The DOI matches its Crossref record; 206 of the 207 references it cites were found in a registry or an index.
Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review
Open accessPublished version of a preprint
Abstract
BACKGROUND: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users' interaction and usage behavior) and acceptability (ie, users' subjective perceptions and experiences) to help explain how and why apps and wearables work. OBJECTIVES: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. METHOD: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. RESULTS: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). CONCLUSIONS: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, knowledge on these apps’ potential is lacking, particularly in regard to testing apps in practical settings and using objective data, and health apps generally are not evidence-based [63].”
From Advantages and disadvantages of mobile applications for workplace health promotion: A scoping review (2024) · cites this paper as [63]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, knowledge on these apps’ potential is lacking, particularly in regard to testing apps in practical settings and using objective data, and health apps generally are not evidence-based [63].”
From Advantages and disadvantages of mobile applications for workplace health promotion: A scoping review (2024) · cites this paper as [63]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Scoping studies: towards a methodological framework
Arksey, H., & O'Malley, L. (2005) · International Journal of Social Research Methodology · doi:10.1080/1364557032000119616 · Cited by 36,742
International physical activity questionnaire: 12-country reliability and validity
CRAIG, C. L., MARSHALL, A. L., SJ??STR??M, M., BAUMAN, A. E., BOOTH, M. L., AINSWORTH, B. E., PRATT, M., EKELUND, U., YNGVE, A., SALLIS, J. F., et al. (2003) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000078924.61453.fb · Cited by 21,619
Scoping studies: advancing the methodology
Levac, D., Colquhoun, H., & O'Brien, K. K. (2010) · Implementation Science · doi:10.1186/1748-5908-5-69 · Cited by 15,268
CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials
the CONSORT Group, Schulz, K. F., Altman, D. G., & Moher, D. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-18 · Cited by 13,371
Developing and evaluating complex interventions: the new Medical Research Council guidance
Craig, P., Dieppe, P., Macintyre, S., Michie, S., Nazareth, I., & Petticrew, M. (2008) · BMJ · doi:10.1136/bmj.a1655 · Cited by 10,995
CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials
Schulz, K. F., Altman, D. G., Moher, D., & for the CONSORT Group (2010) · BMJ · doi:10.1136/bmj.c332 · Cited by 9,329
Global status report on noncommunicable diseases 2010.
Alwan, A. (2011) · Cited by 8,494
Guidance for conducting systematic scoping reviews
Peters, M. D. J., Godfrey, C. M., Khalil, H., McInerney, P., Parker, D., & Soares, C. B. (2015) · International Journal of Evidence-Based Healthcare · doi:10.1097/xeb.0000000000000050 · Cited by 7,472
Process evaluation of complex interventions: Medical Research Council guidance
Moore, G. F., Audrey, S., Barker, M., Bond, L., Bonell, C., Hardeman, W., Moore, L., O'Cathain, A., Tinati, T., Wight, D., et al. (2015) · BMJ · doi:10.1136/bmj.h1258 · Cited by 6,204
Usability Evaluation In Industry
