Investigating intervention components and exploring states of receptivity for a smartphone app to promote physical activity: Protocol of a microrandomized trial

Kramer, Jan-Niklas; Künzler, Florian; Mishra, Varun; Presset, Bastien; Kotz, David; Smith, Shawna; Scholz, Urte; Kowatsch, Tobias

doi:10.2196/11540

Cited by 74Mobile Health and mHealth ApplicationsDigital Mental Health InterventionsPhysical Activity and Health

Investigating intervention components and exploring states of receptivity for a smartphone app to promote physical activity: Protocol of a microrandomized trial

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Kramer, Jan-Niklas, Künzler, Florian, Mishra, Varun, Presset, Bastien, Kotz, David, Smith, Shawna, Scholz, Urte, Kowatsch, Tobias·2019·JMIR Research Protocols

DOI 10.2196/11540PMC PMC6374735

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Abstract

BACKGROUND: Smartphones enable the implementation of just-in-time adaptive interventions (JITAIs) that tailor the delivery of health interventions over time to user- and time-varying context characteristics. Ideally, JITAIs include effective intervention components, and delivery tailoring is based on effective moderators of intervention effects. Using machine learning techniques to infer each user's context from smartphone sensor data is a promising approach to further enhance tailoring. OBJECTIVE: The primary objective of this study is to quantify main effects, interactions, and moderators of 3 intervention components of a smartphone-based intervention for physical activity. The secondary objective is the exploration of participants' states of receptivity, that is, situations in which participants are more likely to react to intervention notifications through collection of smartphone sensor data. METHODS: In 2017, we developed the Assistant to Lift your Level of activitY (Ally), a chatbot-based mobile health intervention for increasing physical activity that utilizes incentives, planning, and self-monitoring prompts to help participants meet personalized step goals. We used a microrandomized trial design to meet the study objectives. Insurees of a large Swiss insurance company were invited to use the Ally app over a 12-day baseline and a 6-week intervention period. Upon enrollment, participants were randomly allocated to either a financial incentive, a charity incentive, or a no incentive condition. Over the course of the intervention period, participants were repeatedly randomized on a daily basis to either receive prompts that support self-monitoring or not and on a weekly basis to receive 1 of 2 planning interventions or no planning. Participants completed a Web-based questionnaire at baseline and postintervention follow-up. RESULTS: Data collection was completed in January 2018. In total, 274 insurees (mean age 41.73 years; 57.7% [158/274] female) enrolled in the study and installed the Ally app on their smartphones. Main reasons for declining participation were having an incompatible smartphone (37/191, 19.4%) and collection of sensor data (35/191, 18.3%). Step data are available for 227 (82.8%, 227/274) participants, and smartphone sensor data are available for 247 (90.1%, 247/274) participants. CONCLUSIONS: This study describes the evidence-based development of a JITAI for increasing physical activity. If components prove to be efficacious, they will be included in a revised version of the app that offers scalable promotion of physical activity at low cost. TRIAL REGISTRATION: ClinicalTrials.gov NCT03384550; https://clinicaltrials.gov/ct2/show/NCT03384550 (Archived by WebCite at http://www.webcitation.org/74IgCiK3d). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11540.

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All analyses were prespecified.
“All analyses were prespecified (21).”
From Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results From an Optimization Trial (2020) · cites this paper as [21]
Previous studies in other health domains have demonstrated promising results in using conversational agents to improve outcomes, such as promoting physical activity for childhood obesity.
“Previous studies in other health domains have demonstrated promising results in using conversational agents to improve outcomes, such as promoting physical activity for childhood obesity [104,114].”
From Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study (2021) · cites this paper as [114]

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Investigating Intervention Components and Exploring States of \nReceptivity for a Smartphone App to Promote Physical Activity: \nProtocol of a Microrandomized Trial
Kramer, J.-N., Künzler, F., Mishra, V., Presset, B., Kotz, D., Smith, S. N., Scholz, U., & Kowatsch, T. (2019) · Alexandria (UniSG) (University of St.Gallen)
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Authors: Kramer, J.-N., Künzler, F., Mishra, V., Presset, B., Kotz, D., Smith, S., Scholz, U., & Kowatsch, T.
Affiliations: University of St.Gallen (CH)
ETH Zurich (CH)
Dartmouth College (US)
University of Lausanne (CH)
University of Michigan (US)
University of Zurich (CH)
Corresponding author: Kramer, Jan-Niklas
ORCID: Kramer, Jan-Niklas
Künzler, Florian
Mishra, Varun
Presset, Bastien
Kotz, David
Smith, Shawna
Scholz, Urte
Kowatsch, Tobias
Venue: JMIR Research Protocols
Publisher: JMIR Publications Inc.
Published: 2019-01-31
Volume: 8
Issue: 1
Pages: e11540
ISSN: 1929-0748 (ISSN-L)
DOI: 10.2196/11540
PMC: PMC6374735
OpenAlex: W2898978558
Cited by: 74
References: 69
Citations by year: 2026: 6 · 2025: 7 · 2024: 8 · 2023: 3 · 2022: 10 · 2021: 13 · 2020: 17 · 2019: 10
FWCI: 15.27
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
Locations: JMIR Research Protocols (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, cc-by-nc)
Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by-nc)
ETH Zürich Research Collection (cc-by)
Zurich Open Repository and Archive (University of Zurich)
Topics: Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Health Sciences › Medicine › Physiology › Physical Activity and Health
Keywords: physical activity promotion, just-in-time adaptive interventions, smartphone-based intervention, chatbots, mobile health, financial incentives, planning, step goals, smartphone sensor data, intervention moderators, insurance company employees, health behavior change

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Investigating intervention components and exploring states of receptivity for a smartphone app to promote physical activity: Protocol of a microrandomized trial

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