Psychiatry Investigation最新文献

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.

Objective: Attention-deficit/hyperactivity disorder (ADHD) includes three subtypes: inattentive type (ADHD-I), hyperactive/impulsive type (ADHD-HI), and combined type (ADHD-C). Diagnosis mainly relies on subjective behavioral rating scales, lacking objective biomarkers. Electroencephalography (EEG) and serum neurotrophic factors-brain-derived neurotrophic factor (BDNF), nerve growth factor (NGF), glial cell line-derived neurotrophic factor (GDNF), and neurotrophin-3 (NTF3)-may aid subtype differentiation. This study evaluates their combined diagnostic value in children with ADHD.

Methods: A retrospective cohort of 322 children aged 6-12 years diagnosed with ADHD based on DSM-5 criteria was analyzed. EEG recordings were processed using Fast Fourier Transform to extract frequency band powers and P300 wave features. Serum levels of BDNF, NGF, GDNF, and NTF3 were measured via ELISA. Analysis of variance (ANOVA), multivariate regression, and ROC curve analyses were performed to assess diagnostic performance.

Results: ADHD-I patients exhibited elevated frontal θ power, higher θ/β ratios, prolonged P300 latency, and reduced P300 amplitude. ADHD-HI patients demonstrated increased β power in parietal regions and elevated NGF and NTF3 levels. Multivariate analysis identified θ power, θ/β ratio, NGF, NTF3, and P300 amplitude area as independent predictors for subtype differentiation. Combined EEG and serum markers yielded an area under the curve (AUC) (0.90) in distinguishing ADHD-I from ADHD-HI.

Conclusion: The integration of EEG features and neurotrophic factor profiles offers high diagnostic accuracy in differentiating ADHDI from ADHD-HI and moderate accuracy for the other subtype comparisons. These findings support the development of objective biomarker- based diagnostic tools for precision psychiatry in ADHD.

Objective: This study examined the moderating effect of dating violence awareness on the relationship between clinginess and dating violence.

Methods: A survey was conducted online (Google Forms) and only those with dating experience (more than 3 months) were included in the study. A total of 450 participants were included in the final analysis (mean age=27.96 years, SD=5.04). The moderating effect was verified using the PROCESS macro for SPSS 2.16.

Results: The results showed that clinginess positively impacted dating violence. Second, past fixation, lack of nowness, and desire obsession were among the subfactors of clinginess that had a positive impact on dating violence. Third, dating violence awareness moderated the relationship between clinginess and dating violence.

Conclusion: This study provides a theoretical basis for preventing dating violence in early adulthood and providing intervention.

Objective: Stress and coping strategies can influence the onset and recurrence of mood episodes. Assessment and classification of stress-coping behaviors might be necessary for intervention to correct maladaptive coping strategies. This study aimed to explore clinical types of stress-coping behaviors in patients with mood disorders using cluster analysis, and compare clinical characteristics among clusters.

Methods: This study included 252 patients with mood disorders. Types of stress-coping behaviors were classified by cluster analysis using the scores of the Behavioral Checklist for Coping with Stress. Clinical characteristics, measured by Clinical Global Impression Severity, Mood Disorder Questionnaire, and Bipolar Spectrum Diagnostic Scale, Beck Depression Inventory-II, State-Trait Anxiety Inventory, were compared among clusters.

Results: Stress-coping behaviors were identified into four clusters named Balanced, Withdrawn, Impulsive, and Active Clusters. The Balanced Cluster used personal and social activities predominantly and was coping adaptively and less depressed. The Withdrawn Cluster showed significantly fewer coping behaviors and was more depressed. The Impulsive Cluster used pleasure-seeking behaviors predominantly and personal activities minimally. They showed more bipolarity and were depressed. The Active Cluster used the most numerous coping behaviors. They showed more bipolarity and were not depressed.

Conclusion: This study showed four types of stress-coping behaviors, such as Balanced, Withdrawn, Impulsive, and Active types, reflecting different clinical characteristics. Future research needs to be conducted to determine whether each type of stress-coping behavior is related to clinical prognosis in prospective studies and whether modification of coping behavior can improve prognosis.

Objective: This study examined the modifying effects of functional levels on the associations of the low frequency (LF) and high frequency (HF) components of heart rate variability (HRV) with post-traumatic stress disorder (PTSD) development.

Methods: Participants with physical injuries were recruited from a trauma center and followed for 2 years. Baseline assessments included LF, HF, and functional levels measured by the Social and Occupational Functioning Scale. Socio-demographic and clinical covariates were collected. PTSD diagnoses were made at 3, 6, 12, and 24 months post-injury using the Clinician-Administered PTSD Scale for DSM-5. Logistic regression analyses were performed to assess associations. Among 538 participants, 58 (10.8%) developed PTSD during the study period.

Results: A significant modifying effect was found: lower LF/HF were significantly associated with PTSD in patients with lower functioning levels, but not in those with higher functioning levels, with significant interaction terms.

Conclusion: The study observed functioning level-dependent associations between LF/HF and PTSD development, highlighting the buffering effects of higher functioning levels. These findings underscore the importance of considering functional status in PTSD risk assessments and the potential benefits of interventions aimed at enhancing social and occupational functioning to mitigate PTSD risk.

Objective: This study aims to identify the cognitive and psychological characteristics associated with suicide attempts in young adults with major depressive disorder (MDD).

Methods: The study involved 49 young adults aged 19-29 years diagnosed with MDD (28 attempters and 21 non-attempters) who visited psychological tests were retrospectively conducted. Additionally, data were collected from a healthy control (HC) group of 49 individuals, matched for age and gender, who were screened from the community. The Korean Beck Depression Inventory-2, Korean Reasons for Living Inventory, Korean Wechsler Adult Intelligence Scale-IV (K-WAIS-IV), Minnesota Multiphasic Personality Inventory-2 (MMPI-2) were used to assess psychological factors. Kruskal-Wallis was conducted to compare the mean differences among the three groups in each test.

Results: In the K-WAIS-IV, individuals with attempters and non-attempters exhibited significantly lower performance in the Full-Scale Intelligence, Perceptual Reasoning Index, and Processing Speed Index compared to the HCs. The MMPI-2 revealed significant differences between the suicide attempt and non-suicide attempt groups in scales Hypomanic Activation (RC9), Anger (ANG), Antisocial Practices (ASP), Social Responsibility (Re), MacAndrew's Alcoholism-Revised, Addiction, and Disconstraint (DISC).

Conclusion: Young adults with MDD who attempted suicide are characterized by heightened externalized psychological issues such as anger, impulsivity, and lack of control. This study provides clinical implications for reducing suicide risk and improving mental health among young adults with MDD.