Iranian Journal of Psychiatry最新文献

Objective: The objective of this meta-analysis was to establish the prevalence of poor sleep quality among individuals aged over 60 years old, utilizing the Pittsburgh Sleep Quality Index (PSQI). Method : To identify appropriate records, a thorough search of PubMed, Scopus, and Web of Knowledge databases was conducted until May 22, 2024. The quality of the included studies was assessed using the Hoy tool. To calculate the pooled prevalence with a 95% confidence interval, the random effects model was utilized. Additionally, subgroup analyses were carried out to investigate the potential sources of heterogeneity. Results: This study examined 52 cross-sectional studies encompassing 24,217 individuals aged 60 and older. The quality of the studies was assessed, with 4 rated as moderate and 48 as good. China reported the lowest prevalence of poor sleep quality at 14%, while Malaysia recorded the highest at 96%. The overall pooled prevalence was found to be 50% (95% CI: 45-55%), exhibiting significant heterogeneity across the studies (I² = 99.60%, Pheterogeneity < 0.001). Subgroup analysis indicated that geographic location significantly influenced this heterogeneity (p < 0.001), with Africa showing a lower prevalence of poor sleep quality at 27% (95% CI: 23%-32%) compared to other regions. However, no significant differences were observed in the impact of other factors, such as gender, level of development, sample size, survey time, PSQI cut-off, and response rate on the overall heterogeneity of the analyzed data. Conclusion: This study reveals that approximately half of older adults experience poor sleep quality. However, this prevalence varies across different locations, underscoring the necessity for targeted interventions that consider regional factors influencing sleep health.

Objective: This systematic review aims to explore the effects of listening to the Quran on the electrophysiological aspects of the human brain, particularly focusing on how this auditory experience influences cognitive function, emotional well-being, and mental health. Method : We conducted a comprehensive search across multiple databases, including Web of Science, PubMed, Scopus, and Google Scholar, using keywords such as "Quran" and "EEG." Studies included in this review were observational or clinical trials that investigated the effects of Quran listening on brain activity using EEG. Eligibility criteria were assessed according to predefined standards, with a focus on studies published in English. The Newcastle-Ottawa Scale was employed to evaluate the quality of the selected articles, and data extraction followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: A total of 236 studies were evaluated, leading to the inclusion of 22 eligible studies in this review. Findings indicate that listening to Quranic verses is associated with increased alpha and theta power, which correlates with relaxation and improved emotional states in participants, including non-Muslims. The review identified significant variations in study designs, methodologies, and quality, with many studies displaying a high risk of bias. Conclusion: Listening to Quranic verses demonstrates potential therapeutic effects by activating brain regions associated with relaxation and emotional regulation. Despite promising findings, the current body of research is limited, particularly regarding nonlinear EEG dynamics and comprehensive study designs. Further neuroimaging and clinical investigations are warranted to validate these results and explore the therapeutic applications of Quranic listening in diverse contexts, such as pain management, psychological health, and rehabilitation.

Objective: The Personality Inventory for DSM-5 (PID-5) is a widely used scale to evaluate the dimensional constructs of two trait models proposed by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the International Classification of Diseases (ICD-11). The present meta-analysis first aimed to examine the factor structure, reliability, and congruence coefficients of the Persian version of the PID-5 to assess both trait models. The second aim was to evaluate the factor structure and reliability of the Persian version of the Personality Inventory for DSM-5-Brief Form (PID-5-BF). Method : A systematic search was conducted in PubMed, Magiran, and SID to find records in English and Farsi from January 2013 to December 2023. According to the PRISMA, data from nine medium- to high-quality reports including 7,608 participants were analyzed using the random-effects method. Quality of studies, heterogeneity, and publication bias were reported. Results: The five-factor structure of the PID-5 to measure both trait models was supported by the pooled estimates of factor loadings. The alpha coefficient median for the DSM-5 model was 0.83 (range: 0.82-0.90), and the congruence coefficient median was .91 (range: 0.80-0.97). The ICD-11 alpha median was .78 (range: 0.68-0.91), and congruency median was 0.90 (range: 0.71-0.96). The factor loadings for negative affectivity, detachment, antagonism, disinhibition, and psychoticism on the PID-5-BF were 0.44-0.69, 0.38-0.67, 0.46-0.72, 0.42-0.70, and 0.44-0.76, respectively, and the alpha median was 0.73 (range: 0.65-0.76). Conclusion: Since both the original and brief versions of the PID-5 are valid and strongly similar to international structures, the clinical and research applications of these questionnaires are recommended to mental health professionals in Iran.

