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Record W4414608410 · doi:10.15273/hpj.v4i3.11985

Examining Student Perceptions and Awareness of Social Prescribing in a Canadian University

2024· article· en· W4414608410 on OpenAlexaffabout
Alison Smoke, Stephanie Wadge, Anthony A. Barrett, Sophia Nikitin, Evelin Melekh, Madelyn Law, Caitlin Muhl

Bibliographic record

VenueHealthy Populations Journal · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsBrock University
Fundersnot available
KeywordsPerceptionCurriculumQualitative researchData collectionHealth careSocial careQualitative property

Abstract

fetched live from OpenAlex

Introduction: As the social prescribing movement grows in Canada, there is a need to understand whether students (a) are aware of this concept and (b) think it is important. Objectives: The aim of this study was to examine student perceptions and awareness of social prescribing in a Canadian university. Methods: This study was conducted at Brock University. Data collection took place between March and June of 2023. Eligibility criteria included (a) being a student at Brock University and (b) being able to read and write English. Participants completed an online survey. Quantitative data analysis consisted of basic mathematical computations. Qualitative data analysis consisted of qualitative content analysis. Results: Most participants (138/183, 75.4%) had never heard about social prescribing before. Once they were told what social prescribing is, the vast majority of participants thought that it seemed like a useful way to support health and well-being (121/126, 96.0%), felt that offering it on campus would be beneficial (129/130, 99.2%), believed that it is relevant to future health care professionals (121/128, 94.5%), thought that it should be part of the curriculum for health sciences programs (118/128, 92.2%), and expressed that they would be willing to follow their physician’s advice if they were to suggest social prescribing at an appointment (119/126, 94.4%). Conclusion/Discussion: Given the lack of awareness about social prescribing and the positive perceptions about this concept among the student body, Canadian post-secondary institutions are encouraged to (a) integrate this concept into the curriculum for health sciences programs and (b) offer social prescribing on campus.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.913

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)0.0000.000

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 head0.166
GPT teacher head0.360
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2024
Admission routes2
Has abstractyes

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