Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression

Laranjo, Liliana; Ding, Ding; Heleno, Bruno; Kocaballi, Baki; Quiroz, Juan C; Tong, Huong Ly; Chahwan, Bahia; Neves, Ana Luisa; Gabarron, Elia; Dao, Kim Phuong; Rodrigues, David; Neves, Gisela Costa; Antunes, Maria L; Coiera, Enrico; Bates, David W

doi:10.1136/bjsports-2020-102892

Cited by 400Mobile Health and mHealth ApplicationsPhysical Activity and HealthContext-Aware Activity Recognition Systems

Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression

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Laranjo, Liliana, Ding, Ding, Heleno, Bruno, Kocaballi, Baki, Quiroz, Juan C, Tong, Huong Ly, Chahwan, Bahia, Neves, Ana Luisa +7 more·2021·British Journal of Sports Medicine

DOI 10.1136/bjsports-2020-102892

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Abstract

Objective: To determine the effectiveness of physical activity interventions involving mobile applications (apps) or trackers with automated and continuous self-monitoring and feedback. Design: Systematic review and meta-analysis. Data sources: PubMed and seven additional databases, from 2007 to 2020. Study selection: Randomised controlled trials in adults (18–65 years old) without chronic illness, testing a mobile app or an activity tracker, with any comparison, where the main outcome was a physical activity measure. Independent screening was conducted. Data extraction and synthesis: We conducted random effects meta-analysis and all effect sizes were transformed into standardised difference in means (SDM). We conducted exploratory metaregression with continuous and discrete moderators identified as statistically significant in subgroup analyses. Main outcome measures: Physical activity: daily step counts, min/week of moderate-to-vigorous physical activity, weekly days exercised, min/week of total physical activity, metabolic equivalents. Results: Thirty-five studies met inclusion criteria and 28 were included in the meta-analysis (n=7454 participants, 28% women). The meta-analysis showed a small-to-moderate positive effect on physical activity measures (SDM 0.350, 95% CI 0.236 to 0.465, I 2 =69%, T 2 =0.051) corresponding to 1850 steps per day (95% CI 1247 to 2457). Interventions including text-messaging and personalisation features were significantly more effective in subgroup analyses and metaregression. Conclusion: Interventions using apps or trackers seem to be effective in promoting physical activity. Longer studies are needed to assess the impact of different intervention components on long-term engagement and effectiveness.

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Digital technology-based programs have resulted in increased physical activity and reduced body weight, at least for a short duration.
“Several systematic reviews and meta-analyses [15–19] have shown that these digital technology-based programs resulted in increased PA and reduced body weight, at least for a short duration.”
From A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss (2021) · cites this paper as [19]

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Using a Mobile Social Networking App to Promote Physical Activity: A Qualitative Study of Users’ Perspectives
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The Effectiveness of a Web-Based Computer-Tailored Physical Activity Intervention Using Fitbit Activity Trackers: Randomized Trial
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Changing the physical activity behavior of adults with fitness trackers: a systematic review and meta-analysis
Lynch, C., Bird, S., Lythgo, N., & Selva-Raj, I. (2020) · American Journal of Health Promotion · doi:10.1177/0890117119895204 · Cited by 58 · see citing works
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Wearable Devices to Improve Physical Activity and Sleep: A Randomized Controlled Trial of College-Aged African American Women
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053 Multivariate metaregression models with statistically significant moderators identified in subgroup analyses, a dichotomous variable representing studies where the app or tracker was the only difference between intervention and control, and continuous moderators (number of BCTs in the intervention, retention rate and study duration). Statistically significant moderators were kept in successive models. R 2 was calculated to determine the proportion of total between-study variance explained by the model. Italicised numbers correspond to statistically significant p values. *Goals and planning: studies where the intervention includes BCTs in this category. †Text messaging: studies where the intervention includes text messaging. ‡Personalisation: studies mentioning personalisation in the intervention. §Conflicts of interest: studies where the authors mention conflicts of interest. ¶Graded tasks: studies where the intervention included this BCT. **Behaviour change theories: studies mentioning use of behaviour change theories. † †Reference for all dichotomous variables: remaining studies. ‡ ‡Retention rate: retention rate in the intervention group (continuous variable). BCT, behaviour change technique. on May 17, 2021 by guest. Protected by copyright. http://bjsm.bmj.com/ Br J Sports Med: first published as 10.1136/bjsports-2020-102892 on 21 December 2020. Downloaded from REFERENCES
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Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness
Canali, S., Schiaffonati, V., & Aliverti, A. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000104 · Cited by 416 · see citing works
“Consider one of the prime areas of application of wearables for health: the tracking of physical activity to suggest interventions and behavioural change [57,58].”
A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss
Oh, Y. J., Zhang, J., Fang, M.-L., & Fukuoka, Y. (2021) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-021-01224-6 · Cited by 278 · see citing works
“Several systematic reviews and meta-analyses [15–19] have shown that these digital technology-based programs resulted in increased PA and reduced body weight, at least for a short duration.”
Background
Exercise for Primary and Secondary Prevention of Cardiovascular Disease
Tucker, W. J., Fegers‐Wustrow, I., Halle, M., Haykowsky, M. J., Chung, E. H., & Kovacic, J. C. (2022) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2022.07.004 · Cited by 256 · see citing works
The molecular athlete: exercise physiology from mechanisms to medals
Furrer, R., Hawley, J. A., & Handschin, C. (2023) · Physiological Reviews · doi:10.1152/physrev.00017.2022 · Cited by 232 · see citing works
The effectiveness of digital interventions for increasing physical activity in individuals of low socioeconomic status: a systematic review and meta-analysis
Western, M. J., Armstrong, M. E. G., Islam, I., Morgan, K., Jones, U., & Kelson, M. J. (2021) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-021-01218-4 · Cited by 218 · see citing works
“ulatory BCTs is growing [70, 74, 75], our results suggest that such interventions may be of little benefit to partici-”
Background
The Evolution of Technology and Physical Inactivity: The Good, the Bad, and the Way Forward
Woessner, M. N., Tacey, A., Levinger-Limor, A., Parker, A. G., Levinger, P., & Levinger, I. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.655491 · Cited by 215 · see citing works
“Short term studies have indicated strong efficacy and enjoyment of a variety of technology platforms (accelerometers, phone applications, online interventions) targeting increases in physical activity and improvements in a variety of health parameters (38, 45, 46).”
