Knowledge Brokering in Children's Rehabilitation Organizations: Perspectives from Administrators
Bibliographic record
Abstract
INTRODUCTION: Administrators must balance the demands of delivering therapy services with the need to provide staff with educational opportunities promoting evidence-based practice. Increasingly, the use of multifaceted, interactive knowledge translation strategies, such as knowledge brokering, is suggested as an effective way to encourage clinician behavior changes and implement new knowledge. The purpose of this qualitative study is to describe administrators' perceptions of the successes and challenges in using a knowledge broker (KB) to promote the use of evidence-based measures of motor function for children with cerebral palsy. METHODS: Administrators from 27 pediatric facilities completed a semi-structured telephone interview following 6 months of knowledge brokering within their organizations. Using thematic analysis, interview transcripts were reviewed to identify common themes. RESULTS: Six interview themes were identified: "Efficient and Effective," "Stimulating Peer-to-Peer Learning Environment," "Committed and Respected Knowledge Brokers," "Sharing Beyond," "Organizational Beliefs and Values," and "The Dilemma of Moving Forward". Administrators were positive about the KB experience, acknowledging its efficiency and effectiveness. They commented on the stimulating peer-to-peer and interdisciplinary learning environment that the KB process encouraged. Administrators referred to their organizational beliefs and values when discussing their need to make priorities for limited resources, which influenced their decisions about whether to continue with a KB after the study was completed. DISCUSSION: Although administrators were philosophically supportive of knowledge brokering, they identified funding and resource constraints and the absence of evidence of the effectiveness of knowledge brokering as major barriers to the continuation of a KB role in their facility.
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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 | 0.028 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.014 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.007 |
| 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".