, challenges, and concerns of kidney disease patients and their caregivers in South Korea. Specifically, it explores how online communities assist in disease management and examines the sentiment surrounding dietary management. Methods: Data were collected from "KidneyCafe," a prominent South Korean online community for kidney disease patients hosted on the Naver platform. A total of 124,211 posts from ten disease-specific boards were analyzed using latent Dirichlet allocation for topic modeling and Bidirectional Encoder Representations from Transformers (BERT)-based sentiment analysis. Additionally, efficiently learning an encoder that classifies token replacements accurately (ELECTRA)-based classification was used to analyze posts related to disease management further. Results: The analysis identified six main topics within the community: Family Health and Support, Medication and Side Effects, Examination and Diagnosis, Disease Management, Surgery for Dialysis, and Costs and Insurance. Sentiment analysis revealed that posts related to Medication and Side Effects topic and Surgery for Dialysis topic predominantly expressed negative sentiments. Both significant negative sentiments concerning worries about kidney transplantation among family members and positive sentiments regarding physical improvements post-transplantation were expressed in posts about family health and support. For Disease Management, seven key subtopics were identified, with inquiries about dietary management being the leading topic. Conclusions: The findings highlight the critical role of online communities in providing support and information for kidney disease patients and their caregivers. The insight gained from this study can inform healthcare providers, policymakers, and support organizations to better address the needs of kidney disease patients, particularly in areas related to dietary management and emotional support.
Analysis of 25 million Shanghai citizens’ daily movements supports the city-cut approach for travel restrictions in the early stage of the COVID-19 pandemic. The city’s high connectivity and compa...
Analysis of 25 million Shanghai citizens’ daily movements supports the city-cut approach for travel restrictions in the early stage of the COVID-19 pandemic. The city’s high connectivity and compact nature justify the city-cut approach over the geographic distance-based radius-cut approach, effectively containing the spread of COVID-19 within the metropolis.
Background: Educational technology (EdTech) has been instrumental in the last few decades in promoting inclusive education by overcoming various learning barriers and offering tools and opportunities...
Background: Educational technology (EdTech) has been instrumental in the last few decades in promoting inclusive education by overcoming various learning barriers and offering tools and opportunities to all students, including those with special educational needs and disabilities (SEND). However, there is limited understanding of current classroom practices and policies and of the effects of the COVID-19 pandemic on EdTech use in the inclusive classroom. Objective: This systematic review aims to outline the current knowledge on the use of EdTech to support the learning of students with SEND in inclusive primary schools in high-income countries. Methods: We followed the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) and the Generalized Systematic Review Registration Form in reporting the details of this protocol. The inclusion criteria for the systematic review require that studies focus on students with SEND who are attending the primary stage of school in high-income countries. The studies can be qualitative or quantitative and should explore the design and use of EdTech with these students. Eligible studies must be published between 2016 and 2024, be peer-reviewed with the exception of relevant reports from Non-Governmental Organizations, and be available in English. We systematically searched the ACM, Directory of Open Access Journals, British Educational Index, ERIC, Google Scholar (first 100 records), IEEE, PsycINFO, Scopus, and Web of Science databases. The titles and abstracts of all records will be screened for relevance according to the inclusion criteria. Following this, the full text of the articles will be screened. To ensure the reliability of the screening process, an independent reviewer will screen a percentage of the records for the first screening round. The data extraction process for this systematic review will start with a pilot stage to validate and eventually update the list of entities to be extracted. Following the pilot stage, the final data extraction will be undertaken. An independent reviewer will extract data from a subsample of the records to ensure the reliability of the data extraction process. Results: The database search was conducted in July 2024. The database search identified a total of 549 records. It is anticipated that the study findings will be submitted for publication in a peer-reviewed journal by the end of September 2024. Conclusions: This study will provide up-to-date evidence of the use of EdTech in inclusive primary school settings in high-income countries and will describe the impact of the COVID-19 pandemic on the use of Ed-Tech with students with SEND. Clinical Trial: https://doi.org/10.17605/OSF.IO/YS7AZ
Transient tachypnea of the newborn (TTN) is one of the most common causes of respiratory distress, shortly after birth, and is generally a benign, self-limited condition. Meanwhile, a lot of studies h...
Transient tachypnea of the newborn (TTN) is one of the most common causes of respiratory distress, shortly after birth, and is generally a benign, self-limited condition. Meanwhile, a lot of studies have linked vitamin D (VitD) levels with probably contributing to neonatal lung development. This study aimed to assess whether the serum levels of VitD are associated with TTN in infants and mothers in natural childbirth. This descriptive-analytical research was performed on 39 infants with TTN and their mothers and 39 control infants and their mothers referred to the Motazedi hospital in Kermanshah University of Medical Sciences. Serum concentrations of VitD were measured in the first 12-24 h of postnatal age in both infants and mothers. In the present study, no significant difference was found between healthy and TTN groups in terms of gender, mother's education level, drug use, asthma, diabetes, 1th min Apgar score, mother's age, birth weight, and birth height. But, there was a significant difference between the two groups of control and intervention in terms of 5th min Apgar score, and birth order. The mean levels of serum VitD were significantly lower in both TTN neonate patients and mothers. The results of the Pearson correlation coefficient indicated that there is a significant relationship between the serum VitD level of mothers and term infants in both groups. We observed that maternal VitD levels can be preventive for the development of TTN in infants through improving respiratory distress, and potentially shortening the duration of tachypnoea in natural childbirth.
Background: Up to 75% of young adult cancer survivors (YACS) experience chronic insomnia, negatively affecting physical and emotional health and overall quality of life. Cognitive behavioral therapy f...
Background: Up to 75% of young adult cancer survivors (YACS) experience chronic insomnia, negatively affecting physical and emotional health and overall quality of life. Cognitive behavioral therapy for insomnia (CBT-I) is a gold standard intervention to address insomnia. However, widespread uptake of CBT-I remains limited and new strategies of CBT-I delivery are warranted. Objective: We wished to understand how YACS experience insomnia, how they might incorporate technology-delivered CBT-I into a daily routine and test the feasibility and acceptability of a novel voice-activated virtual assistant-delivered CBT-I prototype. Methods: We conducted four focus groups (6-7 participants per group, N=26 total) to understand the YACS experience of insomnia, their routine use of technology at home, particularly voice-activated virtual assistants such as the Amazon Alexa, and input on how CBT-I might be delivered at home through a smart speaker system. We developed a prototype device to deliver key elements of CBT-I at home along with circadian lighting and monitoring of post-bedtime device use, collected YACS user perspectives on this prototype, and then conducted a single-arm feasibility and acceptability study. Results: Twenty-six YACS experiencing insomnia participated in focus groups to share experiences of insomnia during cancer survivorship and to provide input regarding a CBT-I prototype. Common triggers of insomnia included worry about disease management and progression, disease-related pain and other symptoms, choices regarding personal device use, and worry about the impact of poor sleep on daily functioning. Twelve participants completed device prototype testing, exceeding pre-determined feasibility and acceptability benchmarks and providing qualitative data to inform future device refinement. Conclusions: YACS were highly engaged with our voice-activated virtual assistant-delivered CBT-I prototype and found it acceptable to use. Following final device development, future studies should evaluate efficacy of this intervention among YACS. Clinical Trial: NCT05875129
Background: Alcohol consumption is a leading cause of death and disability worldwide, associated with numerous acute and chronic medical conditions. Digital health interventions offer a promising solu...
Background: Alcohol consumption is a leading cause of death and disability worldwide, associated with numerous acute and chronic medical conditions. Digital health interventions offer a promising solution to overcome barriers associated with traditional treatment methods, providing accessible, scalable, and cost-effective means to support individuals in reducing hazardous drinking. Objective: This pilot study aims to evaluate the feasibility, acceptability, and preliminary efficacy of the "Sober" smartphone app in individuals with hazardous alcohol use. Methods: This single-group, pre-post pilot study included 20 participants with hazardous alcohol use, identified using the Alcohol Use Disorder Identification Test (AUDIT). Participants used the "Sober" app for four weeks, which incorporates cognitive behavioral therapy(CBT)-based interventions. Feasibility was assessed by study and session completion rates, acceptability by participant satisfaction and perceived usefulness, and preliminary efficacy by changes in alcohol consumption and psychiatric symptoms. Results: Of the 20 enrolled participants, 17 completed the study. The app demonstrated high feasibility with an 85% study completion rate, and 58.8% completed all CBT sessions. Participants reported positive acceptability, with average satisfaction and usefulness ratings of 3.8 and 3.7 out of 5, respectively. Preliminary efficacy outcomes showed significant improvements: abstinence days increased from 66.8% to 84.8% (Z=-3.165, P=.002), heavy drinking episodes decreased from 3.3 to 1.9 (t=-2.965, P=.003), and total alcohol consumption reduced from 456.8 mL to 195.9 mL (t=3.159, P=.002). AUDIT scores dropped from 17.5 to 10.7 (t=4.513, P<.001). Additionally, depression (PHQ-9) scores decreased from 5.8 to 4.4 (t=2.908, P=.010), and anxiety (GAD-7) scores from 3.4 to 2.1 (Z=-2.801, P=.005). No adverse events were reported. Conclusions: The mobile application "Sober" shows promise as an effective tool for reducing hazardous alcohol consumption and improving related psychiatric symptoms. The study demonstrated high feasibility and positive acceptability, with significant preliminary efficacy in reducing alcohol use. Feedback from participants and clinicians highlighted areas for improvement, which will be used to refine the app and study design for future research. Further research through a randomized controlled trial is warranted to confirm these findings and optimize the application’s features and content. Clinical Trial: The trial was registered on ClinicalTrials.gov (NCT06502756)
Background: Effective dermatological practices are essential for maintaining healthy skin and addressing health concerns such as acne. Traditional dermatological consultations often face limitations,...
Background: Effective dermatological practices are essential for maintaining healthy skin and addressing health concerns such as acne. Traditional dermatological consultations often face limitations, including accessibility, cost, and variability in expertise. The potential application of Large Language Models (LLMs) in healthcare, particularly for dermatology, is an area of growing interest. Objective: This study aims to evaluate the feasibility of utilizing various mainstream LLMs, including GPT-3.5-turbo, GPT-4, and GPT-4o, as consultants for acne-related health concerns. The primary objective is to determine whether these models can deliver accurate, relevant, and competitive solutions in line with professional dermatological standards. Additionally, the study compares the performance of these models, to identify which offers the best overall performance for acne management consultations. Methods: Real human question data were sourced from major social media platforms, health forums, and dermatology clinics. Personally Identifiable Information (PII) filtering was applied when selecting 37 related questions to ensure privacy compliances. Each LLM generated responses three times. An automated evaluation system using GPT-4o assessed the responses based on ten criteria: accuracy of terminology, evidence support, factual correctness, completeness, ethical considerations, practicality, safety advice, tone, personalization, and up-to-date information. Each response was categorized as Pass, Fail, or Ignore. Results: The evaluation revealed high performance of GPT-3.5-turbo, GPT-4, and GPT-4o in accuracy, with pass rates for correct terminology (95.20%), evidence support (99.10%), and factual correctness (96.10%). Limitations were observed in personalization (24.62%), safety advice (76.88%), and up-to-date information (75.98%). A comparative analysis showed that GPT-4 generally outperformed GPT-3.5-turbo and GPT-4o in most criteria, achieving higher completeness (91.89%) and ethical considerations (97.30%). GPT-4 excelled in tailoring recommendations to individual profiles. In contrast, GPT-4o demonstrated the highest accuracy. Conclusions: All models demonstrated strong performance in accuracy, ethical considerations, and providing polite and respectful responses. However, the models showed limitations in personalization and safety advice. Overall, GPT models at the current stage demonstrated the capability in initial dermatological consultations and assist patient as a self-explanatory tool, but ongoing enhancements are necessary to address their current shortcomings and ensure even more reliable and effective performance in the future.
Background: Telepathology has proven to be a viable solution to provide timely, high-quality diagnostic services to underserviced, remote areas, and is widely applied in the word. The government stron...
Background: Telepathology has proven to be a viable solution to provide timely, high-quality diagnostic services to underserviced, remote areas, and is widely applied in the word. The government strongly supports the development of telepathology to alleviate the shortage of pathologists in China. This study aimed to survey telepathology in China, and analyze the usage and attitudes of both pathologists and patient. Objective: This study aims to analyze the construction, application, and development of telepathology in China from 2018 to 2023, understand the usage, evaluation, and attitudes of pathologists and patients towards telepathology, and analyze the existing problems and improvement suggestions in the application of telepathology. Methods: A national survey was administered to Chinese hospitals in 2018, 2019, 2020 and 2023. A survey to doctors and patients who participated in telemedicine services was conducted in 2019. Based on this data, we analyze telepathology in China. Chi-square test and Fisher's exact probability test were used to test the difference among different years, different levels of hospitals, and different regions. Results: The annual average growth rate of the proportion of telepathology software in the surveyed hospitals was 7.60%, from 29.53% in 2018 to 42.55% in 2023. From 2018 to 2023, the number of telepathology service cases in China has been continuously increasing, with the median number per hospital growing from 51 to 200 cases, and the fastest growth was in the eastern region. Once a week was the dominant frequency(63.64%) among pathologists in China. The average time for participating in telepathology services was mainly 11-20 min and 21-30min. The pathologists' overall satisfaction rate was 99.35%, and the most frequently mentioned difficulties were unreasonable scheduling, small coverage, inadequate publicity, and network problems. 92.20% of the patients received their diagnostic results within 24 hours, all patients were satisfied with telepathology, and 99.29% of them were willing to recommend it to other patients. Conclusions: The construction and application of telepathology in China have achieved significant growth from 2018 to 2023. Despite some existing barriers with its application, both pathologists and patients exhibit high satisfaction with telepathology. Unreasonable scheduling, limited coverage, inadequate publicity, and network issues are the main problems affecting telepathology. Recommendations include expanding service methods, shortening wait times, strengthening publicity, incorporating telepathology fees into medical insurance, and enhancing training for primary healthcare personnel.
Background: Artificial intelligence (AI)-based clinical decision support systems are increasingly used in healthcare. Uncertainty-aware AI presents the model’s confidence in its decision alongside i...
