How Is the Suicide Ideation in the Korean Armed Forces Affected by Mental Illness, Traumatic Events, and Social Support?

BACKGROUND: Suicide is one of the leading causes of death in the military as in the general population. To mitigate such a serious public health problem, identifying the risk or protective factors of suicide behaviors is crucial. METHODS: We analyzed the representative data of the 2014 Korean Armed Forces to explore the relationship between past year adverse events (PAE), accumulated lifetime trauma (ALT), mental illness vulnerability, perceived social support, and suicidal ideation in the previous year. RESULTS: Among the 6,377 subjects, 3.7% of males and 6.2% of females reported suicidal ideation in the previous year. Multivariate analytic models identified significant associations of PAE and ALT with suicidal ideation with a dose-response pattern. The mental illness vulnerability showed the most significant association with suicidal ideation even after controlling PAE or ALT. We found that perceived social support may be potentially linked with a reduced risk of suicidal ideation. CONCLUSION: This Korean military representative data demonstrates mental illness vulnerability; PAE; and lifetime trauma as significant risk factors of suicidal ideation, while perceived social support was found as a potential protective factor. Given the importance of the prevention of suicide in the military, those risk and protective factors may be used to screen soldiers at risk of suicide and provide further support on mental health services as needed.

Large-Scale Functional Brain Network Architecture Changes Associated With Trauma-Related Dissociation.

OBJECTIVE: Dissociative experiences commonly occur in response to trauma, and while their presence strongly affects treatment approaches in posttraumatic spectrum disorders, their etiology remains poorly understood and their phenomenology incompletely characterized. Methods to reliably assess the severity of dissociation symptoms, without relying solely on self-report, would have tremendous clinical utility. Brain-based measures have the potential to augment symptom reports, although it remains unclear whether brain-based measures of dissociation are sufficiently sensitive and robust to enable individual-level estimation of dissociation severity based on brain function. The authors sought to test the robustness and sensitivity of a brain-based measure of dissociation severity. METHODS: An intrinsic network connectivity analysis was applied to functional MRI scans obtained from 65 women with histories of childhood abuse and current posttraumatic stress disorder (PTSD). The authors tested for continuous measures of trauma-related dissociation using the Multidimensional Inventory of Dissociation. Connectivity estimates were derived with a novel machine learning technique using individually defined homologous functional regions for each participant. RESULTS: The models achieved moderate ability to estimate dissociation, after controlling for childhood trauma and PTSD severity. Connections that contributed the most to the estimation mainly involved the default mode and frontoparietal control networks. By contrast, all models performed at chance levels when using a conventional group-based network parcellation. CONCLUSIONS: Trauma-related dissociative symptoms, distinct from PTSD and childhood trauma, can be estimated on the basis of network connectivity. Furthermore, between-network brain connectivity may provide an unbiased estimate of symptom severity, paving the way for more objective, clinically useful biomarkers of dissociation and advancing our understanding of its neural mechanisms.