Background
Effective Behavior Change Techniques in Digital Health Interventions for the Prevention or Management of Noncommunicable Diseases: An Umbrella Review
Mair, J. L., Salamanca-Sanabria, A., Augsburger, M., Frese, B. F., Abend, S., Jakob, R., Kowatsch, T., & Haug, S. (2023) · Annals of Behavioral Medicine · doi:10.1093/abm/kaad041 · Cited by 157 · see citing works
“[85] linked four BCTs or BCT clusters to intervention effectiveness; text messaging, personalization, graded tasks, and goals and planning.”
Background
Personalized mobile technologies for lifestyle behavior change: A systematic review, meta-analysis, and meta-regression
Tong, H. L., Quiroz, J. C., Kocaballi, A. B., Fat, S. C. M., Dao, K. P., Gehringer, H., Chow, C. K., & Laranjo, L. (2021) · Preventive Medicine · doi:10.1016/j.ypmed.2021.106532 · Cited by 136 · see citing works
Self-citation
Multidisciplinary collaborative consensus guidance statement on the assessment and treatment of fatigue in postacute sequelae of SARS‐CoV ‐2 infection ( PASC ) patients
Herrera, J. E., Niehaus, W., Whiteson, J. H., Azola, A. M., Baratta, J. M., Fleming, T. K., Kim, S. Y., Naqvi, H., Sampsel, S., Silver, J. K., et al. (2021) · PM&R · doi:10.1002/pmrj.12684 · Cited by 132 · see citing works
“Smartphones and activity trackers may also be effective methods to monitor duration and intensity of activity.(19) The severity of PASC fatigue can range from mild to severe.”
Method
World Heart Federation Roadmap for Secondary Prevention of Cardiovascular Disease: 2023 Update
Laranjo, L., Lanas, F. T., Sun, M. C., Chen, D. A., Hynes, L., Imran, T. F., Kazi, D. S., Kengne, A. P., Komiyama, M., Kuwabara, M., et al. (2024) · Global Heart · doi:10.5334/gh.1278 · Cited by 133 · see citing works
“Other studies have shown that personalisation of the content and features of mobile health interventions for lifestyle behaviour change are associated with higher effectiveness [237, 238].”
BackgroundSelf-citation
Clinical Pathway for Coronary Atherosclerosis in Patients Without Conventional Modifiable Risk Factors
Figtree, G. A., Vernon, S. T., Harmer, J. A., Gray, M. P., Arnott, C. G., Bachour, E., Barsha, G., Brieger, D. B., Brown, A. D. H., Celermajer, D. S., et al. (2023) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2023.06.045 · Cited by 113 · see citing works
Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management
Mateus, N., Abade, E., Coutinho, D., Gómez, M., Lago‐Peñas, C., & Sampaio, J. E. (2024) · Sensors · doi:10.3390/s25010139 · Cited by 90 · see citing works
mHealth Interventions to Reduce Physical Inactivity and Sedentary Behavior in Children and Adolescents: Systematic Review and Meta-analysis of Randomized Controlled Trials
Baumann, H., Fiedler, J., Wunsch, K., Wöll, A., & Wollesen, B. (2022) · JMIR mhealth and uhealth · doi:10.2196/35920 · Cited by 84 · see citing works
“nonindividualized interventions has been repeatedly demonstrated in various populations [30,38,39], especially in adults [40], but not yet in children or adolescents, although several randomized controlled trials address this matter.”
Background
Wearable Devices to Improve Physical Activity and Reduce Sedentary Behaviour: An Umbrella Review
Longhini, J., Marzaro, C., Bargeri, S., Palese, A., Dell’Isola, A., Turolla, A., Pillastrini, P., Battista, S., Castellini, G., Cook, C. E., et al. (2024) · Sports Medicine - Open · doi:10.1186/s40798-024-00678-9 · Cited by 86 · see citing works
“For example, Laranjo et al. [65] have demonstrated that the intervention might be more effective if it includes text conveying motivational messages or personalisation (e.g., personalized goal setting, contents and feedback).”
Background
Do physical activity interventions combining self-monitoring with other components provide an additional benefit compared with self-monitoring alone? A systematic review and meta-analysis
Vetrovsky, T., Borowiec, A., Juřík, R., Wahlich, C., Śmigielski, W., Steffl, M., Tufano, J. J., Drygas, W., Stastny, P., Harris, T., et al. (2022) · British Journal of Sports Medicine · doi:10.1136/bjsports-2021-105198 · Cited by 68 · see citing works
“15 17–19 A succession of systematic reviews has demonstrated that self-monitoring using different”
Effectiveness of Smartphone‐Based Physical Activity Interventions on Individuals’ Health Outcomes: A Systematic Review
Emberson, M. A., Lalande, A., Wang, D., McDonough, D. J., Liu, W., & Gao, Z. (2021) · BioMed Research International · doi:10.1155/2021/6296896 · Cited by 64 · see citing works
“[4], 25 of the 28 included studies found an increase in physical activity following an intervention carried out on an application on a mobile phone.”
