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

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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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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·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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RETRACTED: Accelerometer- and Pedometer-Based Physical Activity Interventions Among Adults With Cardiometabolic Conditions: A Systematic Review and Meta-analysis
Hodkinson, A., Kontopantelis, E., Adeniji, C., van Marwijk, H., McMillan, B., Bower, P., & Panagioti, M. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.12895 · Cited by 55
Retracted
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
The Cochrane Collaboration's tool for assessing risk of bias in randomised trials
Higgins, J. P. T., Altman, D. G., Gotzsche, P. C., Juni, P., Moher, D., Oxman, A. D., Savovic, J., Schulz, K. F., Weeks, L., Sterne, J. A. C., et al. (2011) · BMJ · doi:10.1136/bmj.d5928 · Cited by 33,817
Statistical Power Analysis for the Behavioral Sciences
Cohen, J. (2013) · doi:10.4324/9780203771587 · Cited by 25,373
Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series
(2008) · doi:10.1002/9780470712184 · Cited by 25,048
GRADE: an emerging consensus on rating quality of evidence and strength of recommendations
Guyatt, G. H., Oxman, A. D., Vist, G. E., Kunz, R., Falck-Ytter, Y., Alonso-Coello, P., & Schünemann, H. J. (2008) · BMJ · doi:10.1136/bmj.39489.470347.ad · Cited by 23,305
The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gotzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · BMJ · doi:10.1136/bmj.b2700 · Cited by 17,648
Introduction to Meta‐Analysis
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009) · doi:10.1002/9780470743386 · Cited by 14,225
High-performance medicine: the convergence of human and artificial intelligence
Topol, E. J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0300-7 · Cited by 10,450
Introduction to Meta‐Analysis
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2021) · doi:10.1002/9781119558378 · Cited by 9,799
The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions
Michie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., Eccles, M. P., Cane, J., & Wood, C. E. (2013) · Annals of Behavioral Medicine · doi:10.1007/s12160-013-9486-6 · Cited by 7,629
Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1·9 million participants
Guthold, R., Stevens, G. A., Riley, L. M., & Bull, F. C. (2018) · The Lancet Global Health · doi:10.1016/s2214-109x(18)30357-7 · Cited by 4,819
The pandemic of physical inactivity: global action for public health
Kohl, H. W., Craig, C. L., Lambert, E. V., Inoue, S., Alkandari, J. R., Leetongin, G., & Kahlmeier, S. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60898-8 · Cited by 2,985
The Law of Attrition
Eysenbach, G. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.1.e11 · Cited by 2,524
Effective techniques in healthy eating and physical activity interventions: A meta-regression.
Michie, S., Abraham, C., Whittington, C., McAteer, J., & Gupta, S. (2009) · Health Psychology · doi:10.1037/a0016136 · Cited by 2,229
The economic burden of physical inactivity: a global analysis of major non-communicable diseases
Ding, D., Lawson, K. D., Kolbe-Alexander, T. L., Finkelstein, E. A., Katzmarzyk, P. T., van Mechelen, W., & Pratt, M. (2016) · The Lancet · doi:10.1016/s0140-6736(16)30383-x · Cited by 2,201
Self-citation
Using Pedometers to Increase Physical Activity and Improve Health: A Systematic Review
Bravata, D. M., Smith-Spangler, C., Sundaram, V., Gienger, A. L., Lin, N., Lewis, R., Stave, C. D., Olkin, I., & Sirard, J. R. (2007) · JAMA · doi:10.1001/jama.298.19.2296 · Cited by 2,064
Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: systematic review and harmonised meta-analysis
Ekelund, U., Tarp, J., Steene-Johannessen, J., Hansen, B. H., Jefferis, B., Fagerland, M. W., Whincup, P., Diaz, K. M., Hooker, S. P., Chernofsky, A., et al. (2019) · BMJ · doi:10.1136/bmj.l4570 · Cited by 1,769
Leisure Time Physical Activity and Mortality: A Detailed Pooled Analysis of the Dose-Response Relationship
Arem, H., Moore, S. C., Patel, A., Hartge, P., Berrington de Gonzalez, A., Visvanathan, K., Campbell, P. T., Freedman, M., Weiderpass, E., Adami, H. O., et al. (2015) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2015.0533 · Cited by 1,498
The effect of physical activity on mortality and cardiovascular disease in 130 000 people from 17 high-income, middle-income, and low-income countries: the PURE study
Lear, S. A., Hu, W., Rangarajan, S., Gasevic, D., Leong, D., Iqbal, R., Casanova, A., Swaminathan, S., Anjana, R. M., Kumar, R., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)31634-3 · Cited by 1,331
Physical activity and risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events: systematic review and dose-response meta-analysis for the Global Burden of Disease Study 2013.
Kyu, H. H., Bachman, V. F., Alexander, L. T., Mumford, J. E., Afshin, A., Estep, K., Veerman, J. L., Delwiche, K., Iannarone, M. L., Moyer, M. L., et al. (2016) · BMJ · doi:10.1136/bmj.i3857 · Cited by 1,272
Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations
Chen, J. H., & Asch, S. M. (2017) · New England Journal of Medicine · doi:10.1056/nejmp1702071 · Cited by 1,171
Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions
Yardley, L., Spring, B. J., Riper, H., Morrison, L. G., Crane, D. H., Curtis, K., Merchant, G. C., Naughton, F., & Blandford, A. (2016) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2016.06.015 · Cited by 1,118
A meta-analysis of computer-tailored interventions for health behavior change
Krebs, P., Prochaska, J. O., & Rossi, J. S. (2010) · Preventive Medicine · doi:10.1016/j.ypmed.2010.06.004 · Cited by 854
Digital Phenotyping: Technology for a New Science of Behavior
Insel, T. R. (2017) · JAMA · doi:10.1001/jama.2017.11295 · Cited by 833
Interventions to promote walking: systematic review
Ogilvie, D., Foster, C. E., Rothnie, H., Cavill, N., Hamilton, V., Fitzsimons, C. F., & Mutrie, N. (2007) · BMJ · doi:10.1136/bmj.39198.722720.be · Cited by 695
What are the most effective intervention techniques for changing physical activity self-efficacy and physical activity behaviour--and are they the same?
Williams, S. L., & French, D. P. (2011) · Health Education Research · doi:10.1093/her/cyr005 · Cited by 690
Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis
Brickwood, K.-J., Watson, G., O'Brien, J., & Williams, A. D. (2019) · JMIR mHealth and uHealth · doi:10.2196/11819 · Cited by 689
Efficacy of text messaging-based interventions for health promotion: A meta-analysis
Head, K. J., Noar, S. M., Iannarino, N. T., & Harrington, N. G. (2013) · Social Science & Medicine · doi:10.1016/j.socscimed.2013.08.003 · Cited by 647
Association of Step Volume and Intensity With All-Cause Mortality in Older Women
Lee, I.-M., Shiroma, E. J., Kamada, M., Bassett, D. R., Matthews, C. E., & Buring, J. E. (2019) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2019.0899 · Cited by 604
Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis
Flores Mateo, G., Granado-Font, E., Ferré-Grau, C., & Montaña-Carreras, X. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4836 · Cited by 540
Mobile Devices and Health
Sim, I. (2019) · New England Journal of Medicine · doi:10.1056/nejmra1806949 · Cited by 491
Can smartphone apps increase physical activity? Systematic review and meta-analysis
Romeo, A., Edney, S., Plotnikoff, R., Curtis, R., Ryan, J., Sanders, I., Crozier, A., & Maher, C. (2019) · Journal of Medical Internet Research · doi:10.2196/12053 · Cited by 487
Randomized Trial of a Fitbit-Based Physical Activity Intervention for Women
Cadmus-Bertram, L. A., Marcus, B. H., Patterson, R. E., Parker, B. A., & Morey, B. L. (2015) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2015.01.020 · Cited by 469
Increasing Physical Activity With Mobile Devices: A Meta-Analysis
Fanning, J., Mullen, S. P., & McAuley, E. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.2171 · Cited by 457
Systematic review of maintenance of behavior change following physical activity and dietary interventions.
Fjeldsoe, B., Neuhaus, M., Winkler, E., & Eakin, E. (2011) · Health Psychology · doi:10.1037/a0021974 · Cited by 413
Effectiveness of activity trackers with and without incentives to increase physical activity (TRIPPA): a randomised controlled trial
Finkelstein, E. A., Haaland, B. A., Bilger, M., Sahasranaman, A., Sloan, R. A., Nang, E. E. K., & Evenson, K. R. (2016) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(16)30284-4 · Cited by 402
Behavioral Counseling to Promote a Healthful Diet and Physical Activity for Cardiovascular Disease Prevention in Adults Without Known Cardiovascular Disease Risk Factors: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force
Patnode, C. D., Evans, C. V., Senger, C. A., Redmond, N., & Lin, J. S. (2017) · JAMA · doi:10.1001/jama.2017.3303 · Cited by 380
Smartphone Applications for Patients' Health and Fitness
Higgins, J. P. (2015) · The American Journal of Medicine · doi:10.1016/j.amjmed.2015.05.038 · Cited by 357
mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials.
Direito, A., Carraça, E., Rawstorn, J., Whittaker, R., & Maddison, R. (2017) · Annals of Behavioral Medicine · doi:10.1007/s12160-016-9846-0 · Cited by 337
Beyond validation: getting health apps into clinical practice
Gordon, W. J., Landman, A., Zhang, H., & Bates, D. W. (2020) · npj Digital Medicine · doi:10.1038/s41746-019-0212-z · Cited by 322
Self-citation
Wearable Sensor/Device (Fitbit One) and SMS Text-Messaging Prompts to Increase Physical Activity in Overweight and Obese Adults: A Randomized Controlled Trial
Wang, J. B., Cadmus-Bertram, L. A., Natarajan, L., White, M. M., Madanat, H., Nichols, J. F., Ayala, G. X., & Pierce, J. P. (2015) · Telemedicine and e-Health · doi:10.1089/tmj.2014.0176 · Cited by 308
Effectiveness of a smartphone application to promote physical activity in primary care: the SMART MOVE randomised controlled trial
Glynn, L. G., Hayes, P. S., Casey, M., Glynn, F., Alvarez‐Iglesias, A., Newell, J., OLaighin, G. M., Heaney, D., O'Donnell, M. J., & Murphy, A. W. (2014) · British Journal of General Practice · doi:10.3399/bjgp14x680461 · Cited by 293
Effects of Mobile Health App Interventions on Sedentary Time, Physical Activity, and Fitness in Older Adults: Systematic Review and Meta-Analysis
Yerrakalva, D., Yerrakalva, D., Hajna, S., & Griffin, S. J. (2019) · Journal of Medical Internet Research · doi:10.2196/14343 · Cited by 290
Effect of Pedometer-Based Physical Activity Interventions
Kang, M., Marshall, S. J., Barreira, T. V., & Lee, J.-O. (2009) · Research Quarterly for Exercise and Sport · doi:10.1080/02701367.2009.10599604 · Cited by 289
Digital Health Equity as a Necessity in the 21st Century Cures Act Era
Rodriguez, J. A., Clark, C. R., & Bates, D. W. (2020) · JAMA · doi:10.1001/jama.2020.7858 · Cited by 289
Self-citation
Barriers to and Facilitators of Engagement With Remote Measurement Technology for Managing Health: Systematic Review and Content Analysis of Findings
Simblett, S., Greer, B., Matcham, F., Curtis, H., Polhemus, A., Ferrão, J., Gamble, P., & Wykes, T. (2018) · Journal of Medical Internet Research · doi:10.2196/10480 · Cited by 270
mActive: A Randomized Clinical Trial of an Automated mHealth Intervention for Physical Activity Promotion
Martin, S. S., Feldman, D. I., Blumenthal, R. S., Jones, S. R., Post, W. S., McKibben, R. A., Michos, E. D., Ndumele, C. E., Ratchford, E. V., Coresh, J., et al. (2015) · Journal of the American Heart Association · doi:10.1161/jaha.115.002239 · Cited by 267
The Effect of Physical Activity Interventions Comprising Wearables and Smartphone Applications on Physical Activity: a Systematic Review and Meta-analysis
Gal, R., May, A. M., van Overmeeren, E. J., Simons, M., & Monninkhof, E. M. (2018) · Sports Medicine - Open · doi:10.1186/s40798-018-0157-9 · Cited by 257
Effect of a Game-Based Intervention Designed to Enhance Social Incentives to Increase Physical Activity Among Families: The BE FIT Randomized Clinical Trial
Patel, M. S., Benjamin, E. J., Volpp, K. G., Fox, C. S., Small, D. S., Massaro, J. M., Lee, J. J., Hilbert, V., Valentino, M., Taylor, D. H., et al. (2017) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2017.3458 · Cited by 218
Why Do Pedometers Work?
