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The effect of digital physical activity interventions on daily step count: a randomised controlled crossover substudy of the MyHeart Counts Cardiovascular Health Study
Open accessAbstract
BACKGROUND: Smartphone apps might enable interventions to increase physical activity, but few randomised trials testing this hypothesis have been done. The MyHeart Counts Cardiovascular Health Study is a longitudinal smartphone-based study with the aim of elucidating the determinants of cardiovascular health. We aimed to investigate the effect of four different physical activity coaching interventions on daily step count in a substudy of the MyHeart Counts Study. METHODS: In this randomised, controlled crossover trial, we recruited adults (aged ≥18 years) in the USA with access to an iPhone smartphone (Apple, Cupertino, CA, USA; version 5S or newer) who had downloaded the MyHeart Counts app (version 2.0). After completion of a 1 week baseline period of interaction with the MyHeart Counts app, participants were randomly assigned to receive one of 24 permutations (four combinations of four 7 day interventions) in a crossover design using a random number generator built into the app. Interventions consisted of either daily prompts to complete 10 000 steps, hourly prompts to stand following 1 h of sitting, instructions to read the guidelines from the American Heart Association website, or e-coaching based upon the individual's personal activity patterns from the baseline week of data collection. Participants completed the trial in a free-living setting. Due to the nature of the interventions, participants could not be masked from the intervention. Investigators were not masked to intervention allocation. The primary outcome was change in mean daily step count from baseline for each of the four interventions, assessed in the modified intention-to-treat analysis set, which included all participants who had completed 7 days of baseline monitoring and at least 1 day of one of the four interventions. This trial is registered with ClinicalTrials.gov, NCT03090321. FINDINGS: Between Dec 12, 2016, and June 6, 2018, 2783 participants consented to enrol in the coaching study, of whom 1075 completed 7 days of baseline monitoring and at least 1 day of one of the four interventions and thus were included in the modified intention-to-treat analysis set. 493 individuals completed the full set of assigned interventions. All four interventions significantly increased mean daily step count from baseline (mean daily step count 2914 [SE 74]): mean step count increased by 319 steps (75) for participants in the American Heart Association website prompt group (p<0·0001), 267 steps (74) for participants in the hourly stand prompt group (p=0·0003), 254 steps (74) for participants in the cluster-specific prompts group (p=0·0006), and by 226 steps (75) for participants in the 10 000 daily step prompt group (p=0·0026 vs baseline). INTERPRETATION: Four smartphone-based physical activity coaching interventions significantly increased daily physical activity. These findings suggests that digital interventions delivered via a mobile app have the ability to increase short-term physical activity levels in a free-living cohort. FUNDING: Stanford Data Science Initiative.
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A considerable proportion of participants stopped using the app over the 8-week study, although attrition appeared somewhat lower compared to similar studies of mHealth apps.
“In addition, a considerable proportion of participants stopped using the app over the course of the 8 week study, although attrition appeared to be somewhat lower compared to similar studies of mHealth apps (42, 44).”
