Psychiatry Investigation最新文献

Objective: This study aimed to examine the current status of psychiatric therapy and anti-craving prescriptions for patients with alcohol-related diseases and to evaluate the impact of these treatments on the prognosis of alcohol-related diseases for drawing implications.

Methods: Data were analyzed by combining data extracted from one hospital, data of the National Health Insurance Service, and the National Statistical Office mortality data. The rationale for utilizing an integrated data set was that a single dataset from a single hospital was insufficient for comprehending economic factors, mortality rates, and medical information.

Results: The analysis yielded two principal conclusions. Firstly, concurrent administration of psychiatric therapy and anti-craving prescriptions was demonstrated to be an effective approach in the management of alcohol-related disorders. Secondly, the economic status of patients was found to influence outcomes of psychiatric pharmacotherapy.

Conclusion: The integration of diverse alcohol-related data for management could facilitate the implementation of personalized prescriptions tailored to specific needs of each patient. This approach has the potential to reduce mortality rates and mitigate societal burdens associated with alcohol-related diseases.

Objective: This study aimed to examine the predictive validity of the revised Suicide Crisis Inventory (SCI-2) and determine its optimal cutoff score.

Methods: Data from 662 community adults participating in a one-year follow-up study were analyzed. Receiver operating characteristic analysis was conducted to examine whether the SCI-2 could predict suicide attempts and ideation with intent at the follow-up and to determine the optimal cutoff score for identifying individuals at high risk for suicide.

Results: The SCI-2 demonstrated adequate predictive validity for suicide attempts and ideation with intent at the one-year follow-up. Based on Youden's index and Runeson et al.'s criteria, a cutoff score of 102 was proposed as the threshold for high-risk groups.

Conclusion: The SCI-2, a measure of Suicide Crisis Syndrome, demonstrated predictive validity using longitudinal data. It is effective in identifying high-risk individuals in a community population. These findings highlight the SCI-2 as a valuable tool for early suicide risk detection and prevention.

Objective: Despite an increase in the depressive disorders burden during the coronavirus disease-2019 (COVID-19) pandemic, research remains insufficient. This study aims to advance the understanding of the global depressive disorders burden, focusing on the COVID-19 pandemic.

Methods: Global and regional estimates of incidence, prevalence, and disability-adjusted life years (DALYs) for depressive disorders from 1990 to 2021 were analyzed using the Global Burden of Disease Study 2021. Depressive disorders were defined as the aggregate of major depressive disorder and dysthymia. Estimates were stratified by age, sex, Socio-demographic Index (SDI), and region, and trends were assessed by annual percent change. Attributable risk factors and projections to 2050 were assessed by modeling risk factors.

Results: In 2021, depressive disorders accounted for 56,330.36 (95% uncertainty interval [UI], 39,339.99 to 76,538.17) DALYs. The age-standardized DALYs rate (ASDR) remained stable until 2019, followed by an increase during the COVID-19 pandemic (ASDR in 1990: 600.51 [95% UI, 420.94 to 818.45] per 100,000; in 2019: 593.50 [413.34 to 810.07]; in 2021: 681.14 [475.19 to 923.83]). The highest ASDRs were observed in low (837.53 [95% UI, 569.85 to 1,140.07] per 100,000) and low-middle (784.07 [542.47 to 1,059.21]) SDI regions. The burden increased rapidly among adolescents and remained higher in females than in males. The burden attributable to intimate partner violence increased during the COVID-19 pandemic. Projections suggest a modest decline in global ASDR, reaching 622.30 (95% UI, 430.96 to 847.82) per 100,000 by 2050.

Conclusion: The global burden of depressive disorders increased sharply during the COVID-19 pandemic. It is essential to address regional disparities in mental health care and promote access to tailored treatment.

Objective: Psychiatric morbidity patterns and associated outcomes among individuals with borderline intellectual functioning (BIF) remain poorly characterized. This systematic review aims to examine mental health outcomes in BIF populations compared to individuals with normal intellectual functioning and those with intellectual disability (ID).

