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Are family medicine residents trained to counsel patients on physical activity? The Canadian experience and a call to action

2021· article· en· W3204749788 on OpenAlexaffabout
Jane S Thornton, Karim Khan, Richard Weiler, Christopher Mackie, Robert J. Petrella

Bibliographic record

VenuePostgraduate Medical Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsMcMaster UniversityMiddlesex London Health UnitUniversity of British ColumbiaFowler Kennedy Sport Medicine ClinicCentre for Family MedicineWestern University
Fundersnot available
KeywordsMedicineMedical prescriptionFamily medicinePhysical activityAlternative medicineMedical educationNursingPhysical therapy

Abstract

fetched live from OpenAlex

Physical inactivity is a leading risk factor for non-communicable diseases (NCDs) and early mortality. Family physicians have an important role in providing physical activity counselling to patients to help prevent and treat NCDs. Lack of training on physical activity counselling is a barrier in undergraduate medical education, yet little is known regarding physical activity teaching in postgraduate family medicine residency. We assessed the provision, content and future direction of physical activity teaching in Canadian postgraduate family medicine residency programs to address this data gap. Fewer than half of Canadian Family Medicine Residency Programme directors reported providing structured physical activity counselling education to residents. Most directors reported no imminent plans to change the content or amount of teaching. These results reflect significant gaps between the recommendations of WHO, which calls on doctors to prescribe physical activity, and the current curricular content and needs of family medicine residents. Almost all directors agreed that online educational resources developed to assist residents in physical activity prescription would be beneficial. By describing the provision, content and future direction of physical activity training in family medicine, physicians and medical educators can develop competencies and resources to meet this need. When we equip our future physicians with the necessary tools, we can improve patient outcomes and do our part to reduce the global epidemic of physical inactivity and chronic disease.

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)0.003
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 score0.929
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.112
GPT teacher head0.390
Teacher spread0.279 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

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