Implementation of a Mental Health Guideline in a Long-Term Care Home: A Participatory Action Approach
Bibliographic record
Abstract
AbstractBackground: The goal of this pilot study was to implement a Canadian mental health guideline in a long-term care residence in order to improve interprofessional care of clients with mood and behavioural issues.Methods: Using a participatory action approach, this pilot study engaged staff/physicians, residents, and families in identifying key priorities for action related to the goal of improving interprofessional care. This resulted in the implementation of educational interventions, a mandate for non-registered nursing staff to attend interprofessional rounds, and enhanced interprofessional collaboration through unit-based huddles. A staff satisfaction survey and focus groups were conducted to assess perceptions of change.Findings: The staff satisfaction survey revealed statistically significant improvements in perceived job satisfaction, leadership, and workplace resources. Focus group findings indicated improved interprofessional collaboration, teamwork, support, and communication. Staff noted a stronger perception of being valued and increased confidence in their own contributions.Conclusions: Both qualitative and quantitative improvements were noted in staffjob satisfaction. Despite some limitations, these findings suggest that further dissemination of this initiative with rigorous evaluation is warranted.
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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 | 0.049 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".