Background: There is growing awareness of the need for effective prevention, early detection, and novel treatment approaches for common mental disorders (CMDs) among university students. Reliable epidemiological data on prevalence and correlates are the cornerstones of planning and implementing effective health services and adopting a public health approach to student wellness. Yet, there is a comparative lack of sound psychiatric epidemiological studies on CMDs among university students in low-and middle-income countries, like South Africa (SA). It is also unclear if historically marginalised groups of students are at increased risk for mental health problems in post-apartheid SA. The objective of the study was to investigate the prevalence and sociodemographic correlates of lifetime and 12-month CMDs among university students in SA, with a particular focus on vulnerability among students in historically excluded and marginalised segments of the population. Methods: Data were collected via self-report measures in an online survey of first-year students registered at two large universities (n = 1402). CMDs were assessed with previously-validated screening scales. Data were weighted and analysed using multivariate statistical methods. Results: A total of 38.5% of respondents reported at least one lifetime CMD, the most common being major depressive disorder (24.7%). Twelve-month prevalence of any CMD was 31.5%, with generalised anxiety disorder being the most common (20.8%). The median age of onset for any disorder was 15 years. The median proportional annual persistence of any disorder was 80.0%. Female students, students who reported an atypical sexual orientation, and students with disabilities were at significantly higher risk of any lifetime or 12-month disorder. Female gender, atypical sexual orientation, and disability were associated with elevated risk of internalising disorders, whereas male gender, identifying as White, and reporting an atypical sexual orientation were associated with elevated risk of externalising disorders. Older age, atypical sexual orientation, and disability were associated with elevated risk of bipolar spectrum disorder.

Background: Addressing inequalities in mental healthcare utilisation among university students is important for socio-political transformation, particularly in countries with a history of educational exclusion. Methods: As part of the WHO World Mental Health International College Student Initiative, we investigated inequalities in mental healthcare utilisation among first-year students at two historically "White" universities in South Africa. Data were collected via a web-based survey from first-year university students (n = 1402) to assess 12-month mental healthcare utilisation, common mental disorders, and suicidality. Multivariate logistic regression models were used to estimate associations between sociodemographic variables and mental healthcare utilisation, controlling for common mental disorders and suicidality. Results: A total of 18.1% of students utilised mental healthcare in the past 12 months, with only 28.9% of students with mental disorders receiving treatment (ranging from 28.1% for ADHD to 64.3% for bipolar spectrum disorder). Of those receiving treatment, 52.0% used psychotropic medication, 47.3% received psychotherapy, and 5.4% consulted a traditional healer. Treatment rates for suicidal ideation, plan and attempt were 25.4%, 41.6% and 52.9%, respectively. In multivariate regression models that control for the main effects of mental health variables and all possible joint effects of sociodemographic variables, the likelihood of treatment was lower among males (aOR = 0.57) and Black students (aOR = 0.52). An interaction was observed between sexual orientation and first generation status; among second-generation students, the odds of treatment were higher for students reporting an atypical sexual orientation (aOR = 1.55), while among students with atypical sexual orientations, the likelihood of mental healthcare utilisation was lower for first-generation students (aOR = 0.29). Odds of treatment were significantly elevated among students with major depressive disorder (aOR = 1.88), generalised anxiety disorder (aOR = 2.34), bipolar spectrum disorder (aOR = 4.07), drug use disorder (aOR = 3.45), suicidal ideation (without plan or attempt) (aOR = 2.00), suicide plan (without attempt) (aOR = 3.64) and suicide attempt (aOR = 4.57). Likelihood of treatment increased with level of suicidality, but not number of mental disorders. Conclusion: We found very low mental healthcare treatment utilisation among first-year university students in South Africa, with enduring disparities among historically marginalised groups. Campus-based interventions are needed to

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Considerable evidence suggests that mood disturbance is common among patients living with HIV and may be an important barrier to anti-retroviral therapy (ART) adherence. Thus the assessment of depressed mood is an important and necessary aspect of the experience of persons living with HIV as it may impact the health status of individuals directly and indirectly. We sought to determine the factor structure of the Beck Depression Inventory (BDI) among a sample of 185 South Africans living with HIV and receiving ART. The mean BDI score was 16.5 (SD 12.15) with a range from 0-50 (out of a possible 63), indicating on average moderate levels of depression. Cronbach's alpha for the total scale was 0.90. Although the four factors had eigenvalues that were technically above 1.0, only three factors could logically be extracted, the combination of which accounted for 47.29% of the variance. These three factors were Cognitive, Affective and Somatic. The results indicate that the BDI-II is a reliable measure of symptoms of depression among persons living with HIV. The factor structure among South Africans receiving ART is similar to that of other samples, although surprisingly, the item assessing appetite disturbance did not load on any factor. The results of the study suggest that the BDI-II is a useful measure among South Africans living with HIV. In the context of the need to rapidly identify depressed mood among persons receiving ART in public health clinics, the BDI may be a useful instrument. We end the paper with certain cautions associated with routine screening.

Universities in South Africa face ongoing challenges with low rates of academic attainment and high rates of attrition. Our aims were to (1) investigate the extent to which common mental disorders evaluated early in the first year predict academic failure at the end of the year, controlling for sociodemographic factors and (2) establish the potential reduction in prevalence of failure that could be achieved by effectively treating associated mental disorders. Self-report data were collected from first-year students ( n = 1402) via an online survey at the end of the first semester. Participants were assessed for six common mental disorders. Academic performance data were subsequently obtained from institutional records at the end of the year. Bivariate and multivariate logistic regression models were used to identify the best sociodemographic and mental health predictors of academic failure. Population attributable risk analysis was used to assess the potential impact of treating associated mental disorders. In multivariate logistic regression models controlling for significant sociodemographic factors, the odds of failure were elevated among students with major depressive disorder (aOR = 3.69) and attention deficit hyperactivity disorder (aOR = 2.05). Population attributable risk analysis suggests that providing effective treatment to students with major depressive disorder and/or attention deficit hyperactivity disorder could yield a 6.5% absolute reduction in prevalence of academic failure (equivalent to a 23.0% proportional reduction in prevalence of academic failure). Providing effective and accessible campus-based mental healthcare services is integral to supporting students’ academic attainment and promoting transformation at South African universities.