Social Conditions and the Gender Binary: A Psycho-Social Investigation of Mental Health through a Gendered Lens

Prakriti Sharma
Symbiosis School for Liberal Arts


This paper aims to explore the relationship between specific social conditions and the extent of their influence in determining psychological outcomes. Conditions and norms established by a society on the basis of gender have resulted in an uneven distribution of psychological distress between sexes. This paper has deliberately limited its exploration to the gender binary. It assesses the principal contributing factors, as identified by existing research, and applies them to the Indian context. The objective is to demonstrate the linkages between social structures and functionality in influencing mental health outcomes. Social networks and support systems have illustrated how the difference in gender-specific social structures can result in impaired coping abilities. The discussion of gendered social roles outlines the importance of considering how men and women interpret these responsibilities and fulfil their role functions. The research revealed that it was not the frequency of negative events that mattered, but rather how much they could emotionally affect the individual. Gender-related violence like hate crimes suffered by women provides evidence of the direct impact of gender inequality on the increase in psychological disorders. The exploration of these ideas allowed an understanding of the practical issue they present in the fields of research and treatment. It was observed that a clear gender bias issue can be identified within research and treatment that deterred the efficiency and reliability of both. The research has identified a definite correlation between gender inequality and their effect on mental health even though these effects cannot be studied in isolation of other social factors. The paper concludes by making an effort to suggest preliminary recommendations to combat this.

Keywords: Gender binary, psychology, sociology, mental health, gender inequality, gender bias