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Hospital-Based Psychosocial Case Management and Suicide Prevention in South Korea: A Randomized Clinical Trial

2025-12-31T15:00:00Z

Title: Hospital-Based Psychosocial Case Management and Suicide Prevention in South Korea: A Randomized Clinical Trial All Author(s): Sang Min Lee; Kyoung-Hoon Kim; Kyu-Man Han; Min-Hyuk Kim; Min-Kyoung Kim; Kwang-Yeon Choi; A-La Park; Myungjae Baik; Ah Rah Lee; Peter Jongho Na; Hyeon-Ah Lee; Hwa-Young Lee; Jong-Woo Paik Abstract: Importance: South Korea maintains the highest suicide rate in the Organization for Economic Cooperation and Development, with major depressive disorder (MDD) being the leading diagnosis among suicide deaths. Evidence from large-scale randomized clinical trials (RCTs) is limited, particularly for diagnosis-specific, long-term programs in outpatient settings. Objective: To evaluate the effectiveness of a structured, hospital-based case management program in reducing suicidal ideation and associated clinical outcomes among patients with MDD. Design, setting, and participants: This RCT was conducted at 6 general hospitals in South Korea from January 18, 2021, to July 31, 2024. Participants included outpatients 18 years or older with MDD who had current suicidal ideation or a suicide attempt within the past 2 months. All efficacy analyses were performed according to the intention-to-treat principle. Intervention: Participants were randomized 1:1 to receive either 6 months of structured assertive case management (ACM) as an adjunct to standard treatment (n = 158) or usual psychiatric care alone (control [n = 156]). Main outcomes and measures: The primary outcome was the change from baseline to 6 months in the overall severity of suicidal thoughts and behaviors (STBs), as assessed by the Columbia-Suicide Severity Rating Scale (C-SSRS). Secondary outcomes included changes in depression, suicidal intent and ideation, anxiety, loneliness, impulsivity, quality of life, and service utilization. Results: Of 314 participants enrolled (mean [SD] age, 32.3 [13.1] years; 207 [65.9%] female), 158 were randomized to the ACM group and 156 to the control group; 245 (132 in the ACM and 113 in the control groups) completed the 6-month follow-up. The ACM group showed a significantly greater mean (SD) reduction in C-SSRS total score than the control group (-9.22 [0.49] vs -7.23 [0.50]; adjusted mean difference, -1.99 [95% CI, -3.37 to -0.61]; P = .005). Greater mean improvements were also observed in the ACM group for depressive symptoms (Hamilton Depression Rating Scale mean [SD] change, -9.19 [0.70] vs -6.23 [0.69]; P = .003), suicidal ideation (Beck Scale for Suicidal Ideation mean [SD] change, -7.96 [0.62] vs -5.58 [0.75]; P = .01), and anxiety (Generalized Anxiety Disorder-7 mean [SD] change, -3.90 [0.44] vs -1.85 [0.48]; P = .002). No significant between-group differences were observed in suicide attempts, and 1 suicide death occurred in the control group. Conclusions and relevance: In this RCT of outpatients with MDD and high suicide risk, ACM significantly reduced C-SSRS total scores and psychological distress compared with usual care. These findings provide a critical, high-level evidence base for the national implementation of standardized, hospital-centered psychosocial interventions as a scalable public health strategy for suicide prevention. Trial registration: Clinical Research Information Service Identifier: KCT0008123.

EEG microstate and functional connectivity analyses for differentiating suicide attempt from suicidal ideation in major depressive disorder

