Uncovering social-contextual and individual mental health factors associated with violence via computational inference.

ABSTRACT: The identification of human violence determinants has sparked multiple questions from different academic fields. Innovative methodological assessments of the weight and interaction of multiple determinants are still required. Here, we examine multiple features potentially associated with confessed acts of violence in ex-members of illegal armed groups in Colombia (N = 26,349) through deep learning and feature-derived machine learning. We assessed 162 social-contextual and individual mental health potential predictors of historical data regarding consequentialist, appetitive, retaliative, and reactive domains of violence. Deep learning yields high accuracy using the full set of determinants. Progressive feature elimination revealed that contextual factors were more important than individual

SUBMITTER: Santamaria-Garcia H 

PROVIDER: S-EPMC7892360 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature