Consumer engagement in living evidence “a beautiful opportunity”: International qualitative study with patients and methodologists
Bibliographic record
Abstract
Abstract Objective We aimed to explore the opportunities, challenges and practical strategies for consumer engagement (i.e., patient and public involvement) in living evidence (systematic reviews, guidelines and health technology assessments that are continually updated with the latest evidence). Study Design and Setting In this international qualitative study, methodologists (producers of systematic reviewers, guidelines and health technology assessments) with an interest in living evidence, and consumers (patients, informal carers, the public and their representatives) with experience contributing to evidence synthesis production participated in either a face‐to‐face workshop, online focus group or semistructured interview. We analysed data using descriptive synthesis. Results Forty‐one methodologists and seven consumers from nine countries participated. A minority of participants in both groups had direct experience with living evidence synthesis. We identified seven themes: harnessing consumer enthusiasm in recruitment; ‘better’ consumer engagement based on deeper relationships; improved and ongoing orientation, support and remuneration; maintaining an ongoing commitment; potentially different guideline development stages and tasks; larger groups of consumers and multiple roles; and ongoing incorporation of consumer insights. Conclusion Methodologists and consumers believe living evidence approaches present an imperative and an opportunity to explore new models of consumer engagement, bringing together larger and more diverse communities of consumers in true partnerships with methodologists. Consumer engagement strategies for living evidence allow ongoing improvement to engagement methods and ongoing incorporation of consumer experiences, preferences and values as they develop and change over time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.088 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".