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Published Online: 16 April 2020

Tailored Daily Activity: An Adaptive Physical Activity Smartphone Intervention

Publication: Telemedicine and e-Health
Volume 26, Issue Number 4


Background: Nontailored and static goals may hinder behavior change. We investigated the feasibility and acceptability of an adaptive proof-of-concept smartphone-delivered intervention by using real-world movement data capture of physical activity (PA) and sedentary behavior (SB) to inform behavior change content delivery.
Materials and Methods: A single-group 8-week study with pre- and post-intervention assessments was conducted in Auckland, New Zealand. Participants aged 17–69 years who owned an Android smartphone were recruited and used the application (app). Usage data, self-reported acceptability and PA and SB were assessed. Daily repeated measurement of PA and SB outcomes were analyzed through random-effects mixed models.
Results: Participants (n = 69) were predominantly female (78%) with a mean age of 34.5 years (range 18–61). On average, participants opened the app on 11.4 days throughout the 8 weeks. Use decreased over time; 20% of participants opened the app every day. Feedback on behavior (73%), behavior substitution (71%), discrepancy between behavior and goal (58%) and goal setting (54%) were rated as the most useful behavior change techniques by participants. Time spent on light, moderate-to-vigorous intensity and total PA increased post-intervention, whereas time spent on SB decreased.
Conclusions: The adaptive proof-of-concept app was considered acceptable, with preliminary support for its positive effects on PA and SB.

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Information & Authors


Published In

cover image Telemedicine and e-Health
Telemedicine and e-Health
Volume 26Issue Number 4April 2020
Pages: 426 - 437
PubMed: 31063038


Published online: 16 April 2020
Published in print: April 2020
Published ahead of print: 7 May 2019
Accepted: 11 March 2019
Revision received: 10 March 2019
Received: 10 February 2019


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Artur Direito [email protected]
National Institute for Health Innovation, University of Auckland, Auckland, New Zealand.
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Mark Tooley
National Institute for Health Innovation, University of Auckland, Auckland, New Zealand.
Moohamad Hinbarji
The Insight Centre for Data Analytics, Dublin City University, Dublin, Ireland.
Rami Albatal
The Insight Centre for Data Analytics, Dublin City University, Dublin, Ireland.
Yannan Jiang
National Institute for Health Innovation, University of Auckland, Auckland, New Zealand.
Robyn Whittaker
National Institute for Health Innovation, University of Auckland, Auckland, New Zealand.
Ralph Maddison
National Institute for Health Innovation, University of Auckland, Auckland, New Zealand.
Institute for Physical Activity and Nutrition, Deakin University, Melbourne, Australia.


Address correspondence to: Artur Direito, National Institute for Health Innovation, School of Population Health, The University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland 1142, New Zealand [email protected]

Disclosure Statement

All authors declare that no competing financial interests exist. All authors declare that they have no conflict of interest.

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