Is research working for you? validating a tool to examine the capacity of health organizations to use research
Bibliographic record
Abstract
BACKGROUND: 'Is research working for you? A self-assessment tool and discussion guide for health services management and policy organizations', developed by the Canadian Health Services Research Foundation, is a tool that can help organizations understand their capacity to acquire, assess, adapt, and apply research. Objectives were to: determine whether the tool demonstrated response variability; describe how the tool differentiated between organizations that were known to be lower-end or higher-end research users; and describe the potential usability of the tool. METHODS: Thirty-two focus groups were conducted among four sectors of Canadian health organizations. In the first hour of the focus group, participants individually completed the tool and then derived a group consensus ranking on items. In the second hour, the facilitator asked about overall impressions of the tool, to identify insights that emerged during the review of items on the tool and to elicit comments on research utilization. Discussion data were analyzed qualitatively, and individual and consensus item scores were analyzed using descriptive and non-parametric statistics. RESULTS: The tool demonstrated good usability and strong response variability. Differences between higher-end and lower-end research use organizations on scores suggested that this tool has adequate discriminant validity. The group discussion based on the tool was the more useful aspect of the exercise, rather than the actual score assigned. CONCLUSION: The tool can serve as a catalyst for an important discussion about research use at the organizational level; such a discussion, in and of itself, demonstrates potential as an intervention to encourage processes and supports for research translation.
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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 | 0.286 | 0.417 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".