Cross-sectional study shows that mood states mediate and moderate emotional intelligence's link to suicidal ideation in university students, highlighting potential targets for suicide prevention.
Suicidal ideation (SI) is an emerging public health problem in university students in Bangladesh, but its psychological antecedents are not well understood. The aim of this cross-sectional study was to investigate the link between emotional intelligence (EI) and SI and to test mood states as parallel mediators and as moderators of this association in separate models. The University of Rajshahi undergraduate and postgraduate students (M age = 23.32, SD = 1.34, 82.5% female) filled out the Adult Suicidal Ideation Questionnaire (ASIQ), the Emotional Intelligence Scale (EIS), and the Bengali Brunel Mood Scale (BRUMS). Three parallel mediational models using Hayes’ PROCESS Macro (Model 4) and three separate hierarchical OLS moderation models were used to test the six BRUMS subscales as mediators and moderators of the association between EI and SI, respectively. There was a significant negative correlation between EI and SI ( r = − 0.37, p < 0.001). Depressive mood (β = − 0.09, 95% CI [− 0.15, − 0.04]), tension (β = −0.05 [− 0.10, − 0.01]), anger (β = −0.03 [− 0.07, − 0.001]), and vigor (β = 0.04 [0.01, 0.08]) were significant parallel mediators, together accounting for 29.5% of the total EI–SI effect. The association between EI and SI was also significantly moderated by all four mood subscales in separate models, with higher negative mood being associated with a stronger negative correlation, and higher vigor being associated with higher negative correlation. Mood also seemed to be a statistical mediator as well as an independent moderator of the relationship between EI and SI, lending weight to the idea that EI is a protective factor whose effect has some variability that appears to be moderated by mood. They nonetheless suggest that a promising approach for future research on intervention in Bangladeshi higher education is to focus on EI and mood-based programming.
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Islam et al. (2026) studied this question.
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