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 [42]
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Salman, D., Feuvre, P. A. L., Hill, O., Conway, D., Taylor, S., Turner, S., Korgaonkar, J., Hettiaratchy, S. P., & McGregor, A. H. (2023) · BMJ Open Sport & Exercise Medicine · doi:10.1136/bmjsem-2023-001557 · Cited by 2
Artificial Intelligence Based Diagnosis of Parkinson’s Disorders
Kamini, Rani, S., & Bashir, A. K. (2023) · Cognitive technologies · doi:10.1007/978-981-99-2154-6_13 · Cited by 2
Wang, J., Fang, Y., Frank, E., Walton, M. A., Burmeister, M., Tewari, A., Dempsey, W., NeCamp, T., Sen, S., & Wu, Z. (2022) · medRxiv · doi:10.1101/2022.03.11.22272278 · Cited by 2
Martin, J. M., Errington, N., Schütz, N., Johnson, A., Kim, D. S., Gupta, V., Hershman, S. G., Toshner, M. R., Wilkins, M. R., Kiely, D. G., et al. (2025) · medRxiv · doi:10.1101/2025.04.08.25325466 · Cited by 2
Koemel, N. A., Bissett, M., Ryde, G. C., Ahmadi, M. N., Atsiaris, K., Chen, I., Teixeira-Pinto, A. M., Liu, S., Maher, C. A., Chong, K. H., et al. (2025) · medRxiv · doi:10.1101/2025.10.28.25339013 · Cited by 2
Spiers, G., McDermott, J., Johnson, E. E., Kunonga, P., & Hanratty, B. (2025) · Journal of Health Equity · doi:10.1080/29944694.2025.2530969 · Cited by 1
Wakai, N., Yamada, T., Tomoyama, H., & Iida, S. (2025) · The Journal of Frailty & Aging · doi:10.1016/j.tjfa.2025.100059 · Cited by 1
ILSE bewegt? Eine IKT-gestützte Bewegungsintervention für 60+
Ring‐Dimitriou, S., & Pühringer, M. (2022) · Springer eBooks · doi:10.1007/978-3-658-34970-7_8 · Cited by 1
Javed, A., Kim, D. S., Hershman, S. G., Shcherbina, A., Johnson, A., Tolas, A., O’Sullivan, J. W., McConnell, M. V., Lazzeroni, L. C., King, A. C., et al. (2023) · medRxiv · doi:10.1101/2023.04.09.23287650 · Cited by 1
Kim, D. S., Schütz, N., Johnson, A., Tolas, A., Mantena, S., O’Sullivan, J. W., Hershman, S. G., King, A. C., Christle, J. W., Oppezzo, M., et al. (2024) · medRxiv · doi:10.1101/2024.06.26.24309535 · Cited by 2
Bissett, M., Koemel, N. A., Ahmadi, M. N., Atsiaris, K., Liu, S., Thøgersen‐Ntoumani, C., Gray, C. M., Gill, J. M. R., Stamatakis, E. A., & Ryde, G. C. (2025) · medRxiv · doi:10.1101/2025.10.29.25339035 · Cited by 1
Diverse research designs are needed for population health: Lessons from Maslow
Schmitt‐Egenolf, M., & Birrell, F. N. (2022) · Lifestyle Medicine · doi:10.1002/lim2.55
Sin, D. D. (2020) · European Respiratory Society eBooks · doi:10.1183/2312508x.10029019
Dimitriou, M. (2022) · Springer eBooks · doi:10.1007/978-3-658-34970-7_3
Effects of Diabetes Quality Assessment on Diabetes Management Behaviors Based on a Nationwide Survey
Choi, C. K., Yang, J.-H., Jeong, J.-A., & Shin, M. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192315781
Heffron, S. P., O’Neill, K., Zhong, J., Xia, Y., & McCarthy, M. M. (2025) · American Journal of Health Promotion · doi:10.1177/08901171251324018
Bondaronek, P., Slee, A. E., & Hamilton, F. L. (2025) · Qeios · doi:10.32388/pgu6li
Takeji, Y., Nomura, A., Tada, H., Usui, S., Sakata, K., Tabuchi, T., & Takamura, M. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.124.040402
Mistiri, M. E., Torre, S. A. D. L., Marlin, B. M., Misha Pavel, C., Klasnja, P., Spruijt‐Metz, D., & Rivera, D. E. (2025) · Control Engineering Practice · doi:10.1016/j.conengprac.2025.106460
