Entry-level physical therapist curricula in geriatric care: an Italian national survey study
Bibliographic record
Abstract
Introduction: To address the health needs of the aging population, it is necessary to map entry-level curricula for health professionals. This survey investigated geriatric-related content in entry-level physical therapist (PT) curricula offered by Italian universities. Methods: A cross-sectional observational study was conducted using the CROSS checklist. A 66 questions survey was developed and sent via e-mail to all entry-level PT program directors of the Italian universities. Results: A total of 34 physical therapist undergraduate course directors out of 62 completed the survey, yielding a 54.8% response rate. These results highlight the need for greater emphasis on health promotion and prevention. Although essential competencies such as the promotion of an active lifestyle and fall prevention appear to be well covered, other aspects remain underrepresented. Relevant gaps were also noted in the care and rehabilitation of some common chronic conditions (e.g., constipation, depression, and diabetes), as well as in therapeutic education. Greater attention to these topics could help align training with the emerging needs of the healthcare system. However, 11.76% of Italian PT programs do not include specific modules or courses dedicated to geriatric rehabilitation. Overall, there is considerable variability in teaching hours, topic coverage, and depth. Conclusions: This study provides meaningful insights for updating the current PT curricula in geriatric care. This survey could represent a tool for future longitudinal research on mapping curricula over time in response to the aging population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".