(1996) · CRC Press eBooks · doi:10.1201/9781498710411 · Cited by 4,445
Research works printed but not linked: 6
- Blair, SN, 2009, Br J Sports Med, 43, 1
- 10.1007/978-3-642-27-2_39 · DOI
- Taylor, D, 2016, Stud Health Technol Inform, 220, 414
- Godin, G, 1985, Can J Appl Sport Sci, 10, 141
- ConnellyKOn developing a technology acceptance model for pervasive computingWorkshop of Ubiquitous System Evaluation (USE)20079th International Conference on Ubiquitous Computing (UBICOMP) 2007September 16-19Innsbruck, Austria
- Quesenbery, W, 2003, Content and complexity: Information design in technical communication, 81
Cited by
Sorted by citations
A Survey on Wearable Technology: History, State-of-the-Art and Current Challenges
Ometov, A., Shubina, V., Klus, L., Skibińska, J., Saafi, S., Pascacio, P., Flueratoru, L., Quezada-Gaibor, D., Chukhno, N., Chukhno, O., et al. (2021) · Computer Networks · doi:10.1016/j.comnet.2021.108074 · Cited by 572
Short, C. E., DeSmet, A., Woods, C., Williams, S. L., Maher, C., Middelweerd, A., Müller, A. M., Wark, P. A., Vandelanotte, C., Poppe, L., et al. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9397 · Cited by 400
Fitbit-based interventions for healthy lifestyle outcomes: systematic review and meta-analysis
Ringeval, M., Wagner, G., Denford, J., Paré, G., & Kitsiou, S. (2020) · Journal of Medical Internet Research · doi:10.2196/23954 · Cited by 225
Buckingham, S. A., Williams, A. J., Morrissey, K., Price, L., & Harrison, J. (2019) · Digital Health · doi:10.1177/2055207619839883 · Cited by 202
Liang, J., Xian, D., Liu, X., Fu, J., Zhang, X., Tang, B., & Lei, J. (2018) · JMIR mhealth and uhealth · doi:10.2196/11066 · Cited by 148
Domin, A., Spruijt‐Metz, D., Theisen, D., Ouzzahra, Y., & Vögele, C. (2021) · JMIR mhealth and uhealth · doi:10.2196/24308 · Cited by 126
Trends in Persuasive Technologies for Physical Activity and Sedentary Behavior: A Systematic Review
Aldenaini, N., Alqahtani, F., Orji, R., & Sampalli, S. (2020) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.00007 · Cited by 106
Shcherbina, A., Hershman, S. G., Lazzeroni, L., King, A. C., O'Sullivan, J. W., Hekler, E., Moayedi, Y., Pavlovic, A., Waggott, D., Sharma, A., et al. (2019) · The Lancet Digital Health · doi:10.1016/s2589-7500(19)30129-3 · Cited by 90
Wearable Sensors to Monitor, Enable Feedback, and Measure Outcomes of Activity and Practice
Dobkin, B. H., & Martinez, C. A. (2018) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-018-0896-5 · Cited by 79
Korpershoek, Y. J. G., Hermsen, S., Schoonhoven, L., Schuurmans, M. J., & Trappenburg, J. C. A. (2020) · Journal of Medical Internet Research · doi:10.2196/15449 · Cited by 78
“Can you see my screen?” Addressing Racial and Ethnic Disparities in Telehealth
Haynes, N., Ezekwesili, A. C., Nunes, K. L., Gumbs, E., Haynes, M., & Swain, J. D. (2021) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-021-00685-5 · Cited by 78
Bidargaddi, N., Pituch, T., Maaieh, H., Short, C., & Strecher, V. (2018) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2018.07.004 · Cited by 77
Heidel, A., & Hagist, C. (2020) · JMIR mhealth and uhealth · doi:10.2196/16444 · Cited by 72
Zahrt, O. H., Evans, K. M., Murnane, E. L., Santoro, E., Baiocchi, M., Landay, J. A., Delp, S. L., & Crum, A. J. (2022) · Journal of Medical Internet Research · doi:10.2196/40529 · Cited by 69
