The Quebec Rural Emergency Department Project: A Cross-Sectional Study of a Potential Two-Pronged Strategy in the Knowledge Transfer Process
Bibliographic record
Abstract
INTRODUCTION: Health services research generates useful knowledge. Promotion of implementation of this knowledge in medical practice is essential. Prior to initiation of a major study on rural emergency departments (EDs), we deployed two knowledge transfer strategies designed to generate interest and engagement from potential knowledge users. The objective of this paper was to review: 1) a combined project launch and media press release strategy, and 2) a pre-study survey designed to survey potential knowledge users' opinions on the proposed study variables. MATERIALS AND METHODS: We evaluated the impact of the project launch (presentation at two conferences hosted by key stakeholders) and media press release via a survey of participants/stakeholders and by calculating the number of media interview requests and reports generated. We used a pre-study survey to collect potential key stakeholder' opinions on the study variables. RESULTS: Twenty-one of Quebec's 26 rural EDs participated in the pre-study survey (81% participation rate). The press release about the study generated 51 press articles and 20 media request for interviews, and contributed to public awareness of a major rural research initiative. In the pre-study survey, thirteen participants (46%) mentioned prior knowledge of the research project. Results from the pre-study survey revealed that all of the potential study variables were considered to be relevant for inclusion in the research project. Respondents also proposed additional variables of interest, including factors promoting retention of human resources. CONCLUSIONS: The present study demonstrated the potential utility of a two-pronged knowledge transfer strategy, including a combined formal launch and press release, and a pre-study survey designed to ensure that the included variables were of interest to participants and stakeholders.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".