MétaCan
Menu
Back to cohort
Record W4384344015 · doi:10.1136/bmjopen-2022-070184

Establishing internationally accepted conceptual and operational definitions of social prescribing through expert consensus: a Delphi study

2023· article· en· W4384344015 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

VenueBMJ Open · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsPublic Health OntarioUniversity of TorontoQueen's University
Fundersnot available
KeywordsDelphi methodMedicineMultidisciplinary approachConceptual frameworkDelphiSocial workPublic relationsManagement scienceKnowledge managementSocial scienceSociologyComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to establish internationally accepted conceptual and operational definitions of social prescribing. DESIGN: A three-round Delphi study was conducted. SETTING: This study was conducted virtually using an online survey platform. PARTICIPANTS: This study involved an international, multidisciplinary panel of experts. The expert panel (n=48) represented 26 countries across five continents, numerous expert groups and a variety of years of experience with social prescribing, with the average being 5 years (range=1-20 years). RESULTS: After three rounds, internationally accepted conceptual and operational definitions of social prescribing were established. The definitions were transformed into the Common Understanding of Social Prescribing (CUSP) conceptual framework. CONCLUSION: This foundational work offers a common thread-a shared sense of what social prescribing is, which may be woven into social prescribing research, policy and practice to foster common understanding of this concept.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.409
GPT teacher head0.442
Teacher spread0.033 · 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