Sousa, A. C., Ferrinho, S. N., & Travassos, B. F. R. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20043402 · Cited by 63
Examining Responsiveness to an Incentive-Based Mobile Health App: Longitudinal Observational Study
Brower, J., LaBarge, M., White, L., & Mitchell, M. (2020) · Journal of Medical Internet Research · doi:10.2196/16797 · Cited by 58
Müller, A. M., Wang, N. X., Yao, J., Tan, C. S., Low, I. C. C., Lim, N., Tan, J., Tan, A. W. H., & Müller‐Riemenschneider, F. (2019) · JMIR mhealth and uhealth · doi:10.2196/14120 · Cited by 56
Šilarova, B., Nelis, S. M., Ashworth, R., Ballard, C. G., Bieńkiewicz, M., Henderson, C., Hillman, A., Hindle, J. V., Hughes, J. C., Lamont, R. A., et al. (2018) · BMC Public Health · doi:10.1186/s12889-018-6129-7 · Cited by 54
Baretta, D., Bondaronek, P., Direito, A., & Steca, P. (2019) · Digital Health · doi:10.1177/2055207619862706 · Cited by 53
Factors and Design Features Influencing the Continued Use of Wearable Devices
El-Gayar, O., & Elnoshokaty, A. (2023) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-023-00135-4 · Cited by 52
Behavior Change Techniques Incorporated in Fitness Trackers: Content Analysis
Chia, G. L. C., Anderson, A., & McLean, L. A. (2019) · JMIR mHealth and uHealth · doi:10.2196/12768 · Cited by 50
Düking, P., Stammel, C., Sperlich, B., Sutehall, S., Muñiz-Pardos, B., Lima, G. H. O., Kilduff, L. P., Keramitsoglou, I., Li, G., Pigozzi, F., et al. (2018) · Current Sports Medicine Reports · doi:10.1249/jsr.0000000000000495 · Cited by 50
Wiesner, M., Zowalla, R., Suleder, J., Westers, M., & Pobiruchin, M. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9623 · Cited by 46
Hawkins, J. L., Charles, J. M., Edwards, A., Hallingberg, B., McConnon, L., Edwards, R. T., Jago, R., Kelson, M. J., Morgan, K., Murphy, S., et al. (2018) · Journal of Medical Internet Research · doi:10.2196/12374 · Cited by 45
Understanding and Preventing Health Concerns About Emerging Mobile Health Technologies
Materia, F. T., Faasse, K., & Smyth, J. M. (2020) · JMIR mhealth and uhealth · doi:10.2196/14375 · Cited by 42
Ridgers, N. D., Timperio, A. F., Ball, K., Lai, S. K., Brown, H. L., Macfarlane, S., & Salmon, J. (2021) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-021-01110-1 · Cited by 42
Kwaśnicka, D., Keller, J., Perski, O., Potthoff, S., ten Hoor, G. A., Ainsworth, B., Crutzen, R., Dohle, S., van Dongen, A., Heino, M. T. J., et al. (2022) · Health Psychology Review · doi:10.1080/17437199.2022.2046482 · Cited by 42
Self-citationAlmoallim, S., & Sas, C. (2022) · JMIR Formative Research · doi:10.2196/31730 · Cited by 40
AlSwayied, G., Guo, H., Rookes, T., Frost, R., & Hamilton, F. L. (2022) · JMIR mhealth and uhealth · doi:10.2196/40271 · Cited by 40
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 40
User Experience & Usability of Wearable Health Device: A Bibliometric Analysis of 2014–2023
Hu, L., Chen, Y., Cao, E., & Hu, W. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2357905 · Cited by 39
Yfantidou, S., Sermpezis, P., & Vakali, A. I. (2023) · ACM Transactions on Computing for Healthcare · doi:10.1145/3592621 · Cited by 36
Moorthy, P., Weinert, L., Schüttler, C., Svensson, L., Sedlmayr, B., Müller, J., & Nagel, T. (2024) · JMIR mhealth and uhealth · doi:10.2196/52179 · Cited by 34
The Physical Activity Wearables in the Police Force (PAW-Force) study: acceptability and impact
