Knowledge translation interventions to sustain direct care provider behaviour change in long‐term care: A process evaluation
Bibliographic record
Abstract
RATIONALE, AIMS, AND OBJECTIVES: Process evaluation can be used to understand the factors influencing the impact of knowledge translation (KT) interventions. The aim of this mixed methods process evaluation was to evaluate the processes and perceived outcomes of eight KT interventions that were used with healthcare aides (HCAs) to introduce a mobility innovation into their daily care practices. The study examined the perceived effectiveness of various KT interventions in sustaining daily performance of the sit-to-stand mobility innovation by HCAs with residents in long-term care. METHOD: In-person interviews were conducted with four leaders across three long-term care facilities. Seven focus groups with 27 HCAs were conducted across the three facilities. All participants were asked to rank the eight interventions involved in the trial according to their perceived effectiveness and, for the leaders, their perceived ease of implementation. Focus group and interview questions asked participants to discuss the relative merits of each KT intervention. Two research assistants coded all of the transcripts independently using content analysis. RESULTS: Both HCAs and their leaders perceived reminders, followed by discussion groups, to be the most effective KT interventions to sustain practice change. Healthcare aide champions were deemed least effective by both leaders and HCAs. Leaders identified both the focus group discussion and audit and feedback posters in the study as the most difficult to implement. Participants valued interventions that were strategically visible, helped to clarify misconceptions about the new care innovation, supported teamwork, and made visible the resident benefits of the care innovation. Logistical issues, such as staff scheduling and workload, influenced the perceived feasibility of the various KT interventions. CONCLUSIONS: Understanding how care staff in long-term care settings perceive KT interventions can inform the choice of future use of these interventions to move research evidence into practice.
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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 | 0.099 | 0.109 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".