Distress, desperation and despair: anxiety, depression and suicidality among rural South African youth
Bibliographic record
Abstract
Common mental disorders (CMDs) affect millions of people worldwide and impose a high cost to individuals and society. Youth are disproportionately affected, as has also been confirmed in South Africa. Mental disorders and substance use disorders often occur as concurrent disorders. Although youth in rural South Africa grow up in d Steel, Z., Marnane, C., Iranpour, C., Chey, T., Jackson, J. W., Patel, V., & Silove, D. (2014). The global prevalence of common mental disorders: A systematic review and meta-analysis 1980-2013. International Journal of Epidemiology, 43(2), 476–493. https://doi.org/https://dx.doi.org/10.1093/ije/dyu038[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]ifficult social and economic conditions, the study of mental disorders in South Africa has focussed primarily on urban populations. One such rural area in South Africa is the Harry Gwala District, where rates of interpersonal violence and self-inflicted injuries among 15–24-year-old men, are extraordinarily high. Suicide is an important proxy measure of severe emotional distress, predominantly depression and hopelessness. This study reports on rates of fatal self-harm among 15–24-year-old men in the Harry Gwala District. We determined the rates and severity of CMDs and their correlates among 355 young males ranging in age from 14 to 24 years in the Harry Gwala District community. High rates of depression, anxiety, hopelessness and worthlessness were reported. One in four of the young men and boys reported current suicidal thoughts associated with depression, anxiety, feelings of worthlessness and binge drinking. Reports of alcohol use were high, as were those of daily cannabis use. Our findings show high rates of CMDs and alcohol use, and highlight the impact of collective dysphoria on the mental well-being of rural youth in South Africa, who are likely coping through drug and alcohol use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".