Analiz Riska Zdorovʹû (Mar 2024)

Prognosis of suicidal risk among law enforcement officials including military personnel

  • E.S. Shchelkanova,
  • M.R. Nazarova,
  • I.M. Gudimov,
  • N.A. Galkin,
  • E.A. Zhurbin

DOI
https://doi.org/10.21668/health.risk/2024.1.14.eng
Journal volume & issue
no. 1
pp. 141 – 149

Abstract

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Suicide is a major medical and social concern for law enforcement, a contemporary army included, not only in Russia but abroad as well. In recent years, frequency of suicides and suicidal attempts has been growing among law enforcement officials (LEOs), military personnel included. Therefore, it seems relevant to develop a model for predicting suicide risk. In this study, our aim was to develop a model for predicting suicide risk in LEOs based on express testing results. Our research object was represented by LEOs (n = 591), their average age being 23.71 ± 1.12 years. To assess suicide risk, we used a questionnaire for suicide risk assessment ‘SSR-2’, which is a part of DAP-2 methodology for deviant behavior research, and a clinical-psychopathological method. LEOs’ personality characteristics and their current psychophysiological state were identified by using vibration imaging, a technology for recording and mathematically analyzing micro-vibrations of the head and face. It has certain advantages over its analogues. We determined psychophysiological characteristics, basic abilities (types of Gardner’s multiple intelligence) and moral qualities that differed in people with elevated suicide risk against the control. We identified a difference between unconscious reactions of the examined people to stimuli and declared (conscious) ones, which indicates that LEOs tend to hide any signs of suicidal behavior in them. A mathematical model was built for predicting suicide risk: we developed an integral suicide risk assessment and created a probabilistic nomogram that makes it possible to establish likelihood of suicidal behavior signs with accuracy above 98 % relying on results obtained by a 5-minute express test. Use of this predictive model helps identify those people among personnel who should undergo a profound check-up by a psychological support team. Our research results can serve as a basis for creating an objective concept for diagnostics of suicide risk factors in LEOs.

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