Evaluating the Uptake and Acceptability of Standardized Postoperative Rehabilitation Guidelines Using an Online Knowledge Translation Approach
Bibliographic record
Abstract
BACKGROUND: Providing physical therapists with evidence-based and consensus-derived guidelines to manage postoperative shoulder patients is essential; these guidelines should be readily available and provide clinically applicable information. Knowledge translation (KT) initiatives that encourage interaction between clinicians and researchers, that have multifaceted components and use a variety of strategies, can significantly change practice. OBJECTIVE: The objective of this study was to determine the uptake and acceptability of standardized postoperative shoulder guidelines with an accompanying online KT resource through evaluation of website analytics and a quantitative survey. DESIGN: A multi-pronged approach was used to assess uptake and acceptability of the guidelines and online KT resource. METHODS: Website analytics of usage and geographical location of users was measured as were physical therapist survey responses. RESULTS: Website analytics revealed that 5406 individuals used the online resource between October 2012 and September 2013 with the average visit lasting 8 minutes; only 47% of users were within the guideline developers' surgical referral region. Physical therapists who used the new shoulder guidelines were very satisfied or satisfied (96%) with the guidelines, reporting they promoted patient-specific clinical decision-making extremely or very well (68%). They viewed the online KT resource positively, with 79% rating it as "very useful" or "quite useful." Physical therapists from regions beyond those expected to use the new shoulder guidelines were also aware of the website and also rated it as very useful. LIMITATIONS: The survey sample was relatively small and did not directly assess patient outcomes. CONCLUSIONS: An online KT web resource developed in conjunction with standardized postoperative shoulder guidelines was perceived as useful based on website analytics and survey responses. Active KT strategies such as this can improve uptake and dissemination of best practice in physical therapy.
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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 | 0.066 | 0.147 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".