ArticlePatterns (New York, N.Y.)2021
Uncovering social-contextual and individual mental health factors associated with violence via computational inference.
Article in Patterns (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- Understanding violence as a health determinant among ethnic communities in Colombia's Pacific region: a qualitative analysis.Cadernos de saude publica · 2026Article
- Relearning the epistemology, history, and future of neuropsychiatry.Frontiers in human neuroscience · 2026Review
- Predicting neighborhood-level violence from features of the physical and social environment with machine learning.Injury epidemiology · 2025Article
- Resilience and brain health in global populations.Nature medicine · 2025Review
- Factors associated with healthy aging in Latin American populations.Nature medicine · 2023Article
- The impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations.GeroScience · 2023Article
- Source space connectomics of neurodegeneration: One-metric approach does not fit all.Neurobiology of disease · 2023Article
- Understanding mental health through computers: An introduction to computational psychiatry.Frontiers in psychiatry · 2023Review
- Predicting and Characterizing Neurodegenerative Subtypes with Multimodal Neurocognitive Signatures of Social and Cognitive Processes.Journal of Alzheimer's disease : JAD · 2021Article
- Harmonized multi-metric and multi-centric assessment of EEG source space connectivity for dementia characterization.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
14 authors at 9 institutions in 6 countries.
Funding
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 factors. Combined social network adversities, membership identification, and normalization of violence were among the more accurate social-contextual factors. To a lesser extent the best individual factors were personality traits (borderline, paranoid, and antisocial) and psychiatric symptoms. The results provide a population-based computational classification regarding historical assessments of violence in vulnerable populations.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.