Sociodemographic and Geographic Influences of Mental Health Literacy: A Cross-Sectional Survey Among Community Health Clinic Attendees in Tshwane, South Africa.

Urban clinic attendees were significantly more likely to correctly identify mental disorders than township clinic attendees.

• Odds ratio of 0.32 (95% CI: 0.11, 0.93) for township versus urban clinic attendees
• Wald χ²(1): 4.3681; p value = 0.036
• Geographic location was identified as a significant predictor of correct disorder recognition alongside gender and level of education

Urban clinic attendees were significantly more accurate at identifying the correct cause of mental disorders than township clinic attendees.

• Odds ratio of 0.42 (95% CI: 0.21, 0.83) for township versus urban clinic attendees
• Wald χ²(1): 6.1504; p value = 0.013
• Significant predictors of correct cause identification included gender, education level, and geographic location

The study sample had a mean age of 37.39 years with a wide age range across five community health clinic sites in Tshwane.

• Mean age was 37.39 ± 11.14 years with a range of 13–80 years
• A total of 385 participants were recruited through convenience sampling
• Approximately 77 individuals were recruited per clinic across five sites
• Data were collected between November 2019 and January 2020

Gender and level of education were significant predictors of both mental disorder recognition and identification of correct causes.

• Gender was a significant predictor for both correct recognition of disorders and correct identification of causes
• Education level was a significant predictor for both correct recognition of disorders and correct identification of causes
• Hierarchical logistic regression was used to identify these predictors
• Statistical significance was set at p < 0.05

Mental health literacy was assessed using three fictive clinical case studies representing major mental disorders.

• Three fictive cases with clinical pictures indicative of major depressive disorder, schizophrenia, and generalized anxiety disorder were used
• Two dimensions were assessed: disorder recognition ('what type of illness do you think the person is suffering from') and perceived causes ('what do you think causes the persons' suffering')
• A two-part questionnaire was used, with part A covering demographics and part B covering the clinical case studies
• Participants' responses were analyzed via Pearson's chi-square tests and hierarchical logistic regression