A Scoping Review of the Use of Theory in Studies of Knowledge Translation
Bibliographic record
Abstract
BACKGROUND: Advancing the science of knowledge translation (KT) in occupational therapy is critical. Explicit application of theory can advance this science; yet, how theory is applied and the degree to which it can guide research remain poorly defined. PURPOSE: To understand how theory is applied within KT research. METHODS: A scoping review was conducted to examine and summarize the extent, range, and nature of the application of three specific KT theories: Diffusion of Innovations, Promoting Action on Research Implementation in Health Services framework, and Theory of Planned Behaviour. FINDINGS: Theory use was seen most frequently in medicine and nursing. Only 3 of 90 articles were in rehabilitation. Five approaches to theory application were found, the most common being the use of to predict success of KT (57/90). IMPLICATIONS: In-depth study of the importance and methods of theory application in KT research is needed, in particular in occupational 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 | 0.071 | 0.199 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.039 | 0.040 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".