Background: Artificial intelligence (AI)-based clinical decision support systems are increasingly used in healthcare. Uncertainty-aware AI presents the model’s confidence in its decision alongside its prediction whereas black-box AI only provides a prediction. Little is known about how this type of AI affects healthcare providers’ work performance and reaction time. Objective: To determine the effects of black-box and uncertainty-aware AI advice on pharmacist decision-making and reaction time. Methods: Thirty licensed pharmacists participated in a crossover, randomized controlled trial. Eligible participants were randomized to either the black-box AI or uncertainty-aware AI condition in a 1:1 manner. Participants completed 100 mock verification tasks with AI help and 100 without AI help. The order of no help and AI help was randomized. Participants were exposed to correct and incorrect prescription fills, where the correct decision was to ‘accept’ or ‘reject’, respectively. AI help provided correct (79%) or incorrect (21%) advice. Reaction times, participant decision, AI advice, and AI help type were recorded for each verification. Likelihood ratio tests (LRT) compared means across the three categories of AI type for each level of AI correctness. Results: Participants’ decision-making performance and reaction times differed across the three conditions. Accurate AI recommendations resulted in the rejection of the incorrect drug 96.1% and 91.8% of the time for uncertainty-aware AI and black-box AI respectively, compared to 81.2% without AI help. Correctly dispensed medications were accepted at rates of 99.2% with black-box help, 94.1% with uncertainty-aware AI help, and 94.6% without AI help. Uncertainty-aware AI protected against bad AI advice to approve an incorrectly filled medication compared to black-box AI (83.3% vs 76.7%). When the AI recommended rejecting a correctly filled medication, pharmacists without AI help had a higher rate of correctly accepting the medication (94.6%) compared to uncertainty-aware AI help (86.2%) and black-box AI help (81.2%). Uncertainty-aware AI resulted in shorter reaction times than black-box AI and no AI help except in the scenario where "AI rejects the correct drug". Black-box AI did not lead to reduced reaction times compared to pharmacists acting alone. Conclusions: Pharmacists’ performance and reaction times varied by AI type and AI accuracy. Overall, uncertainty-aware AI resulted in faster decision-making and acted as a safeguard against bad AI advice to approve a misfilled medication. Conversely, black-box AI had the longest reaction times, and user performance degraded in the presence of bad AI advice. However, uncertainty-aware AI could result in unnecessary double-checks, but it is preferred over false negative advice, where patients receive the wrong medication. These results highlight the importance of well-designed AI that addresses users’ needs, enhances performance, and avoids overreliance on AI.
Background: The field of Alzheimer’s disease (AD) moves towards earlier diagnoses in pre-dementia stages, personalized prognosis, and dementia prevention. In the near future, a gap is expected betw...
Background: The field of Alzheimer’s disease (AD) moves towards earlier diagnoses in pre-dementia stages, personalized prognosis, and dementia prevention. In the near future, a gap is expected between the growing demand for Alzheimer-related healthcare and a shrinking workforce. Responsibility is increasingly assigned to individuals to take an active role in their own brain health. Digital tools are thought to offer support with regard to these processes. Objective: The aim of this scoping review is to create an overview of digital tools published in scientific literature in the context of Alzheimer’s disease and dementia, with cognitively unimpaired people and/or people in pre-dementia stages as primary end-users interacting with these digital tools. Additionally, we aim to gain insight into study sample diversity, the stage of maturity and evaluation of these tools, and recommended future directions. Methods: PubMed, IEEE Xplore, Ovid, and Web of Science were searched in January 2023, using terms on Alzheimer’s disease and dementia, (pre-)disease stages, digital tools, and purposes of digital tools. Two independent reviewers screened 2811 records on title and abstract, and subsequently 408 full text articles, based on in- and exclusion criteria. Articles on tools targeting those with an Alzheimer’s disease or dementia diagnosis were excluded. Data extraction included information on the sample characteristics, the digital tool, stage of maturity and evaluation, and future (research) directions. Results: We included 39 articles, which were aimed at primary prevention (15/39; 38.5%), secondary prevention (10/39;25.6%), daily life support (8/39; 20.5%), diagnosis and risk assessment (4/39;10.3%), or decision-making (2/39; 5.1%). Variation in study sample emerged regarding cognitive abilities (healthy (11/39; 28.2%); mild cognitive impairment (11/39; 28.2%), (subjective) cognitive impairment (10/39; 25.6%); ‘no dementia’ (1/39; 2.6%), and variation of cognitive abilities (6/39; 15.4%)). Less variation was found regarding sex (>50% female: 27/39; 69.2%), education ( >50% high education: 13/39; 33.3%), and age (>50% >60 years: 23/39; 59%). Few articles reported on ethnicity (12/39; 30.7%) and digital literacy (11/39; 28.2%). Most tools were in an early evaluation and maturity stage (31/39; 79.5%), comprising pre-prototyping (1/35; 2.9%), prototyping (15/35; 42.9%), pilot testing (19/35; 54.3%), efficacy testing (18/40; 45%), usability testing (12/40; 30%), and feasibility testing (10/40; 25%). Future (research) directions comprise the need for further tool development, attention to diversity, and study advancements, such as large-scale longitudinal studies. Conclusions: 79.5% of tools as reported on in academic literature are considered to be in an early maturity stage. Studies and evidence gathered for digital tools for people (at risk) in pre-dementia stages is thus preliminary and further developments and research is needed before these tools can be implemented for assessing, supporting and preventing cognitive decline.
Background: Traditional medical education in Palestinian higher education institutions faces challenges such as limited interactive practical training and the need for more immersive learning experien...
Background: Traditional medical education in Palestinian higher education institutions faces challenges such as limited interactive practical training and the need for more immersive learning experiences. Emerging technologies like Extended Reality (XR), which includes Virtual Reality (VR) and Augmented Reality (AR), are being integrated into educational environments worldwide to address these issues. Objective: This study aims to explore and understand the factors influencing the adoption and impact of using XR in healthcare education within Palestinian universities. Methods: A mixed-methods approach was employed, combining qualitative and quantitative data from surveys and interviews with instructors and students across multiple Palestinian universities. The study also reviews global implementations of XR technologies in medical education to provide a comparative analysis. Results: The findings indicate that XR technologies significantly enhance the learning outcomes in healthcare settings. However, three main themes served as factors influencing educators’ usage of XR including external, internal, and design factors. Despite challenges, such as financial constraints and technical issues, the long-term benefits include better educational outcomes and cost-effectiveness. The study also highlights the initial success of XR implementations in Palestinian universities and their potential to transform medical education. Conclusions: XR technologies hold promise for revolutionizing medical education by providing immersive learning experiences that enhance practical skills and knowledge retention. The study underscores the importance of strategic investments in technology and infrastructure to overcome initial barriers. The adoption of XR technologies aligns with the Sustainable Development Goals (SDGs) of quality education and good health, suggesting a promising future for broader integration in medical and nursing programs in Palestine.
Background: Heart failure is a prevalent and debilitating condition, affecting millions globally and imposing significant burden on patients, families, and healthcare systems. Despite advancements in...
Background: Heart failure is a prevalent and debilitating condition, affecting millions globally and imposing significant burden on patients, families, and healthcare systems. Despite advancements in medical treatments, the gap in effective, continuous, and personalized supportive care remains glaringly evident. To address this pressing issue, virtual healthcare services, delivered by interdisciplinary teams, represent a promising solution. There is a lack of comprehensive data on the benefits of interdisciplinary virtual heart failure remote monitoring support programs on patient adherence, quality of life, and overall healthcare costs in Australia. Understanding the outcomes and experience of remote monitoring enabled chronic disease management programs can inform better resource allocation and healthcare policy decisions. Objective: The purpose of this study was to evaluate the clinical and behavioural outcomes of patients undertaking a Virtual Home Health Heart Failure Program (VHHHFP) and explore the experiences of patients and health care practitioners. Methods: A mixed methods study was conducted in collaboration with patients and health practitioners. Self-reported outcome data (KCCQ12, PHQ4, PAM13 and PREMS) were obtained from the records of patients (n=55) who completed the intensive phase (0- 3 months) of the VHHHFP; and interviews were conducted with patients (n= 9) and health practitioners (n= 6). Results: Thirty-one (77.5%) of the n=55 patients completed the baseline and three-month follow-up KCCQ12 assessment. The mean KCCQ12 Summary Score at three months was 72.20 which was significantly higher than the mean Summary Score at baseline of 50.51 (p<.001). These findings were similar for the KCCCQ12 sub-scales: Physical Limitations (47.09 and 69.43, p<0.001), Quality of Life (43.75 and 62.91, p<0.001), Symptom Frequency (60.40 and 91.70; p<0.001) and Social Limitation (50.0 and 82.50; p<0.001). The PHQ-4 measure of psychological health was completed by n=32 (80%). The median scores at baseline and follow-up for Total Distress (1.50 and 0.0; p<0.02), and the Anxiety sub-scale (1.0 and 0.0; p <0.02) reduced over time. Six hospital admissions were recorded for five patients (10.2% of n=49) within 30 days of commencement of the VHHHFP. Nine patient interviews were informed by the Value Based Healthcare (VBHC) Capability Comfort and Calm (CCC) Framework. Three themes were identified 1) Enhanced patient capability, 2) Improved patient comfort and 3) Positive influences on Calm. Six healthcare professionals shared experiences and perceptions of the VHHHFP, with three emerging themes- 1) Improved patient capability through shared decision making, 2) Improving Capability through care practices and 3) Promoting Comfort and Calm through virtual coordination and collaboration. Conclusions: The use of technologies to support the management of HF is an area of growth and development. This study contributes to the understanding of how remote patient monitoring with interdisciplinary chronic disease support integrated into an existing system can improve clinical outcomes for patients.
Background: Depression is a prevalent comorbidity in patients with pancreatic cancer, negatively impacting their quality of life, treatment adherence, and survival. Inflammation is a key biological pr...
Background: Depression is a prevalent comorbidity in patients with pancreatic cancer, negatively impacting their quality of life, treatment adherence, and survival. Inflammation is a key biological process that may link pancreatic cancer and depression, with inflammatory markers like C-reactive protein (CRP) and neutrophil-lymphocyte ratio (NLR) playing significant roles. Machine learning (ML) provides a novel approach to predicting depression based on these biomarkers, potentially enabling early intervention and improved patient outcomes. Objective: This study aimed to investigate the clinical associations between depression, inflammation, and pancreatic cancer, and to utilize machine learning to predict depression using biomarker levels and clinical data. Methods: A prospective cohort study was conducted between May 2021 and November 2023, including 328 patients diagnosed with pancreatic cancer. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9). Generalized estimating equations (GEE) were used to explore relationships between depression and inflammatory markers, with significant variables from univariate analyses included in multivariate models. Various ML algorithms, including Random Forest, K-Nearest Neighbors (KNN), and Extreme Gradient Boosting (XGBoost), were employed to predict depression, evaluated using classification metrics such as accuracy, precision, recall, and F1-score. Results: The cohort had a mean age of 65 years, with most patients diagnosed at stage IV. Clinically significant depression (PHQ-9 ≥10) was observed in 35% of patients at baseline, decreasing over time. Univariate analyses indicated associations between depression and factors such as lack of surgical resection and metastatic disease; however, these were not significant in multivariate models. Only log-transformed CRP and NLR remained significant inflammatory markers in multivariate analyses. Among the ML models, XGBoost achieved the highest performance, with an accuracy of 81%, precision of 84%, recall of 91%, and an F1-score of 86%. CRP, NLR, and platelet-lymphocyte ratio (PLR) emerged as the strongest predictors of depression. Conclusions: Depression is prevalent among pancreatic cancer patients and is likely linked to inflammation. Machine learning models, particularly XGBoost, effectively predicted depression using inflammatory markers. Integrating ML-based predictions into mental health care within cancer treatment protocols may improve patient outcomes. Future research should focus on refining these predictive models and exploring their clinical implementation for early depression detection and intervention in pancreatic cancer care.
Background: Technology has transformed the access to information and our learning landscape. During the COVID-19 crisis the accessible and affordable information with appropriate use of technology for...
Background: Technology has transformed the access to information and our learning landscape. During the COVID-19 crisis the accessible and affordable information with appropriate use of technology for healthcare became critical to train health professionals and fight with misinformation. This online based training is gaining increased attention during the last couple of decades both in developed and developing country. The mobile and internet coverage and speed of the internet has significantly improved, and this network coverage opens the opportunity to use the online based training programs for the huge grass root health care service providers. Though the health care providers receive some sort of training specifically for maternal and child health, contraceptives and other common physical illness, they hardly have any opportunity to receive the mental health training. Online based mental health training program for the community health care provider and volunteers can be good option for Bangladesh to reduce its’ wide mental health treatment gap. Objective: This study aimed to find out the potential barrier of the online based mental health trainings for the volunteers who are working in the community to promote mental health and well-being and reduce the mental health stigma in Bangladesh. We also attempted to find out the approaches those might minimize the barriers. The findings of this study will help to develop a realistic expectation and also will provide the insight to predict and prepare to mitigate the challenges of the training implementation. Methods: To understand the complexity of the online based training for mental health we conducted two batches of training with the students who are the mental health volunteers working in the community. We conducted Focus Group Discussions at the end of the 3 days long training of each batch and In-depth Interviews were conducted with also the trainers to find out the barriers of these online training program. The interviews were conducted in Bangla those were recorded transcribed, translated and thematically analyzed. Results: We found the most common barriers to online mental health training was the lack of physical presence, technical issues (e.g., network disturbances, device integration problems), cost of internet, electricity issues, and privacy concern. Moreover, participants reported physical strain of siting in front of desktop and laptop for the training and many of them were concerned about the about privacy breaches, accidental content sharing, and maintaining constant vigilance online. Conclusions: The online based training opened the window to help millions of people at a time however we to be careful about the barriers those threatens the successful implementation of this programs.
Background: Roughly 40% of Alzheimer’s disease (AD) and AD related dementias (ADRD) and up to 20% of AD/ADRD deaths are preventable by addressing modifiable risk factors like physical inactivity. Pa...
