Facet-level analysis of the relations between personality and laboratory aggression.

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    • Source:
      Publisher: Wiley-Liss Country of Publication: United States NLM ID: 7502265 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1098-2337 (Electronic) Linking ISSN: 0096140X NLM ISO Abbreviation: Aggress Behav Subsets: MEDLINE
    • Publication Information:
      Publication: <2005-> : Hoboken, N.J. : Wiley-Liss
      Original Publication: New York, Liss.
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    • Abstract:
      Multiple reviews and meta-analyses have identified the low pole of the Five-Factor Model (FFM) Agreeableness (also called Antagonism) as the primary domain-level personality correlates of aggression across self-report and behavioral methodologies. In the current study, we expand on this literature by investigating the relations between FFM facets and aggressive behavior as measured by laboratory competitive reaction time tasks (CRTTs). Across three samples (total N = 639), we conducted weighted mean analyses, multiple regression analyses, and dominance analyses to determine which FFM facets were the strongest predictors of aggression within and across domains. These analyses suggested that facets of Agreeableness were among the strongest consistent predictors of CRTT aggression, including Sympathy (r = -.21) and Cooperation (r = -.14), but facets from other FFM domains also yielded meaningful relations (e.g., Anger from Neuroticism; r = .17). We conclude by discussing these results in the context of controversies surrounding laboratory aggression paradigms and emphasizing the importance of considering small effect sizes in the prediction of societally harmful behavior like aggression.
      (© 2020 Wiley Periodicals, Inc.)
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    • Contributed Indexing:
      Keywords: antagonism; facet; five-factor model; laboratory aggression; personality
    • Publication Date:
      Date Created: 20200310 Date Completed: 20201016 Latest Revision: 20201016
    • Publication Date:
      20240105
    • Accession Number:
      10.1002/ab.21887
    • Accession Number:
      32149387