BackgroundResult
Efficacy of Mobile Health Applications to Improve Physical Activity and Sedentary Behavior: A Systematic Review and Meta-Analysis for Physically Inactive Individuals
Zhang, M., Wang, W., Li, M., Sheng, H., & Zhai, Y. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19084905 · Cited by 63 · see citing works
The effectiveness of digital physical activity interventions in older adults: a systematic umbrella review and meta-meta-analysis
Alley, S., Waters, K., Parker, F., Peiris, D. L. I. H. K., Fien, S., Rebar, A. L., & Vandelanotte, C. (2024) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-024-01694-4 · Cited by 56 · see citing works
“Digital interventions such as activity monitors, smartphone and tablet applications (apps), automated Short Message Service (SMS), chatbots, and computer-tailored advice are effective in the general population [8, 9] and show promise in older adults [10, 11].”
Privacy in consumer wearable technologies: a living systematic analysis of data policies across leading manufacturers
Doherty, C., Baldwin, M., Lambe, R., Altini, M., & Caulfield, B. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01757-1 · Cited by 55 · see citing works
Smartwatch interventions in healthcare: A systematic review of the literature
Triantafyllidis, A. K., Kondylakis, H., Katehakis, D. G., Kouroubali, A., Alexiadis, A., Segkouli, S., Votis, K., & Tzovaras, D. K. (2024) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2024.105560 · Cited by 57 · see citing works
“Other previous reviews have focused more broadly on wearable devices [16,17] and their use in specific diseases such as cardiovascular disease [18], diabetes [19], depression [20], or ordinary trackers for physical activity promotion [21,22].”
Background
Daily Step Count and Depression in Adults
Bizzozero‐Peroni, B., Goñi, V. D., Jiménez‐López, E., Rodríguez‐Gutiérrez, E., Sequí‐Domínguez, I., de Arenas‐Arroyo, S. N., López‐Gil, J. F., Martínez‐Vizcaíno, V., & Mesas, A. E. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.51208 · Cited by 57 · see citing works
Designing personalised mHealth solutions: An overview
Rivera-Romero, O., Gabarrón, E., Ropero, J., & Denecke, K. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104500 · Cited by 48 · see citing works
Smartphone applications for physical activity and sedentary behaviour change in people with cardiovascular disease: A systematic review and meta-analysis
Patterson, K., Davey, R., Keegan, R. J., & Freene, N. (2021) · PLoS ONE · doi:10.1371/journal.pone.0258460 · Cited by 45 · see citing works
Behaviour change techniques in cardiovascular disease smartphone apps to improve physical activity and sedentary behaviour: Systematic review and meta-regression
Patterson, K., Davey, R., Keegan, R. J., Kunstler, B., Woodward, A. P., & Freene, N. (2022) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-022-01319-8 · Cited by 45 · see citing works
“The BCTs included in these categories are consistent with reviews in eHealth interventions in CVD [13] and non-CVD populations [9, 52].”
Background
Lifestyle Walking Intervention for Patients With Heart Failure With Reduced Ejection Fraction: The WATCHFUL Trial
Větrovský, T., Širanec, M., Frybova, T., Gant, I., Svobodová, I., Linhart, A., Pařenica, J., Miklíková, M., Šujáková, L., Pospíšil, D., et al. (2023) · Circulation · doi:10.1161/circulationaha.123.067395 · Cited by 45 · see citing works
“20 It also aligns with findings from other trials evaluating various PA interventions across a range of populations and settings, including patients with chronic conditions 23 as well as healthy 21 and older 22 adults in community settings.”
Background
Real-World Accuracy of Wearable Activity Trackers for Detecting Medical Conditions: Systematic Review and Meta-Analysis
Singh, B., CHASTIN, S. F. M., Miatke, A., Curtis, R., Dumuid, D., Brinsley, J., Ferguson, T., Szeto, K., Simpson, C., Eglitis, E., et al. (2024) · JMIR mhealth and uhealth · doi:10.2196/56972 · Cited by 48 · see citing works
Psychophysiological foundations of human physical activity behavior and motivation: theories, systems, mechanisms, evolution, and genetics
Gerber, M., Cheval, B., Cody, R., Colledge, F., Hohberg, V., Klimentidis, Y. C., Lang, C., Looser, V. N., Ludyga, S., Stults‐Kolehmainen, M., et al. (2025) · Physiological Reviews · doi:10.1152/physrev.00021.2024 · Cited by 53 · see citing works
The use of mobile apps and fitness trackers to promote healthy behaviors during COVID-19: A cross-sectional survey
Tong, H. L., Maher, C. A., Parker, K. E., Pham, T., Neves, A. L., Riordan, B. C., Chow, C. K., Laranjo, L., & Quiroz, J. C. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000087 · Cited by 45 · see citing works
“Moreover, existing research has not examined the use of fitness trackers, which have been known to have a positive impact on health behaviors [18,20,21].”
BackgroundSelf-citation
Nomophobia (No Mobile Phone Phobia) and Psychological Health Issues among Young Adult Students
Abdoli, N., Sadeghi-Bahmani, D., Salari, N., Khodamoradi, M., Farnia, V., Jahangiri, S., Brühl, A., Dürsteler, K. M., Stanga, Z., & Brand, S. (2023) · European Journal of Investigation in Health, Psychology and Education · doi:10.3390/ejihpe13090128 · Cited by 45 · see citing works
The Effectiveness of E-Health Interventions Promoting Physical Activity and Reducing Sedentary Behavior in College Students: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Peng, S., Yuan, F., Othman, A. T., Zhou, X., Shen, G., & Liang, J. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20010318 · Cited by 47 · see citing works
“Several studies [34,71,72] confirmed that hybrid intervention modes were better than single intervention modes.”
Background
Physical activity promotion interventions in chronic airways disease: a systematic review and meta-analysis
Reilly, C., Sails, J., Stavropoulos‐Kalinoglou, A., Birch, R. J., McKenna, J., Clifton, I., Peckham, D. G., Birch, K. M., & Price, O. J. (2023) · European Respiratory Review · doi:10.1183/16000617.0109-2022 · Cited by 41 · see citing works
Effects of Gamified Smartphone Applications on Physical Activity: A Systematic Review and Meta-Analysis
Yang, Y., Hu, H., & Koenigstorfer, J. (2021) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2021.10.005 · Cited by 38 · see citing works
Leveraging Mobile Technology for Public Health Promotion: A Multidisciplinary Perspective
Hicks, J. L., Boswell, M. A., Althoff, T., Crum, A. J., Ku, J. P., Landay, J. A., Moya, P. M. L., Murnane, E. L., Snyder, M. P., King, A. C., et al. (2022) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-060220-041643 · Cited by 43 · see citing works
“Meta-analyses of mobile interventions to improve health behaviors provide some evidence that personalized interventions improve physical activity and other behaviors and, in some cases, are more effective when compared directly to nonpersonalized approaches (33, 58, 110).”
