Perceptions of provider awareness of traditional and cultural treatments among Indigenous people who use unregulated drugs in Vancouver, Canada
Bibliographic record
Abstract
INTRODUCTION: Indigenous people who use unregulated drugs (IPWUD) face significant barriers to care, including sparse availability of culturally safe health services. Integrating Indigenous traditional and cultural treatments (TCT) into health service delivery is one way to enhance culturally safe care. In a Canadian setting that implemented cultural safety reforms, we sought to examine the prevalence and correlates of client perceptions of primary care provider awareness of TCT among IPWUD. METHODS: Data were derived from two prospective cohort studies of PWUD in Vancouver, Canada between December 2017 and March 2020. A generalized linear mixed model with logit-link function was used to identify longitudinal factors associated with perceived provider awareness of TCT. RESULTS: Among a sample of 507 IPWUD who provided 1200 survey responses, a majority (n = 285, 56%) reported their primary care provider was aware of TCT. In multiple regression analyses, involvement in treatment decisions always (Adjusted Odds Ratio [AOR] = 3.6; 95% confidence interval [CI]: 1.6-7.8), involvement in treatment decisions most or some of the time (AOR = 3.3; 95% CI: 1.4-7.7), comfort with provider or clinic (AOR = 2.7; 95% CI: 1.5-5.0), and receiving care from a social support worker (AOR = 1.5; 95% CI: 1.0-2.1) were positively associated with provider awareness of TCT. CONCLUSION: We found high levels of perceived provider awareness of TCT and other domains of culturally safe care within a cohort of urban IPWUD. However, targeted initiatives that advance culturally safe care are required to improve healthcare and health outcomes for IPWUD, who continue to bear a disproportionate burden of substance use harms.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".