Health of Black children and youth in Canada: a scoping review
Bibliographic record
Abstract
BACKGROUND: Black children and youth in Canada experience significant health inequity due to systemic racism, socioeconomic inequities, and inadequate access to culturally responsive healthcare services, affecting their overall well-being. This scoping review mapped and synthesised empirical evidence on the health of Black children and youth in Canada to inform policy and practice. METHODS: The review followed Arksey and O'Malley's scoping review framework and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Seven databases (Ovid MEDLINE, EMBASE, APA PsycINFO, Web of Science, Scopus, Academic Search Complete, and SocINDEX) were searched for empirical studies published in peer-reviewed journals. Studies were included if they focused on Black children and youth (0-30 years) residing in Canada and their findings were synthesised thematically. RESULTS: A total of 56 health-related studies were included. The included studies were conducted across all the Canadian provinces and territories between 1993 and 2024, with 87.5% based in a single province and 48.2% published between 2021 and 2024. Quantitative studies accounted for 55.4% of the total. The health conditions identified included sickle cell disease, preterm birth, HIV, pediatric lupus, and mental health disorders such as depression, PTSD, and psychosomatic symptoms (reported in up to 81.7% of participants in one study). Racism was a prominent social determinant contributing to health conditions and barriers to healthcare access. Cultural practices and religiosity protected the Blacks from engaging in risky lifestyles while contributing to the distorted view of some illnesses. CONCLUSION: A high variety of health conditions were identified, with racism being a key determinant of health for Black children and youth in Canada. Culturally responsive, anti-racist health policies, community-led health education, and equitable access to services are critical to improving health outcomes.
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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 | 0.014 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.023 | 0.032 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".