Background
Evaluation of Digital Interventions for Physical Activity Promotion: Scoping Review
Santis, K. K. D., Jahnel, T., Matthias, K., Mergenthal, L., Khayyal, H. A., & Zeeb, H. (2022) · JMIR Public Health and Surveillance · doi:10.2196/37820 · Cited by 35 · see citing works
Human Factors in AI-Driven Digital Solutions for Increasing Physical Activity: Scoping Review
Gabarrón, E., Larbi, D., Rivera-Romero, O., & Denecke, K. (2024) · JMIR Human Factors · doi:10.2196/55964 · Cited by 42 · see citing works
“Equipped with built-in sensors that can monitor and encourage PA in real time, they can facilitate sending personalized reminders and motivational messages [7-10], which have been proven to significantly increase PA [10-12].”
Background
Digital Health Interventions to Improve Mental Health in Patients With Cancer: Umbrella Review
Zhong, C., Luo, X., Tan, M., Chi, J., Guo, B., Tang, J., Guo, Z., Deng, S., Zhang, Y., & Wu, Y. (2025) · Journal of Medical Internet Research · doi:10.2196/69621 · Cited by 39 · see citing works
“The capabilities of push notifications and real-time data tracking that smartphone apps have led to increased user engagement and adherence to interventions [98,99].”
Usability Testing of a Social Media Chatbot for Increasing Physical Activity Behavior
Larbi, D., Denecke, K., & Gabarrón, E. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12050828 · Cited by 39 · see citing works
“MYA’s design includes behavior change techniques that have been proven to be effective in increasing physical activity behavior in digital interventions [7]: goals and planning; feedback and monitoring; social support (unspecified); associations (prompts/cues); and reward and threat (social reward) [13].”
Background
Impact of COVID-19 lockdown on physical activity and sedentary behaviour in Dutch cardiovascular disease patients
van Bakel, B. M. A., Bakker, E. A., de Vries, F., Thijssen, D. H. J., & Eijsvogels, T. M. H. (2021) · Netherlands Heart Journal · doi:10.1007/s12471-021-01550-1 · Cited by 36 · see citing works
Effects of Structured Supervised Exercise Training or Motivational Counseling on Pregnant Women’s Physical Activity Level: FitMum - Randomized Controlled Trial
Knudsen, S. D. P., Alomairah, S. A., Roland, C. B., Jessen, A. D., Hergel, I.-M., Clausen, T. D., Larsen, J. E., van Hall, G., Jensen, A. K., Mølsted, S., et al. (2022) · Journal of Medical Internet Research · doi:10.2196/37699 · Cited by 36 · see citing works
Considerations for the Use of Consumer-Grade Wearables and Smartphones in Population Surveillance of Physical Activity
Strain, T., Wijndaele, K., Pearce, M., & Brage, S. (2022) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2021-0046 · Cited by 30 · see citing works
“Consumer-grade wearable devices and smartphone applications also appear to be effective components in interventions to increase activity levels (Laranjo et al., 2021).”
Background
Wearable technology: Covid-19 and the rise of remote clinical monitoring
Best, J. (2021) · BMJ · doi:10.1136/bmj.n413 · Cited by 30 · see citing works
Use Patterns of Smartphone Apps and Wearable Devices Supporting Physical Activity and Exercise: Large-Scale Cross-Sectional Survey
Oba, T., Takano, K., Katahira, K., & Kimura, K. (2023) · JMIR mhealth and uhealth · doi:10.2196/49148 · Cited by 30 · see citing works
“…interventions not limited to self-monitoring (or just wearing an activity tracker); instead, activity trackers, combined with smartphone or web-based applications, offer more interactive BCT components, such as goals and planning, rewards and threats, social support, and gamification [9].”
Background
An Exploratory Investigation of Chatbot Applications in Anxiety Management: A Focus on Personalized Interventions
Manole, A., Cârciumaru, R., Brînzaș, R., & Manole, F. (2024) · Information · doi:10.3390/info16010011 · Cited by 34 · see citing works
Assessing the Acceptability and Effectiveness of Mobile-Based Physical Activity Interventions for Midlife Women During Menopause: Systematic Review of the Literature
AlSwayied, G., Guo, H., Rookes, T., Frost, R., & Hamilton, F. L. (2022) · JMIR mhealth and uhealth · doi:10.2196/40271 · Cited by 33 · see citing works
“Similarly, the meta-analysis by Laranjo et al [91] found that mobile apps and WATs caused small to moderate increases in PA (equivalent to 1850 steps per day) among healthy adult populations.”
Background
StepAdd: A personalized mHealth intervention based on social cognitive theory to increase physical activity among type 2 diabetes patients
Sze, W. T., Waki, K., Enomoto, S., Nagata, Y., Nangaku, M., Yamauchi, T., & Ohe, K. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104481 · Cited by 29 · see citing works
Promoting work ability with a wearable activity tracker in working age individuals with hip and/or knee osteoarthritis: a randomized controlled trial
Östlind, E., Eek, F., Stigmar, K., Sant’Anna, A., & Hansson, E. E. (2022) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-022-05041-1 · Cited by 30 · see citing works
“Several systematic reviews with meta-analysis have established that WAT-use is effective to increase PA [22, 23, 26] which in turn might improve cardiometabolic health and mobility [24, 25].”
