Clinical Specialists and Advanced Practitioners in Physical Therapy: A Survey of Physical Therapists and Employers of Physical Therapists in Ontario, Canada
Bibliographic record
Abstract
PURPOSE: Opportunities to expand the role of physical therapists (PTs) have evolved to include clinical specialists and advanced practitioners, although the literature on these roles is limited. We examined perceptions of PTs and PT employers in Ontario regarding clinical specialization and advanced practice. METHODS: Using a modified Dillman approach, a cross-sectional survey was conducted with 500 PTs and 500 PT employers in Ontario. Questionnaires were tailored to address specific issues related to each cohort. RESULTS: Sixty percent of PTs and 53% of PT employers responded to the survey. Thirty-three percent of PT respondents already considered themselves "clinical specialists" (CS), and 8% considered themselves "advanced practitioners" (AP), although neither role is yet formally recognized in Canada. Both groups had substantial interest in pursuing formal recognition of CS and AP status. Respondents indicated that their primary motivation to pursue such roles was to enhance clinical reasoning skills with the goal of improving client outcomes (82% for the role of CS, 71% for the role of AP). Respondents supported the involvement of academic institutions in the process (60% for CS, 70% for AP). CONCLUSION: PTs and PT employers are supportive of the roles of the CS and AP within the profession, even though there is currently no formal recognition of either role in Canada.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".