Pai, S. G. S., Tan, K. Z., Bao, H., Pham, B. T. P., Theng, Y. L., Lee, E. W. J., & Singh, N. B. (2025) · medRxiv · doi:10.1101/2025.08.12.25332025
Houwen, J., Janssen, V. R., Hondmann, S. M., Chavannes, N. H., Kleinsmann, M. S., Atsma, D. E., & Pannunzio, V. (2025) · doi:10.2196/preprints.83055
Serra, M., Alceste, D., Jucker, N., Haupt, L., Elben, S., Müller, S., Hulshof, P. J. M., Meijer, H. A. J., Thalheimer, A., Steinert, R. E., et al. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5646777
Ye, Z., Rudd, J. R., Chow, J. Y., Sit, C. H. P., Leung, S. K. Y., Choi, S. M., Li, M., & Sum, R. K. W. (2025) · BMC Public Health · doi:10.1186/s12889-025-25753-y
LIFETRACE: A Longitudinal Multimodal Dataset on Daily Physical Activity, Well-Being, and Habits
Bona, F. B. D., Câmpanu, I. A., Langheinrich, M., Gjoreski, M., & Juravle, G. (2025) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3770676
Carrera, A., Zoccarato, F., Mazzeo, M., Lettieri, E., Toletti, G., Bertoli, S., Castelnuovo, G., & Fresa, E. (2024) · Figshare · doi:10.6084/m9.figshare.26567723
Advancing implementation of behavioural medicine in cardiovascular care
Burg, M. M., Stewart, J. C., Gaffey, A. E., Särnholm, J., VELA, A. M., & Crawford, C. A. (2026) · Nature Reviews Psychology · doi:10.1038/s44159-026-00531-8
Choi, S. J. S., Gesierich, C., Klasnja, P., Resnicow, K., Nallamothu, B. K., & Golbus, J. R. (2026) · doi:10.2196/preprints.53934
Houwen, J., Janssen, V. R., Hondmann, S. M., Chavannes, N. H., Kleinsmann, M. S., Atsma, D. E., & Pannunzio, V. (2026) · JMIR Cardio · doi:10.2196/83055
Tolas, A., Johnson, A., Schütz, N., Ramírez‐Posada, M., Montalvo, S., Yang, E., Schmiedmayer, P., Rodríguez, F., Lawrie, A., MYERS, J. N., et al. (2026) · doi:10.2196/preprints.102176
Чухланцева, Н., Чередниченко, І. А., & Mazin, V. M. (2026) · Acta Gymnica · doi:10.5507/ag.2026.013
Metadata
- Authors
- Shcherbina, A., Hershman, S. G., Lazzeroni, L., King, A. C., O'Sullivan, J. W., Hekler, E., Moayedi, Y., Pavlovic, A., Waggott, D., Sharma, A., Yeung, A., Christle, J. W., Wheeler, M. T., McConnell, M. V., Harrington, R. A., & Ashley, E. A.
- Affiliations
- Stanford University (US)
- Stanford Medicine (US)
- United States Department of Veterans Affairs (US)
- University of California San Diego (US)
- University Health Network (CA)
- University of Alberta (CA)
- Corresponding author
- Ashley, Euan A
- ORCID
- Venue
- The Lancet Digital Health
- Publisher
- Elsevier BV
- Published
- 2019-11
- Volume
- 1
- Issue
- 7
- Pages
- e344-e352
- ISSN
- 2589-7500 (ISSN-L)
- OpenAlex
- W2979402731
- Cited by
- 90
- References
- 30
- Citations by year
- 2026: 10 · 2025: 20 · 2024: 11 · 2023: 17 · 2022: 16 · 2021: 8 · 2020: 7 · 2019: 1
- FWCI
- 10.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Digital Health (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- American Heart Association
- Stanford University
- Alberta Innovates - Health Solutions
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- physical activity interventions, mobile application, step count, e-coaching, 10,000 steps goal, sitting breaks, American Heart Association guidelines, cardiovascular health, free-living physical activity, wearable activity trackers
- MeSH terms
- Smartphone, Adult, Cardiovascular Diseases, Female, Health Promotion, Humans, Male, Middle Aged, United States, Exercise, Cross-Over Studies, Mobile Applications
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