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.