Methods: A systematic literature search was conducted across the PubMed, Web of Science, PsycInfo, and ERIC databases from inception to January 2025 using comprehensive search terms for BIF. Studies were included in this analysis if they examined individuals with intelligence quotient (IQ) 71-84 and reported mental health outcomes. Data extraction focused on subjective well-being, psychopathology prevalence, and comparative analyses. Quality assessment utilized the Mixed Methods Appraisal Tool.

Results: Forty-five studies encompassing 93,396 individuals with BIF were included. Individuals with BIF demonstrated significantly elevated psychiatric morbidity compared with average IQ populations across multiple domains including anxiety, mood, personality, and neurodevelopmental disorders. Mental health outcomes of BIF individuals typically fell intermediate to those observed in normal IQ and mild ID populations.

Conclusion: Individuals with BIF represent a vulnerable population with substantially elevated mental health risks, yet remain inadequately differentiated from adjacent cognitive groups. The field requires specialized clinical attention, educational support, and targeted interventions to address their unique mental health challenges and improve outcomes.

Objective: Machine learning (ML) can assist in predicting suicide risk and identifying associated risk factors. Various resampling methods and algorithms must be applied to develop an ML prediction model with better performance. In this study, we developed an optimal Korean suicide prediction model by applying five ML algorithms, unsampled data, and two resampling methods.

Methods: In this study, data from the Korea National Health and Nutrition Examination Survey for 2017, 2019, and 2021 were integrated and analyzed to predict suicidal ideation in subjects aged ≥19 years. Logistic regression, random forest (RF), k-nearest neighbor, gradient boosting, and adaptive boosting were used as ML algorithms. Undersampling and oversampling are used as resampling methods to solve data imbalance problems.

Results: Among the study participants, 16,947 (95.14%) and 866 (4.86%) belonged to the control and suicidal ideation groups, respectively. Among the 15 ML models, the RF model exhibited excellent performance (sensitivity=0.781, area under the curve=0.870) in an algorithm trained with undersampled data.

Conclusion: Developing an optimized Korean suicide prediction model through additional validation based on the ML model developed in this study will help predict suicide risk factors caused by the interaction of individual, social, and environmental factors.

Objective: This study investigates the prevalent characteristics of suicidality in college students with borderline personality (BP) features. In addition, it explores the relationship between BP features and suicidality and analyzes related psychological mechanisms.

Methods: The study encompassed 6,854 college students from 12 universities in Southern China from October to December 2020. The subjects completed a general information questionnnaire, Personality Diagnostic Questionnaire 4+, ruminative responses scale, 10 items in the Connor-Davidson resilience scale, and an assessment for suicidality.

Results: Among all participants, subjects with BP features reported higher rates of suicidal ideation and suicidal attempt than those without BP features, and the differences were statistically significant (all p<0.05). Logistic regression analysis demonstrated that resilience served as a significant protective factor against both suicidal ideation and suicidal attempt in both females and males (all p<0.05). Higher borderline personality disorder (BPD) score emerged as risk factor for suicidal ideation and suicidal attempt in both females and males (all p<0.001). Symptom rumination was a risk factor for suicidal ideation in both females and males (all p<0.001). Reflection was a risk factor for suicidal attempt in both males and females (all p<0.05). Resilience and symptom rumination mediated the relationship between BPD score and suicidal ideation in both females and males. Resilience mediated the relationship between BPD score and suicidal attempt only in males.

Conclusion: College students with BP features exhibit an elevated rate of suicide-related behaviors. The relationship between BP features and suicidality is mediated by rumination and resilience.

Objective: The Korean version of the Center for Epidemiologic Studies Depression Scale-Revised (K-CESD-R) is widely used in community epidemiology studies to screen depressive symptoms, given its proven reliability in diverse populations. However, it has not yet been validated in Korean adolescents. Therefore, this study validated and standardized the K-CESD-R for use in Korean adolescents.

