期刊
PERSONALITY AND INDIVIDUAL DIFFERENCES
卷 136, 期 -, 页码 140-147出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.paid.2017.12.032
关键词
Big Five; Everyday context; Affect; Experience sampling methodology; Poisson regression; Multilevel modeling
资金
- National Institute for Mental Health, National Research Service Award [F31-MH093041]
- Society of Multivariate Experimental Psychology
- National Science Foundation [SMA-1419324]
- Direct For Social, Behav & Economic Scie
- SBE Off Of Multidisciplinary Activities [1419324] Funding Source: National Science Foundation
Prior research shows that personality traits predict time spent with different people and frequency of engagement in different activities. Further, personality traits, company, and activity are related to the experience of affect. However, little research has examined personality, context, and affect together in the same study. In the current study, 78 people described their Big Five traits and took part in a 1-week experience sampling study using mobile phones as a means for data collection. Participants indicated their current company, activity, and momentary affect along the dimensions of energetic arousal (EA), tense arousal (TA), and hedonic tone (HT). Poisson regressions revealed that traits predicted higher frequencies of trait-consistent contexts: for example, extraversion was related to more frequently being with various types of company. Results predicting contexts from multilevel logistic regressions were sparser. Multilevel models revealed that traits and contexts had main effects on affect, yet there were relatively few interactions of traits X contexts predicting affect. We discuss more specific implications of these findings.
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