Health App Use Among US Mobile Phone Owners: A National Survey
Open accessAbstract
BACKGROUND: Mobile phone health apps may now seem to be ubiquitous, yet much remains unknown with regard to their usage. Information is limited with regard to important metrics, including the percentage of the population that uses health apps, reasons for adoption/nonadoption, and reasons for noncontinuance of use. OBJECTIVE: The purpose of this study was to examine health app use among mobile phone owners in the United States. METHODS: We conducted a cross-sectional survey of 1604 mobile phone users throughout the United States. The 36-item survey assessed sociodemographic characteristics, history of and reasons for health app use/nonuse, perceived effectiveness of health apps, reasons for stopping use, and general health status. RESULTS: A little over half (934/1604, 58.23%) of mobile phone users had downloaded a health-related mobile app. Fitness and nutrition were the most common categories of health apps used, with most respondents using them at least daily. Common reasons for not having downloaded apps were lack of interest, cost, and concern about apps collecting their data. Individuals more likely to use health apps tended to be younger, have higher incomes, be more educated, be Latino/Hispanic, and have a body mass index (BMI) in the obese range (all P<.05). Cost was a significant concern among respondents, with a large proportion indicating that they would not pay anything for a health app. Interestingly, among those who had downloaded health apps, trust in their accuracy and data safety was quite high, and most felt that the apps had improved their health. About half of the respondents (427/934, 45.7%) had stopped using some health apps, primarily due to high data entry burden, loss of interest, and hidden costs. CONCLUSIONS: These findings suggest that while many individuals use health apps, a substantial proportion of the population does not, and that even among those who use health apps, many stop using them. These data suggest that app developers need to better address consumer concerns, such as cost and high data entry burden, and that clinical trials are necessary to test the efficacy of health apps to broaden their appeal and adoption.
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The review added measures such as Flesch-Kincaid metrics and the IMS, which have not been employed in previous app reviews.
“Strengths include the addition of measures, such as the Flesch-Kincaid metrics and the IMS, which have not been employed in previous app reviews [16,21,22].”
From Patient-facing cancer mobile apps that enable patient reported outcome data to be collected: A systematic review of content, functionality, quality, and ability to integrate with electronic health records (2023) · cites this paper as [16]
The Results section reports survey respondents’ health-app use and preferences, while the Discussion’s Future Directions section discusses evidence for apps and expert-panel reviews. Neither addresses whether previous app reviews used Flesch-Kincaid metrics or the IMS; searches for those measures and app-review methods found no relevant passage. (LLM, conf=0.76)
Experimental — accuracy not yet measuredAround half of all mHealth app users stop engaging for various reasons, including loss of interest.
“One study revealed that around half of all mHealth app users stop engaging for various reasons, including loss of interest [14].”
From Usability of Mobile Health Apps for Postoperative Care: Systematic Review (2020) · cites this paper as [14]
The widespread use of smartphones makes app-based intervention delivery a viable and scalable medium.
“The widespread use of smartphones makes app-based intervention delivery a viable and scalable medium.”
From A Therapeutic Relational Agent for Reducing Problematic Substance Use (Woebot): Development and Usability Study (2021) · cites this paper as [10]
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Cites
A General Inductive Approach for Analyzing Qualitative Evaluation Data
Thomas, D. R. (2006) · American Journal of Evaluation · doi:10.1177/1098214005283748 · Cited by 10,858 · see citing works
Mobile medical and health apps: state of the art, concerns, regulatory control and certification
Kamel Boulos, M. N., Brewer, A. C., Karimkhani, C., Buller, D. B., & Dellavalle, R. P. (2014) · Online Journal of Public Health Informatics · doi:10.5210/ojphi.v5i3.4814 · Cited by 659 · see citing works
Arnhold, M., Quade, M., & Kirch, W. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.2968 · Cited by 417 · see citing works
Bender, J. L., Yue, R. Y. K., To, M. J., Deacken, L., & Jadad, A. R. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2661 · Cited by 346 · see citing works
Chuah, S. H., Rauschnabel, P. A., Krey, N., Nguyen, B., Ramayah, T., & Lade, S. (2016) · Rowan Digitals Works (Rowan University) · Cited by 213 · see citing works
Knight, E., Stuckey, M. I., Prapavessis, H., & Petrella, R. J. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.4003 · Cited by 112 · see citing works
Smartphone Medical Applications for Women’s Health: What Is the Evidence-Base and Feedback?
