Consumer‐driven health care: Building partnerships in research
Bibliographic record
Abstract
Over the past four decades, there has been a widespread movement to increase the involvement of patients and the public in health care. Strategies to effectively foster consumer participation are occurring within all research activities from research priority setting to utilization. One of the ten principles of the Cochrane Collaboration is to 'enable wide participation', and this includes consumers. The Cochrane Musculoskeletal Group (CMSG) is a review group of 50 within the Collaboration that has been working to increase consumer participation since its inception in 1993. Based in Canada, the CMSG has embraced the concept of knowledge translation as advocated by the Canadian Institutes of Health Research. The emphasis in knowledge translation is on interactions or partnerships between researchers and users to facilitate the use of relevant research in decision making. While the CMSG recognizes the importance of reaching all users, much of its work has focused on developing relationships with people with musculoskeletal diseases to enhance consumer participation in research. The CMSG has built a network of consumer members who guide research priorities, peer review systematic reviews and also promote and facilitate consumer-appropriate knowledge dissemination. Consumers were recruited through links with other arthritis organizations and the recruitment continues. Specific roles were established for the consumer team and responsibilities of the CMSG staff developed. The continuing development of a diversified team of consumer participants enables the CMSG to produce and promote access to high quality relevant systematic reviews and summaries of those reviews to the consumer.
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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 | 0.391 | 0.330 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.017 | 0.051 |
| Scholarly communication | 0.032 | 0.056 |
| Open science | 0.009 | 0.093 |
| Research integrity | 0.018 | 0.020 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".