Background: Roughly 40% of Alzheimer’s disease (AD) and AD related dementias (ADRD) and up to 20% of AD/ADRD deaths are preventable by addressing modifiable risk factors like physical inactivity. Past programs and technologies to promote and measure physical activity often overlook the voices of the end-user in minoritized groups living with AD/ADRD, or memory challenges. Objective: We apply a human-centered design framework as a call to action to address these gaps and provide a use case. Methods: We applied a human-centered design based on our published Innovation Biodesign framework, to identify clinical needs and map solutions, including gaps in the design and usability testing of technology to measure and monitor physical activity in dementia care. We illustrated the implementation of the framework utilizing a needs assessment and secondary data from the co-design process of a Green Activity Program that tailors nature or “green” activities to improve well-being measuring sleep, activity, and heart rate using the ActiGraph LEAP activity tracker. The program was designed in collaboration with multiple partners, including Hispanic/Latino individuals living with memory challenges in the Bronx, New York. Results: The framework involved problem and solution spaces with an iterative refinement process and highlighted a need to utilize human-centered approaches to select, monitor, and assess desired outcomes of well-being, activity, and sleep for Hispanic/Latino people living with memory challenges. The framework enabled us to conduct a needs assessment and an iterative co-design process to design the program and a future pilot study utilizing the ActiGraph LEAP. Conclusions: The framework empowered us to identify and characterize a clinical problem and gaps in the use of technology to measure and monitor physical activity and advance towards a solution space when designing the Green Activity Program to address the unique social needs of older Hispanic/Latino people living with memory challenges. Application of the framework serves as a call to action to apply human-centered approaches to address the clinical needs of minoritized groups with memory challenges. Clinical Trial: ClinicalTrials.gov NCT06403345.
Background: The increasing prevalence of paediatric obesity presents a major challenge for healthcare services. In England, Complications of Excess Weight (CEW) clinics provide specialist multidiscipl...
Background: The increasing prevalence of paediatric obesity presents a major challenge for healthcare services. In England, Complications of Excess Weight (CEW) clinics provide specialist multidisciplinary care for children presenting with co-morbidities of severe obesity. Positive treatment outcomes require the young person and their family to make behavioural changes to improve the child’s health. However, there are many barriers to health behaviour change, particularly for adolescents. Digital technology could be used to enhance the support offered by CEW clinics to adolescent patients to increase the likelihood of successful behavioural change, but little is known about their and their families’ views of this. Objective: We aimed to explore the views of adolescent patients and their families on how digital technology could be utilised by CEW clinics to support health behaviour change. Methods: The study took a participatory design approach. Four focus groups and co-design workshops were facilitated by a cross-disciplinary team of clinicians, academics and technology innovators. Participants were adolescent CEW clinic patients (aged 10-16 years) and their adult family members. Focus groups and workshops explored young people’s health priorities, the barriers and facilitators of health behaviour change, and co-designed ways in which technology could be used to support young people in overcoming these barriers to achieve their health goals. Focus group data were analysed using inductive content analysis, with findings integrated with key co-design workshop outputs. Results: 37 individuals (19 adolescents, 18 family members) participated across the focus groups and workshops. Participants were in favour of the increased use of digital technology by CEW clinics as an adjunct to in-person support. Weight was not mentioned by participants as an important aspect of their health. Instead, mental health, sleep and peer support were identified as the domains in which adolescent CEW patients felt they would most benefit from additional support and participants reported that technology could be helpful in providing this support. Participants expressed a preference for technology able to individually tailor content to the young person’s needs, including relatable peer-produced content. The need for support for both the young person themselves and their family members was highlighted, as well as the need to integrate strategies to maintain engagement with any technological offering. Conclusions: There is clear potential for digital technology to be used to support the holistic health priorities of young people receiving specialist care for co-morbidities related to excess weight. We plan to use the findings of this study as the basis to begin developing innovative approaches to the use of technology to support this high-need group.
Background: Black/African American and Hispanic/Latina cisgender women in the United States continue to bear disproportionate incidence of HIV related to sexual transmission and injection drug use. Sp...
Background: Black/African American and Hispanic/Latina cisgender women in the United States continue to bear disproportionate incidence of HIV related to sexual transmission and injection drug use. Specifically, women with substance use disorders (SUD) are more likely to engage in vaginal or anal condomless sex associated with HIV transmission. Pre-exposure prophylaxis (PrEP) is a highly effective HIV prevention tool but is not widely used by racial/ethnic minority women. Effective interventions for engaging women with SUD in HIV prevention interventions that are culturally tailored and, therefore, more appealing to racial/ethnic minority women with SUD are critically needed. Objective: This study will assess the initial efficacy, feasibility, and acceptability of an integrated SUD treatment and PrEP services intervention to increase the uptake and adherence to PrEP among racial/ethnic minority cisgender women. Methods: A three-phased mixed methods research design will involve formative qualitative methods to design the intervention (Phase 1), theatre testing to adapt and refine the intervention (Phase 2), and randomized controlled trial (RCT) methods to pilot test the intervention for efficacy, feasibility, and acceptability (Phase 3). The pilot RCT will enroll and randomize 60 women to either the standard SUD treatment program or SUD treatment integrated with PrEP services. The integrated intervention will include four motivational counseling sessions guided by the Information-Motivation-Behavioral (IMB) Skills Model to increase the uptake of PrEP. A mobile health app will be used to engage participants with the intention of motivating PrEP initiation and supporting adherence to PrEP. Results: Findings from individual qualitative interviews informed the development of the integrated intervention. Study recruitment for the randomized pilot (Phase 3) launched in May 2024. Additional statistical analyses will be performed upon completion of the study. Conclusions: This addiction-clinic based behavioral intervention aims to increase PrEP uptake and adherence among racial/ethnic minority cisgender women who engage in sexual and substance use behaviors associated with increased susceptibility to HIV transmission. The integrated intervention has the potential to reduce HIV-related disparities among Black and Hispanic/Latina cisgender women with SUD. Findings from this study will provide a foundation for future HIV prevention interventions for racial/ethnic minority cisgender women with SUD. Clinical Trial: This study is registered on ClinicalTrials.gov (NCT06158607).
You may have come across the term “personalized medicine” before, but what is it? Genetic testing has become commonplace for investigating ancestry and disease risk. There are a myriad of genetic...
You may have come across the term “personalized medicine” before, but what is it? Genetic testing has become commonplace for investigating ancestry and disease risk. There are a myriad of genetic tests available for sale online claiming to offer meal plans and exercise routines tailored to your genetic code. After all, what could be more personalized than DNA? As health information has become more accessible online, another question arises: what information is reliable and what is not? This open educational resource explores 6 questions that can be used by anyone to evaluate the trustworthiness of online health information: Who runs the website? What is the website about? Where are the sources of health information? When was the website last updated? Why was the website made? How is the website funded? Asking these questions is key for the public and medical professionals alike.
Background: Neurological development in children aged 3-11 is highly sensitive and variable. Critical skills for daily and professional
life depend on the development of executive functions, and diff...
Background: Neurological development in children aged 3-11 is highly sensitive and variable. Critical skills for daily and professional
life depend on the development of executive functions, and difficulties in this process can manifest as learning disorders
such as ADHD, Dyslexia, and Dysgraphia, affecting 5-10% of children worldwide. Early screening is crucial to ensure
timely intervention and enhance the quality of life for affected individuals. However, challenges include high costs,
lengthy wait times, and logistical barriers, leading to underdiagnosis and delayed intervention. Objective: To systematically review technological solutions for early screening and improve diagnosis and intervention strategies
for neurodevelopmental disorders in children Methods: Relevant studies were selected using specific inclusion and exclusion criteria to assess the effectiveness of various
technologies and methodologies. Technologies evaluated included gamified eye-tracking tests and machine learning
algorithms. The review employed quality appraisal tools such as the MMAT table and PRISMA flow chart to synthesize
findings from the included studies. Results: The review highlights the efficacy of technologies such as gamified eye-tracking tests and machine learning algorithms
in screening for learning disorders. Despite promising results documented in the literature, there is a significant gap in
translating these technologies into clinical practice. Current practices rely heavily on paper-based tests, which are
inefficient for continuous monitoring and vary widely across regions. No specific sample sizes, response rates, P values,
or Confidence Intervals were detailed in the abstract. Conclusions: Integrating advanced technologies into clinical settings could significantly enhance early diagnosis and intervention for
learning disorders. This aligns with the UK NHS Long Term Plan, advocating for digital and personalized healthcare
solutions to improve access to services, enhance patient experiences, support clinical decision-making, and optimize care
delivery. Future research should focus on bridging the gap between technological advancements and clinical application. Clinical Trial: Not applicable (No RCTs involved).
Background: Generative artificial intelligence (AI), particularly in the form of large language models (LLMs), has rapidly developed. The LLM by Meta AI (LLaMA) series are popular and recently updated...
Background: Generative artificial intelligence (AI), particularly in the form of large language models (LLMs), has rapidly developed. The LLM by Meta AI (LLaMA) series are popular and recently updated from LLaMA2 to LLaMA3. However, impacts of the update in diagnostic performance have not been well documented. Objective: We conducted a comparative evaluation of the diagnostic performance in differential diagnosis lists generated by LLaMA3 and LLaMA2 for case reports. Methods: We analyzed case reports published in the American Journal of Case Reports from 2022 to 2023. After excluding non-diagnostic and pediatric cases, we input the remaining cases into LLaMA3 and LLaMA2 using the same prompt and the same adjustable parameters. Diagnostic performance was defined by whether the differential diagnosis lists included the final diagnosis. Multiple physicians independently evaluated whether the final diagnosis was included in the top 10 differentials generated by LLaMA3 and LLaMA2. Results: In our comparative evaluation of the diagnostic performance between LLaMA3 and LLaMA2, we analyzed differential diagnosis lists for 392 case reports. The final diagnosis was included in the top 10 differentials generated by LLaMA3 in 79.6% (312/392) of the cases, compared to 49.7% (195/392) for LLaMA2, indicating a statistically significant improvement (P <.001). Additionally, LLaMA3 showed higher performance in including the final diagnosis in the top 5 differentials, observed in 63.0% (247/392) of cases, compared to LLaMA2’s 38.0% (149/392, P <.001). Furthermore, the top diagnosis was accurately identified by LLaMA3 in 33.9% (133/392) of cases, significantly higher than the 22.7% (89/392) achieved by LLaMA2 (P <.001). The analysis across various medical specialties revealed variations in diagnostic performance with LLaMA3 consistently outperforming LLaMA2. Conclusions: The results reveal that the LLaMA3 model significantly outperforms LLaMA2 in terms of diagnostic performance, with a higher percentage of case reports having the final diagnosis listed within the top 10, top 5, and as the top diagnosis. Overall dDiagnostic performance improved almost 1.5 times from LLaMA2 to LLaMA3. These findings support the rapid development and continuous refinement of generative AI systems to enhance diagnostic processes in medicine. However, these findings should be carefully interpreted for clinical application, as generative AI, including the LLaMA series, has not been approved for medical applications such as AI-enhanced diagnostics. Clinical Trial: Not applicable
Background: Older adults with cognitive deficits face difficulties recalling daily obstacles and lack self-awareness, amplifying the challenges for homecare clinicians to obtain reliable information o...
Background: Older adults with cognitive deficits face difficulties recalling daily obstacles and lack self-awareness, amplifying the challenges for homecare clinicians to obtain reliable information on functional decline and homecare needs. The result may be suboptimal service delivery. Telemonitoring of ADL has emerged as a tool to optimize ADL homecare needs evaluation. Utilizing ambient sensors, telemonitoring of ADL gathers information about an individual's ADL behaviors within the home, such as preparing meals and sleeping. However, there is a significant gap in the comprehension of how ADL telemonitoring data can be integrated into clinical reasoning to better target homecare services. Objective: The current paper aimed to describe 1) how ADL telemonitoring data is used by clinicians in the process of maintaining care recipients with cognitive deficits at home as well as 2) the impact of ADL telemonitoring on homecare service delivery. Methods: We used an embedded mixed-methods multiple-case study design in which our cases of interest were three health institutions located in the greater Montreal region and offering public homecare services. An ADL telemonitoring system, named NEARS-SAPA, was deployed within those three health institutions for 4 years. Within each case were embedded sub-cases (care recipient, informal caregiver, clinician(s)). For the objectives of the present paper, we used the data collected during 45-60 min interviews with clinicians only. Quantitative metadata were also collected on each service provided to care recipients before and after the implementation of NEARS-SAPA to triangulate the qualitative data. Results: We analyzed 27 sub-cases, comprising 23 clinicians, that completed a total of 57 post-implementation interviews concerning 147 telemonitoring reports. Data analysis showed a 4-step decision-making process used by clinicians 1) Extraction of relevant telemonitoring data, 2) Comparison of telemonitoring data with other sources of information, 3) Risk assessment of the care recipient’s ADL performance and ability to remain at home, and 4) Maintenance or modification of the intervention plan. Quantitative data reporting the number of services received allowed to triangulate qualitative data pertaining to step 4. Overall, the results suggest a stabilization in monthly services following the introduction of the ADL telemonitoring system, particularly in cases where services were increasing prior to its implementation. This is consistent with qualitative data indicating that, in light of the telemonitoring data, most HSCP decided to maintain the current intervention plan rather than increasing or reducing services. Conclusions: Results suggest that ADL telemonitoring contributed to service optimization on a case-to-case basis. ADL telemonitoring may have an important role in reassuring clinicians about their risk management and the appropriateness of services delivery, especially when questions remain as to the relevance of services. Future studies may further explore the benefits of ADL telemonitoring for public healthcare systems with larger-scale implementation studies.
Background: The increasing use of direct-to-consumer AI-enabled mHealth (AI-mHealth) applications presents an opportunity for more effective health management and monitoring and expanded mHealth capab...
Background: The increasing use of direct-to-consumer AI-enabled mHealth (AI-mHealth) applications presents an opportunity for more effective health management and monitoring and expanded mHealth capabilities. However, AI’s early developmental stage has prompted ethical concerns related to privacy, informed consent, and bias, among others. While some of these concerns have been explored in early stakeholder research related to AI-mHealth, the limited literature suggests that the broader landscape of considerations that hold ethical significance to users may remain underexplored. Objective: Our aim was to document and explore the ethical perspectives of users of mHealth regarding AI-mHealth applications. Methods: We conducted semi-structured interviews with users of mHealth applications (N=21) and employed a qualitative descriptive design to document and describe their ethical perspectives. Results: Through qualitative analysis, three major categories and nine subcategories describing users’ perspectives were identified. Users described attitudes toward the impact of AI-mHealth on their health and data (i.e., influences on health awareness and management, value for mental versus physical health, and the inevitability of data sharing); influences on their trust in AI-mHealth (i.e., expert recommendations, attitudes toward technology companies, and AI explainability); and their preferences relating to information sharing in AI-mHealth (i.e., the type of data that is collected, future uses of their data, and the accessibility of information). Conclusions: This paper provides additional context relating to a number of ethical concerns previously posited or identified in the AI-mHealth literature, including trust, explainability, and information sharing, and revealed additional considerations that have not been previously documented, i.e., users’ differentiation between the value of AI-mHealth for physical and mental health use cases, and their willingness to extend empathy to non-explainable AI. To our best knowledge, this study is the first to apply an open-ended, qualitative descriptive approach to explore the perspectives of end users of direct-to-consumer AI-mHealth applications. Clinical Trial: This study addressed a supplemental aim to an ongoing study about the ethics of AI use in medicine (NCATS R01-TR-003505). This study obtained human subjects research approval from the Institutional Review Board of Stanford University on June 21, 2022 (#58118).
