BACKGROUND:Healthy lifestyle beliefs are important for adolescent health promotion, yet they are embedded within broader psychosocial contexts involving family relationships and educational stress. Although these domains are likely to interact, little is known about how their specific components are organized within a broader psychosocial system. This study examined the interrelationships among healthy lifestyle beliefs, educational stress, and family relationship quality among Bangladeshi adolescents using network analysis and directed acyclic graph (DAG) modeling. METHODS:Data from 501 college-attending adolescents in Bangladesh were analyzed using the Healthy Lifestyle Beliefs Scale, the Educational Stress Scale for Adolescents, and the Brief Family Relationship Scale. An undirected Gaussian graphical model was estimated to examine network structure, centrality, bridge centrality, predictability, and stability. Gender differences were assessed using the Network Comparison Test. Directed acyclic graph analyses were conducted at the subscale level to explore statistical dependency structures and edge orientations among domains. RESULTS:The strongest positive edge in the network was observed between family cohesion and family expressiveness (0.520), whereas the strongest negative edge was observed between family cohesion and family conflict (-0.232). Confidence in handling problems effectively emerged as the most central node (strength = 1.325). The strongest bridge node was belief in family support for achieving goals (0.522), followed by belief in achieving personal goals and family expressiveness. Network stability was good (CS-coefficient = 0.75). Gender comparison indicated a significant difference in network structure (p = 0.003), but not in global strength (p = 0.511). DAG analyses identified dependency structures linking family relationships, educational stress, and healthy lifestyle beliefs; edge orientations were interpreted as exploratory rather than as evidence of temporal or causal ordering. CONCLUSIONS:Healthy lifestyle beliefs, educational stress, and family relationship quality were interconnected within a broader psychosocial system among adolescents. Coping-related healthy lifestyle beliefs appear central within this system, while family relational processes and academic stress showed meaningful connections with health-related beliefs. These findings may inform future longitudinal and preventive research examining coping-related beliefs alongside family communication, support, and academic stress.
OBJECTIVES:To compare mental illness prevalence, and agreement between mental illness measures, in home care (HC) and long-term care (LTC) using administrative definitions and Resident Assessment Instrument (RAI)-diagnoses. METHODS:Applying a common protocol to linked administrative-RAI datasets in Alberta, Manitoba, and Ontario, Canada, we selected adults receiving HC or LTC between 2012 and 2023. Cross-sectionally, we compared administrative definitions with RAI-diagnoses (depression, anxiety, bipolar disorder and schizophrenia) using kappa, sensitivity, specificity, positive and negative predictive value. We examined discordance-associated factors using multivariable logistic regression. RESULTS:Depression was the most prevalent mental illness (administrative data, HC: 29%-34% of 493,895 people; LTC: 21%-51% of 357,117 people). Prevalence estimates were consistently lower using RAI-diagnoses than administrative definitions. Agreement between data sources was moderate for depression (k = 0.33-0.57) and anxiety disorders (k = 0.35-0.63). Younger age, dementia, and more physician visits were associated with higher likelihood of discordance between data sources; male sex had a lower likelihood. CONCLUSION:While mental illness prevalence is high in HC and LTC populations, RAI-based estimates are lower than administrative data estimates. Discordance between data sources differs by individual characteristics. Concurrent comparison of RAI-diagnoses and administrative data to a gold standard clinical interview would clarify the optimal surveillance strategy.
BACKGROUND:The development and maintenance of sleep habits are significantly influenced by dysfunctional attitudes and perspectives about sleep. There is a paucity of research on sleep issues in Arab environments, which is probably due to a lack of validated and culturally appropriate assessment instruments. An Arabic version of the Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16) will be psychometrically validated in this study using a sample of college students. METHODS:A total of 670 university students (mean age = 20.38 ± 1.97 years; 59.1% female) participated in a cross-sectional study. To ensure semantic equivalency between the original and Arabic forms, the DBAS-16 scale was translated and modified for use in the current study. The translation team made sure to carefully balance the literal and cultural distinctions. To identify and correct any discrepancies, the original and translated English versions were thoroughly compared. Composite reliability was assessed using McDonald's and Cronbach's α, with values greater than 0.70 reflecting adequate composite reliability. Concurrent validity was examined via correlations with psychological distress (PHQ-4). RESULTS:The four-factor and the second order models demonstrated acceptable fit. Measurement invariance was supported at all levels across genders, with no significant difference in DBAS-16 scores between males and females. Higher DBAS-16 total scores were significantly, albeit modestly, associated with higher psychological distress (PHQ-4), providing evidence of concurrent validity. CONCLUSION:The Arabic translation of the DBAS-16 demonstrated a factor structure similar to the original scale, with acceptable internal consistency, reliability, and measurement invariance across genders. The Arabic DBAS-16 may be useful in both research and clinical settings for assessing dysfunctional sleep beliefs in Arabic speaking populations.
