ABSTRACT
Understanding and eliminating mental illness stigma is crucial for improving population mental health. In many settings, this stigma is gendered, from the perspectives of both the stigmatized and the stigmatizers. We aimed to find the differences in the level of stigma across different mental disorders while considering the gender of the study participants as well as the gender of the people depicted in the vignettes. This was a population-based, experimental vignette study conducted in Buyende District of Eastern Uganda in 2023. We created 8 vignettes describing both men and women with alcohol use disorder, major depressive disorder, generalized anxiety disorder, and schizophrenia consistent with DSM-5 criteria. Participants from 20 villages in rural Buyende District of Uganda (N=379) were first read a randomly selected vignette and administered a survey eliciting their attitudes (Personal Acceptance Scale [PAS] and Broad Acceptance Scale [BAS]) towards the person depicted in the vignette. We used analysis of variance (ANOVA) with Bonferroni-adjusted, empirical p-values to compare levels of acceptance across disorders and genders. Attitudes towards people with mental illness, as measured by the PAS, varied across different mental disorders (p=0.002). In pairwise mean comparisons, the greater acceptance of anxiety disorder vs. schizophrenia was statistically significant (Mean [SD] PAS: 2.91 [3.15] vs 1.62 [1.95], p=0.008). Secondary analyses examining differences in acceptance across gender combinations within mental disorders showed that PAS varied across gender combinations for depression (p=0.017), suggesting that acceptance is higher for women with depression than men with depression. In this population-based vignette study from rural Uganda, we found that people with schizophrenia were less accepted compared to people with anxiety disorders. We also found that there was greater acceptance of women with depression than men with depression. Anti-stigma initiatives may need to be targeted to specific disorders and genders.