From reflection to phronesis in ‘good’ physiotherapy practice
Bibliographic record
Abstract
BACKGROUND: Reflection is promoted in health professional education as a way to learn in and on practice. 'Being reflective' is considered important to 'good' and 'expert' physiotherapy practice, yet there is limited research on reflective practices of experienced physiotherapists. For Aristotle, a good person reasons and acts in ways to promote human flourishing. Physiotherapists' perspectives on the place of reflection in good practice has the potential to advance professional understandings of how it may be enacted. Such knowledge may inform health professions education, regulatory guidelines, professional practices, and patient interactions. PURPOSE: The purpose of this research was to examine experienced musculoskeletal (MSK) practitioners' perceptions of reflection in the practice of a 'good' physiotherapist. METHODS: A secondary analysis of data arising from a hermeneutic phenomenological study into physiotherapists' perceptions of the qualities and practices that constitutes a 'good' physiotherapist was undertaken. The secondary analysis focused on ways of 'being reflective', which emerged as a major theme in the original study. FINDINGS: Six themes were identified related to 'being reflective' in a 'good' physiotherapist: 1) learning from experience; 2) integrating multiple perspectives; 3) navigating indeterminate zones; 4) developing embodied knowledge; 5) questioning assumptions; and 6) cultivating wisdom. CONCLUSIONS: Findings support the notion that 'good' physiotherapy involves a disposition toward making wise judgments through reflection. This practice-based knowledge can inform educational initiatives that nurture practices that foster attention to reflective processes that inform phronesis in professional life. Through reflexivity on what the profession takes for granted, physiotherapists may be better prepared when navigating the indeterminate zones of practice.
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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 | 0.029 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.055 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".