Background: Managing preoperative anxiety in pediatric anesthesia is challenging, as it impacts patient cooperation and postoperative outcomes. Both pharmacological interventions and non-pharmacologic...
Background: Managing preoperative anxiety in pediatric anesthesia is challenging, as it impacts patient cooperation and postoperative outcomes. Both pharmacological interventions and non-pharmacological interventions are used to reduce children’s anxiety levels. However, the optimal approach remains debated, with evidence-based guidelines still lacking. As a consequence, many different approaches exist. Objective: To increase understanding of the current anxiety management practices, we conducted a public survey via social media platforms, aiming to compare anesthesia providers from an “expert” group and a “social media” group in terms of pediatric anesthesia expertise and to identify differences in preoperative anxiety management between the two groups. Methods: Two surveys were conducted: The first survey targeted attendees of the Scientific Working Group on Pediatric Anesthesia in June 2023 forming the ‘Expert Group’ (EG), and the second survey targeted followers of a pediatric anesthesia platform on social media forming the ‘Social Media Group’ (SG). Both surveys with 24 items were conducted using the same online platform. Questions were grouped into five categories: Pediatric Anesthesia Expertise, Representativity, Structural Conditions, Practices of Pharmacological Management and Practices in Non-Pharmacological Management. The primary objective was to assess the pediatric anesthesia expertise of the SG compared to the EG. Secondary objectives were the differences in the clustered categories with regards to preoperative anxiety management. Results: The study included 198 respondents, with 194 analyzed after excluding 4 due to prior participation or missing data (82 in EG and 112 in SG). The EG cohort exhibited significantly greater professional experience in pediatric anesthesia than the SG cohort (median 19 vs. 10 years, p<0.001), higher specialist status (97.6% vs. 64.6%, p<0.001), and a greater pediatric anesthesia volume (43.9% vs. 12.0% with more than 500 cases per year, p<0.001). Regarding the representativity, two items out of four were statistically significant (level of care of institution, annual case load of institution). Regarding the overall anxiety management practices used, there is a heterogeneous response pattern within both groups, with only five out of 17 items showing statistical significance (feasibility of parental presence during induction, known anxiety measurement tools, induction-based prescription of drugs, minimum age and use of non-pharmacological interventions). Conclusions: Although the respondents do not reflect the level of expertise as a survey of a scientific working group, social media surveys on pediatric anesthesia may be feasible to get an overview of a specific topic when there is great heterogeneity overall. In our case, both cohorts showed little difference in the management of preoperative anxiety in daily practice with very heterogeneous approaches. Evidence-based recommendations could help to standardize preoperative anxiety management and improve anxiety levels in children. Clinical Trial: not necessary
Background: People with disabilities are a priority population for health services research. People who are blind/low vision (B/LV) are a segment of this priority population, who experience difficulty...
Background: People with disabilities are a priority population for health services research. People who are blind/low vision (B/LV) are a segment of this priority population, who experience difficulty to accessing healthcare facilities due to architectural and navigational barriers. These barriers persist despite disability civil rights law in the U.S. Objective: The purpose of this manuscript is to report on a program that was developed to train way finders in human guide technique for people who are B/LV. Methods: This study took place at Michigan Medicine, an academic medical center in southeast Michigan. We conducted a needs assessment through cohort discovery and soliciting expert feedback. The human guide training program was developed using the PRECEDE-PROEED health promotion program development model, and targeted healthcare volunteers and staff. The intended components included in-person training, an online module, and tip sheets. Due to COVID-19, the in-person training was not implemented. We report findings from a process evaluation, measuring reach, knowledge, behavioral capability, and satisfaction pre- and post-program. Results: 87 participants completed the training, most of them were Michigan Medicine volunteers. There were significant improves in behavioral capability related to human guide technique. Participants were satisfied with the training, and provided recommendations for more detailed demonstrations and scenarios in future training sessions. Conclusions: The training improve participants’ knowledge and confidence in providing wayfinding assistance to patients who are B/LV. However, further in-person training is recommended to provide hands-on experience and detailed feedback. Addressing architectural barriers and providing accessible patient education materials is crucial for improving healthcare accessibility for patients who are B/LV.
Background: Artificial intelligence (AI) is revolutionizing various sectors, including healthcare, by enhancing administration, diagnostics, treatment planning, medical education, and more. However, i...
Background: Artificial intelligence (AI) is revolutionizing various sectors, including healthcare, by enhancing administration, diagnostics, treatment planning, medical education, and more. However, its adoption in developing countries like Nigeria is limited. This study investigates the knowledge and attitude of medical students at the University of Ilorin towards AI in medicine. Objective: 1. To assess the knowledge level of artificial intelligence among medical students and doctors
2. To determine the attitude of medical students and doctors to artificial intelligence
3. To assess the perception of respondents on their willingness to apply AI in the near future. Methods: A cross-sectional study was conducted at the University of Ilorin and its teaching hospital, involving 343 medical students. Data were collected using a self-administered questionnaire distributed via social media and class representatives. The questionnaire assessed demographics, knowledge, and attitudes towards AI. Descriptive statistics and chi-square tests were used to analyze the data, with significance set at p < 0.05. Results: The majority (98.8%) of students had heard of AI, but only 76.4% could define it. Most (90.4%) learned about AI through media, and a small percentage (24.1%) from university lectures. Only 9.3% had received AI training. While 63% believed AI would play an important role in healthcare, 63.9% felt it would not render doctors expendable. Almost half (46.3%) felt AI would influence their specialty choice. A significant portion (87.1%) supported including AI in medical education, though 84% acknowledged it would pose new ethical challenges. Gender significantly influenced knowledge of AI (p < 0.05), but level of training did not. Conclusions: Despite limited formal education on AI, medical students at the University of Ilorin exhibit a positive attitude towards its integration into healthcare and education. There is a strong interest in learning more about AI, highlighting the need for its inclusion in the medical curriculum to prepare future doctors for technological advancements in healthcare.
Background: Cancer prevention holds significant importance in modern healthcare. Artificial intelligence (AI) chatbots have simplified public queries on cancer prevention and increased the effectivene...
Background: Cancer prevention holds significant importance in modern healthcare. Artificial intelligence (AI) chatbots have simplified public queries on cancer prevention and increased the effectiveness of prevention strategies. However, further assessment is essential to determine the accuracy and professionalism of the responses provided by these chatbots. Objective: We aimed to investigate the accuracy and consistency of ChatGPT and NewBing in providing cancer prevention advice, and to establish an evaluation framework to support the enhancement of cancer prevention strategies. Methods: We followed guidelines from the American Cancer Society and the National Comprehensive Cancer Network to develop 25 questions after consultations with oncologists. These questions cover four modules on cancer lesions, screening, prevention, and risk. ChatGPT 3.5 and NewBing were utilized for generating responses, with questions reiterated to evaluate model answer stability and reliability. 28 specialists from diverse regions rated the model answers on a 1-5 scale based on clinical experience and guidelines. The scores were statistically analyzed by Excel and SPSS to evaluate their accuracy and consistency with the medical community's consensus. Results: In the four modules, the median total scores for ChatGPT and NewBing were 73 and 71.5 (p > 0.05), respectively. For specific questions such as "What is a nodule?" and “What are the early symptoms of cancer in the body?” in the "cancer lesion-related" module, and certain questions in the "cancer screening" and "cancer risk" modules, ChatGPT scores higher than NewBing (p < 0.05). Subgroup analyses were conducted between clinicians' and non-clinicians' scores (p < 0.05). Conclusions: Both ChatGPT and NewBing exhibited high accuracy and stability when offering cancer prevention advice, showcasing proficiency in handling intricate medical data. Overall, ChatGPT outperformed NewBing, especially on several specific areas. As AI advances, its role in personalized health services will become more significant. It is essential to consistently enhance model performance, guarantee response accuracy, and address ethical concerns.
Background: Compelling evidence shows screening detects colorectal cancer (CRC) at earlier stages and prevents the development of CRC through removal of pre-cancerous polyps. For average risk patients...
Background: Compelling evidence shows screening detects colorectal cancer (CRC) at earlier stages and prevents the development of CRC through removal of pre-cancerous polyps. For average risk patients, there are three commonly used screening tests used in the United States—two types of stool tests collected at home (FIT/FOBT and FIT-DNA) and colonoscopy completed at procedural centers. Objective: This study’s purpose is to examine variation by month for the three types of CRC testing to evaluate consistent patient care by clinical staff. Methods: Data from 31 federally qualified health center (FQHC) clinics in Missouri from 2011-2023 were analyzed. A sample of 37,994 unique eligible patients were identified. Simple statistics characterize the sample, while bivariate analyses assess differences in screening types by month. Results: In the post COVID-19 era, from 2021 to 2023, colonoscopy testing remained stable with about one third of patients (38%) completing this test. Whereas FIT-DNA increased (16% to 26%) and FIT/FOBT decreased (46% to 35%). Completion of CRC screening yielded statistically significant differences for patients completing the different types of CRC screening by month. For patients who received a colonoscopy (n=7,850), October – January were the highest months for screening, while February-April was the lowest. For FIT/FOBT (n=6,818), March-August was higher whereas December-February were the lowest screening months. For FIT-DNA (n=2,663), March was the most popular month followed by April, May and November, with January the lowest month of testing. Conclusions: Home-based tests are more popular than the gold standard, colonoscopy. However, variation of screening over the course of a year suggests under-utilized CRC screening efforts and therefore less than ideal patient care. Months with lower rates of screening for each type of CRC test represent opportunities for improving CRC screening.
Background: The United States population is aging. With this demographic shift, more older adults will be living with chronic conditions and geriatric syndromes. To prepare the next generation of heal...
Background: The United States population is aging. With this demographic shift, more older adults will be living with chronic conditions and geriatric syndromes. To prepare the next generation of health care professionals for this aging population, we need to provide training that captures the complexity of geriatric care. Objective: The aim of this pilot study was to assess the feasibility of the cinematic virtual reality (cine-VR) training in the complexity of geriatric care. We measured changes in attitudes to disability, self-efficacy to identify and manage elder abuse and neglect, and empathy before and after participating in the training program. Methods: We conducted a single arm, pre-test and post-test pilot study to assess the feasibility of a cine-VR training and measure changes in attitudes to disability, self-efficacy to identify and manage elder abuse and neglect, and empathy. Health professional students from a large university in the Midwest were invited to participate in one of four cine-VR trainings. Participants completed three surveys before and after the cine-VR training. We performed paired t-tests to examine changes in these constructs before and after the training. Results: A total of 65 health professional students participated in and completed the full cine-VR training for 100% retention. Participants did not report any technological difficulties or adverse effects from wearing the head-mounted displays or viewing the 360-degree video. Of the 65 participants, 48 completed the pre- and post-assessments. We observed an increase in awareness of discrimination towards people with disability (t.05,47= -3.967, P<.001). Additionally, we observed significant improvements in self-efficacy to identify and manage elder abuse and neglect (t.05,47= -3.364, P=.002). Lastly, we observed an increase in participants’ empathy (t.05,47= -2.329, P=.024). Conclusions: We demonstrated that our cine-VR training program was feasible and acceptable to health professional students at our Midwestern university. Findings suggest that the cine-VR training increased awareness of discrimination towards people with disabilities, improved self-efficacy to identify and manage elder abuse and neglect, and increased empathy. Future research utilizing a randomized control trial design with a larger, more diverse sample and a proper control condition is needed to confirm the effectiveness of our cine-VR training. Clinical Trial: Not applicable
Background: Evolving societal trends mean that fathers are having an increasing influence on the health-related behaviours that children develop. Research shows that most fathers are committed to thei...
Background: Evolving societal trends mean that fathers are having an increasing influence on the health-related behaviours that children develop. Research shows that most fathers are committed to their role and when equipped with knowledge, can have a positive impact on their child’s health. However, parenting resources typically target mothers, with fathers invariably excluded. While evolving mobile phone technology provides an efficient means for delivering parenting resources, many fathers find mHealth technology does not provide material they can engage with. Objective: The aim of this study is to explore how to make parenting apps more engaging and useful for fathers using an existing parenting mHealth resource; the My Baby Now app (MBN), as a case study. Methods: Fourteen, purposefully selected, Australian fathers of 7 months to 5-year-old children took part in a qualitative study, comprising either focus groups or interviews. Recorded focus groups/ interviews were transcribed verbatim, then coded and analysed for themes using thematic analysis. Results: Current parenting apps, including MBN, provide parenting information that can be unappealing for fathers. For fathers to engage in mHealth resources, the information needs to be father specific, there should be positive imagery and descriptives of fathers in their parenting role, there should be father exclusive domains such as forums, and there should also be push notifications/ messages to support fathers in times where they may be under stress. Conclusions: Smartphone technology has the capacity to deliver father-specific information when needed. This reduces the risks of fathers becoming frustrated and disengaged from parenting. Future research will be benefited by understanding possible differences in mHealth app usage by fathers of differing SEP, cultural backgrounds and family status, such as single fathers and same sex couples.
Background: Musculoskeletal disorders are the leading cause of disability in people, and managing them can be challenging. Virtual reality (VR) technology has been recognized as a promising simulation...
