StandUPTV: Preparation and optimization phases of a mHealth intervention to reduce sedentary screen time in adults.

Recreational sedentary screen time (rSST) is the most prevalent sedentary behavior for adults outside of work, school, and sleep, and is strongly linked to poor health. StandUPTV is a mHealth trial that uses the Multiphase Optimization Strategy (MOST) framework to develop and evaluate the efficacy of three theory-based strategies for reducing rSST among adults. This paper describes the preparation and optimization phases of StandUPTV within the MOST framework. We identified three candidate components based on previous literature: (a) rSST electronic lockout (LOCKOUT), which restricts rSST through electronic means; (b) adaptive prompts (TEXT), which provides adaptive prompts based on rSST behaviors; and (c) earning rSST through increased moderate-vigorous physical activity (MVPA) participation (EARN). We also describe the mHealth iterative design process and the selection of an optimization objective. Finally, we describe the protocol of the optimization randomized controlled trial using a 23 factorial experimental design. We will enroll 240 individuals aged 23-64 y who engage in >3 h/day of rSST. All participants will receive a target to reduce rSST by 50% and be randomized to one of 8 combinations representing all components and component levels: LOCKOUT (yes vs. no), TEXT (yes vs. no), and EARN (yes vs. no). Results will support the selection of the components for the intervention package that meet the optimization objective and are acceptable to participants. The optimized intervention will be tested in a future evaluation randomized trial to examine reductions in rSST on health outcomes among adults.

Assessing the Pragmatic Nature of Mobile Health Interventions Promoting Physical Activity: Systematic Review and Meta-analysis.

BACKGROUND: Mobile health (mHealth) apps can promote physical activity; however, the pragmatic nature (ie, how well research translates into real-world settings) of these studies is unknown. The impact of study design choices, for example, intervention duration, on intervention effect sizes is also understudied. OBJECTIVE: This review and meta-analysis aims to describe the pragmatic nature of recent mHealth interventions for promoting physical activity and examine the associations between study effect size and pragmatic study design choices. METHODS: The PubMed, Scopus, Web of Science, and PsycINFO databases were searched until April 2020. Studies were eligible if they incorporated apps as the primary intervention, were conducted in health promotion or preventive care settings, included a device-based physical activity outcome, and used randomized study designs. Studies were assessed using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) and Pragmatic-Explanatory Continuum Indicator Summary-2 (PRECIS-2) frameworks. Study effect sizes were summarized using random effect models, and meta-regression was used to examine treatment effect heterogeneity by study characteristics. RESULTS: Overall, 3555 participants were included across 22 interventions, with sample sizes ranging from 27 to 833 (mean 161.6, SD 193.9, median 93) participants. The study populations' mean age ranged from 10.6 to 61.5 (mean 39.6, SD 6.5) years, and the proportion of males included across all studies was 42.8% (1521/3555). Additionally, intervention lengths varied from 2 weeks to 6 months (mean 60.9, SD 34.9 days). The primary app- or device-based physical activity outcome differed among interventions: most interventions (17/22, 77%) used activity monitors or fitness trackers, whereas the rest (5/22, 23%) used app-based accelerometry measures. Data reporting across the RE-AIM framework was low (5.64/31, 18%) and varied within specific dimensions (Reach=44%; Effectiveness=52%; Adoption=3%; Implementation=10%; Maintenance=12.4%). PRECIS-2 results indicated that most study designs (14/22, 63%) were equally explanatory and pragmatic, with an overall PRECIS-2 score across all interventions of 2.93/5 (SD 0.54). The most pragmatic dimension was flexibility (adherence), with an average score of 3.73 (SD 0.92), whereas follow-up, organization, and flexibility (delivery) appeared more explanatory with means of 2.18 (SD 0.75), 2.36 (SD 1.07), and 2.41 (SD 0.72), respectively. An overall positive treatment effect was observed (Cohen d=0.29, 95% CI 0.13-0.46). Meta-regression analyses revealed that more pragmatic studies (-0.81, 95% CI -1.36 to -0.25) were associated with smaller increases in physical activity. Treatment effect sizes were homogenous across study duration, participants' age and gender, and RE-AIM scores. CONCLUSIONS: App-based mHealth physical activity studies continue to underreport several key study characteristics and have limited pragmatic use and generalizability. In addition, more pragmatic interventions observe smaller treatment effects, whereas study duration appears to be unrelated to the effect size. Future app-based studies should more comprehensively report real-world applicability, and more pragmatic approaches are needed for maximal population health impacts. TRIAL REGISTRATION: PROSPERO CRD42020169102; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=169102.