Abstract Situations involving risk are common in human affairs, from financial investments, criminal behavior, and health-related decisions. Peoples’ self-reported risk preferences, where individuals in various ways report how they feel about risk, have been considered central to understanding why, and predict when, people behave differently in real-life situations involving risk. However, various other factors have also been suggested as predictors, including age, gender, education, income, anxiety, sensation seeking, impulsivity, and personality traits like neuroticism and extraversion. Still, research is limited on which factors best predict the frequency of risk-taking in real life. In this study, we asked respondents ( n = 760) to report how often they engaged in various risk-taking behaviors along with the abovementioned variables with the aim of predicting risk-taking frequency. The results from Bayesian multi-model inference analyses showed that the most important predictors of risk-taking frequency were impulsivity, sensation seeking, health and social risk preferences, and gender. The study highlights the importance of examining multiple variables simultaneously when predicting risk-taking frequency. The importance of the concept of general risk-preference, which occupies a central role in many influential theories of risk-taking, should arguably be reconsidered.
Asp et al. (Fri,) studied this question.