Online interventions to increase physical activity levels in self-reported inactive adults: the ONWARDS randomised controlled trial
Bibliographic record
Abstract
Background: Digital interventions have the potential to increase physical activity in adults with the use of few resources, but evidence of long-term effectiveness is limited. This study aimed to evaluate the effects of three digital interventions on physical activity. Methods: 183 self-reported inactive adults (<150 min per week of moderate to vigorous physical activity (MVPA)) aged 22-55 years were included in a hybrid type 1 effectiveness-implementation trial over 18 months and were randomised to three fully web-based interventions: (A) activity tracker with the personalised metric Personal Activity Intelligence on a mobile app, (B) group A+home-based online training and (C) group B+online peer support through social media. Physical activity was measured with hip-worn accelerometers (ActiGraph GT3X-BT) at baseline, 6, 12 and 18 months. Outcome measures included MVPA, light and total physical activity, steps, adherence to physical activity recommendations, waist circumference (WC), quality of life, perceived competence for exercise, self-efficacy for exercise, social support and reasons for performing physical activity. Longitudinal changes in outcomes were evaluated using linear mixed models adjusted for baseline values. Results: Mean MVPA in all groups at baseline was over two times higher than the criteria for inactive and decreased from 69.7 min per day (95% CI: 67.3 to 72.1) to 60.2 min (95% CI: 56.8 to 63.7) through 18 months (p<0.001). No time by group interaction was observed (p=0.97). Similar patterns were observed for light and total physical activity (main effect of time: both p<0.02, time by group interaction: both p>0.59). WC increased from baseline through follow-up (all p<0.001), but with no time by group interaction (all p>0.15). Conclusion: Self-reported physically inactive adults receiving an activity tracker with a mobile app accumulated high physical activity levels at baseline but decreased their activity levels over 18 months. Adding home-based online training and peer support did not provide additional effects. Trial registration number: Prospectively registered, 23 of April 2021, identifier: NCT04526, https://clinicaltrials.gov/ct2/show/NCT04526444.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".