Cognitive and Affective Influences on Decision Quality

Introduction: Cognitive and affective factors influence decision outcomes, but few studies have examined both factors simultaneously. Study 1 used cluster analysis to test whether affective profiles related to decision domains could be identified as individual difference factors. Study 2 extended these findings to test whether such profiles can predict decision quality. Methods:  We analyzed importance and meaningfulness ratings from 1123 adults regarding four low-frequency but high-salience decisions. Profile analyses revealed three meaningful profiles. A subset (n = 56) of adults completed quasi-experimental decision tasks in two of these domains. Results: Hierarchical regression examined the contributions of the affective cluster from Study 1 and executive functions to decision quality. We first regressed decision quality onto an index of executive function (F (1, 53) = 4.57, p = .037). At Step 2, affective cluster accounted for an additional 12.5% of the variance in decision quality, Fchange (2, 51) = 4.01, p = .024.  The overall model retained its significance, F (3, 51) = 4.37, p = .008, R2 = .205.  Conclusions: Together, Study 1 and 2 demonstrate that affective components related to the decision domain can be used as individual difference factors and that these account for unique variance in decision outcomes.