Physical Activity and Sedentary Behaviour of Master of Physical Therapy Students: An Exploratory Study of Facilitators and Barriers
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".