Moving stroke rehabilitation evidence into practice: a systematic review of randomized controlled trials
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to investigate the effectiveness of interventions aimed at moving research evidence into stroke rehabilitation practice through changing the practice of clinicians. DATA SOURCES: EMBASE, CINAHL, Cochrane and MEDLINE databases were searched from 1980 to April 2019. International trial registries and reference lists of included studies completed our search. REVIEW METHODS: Randomized controlled trials that involved interventions aiming to change the practice of clinicians working in stroke rehabilitation were included. Bias was evaluated using RevMan to generate a risk of bias table. Evidence quality was evaluated using GRADE criteria. RESULTS: A total of 16 trials were included (250 sites, 14,689 patients), evaluating a range of interventions including facilitation, audit and feedback, education and reminders. Of which, 11 studies included multicomponent interventions (using a combination of interventions). Four used educational interventions alone, and one used electronic reminders. Risk of bias was generally low. Overall, the GRADE criteria indicated that this body of literature was of low quality. This review found higher efficacy of trials which targeted fewer outcomes. Subgroup analysis indicated moderate-level GRADE evidence (103 sites, 10,877 patients) that trials which included both site facilitation and tailoring for local factors were effective in changing clinical practice. The effect size of these varied (odds ratio: 1.63-4.9). Education interventions alone were not effective. CONCLUSION: A large range of interventions are used to facilitate clinical practice change. Education is commonly used, but in isolation is not effective. Multicomponent interventions including facilitation and tailoring to local settings can change clinical practice and are more effective when targeting fewer changes.
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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 | 0.180 | 0.961 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.066 | 0.030 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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; both teacher heads agree on what is shown here.
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".