Barriers and facilitators to the implementation of vitamin A supplementation programs in Africa: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Vitamin A deficiency (VAD) impacts over 50% of children aged 6–59 months in sub-Saharan Africa, causing severe health issues. Despite the importance of vitamin A supplementation (VAS) programs, barriers limit their effectiveness, making it essential to understand these factors for better outcomes. Aim: This systematic review aimed to identify the barriers and facilitators to VAS programs in Africa, using the Consolidated Framework for Implementation Research (CFIR) to conceptualize the findings. Methods: A comprehensive search was conducted across OVID Embase, OVID Medline, Web of Science Core Collection, Scopus, CINAHL and CAB Direct. Studies were excluded if they did not report VAS administration via capsules or droplets in large-scale programs or omitted discussions on implementation barriers and facilitators. Results: The search yielded 4377 citations, with 10 studies meeting eligibility criteria, published from 2002 to 2021 across 12 countries. The most frequently represented were Ethiopia and Zimbabwe. A total of nine barriers and seven facilitators to VAS programs were identified. The most frequently cited barriers were capsule stock-outs, limited resources and lack of incentive for staff, while the most frequently cited facilitators were Child Health Days and involvement of community-based health workers. The key CFIR constructs associated with these findings were Tailoring Strategies, Incentive Systems and Available Resources. Conclusion: The barriers and facilitators identified in this review offer valuable insights for improving VAS coverage and implementation in Africa. Tailoring implementation strategies based on these findings can enhance the effectiveness and coverage of VAS programs.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it