BACKGROUND:Secondary depression frequently develops in people with chronic diseases, and it may hinder disease progress and treatment outcomes. This study aimed to examine the construct validity and measurement invariance of the Arabic version of the Patient Health Questionnaire-9 (PHQ-9) among patients with chronic physical conditions. METHODS:This cross-sectional study used confirmatory factor analysis (CFA) and multigroup CFA to evaluate the Arabic PHQ-9 in a convenience sample comprising patients with cancer, heart failure (HF), and renal failure (RF) from Oman and Yemen. RESULTS:Out of eight models, the unidimensional PHQ-9 (depression) displayed satisfactory fit when three pairs of error were correlated whereas a similar fit was exhibited by a three-factor (somatic, cognitive/affective, and concentration/motor) solution, which was modified into (somatic, affective, and cognitive-psychomotor) solution based on partial scalar analysis tests. This structure was invariant across all sociodemographic characteristics, with better values of reliability coefficients, average variance extracted, and heterotrait-monotrait ratios of correlation. CONCLUSION:The Arabic PHQ-9 is a reliable and psychometrically stable tool that may differentiate depressive symptoms in people with chronic disorders into three symptom groups. Meaningful comparisons between countries support higher psychological burden of physical disorders in Yemen than Oman.
OBJECTIVES:This study translated the UCLA PTSD Reaction Index for DSM-5 into Turkish (PTSD-RI-5-TR), evaluated its psychometric properties, and examined whether PTSD symptom severity predicts functional impairment in Turkish adolescents aged 11-17. METHODS:A total of 157 trauma-exposed adolescents from a tertiary Child and Adolescent Psychiatry Clinic participated. Internal consistency and test-retest reliability were evaluated. Construct validity was examined via confirmatory factor analysis (CFA) of a five-factor model. Convergent, divergent, criterion, and known-groups validity were tested. ROC analysis assessed diagnostic accuracy. Binary logistic regression was used to evaluate the impact of scores on four functional domains. RESULTS:PTSD-RI-5-TR showed good internal consistency and test-retest reliability (acceptable for Category C). CFA indicated excellent fit (CMIN/DF, CFI, TLI, RMSEA) and good fit (GFI, NFI). Scores correlated strongly with NSESSS-PTSD and moderately with DES-B. PTSD diagnoses were associated with significantly higher scores. ROC analysis yielded an AUC = 0.909, sensitivity = 86.4%, specificity = 84.1% with an optimal cutoff score of 49.5. In total score models, each one-point increase predicted impairment in developmental progression (OR = 1.097), home (OR = 1.084), peer (OR = 1.071), and school functioning (OR = 1.063). In symptom cluster models, negative mood/cognition (D) most strongly predicted peer (OR = 1.205) and developmental impairment (OR = 1.155); avoidance (C) predicted home impairment (OR = 1.250); arousal/reactivity (E) predicted home (OR = 1.144) and school impairment (OR = 1.131); intrusion (B) showed no independent effect. CONCLUSION:PTSD-RI-5-TR is a reliable, valid tool for assessing PTSD in Turkish adolescents. Higher total PTSD scores and higher scores in the C, D, and E symptom clusters may indicate a greater likelihood of functional impairment. TRIAL REGISTRATION:This study was prospectively registered at ClinicalTrials.gov (Identifier: NCT06077474 {2023-10-05}).