Tudor-Locke, C. E., & Lutes, L. D. (2009) · Sports Medicine · doi:10.2165/11319600-000000000-00000 · Cited by 208
Remote and web 2.0 interventions for promoting physical activity
Foster, C. E., Richards, J. A., Thorogood, M., & Hillsdon, M. M. (2013) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd010395.pub2 · Cited by 195
Using an electronic activity monitor system as an intervention modality: A systematic review
Lewis, Z. H., Lyons, E., Jarvis, J. M., & Baillargeon, J. (2015) · BMC Public Health · doi:10.1186/s12889-015-1947-3 · Cited by 193
Effectiveness of Behaviorally Designed Gamification Interventions With Social Incentives for Increasing Physical Activity Among Overweight and Obese Adults Across the United States
Patel, M. S., Small, D. S., Harrison, J. D., Fortunato, M. P., Oon, A. L., Rareshide, C. A. L., Reh, G., Szwartz, G., Guszcza, J., Steier, D. M., et al. (2019) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2019.3505 · Cited by 179
Examining the active ingredients of physical activity interventions underpinned by theory versus no stated theory: a meta-analysis
McEwan, D., Beauchamp, M. R., Kouvousis, C., Ray, C. M., Wyrough, A. B., & Rhodes, R. E. (2018) · Health Psychology Review · doi:10.1080/17437199.2018.1547120 · Cited by 171
The effect of a programme to improve men’s sedentary time and physical activity: The European Fans in Training (EuroFIT) randomised controlled trial
Wyke, S., Bunn, C., Andersen, E., Silva, M. N., van Nassau, F., McSkimming, P., Kolovos, S., Gill, J. M. R., Gray, C. M., Hunt, K., et al. (2019) · PLoS Medicine · doi:10.1371/journal.pmed.1002736 · Cited by 157
Individual Versus Team-Based Financial Incentives to Increase Physical Activity: A Randomized, Controlled Trial
Patel, M. S., Asch, D. A., Rosin, R. M., Small, D. S., Bellamy, S. L., Eberbach, K., Walters, K. J., Haff, N., Lee, S. M., Wesby, L., et al. (2016) · Journal of General Internal Medicine · doi:10.1007/s11606-016-3627-0 · Cited by 148
Effects of Three Motivationally Targeted Mobile Device Applications on Initial Physical Activity and Sedentary Behavior Change in Midlife and Older Adults: A Randomized Trial
King, A. C., Hekler, E. B., Grieco, L. A., Winter, S. J., Sheats, J. L., Buman, M. P., Banerjee, B., Robinson, T. N., & Cirimele, J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0156370 · Cited by 148
Effect of Pedometer-Based Physical Activity Interventions: A Meta-Analysis
Kang, M., Marshall, S. J., Barreira, T. V., & Lee, J.-O. (2009) · Research Quarterly for Exercise & Sport · doi:10.5641/027013609x13088500160000 · Cited by 148
Behavior Change Techniques Associated With Changes in Postintervention and Maintained Changes in Self-Efficacy For Physical Activity: A Systematic Review With Meta-analysis
Tang, M. Y., Smith, D. M., Mc Sharry, J., Hann, M., & French, D. P. (2019) · Annals of Behavioral Medicine · doi:10.1093/abm/kay090 · Cited by 141
The effectiveness of smoking cessation, physical activity/diet and alcohol reduction interventions delivered by mobile phones for the prevention of non-communicable diseases: A systematic review of randomised controlled trials
Palmer, M., Sutherland, J., Barnard, S., Wynne, A., Rezel, E., Doel, A., Grigsby-Duffy, L., Edwards, S., Russell, S., Hotopf, E., et al. (2018) · PLOS ONE · doi:10.1371/journal.pone.0189801 · Cited by 136
Wearable Technology and Physical Activity Behavior Change in Adults With Chronic Cardiometabolic Disease: A Systematic Review and Meta-Analysis
Kirk, M., Amiri, M., Pirbaglou, M., & Ritvo, P. (2018) · American Journal of Health Promotion · doi:10.1177/0890117118816278 · Cited by 132
Health Apps and Health Policy
Bates, D. W., Landman, A., & Levine, D. M. (2018) · JAMA · doi:10.1001/jama.2018.14378 · Cited by 120
Self-citation
Use of Wearable Technology and Social Media to Improve Physical Activity and Dietary Behaviors among College Students: A 12-Week Randomized Pilot Study
Pope, Z., Barr‐Anderson, D. J., Lewis, B. A., Pereira, M. A., & Gao, Z. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16193579 · Cited by 119
