Do More of What Makes You Happy? The Applicability of Signature Character Strengths and Future Physicians’ Well-Being and Health Over Time

Frontiers in Psychology 12 (2021)
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Abstract

Research on applying signature character strengths demonstrated positive effects on well-being, health and work behavior. Future health care professionals represent a group at risk for impaired well-being due to high study demands. This study investigates potential long-term protective effects on well-being. In total, 504 medical students participated in a longitudinal online study, with at least 96 providing complete data at all three time points. Data on individual signature character strengths and their applicability, thriving, work engagement, burnout, mental and physical health were collected. Longitudinal relations of signature character strengths’ applicability and well-being, mental and physical health were tested with cross-lagged panel analyses. Moreover, indirect longitudinal mediation effects via work engagement and emotional exhaustion were considered. Cross-lagged panel analyses demonstrated significant positive effects of thriving on signature character strengths’ applicability at later time points indicating that higher levels of well-being might be mandatory first to have access to one’s own signature character strengths in a naturalistic setting. Disentangling thriving, the effect was only significant for psychological well-being. Across all three time points, significant indirect effects via work engagement on the relation of the applicability of signature character strengths and well-being were identified, whereas significant indirect effects on mental and physical health were only evident at t2 and t3. A longitudinal mediation analysis via work engagement revealed a significant indirect effect. These results call for further research as previous studies showed that the applicability of signature character strengths affected well-being, not vice versa. The ‘broaden-and-build’ theory and the assumption of well-being in a “top-down” model could possibly explain these novel results.

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