Effect and Process Evaluation of a Smartphone App to Promote an Active Lifestyle in Lower Educated Working Young Adults: Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Mobile technologies have great potential to promote an active lifestyle in lower educated working young adults, an underresearched target group at a high risk of low activity levels. OBJECTIVE: The objective of our study was to examine the effect and process evaluation of the newly developed evidence- and theory-based smartphone app "Active Coach" on the objectively measured total daily physical activity; self-reported, context-specific physical activity; and self-reported psychosocial variables among lower educated working young adults. METHODS: We recruited 130 lower educated working young adults in this 2-group cluster randomized controlled trial and assessed outcomes at baseline, posttest (baseline+9 weeks), and follow-up (posttest+3 months). Intervention participants (n=60) used the Active Coach app (for 9 weeks) combined with a Fitbit activity tracker. Personal goals, practical tips, and educational facts were provided to encourage physical activity. The control group received print-based generic physical activity information. Both groups wore accelerometers for objective measurement of physical activity, and individual interviews were conducted to assess the psychosocial variables and context-specific physical activity. Furthermore, intervention participants were asked process evaluation questions and generalized linear mixed models and descriptive statistics were applied. RESULTS: No significant intervention effects were found for objectively measured physical activity, self-reported physical activity, and self-reported psychosocial variables (all P>.05). Intervention participants evaluated the Active Coach app and the combined use with the Fitbit wearable as self-explanatory (36/51, 70.6%), user friendly (40/51, 78.4%), and interesting (34/51, 66.7%). Throughout the intervention, we observed a decrease in the frequency of viewing graphical displays in the app (P<.001); reading the tips, facts, and goals (P<.05); and wearing the Fitbit wearable (P<.001). Few intervention participants found the tips and facts motivating (10/41, 24.4%), used them to be physically active (8/41, 19.6%), and thought they were tailored to their lifestyle (7/41, 17.1%). CONCLUSIONS: The lack of significant intervention effects might be due to low continuous user engagement. Advice or feedback that was not perceived as adequately tailored and the difficulty to compete with many popular commercial apps on young people's smartphones may be responsible for a decrease in the engagement. A stand-alone app does not seem sufficient to promote an active lifestyle among lower educated working young adults; therefore, multicomponent interventions (using both technological and human support), as well as context-specific sensing to provide tailored advice, might be needed in this population. TRIAL REGISTRATION: ClinicalTrials.gov NCT02948803; https://clinicaltrials.gov/ct2/show/results/NCT02948803 (Archived by WebCite at http://www.webcitation.org/71OPFwaoA).
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".