Background: Musculoskeletal disorders are the leading cause of disability in people, and managing them can be challenging. Virtual reality (VR) technology has been recognized as a promising simulation tool in the field of medicine and rehabilitation, and is an important part of the rehabilitation care of patients in the field of orthopedics. The efficacy of VR interventions for musculoskeletal disorders remains to be determined. Objective: To analyze the impact of the virtual reality on musculoskeletal diseases rehabilitation and assess the consistency of evidence from existing systematic reviews and meta-analyses. Methods: The PubMed/Medline, Embase, and Cochrane Library databases were searched for relevant articles published up to April 2024. Literature screening, quality evaluation, and data extraction were performed based on predefined inclusion and exclusion criteria. The Measurement Tool to Assess Systematic Reviews (AMSTAR) 2 was used to evaluate the methodological quality of the included meta-analyses. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was used to rate the evidence level for each outcome as high, moderate, low, or very low. Furthermore, the ratings were classified into four categories based on the evidence classification criteria: I (convincing); II (highly suggestive); III (suggestive); IV (weak); and non-significant. Results: Results from 15 meta-analyses were synthesized. Seven meta-analyses had high, eight had moderate, and the remaining had low AMSTAR 2 ratings. Virtual reality (VR) shows promising results in musculoskeletal rehabilitation, significantly reducing knee pain (MD=-1.38, 95%CI: -2.32, -0.44, P=.004, I²=94%) and enhancing balance. In Fibromyalgia Syndrome, VR effectively decreases pain (SMD=-0.45, 95%CI: -0.70, -0.20, P<.01), fatigue (SMD=-0.58, 95%CI: -1.01, -0.14, P=.01), anxiety (SMD=0.50, 95%CI: -0.908, -0.029, P=.04), and depression (SMD=0.02, 95%CI: -0.76, -0.15, P=.003), also improving life quality. For back pain sufferers, VR lessens pain-related fears (MD=-5.46, 95%CI: -9.40, -1.52, P=.007, I²=90%) and pain itself (MD=-1.43, 95%CI: -1.86, -1.00, P<.01, I²=95%). Post-arthroplasty, it positively impacts knee functionality (MD=8.30, 95%CI: 6.92, 9.67, P<.01, I²=24%) and lowers anxiety (MD=-3.95, 95%CI: -7.76, -0.13, P=.04, I²=0%). Conclusions: Virtual reality has shown potential value in rehabilitating various musculoskeletal conditions. It can reduce pain, improve psychological state, and promote patient motor function recovery.
Background: Emotion regulation problems are a common contributor for delinquent behavior in adolescence. These adolescents show difficulties in recognizing, comprehending and controlling emotions, whi...
Background: Emotion regulation problems are a common contributor for delinquent behavior in adolescence. These adolescents show difficulties in recognizing, comprehending and controlling emotions, which impedes the effectiveness of current forensic treatments. In addition, forensic care often faces challenges regarding treatment engagement due to a lack of motivation and difficulties building an alliance between clients and caregivers. The use of Feelee, an app that collects and displays active and passive data, is promising to support adolescents in obtaining more insight in their emotion regulation abilities. Furthermore, the integration of smartphone applications, like Feelee, offers new perspectives to increase adolescents’ engagement and adherence in treatment. Objective: This study aims to describe the research protocol to evaluate the initial effects of the Feelee app in enhancing emotion regulation skills among adolescents in the forensic outpatient setting. The Feelee app, the addition of Feelee to treatment as usual (TAU), as well as the study design, a repeated Single Case Experimental Design (SCED), are discussed in detail. Methods: A repeated ABA-design will be applied to examine the initial effectiveness of Feelee. Both quantitative and qualitive methods will be used. In total 24 participants will be recruited from different forensic outpatient care centers. Participants will follow a 2-week baseline (phase A1), 4-week intervention (phase B) and a 2-week follow-up (phase A2) in which daily measurement on emotion regulation will be conducted. Results: Data-collection has started in June 2023 and is planned to be completed in December 2024. Study results will be published in peer-reviewed journals and presented at national and international conferences. Conclusions: This study aims to evaluate the effectiveness of the Feelee app in enhancing emotion regulation skills. By using a repeated ABA-design, we will get a first insight about the addition of Feelee to TAU in the forensic outpatient setting. Study strengths include the low-threshold addition, ecological validity and the use of both quantitively and qualitative research methods. Further implications for clinical practice are discussed. Clinical Trial: Central Committee on Research Involving Human Subjects NL78889.029.21, Internation Registration for Clinical Trials: ClinicalTrials.gov NCT06509360
Background: Over the last decade, the healthcare technology landscape has expanded significantly, introducing new and innovative solutions to address healthcare needs. The implications of cybersecurit...
Background: Over the last decade, the healthcare technology landscape has expanded significantly, introducing new and innovative solutions to address healthcare needs. The implications of cybersecurity incidents in the healthcare context extend beyond data breaches to potentially harming individuals' health and safety. Risk perception is influenced by various contextual factors, contributing to cybersecurity concerns that technological safeguards alone cannot address. Thus, it is imperative to study risk perceptions, contextual factors, and technological benefits to guide policy development, risk management, education, and implementation strategies. Objective: To investigate the differences in cybersecurity risk perception among various stakeholders in the healthcare sector in Norway and British Columbia (BC), Canada, and identify specific contextual factors that shape these perceptions. We expect to identify differences in risk perceptions for the explored healthcare technologies. Methods: Using a mixed-methods approach comprising surveys and interviews, we sampled healthcare-related wearable technology stakeholders, including healthcare workers, patients (adults and adolescents) and their families, health authorities and hospital staff (biomedical engineers, IT support, research), and device vendors/industry professionals in both Norway and BC.
Surveys explored information security scenarios based on the Behavioural Cognitive Internet Security Questionnaire (BCISQ), risk perception, and contextualizing variables. We analyzed both survey datasets to summarize participants’ characteristics and responses to questions related to the BCISQ (behaviour and attitude) and risk perception. Interviews were analyzed thematically using an inductive-deductive approach to explore risk perception and contextual factors. Results: Data from 274 survey respondents were available for analysis: 185 from Norway, including 139 (75%) females, and 89 from BC, including 57 (64%) females. Forty-five respondents (31 in Norway and 14 in BC) participated in interviews. The BCISQ showed minor differences between locations; respondents demonstrated generally low-risk behaviour and robust information security awareness. However, password simulation demonstrated discrepancies between self-assessed and “real” behaviour by sharing or willingness to share passwords. Perceived risk is generally considered low, yet consequences of cybersecurity risks were evaluated as major but unlikely. Risk perception was stronger for assisted living and diabetes technologies than for smartwatches. The most important contextual factors shaping risk perceptions are human factors encompassing knowledge, competence, familiarity, feelings of dread, perceived benefit, and trust, as well as the technological factor of device functionality. Organizational and technological factors had lesser effects. Conclusions: We found minimal differences in behaviour and risk perception among Norwegian and BC participants. Human factors and device functionality were most influential in shaping cybersecurity risk perceptions. Considering the rising need for assisted living technologies and wearables, insight into risk perceptions can strengthen risk management, awareness, and competence building. Further, it can address potential concerns amongst stakeholders to enable quicker technology adoption.
Background: Background: The emergence of generative artificial intelligence (GenAI) presents unprecedented opportunities to redefine conceptions of personhood and cognitive disability, potentially enh...
Background: Background: The emergence of generative artificial intelligence (GenAI) presents unprecedented opportunities to redefine conceptions of personhood and cognitive disability, potentially enhancing the inclusion and participation of individuals with cognitive disabilities in society. Objective: Objective: Explore the transformative potential of GenAI in reshaping perceptions of cognitive disability, dismantling societal barriers, and promoting social participation for individuals with cognitive disabilities. Methods: Method: Critical review of current literature in disability studies, artificial intelligence (AI) ethics, and computer science, integrating insights from disability theories and the philosophy of technology. The analysis focused on two key aspects: GenAI as a social mirror reflecting societal values and biases, and GenAI as a cognitive partner for individuals with cognitive disabilities. Results: Results: The article proposes a theoretical framework for understanding the impact of GenAI on perceptions of cognitive disability. It introduces the concepts of GenAI as a "social mirror" that reflects and potentially amplifies societal biases, and as a "cognitive co-pilot" providing personalized assistance in daily tasks, social interactions, and environmental navigation. The article also presents a novel protocol for developing AI systems tailored to the needs of individuals with cognitive disabilities, emphasizing user involvement, ethical considerations, and the need to address both the opportunities and challenges posed by GenAI. Conclusions: Conclusions: Although GenAI has great potential for promoting the inclusion and empowerment of individuals with cognitive disabilities, realizing this potential requires a change in societal attitudes and development practices. The article calls for interdisciplinary collaboration and close partnership with the disability community in the development and implementation of GenAI technologies.
Implications: Realizing the potential of GenAI for promoting the inclusion and empowerment of individuals with cognitive disabilities requires a multi-faceted approach. This involves a shift in societal attitudes, inclusive AI development practices that prioritize the needs and perspectives of the disability community, and ongoing interdisciplinary collaboration. The article emphasizes the importance of proceeding with caution, recognizing the ethical complexities and potential risks alongside the transformative possibilities of GenAI technology.
Background: The use of extended reality (XR) technologies in healthcare can potentially address some of the significant resource and time constraints related to delivering training for healthcare prof...
Background: The use of extended reality (XR) technologies in healthcare can potentially address some of the significant resource and time constraints related to delivering training for healthcare professionals. While substantial progress in realising this potential has been made across several domains including surgery, anatomy, and rehabilitation, the implementation of XR in mental health training, where nuanced humanistic interactions are central, has lagged. Objective: Given the growing societal and healthcare service need for trained mental health and care workers, coupled with the heterogeneity of exposure during training and the shortage of placement opportunities, we explored the feasibility and utility of a novel XR tool for mental health consultation training. Specifically, we set out to evaluate a training simulation created through a collaboration between software developers, clinicians and learning technologists, in which users interact with a virtual patient, ‘Stacey’, through a virtual reality or augmented reality head-mounted display. The tool was designed to provide trainee healthcare professionals with an immersive experience of a consultation with a patient presenting with perinatal mental health symptoms. Users verbally interacted with the patient, and a human instructor selected responses from a repository of pre-recorded voice-acted clips. Methods: In a Pilot Experiment, we confirmed the face validity and usability of this platform for perinatal and primary care training with subject-matter experts. In our follow-up experiment, we delivered personalised one-hour training sessions to 123 participants, comprising Mental Health Nursing trainees, General Practitioner Doctors in Training, and students in psychology and medicine. This phase involved a comprehensive evaluation focusing on usability, validity, and both cognitive and affective learning outcomes. Results: We found significant enhancements in learning metrics across all participant groups. Notably, there was a marked increase in understanding (p<.001) and motivation (p<.001), coupled with decreased anxiety related to mental health consultations (p<.001). There were also significant improvements to considerations towards careers in perinatal mental health (p<.001). Conclusions: These findings show, for the first time, that XR can be used to provide an effective, standardised, and reproducible tool for trainees to develop their mental health consultation skills. We suggest that XR could provide a solution to overcoming the current resource challenges associated with equipping current and future healthcare professionals, which are likely to be exacerbated by workforce expansion plans.
Background: The link between atrial fibrillation (AF) and stroke has gained attention due to AF's significant impact on stroke risk. Detecting AF, especially paroxysmal AF, presents challenges, highli...
Background: The link between atrial fibrillation (AF) and stroke has gained attention due to AF's significant impact on stroke risk. Detecting AF, especially paroxysmal AF, presents challenges, highlighting the necessity for continuous Holter monitoring. Objective: In our investigation, we utilized commercial data archives to examine AF prevalence and associated cardiac arrhythmias among stroke patients and controls. We also analyzed various factors, such as age, gender, symptoms, test duration, and duration post-stroke, to identify predictors of arrhythmias and enhance paroxysmal detection rates. Methods: We included 98 stroke patients and 98 controls for comparing AF prevalence within 72 hours post-stroke and analyzed 779 stroke patients within 4 days to 10 weeks post-stroke. Results: Our findings revealed a higher AF detection rate in stroke patients compared to controls, with AF being the most prevalent arrhythmia observed. Older age and symptom presence were associated with significant findings, particularly AF. Temporal analysis showed a negative correlation between AF and complete heart block occurrence over time, while ventricular tachycardia exhibited a positive correlation. Paroxysmal fibrillation detection rates were highest within the initial month, with the optimal duration of Holter monitoring being 10 days, underscoring the importance of extended monitoring for detecting paroxysmal atrial fibrillation. Conclusions: Detecting paroxysmal atrial fibrillation could influence stroke management. Furthermore, our study suggests the potential utility of commercial data in yielding comparable outcomes to research data.
Background: Evidence that Artificial Intelligence (AI) may improve melanoma detection has led to calls for increased human-AI collaboration in clinical workflows. However, “AI-based support” may e...
Background: Evidence that Artificial Intelligence (AI) may improve melanoma detection has led to calls for increased human-AI collaboration in clinical workflows. However, “AI-based support” may entail a wide range of precise functions for AI. In order to appropriately integrate AI into decision-making processes, it is therefore crucial to understand the precise role that clinicians see AI playing within their clinical deliberations. Objective: This study sought to provide an in-depth understanding of how a range of clinicians involved in melanoma screening and diagnosis conceptualise the role of AI within their decision-making, and what these conceptualisations mean for good decision-making. Methods: This qualitative exploration used in-depth individual interviews with 30 clinicians predominantly from Australia/New Zealand (26/30) who engage in melanoma detection (17 dermatologists, 6 General Practitioners with an interest in skin cancer, and 7 melanographers). The vast majority of the sample (83%) had interacted with or used, 2D/3D skin imaging technologies with AI tools for screening or diagnosis of melanoma, either as part of testing, through clinical AI reader studies, or within their clinical work. Results: We constructed five themes to describe how participants conceptualised the role of AI within decision-making when it comes to melanoma detection. Theme 1 (integrative theme): the importance of good clinical judgement; Theme 2: AI as just one tool among many; Theme 3: AI as an adjunct after a clinician’s decision; Theme 4: AI as a second opinion on unresolved decisions; Theme 5: AI as an expert guide before decision-making. Participants articulated a major conundrum - AI may benefit inexperienced clinicians when conceptualised as an “expert guide”, but over-reliance, de-skilling, and a failure to recognise AI errors, may mean only experienced clinicians should use AI “as a tool”. However, experienced clinicians typically relied on their own clinical judgement, and some could be wary of allowing AI to “influence” their deliberations. The benefit of AI was often then to reassure decisions once they had been reached, by conceptualising AI as a kind of “checker”, “validator”, or in a small number of equivocal cases as a genuine “second opinion”. This perhaps raises queries about the extent to which experienced clinicians then truly seek to “collaborate” with AI or use it to inform decisions. Conclusions: Clinicians conceptualised AI-support in an array of potentially disparate ways that potentially impact AI’s incorporation, whilst prioritising the conservation of good clinical acumen. This must be a priority when developing and adopting AI into decision-making process, and our study implores a more focused engagement with users about the precise way, and in what position, they envisage AI being incorporated into their decision-making process for melanoma detection.
Background: Dermoscopy is a non-invasive technology used to examine the skin's invisible microstructures in dermatological practice. It is an established technique for analyzing skin lesions that have...
