The LvL UP trial: Protocol for a sequential, multiple assignment, randomised controlled trial to assess the effectiveness of a blended mobile lifestyle intervention.

BACKGROUND: Blended mobile health (mHealth) interventions - combining self-guided and human support components - could play a major role in preventing non-communicable diseases (NCDs) and common mental disorders (CMDs). This protocol describes a sequential, multiple assignment, randomised trial aimed at (i) evaluating the effectiveness and cost-effectiveness of LvL UP, an mHealth lifestyle intervention for the prevention of NCDs and CMDs, and (ii) establishing the optimal blended approach in LvL UP that balances effective personalised lifestyle support with scalability. METHODS: LvL UP is a 6-month mHealth holistic intervention targeting physical activity, diet, and emotional regulation. In this trial, young and middle-aged Singaporean adults at risk of developing NCDs or CMDs will be randomly allocated to one of two initial conditions ('LvL UP' or 'comparison'). After 4 weeks, participants categorised as non-responders from the LvL UP group will be re-randomised into second-stage conditions: (i) continuing with the initial intervention (LvL UP) or (ii) additional motivational interviewing (MI) support sessions by trained health coaches (LvL UP + adaptive MI). The primary outcome is mental well-being. Secondary outcomes include anthropometric measurements, resting blood pressure, blood metabolic profile, health status, and health behaviours (physical activity, diet). Outcomes will be measured at baseline, 6 months (post-intervention), and 12 months (follow-up). DISCUSSION: In addition to evaluating the effectiveness of LvL UP, the proposed study design will contribute to increasing evidence on how to introduce human support in mHealth interventions to maximise their effectiveness while remaining scalable. TRIAL REGISTRATION: The LvL UP Pilot trial was prospectively registered with ClinicalTrials.gov (NCT06360029).

Duke Scholars

Author Bibhas Chakraborty Biostatistics & Bioinformatics, Division of Biostatistics