Department of Psychology, Temple University, Philadelphia, PA, United States.
Department of Psychology, Stony Brook University, Stony Brook, NY, United States.
Biol Psychol. 2023 Oct;183:108670. doi: 10.1016/j.biopsycho.2023.108670. Epub 2023 Aug 29.
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.
社会拒绝引发的攻击行为代价高昂、普遍存在且常常致命。使用基于特质的数据预测拒绝引发的攻击行为收效甚微。这可能是因为即时攻击是一个复杂的过程，受到注意力、唤醒和情绪的当前状态的影响，而特质水平的特征很难预测这些状态。在一项对年轻人（N=89；18-25 岁）的研究中，机器学习测试了在新的社会互动范式中，非言语行为注意力（目光接触）、唤醒（瞳孔反应）和情绪（面部表情）的非言语行为指标在多大程度上可以预测随后对拒绝和接受同伴的攻击行为。目光接触和瞳孔反应可以预测攻击行为；预测结果优于基于特质的攻击行为和严厉养育方式的测量结果。这些初步结果表明，非言语行为可能阐明了即时攻击行为的潜在机制。
