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Record W2914097460 · doi:10.3899/jrheum.181071

OMERACT Development of a Core Domain Set of Outcomes for Shared Decision-making Interventions

2019· article· en· W2914097460 on OpenAlexafffundvenue
Karine Toupin‐April, Jennifer L. Barton, Liana Fraenkel, Alexa Meara, Linda Li, Peter Brooks, Maarten de Wit, Dawn Stacey, France Légaré, Beverley Shea, Anne Lyddiatt, C. Richard Hofstetter, Robin Christensen, Marieke Scholte Voshaar, María E. Suarez‐Almazor, Annelies Boonen, Tanya Meade, Lyn March, Janet Jull, Willemina Campbell, Rieke Alten, Suvi Karuranga, Esi M. Morgan, Ayano Kelly, Jessica Kaufman, Sophie Hill, Lara Maxwell, Dorcas E. Beaton, Yasser El Miedany, Shikha Mittoo, Susan J. Bartlett, Jasvinder A. Singh, Peter Tugwell

Bibliographic record

VenueThe Journal of Rheumatology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsChildren's Hospital of Eastern Ontario
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesUniversity of Texas MD Anderson Cancer CenterUniversity of TorontoNational Institutes of HealthMaastricht Universitair Medisch CentrumQueen's UniversityUniversiteit MaastrichtLa Trobe UniversityArthritis SocietyOdense UniversitetshospitalUniversité LavalOttawa Hospital Research InstituteMcGill UniversityUniversity of OttawaWestern Sydney UniversityKing's College LondonParker Institute for Cancer ImmunotherapyCincinnati Children's Hospital Medical CenterUniversity of TwenteAin Shams UniversityOak Foundation
KeywordsMedicineCore (optical fiber)Psychological interventionSet (abstract data type)Nursing

Abstract

fetched live from OpenAlex

OBJECTIVE: The Outcome Measures in Rheumatology (OMERACT) Shared Decision Making (SDM) Working Group aims to determine the core outcome domain set for measuring the effectiveness of SDM interventions in rheumatology trials. METHODS: A white paper was developed to clarify the draft core domain set. It was then used to prepare for interviews to investigate reasons for lack of consensus on it and to suggest further improvements. RESULTS: OMERACT scientists/clinicians (n = 13) and patients (n = 10) suggested limiting the core domain set to outcome domains, removing process domains, and clarifying remaining domains. CONCLUSION: A revised core domain set will undergo further consensus-building.

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 imitation

Not 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.

metaresearch head score (Codex)0.166
metaresearch head score (Gemma)0.195
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.166
Threshold uncertainty score0.879

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1660.195
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0020.007
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.158
GPT teacher head0.494
Teacher spread0.336 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations20
Published2019
Admission routes3
Has abstractyes

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