Mental Health Stigma: What is being done to raise awareness and reduce stigma in South Africa?
Bibliographic record
Abstract
OBJECTIVE: Stigma plays a major role in the persistent suffering, disability and economic loss associated with mental illnesses. There is an urgent need to find effective strategies to increase awareness about mental illnesses and reduce stigma and discrimination. This study surveys the existing anti-stigma programmes in South Africa. METHOD: The World Health Organization's Assessment Instrument for Mental Health Systems Version 2.2 and semi-structured interviews were used to collect data on mental health education programmes in South Africa. RESULTS: Numerous anti-stigma campaigns are in place in both government and non-government organizations across the country. All nine provinces have had public campaigns between 2000 and 2005, targeting various groups such as the general public, youth, different ethnic groups, health care professionals, teachers and politicians. Some schools are setting up education and prevention programmes and various forms of media and art are being utilized to educate and discourage stigma and discrimination. Mental health care users are increasingly getting involved through media and talks in a wide range of settings. Yet very few of such activities are systematically evaluated for the effectiveness and very few are being published in peer-review journals or in reports where experiences and lessons can be shared and potentially applied elsewhere. CONCLUSION: A pool of evidence for anti-stigma and awareness-raising strategies currently exists that could potentially make a scientific contribution and inform policy in South Africa as well as in other countries.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".