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Record W4390942354 · doi:10.5334/ijic.icic23475

Defining Social Prescribing: Fostering Common Understanding of a Vital Tool in the Integrated Care Toolbox

2023· article· en· W4390942354 on OpenAlexaffabout
Caitlin Muhl, Kate Mulligan, Imaan Bayoumi, Rachelle Ashcroft, Christina Godfrey

Bibliographic record

VenueInternational Journal of Integrated Care · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of TorontoQueen's University
Fundersnot available
KeywordsOperationalizationDelphi methodPublic relationsIntegrated careAllianceHealth careMultidisciplinary approachMedicinePsychologySociologyPolitical scienceSocial scienceComputer science

Abstract

fetched live from OpenAlex

According to the World Health Organization, social prescribing is a holistic approach to health and wellbeing that promotes integrated care. There is growing interest in social prescribing around the world, with over 20 countries involved in the social prescribing movement. However, an agreed definition of social prescribing has yet to emerge. This is problematic for social prescribing research, policy, and practice. Since there are two types of definitions – conceptual and operational, agreement on both types of definitions is needed. The aim of this study was to establish internationally accepted conceptual and operational definitions of social prescribing. This study was conducted for the social prescribing community to support the advancement of the social prescribing movement. The research team – one doctoral student and four committee members, collectively designed, implemented, and monitored this research. This study involved an international, multidisciplinary panel of experts. The expert panel (n=48) represented 26 different countries across five continents and numerous expert groups, including service providers, service users, researchers, students, and representatives of the Global Social Prescribing Alliance, the Social Prescribing Network, the Social Prescribing Youth Network, the National Academy for Social Prescribing, and the Canadian Institute for Social Prescribing. A three-round Delphi study was conducted. 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. Consensus was reached on the definitions in this round, which signified the successful development of internationally accepted conceptual and operational definitions of social prescribing. The definitions were transformed into the Common Understanding of Social Prescribing (CUSP) conceptual framework. For the first time in the history of the social prescribing movement, we now have internationally accepted conceptual and operational definitions of social prescribing. Additionally, the conceptual definitions are distinct from pre-existing definitions, and to our knowledge, the operational definition is the first in the world. Together, the CUSP conceptual framework and the definitions offer a common thread – a shared sense of what social prescribing is. Social prescribing researchers, policymakers, and practitioners are encouraged to use the outputs of this work in 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.

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)0.200
metaresearch head score (Gemma)0.129
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.200
Threshold uncertainty score0.987

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2000.129
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0090.004
Science and technology studies0.0150.081
Scholarly communication0.0260.048
Open science0.0070.063
Research integrity0.0100.025
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 head0.098
GPT teacher head0.325
Teacher spread0.227 · 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.

Study designNot applicable
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

Citations0
Published2023
Admission routes2
Has abstractyes

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