Evaluating the Women Health Volunteers Program in Iran- a Quarter Century Experience (1992-2016).
Bibliographic record
Abstract
BACKGROUND: Running for more than 25 years, the Women Health Volunteers (WHV) program in Iran has made many great achievements. Considering the new expectations from the health system, this national program needs to be revised and undergo fundamental changes. Although many studies have been conducted to evaluate this program, there still is a lack of a comprehensive nationwide assessment containing policy recommendations. METHODS: This study was conducted in a qualitative approach. The data were obtained from 3 sources: national documentations, semi-structured questionnaires by 49 key informants, and focused group discussions. The program was assessed in 4 domains including the program, goals, achievements, improved opportunities (weaknesses), and strategies for improvements. RESULTS: The collected data were categorized into 4 main themes including goals and objectives, achievements, weaknesses, and recommendations. Main achievements of the WHV program are: increasing people's participation especially women, increasing health literacy, and increasing coverage and utilization of health services. The most important weaknesses of the program include: lack of a national roadmap and policy plan for the WHV program, lack of true belief in people's participation in policymakers, weakness in comprehensive system monitoring and evaluation, and inadequate funding. CONCLUSION: Like many other health system programs in the country, the WHV program suffers from the lack of a binding strategic plan and goal so that by changes in management, sustainability of the program becomes hampered. An appropriate solution would be to operate the WHV program like a non-government organization (NGO) under the supervision of the Ministry of Health and Medical Education (MoHME).
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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 | 0.021 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".