Facilitating Implementation of Research Evidence (FIRE): an international cluster randomised controlled trial to evaluate two models of facilitation informed by the Promoting Action on Research Implementation in Health Services (PARIHS) framework
Bibliographic record
Abstract
BACKGROUND: Health care practice needs to be underpinned by high quality research evidence, so that the best possible care can be delivered. However, evidence from research is not always utilised in practice. This study used the Promoting Action on Research Implementation in Health Services (PARIHS) framework as its theoretical underpinning to test whether two different approaches to facilitating implementation could affect the use of research evidence in practice. METHODS: A pragmatic clustered randomised controlled trial with embedded process and economic evaluation was used. The study took place in four European countries across 24 long-term nursing care sites, for people aged 60 years or more with documented urinary incontinence. In each country, sites were randomly allocated to standard dissemination, or one of two different types of facilitation. The primary outcome was the documented percentage compliance with the continence recommendations, assessed at baseline, then at 6, 12, 18, and 24 months after the intervention. Data were analysed using STATA15, multi-level mixed-effects linear regression models were fitted to scores for compliance with the continence recommendations, adjusting for clustering. RESULTS: Quantitative data were obtained from reviews of 2313 records. There were no significant differences in the primary outcome (documented compliance with continence recommendations) between study arms and all study arms improved over time. CONCLUSIONS: This was the first cross European randomised controlled trial with embedded process evaluation that sought to test different methods of facilitation. There were no statistically significant differences in compliance with continence recommendations between the groups. It was not possible to identify whether different types and "doses" of facilitation were influential within very diverse contextual conditions. The process evaluation (Rycroft-Malone et al., Implementation Science. doi: 10.1186/s13012-018-0811-0) revealed the models of facilitation used were limited in their ability to overcome the influence of contextual factors. TRIAL REGISTRATION: Current Controlled Trials ISRCTN11598502 . Date 4/2/10. The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 223646.
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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 | 0.076 | 0.109 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".