Suicide Typologies in the United States Air Force: A Hierarchical Cluster Analysis

Characteristics of suicide attempts associated with lethality and method: A latent class analysis of the Military Suicide Research Consortium

While suicide prevention is a national priority, particularly among service members and veterans (SMVs), understanding of suicide-related outcomes remains poor. Person-centered approaches (e.g., latent class analysis) have promise to identify unique risk profiles and subgroups in the larger population. The current study identified latent subgroups characterized by prior self-directed violence history and proximal risk factors for suicide among suicide attempt survivors, and compared subgroups on demographics and most-lethal attempt characteristics. Participants included civilians and SMVs reporting lifetime suicide attempt(s) (n = 2643) from the Military Suicide Research Consortium. Two classes emerged from Common Data Elements: suicide attempt and non-suicidal self-injury frequency, suicide attempt method, perceived likelihood of future suicide, suicide disclosure, suicide intent, and perceived and actual lethality of attempt. A Higher-Risk History class was characterized by greater intent to die, certainty about attempt fatality and method lethality, belief injury would be medically unfixable, and likelihood of prior non-suicidal self-injury. A Lower-Risk History class was characterized by greater ambivalence toward death and methods. Higher-Risk class members were more likely to be male, older, SMVs, have less formal education, use firearms as most-lethal attempt method, and require a higher degree of medical attention. Lower-Risk class members were more likely to be female, civilian, use cutting as most-lethal attempt method, and require less medical attention for attempts. Findings have implications for risk assessments and highlight the importance of subjective perceptions about suicidal behavior. Further investigation of real-time individual-level is necessary, especially for SMVs who may be at greatest risk for potentially lethal suicidal behavior.

Overtime working patterns and adverse events in work-related suicide cases: hierarchical cluster analysis of national compensation data in Japan (fiscal year 2015-2016)

Background

Although various work-related adverse events affect workers’ mental health, the association between long working hours and mental disorders remains unclear. We investigated the characteristics of overtime work and work-related adverse events among all cases of compensated work-related suicide in Japan to empirically reveal the context of the serious consequences.

Methods

We analysed all 167 cases of mental disorders resulting in suicide that were compensated in fiscal year 2015–2016. Hierarchical clustering was applied to the overtime working history. Work-related adverse events were also evaluated as the qualitative aspects of their jobs.

Results

More than half of the cases committed suicide within a month of developing a mental disorder. The Administrative and professional or engineering workers had a higher suicide rate. The clustering analysis revealed chronic long working hours (19%), gradual increase (27%), or rapid increase (25%) in working hours before the onset of a mental disorder. A group of cases with less overwork experienced more interpersonal conflicts.

Conclusion

This is the first study to employ a clustering technique to objectively reveal the actual working patterns behind suicide. The patterns of working overtime before the onset of mental disorders varied considerably among the cases. Taking the transition of working overtime into account may provide clearer insight into the relationship between long working hours and workers’ mental health. These results highlight the need for countermeasures especially for causes of chronic overworking, drastic increases in working hours, and interpersonal conflicts to prevent work-related suicide.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00420-021-01760-5.