Fit Physician - An Interdisciplinary Approach To Promoting Physical Activity In Medical Students Utilizing Activity Trackers
Bibliographic record
Abstract
Healthy people 2020 and the American College of Sports Medicine’s (ACSM) program, “Exercise is Medicine” have called for an increase in the amount of physician office visits that include discussions on physical activity and health promotion. However, physicians are not counseling their patients on physical activity at sufficient rates. It has been shown that physicians who are more physically active and who have positive health habits are more likely to counsel their patients. Currently under 20% of Canadian and US medical schools offer any kind of health promotion and education to medical students. PURPOSE: To develop a physical activity and health promotion program among first year osteopathic medical students. METHODS: 80 first year medical students were randomized into 2 groups. Both groups were given activity trackers. Group 1 (n=40) participated in educational seminars on nutrition and healthy lifestyle habits. In addition, Group 1 attended weekly mentored walks or runs along with fitness challenges were given weekly updates on their activity level. Group 2 (n=40) was given activity trackers with no other intervention. Data was collected on a dashboard that records each subject’s daily activity and sleep duration. Academic test scores were obtained from subjects first comprehensive examination within the first 8 weeks of this program. A two way t-test was used to analyze daily steps taken, sleep duration, and academic performance for 10 weeks between groups. Statistical significance was set at p<0.05. RESULTS: After 8 weeks of our FIT-PHYSICIAN program demonstrated that the intervention group (Group 1) had significantly more steps taken compared to Group 2 (p=0.001). There were no statistically significant differences in sleep duration (p=0.16) or in average composite test scores (p=0.30). CONCLUSIONS: Utilizing activity trackers in conjunction with health education and weekly activity interventions in the first 8 weeks of medical school yielded an increased step count compared to wearing an activity tracker alone. Physical activity and educational intervention did have an effect on composite test scores and sleep duration between groups.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".