Effectiveness of an Activity Tracker- and Internet-Based Adaptive Walking Program for Adults: A Randomized Controlled Trial
Poirier, J., Bennett, W. L., Jerome, G. J., Shah, N. G., Lazo, M., Yeh, H.-C., Clark, J. M., & Cobb, N. K. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5295 · Cited by 111
Feasibility and preliminary efficacy of the ‘HEYMAN’ healthy lifestyle program for young men: a pilot randomised controlled trial
Ashton, L. M., Morgan, P. J., Hutchesson, M. J., Rollo, M. E., & Collins, C. E. (2017) · Nutrition Journal · doi:10.1186/s12937-017-0227-8 · Cited by 111
Gamification Use and Design in Popular Health and Fitness Mobile Applications
Cotton, V., & Patel, M. S. (2019) · American Journal of Health Promotion · doi:10.1177/0890117118790394 · Cited by 110
Evaluating the effectiveness of organisational-level strategies with or without an activity tracker to reduce office workers’ sitting time: a cluster-randomised trial
Brakenridge, C. L., Fjeldsoe, B. S., Young, D. C., Winkler, E. A. H., Dunstan, D. W., Straker, L. M., & Healy, G. N. (2016) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-016-0441-3 · Cited by 109
What is the role of smartphones on physical activity promotion? A systematic review and meta-analysis
Feter, N., dos Santos, T. S., Caputo, E. L., & da Silva, M. C. (2019) · International Journal of Public Health · doi:10.1007/s00038-019-01210-7 · Cited by 106
"Not just another walking program": everyday activity supports You (EASY) model-a randomized pilot study for a parallel randomized controlled trial
Ashe, M. C., Winters, M., Hoppmann, C. A., Dawes, M. G., Gardiner, P. A., Giangregorio, L. M., Madden, K. M., McAllister, M. M., Wong, G., Puyat, J. H., et al. (2015) · Pilot and Feasibility Studies · doi:10.1186/2055-5784-1-4 · Cited by 103
A Randomized Trial of Social Comparison Feedback and Financial Incentives to Increase Physical Activity
Patel, M. S., Volpp, K. G. M., Rosin, R. M., Bellamy, S. L., Small, D. S., Fletcher, M., Osman-Koss, R., Brady, J. L., Haff, N., Lee, S. M., et al. (2016) · American Journal of Health Promotion · doi:10.1177/0890117116658195 · Cited by 101
An mHealth Intervention Using a Smartphone App to Increase Walking Behavior in Young Adults: A Pilot Study
Walsh, J. C., Corbett, T. K., Hogan, M., Duggan, J., & McNamara, A. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.5227 · Cited by 101
Use of Wearable Activity Trackers to Improve Physical Activity Behavior in Patients With Rheumatic and Musculoskeletal Diseases: A Systematic Review and Meta‐Analysis
Davergne, T., Pallot, A., Dechartres, A., Fautrel, B., & Gossec, L. (2018) · Arthritis Care & Research · doi:10.1002/acr.23752 · Cited by 101
Effect of interventions using physical activity trackers on physical activity in people aged 60 years and over: a systematic review and meta-analysis
Oliveira, J. S., Sherrington, C., Zheng, E. R. Y., Franco, M. R., & Tiedemann, A. (2019) · British Journal of Sports Medicine · doi:10.1136/bjsports-2018-100324 · Cited by 98
Designing engaging online behaviour change interventions: A proposed model of user engagement
Short, C. E., Rebar, A. L., Plotnikoff, R. C., & Vandelanotte, C. (2015) · Adelaide Research & Scholarship (AR&S) (University of Adelaide) · Cited by 89
A Randomized, Controlled Trial of Lottery-Based Financial Incentives to Increase Physical Activity Among Overweight and Obese Adults
Patel, M. S., Volpp, K. G. M., Rosin, R. M., Bellamy, S. L., Small, D. S., Heuer, J., Sproat, S., Hyson, C., Haff, N., Lee, S. M., et al. (2018) · American Journal of Health Promotion · doi:10.1177/0890117118758932 · Cited by 84
The impact of interventions that integrate accelerometers on physical activity and weight loss: a systematic review
Goode, A. P., Hall, K. S., Batch, B. C., Huffman, K. M., Hastings, S. N., Allen, K. D., Shaw, R. J., Kanach, F. A., McDuffie, J. R., Kosinski, A. S., et al. (2017) · Annals of Behavioral Medicine · doi:10.1007/s12160-016-9829-1 · Cited by 80
Using a Mobile Social Networking App to Promote Physical Activity: A Qualitative Study of Users’ Perspectives
Tong, H. L., Coiera, E. W., & Laranjo, L. (2018) · Journal of Medical Internet Research · doi:10.2196/11439 · Cited by 76