Background
Artificial intelligence-powered social robots for promoting physical activity in older adults: A systematic review
Shen, J., Yu, J., Zhang, H., Lindsey, M. A., & An, R. (2025) · Journal of sport and health science/Journal of Sport and Health Science · doi:10.1016/j.jshs.2025.101045 · Cited by 28 · see citing works
“63,64 These devices are widely accessible and can continuously track PA with minimal user effort.”
The Impact of the COVID-19 Pandemic on Physical Activity, Function, and Quality of Life
Said, C. M., Batchelor, F., & Duque, G. (2022) · Clinics in Geriatric Medicine · doi:10.1016/j.cger.2022.04.003 · Cited by 30 · see citing works
“progress and set goals, and have been shown to increase physical activity.(62,63) However, although technology has the potential to increase accessibility to physical activity support, inequities remain.”
Blended Care Interventions to Promote Physical Activity: A Systematic Review of Randomized Controlled Trials
Hohberg, V., Fuchs, R., Gerber, M., Künzler, D., Paganini, S., & Faude, O. (2022) · Sports Medicine - Open · doi:10.1186/s40798-022-00489-w · Cited by 25 · see citing works
“A further meta-analysis showed that app-based interventions to increase physical activity are more effective when they include personal components such as face-to-face sessions, phone calls or text messages from real coaches or therapists [31].”
Background
The Use of Mobile Technologies to Promote Physical Activity and Reduce Sedentary Behaviors in the Middle East and North Africa Region: Systematic Review and Meta-Analysis
Tong, H. L., Alnasser, A., Alshahrani, N. Z., Bawaked, R. A., AlAhmed, R. S., Alsukait, R. F., Rakić, S., Çetinkaya, V., Al-Hazzaa, H. M., & Alqahtani, S. A. (2024) · Journal of Medical Internet Research · doi:10.2196/53651 · Cited by 32 · see citing works
“Although some systematic reviews have reported a positive effect of mobile technologies on behavioral outcomes [18,20-31], none of these studies have focused on evidence from the MENA region.”
InfluentialSelf-citation
Person-specific dose-finding for a digital messaging intervention to promote physical activity.
Hojjatinia, S., Hojjatinia, S., Lagoa, C. M., Brunke-Reese, D., & Conroy, D. E. (2021) · Health Psychology · doi:10.1037/hea0001117 · Cited by 25 · see citing works
Compositional insights on the association between physical activity and sedentary behavior on momentary mood in daily life
Giurgiu, M., Ebner‐Priemer, U., & Dumuid, D. (2021) · Psychology of sport and exercise · doi:10.1016/j.psychsport.2021.102102 · Cited by 26 · see citing works
Barriers and enablers to a healthy lifestyle in people with infertility: a mixed-methods systematic review
Torkel, S., Wang, R., Norman, R. J., Zhao, L., Liu, K., Boden, D., Xu, W., Moran, L., & Cowan, S. (2024) · Human Reproduction Update · doi:10.1093/humupd/dmae011 · Cited by 24 · see citing works
“…meaningful behaviour change, supported by self-monitoring of diet, physical activity, and/or weight via digital health, being associated with improved diet and physical activity or weight loss in adults with overweight or obesity (Teasdale et al. , 2018; Patel et al. , 2021; Laranjo et al. , 2021).”
Background
A personalized mobile app for physical activity: An experimental mixed-methods study
Tong, H. L., Quiroz, J. C., Kocaballi, A. B., Ijaz, K., Coiera, E. W., Chow, C. K., & Laranjo, L. (2022) · Digital Health · doi:10.1177/20552076221115017 · Cited by 27 · see citing works
“However, as many factors vary between people, and even within the same person over time,(25) research has suggested that a one-size-fits-all approach is insufficient, and personalized mobile apps can lead to greater physical activity increases, compared to non-personalized apps.(17,26,27) Several meta-analyses suggest…”
BackgroundResultInfluentialSelf-citation
mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED): rationale and study protocol for a pragmatic randomised controlled trial
Větrovský, T., Král, N., Pfeiferová, M., Kühnová, J., Novák, J., Wahlich, C., Jaklova, A., Jurková, K., Janek, M., Omcirk, D., et al. (2023) · BMC Public Health · doi:10.1186/s12889-023-15513-1 · Cited by 25 · see citing works
Smartphone Applications to Prevent Type 2 Diabetes: A Systematic Review and Meta-Analysis
Jahan, E., Almansour, R., Ijaz, K., Baptista, S. N., Giordan, L. B., Ronto, R., Zaman, S. J., O’Hagan, E. T., & Laranjo, L. (2024) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2024.01.008 · Cited by 25 · see citing works
Self-citation
Experiences of activity monitoring and perceptions of digital support among working individuals with hip and knee osteoarthritis – a focus group study
Östlind, E., Hansson, E. E., Eek, F., & Stigmar, K. G. E. (2022) · BMC Public Health · doi:10.1186/s12889-022-14065-0 · Cited by 22 · see citing works
“WATs have been used in interventions to promote PA and systematic reviews have shown that they can be effective in increasing PA levels in healthy adults [25], older adults [19], individuals with rheumatic and musculoskeletal diseases [26], and other chronic diseases [27].”
Method
Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study
Delobelle, J., Lebuf, E., Dyck, D. V., Compernolle, S., Janek, M., Backere, F. D., & Větrovský, T. (2024) · Digital Health · doi:10.1177/20552076241262710 · Cited by 24 · see citing works
“61 However, frequent syncing is of utmost importance for adequately gathering real-time data and for preventing data loss.”
