Abstract P-057: THE TERRY HICKSON RESEARCH IN PRACTICE CHALLENGE: INTEGRATING RESEARCH AND PRACTICE
Bibliographic record
Abstract
Aims & Objectives: The Terry Hickson Research in Practice Challenge (THRPC) is an evidence informed educational program designed to promote local unit research culture and enhance the capacity of frontline providers to engage with, utilize and add to the evidence informing pediatric critical care practice. We describe THRPC program design, participant experiences and program outcomes. Methods Project ideas submitted by frontline critical care providers were selected for participation. Two research workshops were delivered at the start and completion of a 2 month mentored proposal development period. Completed proposals were presented by participants for peer review and 2 proposals were selected for the award. Results A total of 6 projects were accepted to the program. Participants (11) were nurses (7), respiratory therapists (2) and dietitians (2). 100% (11) of participants self-identified as having novice research skills and novice/ beginner skills in project development. Mentorship was reported as the most influential on participant learning. 83% (5) of accepted projects completed the THRPC and of those 100% (5) plan on continuing the mentor relationship until project completion. 90% (10) of participants agree/strongly agree that they have gained new knowledge of the research process, understand local resources and have developed new skills for research. All participants reported they intend to implement and publish their proposed projects. Conclusions The THRPC is an effective intervention to increase frontline provider knowledge, skill and engagement in 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 | 0.027 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.030 | 0.009 |
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".