OBJECTIVES:A systematic review and meta-analysis were conducted to investigate the association between loneliness and hikikomori symptoms. METHODS:We searched three electronic databases (plus hand search). Our review followed the PRISMA guidelines, and a PROSPERO registration was made. We included observational studies determining the association between loneliness and hikikomori symptoms. RESULTS:Eight cross-sectional studies were finally included. Our psychometric meta-analysis revealed a mean corrected correlation of 0.68 (95% CI: 0.62 to 0.74). The mean corrected correlations of loneliness with the subscales socialization, isolation, and emotional support were 0.54 (95% CI: 0.50 to 0.58), 0.62 (95% CI: 0.60 to 0.64), and 0.71 (95% CI: 0.67 to 0.75), respectively. The mean corrected correlation for the association between loneliness and hikikomori symptoms was 0.66 (95% CI: 0.62 to 0.70) among European countries, whereas it was 0.90 (95% CI: 0.81 to 0.99) among Asian countries. Five of the studies were of good quality, and three were of fair quality. CONCLUSION:Our work identified a strong, positive association between loneliness and hikikomori symptoms. Upcoming longitudinal studies are required to clarify the directionality between such factors. There is also a clear need for research in regions that have been neglected so far.
OBJECTIVE:This study aimed to evaluate the validity and reliability of the Turkish version of the Modified Agitation Severity Scale (MASS) among patients diagnosed with schizophrenia and bipolar disorder. METHODS:The study was conducted in the acute male psychiatry unit of a regional mental health hospital in Istanbul, with 136 patients who met the inclusion criteria. The adaptation process involved translation, back-translation, expert review, and pilot testing. Reliability analyses included the Kuder-Richardson Formula 20 (KR-20) for dichotomous scoring and Cronbach's alpha for weighted scoring. Item-total correlations and "alpha if item deleted" values were examined. Construct validity was assessed through correlations with the Overt Aggression Scale (OAS). Criterion validity was evaluated by comparing MASS scores between patients who required clinical intervention and those who did not. RESULTS:The Turkish MASS demonstrated strong internal consistency (KR-20 = 0.863; Cronbach's alpha = 0.828). Item-total correlations were within acceptable ranges. Significant positive correlations were observed between MASS total scores and OAS subscale scores (r = 0.324-0.816), supporting construct validity. Patients who required intervention had significantly higher MASS scores than those who did not (17.57 ± 10.01 vs. 2.58 ± 2.55; p < 0.001), confirming criterion-related validity. CONCLUSION:The Turkish version of the MASS is a valid, reliable, and practical instrument for assessing agitation in psychiatric settings. It offers an objective and standardized method that supports timely detection, early intervention, and improved patient safety.
BACKGROUND/AIM:Risky alcohol use is common among university students and negatively impacts physical and psychosocial health. Current screening instruments focus only on behavioral indicators, neglecting psychosocial factors. This study aimed to develop an AI-supported, brief student-focused tool for assessing alcohol-related risk and to evaluate its preliminary reliability and validity among university students. MATERIALS AND METHODS:A total of 599 university students participated in this cross-sectional study. From a pool of 59 items covering behavioral, psychological, social, and academic questions related to alcohol use, a new risk model was created using 15 items selected with ChatGPT-supported AI algorithms (SARAS-15). Risk scores ranged from 0 to 27, categorizing participants into low, medium, and high-risk groups. The model's performance was evaluated using machine learning methods such as Random Forest, Logistic Regression, SVM, and KNN, along with cross-validation and ROC analysis. We also analyzed its internal consistency and its correlations with screening instruments (AUDIT, RAPS4-QF, CAGE). RESULTS:In machine learning analyses, the logistic regression model achieved the highest performance (93.5% accuracy, F1-score = 0.864, sensitivity = 0.826, specificity = 0.959). ROC analysis demonstrated excellent discrimination between low-risk (AUC = 0.96) and high-risk (AUC = 0.93) groups, with strong discrimination for the intermediate-risk group (AUC = 0.88). The Random Forest model achieved an overall accuracy of 87%, successfully differentiating between the low-risk group (F1 score = 0.91) and the high-risk group (F1 score = 1.00). The new model's Cronbach's alpha was 0.811, with strong convergent validity correlations with screening instruments (AUDIT, r = 0.861; RAPS4-QF, r = 0.793; CAGE, r = 0.631). CONCLUSION:The developed artificial intelligence-supported 15-item new risk score model is valid and reliable in assessing risky alcohol use among university students. This scale demonstrates a high level of agreement with traditional tests and can accurately detect three risk levels. Due to its multi-domain content structure, which addresses both behavioral and psychosocial effects, it serves as a complementary screening tool for early risk identification and intervention planning.