Self-citation
The Effectiveness of a Web-Based Computer-Tailored Physical Activity Intervention Using Fitbit Activity Trackers: Randomized Trial
Vandelanotte, C., Duncan, M. J., Maher, C. A., Schoeppe, S., Rebar, A. L., Power, D. A., Short, C. E., Doran, C. M., Hayman, M. J., & Alley, S. J. (2018) · Journal of Medical Internet Research · doi:10.2196/11321 · Cited by 68
Activity Monitor Intervention to Promote Physical Activity of Physicians-In-Training: Randomized Controlled Trial
Thorndike, A. N., Mills, S., Sonnenberg, L., Palakshappa, D., Gao, T., Pau, C. T., & Regan, S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0100251 · Cited by 66
Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Healthy Adults’ Activity Levels: Randomized Intervention
Ellingson, L. D., Lansing, J. E., DeShaw, K. J., Peyer, K. L., Bai, Y., Pérez, M., Phillips, L. A., & Welk, G. J. (2019) · JMIR mhealth and uhealth · doi:10.2196/10988 · Cited by 65
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
A smartphone “app”-delivered randomized factorial trial targeting physical activity in adults
Fanning, J. T., Roberts, S. A., Hillman, C. H., Mullen, S. P., Ritterband, L. M., & McAuley, E. (2017) · Journal of Behavioral Medicine · doi:10.1007/s10865-017-9838-y · Cited by 56
Mobile App-Based Small-Group Physical Activity Intervention for Young African American Women: a Pilot Randomized Controlled Trial
Zhang, J., & Jemmott, J. B. (2019) · Prevention Science · doi:10.1007/s11121-019-01006-4 · Cited by 51
Effectiveness of healthcare interventions using objective feedback on physical activity: a systematic review and meta-analysis
Braakhuis, H., Berger, M., & Bussmann, J. (2019) · Journal of Rehabilitation Medicine · doi:10.2340/16501977-2522 · Cited by 51
Time for change: using implementation intentions to promote physical activity in a randomised pilot trial
Robinson, S. A., Bisson, A., Hughes, M. L., Ebert, J. E. J., & Lachman, M. E. (2018) · Psychology and Health · doi:10.1080/08870446.2018.1539487 · Cited by 47
Utilizing wearable technology to increase physical activity in future physicians: A randomized trial
DiFrancisco‐Donoghue, J., Jung, M. K., Stangle, A., Werner, W. G., Zwibel, H., Happel, P., & Balentine, J. (2018) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2018.09.004 · Cited by 41
Exergame Apps and Physical Activity: The Results of the ZOMBIE Trial
Cowdery, J. E., Majeske, P., Frank, R. E., & Brown, D. L. (2015) · American Journal of Health Education · doi:10.1080/19325037.2015.1043063 · Cited by 39
Wearable Devices to Improve Physical Activity and Sleep: A Randomized Controlled Trial of College-Aged African American Women
Melton, B. F., Buman, M. P., Vogel, R. L., Harris, B. S., & Bigham, L. E. (2016) · Journal of Black Studies · doi:10.1177/0021934716653349 · Cited by 36
The Role of Incentive Salience in Habit Formation
John, L. K., Milkman, K. L., Francesca Gino, B., Tuckfield, B., & Foschini, L. (2016) · Cited by 4

Research works printed but not linked: 4

Higgins J , Green S . Cochrane Handbook for systematic reviews of interventions. Chichester: John Wiley & Sons, 2011.
10.1136/bmj.39489.470347.AD · DOI · Paper page
10.1136/bmj.l4570 · DOI · Paper page
Global mobile consumer survey: US edition | a new era in mobile continues. Deloitte 2018.

Sorted by citations

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Canali, S., Schiaffonati, V., & Aliverti, A. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000104 · Cited by 457
“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
“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 280
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 253
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 238
“ulatory BCTs is growing [70, 74, 75], our results suggest that such interventions may be of little benefit to partici-”
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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 › 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: 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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