Affiliation:
1. Department of Psychosocial Science University of Bergen Bergen Norway
2. Department of Developmental Psychology and Socialisation University of Padua Padua Italy
3. Department of Sociology Central South University Changsha China
4. Norwegian Competence Center for Gambling and Gaming Research University of Bergen Bergen Norway
Abstract
Hostility towards women is a type of prejudice that can have adverse effects on women and society, but research on predictors of men's hostility towards women is limited. The present study primarily introduced predictors associated with misogynist involuntary celibates (incels), and then investigated whether loneliness, rejection, attractiveness, number of romantic and sexual partners, right‐wing authoritarianism, and gaming predicted hostility towards women among a more general sample of men. A total of 473 men (aged 18–35, single, heterosexual, UK residents) recruited via Prolific answered the hostile sexism subscale, the misogyny scale, the self‐perceived sexual attractiveness scale, the right‐wing authoritarianism scale, the game addiction scale for adolescents, the adult rejection‐sensitivity scale, the UCLA loneliness scale, and self‐developed questions regarding number of sexual and romantic partners, and time spent gaming. We found a strong positive relationship between right‐wing authoritarianism and hostility towards women, as well as a strong convex curvilinear relationship between attractiveness and hostility towards women. The number of sexual partners showed a moderate concave relationship with hostility towards women. We did not find sufficient support for a relationship between gaming and hostility towards women, and there was no support that loneliness, rejection, or romantic partners predicted hostility towards women among a general sample of men. Our study supports right‐wing authoritarianism and self‐perceived attractiveness as potential strong predictors in understanding men's hostility towards women in the wider community.Pre‐registration: https://osf.io/ms3a4.