Background: Dermoscopy is a non-invasive technology used to examine the skin's invisible microstructures in dermatological practice. It is an established technique for analyzing skin lesions that have been in use since the 17th century when Kohlhaus used a microscope to study nail matrix vessels. [1–3]. However, dermoscopy was not widely used until the 20th century, when Goldman created a portable microscope that could magnify up to ten times more than the naked eye [1–6]. Historically, dermoscopy has been used to diagnose pigmented lesions such as naevi, melanomas, and pigmented basal cell carcinomas [7]. Since the 1990s it has been used to diagnose other dermatological disorders, including infections such as scabies, inflammatory lesions, and hair and nail-fold alterations, and it is also used to track lesions’ progress or reactions to topical treatments such as imiquimod or 5-fluorouracil [8–11]. The evidence-based practice associated with dermoscopy use improves the diagnostic accuracy for skin cancer, reduces unnecessary biopsies of benign lesions, increases survival rates, and improves the early identification of skin malignancies [12–14]. A 2002 meta-analysis of 27 studies revealed that dermoscopy increases experienced physicians’ diagnostic accuracy for melanoma compared to unaided inspection [1]. Moreover, it helps distinguish between various kinds of pigmented and non-pigmented skin malignancies in vivo, and it is significant in differentiating between inflammatory and neoplastic lesions. Currently, the vast majority of worldwide guidelines for skin cancer recommend dermoscopy as a critical component of diagnosing and following up with patients facing an increased risk of this disease [15–20]. Dermoscopy is also increasingly accepted as a standard practice around the globe. Multiple studies have revealed that United States dermatologists use dermoscopy. Indeed, 48% of 3,238 American dermatologists surveyed in 2010 said they used dermoscopy [21]. Chamberlain’s study of dermoscopy revealed a 98% utilization rate use in Australia [22–23], while 95% of dermatologists in France use the practice [24]. However, no study has documented the attitudes toward and use of dermoscopy among future dermatologists in Saudi Arabia. In this study, dermoscopy prevalence among dermatology residents in Riyadh was assessed alongside information sources and elements that influence its use, such as residency levels and the frequency of dermoscopy diagnoses. Objective: to know the attitudes toward and use of dermoscopy among future dermatologists in Saudi Arabia. Methods: In January 2024, A validated and published questionnaire was edited to the research needs was sent to all registered dermatology residents in the Dermatology Saudi Board in Riyadh Results: A total of 63 dermatologist residents in Riyadh, Saudi Arabia completed the online questionnaire equivalent to an 87.5% Response rate The study’s sample was predominantly female (54.0%), and the majority (84.1%) was aged between 26 and 30 years. A considerable proportion of the participants (34.9%) were in the last year of residency. More than half of the participants (54.0%) owned a dermoscopy, and a substantial number (36.5%) offered 21–30 clinics per month on average. More than half the participants (57.1%) had received dermoscopy training. A considerable proportion (36.4%) had used dermoscopy for two years. Additionally, most of the participants (45.5%) had used non-polarized immersion-contact dermoscopy, while (43.2%) had used polarized light dermoscopy. The study’s findings revealed that the majority of the participants (50.0%) had used dermoscopy in < 10% of cases involving the examination of patients with inflammatory skin lesions. The results established a statistically significant association between the participants’ ages, residency levels, and practice centers with the use of dermoscopy, p-values < .05 (0.003,* 0.001,* and 0.004,* respectively). Conclusions: This study has revealed a considerably above-average level of dermatoscopy among use dermatology residents in Riyadh, Saudi Arabia. Dermatoscopy use is increasing among dermatologists, given the practice’s evidence-based advantages and benefits in the early detection and diagnosis of skin diseases. The participants’ ages, residency levels, and practice centers were found to be the main factors that affected dermoscopy use in Saudi Arabia. Finally, this study noted a willingness to improve one’s dermoscopy knowledge and skills, particularly among young dermatologists in Saudi Arabia.
Background: Prolonged sitting and lack of moderate to vigorous physical activity represent two independent risk factors for myriad poor health outcomes. The negative effects of prolonged sitting can b...
Background: Prolonged sitting and lack of moderate to vigorous physical activity represent two independent risk factors for myriad poor health outcomes. The negative effects of prolonged sitting can be ameliorated with as little as 2 minutes of large muscle movement. Further, cardiovascular benefits from moderate to vigorous activity can be accumulated throughout the day in short bouts rather than require continuous long bouts. Taken together, “exercise snacks” provide a way to both interrupt prolonged sitting and accumulate moderate to vigorous physical activity during a sedentary work day. Objective: The current protocol describes the feasibility and acceptability pilot of Move Often eVery Day (MOV'D), a fully-remote, peer-supported behavioral intervention to interrupt prolonged bouts of sitting at work with exercise snack breaks. Methods: The MOV’D pilot study aimed to recruit approximately 60-80 participants who work full-time in a sedentary occupation. Using a randomized 2-group design, participants were randomly assigned either to the “Fitbit Control'' or the “MOV’D” experimental group. The pilot study had a 4-week active intervention and a 4-week follow-up with assessments at baseline, 4-weeks, and 8-weeks. The Fitbit control group received a Fitbit to self-monitor their physical activity prior to getting intervention material at the end of the study. In addition to the Fitbit, the MOV’D intervention features included: a private social support group chat seeded with daily experimenter prompts; weekly, 5-minute behavior change technique videos; daily self-monitoring, and daily exercise snack suggestion videos. Results: Study enrollment began in March 2022 and concluded in June 2022. Data collection concluded in October 2022. We enrolled 70 participants and 68 participants completed all study assessments. Conclusions: This protocol integrates findings from education, behavioral sciences, sedentary behavior, and exercise physiology to promote building an exercise snack habit at work: taking short, intense exercise breaks to break up prolonged sitting. Results from this pilot study will assess the feasibility and acceptability of the MOV’D intervention. Clinical Trial: NCT05360485
Background: Sleep disturbance is one of the most common health concerns reported by breast cancer (BC) survivors and is associated with poor quality of life (QoL) and greater mortality after treatment...
Background: Sleep disturbance is one of the most common health concerns reported by breast cancer (BC) survivors and is associated with poor quality of life (QoL) and greater mortality after treatment. Cognitive behavior therapy for insomnia (CBTi) has shown efficacy for improving sleep and quality of life for BC survivors. Considered the gold standard insomnia treatment, CBTi can be delivered remotely, including via digital intervention. Despite the potential for wider dissemination of CBTi via digital means, these modalities have unique challenges, including technology barriers and poor adherence. We developed a conversational agent (CA) to deliver CBTi via short message service (SMS), supported by mobile-ready web content. Named “Cecebot”, this CA delivers sleep education, implements sleep compression, provides just-in-time intervention on sleep-disrupting behaviors, and includes enhanced support for physical activity (PA) beyond what is typically included in CBTi. This represents a novel modality for a CBTi and PA intervention in BC survivors. Objective: We aim to examine the safety and acceptability of the Cecebot intervention for BC survivors with symptoms of insomnia and explore intervention efficacy. Methods: This trial will recruit 60 BC survivors who are experiencing moderate to severe sleep disturbance. Participants will be assigned to the Cecebot intervention or waitlist control group at a 1:1 ratio. The treatment group will receive Cecebot intervention during weeks 1-6 of the study, while the waitlist control condition will receive the Cecebot intervention during weeks 6-12. The Cecebot intervention utilizes SMS technology paired with Fitbit. Participants will be assessed at baseline, week 6, and week 12. Measurements will include feasibility and acceptability, and explore the effect of a Cecebot intervention. Results: Recruitment of participants began in Spring 2024. The completion of data collection is anticipated to be by Winter 2025. Conclusions: The study results will give insight into the potential for an SMS-based conversational agent to improve sleep in BC survivors with sleep disturbances.
Background: Ventricular fibrillation (VF) is a vicious arrhythmia usually generated after removal of the aortic cross-clamp (ACC) in patients undergoing open heart surgery, which could damage cardiomy...
Background: Ventricular fibrillation (VF) is a vicious arrhythmia usually generated after removal of the aortic cross-clamp (ACC) in patients undergoing open heart surgery, which could damage cardiomyocytes, especially in patients with left ventricular hypertrophy (LVH). Amiodarone has the prominent properties of converting VF and restoring sinus rhythm. However, few studies concentrated on the effect of amiodarone before ACC release on reducing VF in patients with LVH. Objective: The study was designed to explore the effectiveness of prophylactic intravenous amiodarone in reducing VF after the release of ACC in patients with LVH. Methods: Fifty-four patients with LVH scheduled for open-heart surgery were enrolled and randomly divided (1:1) into two groups: group A (amiodarone group) and group P (placebo-controlled group). Thirty minutes before removal of the ACC, the trial drugs were administered intravenously. In group A, 150 mg of amiodarone was pumped in 15 minutes. In group P, the same volume of normal saline was pumped in 15 minutes. The primary outcome was the incidence of VF 10 minutes after removal of the ACC. Results: The incidence of VF was lower in group A than in group P (29.6% vs 70.4%, P = 0.003). The duration of VF, the number of defibrillations, and the defibrillation energy were also lower in group A than in group P (P < 0.05). After the end of cardiopulmonary bypass, the heart rate and mean arterial pressure were lower in group A, the mean pulmonary arterial pressure and the dose of vasoactive drugs was higher than those in group P (P < 0.05). However, there were no significant differences in the use of vasoactive-inotropic agents and hemodynamic status between the two groups before the end of surgery (P > 0.05). Conclusions: In patients with LVH who undergo open-heart surgery, amiodarone can be safely used and reduce the incidence of VF, the duration of VF, the frequency of defibrillation and the energy of defibrillation after ACC removal. Clinical Trial: Chinese Clinical Trial Registry, ChiCTR2000035057; https://www.chictr.org.cn/showprojEN.html?proj=57145
Background: The aim of this study was to develop and validate a nomogram for predicting cancer-specific survival (CSS) in individuals suffering from lower limb melanoma (LLM) at 3-, 5-, and 8-year int...
Background: The aim of this study was to develop and validate a nomogram for predicting cancer-specific survival (CSS) in individuals suffering from lower limb melanoma (LLM) at 3-, 5-, and 8-year intervals following diagnosis. Objective: The aim of this study was to develop and validate a nomogram for predicting cancer-specific survival (CSS) in individuals suffering from lower limb melanoma (LLM) at 3-, 5-, and 8-year intervals following diagnosis. Methods: Patient data pertaining to lower limb melanoma (LLM) cases were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. By employing a random selection process, a training cohort consisting of 70% of the patient population and a validation cohort comprising 30% of the patients were established. Utilizing a backward stepwise Cox regression model, independent prognostic factors were identified. These factors were subsequently integrated into the nomogram, enabling the prediction of cancer-specific survival (CSS) rates at 3-, 5-, and 8-year intervals after diagnosis. The nomogram's performance was evaluated through various metrics, including the concordance index (C-index), the area under the time-dependent receiver operating characteristic curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration curves, and decision-curve analysis (DCA). Results: This study involved a comprehensive cohort comprising 12,580 patients diagnosed with lower limb melanoma (LLM). Through an analysis of the Cox regression model within the training cohort, a total of nine prognostic factors were identified, namely age, RNP (regional node positive), sex, race, AJCC (American Joint Committee on Cancer) stage, surgical status, chemotherapy status, radiation status, and income status. Subsequently, a nomogram was developed and subjected to rigorous internal and external validation procedures. The nomogram demonstrated excellent discriminatory abilities, as reflected by significantly high C-index and AUC values. Calibration curves provided further confirmation of the nomogram's reliability. Notably, the nomogram exhibited superior performance compared to the AJCC model, as evidenced by improved NRI and IDI values. The decision-curve analysis (DCA) curves further validated the clinical utility of the nomogram, underscoring its practical relevance in prognostication for patients with LLM. Conclusions: The current investigation has effectively developed and validated an initial nomogram for prognosticating outcomes in patients with lower limb melanoma (LLM). The nomogram's impressive performance and practical applicability highlight its potential usefulness within clinical settings. However, it is important to note that additional external validation is necessary to further substantiate its reliability and generalizability.
Background: Cancer care complexity heightens communication challenges between healthcare providers and patients, impacting their treatment adherence. This is especially evident upon hospital discharge...
Background: Cancer care complexity heightens communication challenges between healthcare providers and patients, impacting their treatment adherence. This is especially evident upon hospital discharge in patients undergoing surgical procedures. Digital health tools offer potential solutions to address communication challenges seen in current discharge protocols. Objective: We aim to evaluate the usability and acceptability of an interactive health platform among discharged patients who underwent oncology-related procedures Methods: A four-week observational study was conducted. Following hospital discharge, a tablet equipped with an integrated Personal Virtual Assistant (PVA) system was provided to patients who underwent oncology-related procedures. The PVA encompasses automated features that provide personalized care plans, developed through collaboration among clinicians, researchers, and engineers from various disciplines. These plans include guidance on daily specific assignments that were divided into 4 categories: medication intake, exercise, symptom surveys, and post-procedural specific tasks. The primary aim assessed the feasibility of the PVA by quantification of dropout rate <10%, and adherence to each care plan category throughout the study duration. The secondary aim assessed acceptability of the PVA via a Technology Acceptance Model (TAM) questionnaire that examined ease of use, usefulness, attitude towards use, and privacy concerns. Results: Seventeen patients were enrolled. However, 1/17 (5.8%) patients dropped out from the study after 3 days due to health deterioration, leaving 16/17 (94.2%) completing the study (54.5±12.7 years old, 52% Caucasian, 82% gynecological disease, 18% hepatobiliary disease). At the study endpoint, adherence to care plan categories were: 78% for medications, 81% for exercises, 61% for surveys, and 58% for tasks. There was an 80% patient endorsement (strongly agree + agree/very easy + easy) across all TAM categories. Conclusions: The PVA is a feasible and acceptable tool for discharged patients undergoing oncology-related procedures, showing reproducibility for a future clinical study assessing effectiveness.
Background: Artificial intelligence has been deemed revolutionary in medicine, but very few artificial intelligence solutions have been observed in Danish general practice. General practice in Denmark...
