Evaluating the importance of a core competency and capability framework for advanced practice physiotherapy: A cross-sectional survey
Bibliographic record
Abstract
INTRODUCTION: The need for a global core competency and capability framework for advanced practice physiotherapy is important due to the rapidly changing nature of health care delivery internationally and the need to standardize advanced practice physiotherapy. OBJECTIVE: To determine the importance of a proposed international core competency and capability framework for advanced practice physiotherapy. METHODS: We conducted a cross-sectional online survey of advanced practice physiotherapists across seven countries. The importance of each competency and capability was rated on a five-point agreement Likert scale. Participants were from the United Kingdom, Ireland, Australia, New Zealand, Canada, Switzerland and Argentina. RESULTS: A total of 99 participants completed the survey, comprising 63% (57/90) females and 33% (30/90) males. Sixty percent, 60% (54/90), had over 20 years of experience. The survey participants represented a diverse geographic distribution, with 25% (23/90) from Australia, 25% (23/90) from Canada, 18% (6/90) from New Zealand, and 18% (6/90) from the United Kingdom. Four percent 4% (4/90) from Ireland, and 4% (4/90) from other countries (Switzerland and Argentina). The survey revealed a strong consensus among participants, with all competencies and capabilities ranked as high and considered important to advanced practice. CONCLUSION: This study demonstrates a consensus among advanced practice physiotherapists across seven countries on the importance of a proposed competency and capability framework. The findings highlight the need for a global standard in advanced practice physiotherapy, particularly in light of the rapidly changing healthcare landscape.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".