OBJECTIVES:Basic self-disturbance is an abnormality in subjective self-experience and a core feature of schizophrenia. The Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE) is a self-report measure designed to assess basic self-disturbance. Despite its clinical utility, a Japanese version has not yet been established. This study aimed to develop a Japanese version of the IPASE and evaluate its reliability and validity. METHODS:The study included 182 participants (83 individuals with schizophrenia and 99 healthy controls). The Japanese version of the IPASE was administered to all participants, along with the PANSS and YMRS, to assess validity. RESULT:All IPASE domain scores and the total score were significantly higher in the schizophrenia group than in healthy controls. The IPASE total score showed good internal consistency (Cronbach's α > 0.80). In the schizophrenia group, the PANSS positive subscale, general psychopathology subscale, and total scores were all significantly positively correlated with IPASE scores. These positive correlations with the positive subscale support convergent validity. ROC analysis indicated that the IPASE total score had good discriminative ability for schizophrenia diagnosis (AUC = 0.851). CONCLUSION:The Japanese version of the IPASE demonstrated high reliability and validity.
BACKGROUND:Psychotic experiences are commonly reported in population-based surveys, yet brief self-report screening instruments often yield high false-positive rates by capturing normative, culturally sanctioned, or other non-psychotic phenomena. Large surveys and administrative datasets increasingly include free-text responses that could contextualize these endorsements; however, qualitative data are under-analyzed due to resource constraints. METHODS:Using data from a US adult online survey, respondents who endorsed at least one item on the abbreviated World Health Organization Composite International Diagnostic Interview (WHO CIDI) psychosis screen were asked whether they could describe their experiences in an open-ended format. Using reflexive thematic analysis, three coders developed codes that were grouped into categories, and ultimately classified responses as probably psychotic, probably not psychotic, or unclear. RESULTS:Content analysis identified 13 thematic categories, including hallucinations, paranoia, emotional distress, interpersonal conflict, spiritual or paranormal beliefs, sleep-related experiences, and unintelligible responses. Nearly half of the responses were classified as unlikely to reflect psychotic experiences, while approximately 9% were deemed probably psychotic and 41% remained unclear due to insufficient context. Many responses reflected affective distress, stress-related interpretations, grief, or ambiguous experiences rather than clear psychotic phenomena. Descriptions capturing distress, functional impact, and insight were clinically informative but were inconsistently reported. CONCLUSIONS:Brief qualitative descriptions accompanying psychosis screening items provide valuable context that can clarify whether psychotic experiences reflect clinically meaningful psychotic phenomena or normative experiences. Integrating qualitative free-response fields may improve the interpretability and precision of psychosis screening, inform early detection efforts, and reduce the risk of over-pathologization.
BACKGROUND:Family involvement in nursing care is a key component of patient-centered care and is associated with improved patient outcomes and satisfaction. However, in Iran, there is a need for a culturally adapted and psychometrically sound instrument to assess nurses' attitudes toward family involvement in care using a standardized framework. OBJECTIVE:To adapt and evaluate the psychometric properties of the Persian version of the Families' Importance in Nursing Care-Nurses' Attitudes (FINC-NA) questionnaire among Iranian nurses based on the COSMIN framework. METHOD:This cross-sectional methodological study was conducted among 430 nurses from Tabriz educational hospitals between January and March 2025. Participants were randomly divided into exploratory (n = 215) and confirmatory (n = 215) factor analysis groups. The Persian FINC-NA was evaluated for content and face validity, construct validity (EFA and CFA), and reliability (internal consistency and test-retest reliability) following COSMIN guidelines. Data were analyzed using SPSS version 27 and AMOS version 24. RESULTS:Exploratory and confirmatory factor analyses supported a four-factor structure of the Persian FINC-NA: Family as an Active Care Partner, Family Engagement and Support, Family Burden, and Family Strengths and Communication. This structure explained 56.65% of the total variance and demonstrated acceptable model fit indices (χ2/df = 3.63, CFI = 0.901, TLI = 0.949, RMSEA = 0.078, SRMR = 0.069). Internal consistency was acceptable for most subscales (α ≥ 0.83), and test-retest reliability ranged from poor to good across subscales (ICC = 0.158-0.839). CONCLUSION:The Persian version of the FINC-NA demonstrates acceptable validity and reliability for assessing nurses' attitudes toward family involvement in nursing care in Iran. However, further refinement of certain subscales may be required to improve stability over time.
