Mapping the Intersecting Contexts of Migration and Pediatric Pain over the Last Decade: A Rapid Scoping Review Protocol
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Migrant youth often experience multiple, intersecting systems of oppression (e.g., racism, poverty, and discrimination) that may contribute to disparities in pediatric pain prevalence, severity, and management. However, pain in migrant youth remains poorly understood. This rapid scoping review will examine the nature and extent of the existing literature on pain among migrant youth. METHODS: This protocol has been preregistered on the Open Science Framework. The review will follow guidelines for conducting and reporting rapid and scoping reviews, and will be guided by PCC (population, concept, context) and PROGRESS-Plus methodological frameworks. Electronic searches will be conducted in MEDLINE, CINAHL, and Scopus for primary research studies published since 2015 that describe and examine pain among migrant youth (age < 18 years). Two reviewers will independently screen titles, abstracts, and full texts, with disagreements resolved by consensus or a third reviewer. Data charting will be piloted on 5-10 studies, then independently conducted by two reviewers. Extracted data will include study characteristics (authors, year, purpose, methodology); participant sociodemographic information (e.g., racial and/or ethnic identity, age, sex, gender identity, sexual orientation, socioeconomic position); migration status; countries of origin and destination; definition and characteristics of pain; and measures of systemic factors (e.g., racism). RESULTS: Findings will be synthesized descriptively and interpreted within sociocultural and geopolitical contexts to better understand pain among migrant youth. CONCLUSIONS: This review will aim to provide critical insights into the intersections between migration and pediatric pain, offering guidance for future research, clinical practice, and policy to improve pain management and outcomes for migrant youth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.163 | 0.146 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.025 | 0.017 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.056 | 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".