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Cited by 38Mobile Health and mHealth ApplicationsInnovative Human-Technology InteractionDigital Mental Health Interventions

The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining

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Sporrel, Karlijn, De Boer, Rémi D. D., Wang, Shihan, Nibbeling, Nicky, Simons, Monique, Deutekom, Marije, Ettema, Dick, Castro, Paula C. +2 more·2021·Frontiers in Public Health
DOI 10.3389/fpubh.2020.528472PMC PMC7884923
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Abstract

Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for developing personalized apps. In this paper, we describe the design and development of the Playful data-driven Active Urban Living (PAUL): a personalized PA application. Methods: The two-phased development process of the PAUL apps rests on principles from the behavior change model; the Integrate, Design, Assess, and Share (IDEAS) framework; and the behavioral intervention technology (BIT) model. During the first phase, we explored whether location-specific information on performing PA in the built environment is an enhancement to a PA app. During the second phase, the other modules of the app were developed. To this end, we first build the theoretical foundation for the PAUL intervention by performing a literature study. Next, a focus group study was performed to translate the theoretical foundations and the needs and wishes in a set of user requirements. Since the participants indicated the need for reminders at a for-them-relevant moment, we developed a self-learning module for the timing of the reminders. To initialize this module, a data-mining study was performed with historical running data to determine good situations for running. Results: The results of these studies informed the design of a personalized mobile health (mHealth) application for running, walking, and performing strength exercises. The app is implemented as a set of modules based on the persuasive strategies “monitoring of behavior,” “feedback,” “goal setting,” “reminders,” “rewards,” and “providing instruction.” An architecture was set up consisting of a smartphone app for the user, a back-end server for storage and adaptivity, and a research portal to provide access to the research team. Conclusions: The interdisciplinary research encompassing psychology, human movement sciences, computer science, and artificial intelligence has led to a theoretically and empirically driven leisure time PA application. In the current phase, the feasibility of the PAUL app is being assessed.

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Authors
Sporrel, K., De Boer, R. D. D., Wang, S., Nibbeling, N., Simons, M., Deutekom, M., Ettema, D., Castro, P. C., Dourado, V. Z., & Kröse, B.
Affiliations
  • Utrecht University (NL)
  • Amsterdam University of Applied Sciences (NL)
  • Wageningen University & Research (NL)
  • Inholland University of Applied Sciences (NL)
  • Universidade Federal de São Carlos (BR)
  • Universidade Federal de São Paulo (BR)
Corresponding author
Sporrel, Karlijn
ORCID
Venue
Frontiers in Public Health
Publisher
Frontiers Media SA
Published
2021-02-02
Volume
8
Pages
528472-528472
ISSN
2296-2565 (ISSN-L)
DOI
10.3389/fpubh.2020.528472
PMC
PMC7884923
OpenAlex
W3127451197
Cited by
38
References
58
Citations by year
2026: 4 · 2025: 5 · 2024: 8 · 2023: 7 · 2022: 9 · 2021: 5
FWCI
8.14
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Public Health (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
Funders
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek
  • Nationaal Regieorgaan Praktijkgericht Onderzoek SIA
  • Fundação de Amparo à Pesquisa do Estado de São Paulo
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Keywords
physical activity apps, behaviour change theory, IDEAS framework, persuasion techniques, goal setting, feedback, reward, leisure-time physical activity, resistance training, user requirements
MeSH terms
Adult, Artificial Intelligence, Humans, Leisure Activities, Perception, Exercise, Data Mining

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