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Record W2619936541 · doi:10.3138/ptc.2015-76ep

Physical Activity and Sedentary Behaviour of Master of Physical Therapy Students: An Exploratory Study of Facilitators and Barriers

2017· article· en· W2619936541 on OpenAlexaffvenue
Tracey Smetaniuk, Darren L. Johnson, Jeremy Creurer, Kristi Block, M Schlegel, Scotty Butcher, Sarah Oosman

Bibliographic record

VenuePhysiotherapy Canada · 2017
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhotovoiceFocus groupPhysical activityThematic analysisMedicineExploratory researchPhysical therapyMedical educationPsychologyQualitative research

Abstract

fetched live from OpenAlex

Purpose: A full 85% of Canadians fail to meet physical activity (PA) guidelines, and 69% report being sedentary. Physical therapists are uniquely positioned to promote an active lifestyle; thus, we explored the PA and sedentary behaviour (SB) of Master of Physical Therapy (MPT) students as well as the associated facilitators and barriers. Methods: We used a mixed-methods approach, accelerometry and photovoice (a focus group discussion in which participants discussed self-selected photographs). Accelerometer data were used to quantify PA (light, moderate, and vigorous) and SB. Thematic analysis of the focus group discussion was informed by the socio-ecological model. Results: A total of 26% of participants met national PA guidelines, and mean daily sedentary time for participants was 670.7 (SD 34.4) minutes. Photovoice analysis revealed four main themes related to the facilitators of and barriers to PA and SB: (1) priorities and life balance, (2) commitment and accountability, (3) environment, and (4) MPT programming. Conclusions: A full 74% of participants did not meet the recommended PA guidelines; this is concerning given their immanent roles as health care professionals. Physical therapists are well prepared to prescribe PA to clients. Not only do MPT students need competencies in prescribing PA and exercise, but they may also need to be supported in meeting PA guidelines themselves and limiting SB throughout their studies.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.036
GPT teacher head0.360
Teacher spread0.323 · 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

Citations20
Published2017
Admission routes2
Has abstractyes

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