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A Scoping Review of Refugee Children’s Health Conditions, Outcomes and Measures Used in Refugee-Serving Public Health Centres/Clinics in Canada

2025· preprint· W4415842852 on OpenAlexfundaboutno aff
Augustine Aboagye Botwe, Nour Armoush, Cheryl Poth, Sophie Yohani, Rebecca Gokiert

Bibliographic record

VenuePreprints.org · 2025
Typepreprint
Language
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsRefugeePublic healthMental healthHealth equityHealth careInclusion (mineral)Health policyGeneral partnershipHealth promotionEquity (law)

Abstract

fetched live from OpenAlex

Refugee-serving primary health centres/clinics (PHCs) provide culturally safe, integrated care for refugee children, yet little is known about how their health conditions and outcomes are assessed. This scoping review examined the health conditions and outcomes of refugee children aged 0-5 years and how they are measured in refugee-serving PHCs in Canada. Conducted in partnership with the New Canadians Health Centre and guided by Joanna Briggs Institute methodological guidelines, we systematically searched Medline, CINAHL, Scopus, and Embase. Included studies focused on refugee children in Canada and reported health conditions, outcomes, and their measurements within PHCs. Twenty-five studies (2008–2024) met the inclusion criteria, most from Ontario (n=11), followed by Alberta and Saskatchewan (n=4 each). Reported health conditions or outcomes (n=24) spanned physical (n=19), developmental, and mental health domains (n=5). Communicable (e.g., gastrointestinal infections, hepatitis) and non-communicable conditions (e.g., malnutrition, vitamin D deficiency) were mostly reported. Although some standardized approaches were used, variability exists across provinces and conditions or outcomes measured. Findings reveal disproportionate focus on physical health and notable variability and gaps in child health measures, limited cultural adaptation, and lack of longitudinal data. Standardized, culturally responsive, and age-appropriate measurement approaches are needed to enhance health equity and inform evidence-based policy for refugee children in Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.471
Threshold uncertainty score0.947

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.078
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0320.052
Science and technology studies0.0030.002
Scholarly communication0.0070.003
Open science0.0040.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.165
GPT teacher head0.444
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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Same venuePreprints.org→Same topicMigration, Health and Trauma→French-language works237,207→