Migration of Health Workers and Its Impacts on the Nigerian Health Care Sector: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Health worker migration from Nigeria poses significant challenges to the Nigerian health care sector and has far-reaching implications for health care systems globally. Understanding the factors driving migration, its effects on health care delivery, and potential policy interventions is critical for addressing this complex issue. OBJECTIVE: This study aims to comprehensively examine the factors encouraging the emigration of Nigerian health workers, map out the effects of health worker migration on the Nigerian health system, document the loss of investment in health training and education resulting from migration, identify relevant policy initiatives addressing migration, determine the effects of Nigerian health worker migration on destination countries, and identify the benefits and demerits to Nigeria of health worker migration. METHODS: This study will follow the Joanna Briggs Institute methodology. A search strategy will retrieve published studies from MEDLINE, CINAHL, Embase, Global Health, Academic Search Premiere, and Web of Science. Unpublished studies will be sourced from dissertations and theses. A comprehensive search will involve keyword scans and citation searches. Exclusion criteria will filter out irrelevant studies, such as studies unrelated to the international migration of health workers and non-English language studies. A total of 2 independent reviewers will screen the titles and abstracts and then review the full text. Data will be extracted from the included studies using a data extraction tool developed for this study. The study selection process will be shown using a PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) flowchart. While the traditional risk of bias assessments is not applied to scoping reviews, the quality of included studies will be evaluated based on methodological transparency. RESULTS: The process of selecting studies will be shown using a PRISMA ScR flowchart, and information gathering will be done through a charting table that has been prepared in advance. We plan to collect data from January 2025 to March 2025 and present the results to examine publication patterns and study details. The final summary is expected to be released by the summer of 2025. It will provide an in-depth look at how health worker migration impacts the health care sector in Nigeria. CONCLUSIONS: This study holds immense potential to contribute to understanding health worker migration from Nigeria and inform policy and practice interventions to address its challenges. By synthesizing existing evidence, the scoping review will guide future research and policy efforts to mitigate the adverse effects of migration on health care systems and workforce sustainability. Furthermore, the results will aid in recognizing deficiencies in the existing literature; this will offer a defined path for specific policy measures and methods to retain health care workers effectively and thus support the sustainability of health care systems. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/62726.
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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 | 0.078 | 0.068 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.016 |
| Bibliometrics | 0.017 | 0.013 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.083 | 0.014 |
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".