Background
The Effect of Wearable and Smartphone Applications on Physical Activity, Quality of Life, and Cardiovascular Health Outcomes in Overweight/Obese Adults: A Systematic Review and Meta-analysis of Randomized Controlled Trials
Ghahfarokhi, A. D., Vosadi, E., Barzegar, H., & Saatchian, V. (2022) · Biological Research For Nursing · doi:10.1177/10998004221099556 · Cited by 25 · see citing works
Effects of Smartphone-Based Remote Interventions on Dietary Intake, Physical Activity, Weight Control, and Related Health Benefits Among the Older Population With Overweight and Obesity in China: Randomized Controlled Trial
Zhang, N., Zhou, M., Li, M., & Ma, G. (2023) · Journal of Medical Internet Research · doi:10.2196/41926 · Cited by 21 · see citing works
“A study conducted by Laranjo et al [19] found that interventions using a combination of mobile apps and physical activity trackers could effectively promote physical activity.”
Wearable activity trackers and artificial intelligence in the management of rheumatic diseases
Davergne, T., Kedra, J., & Gossec, L. (2021) · Zeitschrift für Rheumatologie · doi:10.1007/s00393-021-01100-5 · Cited by 20 · see citing works
Exercise Recommendations and Practical Considerations for Asthma Management—An EAACI Position Paper
Price, O. J., Papadopoulos, N. G., Antolín‐Amérigo, D., Backer, V., Bougault, V., Giacco, S. R. D., Gawlik, R., Eguíluz‐Gracia, I., Heffler, E. M., Janson, C., et al. (2025) · Allergy · doi:10.1111/all.16573 · Cited by 20 · see citing works
“…suggests that exercise interventions involving mobile apps or trackers with automated and continuous self-monitoring and feedback (particularly those including text-messaging and personalised features) lead to a significant improvement in step-based physical activity in healthy adults [116].”
The Effectiveness of Publicly Available Web-Based Interventions in Promoting Health App Use, Digital Health Literacy, and Media Literacy: Pre-Post Evaluation Study
König, L., & Suhr, R. (2023) · Journal of Medical Internet Research · doi:10.2196/46336 · Cited by 16 · see citing works
“Various studies have shown that health apps can promote both the physical [8] and mental health [9] of their users.”
Large-Scale Fandom-based Gamification Intervention to Increase Physical Activity: A Quasi-experimental Study
Kamada, M., HAYASHI, H., Shiba, K., TAGURI, M., KONDO, N., Lee, I.-M. M., & Kawachi, I. I. (2021) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000002770 · Cited by 18 · see citing works
Digital Peer-Supported App Intervention to Promote Physical Activity Among Community-Dwelling Older Adults: Nonrandomized Controlled Trial
Tabira, K., Oguma, Y., Yoshihara, S., Shibuya, M., Nakamura, M., Doihara, N., Hirata, A., & Manabe, T. (2024) · JMIR Aging · doi:10.2196/56184 · Cited by 18 · see citing works
“Recently, mobile apps have been used successfully to increase physical activity levels [12,13]. eHealth encompasses health care services and information delivered with the aid of information and communication technology (ICT), including computers, mobile phones, and satellite communications.”
Background
Perceived influence of wearable fitness trackers on eating disorder symptoms in a clinical transdiagnostic binge eating and restrictive eating sample
Wons, O. B., Lampe, E. W., Patarinski, A. G. G., Schaumberg, K., Butryn, M. L., & Juarascio, A. S. (2022) · Eating and Weight Disorders - Studies on Anorexia Bulimia and Obesity · doi:10.1007/s40519-022-01466-8 · Cited by 17 · see citing works
Automated classification of hand gestures using a wristband and machine learning for possible application in pill intake monitoring
Moccia, S., Solbiati, S., Khornegah, M., Bossi, F., & Caiani, E. G. (2022) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2022.106753 · Cited by 17 · see citing works
Effect of a coaching intervention to enhance physical activity and prevent falls in community-dwelling people aged 60+ years: a cluster randomised controlled trial
Oliveira, J. S., Sherrington, C., Rissel, C. E., Howard, K., Tong, A., Merom, D., Wickham, J. B., Bauman, A. E., Lord, S. R., Lindley, R. I., et al. (2024) · British Journal of Sports Medicine · doi:10.1136/bjsports-2023-107027 · Cited by 19 · see citing works
Efficacy of digital interventions on physical activity promotion in individuals with noncommunicable diseases: an overview of systematic reviews
Kardan, M., Jung, A., Iqbal, M., Keshtkar, S., Geidl, W., & Pfeifer, K. (2024) · BMC Digital Health · doi:10.1186/s44247-024-00097-6 · Cited by 18 · see citing works
“This finding is consistent with previous reviews in this field that have focused on adults [91] and on specific populations, such as individuals with CVDs [50] and COPD [34].”
Result
Effects of Family-Based Interventions Using Mobile Apps on Youth’s Physical Activity: A Systematic Review
Saiz-González, P., Hassan, M. A. S., & Gao, Z. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11164798 · Cited by 16 · see citing works
“Additionally, PA interventions comprising wearables and smartphone applications seem to be effective to promote PA [18,19].”
BackgroundResult
The link between the use of diet and fitness monitoring apps, body image and disordered eating symptomology: A systematic review
Anderberg, I., Kemps, E., & Prichard, I. (2025) · Body Image · doi:10.1016/j.bodyim.2024.101836 · Cited by 16 · see citing works
Impact of heart rate variability-based exercise prescription: self-guided by technology and trainer-guided exercise in sedentary adults
Casanova‐Lizón, A., Manresa‐Rocamora, A., Sarabia, J. M., Pastor, D., Javaloyes, A., Peña‐González, I., & Moya‐Ramón, M. (2025) · Frontiers in Sports and Active Living · doi:10.3389/fspor.2025.1578478 · Cited by 16 · see citing works
“Furthermore, a systematic review with meta-analysis suggests that the impact on VO 2 peak is greater when mobile apps include features such as continuous monitoring (65) and automated feedback (66).”
The Regulate your Sitting Time (RESIT) intervention for reducing sitting time in individuals with type 2 diabetes: findings from a randomised-controlled feasibility trial
Brierley, M. L., Chater, A., Edwardson, C. L., Castle, E. M., Hunt, E. R., Biddle, S., Sisodia, R., & Bailey, D. P. (2024) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-024-01336-6 · Cited by 17 · see citing works
“Tailoring interventions to the individual (e.g., through personalised smartphone app features and health coaching with a trained professional) are more likely to lead to improved physical activity and HbA1c outcomes [25, 26].”
