Mental health predictors in Spanish population: Age, gender, emotional intelligence and resilience

Abstract

Introduction: Anxiety, depression and stress are becoming more and more frequent, especially since the COVID-19 health crisis. The main objective of this study was to analyse the predictive power of age, gender, emotional intelligence, and resilience with respect to anxie-ty, depression, and stress-related symptoms in a Spanish population sample. Method: A total of 427 Spanish participants, between 18 and 83 years of age, were assessed through self-report instruments (TMMS-24; BRCS; BASS-21). Hierarchical regression models (HRM) and non-linear methodologies (qualitative comparative analysis or QCA models) are used. Results: The HRM showed that emotional attention, clarity, and repair significantly predicted anxiety, depres-sion, and stress. Gender also played a significant role, with women showing higher levels of anxiety and stress. Age and resilience were not significant predictors in the HRM. However, the QCA models revealed more nuanced interactions: high depression was linked to young age, high emotional attention, and low emotional clarity and repair. High anxiety was predicted by being female, young, with low emotional regulation, and high emotional attention. High stress was associated with being female, low resilience, and high emotional attention. Conversely, low levels of depression, anxiety, and stress were consistently associated with high resilience and emotional clarity and regulation. Conclusions: We consider these results to be of great interest for gaining a deeper understanding of the interaction between the variables under study. In this way, it will be possible to design more effective interventions that benefit from the maximum knowledge regarding the role of these variables.