MoveMentor-examining the effectiveness of a machine learning and app-based digital assistant to increase physical activity in adults: protocol for a randomised controlled trial.

Journal: Trials
Published Date: Jul 1, 2025

Abstract

BACKGROUND: Physical inactivity is prevalent, leading to a high burden of disease and large healthcare costs. Thus, there is a need for affordable, effective and scalable interventions. However, interventions that are affordable and scalable are beset with modest effects and engagement. Interventions that integrate machine learning with real-time data to offer unprecedented levels of personalisation and customisation might offer solutions. The aim of this study is to conduct a randomised controlled trial to evaluate the effectiveness of a machine learning and app-based digital assistant to increase physical activity.

Authors

  • Corneel Vandelanotte
    Central Queensl and University, School of Health, Medical and Applied Sciences, Appleton Institute, Physical Activity Research Group, Rockhampton, QLD 4702, Australia.
  • Stewart Trost
    Institute of Health and Biomedical Innovation at QLD Centre for Children's Health Research, School of Exercise and Nutrition Sciences, Queensland University of Technology, 62 Graham St, South Brisbane, QLD, 4101, Australia. s.trost@qut.edu.au.
  • Danya Hodgetts
    Appleton Institute, Central Queensland University, Rockhampton, Queensland, Australia.
  • Tasadduq Imam
    School of Business and Law, CQUniversity, Melbourne Campus, Melbourne, VIC 3000, Australia.
  • M D Mamunur Rashid
    School of Engineering and Technology, Central Queensland University, 120 Spencer Street, Melbourne, VIC, 3000, Australia.
  • Quyen G To
    Appleton Institute, Central Queensland University, Bruce Highway, Rockhampton, QLD, 4702, Australia.
  • Carol Maher
    Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia.

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