Engaging Community Partners to Understand and Respond to Substance Use and Addiction Crisis Facing Families in Prince Albert, Saskatchewan
Bibliographic record
Abstract
Substance use is a persisting health care crisis that has led to residents' addiction to diverse substances in Prince Albert, Saskatchewan. This public health issue affects not only those with a substance use disorder but also those within their circle of family and friends. This paper aims to outline the community engagement processes that we undertook to identify community priorities for addressing the substance use and addiction issues facing them. We began the community engagement using a patient-oriented research process, which led to the development of a grant application. Following the awarding of this grant application by the Saskatchewan Health Research Foundation and Saskatchewan Centre for Patient-Oriented Research, we conducted interviews with family members affected by addiction in the city. The study provided us with significant insight into the impacts of substance use disorders on family members. The importance of collaboration among people with lived experience, health care providers, and community partners helped us to identify our research questions. Community members also actively participated in the data collection, analysis, and presentation of the findings where priorities for the interventions were identified. The conversations we had because of the community's engagement and participation in the research process enhanced our understanding of the realities of caring for people with substance use disorders and the importance of family involvement throughout the process. We also learned lessons regarding community engagement and participation in research on a stigmatizing and complex topic.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".