Integrating Indigenous healing practices within collaborative care models in primary healthcare in Canada: a rapid scoping review
Bibliographic record
Abstract
OBJECTIVES: , described widespread Indigenous-specific stereotyping, racism and discrimination limiting access to medical treatment and negatively impacting the health and wellness of Indigenous Peoples in British Columbia, Canada. To address the health inequalities experienced by Indigenous peoples, Indigenous healing practices must be integrated within the delivery of care. This rapid scoping review aimed to identify and synthesise strategies used to integrate Indigenous healing practices within collaborative care models available in community-based primary healthcare, delivered by regulated health professionals in Canada. ELIGIBILITY CRITERIA: We included quantitative, qualitative and mixed-methods studies conducted in community-based primary healthcare practices that used strategies to integrate Indigenous healing practices within collaborative care models. SOURCES OF EVIDENCE: We searched MEDLINE, Embase, Indigenous Studies Portal, Informit Indigenous Collection and Native Health Database for studies published from 2015 to 2021. CHARTING METHODS: Our data extraction used three frameworks to categorise the findings. These frameworks defined elements of integrated healthcare (ie, functional, organisational, normative and professional), culturally appropriate primary healthcare and the extent of community engagement. We narratively summarised the included study characteristics. RESULTS: We identified 2573 citations and included 31 in our review. Thirty-nine per cent of reported strategies used functional integration (n=12), 26% organisational (n=8), 19% normative (n=6) and 16% professional (n=5). Eighteen studies (58%) integrated all characteristics of culturally appropriate Indigenous healing practices into primary healthcare. Twenty-four studies (77%) involved Indigenous leadership or collaboration at each phase of the study and, seven (23%) included consultation only or the level of engagement was unclear. CONCLUSIONS: We found that collaborative and Indigenous-led strategies were more likely to facilitate and implement the integration of Indigenous healing practices. Commonalities across strategies included community engagement, elder support or Indigenous ceremony or traditions. However, we did not evaluate the effectiveness of these strategies.
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 | 0.028 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.022 | 0.036 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".