Nonverbal behavioral patterns predict social rejection elicited aggression.

Aggressive behavior Eye tracking Machine learning Social rejection

Journal

Biological psychology
ISSN: 1873-6246
Titre abrégé: Biol Psychol
Pays: Netherlands
ID NLM: 0375566

Informations de publication

Date de publication:
10 2023
Historique:
received: 10 01 2023
revised: 02 08 2023
accepted: 28 08 2023
pmc-release: 01 10 2024
medline: 10 10 2023
pubmed: 1 9 2023
entrez: 31 8 2023
Statut: ppublish

Résumé

Aggression elicited by social rejection is costly, prevalent, and often lethal. Attempts to predict rejection-elicited aggression using trait-based data have had little success. This may be because in-the-moment aggression is a complex process influenced by current states of attention, arousal, and affect which are poorly predicted by trait-level characteristics. In a study of young adults (N = 89; 18-25 years), machine learning tested the extent to which nonverbal behavioral indices of attention (eye gaze), arousal (pupillary reactivity), and affect (facial expressions) during a novel social interaction paradigm predicted subsequent aggression towards rejecting and accepting peers. Eye gaze and pupillary reactivity predicted aggressive behavior; predictions were more successful than measures of trait-based aggression and harsh parenting. These preliminary results suggest that nonverbal behavior may elucidate underlying mechanisms of in-the-moment aggression.

Identifiants

pubmed: 37652178
pii: S0301-0511(23)00190-4
doi: 10.1016/j.biopsycho.2023.108670
pmc: PMC10591947
mid: NIHMS1929299
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

108670

Subventions

Organisme : NIMH NIH HHS
ID : F31 MH125478
Pays : United States
Organisme : NICHD NIH HHS
ID : R21 HD093912
Pays : United States

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

M Quarmley (M)

Department of Psychology, Temple University, Philadelphia, PA, United States.

G Zelinsky (G)

Department of Psychology, Stony Brook University, Stony Brook, NY, United States.

S Athar (S)

Department of Computer Science, Stony Brook University, Stony Brook, NY, United States.

Z Yang (Z)

Department of Computer Science, Stony Brook University, Stony Brook, NY, United States.

J H Drucker (JH)

Aptima Inc., Woburn, MA, United States.

D Samaras (D)

Department of Computer Science, Stony Brook University, Stony Brook, NY, United States.

J M Jarcho (JM)

Department of Psychology, Temple University, Philadelphia, PA, United States. Electronic address: johanna.jarcho@temple.edu.

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