Methods: Data were collected from 2,419 adolescents aged 12-17 years in educational institutions across Daedeok District, Daejeon, South Korea. To evaluate reliability, the internal consistency of the K-CESD-R was measured using Cronbach's alpha. Concurrent validity was tested through Pearson correlation analysis of established scales, and construct validity was assessed via exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

Results: The K-CESD-R had high internal consistency (Cronbach's alpha=0.934). Correlation analyses supported strong concurrent validity with other depression scales, although there was a negative correlation with the self-esteem scale. Factor analysis revealed a three-factor structure that explained 61.792% of the total variance. CFA of the K-CESD-R using a structural equation model affirmed the three-factor structure hypothesized in our EFA. The model fit indices demonstrated acceptable levels of fit, including Root Mean Square Error of Approximation=0.093, Comparative Fit Index=0.886, and Tucker-Lewis Index=0.871.

Conclusion: The K-CESD-R is a valid and reliable instrument for screening for depressive symptoms in Korean adolescents, supporting its use in epidemiological research and clinical settings. Further research should explore its applicability across Korean adolescent populations to confirm these findings.

Objective: Self-compassion plays a crucial role in emotional well-being and positive mental health. Self-Compassion Scale (SCS) can facilitate measurement of psychological distress and positive affect. SCS-Short Form (SCS-SF) offers an economical and efficient means of reducing burden of both respondents and researchers.

Methods: This study conducted secondary data analysis to construct and validate the Korean version of the SCS-SF (K-SCS-SF) using a sample of 650 young adults residing in Korea. To evaluate the factorial structure of the scale, confirmatory factor analyses were performed on two-, three-, and six-factor models, and model comparisons were conducted using multiple fit indices. Concurrent validity was assessed by analyzing correlations of the SCS-SF with measures of resilience, depression, and anxiety. Reliability was examined based on item-total correlations and internal consistency analysis.

Results: Findings revealed that the two-factor model comprising negative and positive indicators was the best-fitting model. The two-factor model demonstrated strong validity and reliability in its application, highlighting its robustness in assessing self-compassion and its associations with resilience, depression, and anxiety.

Conclusion: The validated K-SCS-SF serves as a reliable, efficient, and practical assessment tool, advancing self-compassion research and its applications in mental health assessment, intervention studies, and psychological well-being research.

Objective: There is an increasing body of evidence suggesting that YouTube addiction may be associated with health issues among individuals in Indonesia. However, there is currently no validated instrument available in the Indonesian language to assess YouTube addiction. The present study represents the inaugural effort to translate and evaluate the psychometric properties of the Indonesian version of the YouTube Addiction Scale (YAS).

Methods: An online survey was administered to 515 Indonesian university students (mean age=20 years; 79.8% female), who were recruited through convenience sampling. All participants were proficient in Bahasa Indonesian and completed the survey between February and March 2024. The YAS was evaluated through confirmatory factor analysis (CFA) to assess its one-factor structure. Additionally, multigroup CFA was employed to examine measurement invariance across sex and varying levels of behavioral addictions. Pearson correlation analysis was utilized to establish concurrent validity.

Results: CFA confirmed that YAS has a one-factor structure. Moreover, multigroup CFA provided evidence for invariance across genders as well as varying levels of smartphone and social media addiction. The YAS had acceptable internal consistency (Cronbach's α=0.74, McDonald's ω=0.76). Additionally, the YAS was significantly correlated with scores from other social media behavior questionnaires.

Conclusion: These results suggest that YAS is a psychometrically robust and valid tool for evaluating the risk of YouTube addiction among young adults in Indonesia. Healthcare professionals and researchers may utilize the YAS to determine the severity of YouTube addiction, thereby gaining valuable insights into this specific form of social media dependency.