Vitalizing Practice Through Research and Research Through Practice: The Outcomes of a Conference to Enhance the Delivery of Care
Bibliographic record
Abstract
The American Physical Therapy Association (APTA) provided funding for a series of meetings among a small group of leaders representing the research and clinical communities whose task was to plan a conference, the outcome of which would be a “road map” for the process of generating evidence that would be implemented by clinicians so that the provision of services might be enhanced. Two of these planning sessions were held and resulted in a decision to focus a conference on the identification of strategies to lessen perceived “gaps” between physical therapist clinicians and researchers and the development of strategies to bridge the “gaps” between the 2 groups. These meetings ultimately resulted in the Vitalizing Practice Through Research and Research Through Practice Conference hosted by APTA. A perceived gap between research and practice has been cited as a problem by others within and outside the profession as well. In a recent editorial in the Journal of Orthopaedic and Sports Physical Therapy , Bechtel et al stated, “We have a problem in manual therapy, and perhaps in the whole profession of physical therapy. Our problem is the growing chasm between researchers on the one hand, and clinicians on the other.”1(p451) A recent Institute of Medicine workshop titled “Transforming Clinical Research in the United States: Challenges and Opportunities” echoed this theme and identified bridging the divide between research and practice as one of the most critical needs facing clinical research.2 Discussion of the perceived gap between research and practice extends internationally, as Demers and Poissant3 lamented that research would be meaningless if it did not affect clinical practice. Furthermore, Demers and Poissant discussed the value of creating partnerships across the research process, from conception to dissemination of results. Translational research , at its most macroscopic level, essentially refers to efficient movement …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".