Buckingham, S. A., Morrissey, K., Williams, A. J., Price, L., & Harrison, J. (2020) · BMC Public Health · doi:10.1186/s12889-020-09776-1 · Cited by 34
Baskan, A., & Göncü-Berk, G. (2022) · Applied Sciences · doi:10.3390/app122111154 · Cited by 32
Portz, J. D., Ford, K. L., Bekelman, D. B., Boxer, R. S., Kutner, J. S., Czaja, S. J., Elsbernd, K., & Bull, S. S. (2019) · Journal of Palliative Medicine · doi:10.1089/jpm.2019.0216 · Cited by 32
Pérez-Aranda, J., Robles, E. M. G., & Urbistondo, P. A. (2019) · Information Technology & Tourism · doi:10.1007/s40558-019-00161-2 · Cited by 24
Wang, J., Fang, Y., Frank, E., Walton, M. A., Burmeister, M., Tewari, A., Dempsey, W., NeCamp, T., Sen, S., & Wu, Z. (2023) · npj Digital Medicine · doi:10.1038/s41746-022-00746-y · Cited by 24
Social Networking App Use Among Primary Health Care Professionals: Web-Based Cross-Sectional Survey
Marin-Gomez, F. X., Cuyàs, F. G., Reig-Bolaño, R., Mendioroz, J., Poch, P. R., Pico-Nicolau, M., & Vidal‐Alaball, J. (2018) · JMIR mhealth and uhealth · doi:10.2196/11147 · Cited by 24
Domin, A., Uslu, A. S., Schulz, A., Ouzzahra, Y., & Vögele, C. (2022) · JMIR Formative Research · doi:10.2196/35118 · Cited by 24
Gao, Y., Zhang, J., He, Z., & Zhou, Z. (2025) · JMIR Serious Games · doi:10.2196/65498 · Cited by 22
Panicker, R. M., & Chandrasekaran, B. (2022) · Sport Sciences for Health · doi:10.1007/s11332-021-00885-x · Cited by 22
Liao, J., Xiao, H.-Y., Li, X., Shu-hua, S., Liu, S., Yang, Y., & Xu, D. R. (2020) · JMIR mhealth and uhealth · doi:10.2196/14969 · Cited by 22
Nadal, C., Earley, C., Enrique, Á., Sas, C., Richards, D., & Doherty, G. J. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3617361 · Cited by 20
Buckingham, S. A., Walker, T., Morrissey, K., & on behalf of the Smartline project team (2022) · Digital Health · doi:10.1177/20552076221074124 · Cited by 19
Guest, P. C., Vasilevska, V., Al-Hamadi, A. K., Eder, J., Falkai, P., & Steiner, J. H. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1227426 · Cited by 18
A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Dor‐Haim, H., Katzburg, S., & Leibowitz, D. W. (2019) · Journal of Visualized Experiments · doi:10.3791/59019 · Cited by 18
Hendker, A., Jetzke, M., Eils, E., & Voelcker‐Rehage, C. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17228532 · Cited by 18
Nadal, C., Earley, C., Enrique, Á., Viganò, N., Sas, C., Richards, D., & Doherty, G. J. (2021) · Contemporary Clinical Trials · doi:10.1016/j.cct.2021.106323 · Cited by 18
Saponaro, M., Vemuri, A. K., Dominick, G. M., & Decker, K. (2021) · ACM Conference on Health, Inference, and Learning (CHIL) · doi:10.1145/3450439.3451874 · Cited by 18
Measuring Health: Wearables in Fitness Tracking, Stress Relief, and Sleep Management
Sieniawska, J., Proszowska, P., Madoń, M., Kotowicz, Z., Orzeł, A., Pich-Czekierda, A., & Sieniawska, D. (2024) · Journal of Education Health and Sport · doi:10.12775/jehs.2024.67.003 · Cited by 17
Andreoni, G. (2023) · Applied Sciences · doi:10.3390/app13063595 · Cited by 16
Advantages and disadvantages of mobile applications for workplace health promotion: A scoping review
Junker, M., Böhm, M., & Krcmar, H. (2024) · PLoS ONE · doi:10.1371/journal.pone.0296212 · Cited by 21
“However, knowledge on these apps’ potential is lacking, particularly in regard to testing apps in practical settings and using objective data, and health apps generally are not evidence-based [63].”