Background
The Influence of Social Distancing Behaviors and Psychosocial Factors on Physical Activity During the COVID-19 Pandemic: Cross-sectional Survey Study
Cross, T. J., Isautier, J., Morris, S. J., Johnson, B. D., Wheatley, C. M., & Taylor, B. J. (2021) · JMIR Public Health and Surveillance · doi:10.2196/31278 · Cited by 15 · see citing works
“I feel I'm leading the charge.” Experiences of a virtual physiotherapist-guided knee health program for persons at-risk of osteoarthritis after a sport-related knee injury
Truong, L. K., Mosewich, A. D., Miciak, M., Pajkic, A., Silvester-Lee, T., LI, L. C., & Whittaker, J. L. (2022) · Osteoarthritis and Cartilage Open · doi:10.1016/j.ocarto.2022.100333 · Cited by 15 · see citing works
Flowing data: women’s views and experiences on privacy and data security when using menstrual cycle tracking apps
Mohan, S., & Jenkins, J. (2025) · Oxford Open Digital Health · doi:10.1093/oodh/oqaf011 · Cited by 14 · see citing works
“The participants emphasized the importance of customizing the app’s content to align with the users’ goals, as it helps to create a more comfortable user experience [64].”
Effects of continuous glucose monitoring on dietary behavior and physical activity: A systematic review and meta-analysis
Zhang, D., Huang, J., Zhang, Y. H., Wei, Z., Long, T., Guo, X., & Li, M. (2025) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2025.112907 · Cited by 14 · see citing works
Wearables for Measuring the Physical Activity and Sedentary Behavior of Patients With Axial Spondyloarthritis: Systematic Review
Soulard, J., Carlin, T., Knitza, J., & Vuillerme, N. (2022) · JMIR mhealth and uhealth · doi:10.2196/34734 · Cited by 15 · see citing works
“Indeed, trackers can also be used as an intervention to motivate users to increase physical activity and decrease sedentary behavior [17,64,83-85] and could further prevent inactivity- or sedentary-related diseases (eg, cardiovascular diseases) [12].”
Background
Participatory development of an mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED)
Novák, J., Jurková, K., Lojkaskova, A., Jaklova, A., Kühnová, J., Pfeiferová, M., Král, N., Janek, M., Omcirk, D., Malisova, K., et al. (2024) · BMC Public Health · doi:10.1186/s12889-024-18384-2 · Cited by 14 · see citing works
“To broaden accessibility, including for those with limited technology literacy, the mHealth intervention is delivered in the form of text messages [16, 71].”
BackgroundInfluential
Nigerian physiotherapists’ knowledge, current practice and perceptions of their role for promoting physical activity: A cross-sectional survey
Bello, B., Hartley, S. E., & Yeowell, G. (2022) · PLoS ONE · doi:10.1371/journal.pone.0266765 · Cited by 15 · see citing works
“Evidence has also highlighted the benefits of technology for enhancing physical activity promotion including smartphone apps and activity trackers [53, 54].”
Background
Role of physical activity in obesity treatment and cardiometabolic health: a scientific statement from the American Heart Association
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SNapp, a Tailored Smartphone App Intervention to Promote Walking in Adults of Low Socioeconomic Position: Development and Qualitative Pilot Study
Vos, A. L., de Bruijn, G., Klein, M. C. A., Lakerveld, J., Boerman, S. C., & Smit, E. G. (2023) · JMIR Formative Research · doi:10.2196/40851 · Cited by 13 · see citing works
“Nevertheless, meta-analyses have indicated that app-based PA interventions can significantly increase the daily step count in adult populations [74-76].”
Background
Digital technologies for step counting: between promises of reliability and risks of reductionism
Angelucci, A., Canali, S., & Aliverti, A. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1330189 · Cited by 13 · see citing works
Technology-Supported Behavior Change—Applying Design Thinking to mHealth Application Development
Schweitzer, R., Schlögl, S., & Schweitzer, M. (2024) · European Journal of Investigation in Health Psychology and Education · doi:10.3390/ejihpe14030039 · Cited by 16 · see citing works
“However, most of these positive effects have only been observed in the short-term, after which, high dropout rates are reported [18,23,24].”
Influential
Validity of mHealth devices for counting steps in individuals with Parkinson's disease
Lana, R. D. C., de Paula, A. R., Silva, A. F. S., Costa, P. H. V., & Polese, J. C. (2021) · Journal of Bodywork and Movement Therapies · doi:10.1016/j.jbmt.2021.06.018 · Cited by 13 · see citing works
Association Between Patient Factors and the Effectiveness of Wearable Trackers at Increasing the Number of Steps per Day Among Adults With Cardiometabolic Conditions: Meta-analysis of Individual Patient Data From Randomized Controlled Trials
Hodkinson, A., Kontopantelis, E., Zghebi, S. S., Grigoroglou, C., McMillan, B., van Marwijk, H., Bower, P., Tsimpida, D., Emery, C. F., Burge, M. R., et al. (2022) · Journal of Medical Internet Research · doi:10.2196/36337 · Cited by 13 · see citing works
“Wearable physical activity trackers, such as accelerometers, pedometers, and the Fitbit (Fitbit Inc), are portable electrical or electromechanical devices that count each step a person takes by detecting the motion of the person along the body’s long axis [7,8].”
Long-term Effects of the Use of a Step Count–Specific Smartphone App on Physical Activity and Weight Loss: Randomized Controlled Clinical Trial
Yoshimura, E., Tajiri, E., Michiwaki, R., Matsumoto, N., Hatamoto, Y., & Tanaka, S. (2022) · JMIR mhealth and uhealth · doi:10.2196/35628 · Cited by 14 · see citing works
Technology obsolescence across the adult lifespan in a USA internet sample
Gray, N., & Charness, N. H. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.1005822 · Cited by 13 · see citing works
“Mobile devices can be used to monitor health in ways that can increase effectiveness of health interventions (18).”
