Physiotherapy Practice in Primary Health Care: A Survey of Physiotherapists in Team-Based Primary Care Organizations in Ontario
Bibliographic record
Abstract
Purpose: This study describes (1) the current state of physiotherapy practice in team-based primary care organizations in Ontario, (2) the perceived barriers to and facilitators of providing physiotherapy services, and (3) recommendations for improving how these services are provided. Method: This was a cross-sectional, web-based survey. We analyzed the responses using descriptive statistics and summative content analysis. Results: A total of 66 responses were received, and 61 were included in the final analysis. The respondents reported that most of their practice was directed toward musculoskeletal care, followed by multi-system, neurological, and cardiorespiratory conditions, and that most of their direct patient care was focused on in-person, one-to-one assessment or follow-up. Frequently identified barriers to providing physiotherapy services included a lack of space, resources, time, and equipment. The most common facilitators were support from management, recognition and support from other health care providers about the value and role of physiotherapists, and appropriate referrals from other health care providers. The most common recommendation was to increase the physiotherapist-to-patient ratio at primary care sites. Conclusions: Physiotherapists provide care to diverse populations in team-based primary care, which is influenced by specific barriers and facilitators. Our results highlight opportunities for physiotherapists in this context, such as increasing the provision of first-contact care and group-based interventions.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".