BackgroundDanković, G., Stantić, T., Herodek, R., Stamenković, S., Stojiljković, N., Jelenković, B., & Sporiš, G. (2023) · Applied Sciences · doi:10.3390/app13127194 · Cited by 15
Design and Development of an Intelligent Skipping Rope and Service System for Pupils
Dong, Y., Wang, K., Zhu, S., Li, W., & Yang, P. (2021) · Healthcare · doi:10.3390/healthcare9080954 · Cited by 15
Use of workplace health promotion apps: Analysis of employee log data
Billmann, M., Böhm, M., & Krcmar, H. (2020) · Health Policy and Technology · doi:10.1016/j.hlpt.2020.06.003 · Cited by 14
Martinko, A., Karuc, J., Jurić, P., Podnar, H., & Sorić, M. (2022) · JMIR mhealth and uhealth · doi:10.2196/37547 · Cited by 14
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 14
Can self-monitoring mobile health apps reduce sedentary behavior? A randomized controlled trial
Yamamoto, K., Ebara, T., Matsuda, F., Matsukawa, T., Yamamoto, N., Ishii, K., Kurihara, T., Yamada, S., Matsuki, T., Tani, N., et al. (2020) · Journal of Occupational Health · doi:10.1002/1348-9585.12159 · Cited by 13
Daniels, K., Quadflieg, K., Robijns, J., Vry, J. D., Alphen, H. V., Beers, R. V., Sourbron, B., Vanbuel, A., Meekers, S., Mattheeussen, M., et al. (2025) · Sensors · doi:10.3390/s25030858 · Cited by 12
Chandrasekaran, B., Rao, C. R., Davis, F., & Arumugam, A. (2021) · Work · doi:10.3233/wor-213544 · Cited by 12
The Practicality of Mobile Applications in Healthcare Administration and COVID-19 Pandemic
Zamri, N., & Mohideen, F. B. S. (2021) · Ulum Islamiyyah · doi:10.33102/uij.vol33no1.300 · Cited by 12
A Systematic Literature Review on Computational Fashion Wearables
Jabari, S., Shaikh, A., Genç, Ç., Buruk, O., Virkki, J., & Hamari, J. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2269007 · Cited by 11
Sandham, M. H., Reed, K., Cowperthwait, L., Dawson, A., & Jarden, R. (2023) · Mayo Clinic Proceedings Digital Health · doi:10.1016/j.mcpdig.2023.05.006 · Cited by 11
Adopting wearables to customize health insurance contributions: a ranking-type Delphi
Neumann, D., Tiberius, V., & Biendarra, F. (2022) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-022-01851-4 · Cited by 10
Junker, M., Dünnebeil, S., Böhm, M., & Krcmar, H. (2023) · Health Informatics Journal · doi:10.1177/14604582221148058 · Cited by 10
E-Textiles: A Soft Touch Barometer for Female Students to Self-Manage Their Stress
Coulter, J. E., Magee, J., & Nugent, C. (2022) · Journal of Textile Design Research and Practice · doi:10.1080/20511787.2022.2128033 · Cited by 9
Mao, C., Bayer, J., Ross, M. Q., Rhee, L., Le, H., Mount, J., Chang, H.-C., Chang, Y.-J., Hedstrom, A., & Hovick, S. R. A. (2023) · Mobile Media & Communication · doi:10.1177/20501579221149823 · Cited by 9
Gutiérrez, S. A., Huilcapi-Collantes, C., Tinoco-Giraldo, H., Gándara-Tovar, A. J., & Barrera, D. M. R. (2021) · Ninth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM'21) · doi:10.1145/3486011.3486559 · Cited by 8
Ahraz, A. O., Çar, B., & Cengiz, C. (2021) · Ankara Üniversitesi Beden Eğitimi ve Spor Yüksekokulu SPORMETRE Beden Eğitimi ve Spor Bilimleri Dergisi · doi:10.33689/spormetre.905970 · Cited by 7
Clark, M., & Driller, M. W. (2020) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2019-0034 · Cited by 7