Background
Physical Activity Trends Among Adults in a National Mobile Health Program: A Population-Based Cohort Study of 411,528 Adults
Ang, G., Edney, S. M., Tan, C. S., Lim, N., Tan, J., Müller‐Riemenschneider, F., & Chen, C. (2022) · American Journal of Epidemiology · doi:10.1093/aje/kwac193 · Cited by 13 · see citing works
“However, to translate these improvements to population health, effective interventions need to be scaled up and delivered to large numbers of people within real-world contexts (6).”
Background
Mobile application interventions to increase physical activity and their effect on kinanthropometrics, body composition and fitness variables in adolescent aged 12–16 years old: An umbrella review
Mateo‐Orcajada, A., Vaquero‐Cristóbal, R., & Abenza‐Cano, L. (2023) · Child Care Health and Development · doi:10.1111/cch.13146 · Cited by 13 · see citing works
Smartphone Apps and Wearables for Health Parameters in Young Adulthood: Cross-Sectional Study
Leuzzi, G., Job, M., Scafoglieri, A., & Testa, M. (2025) · JMIR Human Factors · doi:10.2196/64629 · Cited by 12 · see citing works
“…apps and wearables, along with their functions, is crucial for creating preventive and educational interventions [16] that assist young people in monitoring and improving their health [17-19], well-being, and quality of life through familiar technology tailored to their needs and expectations.”
Effects of digital health interventions on muscle mass, muscle strength, and physical function in older adults with sarcopenia: a systematic review and meta-analysis
Chen, W., Yao, J., Wang, H., Jia, S., Zhu, X., & Mao, L. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1711514 · Cited by 12 · see citing works
Impact of digital health interventions on quality of life and mental health in older adults with chronic diseases: a systematic review and meta-analysis
Hu, E., Wang, H., Yao, J., Liao, M., & Chen, W. (2026) · Frontiers in Aging · doi:10.3389/fragi.2025.1737277 · Cited by 12 · see citing works
Associations of Wearable Activity Tracker Use With Physical Activity and Health Outcomes in Patients With Cancer: Findings from a Population-Based Survey Study
Zhou, W., Shang, S., & Cho, Y. (2024) · Journal of Medical Internet Research · doi:10.2196/51291 · Cited by 12 · see citing works
“This is consistent with observational studies of general adults [12] and older adults [13] and meta-analyses of clinical trials [8,10,18].”
Effectiveness of wearable activity trackers on physical activity among adolescents in school-based settings: a systematic review and meta-analysis
Chen, X., Wang, F., Zhang, H., Yang, L., Zhu, S., & Yang, Y. (2025) · BMC Public Health · doi:10.1186/s12889-025-22170-z · Cited by 19 · see citing works
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Getting active through mindfulness: Randomised controlled trial of a digital mindfulness-based intervention promoting physical activity engagement and enjoyment
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Social Media Chatbot for Increasing Physical Activity: Usability Study
Larbi, D., Gabarrón, E., & Denecke, K. (2021) · Studies in health technology and informatics · doi:10.3233/shti210604 · Cited by 13 · see citing works
“Digital technology interventions can successfully increase physical activity among adults [3-6].”
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Dose–response relations between the frequency of two types of momentary feedback prompts and daily physical activity.
Conroy, D. E., Wu, J.-C., Lee, A. M., Brunke-Reese, D., & Lagoa, C. M. (2023) · Health Psychology · doi:10.1037/hea0001271 · Cited by 11 · see citing works
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Are You Counting? Effectiveness of Interventions Using Activity Trackers and Smartphone Applications for Increasing Physical Activity in Older People Living in the Community: A Systematic Review With Meta-Analysis
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Authors: Laranjo, L., Ding, D., Heleno, B., Kocaballi, B., Quiroz, J. C., Tong, H. L., Chahwan, B., Neves, A. L., Gabarron, E., Dao, K. P., Rodrigues, D., Neves, G. C., Antunes, M. L., Coiera, E., & Bates, D. W.
Affiliations: The University of Sydney (AU)
Universidade Nova de Lisboa (PT)
UNSW Sydney (AU)
Macquarie University (AU)
Brigham and Women's Hospital (US)
Corresponding author: Laranjo, Liliana
ORCID: Laranjo, Liliana
Ding, Ding
Heleno, Bruno
Quiroz, Juan C
Tong, Huong Ly
Dao, Kim Phuong
Coiera, Enrico
Bates, David W
Venue: British Journal of Sports Medicine
Publisher: BMJ
Published: 2020-12-21
Volume: 55
Issue: 8
Pages: 422-432
ISSN: 0306-3674 (ISSN-L)
1473-0480
DOI: 10.1136/bjsports-2020-102892
OpenAlex: W3113845499
Cited by: 400
References: 91
Citations by year: 2026: 55 · 2025: 80 · 2024: 102 · 2023: 54 · 2022: 75 · 2021: 34
FWCI: 7.77
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: British Journal of Sports Medicine (publishedVersion)
PubMed (publishedVersion)
Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-nc-nd)
Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by)
Repository of Digital Objects for Teaching Research and Culture (University of Valencia) (submittedVersion, other-oa)
Zenodo (CERN European Organization for Nuclear Research) (cc-by)
Funders: National Health and Medical Research Council (APP1134919)
Topics: Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Health Sciences › Medicine › Physiology › Physical Activity and Health
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords: mobile health apps, wearable activity trackers, physical activity promotion, self-monitoring, feedback, step count, moderate-to-vigorous physical activity, text messaging, personalization, adults
MeSH terms: Smartphone, Fitness Trackers, Adult, Feedback, Humans, Regression Analysis, Health Behavior, Exercise, Mobile Applications

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Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression

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