MétaCan
Menu
← Back to cohort
Record W2605139584

Exploring barriers and facilitators to the implementation of Exercise is Medicine® Canada on campus groups

2016· article· en· W2605139584 on OpenAlexaffabout
Jennifer R. Tomasone, B. McEachern, Susan Yungblut

Bibliographic record

VenueJournal of Exercise, Movement, and Sport · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsCanadian Society for Exercise PhysiologyQueen's University
Fundersnot available
KeywordsEnthusiasmThematic analysisContext (archaeology)Medical educationHealth carePsychologyMedicineQualitative researchNursingSociologyPolitical scienceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

The Exercise is Medicine® Canada on Campus (EIMC-OC) program was established in 2013 to foster relationships between health care professional trainees, while providing opportunities for students to implement PA promotion initiatives. Currently, 34 EIMC-OC groups are in operation, and each has encountered challenges and successes that have yet to be formally documented. The purpose of the current project was to identify barriers and facilitators when implementing an EIMC group on a university or college campus. Representatives from interested EIMC-OC groups were asked to complete a preliminary survey and participate in a semi-structured interview based on the Consolidated Framework for Implementation Research in order to unpack groups' barriers and facilitators at multiple levels of implementation. Interviews were transcribed verbatim and subjected to thematic analysis. Twelve EIMC-OC groups from six provinces participated. Common barriers included lack of finances, time constraints of group members due to other commitments, recruitment of students from a variety of disciplines, and encouraging health care professionals to follow through with exercise prescriptions. Common facilitators included the enthusiasm and commitment of group members, consistent support from one or more faculty members, regular face-to-face group meetings with tangible action items, using a project-based structure where tasks are delegated to appointed leaders, communication with other EIMC-OC groups, and collaboration with other campus or community groups. Although each EIMC-OC group is shaped by its local context, groups face similar barriers and facilitators. The sharing of best practices between groups can provide direction for, and enhance the success of, the EIMC-OC program.

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)0.023
metaresearch head score (Gemma)0.055
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.759

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.055
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.004
Scholarly communication0.0040.002
Open science0.0030.006
Research integrity0.0010.003
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 head0.181
GPT teacher head0.481
Teacher spread0.300 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Exercise, Movement, and Sport→Same topicHealth Policy Implementation Science→French-language works237,207→