Zhang, X., & Liu, L. (2021) · International Conference on Forthcoming Networks and Sustainability in AIoT Era (FoNeS-AIoT) · doi:10.1109/fones-aiot54873.2021.00031 · Cited by 7
Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review
Leong, U., & Chakraborty, B. (2023) · JMIR mhealth and uhealth · doi:10.2196/44685 · Cited by 7
Acceptability of Persuasive Prompts to Induce Behavioral Change in People Suffering from Depression
Arshad, R., Baig, M. A., Tariq, M., & Shahid, S. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29390-1_7 · Cited by 6
Robertson, M. C., Swartz, M. C., Basen‐Engquist, K., Li, Y., Jennings, K., Thompson, D. I., Baranowski, T., Volpi, E., & Lyons, E. (2024) · BMC Public Health · doi:10.1186/s12889-024-19662-9 · Cited by 5
An N-of-1 Evaluation Framework for Behaviour Change Applications
McCallum, C., Rooksby, J., Asadzadeh, P., Gray, C. M., & Chalmers, M. (2019) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3290607.3312923 · Cited by 5
Self-citationA Tertiary Study on Quality in Use Evaluation of Smart Environment Applications
Angeloni, M. P. C., Duque, R., de Oliveira, K. M., Strugeon, E. G.-L., & Tîrnȃucȃ, C. (2024) · Lecture notes in business information processing · doi:10.1007/978-3-031-59465-6_8 · Cited by 5
Mähs, M., Pithan, J. S., Bergmann, I., Gabrys, L., Graf, J., Hölzemann, A., Van Laerhoven, K., Otto-Hagemann, S., Popescu, M. L., Schwermann, L., et al. (2022) · Trials · doi:10.1186/s13063-022-06550-z · Cited by 4
Alizadeh, A., Negarandeh, R., Amiri, F. B., & Yazdani, Z. (2021) · International Journal of Adolescent Medicine and Health · doi:10.1515/ijamh-2020-0302 · Cited by 4
Test-retest reliability of survey items on ownership and use of physical activity trackers
Ng, K., Baďura, P., Dzielska, A., Kokko, S. P., Woods, C. B., & Hamřík, Z. (2019) · Acta Gymnica · doi:10.5507/ag.2019.001 · Cited by 4
John, M., & Kleppisch, M. (2021) · Springer Reference Pflege, Therapie, Gesundheit · doi:10.1007/978-3-662-62426-5_108 · Cited by 4
Gait Pattern Differences Between Young Adults and Physically Active Older Adults
García-Gomáriz, C., Domínguez‐Navarro, F., Fernández-Benet, M. M., Blasco, J., Hernández‐Guillén, D., & Sanchis-Sales, E. (2025) · Medicina · doi:10.3390/medicina61101752 · Cited by 3
Exploring Novel Healthcare Monitoring Modalities: Wearable, Ingestible, and Implantable Biosensors
Scheidt, D. T., Moreli, M. L., Materón, E. M., Michilini, L. M., Carrilho, E., & Brazaca, L. C. (2025) · Springer eBooks · doi:10.1007/978-981-95-2117-3_5 · Cited by 3
Aplicativos de smartphones e atividades físicas:
Verzani, R. H., & Serapião, A. B. D. S. (2020) · Pensar a Prática · doi:10.5216/rpp.v23.59569 · Cited by 3
Mochizuki, L., & Araújo, B. A. (2021) · Modapalavra e-periódico · doi:10.5965/1982615x14322021030 · Cited by 3
Lifestyle-based health awareness using digital gadgets and online interactive platforms
Khan, I., Akhtar, S., & Khan, M. K. A. (2021) · NeuroPharmac Journal · doi:10.37881/1.638 · Cited by 3
Aktives Altern im digitalen Zeitalter
Ring‐Dimitriou, S., & Dimitriou, M. (2022) · Springer eBooks · doi:10.1007/978-3-658-34970-7 · Cited by 3
Dafny, H. A., Champion, S., Gebremichael, L. G., Pearson, V., Nesbitt, K., de Plaza, M. A. P., Bulto, L. N., Noonan, S., Hines, S. J., Hendriks, J., et al. (2022) · JBI Evidence Synthesis · doi:10.11124/jbies-22-00011 · Cited by 3
