Process Evaluation of a Participatory, Multimodal Intervention to Improve Evidence‐Based Care in Long‐Term Care Settings
Bibliographic record
Abstract
BACKGROUND: Evidence-based improvements in long-term care (LTC) are challenging due to human resource constraints. AIMS: To evaluate implementation of a multimodal, participatory intervention aimed at improving evidence-based care. METHODS: Using a qualitative descriptive design, we conducted and inductively analyzed individual interviews with staff at midpoint and end-point to identify action plan implementation processes and challenges. The 9-month intervention engaged professional and unregulated staff in an on-site workshop and provided support for their development and implementation of site-specific action plans. RESULTS: Ten of 12 enrolled sites participated for the full study period. Interviews were conducted with 44 and 69 participants at midpoint and end-point, respectively. Seven of 10 sites focused their action plan on team functioning and communication. Main achievements described at end-point were improved team communication, better staff engagement, and improved teamwork. Internal and external supports for action plan implementation were described as critical for success. DISCUSSION: Three factors influenced change: vertically and horizontally linked teams, external facilitator support for action plan implementation, and coaching by Best Practice Coordinators that emphasized organizational change and normalization of evidence-based practice. IMPLICATIONS: Team functioning and communication are forerunners of clinical practice changes in LTC. An off-site model of facilitation is promising and may provide a more efficient means to reach a wider array of LTC settings. LINKING EVIDENCE TO ACTION: Practice changes need engagement of all staff.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".