2024-12-31T15:00:00Z

Title: EEG microstate and functional connectivity analyses for differentiating suicide attempt from suicidal ideation in major depressive disorder All Author(s): Hyeon-Ho Hwang; Sungkean Kim; Se-Hoon Shim; Ji Sun Kim Abstract: Background: Suicide remains a critical public health issue, with self-report-based clinical assessments often failing to detect imminent risk. This study aimed to identify objective electroencephalography (EEG)-based neurobiological markers for differentiating a suicide attempt (SA) from suicidal ideation (SI) using EEG microstate and microstate-based functional connectivity (FC) analyses. Methods: From 2017 to 2020, this study enrolled 130 medication-naïve major depressive disorder patients (68 SA, evaluated within 7 days of the attempt; 62 SI) at Soonchunhyang University Cheonan Hospital. Resting-state EEG data were analyzed using microstate analysis to explore temporal dynamics of brain topography and microstate-based FC to assess connectivity in theta, alpha, and beta bands. Correlations between EEG features and psychological measures (e.g., suicidal ideation, depression, emotion regulation) were examined. Results: Compared with the SI group, the SA group showed a marginally lower frequency of occurrence for microstates A (auditory/language processing) and B (visual processing) (p = 0.078 for both). The SA group demonstrated significantly higher alpha-band FC during microstate E (linked to the default mode network (DMN)) for several electrode pairs (e.g., F7-C5, p = 0.009; FC5-C5, p = 0.005). The SA group also exhibited marginally higher FC in the alpha band during microstates C (DMN-related) and B, and in the theta band during microstate E. A subsequent within-group analysis revealed that in the SI group, alpha-band FC during microstate E positively correlated with scores for difficulties in emotion regulation (r = 0.433, p = 0.017). Limitations: Findings are limited by potential physiological confounds in the SA group and by the limited anatomical specificity inherent in sensor-space EEG analysis. Conclusion: EEG microstate dynamics and microstate-based FC differ between patients with SA and SI. Specifically, enhanced alpha-band connectivity during microstate E in the SA group potentially reflects condition-specific DMN functions. These EEG-based measures show promise as objective markers that complement clinical suicide risk assessment and inform early intervention strategies.

EEG microstate-based classification using machine learning in depressed adolescents with and without non-suicidal self-injury

2024-12-31T15:00:00Z

Title: EEG microstate-based classification using machine learning in depressed adolescents with and without non-suicidal self-injury All Author(s): Young Wook Song; Sungkean Kim; Hyeon-Ah Lee; Se-Hoon Shim; Ji Sun Kim Abstract: Non-suicidal self-injury (NSSI) is prevalent and concerning behavior among adolescents, particularly those diagnosed with major depressive disorder (MDD). The identification of the neural correlates associated with NSSI in this population is crucial for early detection and intervention. This study investigated the distinct electroencephalography (EEG) microstate patterns in adolescents with depression and NSSI. A total of 134 participants, including 44 MDD adolescents with NSSI, 41 MDD adolescents without NSSI, and 49 healthy controls (HCs) were enrolled, and their EEGs were recorded. Microstate analyses were conducted on all three groups. We performed a correlation analysis between the microstate parameters and psychological assessments. Machine learning algorithms were employed to classify the groups to identify patterns specific to the NSSI group. As for the global explained variance, duration, occurrence, and coverage, microstate B had significantly higher values in HCs than in MDD adolescents with and without NSSI. MDD adolescents with NSSI showed a significantly lower transition probability from class D to B than MDD adolescents without NSSI and HCs. Microstate parameters significantly correlated with psychological assessments. The best classification performances showed 77.42 % accuracy (95 % confidence interval 0.69-0.86, p < 0.001) between MDD adolescents with NSSI and HCs, 71.11 % accuracy (95 % confidence interval 0.61-0.80, p < 0.001) between MDD adolescents without NSSI and HCs, and 63.53 % (95 % confidence interval 0.53-0.74, p = 0.009) accuracy between MDD adolescents with NSSI and MDD adolescents without NSSI. This study investigated the utility of EEG microstate features as biomarkers of NSSI in adolescents with MDD. These findings help elucidate the neural mechanisms underlying NSSI and offer a potential biomarker for MDD adolescents with NSSI.

Evaluation of virtual reality-based guided imagery stabilization intervention for post-traumatic stress symptoms: a randomized controlled trial

2024-12-31T15:00:00Z

Title: Evaluation of virtual reality-based guided imagery stabilization intervention for post-traumatic stress symptoms: a randomized controlled trial All Author(s): Ruyun Dai; Jimoon Kim; Hojoon Choi; Yongmin Shin; Bin-Na Kim; Sungkean Kim; Kibum Kim; Ji Sun Kim Abstract: Post-traumatic stress symptoms (PTSS) have been widely reported among individuals affected by the COVID-19 pandemic. Stabilization interventions aim to reduce distress and enhance emotional regulation as a preparatory step for trauma-focused therapy. This study evaluated a virtual reality (VR)–based stabilization program adapted from three validated guided imagery techniques: light stream, mindful breathing, and containment. In a randomized controlled trial comparing the VR intervention with an imagery- and audio-based mobile App delivering the same therapeutic scripts, participants in the VR group showed significantly greater reductions in PTSS on both self-reported and clinician-rated measures. Moreover, only the VR group demonstrated significant improvements in post-traumatic growth, quality of life, and autonomic regulation indexed by heart rate variability (HRV). These findings suggest that immersive VR can enhance the delivery of stabilization techniques and provide additional psychological and physiological benefits beyond conventional app-based methods.