Protocol of a scoping review on knowledge translation competencies
Bibliographic record
Abstract
BACKGROUND: Knowledge translation (KT) activities can reduce the gap between "what is known" and "what is done". Several factors hinder or facilitate KT activities including individual characteristics and organizational attributes; we will focus on individual healthcare professional modifiable characteristics. The purpose of this scoping review is to summarize knowledge on KT competencies for knowledge users, knowledge brokers, and knowledge producers/researchers to support evidence-based practice (EBP) and inform policy and research in health. Our objectives are to explore the relevant theoretical and empirical literature; map the publications for key themes and research gaps of KT competencies, and interventions for enhancing KT competencies; summarize and disseminate findings; produce an action plan and research agenda; and develop self-assessment tools (the KT Pathways) for professional development for our three target audiences. METHODS: The scoping review method will guide our study by following six stages: formulating the research question; identifying relevant studies; selecting the literature; charting the data; collating, summarizing, and reporting the results; and developing a KT plan and consulting stakeholders involved in the fields of KT, EBP, evidence-informed policy-making, and/or research. We will include empirical and theoretical/conceptual peer-reviewed and grey literature in health that examine knowledge user, knowledge broker and knowledge producer KT competencies. Publications written in the English language and published after 2003 only will be considered. Our multidisciplinary research team will collaborate using technology (i.e., WebEx for discussions and a Web 2.0 website for storing documents). Our KT plan consists of an Advisory Group and dissemination plan of the findings. DISCUSSION: We expect the identified KT competencies to contribute to the KT science by providing positive outcomes in practice, policy, education, and future research. Incorporation of the core KT competencies may enhance safety, effectiveness of clinical care, and quality of health outcomes; contribute to and facilitate collaboration among practitioners, knowledge users, knowledge brokers, researchers, employers, and educators; improve education of healthcare professionals and inform policy-making process; benefit practitioners by guiding their KT professional development to become effective at moving evidence into practice and policy; guide suitable interventions and strategies to enhance KT activities in the health sector; and direct future research.
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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 | 0.195 | 0.235 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.023 | 0.016 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.122 | 0.029 |
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; the direct Gemma label and the distilled Codex classifier 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".