The Mindfulness App Trial for Weight, Weight-Related Behaviors, and Stress in University Students: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: University students are at risk of weight gain during their studies. Key factors related to weight gain in this population include unhealthy weight-related behaviors because of stress. Mindfulness holds promise for weight management. However, there has not been any previous trial that has explored the effectiveness of a student-tailored mindfulness app for stress, weight-related behaviors, and weight. There is limited evidence that current mindfulness apps use evidence-based mindfulness techniques. A novel app was developed that combined evidence-based, mindfulness-based stress reduction and mindful eating (ME) techniques that were tailored to university students, with student-relevant themes for targeting weight behaviors, weight, and stress. OBJECTIVES: The aim of this study was to test the effectiveness, acceptability, and feasibility of a student-tailored mindfulness app for weight, weight-related behaviors, and stress. Testing this app in a rigorous randomized controlled trial (RCT) for these outcomes is a novelty and contribution to this emerging field. METHODS: A 2-arm RCT of an 11-week duration was undertaken at the University of Queensland. Students were either randomized to the mindfulness app (n=45) or to a behavioral self-monitoring electronic diary (e-diary; n=45) for diet and exercise. Analysis of covariance was used to compare differences in weight, stress, mindfulness, ME, physical activity, and eating behaviors between both groups. RESULTS: Neither the mindfulness app group nor the e-diary group lost weight and there were no differences between the groups at follow-up. The mindfulness app group had significantly lower stress levels (P=.02) (adherers only), lower emotional eating (P=.02), and uncontrolled eating (P=.02) as well as higher mindfulness (P≤.001) and ME levels overall (P≤.001). The e-diary group had higher metabolic equivalents of moderate activity levels (P≤.01). However, the effect sizes were small. Regular adherence to mindfulness exercises in the app was low in the group. The majority of students (94%) liked the app and found it to be acceptable. Compared with other exercises, the most helpful reported meditation was the short breathing exercise observing the breath (39.4% [13/33] preferred it). This was the first RCT that tested a mindfulness app for weight and weight-related behaviors in students. The modest level of user adherence likely contributes to the lack of effect on weight loss. However, there was a small, albeit promising, effect on weight-related eating behavior and stress. CONCLUSIONS: A mindfulness app demonstrated effectiveness for stress, eating behaviors, mindfulness, and ME, but the effect sizes were small. Future studies should be conducted over longer periods of time and with greater participant compliance. TRIAL REGISTRATION: Australian New Zealand Trial Registry ACTRN12616001349437; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371370 (Archived by WebCite at http://www.webcitation.org/761cc2K6ft).
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".