Perceived emotional intelligence and affective well-being amongst university students : a nonlinear CHAID approach

Abstract

Emotional intelligence (EI) has been consistently linked to positive affect (PA) and negative affect (NA). However, previous variable-centred research has primarily examined EI dimensions as independent, additive predictors, limiting our understanding of how these dimensions combine within individuals to form distinct affective profiles. This study examined the association between EI, assessed with the Trait Meta-Mood Scale (TMMS-24), and affect measured by the Positive and Negative Affect Schedule (PANAS). A nonlinear approach based on CHAID decision tree analysis was used, alongside hierarchical regression analyses to test methodological convergence. Participants included 364 students attending a Spanish university. CHAID analyses identified emotional repair as the main predictor of PA, with higher repair associated with greater PA. When repair was low or moderate, NA significantly reduced PA, whereas emotional attention was associated with higher PA when repair was moderate to high. Conversely, PA emerged as the primary predictor of NA, with higher PA associated with lower NA. Emotional attention was associated with higher NA, even among profiles characterized by moderate PA. In contrast, emotional clarity acted as a protective factor in profiles characterized by moderate PA and low-to-moderate attention, with higher clarity associated with lower NA. Findings from decision tree and regression models showed convergent patterns, suggesting that CHAID provides complementary configurational information rather than evidence of superior predictive performance. By identifying hierarchical thresholds and conditional profiles that traditional variable-centred models may overlook, this study offers a person-centred, nonlinear account of the association between perceived EI and affective well-being amongst university students.