40 Sex Differences in Emotional Intelligence Ability and Risk-Taking Behavior

Abstract

Objective:

People differ in their propensity to engage in risky behaviors. Numerous factors such as cognition and personality have been utilized in predicting risk-taking, but little is known about the influence of stable emotional competencies, such as Emotional Intelligence (EI), in risk-taking. EI is defined as the ability and capacity to understand, perceive, and manage one's own, as well as others', emotions. However there has been little published research on the effect of ability emotional intelligence in engaging in risk- taking behavior. We hypothesized that those with higher emotional intelligence ability scores would demonstrate higher and more optimal risk-taking propensity. Furthermore, as prior research has demonstrated that males engage in more risk-taking behaviors, we accounted for sex differences within our analysis.

Participants and Methods:

One-hundred and twelve healthy adults completed this study, including 56 females (Mage=21.7, SD=5.8) and 56 males (Mage=21.5, SD=3.2). The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) was used to assess total EI ability while the Balloon Analog Risk Task (BART) was used to assess risk-taking propensity. We specifically analyzed adjusted number of pumps on unexploded balloons throughout the BART to account for the increased risk. We conducted Pearson correlations and a multiple regression to assess the if ability emotional intelligence and gender significantly predicted risk-taking propensity.

Results:

There was a significant correlation between total emotional intelligence ability score and adjusted number of pumps on the BART for females, r(55)=.362, p = .006, but not for males r(55)=.053, p=.701, suggesting that females who score higher in emotional intelligence ability also had a higher risk-taking propensity. Due to these findings, we conducted a multiple regression to assess if ability emotional intelligence and gender significantly predict risk-taking propensity on the BART. The results of the regression indicated the two predictors explained 9.0% of the variance (R² =.09, F(2,108)=5.32, p<.01). However, it was found that ability emotional intelligence significantly predicted risk-taking propensity (β = .23, p<.05), but not sex (β = -.17, p=.06). There was no sex x EI interaction.

Conclusions:

Higher ability emotional intelligence was significantly related to greater risk-taking propensity, but this was only observed for females. However, the lack of significance of sex in significantly predicting risk-taking may just be due to lower statistical power in the study. Importantly, the adjusted number of pumps for the participants in this sample was generally far below the mid-point for popping balloons, suggesting that the higher scores observed here represent more optimal decision performance rather than just greater risk. Thus, greater EI may reflect greater capacity to learn from reward and punishment feedback and apply that learning to optimize performance. Future research should look at the effect of emotional intelligence training in improving optimal risk-taking, particularly for populations known for engaging in risky behaviors such as those with mTBI.