Factors Affecting Weight Counseling Attitudes and Behaviors Among U.S. Medical Students
Bibliographic record
Abstract
PURPOSE: To identify the factors associated with perceived relevance and reported frequency of weight counseling among medical students. METHOD: The authors surveyed all medical students in the Class of 2003 at 16 U.S. medical schools during first-year orientation (1999), orientation to wards (2000-2001), and fourth year (2002-2003). RESULTS: Across the three time points, response rates were, respectively, 89% (1,846/2,080), 82% (1,630/1,982), and 77% (1,469/1,901); a total of 2,316 medical students participated. More than half of the students felt that weight counseling was highly relevant to their intended practice (respectively, 63% [1,149/1,812], 70% [1,050/1,509], and 54% [717/1,329]). Among fourth-year students, 25% (350/1,393) reported that they "usually-always" provided weight counseling to general medicine patients. Perceived relevance peaked at orientation to wards (odds ratio [OR]=1.88), then declined to initial levels.Greater school support for health promotion was positively associated with high counseling frequency (OR=1.06). Students interested in non-primary-care specialties were less likely than others to consider weight counseling highly relevant (OR=0.59) or, in their fourth year, to provide it to patients (OR=0.50). Finally, higher personal fruit/vegetable consumption and confidence that this intake would increase were positively associated with high perceived relevance (both OR=1.07) and frequency of weight counseling (OR=1.09 and 1.16, respectively). CONCLUSIONS: The majority of medical students consider weight counseling relevant to their intended careers. Promoting healthy personal behaviors and encouraging acquisition of skills in weight management across all specialties would likely improve clinical 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".