Key result
Self-organizing maps analysis of >8,000 subjects and 600 variables identified mental disorders, alcoholism, impulsivity, and childhood abuse as the 4 main risk factor groups for suicide attempters.
Cohort (n=8,000)
Self-organizing maps can effectively identify nonlinear risk factor groupings (mental disorders, alcoholism, impulsivity, childhood abuse) in large cohorts of suicide attempters.
The study of the variables involved in suicidal behavior is important from a social, medical, and economical point of view. Given the high number of potential variables of interest, a large population of subjects must be analysed in order to get conclusive results. In this paper, we describe a method based on self-organizing maps (SOMs) for finding the most relevant variables even when their relation to suicidal behavior is strongly nonlinear. We have applied the method to a cohort with more than 8,000 subjects and 600 variables and discovered four groups of variables involved in suicidal behavior. According to the results, there are four main groups of risk factors that characterize the population of suicide attempters: mental disorders, alcoholism, impulsivity, and childhood abuse. The identification of specific subpopulations of suicide attempters is consistent with current medical knowledge and may provide a new avenue of research to improve the management of suicidal cases.
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Leiva-Murillo et al. (2013) conducted a cohort in Suicidal behavior (n=8,000). Self-organizing maps (SOMs) analysis was evaluated on Groups of variables involved in suicidal behavior. Self-organizing maps analysis of >8,000 subjects and 600 variables identified mental disorders, alcoholism, impulsivity, and childhood abuse as the 4 main risk factor groups for suicide attempters.
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