Innovative curriculum is needed to address residents’ attitudes toward older adults: the case of geriatric trauma
Bibliographic record
Abstract
BACKGROUND: Medical trainees' negative perceptions towards older adult care have been widely reported, catalyzing targeted curricula in geriatric medicine. Little is known about surgical residents' attitudes toward and perceptions of the educational value of caring for injured older adults. This information is needed to ensure the surgical workforce is adequately trained to care for this growing patient population. In this study, we assessed surgical trainees' attitudes towards geriatric trauma care to inform a curriculum in geriatric trauma. METHODS: We surveyed North American general surgery trainees' beliefs and attitudes toward caring for older trauma patients, and the educational value they ascribed to learning about older trauma patient care. Descriptive statistics were used to report participant characteristics and responses. RESULTS: Three hundred general surgery trainees from 94 post-graduate programs responded. Respondents reported too much time co-ordinating care (56%), managing non-operative patients (56%), and discharge planning (65%), all activities important to the care of older trauma patients. They recognized the importance of geriatric trauma care for their future careers (52%) but were least interested in reading about managing geriatric trauma patients (28%). When asked to rank clinical vignettes by educational value, respondents ranked the case of an older adult as least interesting (74%). As respondents progressed through their training, they reported less interest in geriatric trauma care. CONCLUSIONS: Our survey results demonstrate the generally negative attitudes and beliefs held by postgraduate surgical trainees towards the care of older adult trauma patients. Future work should focus on identifying specific changes to the postgraduate surgical curriculum which can effectively alter these attitudes and beliefs and improve the care for injured older adults.
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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 | 0.003 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".