Understanding the trends, and drivers of emigration, migration intention and non-migration of health workers from low-income and middle-income countries: protocol for a systematic review
Bibliographic record
Abstract
INTRODUCTION: The WHO estimates a shortage of 18 million health workers (HWs) by 2030, primarily in low-income and middle-income countries (LMICs). The perennial out-migration of HWs from LMICs, often to higher-income countries, further exacerbates the shortage. We propose a systematic review to understand the determinants of HWs out-migration, intention to migrate and non-migration from LMICs. METHODS AND ANALYSIS: This protocol was designed in accordance with the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols guideline for the development and reporting of systematic review protocols. We will include English and French language primary studies (quantitative or qualitative) focused on any category of HWs; from any LMICs; assessed migration or intention to migrate; and reported any determinant of migration. A three-step search strategy that involves a search of one electronic database to refine the preliminary strategy, a full search of all included databases and reference list search of included full-text papers for additional articles will be employed. We will search Ovid MEDLINE, EMBASE, CINAHL, Global Health and Web of Science from inception to August 2022. The retrieved titles will be imported to EndNote and deduplicated. Two reviewers will independently screen all titles and abstract for eligibility using Rayyan. Risk of bias of the individual studies will be determined using the National Institute of Health study quality assessment tools for quantitative studies and the 10-item Critical Appraisal Skills Programme checklists for qualitative studies. The results will be presented in the form of narrative synthesis using a descriptive approach ETHICS AND DISSEMINATION: We will not seek ethical approval from an institutional review board, as this is a systematic review. At completion, we will submit the report of this review to a peer-reviewed journal for publication. Key findings will be presented at local and international conferences. PROSPERO REGISTRATION NUMBER: CRD42022334283.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".