MétaCan
Menu
Back to cohort
Record W4367315111 · doi:10.1186/s40900-023-00433-6

Key issues for stakeholder engagement in the development of health and healthcare guidelines

2023· article· en· W4367315111 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch Involvement and Engagement · 2023
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsWestern UniversityBruyèreCanadian Council on Animal CareOttawa HospitalMontfort HospitalMcMaster University Medical CentreSt. Joseph’s Healthcare HamiltonUniversity of CalgaryImpactAlberta Health ServicesMcMaster UniversityUniversity of Ottawa
Fundersnot available
KeywordsStakeholder engagementKey (lock)Health careStakeholderProcess managementBusinessPublic relationsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Established in 2015, the Multi-Stakeholder Engagement (MuSE) Consortium is an international network of over 120 individuals interested in stakeholder engagement in research and guidelines. The MuSE group is developing guidance for stakeholder engagement in the development of health and healthcare guideline development. The development of this guidance has included multiple meetings with stakeholders, including patients, payers/purchasers of health services, peer review editors, policymakers, program managers, providers, principal investigators, product makers, the public, and purchasers of health services and has identified a number of key issues. These include: (1) Definitions, roles, and settings (2) Stakeholder identification and selection (3) Levels of engagement, (4) Evaluation of engagement, (5) Documentation and transparency, and (6) Conflict of interest management. In this paper, we discuss these issues and our plan to develop guidance to facilitate stakeholder engagement in all stages of the development of health and healthcare guideline development.

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.

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)0.048
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0480.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.906
GPT teacher head0.646
Teacher spread0.259 · 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