The role of community participation in primary health care: practices of South African health committees
Bibliographic record
Abstract
BACKGROUND: Community participation is an essential component in a primary health care (PHC) and a human rights approach to health. In South Africa, community participation in PHC is organised through health committees linked to all clinics. AIMS: This paper analyses health committees' roles, their degree of influence in decision-making and factors impacting their participation. METHODS: Data were collected through a mixed-methods study consisting of a cross-sectional survey, focus groups, interviews and observations. The findings from the survey were analysed using simple descriptive statistics. The qualitative data were analysed using thematic content analysis. Data on health committees' roles were analysed according to a conceptual framework adapted from the Arnstein ladder of participation to measure the degree of participation. FINDINGS: The study found that 55 per cent of clinics in Cape Town were linked to a health committee. The existing health committees faced sustainability and functionality challenges and primarily practised a form of limited participation. Their decision-making influence was curtailed, and they mainly functioned as a voluntary workforce assisting clinics with health promotion talks and day-to-day operational tasks. Several factors impacted health committee participation, including lack of clarity on health committees' roles, health committee members' skills, attitudes of facility managers and ward councillors, limited resources and support and lack of recognition. CONCLUSIONS: To create meaningful participation, health committee roles should be defined in accordance with a PHC and human rights framework. Their primary role should be to function as health governance structures at facility level, but they should also have access to influence policy development. Consideration should be given to their potential involvement in addressing social determinants of health. Effective participation requires an enabling environment, including support, financial resources and training.
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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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".