Key Features of Culturally Inclusive, -Affirming and Contextually Relevant Mental Health Care and Healing Practices with Black Canadians: A Scoping Review
Bibliographic record
Abstract
Black Canadians are one of the fastest-growing groups in Canada, with 59% of this population comprising immigrants. Ongoing systemic racism and discrimination have serious consequences for the mental health of Black Canadians. While research and policy efforts to address the mental health needs of this population are ongoing, a greater understanding of the healing practices relevant to this diverse population is needed. This scoping review synthesized and discussed key features of culturally inclusive, affirming, and contextually relevant approaches and practices for mental health care and healing with Black Canadians, as well as identified limitations and gaps in the current research. This study followed the PRISMA guidelines for scoping reviews and conducted a search in PsycINFO, MEDLINE, Embase, SocINDEX, CINAHL, Sociological Abstracts, and Global Health in October 2023. A total of 34 articles met the inclusion criteria. The review identified that most studies were conducted in one Canadian province (i.e., Ontario) and involved diverse perspectives, including service users and providers. The thematic review of articles revealed limited research regarding specific interventions, but identified many commonly reported features of culturally and contextually relevant approaches to mental health care and healing for Black Canadians that broaden the scope of mental health care beyond Euro-Western clinical models, including taking a holistic and empowerment-based approach, engaging in culturally affirming care, a social justice approach, community-centred and collaborative healing, and the necessity of practitioner education. Recommendations for practice, policy, education, and research are provided to support more inclusive and responsive mental health care systems for Black Canadians.
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 | 0.025 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.031 | 0.036 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".