Facial emotion recognition in women with symptoms of polycystic ovary syndrome

Abstract

Prior research suggests that hormones, notably androgens, influence facial emotion recognition (FER). Most women with Polycystic Ovary Syndrome (PCOS) have elevated androgen levels and related androgenic symptoms, yet no study has directly explored the relationship between PCOS symptoms and FER. This thesis addressed this gap by investigating FER and self-reported PCOS symptoms. During the FER task, men and women identified emotions (anger, disgust, happiness, sadness or neutral) in images of emotional facial expressions. Both overall FER and accuracy recognizing each individual emotion were examined. PCOS symptom severity was assessed in women via self-report measures, including the Polycystic Ovary Syndrome Questionnaire (PCOSQ). Consistent with previous research, women were more accurate than men on FER. Additionally, women with provisional PCOS diagnoses were significantly less accurate at overall facial emotion recognition than women without provisional PCOS diagnoses, but this effect was driven by less accurate fear recognition. There was also a significant negative correlation between FER performance for fear and PCOS symptom severity (e.g., Hair Severity). A significant linear trend emerged for overall facial emotion recognition, revealing men as the least accurate, followed by women with provisional PCOS, and women without PCOS. These findings are consistent with the theory that androgens affect emotion recognition and suggest implications for PCOS symptoms on women's emotional well-being. The results may partly explain higher rates of mood disorders in women with PCOS and allow women with PCOS and healthcare providers to better understand the effects of PCOS.