Objective: Chronic kidney disease (CKD) is a pervasive health issue associated with various complications, including cognitive impairment and depression among patients undergoing hemodialysis. This study aimed to assess the impact of melatonin on depression and cognitive function in hemodialysis patients. Method : A randomized, double-blinded, placebo-controlled clinical trial was conducted in 50 hemodialysis patients, with half of the patients receiving 3 mg daily melatonin and the other half receiving a placebo for two months. Depression and cognitive function were evaluated using the Beck Depression Inventory (BDI) and Mini-Mental State Examination (MMSE) questionnaire, respectively. Quantitative variables were analyzed using a t-test. The Chi-square test also evaluated qualitative variables. Quantitative data were analyzed by covariance analysis before and after the intervention. Results: Hypertension was the most prevalent underlying condition among study participants, affecting 40% of the intervention group. The intervention group exhibited baseline depressive symptoms (mean BDI score: 16.12 ± 7.12), which significantly improved post-intervention (13.6 ± 6.6). Notably, both the intervention and control groups demonstrated significant reductions in depressive symptoms, as assessed by paired t-tests (P = 0.033 and P = 0.02, respectively). Cognitive function, as measured by the MMSE, improved in both groups (1.28 ± 0.81 for melatonin, 1.52 ± 0.1 for placebo), with significant within-group differences (P = 0.048 and P = 0.002, respectively). ANCOVA analysis revealed no significant between-group differences in BDI scores (F(1,47) = 0.196, P = 0.66, partial eta-squared = 0.004). and in MMSE scores (F(1,47) = 0.003, P = 0.954, partial eta-squared = 0.00) post-intervention. Conclusion: While this study did not demonstrate significant effects of melatonin on depression and cognitive impairment in hemodialysis patients, positive changes were observed, warranting further research to optimize treatment regimens and explore the potential therapeutic benefits of melatonin in this patient population.

Objective: Automatic negative thoughts have an important role in development of a persistent negative cognitive bias, which may ultimately result in suicidal ideation. The primary objective of the present study was to examine the relationship between automatic negative thoughts and experiential avoidance in relation to psychological distress. Method : The study sample comprised 441 individuals who had attempted suicide. Participants underwent interviews utilizing standardized questionnaires including Automatic Thoughts Questionnaire, Kessler Psychological Distress Scale, Acceptance and Action Questionnaire-II, and Cognitive Emotion Regulation Questionnaire along with its nine subscales. After internal relationships assessment among the research variables, outlier detection was done using the boxplot analysis and standard deviation distance metrics. To analyze the direct and indirect associations between the input and output variables, Structural Equation Modeling (SEM) was employed. In addition, SPSS-28 and Amos 29 software were used to analyzed the data. Results: The final model showed that automatic negative thoughts were significantly inversely associated with adaptive cognitive emotion regulation (β = -0.42, P ≤ 0.01) and significantly positively related to both maladaptive cognitive emotion regulation (β = 0.49, P ≤ 0.01) and psychological distress (β = 0.53, P < 0.01). Additionally, experiential avoidance showed a significant positive relationship with maladaptive cognitive emotion regulation (β = 0.22, P < 0.01). Conclusion: This research demonstrated that automatic negative thoughts could worsen psychological distress through the regulation of cognitive emotion in those who had a history of suicide. By the clinical management of automatic negative thoughts and shifting individuals' cognitive emotion regulation toward adaptive strategies, there is potential for a substantial reduction in suicidal ideation and attempts which can be evaluated in future clinical trials.

Objective: The integration of behavioral economics and neuroeconomics into mental health offers innovative perspectives on understanding and addressing psychological disorders. This overview aims to synthesize current knowledge and explore the implications of these interdisciplinary approaches in the context of mental health. Method : In this narrative review, we summarized the current evidence regarding the applications of behavioral economics and neuroeconomics approaches in the field of mental health. Results: Behavioral economics and neuroeconomics provide valuable insights into the cognitive and emotional processes underlying mental health disorders, such as irrational decision-making, impulsivity, and self-control issues. Concepts such as loss aversion, temporal discounting, and framing effects inform the development of innovative interventions and policy initiatives. Behavioral economic interventions, including nudges, incentives, and commitment devices, show promise in promoting treatment adherence, reducing risky behaviors, and enhancing mental well-being. Neuroeconomics contributes by identifying neural markers predictive of treatment response and relapse risk, paving the way for personalized treatment approaches. Conclusion: The integration of behavioral economics and neuroeconomics into mental health research and practice holds significant potential for improving the understanding of psychological disorders and developing more effective, personalized interventions. Further research is needed to elucidate the mechanisms of action, optimize intervention strategies, and address ethical considerations associated with these approaches in mental health settings.

