MétaCan
Menu
Back to cohort
Record W4385494461 · doi:10.1186/s13643-023-02279-1

Protocol for the development of guidance for collaborator and partner engagement in health care evidence syntheses

2023· article· en· W4385494461 on OpenAlexafffund
Peter Tugwell, Vivian Welch, Olivia Magwood, Alex Todhunter‐Brown, Elie A. Akl, Thomas W. Concannon, Joanne Khabsa, Richard Morley, Holger J. Schünemann, Lyubov Lytvyn, Arnav Agarwal, Alba Antequera, Marc T. Avey, Pauline Campbell, Christine Chang, Stephanie Chang, Leonila F. Dans, Omar Dewidar, Davina Ghersi, Ian D. Graham, Glen Hazlewood, Jennifer Hilgart, Tanya Horsley, Denny John, Janet Jull, Lara Maxwell, Chris McCutcheon, Zachary Munn, Francesco Nonino, Jordi Pardo Pardo, Roses Parker, Kevin Pottie, Gabriel Rada, Alison Riddle, Anneliese Synnot, Elizabeth Tanjong Ghogomu, E. Tomlinson, Karine Toupin‐April, Jennifer Petkovic

Bibliographic record

VenueSystematic Reviews · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsInstitut du Savoir MontfortRoyal College of Physicians and Surgeons of CanadaWestern UniversityBruyèreCanadian Council on Animal CareQueen's UniversityMcMaster UniversityUniversity of CalgaryImpactOttawa HospitalChildren's Hospital of Eastern OntarioCochraneUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsKnowledge translationMedicineEquity (law)Health careEvidence-based practicePublic relationsNursingMedical educationAlternative medicineKnowledge managementPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Involving collaborators and partners in research may increase relevance and uptake, while reducing health and social inequities. Collaborators and partners include people and groups interested in health research: health care providers, patients and caregivers, payers of health research, payers of health services, publishers, policymakers, researchers, product makers, program managers, and the public. Evidence syntheses inform decisions about health care services, treatments, and practice, which ultimately affect health outcomes. Our objectives are to: A. Identify, map, and synthesize qualitative and quantitative findings related to engagement in evidence syntheses B. Explore how engagement in evidence synthesis promotes health equity C. Develop equity-oriented guidance on methods for conducting, evaluating, and reporting engagement in evidence syntheses METHODS: Our diverse, international team will develop guidance for engagement with collaborators and partners throughout multiple sequential steps using an integrated knowledge translation approach: 1. Reviews. We will co-produce 1 scoping review, 3 systematic reviews and 1 evidence map focusing on (a) methods, (b) barriers and facilitators, (c) conflict of interest considerations, (d) impacts, and (e) equity considerations of engagement in evidence synthesis. 2. Methods study, interviews, and survey. We will contextualise the findings of step 1 by assessing a sample of evidence syntheses reporting on engagement with collaborators and partners and through conducting interviews with collaborators and partners who have been involved in producing evidence syntheses. We will use these findings to develop draft guidance checklists and will assess agreement with each item through an international survey. 3. CONSENSUS: The guidance checklists will be co-produced and finalised at a consensus meeting with collaborators and partners. 4. DISSEMINATION: We will develop a dissemination plan with our collaborators and partners and work collaboratively to improve adoption of our guidance by key organizations. CONCLUSION: Our international team will develop guidance for collaborator and partner engagement in health care evidence syntheses. Incorporating partnership values and expectations may result in better uptake, potentially reducing health inequities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.044
metaresearch head score (Gemma)0.045
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.809
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0440.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.868
GPT teacher head0.733
Teacher spread0.135 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreProtocol

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".

Quick stats

Citations18
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueSystematic ReviewsSame topicHealth Policy Implementation ScienceFrench-language works237,207