A Randomized Controlled Trial of the Effects of a Web-Based Intervention on Perceived Stress and Diet Quality Among First-Year University Students
Bibliographic record
Abstract
Background: e-Health interventions can potentially improve health care. My Viva Plan ® (MVP) is a web-based program that focuses on mindfulness, nutrition, and physical fitness. The aim of this study was to evaluate the effects of this platform on stress indicators and diet quality among first-year university students. Methods: Ninety-seven university students were enrolled in a randomized, controlled clinical trial. Participants were randomized into control ( n = 49) and MVP ( n = 48) groups. Perceived stress was measured using the self-report Stress Indicator Questionnaire. Diet quality was assessed by the nutrient-rich foods index, and body composition was assessed by a hand-to-foot, multifrequency, bioelectrical impedance analysis. Results: There were no differences in physical, sleep, behavioral, emotional, and personal habit indicators between groups. Diet quality and body composition were similar between groups, except among women in the MVP group with decreased body fat (−1.2 ± 2.6 kg, p < 0.05). Participant engagement was low: 50% of the MVP group did not access the platform. Conclusions: The MVP web-based intervention was not associated with improvements in stress indicators, diet quality, and body composition, likely due to the characteristics of our cohort of healthy young individuals. Future studies should focus on enhancing motivational approaches to explore the potential of e-health interventions that improve health behavior. Clinical Trial Registration number: NCT03579264A.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".