Objectives The odds ratio estimate in Fisher's exact test can overestimate the parameter. A simple computer simulation can easily reveal the positive bias of the odds ratio estimate from Fisher's exact test. Bootstrap can facilitate bias correction for the odds ratio estimate. Methods The bias can be estimated, using bootstrap samples and the original sample to approximate the expectation of the odds ratio estimator and the true parameter value-their difference is the bias. Here, the bias is computed from the underlying distribution, conditional on the exclusion of zero cells in sampling, to avoid the infinite expectation. Results A study of depression is used to demonstrate how to use bootstrap to correct the bias in an odds ratio estimate based on Fisher's exact test. Conclusions Bootstrapping can easily estimate and correct the bias of an odds ratio estimate in Fisher's exact test. The results suggest that bootstrapping is sensitive enough to detect even a small bias.
ABSTRACT Background Index construction using the joint probability density (JPD) method is extremely robust and, unlike confirmatory factor analysis (CFA) or item response theory (IRT), puts few restrictions on underlying data. When input variables' numbers are large, however, JPD estimation can be difficult. Objective To assess two simplifications of JPD estimation using the TWEAK, a well validated screener for problematic drinking, and to compare these against the fully estimated JPD, the conventionally scored TWEAK, and TWEAK scores estimated through CFA and IRT. Methods Mailed survey of a nationally representative panel of 410 gender‐stratified, post‐9/11 Veterans with pending disability claims for posttraumatic stress disorder. Results Summary statistics for the TWEAK's fully estimated JPD and the two simplifications were very similar, and Spearman's correlations were 0.97–1.00 (ps < 0.001). Spearman's correlations across the remaining scoring approaches were −0.84 to −0.90 (ps < 0.001). All 6 scoring approaches identified differences in men's TWEAK scores by alcohol use diagnosis (ps ≤ 0.02); the 3 JPD approaches did not reach statistical significance in the women. IRT analysis identified local dependence issues. Conclusions Our simplified estimations of JPD score were very similar to the fully estimated JPD and much easier to calculate. All 3 JPD estimations were highly concordant with more traditional scoring approaches.
ABSTRACT Objectives Associations between physical activity and affect (activity‐affect dynamics) vary among individuals for which reasons remain unclear. We examined whether such heterogeneity is explained by psychiatric status or sociodemographic, clinical, and ambulatory assessment characteristics. Methods Two‐week ambulatory assessment data of 300 participants with current (n = 79), subthreshold (n = 67), and no (n = 154) depressive and/or anxiety disorders or symptoms were obtained from the Netherlands Study of Depression and Anxiety. Positive and negative affect (PA/NA) were assessed with ecological momentary assessment (5xdaily) and physical activity using actigraphy. Group iterative multiple model estimation was used to model associations shared across the sample, psychiatric subgroups, and those specific to individuals. Results No activity‐affect associations were shared across the sample (i.e., present in > 75% of all individuals) or psychiatric subgroups (i.e., present in > 51% of individuals within subgroups). Nevertheless, 45% of participants had at least one activity‐affect association, with considerable heterogeneity in their nature. The most frequent association was a positive contemporaneous association between physical activity and PA (present in 25% of the sample). Conclusions These findings suggest large heterogeneity in activity‐affect dynamics among individuals and underscore the importance of considering the unique dynamics of the individual.
