A systematic review of interventions to increase the use of standardized outcome measures by rehabilitation professionals
Bibliographic record
Abstract
OBJECTIVE: To determine the types and effectiveness of interventions to increase the knowledge about, attitudes towards, and use of standardized outcome measures in rehabilitation professionals. DATA SOURCES: An electronic search using Medline, EMBASE, PsycINFO, CINAHL, Ergonomics Abstracts, Sports Discus. The search is current to February 2016. STUDY SELECTION: All study designs testing interventions were included as were all provider and patient types. Two reviewers independently conducted a title and abstract review, followed by a full-text review. DATA EXTRACTION: Two reviewers independently extracted a priori variables and used consensus for disagreements. Quality assessment was conducted using the Assessment of Quantitative Studies published by the Effective Public Health Practice Group. DATA SYNTHESIS: We identified 11 studies involving at least 1200 providers. Nine of the studies showed improvements in outcome measure use rates but only three of these studies used an experimental or quasi-experimental design. Eight of the studies used an educational approach in the intervention and three used audit and feedback. Poor intervention description and quality of studies limited recommendations. CONCLUSIONS: Increased attention to testing interventions focused on known barriers, matched to behavior change techniques, and with stronger designs is warranted.
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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 | 0.038 | 0.422 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".