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Record W4416794032 · doi:10.2196/preprints.88586

Mental Health Promotion among Black, Caribbean and African immigrants in Canada: a scoping review protocol (Preprint)

2025· article· W4416794032 on OpenAlexaboutno aff
Noah Boakye-Yiadom, Rita Yembilah, Bukola Salami

Bibliographic record

Venuenot available
Typearticle
Language
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
Fundersnot available
KeywordsCINAHLMental healthThematic analysisGrey literatureImmigrationHealth promotionPromotion (chess)Mental illnessPublic health

Abstract

fetched live from OpenAlex

Abstract Background Black, Caribbean, and African immigrant communities in Canada face compounding systemic inequities that undermine mental well-being and limit access to culturally grounded mental health promotion (MHP) strategies. Despite growing national policy attention to these disparities, the landscape of MHP programs and initiatives developed for, with, or by Black, Caribbean, and African populations remains fragmented and poorly synthesized. Objective This scoping review aims to (1) map existing MHP strategies, programs, and activities targeting Black, Caribbean, and African immigrant communities in Canada; (2) identify barriers and facilitators influencing their implementation and uptake; and (3) illuminate gaps in current research, policy, and practice. Methods Guided by Arksey and O’Malley’s scoping review framework and the Joanna Briggs Institute Manual for Evidence Synthesis, the review draws on 6 databases: MEDLINE (OVID), APA PsycINFO (OVID), Embase (OVID), PubMed, CINAHL Plus (EBSCOhost), and Google Scholar. Gray literature sources include community reports and government-funded initiatives such as those supported by the Public Health Agency of Canada’s Promoting Health Equity: Mental Health of Black Canadians Fund. Eligibility criteria focus on English-language sources addressing MHP or mental illness prevention within the Canadian Black, Caribbean, and African immigrant context. Data will be charted independently in duplicate using Covidence and analyzed through descriptive methods, including tabular summaries and narrative synthesis. Results Preliminary searches were conducted in June 2025. Formal database searches were completed in October 2025, yielding 2349 records across 6 databases. Following automated and manual deduplication (n=1048), 1301 records proceeded to title and abstract screening. Of these, 193 studies were sought for retrieval and full-text assessment. Data extraction is underway, with full results expected for publication in late 2026. Conclusions This review will produce the first consolidated map of MHP strategies targeting Black, Caribbean, and African immigrant communities in Canada. Findings are expected to reveal heterogeneity in intervention design, with a concentration of reactive, treatment-adjacent programs and limited representation of upstream, community-led, and culturally rooted approaches. Results will inform equity-driven policy development, support culturally responsive service design, and provide a foundation for future participatory research that centers Black, Caribbean, and African communities as knowledge producers.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: yes
Systematic reviewlow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: yes
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.066
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.762
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.064
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0180.020
Science and technology studies0.0080.004
Scholarly communication0.0100.004
Open science0.0050.005
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0320.005

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 head0.030
GPT teacher head0.396
Teacher spread0.366 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review · Other design
Domainnot available
GenreProtocol

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 routes1
Has abstractyes

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