Background: Artificial intelligence has been deemed revolutionary in medicine, but very few artificial intelligence solutions have been observed in Danish general practice. General practice in Denmark has an excellent system of digitization to develop and utilize artificial intelligence. However, a lack of involvement of general practitioners in the development of artificial intelligence exists. The perspectives of general practitioners as end users are essential to facilitate the development and implementation of artificial intelligence in general practice. Objective: This study aimed to characterize the prerequisites that must be met to enable the development and implementation of artificial intelligence in Danish general practice. Methods: This study applied semi-structured interviews and vignettes to gain perspectives on the potential for developing and implementing artificial intelligence among general practitioners. Twelve general practitioners were interviewed, resulting in an exhaustive dataset. The interviews were transcribed, and thematic analysis was conducted to identify the dominant themes throughout the data. Results: Four main themes were identified in the data analysis as prerequisites that general practitioners found important to consider when developing and implementing AI in general practice: ‘AI must begin with the low-hanging fruit’, ‘AI must be meaningful in the GP’s work’, ‘The GP-patient relationship must be maintained despite AI’, and ‘AI must be a free, active, and integrated option in the EHR’. Conclusions: The four themes contributing to defining prerequisites for artificial intelligence can potentially lead the first steps of future development and implementation of artificial intelligence in Danish general practice. The participating general practitioners were positive towards developing and implementing artificial intelligence in their clinics, and it would be valuable to consider the defined prerequisites when considering new artificial intelligence tools for general practice.
Background: Background: There is a notable lack of psychotherapeutic services tailored to the needs of Black, Brown, People of Color (BBPOC) who are Two Spirit, transgender, and nonbinary (2STNB); res...
Background: Background: There is a notable lack of psychotherapeutic services tailored to the needs of Black, Brown, People of Color (BBPOC) who are Two Spirit, transgender, and nonbinary (2STNB); research indicates that 2STNB BBPOC clients report a lack of competence and cultural humility on the part of their therapists. Objective: Objective: The purpose of this study was to report the feasibility and acceptability of the Healing through Ongoing Psychological Empowerment (HOPE) Intervention using deductive content analysis. Methods: Method: At baseline, 51 clients were enrolled in the open clinical trial, with 49 BBPOC 2STNB clients starting and completing HOPE Intervention. Clients completed up to 15 free virtual therapy sessions that were provided by nine BBPOC 2STNB therapists. Feasibility and acceptability interviews were conducted at prior to the intervention, immediately following the intervention, and 6-month after completing the intervention. Results: Results: The HOPE intervention demonstrated high feasibility and acceptability, specifically regarding data collection, psychometric adequacy, interventionist recruitment/training/retention, delivery of the intervention, acceptability of the intervention to clients, and client engagement with the intervention. Conclusions: Conclusion: These findings propose HOPE as a potentially feasible, culturally specific therapeutic approach for the BBPOC 2STNB community. Future randomized controlled trials comparing HOPE to existing evidence-based treatments are needed. Clinical Trial: Trial registration: The registration number for this clinical trial is ClinicalTrials.Gov: NCT 05140174.
Background: Maternal mortality remains a persistent public health concern in Sub-Saharan African countries such as Ethiopia. Previous research has shown that when healthcare facilities do not have the...
Background: Maternal mortality remains a persistent public health concern in Sub-Saharan African countries such as Ethiopia. Previous research has shown that when healthcare facilities do not have the necessary supplies to provide basic emergency obstetric care (BEmOC), women experiencing these emergencies can receive delayed diagnosis/treatment or suboptimal care. Health information technology solutions are a flexible and low-cost method for tracking medical supply availability. Furthermore, these solutions can lead to improved health outcomes, and have displayed proven benefits in low-to-middle income country health systems. Objective: The purpose of this study was to develop and evaluate the usability of electronic dashboards to monitor facility-level readiness to manage basic emergency obstetric care (BEmOC) in Amhara, Ethiopia. Methods: The study used three methods to iteratively refine the dashboards: (1) user-centered design sessions with individuals who interact with the BEmOC supply chain; (2) review and feedback from domain and information visualization subject matter experts (SMEs) to refine the dashboards; and (3) usability heuristic evaluations from human-computer interaction (HCI) SMEs. Results: User-centered design sessions resulted in a preliminary version of the dashboards informed by end-user preferences and perceptions. Next, domain and visualization SMEs continued the dashboards’ iterative refinement, by confirming design choices and recommending changes to enhance the dashboards’ navigation. HCI SMEs rated the dashboards as highly usable (0.82 on a scale of 0-4). Conclusions: Dashboards are a novel method for promoting and tracking a facility’s capacity to manage BEmOC. By including targeted end-users and experts in the design process the team was able to tailor the dashboards to meet user needs, fit into the existing government health systems, and ensure that the dashboards follow design best practices. Collectively, the novel, customized BEmOC dashboards can be used to track and improve facility readiness in Amhara, Ethiopia, and similar global BEmOC facilities.
Background: With the development of informatics in nursing and the advancement of modern technologies, handwriting a schedule on paper has become an obsolete practice. The introduction of electronic t...
Background: With the development of informatics in nursing and the advancement of modern technologies, handwriting a schedule on paper has become an obsolete practice. The introduction of electronic timetables in nursing is a measure of the digitalization of nursing, with many different outcomes for both patients and nurses, which can be either positive or negative. Objective: The purpose of this literature review is to identify the evidence of the outcomes of the digitalization of schedules in nursing. Methods: To find out what are the digital nursing schedule outcomes, we undertook a systematic review study method of the literature in electronic databases. Data was gathered in electronic databases: CINAHL, Medline, Cochrane Library, PubMed, ScienceDirect, JSTOR and SpringerLink. We searched through the literature in electronic databases. Seventy-four relevant literature items were identified according to the aim and objective of the study. Results: Eleven studies published between 2015 and 2024 were evaluated and critically analysed using the JBI Critical Appraisal Checklist: four systematic literature reviews; three case studies; three quasi-experimental methods and one quantitative descriptive method. Conclusions: The literature on electronic schedules in nursing shows a variety of positive and negative impacts on nurses, patients and healthcare organizations. The introduction of electronic schedules in nursing is mainly a positive measure which, if appropriately implemented, leads to better patient health outcomes and increased job satisfaction among nurses. Our study offers an outlook on the outcomes of using digital nursing schedules. The outcomes apply to both patients and nurses and are mostly positive, although more research is needed on that topic. Clinical Trial: -
Background: Although anthocyanin-rich foods have been associated with health benefits, it is unclear how well these effects extend to older adults and common geriatric syndromes. In addition, many st...
Background: Although anthocyanin-rich foods have been associated with health benefits, it is unclear how well these effects extend to older adults and common geriatric syndromes. In addition, many studies have relied upon supplements or food extracts, and the effects of whole-food supplementation remain uncertain. Objective: To determine the effectiveness of highbush blueberry supplementation, compared with an isocaloric serving of Deglet Noor dates, on blood pressure, physical function, falls, cognition, and other domains relevant to older adults. Methods: We are conducting a single-center randomized controlled trial among older adults residing in the greater Boston, MA region. Eligible participants include women and men aged 70 years and older. The trial was planned for conduct at a single congregate living facility for older adults, but after the COVID-19 pandemic hit, the initial recruitment was moved to an alternate senior congregate living facility and has subsequently been expanded to a second facility and the larger community. Participants are randomized on a 1:1 basis to consume 1 cup of frozen blueberries or 2-3 pitted dates daily for 3 months. Following a one-week wash-out, participants attend a fasting baseline visit that includes phlebotomy, questionnaires, functional assessments, anthropometric measurements and 24-hour electrocardiographic monitoring and ambulatory blood pressure monitoring. Participants return after 3 months for identical measurements. Recruitment was planned for 70 individuals with 15% attrition. Results: Recruitment for the trial began in April 2022 and ended in April 2024, when the originally planned number of completers was reached. The final population included 61 participants with a median age of 76 years (range 70-94 years), 56% women, and 53% assigned to blueberries. The demographic characteristics of enrolled participants demonstrate the tradeoffs of recruitment based in senior congregate living facilities, with unusually advanced ages but limited racial diversity and a fixed pool of potential participants. Conclusions: This randomized trial will test the effectiveness of whole highbush blueberry supplementation, compared with an isocaloric serving of dates, upon physiological and clinical parameters of interest to older adults. With its emphasis on whole foods, its results will add to a growing number of studies that test the effects of anthocyanins on common chronic diseases of aging. Clinical Trial: The trial is registered at clinicaltrials.gov (NCT05358210).
Background: Discrimination can greatly impact both physical and mental health due to frequent stressors. Younger individuals, particularly those under 17 years old, are more adversely affected by vict...
Background: Discrimination can greatly impact both physical and mental health due to frequent stressors. Younger individuals, particularly those under 17 years old, are more adversely affected by victimization. Within the European Union, Romania exhibits poor rankings concerning LGBT+ inclusion. Notably, half of Romanian respondents aged 15-17 have reported experiencing bullying due to their sexual orientation. Given that much of this discrimination and harassment occurs within schools, schoolteachers and counselors are vital in affecting institutional change. Objective: This study investigates the impact of an intervention on reducing prejudice against the LGBT community in Romanian schoolteachers and counselors. Most prior interventions of this nature target WEIRD (Western, educated, industrialized, rich, and democratic) populations. Methods: In this randomized control trial, we recruited 175 participants via a national closed online user group and assigned them to either the experimental or control condition. Participants in the experimental condition received the intervention first and then completed the web-based outcome measures, while those in the control condition completed the measures first and then received the intervention. The intervention, designed for internet-based delivery, consisted of a one-hour video session led by a pair of researchers. It blended educational information with testimonials of LGBT+ people, perspective-taking tasks, and a self-efficacy exercise. We measured LGBT prejudice using three scales (ATLG, HS, and ATH). As additional outcomes, we looked at behavioral intentions, self-efficacy, perspective taking, intergroup disgust sensitivity, intergroup anxiety, empathy, factual knowledge about LGBT issues, as well as participant’s feelings towards LGB individuals. Results: Participants in the experimental group (N=89) showed significant reductions in prejudice when using the ATLG Scale (F1,173=7.22, P=.008) when compared to the control group (N=86), but not when using the other two attitudinal scales. We also found that the experimental group had warmer feelings (F1,173=4.40, P=.037; d=0.32), were more likely to engage in supportive behaviors (F1,173=13.96, P<.001; d=0.56), displayed more self-efficacy (F1,173=9.14, P=.001; d=0.33), had more factual knowledge (F1,173=11.98, P=.001; d=0.52), and had a higher ability to take the LGBT+ perspective after controlling for contact (F1,172=4.77, P=.030; d=0.28).
We did not observe significant differences in terms of Intergroup Disgust Sensitivity (F1,173=.816, P=.37), Intergroup Anxiety for either positive (F1,173=.383, P=.54) or negative emotions (F1,173=.51, P=.48), or empathy (F1,173=.02, P=.89). Conclusions: The intervention stands as a highly valuable and cost-effective resource for educators and high school counselors, particularly in regions where negative attitudes toward the LGBT+ community are prominent. The results show that a single one-hour online session, integrating blended cognitive (information), affective (indirect contact, perspective taking), and behavioral (self-efficacy, empowerment) recommendations, is sufficient in producing positive outcomes related to LGBT+ issues within the school environment. Clinical Trial: ISRCTN 84290049; https://doi.org/10.1186/ISRCTN84290049
Background: Access to safe abortion care is a reproductive right for all individuals across Canada. Underserved populations are over-represented among those with unintended pregnancies and particularl...
Background: Access to safe abortion care is a reproductive right for all individuals across Canada. Underserved populations are over-represented among those with unintended pregnancies and particularly those seeking abortion. Yet, few resources exist to help healthcare and allied helping professionals provide culturally competent, and gender-affirming abortion care for underserved populations. Objective: This project aimed to redesign and adapt an existing subscription-based medication abortion mentorship platform into a culturally appropriate and gender-affirming open-access website of curated health professional resources to promote equitable, accessible, high-quality abortion care, particularly for underserved populations Methods: We drew on a user-centered design framework to redesign the web platform in five iterative phases. Healthcare and allied helping professionals were engaged in each stage of the development process including the initial design of the platform, curation of the resources, reviewing the content, and evaluation of the wireframes and the end product. Results: This project resulted in an open-access bilingual (English and French) online platform containing comprehensive information and resources on abortion care for healthcare providers (physicians, nurse practitioners, and pharmacists) and allied helping professionals (midwives, medical officers, community workers, and social workers). The website incorporated information on clinical, logistical, and administrative guidance, including culturally competent and gender-affirming toolkits that could equip healthcare professionals with the requisite knowledge to provide abortion care for underserved populations. Conclusions: This platform contains resources that can increase the competencies of healthcare professionals to initiate and sustain culturally and contextually appropriate abortion care for underserved groups while clarifying myths and misconceptions that often militate against initiating abortion. Our resource also has the potential to support equitable access to high-quality abortion care, particularly for those among underserved populations who may have the greatest unmet need for abortion services yet face the greatest barriers to access to care
Background: Health-related data from technological devices are increasingly obtained through smartphone apps and wearable devices. These data can be used to enable physicians and other care providers...
Background: Health-related data from technological devices are increasingly obtained through smartphone apps and wearable devices. These data can be used to enable physicians and other care providers to monitor patients outside the clinic or assist individuals in improving lifestyle factors. However, the use of health technology data might be hampered by the reluctance of patients to share personal health technology data because of the privacy sensitivity of this information. Objective: The present study investigates to what extent psychological factors play a role in people’s willingness to share personal health technology data. Methods: Data for this cross-sectional study were obtained by quota sampling on age and sex in a community-based sample (N= 1013; mean age = 48.6 (SD = 16.6) years; 51.5% women). Willingness to share personal health technology data and related privacy concerns were assessed using an 8-item questionnaire with good psychometric properties (Cronbach’s α = .82). Psychological variables were assessed using validated questionnaires for optimism (LOT-R), psychological flexibility (PFQ), negative affectivity (DS14-NA), social inhibition (DS14-SI), generalized anxiety (GAD-7) and depressive symptoms (PHQ-9). Data were analysed using multiple linear regression analyses and network analysis was used to visualise the associations between the item scores. Results: Higher levels of optimism (β = 0.093, p = .004), psychological flexibility (β = 0.127, p < .001) and lower levels of social inhibition (β = -0.096, p = .002) were significantly associated with higher levels of willingness to share health technology data when adjusting for age, sex and education level in separate regression models. Other associations with psychological variables were not statistically significant. Network analysis revealed that psychological flexibility clustered more towards items that focussed on the benefits of sharing data, while optimism was negatively associated with privacy concerns. Conclusions: The current results suggest that people with higher levels of optimism and psychological flexibility and those with lower social inhibition levels are more likely to share health technology data. Future studies are needed to identify the specific needs of people with these characteristics regarding data sharing such that optimal use of devices in healthcare can be facilitated.
Background: Abstract (237 words)
The American Civil War has been commemorated with a great variety of monuments,
memorials, and markers. These monuments were erected for a variety of reasons, begi...