AnyMApp Framework: Anonymous Digital Twin Human-App Interactions
Ferreira, A., Chilro, R., & Cruz-Correia, R. J. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-17615-9_15 · Cited by 3
Medina‐Inojosa, J. R., Ibarra, M. A. G., Medina‐Inojosa, B. J., Supervía, M., Jenkins, S. M., Johnson, L., Moscoso, N. P. S., Bonikowske, A. R., Somers, V. K., & López-Jiménez, F. A. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.123.031228 · Cited by 3
Untangling the Puzzle of Digital Health Interventions
Simoski, B. (2022) · doi:10.5463/thesis.80 · Cited by 3
Mahmood, R., Hassan, R., Loo, F. L., & Ismail, M. R. (2024) · Malaysian Journal of Social Sciences and Humanities (MJSSH) · doi:10.47405/mjssh.v9i5.2719 · Cited by 2
Castro, M., Zavod, M. J., Rutgersson, A., Jörntén‐Karlsson, M., Dutta, B., & Hagger, L. (2024) · Journal of Asthma and Allergy · doi:10.2147/jaa.s458618 · Cited by 2
Understanding Design Features for Continued Use of Wearables Devices
El-Gayar, O., Elnoshokaty, A., & Behrens, A. (2021) · Journal of the Association for Information Systems · Cited by 2
Mobile Health Revolution in Healthcare: Are We Ready?
Claes, S. J., Berckmans, D., Geris, L., Myin‐Germeys, I., Audenhove, C. V., Diest, I. V., Hoof, C. A. V., Hoyweghen, I. V., Huffel, S. V., & Vrieze, E. (2019) · Lirias · Cited by 2
Soumaré, A., Fezeu, L., Bouchan, J., Delestre, F., Bellicha, A., Cardon, G., Donnelly, A., Hebestreit, A., Touvier, M., Oppert, J., et al. (2025) · JMIR Formative Research · doi:10.2196/76167 · Cited by 1
Tabacchi, G., Scardina, A., Amato, A., Giardina, M., Accardi, G., Liberto, V. D., Giglia, G., Vasto, S., Frinchi, M., Boffetta, P., et al. (2026) · JMIR Public Health and Surveillance · doi:10.2196/75769 · Cited by 1
Charitos, S., Thompson, L., Brigden, A., & Bird, J. (2026) · Journal of Medical Internet Research · doi:10.2196/79291 · Cited by 1
Hansen, S. T., Ehrari, H., Kristiansen, S., Olsen, L. S., Jensen, R. S., Kjær, T. W., & Beck, M. (2021) · Digital Health · doi:10.1177/20552076211045590 · Cited by 1
Technologiegestütztes funktionelles Training in den eigenen vier Wänden
Venek, V., & Rieser, H. (2022) · Springer eBooks · doi:10.1007/978-3-658-34970-7_6 · Cited by 1
Metadata
- Authors
- McCallum, C., Rooksby, J., & Gray, C. M.
- Affiliations
- University of Glasgow (GB)
- Corresponding author
- McCallum, Claire
- Venue
- JMIR mhealth and uhealth
- Publisher
- JMIR Publications Inc.
- Published
- 2018-03-23
- Volume
- 6
- Issue
- 3
- Pages
- e58
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC5889496
- OpenAlex
- W2789449717
- Cited by
- 126
- References
- 207
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 9 · 2023: 18 · 2022: 22 · 2021: 22 · 2020: 18 · 2019: 14 · 2018: 9
- FWCI
- 2.87
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- Northumbria Research Link (Northumbria University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Keywords
- physical activity apps, wearable devices, mobile health, single-case experimental design, multiphase optimization strategy, user engagement, acceptability, effectiveness, accelerometer, research design evaluation, physical activity monitoring
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
