Leadership Education in Physical Therapy: A Roadmap to Prioritize Interventions
Bibliographic record
Abstract
INTRODUCTION: Leadership training is crucial for meeting the evolving demands in health care, but remains inconsistently integrated into physical therapist education programs. This study aims to identify impactful educational interventions from health care programs that would be relevant for developing leadership competencies in entry-level physical therapy programs. REVIEW OF LITERATURE: Although leadership development is well-researched in medicine and nursing, evidence-based interventions specific to physical therapy education remain underexplored. This gap hampers innovation in teaching and research, potentially compromising the profession's capacity to sustain and expand its scope of practice. SUBJECTS: This consensus study involved 19 academic faculty members from 9 Canadian university physical therapy programs, all of which are aligned with global competency frameworks. METHODS: A literature review using Medline, CINAHL, and ERIC identified studies evaluating leadership education interventions in university health sciences programs. Interventions were categorized by Tremblay-Wragg's educational strategies and by impact levels based on Kirkpatrick's model. A Delphi method was employed to reach consensus on the relevance of implementing these interventions in physical therapy education to foster health promotion, advocacy, and scope of practice expansion. RESULTS: Thirty articles were selected, identifying 27 interventions, primarily in medicine (n = 10) and nursing (n = 10). The two-round Delphi study reached consensus on 24 interventions, with the strongest agreement to include internships in community settings (100% agreement), community service projects (95% agreement), and advocacy projects (95% agreement). The most endorsed educational strategies were project-based learning (24%), teamwork (21%), experiential learning (14%), all socio-constructivist approaches. The selected interventions predominantly (63%) demonstrated impacts on attitudes, knowledge, or skills (Kirkpatrick level 2). DISCUSSION AND CONCLUSION: This study offers an evidence-based roadmap of impactful leadership interventions that can be adapted to the practical realities of physical therapy programs. Prioritizing these interventions may enhance students' leadership competencies and support future multisite trials and longitudinal outcome research.
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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 | 0.048 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".