Women in Science, Technology, Engineering, and Mathematics (STEM) Fields: The Importance of the Need to Belong and Self-Esteem on the Intention to Leave a Job

The purpose of the study was to predict individual intentions to leave science, technology, engineering, and mathematics (STEM) field jobs. Psychological predictors were gender, the need to belong, self-esteem, perceived personal discrimination, and perceived group discrimination. We used the Amazon Mechanical Turk to recruit participants and Survey Monkey to conduct an online survey. Participants were 174 men and women who worked or studied in STEM fields. Two-step hierarchical linear regression analyses were performed to analyze the data. As a result, we found that all predictors mentioned above accounted for the variance in the intention to leave a job. Self-esteem and perceived personal discrimination were critical predictors for men in STEM fields; self-esteem and perceived group discrimination were critical predictors for women in STEM fields. For women, interestingly, the interaction effect of the need to belong and self-esteem added an additional variance in predicting the intention to leave a job. The need to belong buffered the effect of self-esteem on the intention of STEM women to leave a job. Thus, it might be that STEM women with low self-esteem are more likely to change a job if their need to belong is not fulfilled