Study of Medical Studentsâ Malpractice Fear and Defensive Medicine: A âHidden Curriculum?â
Bibliographic record
Abstract
Introduction: Defensive medicine is a medical practice in which health care providers’ primary intent is to avoid criticism and lawsuits, rather than providing for patients’ medical needs. The purpose of this study was to characterize medical students’ exposure to defensive medicine during medical school rotations. Methods: We performed a cross- sectional survey study of medical students at the beginning of their third year. We gave students Likert scale questionnaires, and their responses were tabulated as a percent with 95% confidence interval (CI).Results: Of the 124 eligible third-year students,102 (82%) responded. Most stated they rarely worried about being sued (85.3% [95% CI=77.1% to 90.9%]). A majority felt that faculty were concerned about malpractice (55.9% [95% CI=46.2% to 65.1%]), and a smaller percentage stated that faculty taught defensive medicine (32.4% [95% CI=24.1% to 41.9%]). Many students believed their satisfaction would be decreased by MC and lawsuits (51.0% [95% CI=41.4% to 60.5%]). Some believed their choice of medical specialty would be influenced by MC (21.6% [95% CI=14.7% to 30.5%]), and a modest number felt their enjoyment of learning medicine was lessened by MC (23.5% [95% CI=16.4% to 32.6%]). Finally, a minority of students worried about practicing and learning procedures because of MC (16.7% [95% CI=10.7% to 25.1%]).Conclusion: Although third- year medical students have little concern about being sued, they are exposed to malpractice concerns and taught considerable defensive medicine from faculty. Most students believe that fear of lawsuits will decrease their future enjoyment of medicine. However, less than a quarter of students felt their specialty choice would be influenced by malpractice worries and that malpractice concerns lessened their enjoyment of learning medicine. [West J Emerg Med.2014;15(3):293–298.]
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".