Effectiveness and Feasibility of a Self-guided Mobile App Targeting Emotional Well-being in Healthy Adults: 4-Week Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Commercial smartphone apps designed to promote emotional well-being are becoming increasingly popular, but few apps have been empirically validated. OBJECTIVE: This study examined the feasibility and effectiveness of a self-guided app designed to reduce daily stress via positive messaging and tailored short inspirational talks (ie, peps). METHODS: A total of 166 participants (n=112, 67.5% female; mean age 38.48, SD 6.73 years) were recruited through social media advertising and randomized into an intervention (Hey Lemonade app plus twice daily mood monitoring using the Multidimensional Mood Questionnaire [MDMQ]) or active control (twice daily mood monitoring [MDMQ]) group. Primary (coping self-efficacy [CSE]; 3 subscales) and secondary outcomes (vitality, satisfaction with life, perceived stress, positive and negative affect, and hassles and uplifts) were measured at the baseline (week 1) and end point (week 4). The app evaluation questions were assessed at week 2. All interactions and measurements were collected on the internet and through the apps. RESULTS: In total, of 166 participants, 125 (75.3%) completed the trial. There were no differences in dropout rates between the groups (62/81, 76% intervention; 63/85, 74% control). There were significant group-by-time interactions for vitality and hassles but no significant effect for CSE total (P=.05). For the intervention group, the change from baseline to week 4 was significant for vitality (P=.002) and hassles (P=.004), CSE total (P=.008), and CSE Emotional subscale (P=.02). For the control group, any changes over 4 weeks were not significant for any outcome. There was a significant group-by-time interaction for MDMQ calmness (P=.04). By week 4, calmness was significantly higher in the intervention group (P=.046). Of those in the intervention group at week 2 (n=68), 39 (57%) participants recommended the app and 41 (60%) participants wanted to continue using it. Pep talks and customizable voice options were the most popular features. CONCLUSIONS: Participants who had access to the smartphone app on an as-needed basis over the 4-week trial showed significant improvements in emotional well-being indicators. More broadly, this suggests that simple accessible solutions may generate meaningful well-being outcomes. Whether these changes are sustained and can be generalized to other population groups is yet to be determined. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry (ANZCTR) 12622001005741; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384304&isReview=true.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".