Effectiveness of Smartphone-Based Dyadic Interventions to Increase Physical Activity in Romantic Couples: Microrandomized Trial
Bibliographic record
Abstract
BACKGROUND: Social exchange processes, such as social support and social control, can promote health behavior change. However, these processes are often neglected when studying health behavior change and designing interventions. Intervening on these social exchange processes using dyadic interventions may provide a promising approach to promote health behaviors. OBJECTIVE: This study aimed to investigate the effects of dyadic interventions to increase moderate-to-vigorous physical activity (MVPA) in romantic couples. Furthermore, we explored how the target, type, and timing of the interventions affect their effectiveness. METHODS: In total, 38 romantic couples (mean age 34.01, SD 11.03 y) were recruited through online advertisements and participated in a smartphone-based microrandomized trial over 55 days consisting of control and intervention phases. The fully automated dyadic interventions included a one-time psychoeducation intervention, weekly dyadic and collaborative planning, and dyadic just-in-time adaptive interventions (JITAIs). MVPA was measured through daily diaries and wrist-worn accelerometers. We used multilevel modeling to estimate the effect of the intervention phase and weighted and centered estimation for microrandomized trials to estimate the treatment effects of dyadic and collaborative planning, as well as the dyadic JITAIs. RESULTS: =2.13; P=.01) MVPA during the intervention phase compared with the control phase. Dyadic and collaborative planning did not increase device-based (b=6.31, SE=5.18; P=.12) but only self-reported (b=14.25, SE=5.16; P=.005) MVPA. However, the effects of the 2 kinds of planning on self-reported MVPA disappeared when additional covariates were included (b=0.14, SE=3.32; P=.48). Furthermore, the dyadic JITAIs targeting both the actor and the partner increased device-based (actor: b=11.17, SE=3.18; P<.001; partner: b=7.23, SE=3.60; P=.03) and self-reported (actor: b=17.34, SE=3.65; P<.001; partner: b=11.82, SE=4.10; P<.001) MVPA. However, the effects of the dyadic JITAIs targeting the actor disappeared for self-reported MVPA (b=2.20, SE=3.22; P=0.25) when additional covariates were included. Exploratory analyses revealed that different types and timings of dyadic JITAIs were differentially effective. CONCLUSIONS: This study demonstrated the promising effects of dyadic interventions to promote MVPA and highlighted the importance of the target, type, and timing of the interventions. Further research should investigate the mechanisms underlying the effects of dyadic interventions on health behaviors. TRIAL REGISTRATION: ISRCTN registry ISRCTN15673058; https://www.isrctn.com/ISRCTN15673058.
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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) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".