Objective: Suicidal ideation (SI) signifies a psychiatric crisis, and individuals with SI are at a significantly higher risk of suicide attempts compared to those without. According to previous research, three factors that affect SI in adolescent girls are externalization problems, alexithymia, and perceived social support (PSS). As a result, the present research aimed to examine whether internet addiction (IA) is associated with SI through the mediating roles of PSS, externalizing problems, and alexithymia among adolescent girls in Tehran, Iran. Method: The current correlational study employed a structural equation modeling approach. Model fit indices such as the Chi-square to degrees of freedom ratio (CMIN/DF), normed fit index (NFI), root mean square error of approximation (RMSEA), Tucker-Lewis index (TLI), and goodness-of-fit index (CFI) were reported to assess the model's adequacy. A total of 441 adolescent girls were selected from high school and between the ages of 11 and 19 using a convenience sampling method. Participants completed the Multidimensional Scale of Perceived Social Support (MSPSS), the Beck Scale for Suicidal Ideation (BSSI), the Cell-Phone Over-Use Scale (COS), the Youth Self-Report (YSR), and the Toronto Alexithymia Scale-20 (TAS-20) in a written manner. Data analysis was done using SPSS 25 and AMOS 22. Results: Results revealed a significant positive correlation between IA and SI (P < 0.001). The study's most significant findings indicate that PSS, externalizing problems, and alexithymia significantly mediate the relationship between SI and IA. The coefficient of determination for the SI variable was 0.33, which means that predictor variables can explain 33% of the variance in SI (IA, PSS, alexithymia, and externalizing problems). Conclusion: IA showed direct and indirect effects on SI. Using these findings, we can elucidate the mechanism of how IA affects individual SI, providing critical information for the development and implementation of targeted strategies and interventions to reduce SI among Iranian adolescent girls. Psychological interventions that address the role of externalizing behaviors, alexithymia, and PSS in adolescents with IA may help reduce SI.

Objective: This review identifies the characteristic features of artificial intelligence (AI) chatbots and their therapeutic effect; assesses their efficacy in treatment of depression, anxiety, and other mental health disorders; and establishes levels of user engagement and satisfaction. Method : Searches were conducted on the PubMed, Embase, MEDLINE, CENTRAL, CINAHL, PsycINFO, and Google Scholar databases using a set of keywords such as, not limited to, AI cognitive behavioral therapy (AI CBT), Youper, Wysa, Woebot, and other related terms. We included studies that were empirical, peer-reviewed, conducted between January 2017 and June 2024, and primarily focused on efficacy regarding the interventions and therapeutic outcomes. Data were then extracted and analyzed using both qualitative and quantitative methods concerning the mental health outcome. Results: Our review identified large improvements across the three chatbots in symptoms of mental health, as supported by the 10 included studies: five on Woebot, four on Wysa, and one on Youper. Woebot showed remarkable reductions in depression and anxiety with high user engagement; Wysa demonstrated similar improvements, especially in users with chronic pain or maternal mental health challenges; Youper also presented a significant symptom reduction, including a 48% decrease in depression and a 43% decrease in anxiety. Common benefits of all chatbots were the therapeutic alliance and a high rate of satisfaction among users. We have also discussed the included studies' limitations; that is, study design shortcomings and lack of sample diversity. Conclusion: AI CBT chatbots, including but not limited to Woebot, Wysa, and Youper, are highly promising because of their availability and effectiveness in mental health support. They provide a useful complement to standard therapy when professional help is unavailable, and offer constant engagement with tailored interventions. However, it is necessary that further studies investigate their potential impact as long-term intervention models and explore how they may be integrated into holistic mental health care systems.

Objective: The link between individuals' perceptions of social class (PSC) and various forms of bullying, including cyberbullying, has not been extensively studied. Additionally, the mechanisms through which PSC impact aggressive behaviors like cyberbullying remain unclear. Therefore, this study aimed to explore the influence of perceived social class on cyberbullying, considering subjective vitality and psychological distress as serial mediators. Method : Utilizing a cross-sectional design, the research involved 584 Iranian students (Mage = 20.59, SD = 1.99) from several universities who completed questionnaires assessing Subjective Social Class (SSC), Subjective Vitality Scale (SVS), Psychological Distress Scale (K6), and Cyberbullying Involvement Scale (CIS). Hayes' PROCESS macro (Model 6) in SPSS was employed to analyze the chain mediation effects. Results: The Results demonstrated that the direct impact of PSC on cyberbullying was significant (Effect = -0.229, 95% CI: -0.294 to -0.164). Subjective vitality and psychological distress serially mediated the link between PSC and cyberbullying (Effect = -0.022, 95% CI: -0.035 to -0.012). In addition, both subjective vitality (Effect = -0.046, 95% CI: -0.080 to -0.017), and psychological distress (Effect = -0.09, 95% CI: -0.123 to -0.059), independently mediated the association between PSC and cyberbullying. Conclusion: This research not only broadens the theoretical understanding of how individuals' perceptions of their social rank influence cyberbullying behaviors, but also provides actionable strategies for officials and experts to deploy effective interventions in higher education to mitigate cyberbullying.