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


Santamaría-García H, Baez S, Aponte DM, Pascariello GO, Donnelly-Kehoe PA, Maggiotti G, Matallana D, Hesse E, Neely A, Zapata JG, Chiong W, Levy J, Decety J, Ibáñez A.

Santamaría-García H, Baez S, Aponte DM, Pascariello GO, Donnelly-Kehoe PA, Maggiotti G, Matallana D, Hesse E, Neely A, Zapata JG, Chiong W, Levy J, Decety J, Ibáñez A. Uncovering social-contextual and individual mental health factors associated with violence via computational inference. Patterns, 2020 https://www.cell.com/patterns/fulltext/S2666-3899(20)30240-3

We assessed a comprehensive group of social-contextual and individual mental health factors to classify confessed acts of violence committed in the past among a large sample of Colombian ex-members of illegal armed groups (N = 26,349). We used a novel data-driven approach to classify subjects based on four confessed domains of violence (DoVs) and including two groups, (1) ex-members who admitted violent acts and (2) ex-members who denied violence in each DoV, matched by sex, age, and education stage. We found that accurate classification required both social-contextual and individual mental health factors, although the social-contextual factors were the most relevant. Our study provides population-based evidence on the factors associated with historical assessments of violence and describes a powerful analytical approach. This study opens up a new agenda for developing computational approaches for situated, multidimensional, and evidence-based assessments of violence.

 

 

 

 

 

 

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Santamaría-García H, Baez S, Aponte DM, Pascariello GO, Donnelly-Kehoe PA, Maggiotti G, Matallana D, Hesse E, Neely A, Zapata JG, Chiong W, Levy J, Decety J, Ibáñez A.
Viernes, Diciembre 18, 2020