Background: Past research has shown that emotional intelligence (EI) and core self-evaluations (CSE) have a unique and independent role in the prediction of psychological maladjustment in the unemployed population. However, no one to date has examined the joint contribution of EI and CSE in predicting well-being and psychological distress among the unemployed. Our objective was to examine the main and interactive role of EI and CSE in the prediction of indicators for happiness, depression, stress, and anxiety beyond socio-demographics variables.

Methods: A sample of 1796 unemployed participants completed a battery that included socio-demographic data and questionnaires of EI, CSE, happiness, depression, stress, and anxiety. We processed the data with SPSS and Hayes PROCESS macro.

Results: Pearson correlation analyses showed significant associations between EI and CSE with different mental health outcomes. Moderation analyses revealed that, beyond the main effects, the interactive term EI × CSE increased the explained variance of the prediction of happiness, but not of depression, anxiety, or stress.

Limitations: The study comprised an incidental non-clinical sample of unemployed adults, so the results might not generalize to a clinical population. Also, the study was cross-sectional, and we relied only on self-report measures, which do not allow for establishing causal links and might include biases, such as social desirability and common method variance.

Conclusions: These findings highlight the need for developing more comprehensive models including the interaction of EI and dispositional traits as contributing factors in the prediction of positive outcomes among the unemployed. Also, future promotion programs should include dimensions related to EI and CSE for increasing well-being during unemployment.

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http://dx.doi.org/10.1016/j.jad.2019.06.042DOI Listing

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