An Electronic Wellness Program to Improve Diet and Exercise in College Students: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: In transitioning from adolescence to adulthood, college students are faced with significant challenges to their health habits. Independence, stress, and perceived lack of time by college students have been known to result in poor eating and exercise habits, which can lead to increased disease risk. OBJECTIVE: To assess the feasibility and to determine preliminary efficacy of an electronic wellness program in improving diet and physical activity in college students. METHODS: A 24-week diet and physical activity program was delivered via email to 148 college students. The intervention involved weekly, tailored, and interactive diet and physical activity goals. The control group received nondiet and nonexercise-related health fact sheets. Anthropometric and blood pressure measurements, as well as food frequency and physical activity surveys were conducted at baseline, week 12, and week 24. Students' choice of fruit as a snack was also monitored at study visits. RESULTS: Students were 18-20 years old, 69% female, and from a diverse college campus (46% Caucasian, 23% Asian, 20% African American, 11% other). At week 24, 84% of students reported reading at least half of all emails. Mean change (standard error [SE]) from baseline of saturated fat intake was marginally significant between the treatment groups at week 24, 0.7 (SE 0.42) % kcal for control and -0.3 (SE 0.30) % kcal for intervention (P=0.048). A significant difference in percent of snacks chosen that were fruit (χ(2)1, N=221 = 11.7, P<0.001) was detected between the intervention and control group at week 24. CONCLUSIONS: Use of an electronic wellness program is feasible in college students and resulted in a decrease in saturated fat intake and an increase in observed fruit intake compared to a control group.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".