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Record W4309383120 · doi:10.1101/2022.11.14.22282098

Establishing Internationally Accepted Conceptual and Operational Definitions of Social Prescribing Through Expert Consensus: A Delphi Study

2022· preprint· en· W4309383120 on OpenAlexaff
Caitlin Muhl, Kate Mulligan, Imaan Bayoumi, Rachelle Ashcroft, Christina Godfrey

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsPublic Health OntarioUniversity of TorontoQueen's University
Fundersnot available
KeywordsOperationalizationDelphi methodConceptual frameworkManagement scienceMeaning (existential)The Conceptual FrameworkConceptual schemaTheoretical definitionPsychologyKnowledge managementSociologyComputer scienceSocial psychologySocial scienceEngineeringEpistemology

Abstract

fetched live from OpenAlex

ABSTRACT Introduction With the social prescribing movement gaining traction globally, there is a need for an agreed definition of social prescribing. There are two types of definitions – conceptual and operational, meaning agreement on both types of definitions is needed. 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. Methods Consensus was defined a priori as ≥80% agreement. In Round 1, participants were asked to list key elements that are essential to the conceptual definition of social prescribing and to provide corresponding statements that operationalize each of the key elements. In Round 2, participants were asked to rate their agreement with items from the first round for inclusion in the conceptual and/or operational definitions of social prescribing. Based on the findings from this round, the conceptual and operational definitions of social prescribing were developed, including long and short versions of the conceptual definition. In Round 3, participants were asked to rate their agreement with the conceptual and operational definitions of social prescribing. Participants This study involved an international, multidisciplinary panel of experts. The expert panel (n=48) represented 26 different 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. STRENGTHS AND LIMITATIONS OF THIS STUDY Strengths of this study include the consensus method that was chosen, the diversity and size of the expert panel, and the fact that consensus was defined a priori as ≥80% agreement Limitations of this study include the fact that only those who could speak, read, and write English were eligible to participate in this study, the attrition of the expert panel, and the fact that the expert panel did not reach 100% agreement on the definitions

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)0.000
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 score0.324
Threshold uncertainty score0.994

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.203
GPT teacher head0.346
Teacher spread0.143 · 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 teacher head, not a consensus.

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

Citations18
Published2022
Admission routes1
Has abstractyes

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