Background: Abstract (237 words)
The American Civil War has been commemorated with a great variety of monuments,
memorials, and markers. These monuments were erected for a variety of reasons, beginning with
memorialization of the fallen and later to honor aging veterans, commemoration of significant
anniversaries associated with the conflict, memorialization sites of conflict, and celebration of
the actions of military leaders. Sources reveal that during both the Jim Crow and Civil Rights
eras, many were erected as part of an organized propaganda campaign to terrorize African
American communities and distort the past by promoting a ‘Lost Cause’ narrative. Through
subsequent decades, to this day, complex and emotional narratives have surrounded interpretive
legacies of the Civil War. Instruments of commemoration, through both physical and digital intervention approaches, can be provocative and instructive, as the country deals with a slavery legacy and the commemorated objects and spaces surrounding Confederate inheritances.
Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question. Objective: I describe monuments as symbols in the “Lost Cause” narrative and their place in enduring Confederate legacies. I make the case, and offer documented examples, that remnants of the monuments, such as the “decorated” pedestals, if not the original towering statues themselves, should be left in place as sites of reflection that can be socially useful in public interpretation as disruptions of space, creating disturbances of vision that can be provocative and didactic. I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Methods: This article addresses several elements within the purview of the Journal: questions of contemporary society, diversity of opinion, recognition of complexity, subject matter of interest to non-specialists, international relevancy, and history. Drawing from the testimony of scholars and artists, I address the contemporary conceptual landscape of approaches to the presentation and evolving participatory narratives of Confederate monuments that range from absolute expungement and removal to more restrained responses such as in situ re-contextualization, removal to museums, and preservation-in-place. In a new era of social justice surrounding the aftermath of dramatic events such as the 2015 Charleston shooting, the 2017 Charlotteville riot, and the murder of George Floyd, should we see them as symbols of oppression, inviting expungement, or selectively as sites of conscience and reflection, inviting various forms of re-interpretation of tangible and intangible relationships?
I describe monuments as symbols in the “Lost Cause” narrative and their place in enduring Confederate legacies. I make the case, and offer documented examples, that remnants of the monuments, such as the “decorated” pedestals, if not the original towering statues themselves, should be left in place as sites of reflection that can be socially useful in public interpretation as disruptions of space, creating disturbances of vision that can be provocative and didactic. I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Results: I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Conclusions: Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question.
Background: The COVID19 pandemic has caused a large number of infections and fatalities, causing administrations
at various levels to limit public mobility. This paper analyzes the complex associatio...
Background: The COVID19 pandemic has caused a large number of infections and fatalities, causing administrations
at various levels to limit public mobility. This paper analyzes the complex association between the
stringency of restrictions, public mobility, and reproduction rate (R-value) on a national level for Germany. Objective: The goals were to analyze; a) the correlation between government restrictions and public mobility and b)
the association between public mobilities and virus reproduction. Methods: In addition to correlations, a Gaussian
Process Regression Technique is used to fit the interaction between mobility and R-value. Results: The main
findings are that: (i) Government restrictions has a high association with reduced public mobilities,
especially for non-food stores and public transport, (ii) Out of six measured public mobilities, retail,
recreation, and transit station activities have the most significant impact on COVID19 reproduction rates. Conclusions: A mobility reduction of 30% is required to have a critical negative impact on case number dynamics,
preventing further spread.
This paper discusses the specific characteristics of any hypothetical cognitive space that may be modelled in
order to automate (or partially automate) the kind of mental health clinical reasoning -...
This paper discusses the specific characteristics of any hypothetical cognitive space that may be modelled in
order to automate (or partially automate) the kind of mental health clinical reasoning - clinical or psychological
case formulation - that is used by mental health professionals. It argues that work into the use of generative
artificial intelligence (AI) in the field of mental health needs to consider three components of this kind of
clinical reasoning. Firstly, heterotopy. When mental health clinical reasoning statements are made, parsing them
does not result in the same representation when the same words are used, due to the fact that mental health
ontologies contain multiple meanings for the same words. Secondly, orthogonality. Variables relevant to mental
health may not causally intersect but may both be relevant for clinical case formulation and treatment
determination. Thirdly, veridicality. The truth of a clinical case formulation may not be determined by any
testable observations. Even treatment response may not allow for a determination of truth., The truth status of a
clinical case formulation may hinge principally on the degree to which it confers meaning or understanding of a
mental state on the person who is experiencing that mental state, and that truth may be different to the truth
judgements of a mental healthcare clinician. Automated clinical case formulation models need to accommodate
for these features of the cognitive space of mental health clinical case formulation.
Background: Exercise intervention is effective in managing diabetes when delivered in a personalized manner. Personalization of exercise intervention following a systematic fitness assessment can lead...
Background: Exercise intervention is effective in managing diabetes when delivered in a personalized manner. Personalization of exercise intervention following a systematic fitness assessment can lead to better health outcomes Objective: This study aimed to analyze the effect of digitally delivered fitness assessments and exercise prescriptions on the fitness and health outcomes of people with diabetes. Methods: Participants diagnosed with type 2 diabetes (n=86) enrolled in the Fitterfly Diabetes program which included interventions in nutrition, fitness, and mental health delivered via a digital platform. The participants underwent a video call-based fitness assessment consisting of the 1-minute push-up test, wall sit test, 1-minute sit-up test, V-sit and reach test, and 6-minute walk test. Trained physiotherapists conducted the assessments, developed personalized exercise plans, and shared them with the participants via the app. Regular follow-ups were taken. The participants were re-assessed after 90 days. Results: There was a statistically significant improvement in the fitness-related outcome measures (p<0.05), the anthropometric measures (p<0.05), and HbA1c (p<0.05) post-intervention. Improvement in exercise duration was associated with better outcomes in fitness tests and anthropometric measures. Conclusions: Personalized exercise intervention delivered digitally can help achieve better health outcomes in people with type 2 diabetes.
Background: The Corona Virus Disease of 2019 (COVID-19) pandemic motivates research efforts to address this catastrophe from the beginning of 2020 year up to the present. The year 2021 is coming to an...
Background: The Corona Virus Disease of 2019 (COVID-19) pandemic motivates research efforts to address this catastrophe from the beginning of 2020 year up to the present. The year 2021 is coming to an end, and there have been several developments in pharmacotherapy for COVID-19. In terms of antiviral therapy, monoclonal antibody combinations become one of COVID-19 immunotherapy. Remdesivir and Favipiravir are the two antiviral medications typically used to treat COVID-19. Objective: The purpose of this study compares the effects of a combination of antibodies (casirivimab and imdevimab), remdesivir, and favipiravir on COVID-19 swab results in COVID-19 hospitalized patients at discharge. Methods: In this study, 265 COVID-19 patients with polymerase chain reaction (PCR) confirmation and indications for antiviral medication were non-randomized into three groups with a ratio of (1:2:2): REGN3048-3051(group A); Remdesivir (group B); Favipiravir (group C). Non-Randomized Single-blind Controlled study was the study design. The study's medication is provided by Hospital of Mansoura University. Following ethical permission, the study was conducted for approximately 6 months. Results: Compared to Remdesivir and Favipiravir, casirivimab and imdevimab cause more negative swab results at discharge. The three antivirals also have no significant adverse effects. All three antivirals are considered safe with these findings. Casirivimab and imdevimab achieve more negative swab results than Remdesivir & Favipiravir. Conclusions: Casirivimab & imdevimab achieve more negative swab results than Remdesivir and Favipiravir. All three antivirals are safe with no significant toxicity. Clinical Trial: Clinical Trial Registration: Clinicaltrials.gov, NCT05502081
Background: The burgeoning volume of scientific literature being generated today places a great burden on evidence reviewers. On average, only 2% to 8% of articles yielded by a search strategy are ult...
Background: The burgeoning volume of scientific literature being generated today places a great burden on evidence reviewers. On average, only 2% to 8% of articles yielded by a search strategy are ultimately included in a systematic review. Due to the burden of increasing information loads, there is a demand for methods that improve efficiency while maintaining accuracy in performing evidence reviews. Objective: This systematic review aims to determine the accuracy and efficiency of AI-assisted abstract selection compared to manual abstract selection, as assessed by diagnostic performance and workload saved over sampling (WSS). Methods: Two reviewers searched PubMed, Proquest, and Cochrane Library for studies evaluating the diagnostic performance and/or workload savings achieved by any AI tool, whether through full or semi-automation, in the title and abstract screening phase of literature review. Variance-weighted random effects meta-analysis was done to generate univariate measures of sensitivity, specificity, and WSS for the studies using RevMan verson 4.3 and the ‘meta’ and ‘mada’ packages on R version 4.3.1. Bivariate analysis was also performed for the measures of diagnostic accuracy and a hierarchal summary operating characteristics curve (HSROC) was generated. Results: Twenty-two studies were included in this review, where 13 reported diagnostic performance, 14 reported WSS, and five studies reported both outcomes. In fully automated workflows, AI tools had a sensitivity of 85.6% (95% CI: 60.8%-95.8%) and a specificity of 88.7% (95% CI: 58.7%-97.7%) with considerable heterogeneity, which likely stems from the differences in the SRs and AI techniques used. In semi-automated workflows, sensitivity was 87.6% (95% CI: 77.2%-93.6%) and specificity was 94.1% (95% CI: 60.0%-99.4%) also with considerable heterogeneity. Among studies on full automation, the median workload savings for 100% recall was 50.0% (IQR: 10.2), while for studies on semi-automation, the median workload savings was 55.6% (IQR: 16.4). Conclusions: Given the findings of this review, the diagnostic performance of AI tools appeared to be superior when used in semi-automated workflows rather than fully automated ones. This suggest that AI tools hold great potential in augmenting the accuracy and efficiency of human reviewers during study selection in literature review.
Infrapubic penile implant surgery is a viable option for patients with severe penile curvature, shortening, and impaired penile rigidity due to fibrosis of the corpora cavernosa (Sadeghi-Nejad, 2007)....
Infrapubic penile implant surgery is a viable option for patients with severe penile curvature, shortening, and impaired penile rigidity due to fibrosis of the corpora cavernosa (Sadeghi-Nejad, 2007). Studies have shown that patients who undergo penile implant surgery, particularly the infrapubic approach, experience significantly better erectile function and treatment satisfaction compared to those receiving other treatments such as sildenafil citrate and intracavernous prostaglandin E1 (Rajpurkar & Dhabuwala, 2003). The infrapubic approach offers advantages such as ease of reservoir placement, rapid implantation, and direct vision during the procedure, as well as avoiding an extra incision on the scrotum, which can hinder rehabilitation (Montague & Angermeier, 2000; Vollstedt et al., 2017). Additionally, it has been noted that the infrapubic approach can be quickly learned by urologists who are already comfortable with the trans‐scrotal approach (Kramer & Chason, 2010). However, it is important to consider the drawbacks associated with the infrapubic approach, such as the higher risk of surgical errors during the placement of the device in the corpora (Kramer et al., 2010).
Background: The research reports the development of a behavioral satisfaction questionnaire (BSQ) for the use in cognitive-behavioral therapies (CBTs). Objective: It is purposed for semi-structured ps...
Background: The research reports the development of a behavioral satisfaction questionnaire (BSQ) for the use in cognitive-behavioral therapies (CBTs). Objective: It is purposed for semi-structured psychoanalytic interviews, but can also be used for self-report. The design of BSQ seeks to organize a referential scale with a psychodynamic perspective, in order to bridge the gaps among neurological / psychiatric therapies, psychological therapy, and patient / visitor autonomy. Methods: The psychometric evaluations are dissected into different dimensions in the questionnaire design, with a paradigmatic conceptual framework. Results: The test trial has demonstrated high affinity with other major psychometric methods. Conclusions: The BSQ design is valid in overall assessments on complicated psychological case. Clinical Trial: The test trial is registered on ClinicalTrials.gov with the identifier NCT05930912.
Background: Interoperability and electronic health records (EHR) standards in medicine Objective: What is the latest evidence related to EHR data interoperability, and standards in medicine? Methods:...
Background: Interoperability and electronic health records (EHR) standards in medicine Objective: What is the latest evidence related to EHR data interoperability, and standards in medicine? Methods: N/A Results: The need for interoperability is evident in every part of a typical health care organization, as many clinicians in a hospital setting need to communicate with their counterparts in the community and as such the EHRs should be able to share data automatically and seamlessly across institutions and display it in useful ways. Conclusions: Currently, a usable and reliable patient data at the point of care regardless of socioeconomic background is critical to the management of patients in medicine, especially the chronically ill.
Background: Due to the varying symptomology of Alzheimer’s disease (AD), primary care providers (PCPs) find it challenging to disentangle normal cognitive age-related dysfunction versus those indivi...
Background: Due to the varying symptomology of Alzheimer’s disease (AD), primary care providers (PCPs) find it challenging to disentangle normal cognitive age-related dysfunction versus those individuals on the clinical pathway of AD. Mobile health (mHealth) technology shows great potential in for improving health outcomes because of its mobility, instantaneous access for both the patient and PCP, and ease of use. Objective: This critical review aims to summarize findings from other reviews published recently on mHealth platforms used in remote cognitive screening or therapy for AD. Methods: Rapid scoping review techniques were still used to synthesize and create a broad understanding of mHealth platforms and it usage in AD screening or therapy. The PubMed data base was searched on November 8, 2023, for relevant reviews using the strategy mobile and cognitive impairment: “((mhealth) OR (mobile health)) AND (subjective cognitive decline OR mild cognitive impairment OR Alzheimer disease)”. Limits were placed in terms of article type (systematic review or review), and language (English). Results: The initial search identified 23 unique citations. The titles and abstracts were assessed based on the inclusion criteria, and of the 23 unique citations, 7 (30%) were excluded after title and abstract screening. Of those remaining, 5 (2%) were excluded as they were not relevant to the topic, 2 (9%) did not include mHealth components, 1 (4%) did not include AD-related outcome and 1 (4%) was a narrative review. Hence, of the 16 (70%) reviews included for full-text screening, 7 (30%) were included in the research synthesis. Conclusions: mHealth platforms have the potential to increase cognitive screening uptake and allow PCPs to remotely monitor their patients, provide support to caregivers and collect relevant health data. Yet, some important considerations are cognitive test features (i.e., characteristics, duration or frequency, psychometric properties), characteristics of patient (experience, knowledge and support with technology), usability of platform, and delivery method. Future interventions should consider incorporating social media platforms like WhatsApp or Facebook, to offer more customized, educational services to patients and their caregivers. Clinical Trial: N/A