ABSTRACT Background Brief measures of emotion regulation difficulties are useful in survey‐based research and screening, yet evidence for Arabic ultra‐brief tools remains limited. This study evaluated the psychometric properties of an Arabic translation of the Difficulties in Emotion Regulation Scale–8 (DERS‐8) in an Arabic‐speaking sample from Egypt. Methods A cross‐sectional, internet‐based survey was completed by 603 university students (mean age = 19.58 years; 62.7% female). Participants completed the Arabic DERS‐8 alongside measures of psychological distress (PHQ‐4) and perceived social support (MSPSS). Confirmatory factor analysis (CFA) tested the hypothesized one‐factor structure. Internal consistency was examined using Cronbach's α and McDonald's ω. Measurement invariance across gender was evaluated using multigroup CFA (configural, metric, and scalar), followed by independent‐samples t tests. Construct validity was tested via associations with anxiety, depression and social support. Results The one‐factor model showed acceptable fit, and model fit improved after allowing a theoretically plausible correlated residual between two items (final fit: robust RMSEA = 0.071 [90% CI 0.047, 0.096], SRMR = 0.032, robust CFI = 0.974, robust TLI = 0.962). Reliability was adequate (ω = 0.85; α = 0.85). The DERS‐8 demonstrated metric and scalar invariance across gender and total scores did not differ significantly between males and females. Higher DERS‐8 scores were associated with greater anxiety (r = 0.58) and depression (r = 0.55) and with lower perceived social support (r = −0.31) with all p < 0.001. Conclusion The Arabic DERS‐8 appears to be a brief, reliable and valid measure of overall emotion regulation difficulties for use in non‐clinical adults in Egypt, supporting its use in community‐based research and screening contexts.
ABSTRACT Background Depression is a major mental health disorder, and EEG‐based automated detection is emerging as a potential objective diagnostic tool. However, achieving both high accuracy and interpretability remains challenging due to the complex spatiotemporal structure of EEG signals. This study proposes an explainable deep learning framework for depression detection using resting‐state EEG data. Methods A retrospective computational study using deep learning was conducted using EEG data from 122 subjects in the OpenNeuro dataset (ds003478). Based on Beck Depression Inventory (BDI) scores, participants were classified into control (BDI ≤ 13; n = 76) and depressive (BDI ≥ 20; n = 30) groups; intermediate cases (BDI 14–19; n = 16) were excluded to reduce label ambiguity and construct a high‐confidence binary classification framework, although this may reduce applicability to mild or subclinical depression, resulting in a final cohort of 106 subjects. Preprocessing included band‐pass filtering (1–40 Hz), 50 Hz notch filtering, Independent Component Analysis, and average referencing. A subject‐wise 5‐fold cross‐validation was applied. A CNN–BiLSTM architecture with an attention mechanism integrated with explainable AI techniques (Grad‐CAM and SHAP) was developed. Results The proposed model achieved an accuracy of 89.76%, an F1‐score of 89.58%, and an AUC of 0.936. Ablation analysis confirmed the contribution of temporal modeling and attention mechanisms. Explainability analysis using Grad‐CAM and SHAP showed that frontal EEG channels were the most influential in classification, consistent with neurophysiological findings. Conclusion The proposed framework provides an accurate and interpretable method for EEG‐based depression detection, supporting applications in computational psychiatry and decision‐support systems.
ABSTRACT Objectives Using data from the Brain Attack Surveillance in Corpus Christi—Cognitive (BASIC‐C) study, we investigate recruitment mode selection effects and interview mode measurement effects in population‐based applications of the Montreal Cognitive Assessment (MoCA) and Harmonized Cognitive Assessment Protocol (HCAP). Methods We compared participant demographics across in‐person (n = 1212), telephone (n = 645), and community (n = 363) samples recruited over 2018–2023 to American Community Survey statistics for Nueces County, Texas. We then implemented unadjusted and adjusted models to assess differences in harmonized MoCA scores, HCAP eligibility and completion, and HCAP cognitive domain measures across recruitment and interview modes. Results The samples had significantly different levels of selection effects, with significant differences in the odds of HCAP eligibility (Odds Ratios (ORs) of 0.51, 1.32, p‐value < 0.001). The in‐person and telephone interview modes showed significant differences in the cumulative odds of harmonized MoCA score categories (Cumulative OR = 1.58, p‐value < 0.001) and several HCAP domain scores, and these differences were attenuated but not eliminated after adjusting for participant demographics. Conclusions The observed differences in MoCA screening outcomes and HCAP eligibility and cognitive domain scores were largely attributable to recruitment mode selection effects. However, statistical adjustments for population characteristics did not fully attenuate interview mode measurement effects.
