# StandUPTV: A full-factorial optimization trial to reduce sedentary screen time among adults

## TL;DR

This study tested a mobile app with different features to reduce daily screen time by over an hour, finding that combining lockout, prompts, and rewards worked best.

## Contribution

The study introduces a full-factorial mHealth intervention design to optimize screen time reduction strategies using the MOST framework.

## Key findings

- The intervention version with all components active reduced rSST by 125.7 minutes/day.
- Participants found the app helpful, with over 94% satisfaction reported.
- Technical issues caused some dissatisfaction, but the core intervention was feasible and acceptable.

## Abstract

Using the multiphase optimization strategy (MOST) framework, we aimed to identify a feasible, acceptable and optimized set of mHealth-delivered behavioral strategies for reducing recreational sedentary screen time (rSST) by at least 60 min/day.

Eligible participants were 23–64 years old and had high rSST (> 3 h/day). We used a full factorial (23) design in which participants received a “core” mHealth application and were randomized to combinations of three components (on vs. off): LOCKOUT: rSST electronically restricted; TEXT: rSST reduction prompts; and EARN: rSST through physical activity. rSST was assessed at baseline and at 8 and 16 weeks of age via an integrated measure of sedentary time and screen time. We used a linear mixed effect model to test the change in rSST for the three intervention components and their interactions.

A total of 82% of the randomized participants (N = 110) were female, with a mean ± SD age of 41 ± 11.7 y and a BMI of 29.7 ± 7.8 kg/m2, and their mean (95% CI) rSST was 184.7 (172.8, 196.5) min/day at baseline. The expected difference (baseline vs 16 weeks) in rSST was greatest for the intervention versions with a core, LOCKOUT, TEXT, & EARN (−125.7 [−172.0, −79.3] min/day) at the “on” level. The participants were satisfied with the study and found the app helpful in reducing rSST (> 94%). Technical issues resulted in 20% being somewhat dissatisfied with the app.

We identified several promising intervention versions that exceeded our optimization objective. The intervention version that included core, LOCKOUT, TEXT, & EARN components “on” was efficacious, feasible and acceptable and should be used to test the effect of rSST reductions on health outcomes.

(clinicaltrials.gov
NCT04464993)