Determinants of community health workers effectiveness for delivery of maternal and child health in Sub Saharan Africa: A Systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Countries in sub-Sahara African continue to have the highest maternal and under- five child death occurrences in the world and this has become a key health challenge in the region and persists as global public health agenda. Although Community Health Workers (CHWs) are increasingly being acknowledged as crucial members of the healthcare workforce in reducing health disparity, evidence is limited on perspective of community health workers. The objective of this protocol is to outline the methodological process of a systematic review that will gather qualitative data to examine determinants of community health workers effectiveness for delivery of maternal and child health in Sub Saharan Africa. Synthesizing the perspectives of community health workers' perceived experience is crucial to inform decision makers, policy makers, and practitioners to address barriers to and scaleup facilitators of CHWs program to ensure maternal and child health equity and a resilience community health system. METHODS: The protocol has been registered in the PROSPERO (CRD42020206874). We will systematically conduct a literature search from inception in MEDLINE complete, EMBASE, CINAHL complete and Global Health for relevant studies. Eligible studies will be reports of original research, peer reviewed articles having a qualitative component (i.e., qualitative, mixed, or multi-method studies) on empowerment of CHWs associated with maternal and child health in the sub-Saharan Africa. Eligibility will be restricted to studies published in English. Two reviewers will independently screen all included abstracts and full-text articles. The primary outcome will be CHWs' perceived barriers to and facilitators of effectiveness of community health workers in maternal and child health in sub-Saharan Africa. Study methodological quality (or bias) will be appraised using appropriate tools. Narrative analysis will be conducted, and narrative summary of findings will be presented. We will use the 'best fit' framework method as a systematic approach to analyzing the qualitative data. DISCUSSION: This study will systematically and comprehensively search literature and integrate evidence on perceived barriers to and facilitators of effectiveness of community health workers led maternal and child health program in sub-Saharan Africa. Our findings will inform policy and practice on maternal and child health equity and a resilient communities health system. The resulting manuscript will be disseminated in a peer-reviewed journal and at international and national conferences.
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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 | 0.143 | 0.120 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.017 | 0.015 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.063 | 0.009 |
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".