Psychology International

Trichotillomania (TTM) is a psychiatric disorder involving chronic, recurrent urges to pull out one’s own hair, arising frequently in childhood and early adolescence. This disorder predominantly affects women and has a high co-morbidity with many other psychiatric conditions. Currently, the etiology is unknown, which makes treating TTM extremely difficult. While the epidemiology and proposed causes will be discussed briefly, the primary purpose of this review is to provide a comprehensive, updated summary of the psychological and pharmacological management options for patients diagnosed with TTM, as new clinical trial data for previously studied and novel treatments have become available within the last decade. Of the behavioral interventions, cognitive behavioral therapy (CBT) and habit reversal training (HRT) have demonstrated the greatest improvements in hair-pulling severity, with HRT showing the most efficacy for long-term maintenance of progress. Pharmacological therapies with the most success include Olanzapine, Clomipramine, and N-Acetylcysteine, though larger replication studies are needed. Selective serotonin reuptake inhibitors (SSRIs) have yielded inconsistent results in clinical trials, yet they are frequently prescribed for TTM. Naltrexone, Dronabinol, and Inositol are emerging as potential treatments, but the results suggest that additional studies are needed. Future research directions include larger placebo-controlled pharmacological trials, exploring the efficacy of combined behavioral and pharmacological approaches compared to monotherapy, and delving into the potential genetic and neurochemical contributions that may underlie TTM. Full article

Position effects occur when changes in item positions on a test impact the test outcomes (e.g., item parameters or test scores). Previous studies found that position effects may vary by the testing context and conditions and thus affect each test-taker differently. With the increasing adoption of digital assessments involving innovative item types that are focused on problem-solving skills, it is also essential to study position effects within this context. This study incorporates item-level scores and screen-level response time data from the Trends in International Mathematics and Science Study (TIMSS) 2019 problem-solving and inquiry tasks for Grade 4 students to examine position effects on students’ ability and test-taking speed. This dataset included responses from 27,682 students from 36 countries. A structural equation modeling approach was employed to model ability and test-taking speed within the same model. The results indicated a small but statistically significant booklet effect on students’ overall mathematics and science ability. The impact of block position changes within the booklets seemed to be greater than the impact of a reordering of subjects tested in the two sessions. The results also showed that when an item block was placed earlier in a test session, students spent more time on the items and performed better. The implications of these findings are discussed. Full article

As the robust maximum likelihood ${\chi }^2$ goodness-of-fit test had been found to yield inflated type-I error rates for certain two-level confirmatory factor analysis (CFA) models, a new correction for the test was implemented in Mplus version 8.7. In this simulation study, we inspected whether the corrected test statistics follow the expected ${\chi }^2$ distributions when applying more complex two-level models for multitrait-multimethod data with varying sample sizes and correlations within trait factors. Investigating rejection rates and probability-probability plots, we found that the new correction markedly and sufficiently reduced previously inflated rejection rates in conditions with within-trait correlations equal to 1, 100 between-level units, and 10 or 20 within-level units. In other conditions, rejection rates were hardly affected or not sufficiently reduced by the new correction. While in most conditions, 2 within-level units did not suffice, 5 within-level units and 250 between-level units were enough to yield correct rejection rates given within-trait correlations did not exceed 0.80. Correlations above 0.80 required larger sample sizes. In planning studies with multilevel CFA models, researchers should be aware that sample size requirements for likelihood-based model fit evaluations can depend on several different factors and might consider conducting Monte Carlo simulations tailored to their specific modeling conditions. Full article

This paper will argue that memory from early childhood underlies many practices and beliefs that we commonly refer to as “religious”. The consciousness of young children does not yet have certain features that characterize adult consciousness. This paper will concentrate on four of these: (I) a reality that is recognizable; (II) a sense of temporal duration; (III) a sense of self; (IV) an experience of the world that is deeply affected by our acquaintance with (a) language. The absence of these features presumably characterizes the consciousness of infants. It also often characterizes mystical experiences. The paper will argue that the human tendency to engage in so-called religious practices and beliefs makes the most sense based on the assumption that adults somehow preserve the memory of their state of being in childhood. Full article

Background. Network motif analysis is a technique used to explore recurrent and statistically significant subgraphs within a network. Applying a motif analysis to the complex network of inflammation and depression may yield nuanced insight into the specific interaction mechanisms between inflammatory markers and individual depression symptoms, which is our aim. Methods. This cross-sectional study is based on patients with stable coronary heart disease (CHD). A partial correlation network was initially constructed to link inflammatory markers, including C-reactive protein (CRP), Interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 (MCP-1), individual depression symptoms, and covariates. A network-centric approach searched all possible non-isomorphic subgraph patterns of size k = 4 in the network. Results. Although CRP, IL-6, and TNF-α displayed an insignificant association with specific depression symptoms, the motif analysis revealed various subgraph patterns of interactions between depression symptoms associated with MCP-1. Generally, MCP-1 formed a closed loop with psychomotor problems and sleep disturbances, and this configuration was connected in various forms with other symptoms, particularly cognitive (e.g., feelings of worthlessness, concentration difficulty, and suicidal ideation) and neurovegetative/somatic (e.g., appetite changes and fatigue) symptoms. Moreover, MCP-1 was frequently associated with a closed-loop triangle comprising cognitive and neurovegetative/somatic symptoms but not with mood symptoms (e.g., loss of interest and feelings of sadness). Conclusions. The findings provide insight into how MCP-1 may be involved in the pathology of depression among patients with stable CHD in a more precise manner. This study also proposes future directions for research on depression. Full article