Is the Alma Ata vision of comprehensive primary health care viable? Findings from an international project
Bibliographic record
Abstract
BACKGROUND: The 4-year (2007-2011) Revitalizing Health for All international research program (http://www.globalhealthequity.ca/projects/proj_revitalizing/index.shtml) supported 20 research teams located in 15 low- and middle-income countries to explore the strengths and weaknesses of comprehensive primary health care (CPHC) initiatives at their local or national levels. Teams were organized in a triad comprised of a senior researcher, a new researcher, and a 'research user' from government, health services, or other organizations with the authority or capacity to apply the research findings. Multiple regional and global team capacity-enhancement meetings were organized to refine methods and to discuss and assess cross-case findings. OBJECTIVE: Most research projects used mixed methods, incorporating analyses of qualitative data (interviews and focus groups), secondary data, and key policy and program documents. Some incorporated historical case study analyses, and a few undertook new surveys. The synthesis of findings in this report was derived through qualitative analysis of final project reports undertaken by three different reviewers. RESULTS: Evidence of comprehensiveness (defined in this research program as efforts to improve equity in access, community empowerment and participation, social and environmental health determinants, and intersectoral action) was found in many of the cases. CONCLUSIONS: Despite the important contextual differences amongst the different country studies, the similarity of many of their findings, often generated using mixed methods, attests to certain transferable health systems characteristics to create and sustain CPHC practices. These include:1. Well-trained and supported community health workers (CHWs) able to work effectively with marginalized communities2. Effective mechanisms for community participation, both informal (through participation in projects and programs, and meaningful consultation) and formal (though program management structures)3. Co-partnership models in program and policy development (in which financial and knowledge supports from governments or institutions are provided to communities, which retain decision-making powers in program design and implementation)4. Support for community advocacy and engagement in health and social systems decision makingThese characteristics, in turn, require a political context that supports state responsibilities for redistributive health and social protection measures.
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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 | 0.080 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".