ABSTRACT Objectives This study examined prospective pathways to future depressive symptoms among university students, focusing on interpersonal needs, emotion regulation strategies, meaning in life, and suicide risk markers. Methods A longitudinal design was conducted with 737 Spanish university students assessed at baseline (T1) and 225 reassessed 14 weeks later (T2), reflecting substantial attrition across follow‐up. Measures included depressive symptoms, thwarted belongingness, perceived burdensomeness, emotion regulation strategies (cognitive reappraisal and expressive suppression), meaning in life, non‐suicidal self‐injury (NSSI) frequency, and suicidal ideation frequency. Structural equation modeling in JASP (lavaan backend) tested a theory‐driven model estimating direct and indirect effects on depressive symptoms at follow‐up, controlling for baseline depression. Sensitivity analyses were performed excluding baseline depression. Results Baseline depressive symptoms were the strongest predictor of future depression. Thwarted belongingness predicted higher expressive suppression and lower meaning in life, whereas perceived burdensomeness showed a direct association with depressive symptoms at follow‐up. When baseline depression was excluded, thwarted belongingness indirectly predicted future depressive symptoms through expressive suppression. The final models explained up to 42% of the variance in depressive symptoms at T2. Conclusions Interpersonal difficulties and maladaptive emotion regulation processes predicted the persistence of depressive symptoms among university students. Interventions targeting social connectedness and expressive suppression may help reduce the risk of sustained depressive symptomatology in this population.
ABSTRACT Introduction The high comorbidity between depression and anxiety challenges traditional nosological models. In order to better reflect this overlap, dimensional approaches seek to clarify whether these symptoms reflect a single underlying construct of general distress or a more complex multidimensionality. The aim was to examine the underlying structure of depression and anxiety symptoms, measured by the PHQ‐9 and GAD‐7, by estimating and comparing three factor models: one‐factor, two‐factor correlated, and bifactor. Methods Data from 1704 primary care (PC) patients from the PsicAP clinical trial were analysed. Dimensionality was assessed using hierarchical Exploratory Graph Analysis (EGA), and models were estimated using Exploratory Structural Equation Modelling (ESEM). Model fit was compared using the χ2, CFI, TLI, RMSEA, and SRMR indices. Results The bifactor model offered the most acceptable comparative fit to the data (CFI = 0.956; TLI = 0.928; RMSEA = 0.076; SRMR = 0.028). Bifactor indices revealed a relevant but not dominant general factor (ECV = 0.40), indicating it does not account for sufficient variance to justify an essentially unidimensional interpretation. Furthermore, the specific factors of depression and anxiety emerged as well‐defined constructs (H > 0.75) with modest reliable specific variance (ωHS: 0.22 and 0.27, respectively). Discussion The findings suggest a hierarchical structure where a general factor of distress coexists with specific factors. This suggests the potential utility of considering a multi‐level perspective in clinical assessment, accounting for both shared distress and specific symptom profiles.
ABSTRACT Objectives This study aims to identify social and clinical factors associated with antipsychotic medication discontinuation in patients with schizophrenia. Methods This cross‐sectional case‐control study comprised 111 schizophrenia patients, including 55 who discontinued medication on their own initiative and 56 matched continuous‐treatment patients. Assessed factors covered demographics, clinical profiles, and scores from the Positive and Negative Syndrome Scale (PANSS), the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and the Personal and Social Performance (PSP) scale. Results Patients in the discontinuation group demonstrated significantly higher employment rates (χ2 = 24.514, p < 0.001) and marriage rates (χ2 = 14.970, p = 0.002) compared to those in the continuous treatment group. The continuous treatment group had more episodes (p < 0.001) and severe symptoms (PANSS, p < 0.001) with lower cognitive (RBANS, p = 0.001) and social functioning scores (PSP, p < 0.001) compared to the discontinuation group. Regression analysis revealed that fewer episodes (β = 2.799, p = 0.018) and lower PANSS negative symptom scores (β = 0.533, p = 0.011) were associated with a greater likelihood of medication discontinuation. Conclusion The discontinuation group exhibited milder schizophrenia symptoms and higher social functioning than the continuation group. Furthermore, patients with fewer episodes and milder negative symptoms were more likely to discontinue medication.
