Barriers to the participation of people with psychosocial disability in mental health policy development in South Africa: a qualitative study of perspectives of policy makers, professionals, religious leaders and academics
Bibliographic record
Abstract
BACKGROUND: This paper outlines stakeholder views on environmental barriers that prevent people who live with psychosocial disability from participating in mental health policy development in South Africa. METHOD: Fifty-six semi-structured interviews with national, provincial and local South African mental health stakeholders were conducted between August 2006 and August 2009. Respondents included public sector policy makers, professional regulatory council representatives, and representatives from non-profit organisations (NPOs), disabled people's organisations (DPOs), mental health interest groups, religious organisations, professional associations, universities and research institutions. RESULTS: Respondents identified three main environmental barriers to participation in policy development: (a) stigmatization and low priority of mental health, (b) poverty, and (c) ineffective recovery and community supports. CONCLUSION: A number of attitudes, practices and structures undermine the equal participation of South Africans with psychosocial disability in society. A human rights paradigm and multi-system approach is required to enable full social engagement by people with psychosocial disability, including their involvement in policy development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".