A KNOWLEDGE TRANSLATION INITIATIVE TO ENHANCE EVIDENCE-INFORMED CLINICAL MANAGEMENT OF ACHILLES TENDINOPATHY: THE PURPOSE, PROCESS AND OUTCOMES OF THE BC TENDINOPATHY TOOLKIT
Bibliographic record
Abstract
Introduction Translation of knowledge to practice in health care is a significant challenge.1–3 This presentation describes the purpose, process and preliminary outcomes of a knowledge translation (KT) initiative undertaken by a unique partnership of physical therapy researchers, educators and expert clinicians to address the gap between evidence and practice in the management of Achilles tendinopathy. Methods Physiotherapy clinicians in British Columbia requested evidence-informed guidance on the management of tendinopathy. To address this need, the provincial Physical Therapy Knowledge Broker assembled a team of researchers, educators and expert clinicians with the mandate to develop, disseminate and implement a toolkit of decision aids to guide clinical decision-making for Achilles Tendinopathy. The process to develop the toolkit involved the following components: (1) identification of the purpose and scope of the project (2) agreement on the processes for selection of content and format (3) creation of a mechanism for resolution of conflicting opinion (4) an iterative feedback process with stakeholders and (4) the incorporation of concepts and strategies from the knowledge translation and implementation science literature to support the stages of knowledge synthesis, dissemination and implementation.1–4 Results The ‘Tendinopathy Toolkit’ included: (1) a tabulated summary of the evidence for manual therapy, exercise, low level laser therapy, ultrasound, extracorporeal shock wave therapy, iontophoresis using dexamethasone, taping, orthotics, night splints and braces, heel raise inserts, needling techniques, and the appropriate outcome measures for this population (targeted ‘take home messages’ and clinical implications for each were also included); (2) an algorithm to guide the sequence of interventions; (3) and appendices including (a) exercise programmes (b) low level laser dosage calculation (c) tabulated details for each article reviewed and (d) a review of common medical interventions. The second phase of the initiative—utilization of strategies to enhance implementation and uptake of the toolkit—is currently being undertaken. Discussion Clinicians want to provide evidence-informed management of tendinopathy but many struggle with accessing, appraising and synthesising the vast array of literature available on this topic. This KT initiative highlights the need for, challenges associated with, evidence-informed process for and positive response to the development of decision aids synthesising the current evidence to guide clinical management of this patient population.
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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 | 0.158 | 0.212 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".