Community-based participatory research to improve resident wellness in a supportive living facility in the Northwest Territories
Bibliographic record
Abstract
INTRODUCTION: The Spruce Bough is the first supportive living facility in Yellowknife, Northwest Territories, and hosts the first long-term residential managed alcohol program (MAP) in northern Canada. The program accepts individuals who have at least two co-morbid mental health, physical health, substance use, and/or mobility concerns. This study sought to hear from residents about their experiences in the program. METHOD: This study utilized a community-based participatory approach including the residents of the Spruce Bough in development, design, and data analysis, with the aim of generating results that would improve the lives of residents. Resident co-researchers used inductive coding to draw themes from statements gathered through focus groups and interviews and used these to develop recommendations to improve resident wellness for Spruce Bough leadership. RESULTS: Residents reported that life was good at Spruce Bough, they had what they needed, and that staff were supportive and helpful. Concerns included unmet needs for special meals for individuals with specific health-related dietary needs; the disruptive behaviour of individuals drinking outside the MAP; and disrespect felt by residents through actions or comments by staff. CONCLUSION: The Spruce Bough supportive living model is seen as successful by residents; however, they identified potential areas of improvement. Community-based participatory research allowed residents to provide recommendations to be shared with service providers and funders for continued quality improvement. The insights provided and the interest in participation shown by residents indicate that the program would benefit from creating an ongoing mechanism to include resident feedback in decision making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".