Bridging the Gap: Canadian Healthcare Providers’ Perspectives of Harm Reduction and Substance Use Education in Hospital
Bibliographic record
Abstract
Background: The complexity of health concerns associated with unregulated substance use has led to increased hospital utilization by people who use unregulated substances. Health care providers have described inadequate knowledge to adequately support this patient population during hospitalization. Aims: The aim of this research was to explore health care providers’ perspectives on harm reduction and substance use education in hospital settings. Methods: A qualitative secondary analysis was conducted using an interpretive lens. The research was conducted across three hospitals in one city in Southwestern Ontario. To guide the research, 31 health care providers, the majority being nurses, participated in either focus groups or individual interviews based on preference. All focus group or interview data were analyzed using an ethnographic method of analysis focusing on the hospital environment and education. Results: Health care providers described two interconnected states regarding harm reduction and substance use education: the current state and the desired state. Key themes which emerged in the current state and desired state include: (a) insufficient education , (b) lack of resources , (c) inconsistent policy , (d) culture of stigma and suboptimal care , (e) enhanced education , (f) resources , (g) policy change , and (h) culture shift and optimal care . Conclusion: Findings of this study demonstrate the need for supportive policies, adequate resources, and enhanced harm reduction and substance use in hospital settings. Addressing these gaps is essential to transforming hospital culture and improving care for people who use unregulated substances. These insights can inform future policy, practice, education, and guide new research initiatives.
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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 | 0.021 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.053 | 0.017 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".