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Positive Automatic Cognitions Mediate the Relationship Between Personality and Trait Positive Affect
Authors:Owen Richard Lightsey Jr.  George Gharibian Gharghani  Aron Matthew Katz  Valerie Ann McKinney  Eli Benjamin Rarey
Affiliation:1. Department of Counseling, Educational Psychology and Research, The University of Memphis, 100 Ball Hall, Memphis, TN, 38112, USA
Abstract:
Positive affect (PA) has emerged as a key well-being facet and a powerful predictor of physical and psychological well-being. One of the strongest predictors of PA is personality, particularly neuroticism and extraversion. However, the mechanisms via which personality affects PA are not well-understood. Consistent with theories that accord cognitive factors a role in mediating the relationship between personality and outcomes, we tested whether positive automatic thoughts (PATs) mediated the relationship between neuroticism, extraversion, and PA among 199 college students (137 women, 70% White, 66% first and second year students, mean age = 24.13, SD = 8.86). Consistent with hypotheses, structural equation modeling indicated that PATs fully mediated the relationship between both neuroticism and extraversion and PA. The structural model fit the data well, χ2/df = 2.33, CFI = .96, SRMR = .07, RMSEA = .08 (90% CI: .06, .10), AIC = 172.45, and accounted for 58% of the variance in PA. An alternative model in which personality predicted PA, which in turn predicted PATs, did not provide as good a fit to the data, χ2/df = 3.03, CFI = .94, SRMR = .09, RMSEA = .10 (90% CI: .08, .12), AIC = 207.40. Models in which negative automatic thoughts (NATs) were construed as fully [χ2/df = 4.46, CFI = .95, SRMR = .08, RMSEA = .13 (90% CI: .11, .16)] or partially [χ2/df = 4.04, CFI = .96, SRMR = .06, RMSEA = .12 (90% CI: .10, .15)] mediating the relationship between neuroticism and negative affect did not provide a good fit to the data. A final model in which negative affect was tested a mediator of the relationship between neuroticism and NATs also did not fit the data well, χ2/df = 4.03, CFI = .96, SRMR = .07, RMSEA = .12 (90% CI: .10, .15).
Keywords:
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