Promoting the Use of Measurement Tools in Practice: A Mixed-Methods Study of the Activities and Experiences of Physical Therapist Knowledge Brokers
Bibliographic record
Abstract
BACKGROUND: The use of knowledge brokers (KBs) has been recommended as a mechanism to facilitate the use of research evidence in clinical practice. However, little has been written regarding the practical implementation of the KB role. OBJECTIVES: This article (1) describes the brokering activities of 24 pediatric physical therapist KBs (in Ontario, Alberta, and British Columbia, Canada), and (2) reports KBs' perceptions of the utility of their role and their experiences with the brokering process. DESIGN: A mixed-methods research design was used in this investigation, which was part of a larger knowledge translation (KT) study that demonstrated the effectiveness of using KBs to implement a group of evidence-based measurement tools into practice. METHODS: The KBs completed weekly activity logs, which were summarized and described. Semi-structured telephone interviews with KBs were analyzed qualitatively to provide insight into their perceptions of their role and the brokering process. Major interview themes were identified and verified through member checking. RESULTS: Brokering activities varied considerably as KBs adapted to meet the needs of their colleagues. The KBs indicated that they highly valued the connection to the research community and spoke of the enthusiastic engagement of their physical therapist colleagues (and others in their organization) in the brokering process. They discussed the importance of understanding the practice context and organizational factors that could affect knowledge transfer. The KBs spoke of the need to dedicate time for the role and had a strong sense of the supports needed to implement a KB role in future. CONCLUSIONS: Considerable variation in brokering activities was demonstrated across KB participants. The KBs perceived their role as useful and indicated that organizational commitment is crucial to the success of this KT strategy.
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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 | 0.081 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".