Systematic review of determinants influencing knowledge implementation in occupational therapy
Bibliographic record
Abstract
INTRODUCTION: In knowledge translation, implementation strategies are more effective in fostering practice change. When using these strategies, however, many determinants, such as individual or organisational factors, influence implementation. Currently, there is a lack of synthesis concerning how these determinants influence knowledge implementation (KI). The aim of this systematic review was to document how determinants influence KI outcomes with occupational therapists. METHOD: Following the PRISMA statement, we systematically reviewed the literature on KI in occupational therapy across 12 databases: MEDLINE, Embase, CINAHL, AMED, PsychINFO, Cochrane Library, FirstSearch, Web of Science, ProQuest Dissertations & Theses, ERIC, Education Source and Sociological Abstracts. Eligible studies reported KI strategies specifically with occupational therapists. Selected studies were appraised for quality with the Mixed Methods Appraisal Tool. Using the Consolidated Framework for Implementation Research (CFIR), we categorised reported mentions of CFIR (sub-)constructs to identify the determinants studied most often, how they were documented and what influence they had on outcomes. RESULTS: Twenty-two studies were analysed for this review. CFIR (sub-)constructs were mentioned 81 times, and seven (sub-)constructs received at least 5% of these mentions (4/81). These were as follows: (i) Adaptability of the practice; (ii) Learning climate; (iii) Leadership engagement; (iv) Available resources; (v) Knowledge and Beliefs about the Intervention; (vi) Individual Stage of Change; and vii) Executing the KI strategy. The Inner setting domain was the most documented and the domain with the most (sub-)constructs with at least four mentions (3/7). Most studies used questionnaires as assessment tools, but these were mainly non-standardised scales. The data were too heterogenous to perform a meta-analysis. CONCLUSION: Seven (sub-)constructs mentioned most often would benefit from being assessed for salience by researchers intending to develop a KI strategy for occupational therapists. Future research aimed at improving our understanding of KI should also consider using standardised tools to measure the influence of determinants.
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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 | 0.052 | 0.179 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".