Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Long-term usage of a commercial mHealth app

A “multiple-lives” perspective

Bibliographic Data

ID22066690
AuthorsErica Y Lau (0000-0003-4156-6038, University of British Columbia, corresponding author), Marc Mitchell (0000-0002-2772-9614, Western University), Marc S Mitchell, G Faulkner (0000-0001-8898-2536, University of British Columbia)
Year2022
Volume10
Pages914433-914433
Publication date2022-11-10
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2022.914433
PMID36438245
OpenAlexW4308873845
LanguageEN
Citations received1
References cited48

Background: Emerging evidence suggests that individuals use mHealth apps in multiple disjointed ways in the real-world-individuals, for example, may engage, take breaks, and re-engage with these apps. To our knowledge, very few studies have adopted this 'multiple-live' perspective to analyze long-term usage of a physical activity (PA) app. This study aimed to examine the duration of use, as well as the frequency, length, and timing of streaks (uninterrupted periods of use) and breaks (uninterrupted periods of non-use) within a popular commercial PA app called Carrot Rewards over 12 months. We also examined sociodemographic correlates of usage. Method: This retrospective observational study analyzed data from 41,207 Carrot Rewards users participating in the "Steps" walking program from June/July 2016 to June/July 2017. We measured four usage indicators: duration of use, frequency and length of streaks and breaks, time to first break, and time to resume second streak. We also extracted information regarding participants' age, gender, province, and proxy indicators of socioeconomic status derived from census data. We used descriptive statistics to summarize usage patterns, Kaplan-Meier curves to illustrate the time to first break and time to resume second streak. We used linear regressions and Cox Proportional Hazard regression models to examine sociodemographic correlates of usage. Results: Over 60% of the participants used Carrot Rewards for ≥6 months and 29% used it for 12 months (mean = 32.59 ± 18.435 weeks). The frequency of streaks and breaks ranged from 1 to 9 (mean = 1.61 ± 1.04 times). The mean streak and break length were 20.22 ± 18.26 and 16.14 ± 15.74 weeks, respectively. The median time to first break was 18 weeks across gender groups and provinces; the median time for participants to resume the second streak was between 12 and 32 weeks. Being female, older, and living in a community with greater post-secondary education levels were associated with increased usage. Conclusion: This study provides empirical evidence that long-term mHealth app usage is possible. In this context, it was common for users to take breaks and re-engage with Carrot Rewards. When designing and evaluating PA apps, therefore, interventionists should consider the 'multiple-lives' perspective described here, as well as the impact of gender and age

Census · Descriptive statistics · mHealth · Observational study · Population · Proportional hazards model · Psychological intervention · Socioeconomic status · Statistics · Computer Science · Demography · Digital Mental Health Interventions · Mathematics · Mobile Health and mHealth Applications · Physical Activity and Health · Psychology · Artificial Intelligence

  • Modeling the path to digital health intention

    Open Access•Bo Pu, Bowen Pu et al.•Frontiers in Public Health•2025

  • The Law of Attrition

    Open Access•Gunther Eysenbach•Journal of Medical Internet…•2005

  • Conceptualising engagement with digital behaviour change interventions

    Open Access•Olga Perski, Ann Blandford et al.•Translational Behavioral Medicine•2017

  • Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care

    Open Access•Susan Michie, Liz Yardley et al.•Journal of Medical Internet…•2017

  • Health App Use Among US Mobile Phone Owners

    Open Access•Paul Krebs, Dustin T Duncan•JMIR mHealth and uHealth•2015

  • Canadian 24-Hour Movement Guidelines for Adults aged 18–64 years and Adults aged 65 years or older

    Open Access•ROBERT ROSS, Jean‐philippe Chaput et al.•Applied Physiology, Nutrition,…•2020

  • Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour

    Open Access•Stephanie Schoeppe, Stephanie Alley et al.•International Journal of…•2016

  • Long-term health benefits of physical activity – a systematic review of longitudinal studies

    Open Access•Miriam Reiner, Christina Niermann et al.•BMC Public Health•2013

  • Worldwide trends in insufficient physical activity from 2001 to 2016

    Open Access•Regina Guthold, G A Stevens et al.•The Lancet Global Health•2018

  • An Evaluation of a Commercialized mHealth Intervention to Promote Physical Activity in the Workplace

    Open Access•Katie M Di Sebastiano, Erica Y Lau et al.•Frontiers in Public Health•2022

  • Abandonment of personal quantification

    Open Access•Christiane Attig, Thomas Franke•Computers in Human Behavior•2020

  • Differences in mobile health app use

    Nadine Bol, Natali Helberger et al.•The Information Society•2018

  • Socio-demographic determinants of physical activity and app usage from smartphone data

    Open Access•Francesca Pontin, Nik Lomax et al.•Social Science & Medicine•2021

Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae