Consumer involvement in systematic reviews of comparative effectiveness research
Bibliographic record
Abstract
BACKGROUND: The Institute of Medicine recently recommended that comparative effectiveness research (CER) should involve input from consumers. While systematic reviews are a major component of CER, little is known about consumer involvement. OBJECTIVE: To explore current approaches to involving consumers in US-based and key international organizations and groups conducting or commissioning systematic reviews ('organizations'). DESIGN: In-depth, semi-structured interviews with key informants and review of organizations' websites. SETTING AND PARTICIPANTS: Seventeen highly regarded US-based and international (Cochrane Collaboration, Campbell Collaboration) organizations. RESULTS: Organizations that usually involve consumers (seven of 17 in our sample) involve them at a programmatic level in the organization or in individual reviews through one-time consultation or on-going collaboration. For example, consumers may suggest topics, provide input on the key questions of the review, provide comments on draft protocols and reports, serve as co-authors or on an advisory group. Organizations involve different types of consumers (individual patients, consumer advocates, families and caregivers), recruiting them mainly through patient organizations and consumer networks. Some offer training in research methods, and one developed training for researchers on how to involve consumers. Little formal evaluation of the effects of consumer involvement is being carried out. CONCLUSIONS: Consumers are currently involved in systematic reviews in a variety of ways and for various reasons. Assessing which approaches are most effective in achieving different aims of consumer involvement is now required to inform future recommendations on consumer involvement in CER.
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 | 0.845 | 0.912 |
| Meta-epidemiology (narrow) | 0.003 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.029 | 0.028 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.008 | 0.017 |
| Research integrity | 0.018 | 0.013 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".