Derbyshire, E. J., & Dancey, D. (2013) · International Journal of Telemedicine and Applications · doi:10.1155/2013/782074 · Cited by 99 · see citing works
Smartphones and Pediatric Apps to Mobilize the Medical Home
Singh, A., Wilkinson, S., & Braganza, S. F. (2014) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2014.05.037 · Cited by 61 · see citing works
Using MapMyFitness to Place Physical Activity into Neighborhood Context
Hirsch, J. A., James, P., Robinson, J. R. M., Eastman, K. M., Conley, K. D., Evenson, K. R., & Laden, F. (2014) · Frontiers in Public Health · doi:10.3389/fpubh.2014.00019 · Cited by 38 · see citing works
High Quantity But Limited Quality in Healthcare Applications Intended for HIV-Infected Patients
Cortés, M. D. L. A. R., Cuenca, M. R. C., Verdugo, R. M., & Cidoncha, E. C. (2014) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2013.0262 · Cited by 26 · see citing works
Integrating Mobile Fitness Trackers Into the Practice of Medicine
Ahuja, N. K., Ozdalga, E., & Aaronson, A. J. (2015) · American Journal of Lifestyle Medicine · doi:10.1177/1559827615583643 · Cited by 11 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [9]Zhao K Proper estimation of relative risk using PROC GENMOD in population studies Proceedings of the Western Users of SAS Software Conference 2013 Western Users of SAS Software Conference November 13-15, 2013 Las Vegas, NV 1 14
Cited by
Sorted by citations
Torous, J., Nicholas, J., Larsen, M. E., Firth, J., & Christensen, H. (2018) · Evidence Based Mental Health · doi:10.1136/eb-2018-102891 · Cited by 790 · see citing works
The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study
Zhou, L., Bao, J., Setiawan, I. M. A., Saptono, A., & Parmanto, B. (2019) · JMIR mHealth and uHealth · doi:10.2196/11500 · Cited by 675 · see citing works
Shcherbina, A., Mattsson, C., Waggott, D., Salisbury, H., Christle, J., Hastie, T., Wheeler, M., & Ashley, E. (2017) · Journal of Personalized Medicine · doi:10.3390/jpm7020003 · Cited by 625 · see citing works
Torous, J., Lipschitz, J., Ng, M., & Firth, J. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.11.167 · Cited by 546 · see citing works
Mobile Health Apps to Facilitate Self-Care: A Qualitative Study of User Experiences
Anderson, K., Burford, O., & Emmerton, L. (2016) · PLOS ONE · doi:10.1371/journal.pone.0156164 · Cited by 502 · see citing works
Huberty, J., Green, J., Glissmann, C., Larkey, L., Puzia, M., & Lee, C. (2019) · JMIR mHealth and uHealth · doi:10.2196/14273 · Cited by 488 · see citing works
New technologies, new disparities: The intersection of electronic health and digital health literacy
Smith, B., & Magnani, J. W. (2019) · International Journal of Cardiology · doi:10.1016/j.ijcard.2019.05.066 · Cited by 446 · see citing works
Sullivan, A. N., & Lachman, M. E. (2017) · Frontiers in Public Health · doi:10.3389/fpubh.2016.00289 · Cited by 458 · see citing works
Using smartphones and health apps to change and manage health behaviors: a population-based survey
Ernsting, C., Dombrowski, S. U., Oedekoven, M., O´Sullivan, J. L., Kanzler, M., Kuhlmey, A., & Gellert, P. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6838 · Cited by 400 · see citing works
The Handbook of Behavior Change
Hagger, M. S., Cameron, L. D., Hamilton, K., Hankonen, N. E., & Lintunen, T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318 · Cited by 420 · see citing works
Morawski, K., Ghazinouri, R., Krumme, A., Lauffenburger, J. C., Lu, Z., Durfee, E., Oley, L., Lee, J., Mohta, N., Haff, N., et al. (2018) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.0447 · Cited by 333 · see citing works
IntelliCare: An Eclectic, Skills-Based App Suite for the Treatment of Depression and Anxiety
Mohr, D. C., Tomasino, K. N., Lattie, E. G., Palac, H. L., Kwasny, M. J., Weingardt, K., Karr, C. J., Kaiser, S. M., Rossom, R. C., Bardsley, L. R., et al. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6645 · Cited by 301 · see citing works
The Continued Use of Mobile Health Apps: Insights From a Longitudinal Study
Vaghefi, I., & Tulu, B. (2019) · JMIR mhealth and uhealth · doi:10.2196/12983 · Cited by 341 · see citing works
Okumuş, B., Ali, F., Bilgihan, A., & Ozturk, A. B. (2018) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2018.01.001 · Cited by 339 · see citing works
Use of Digital Mental Health for Marginalized and Underserved Populations
Schueller, S. M., Hunter, J. F., Figueroa, C., & Aguilera, A. (2019) · Current Treatment Options in Psychiatry · doi:10.1007/s40501-019-00181-z · Cited by 268 · see citing works
Changing Behavior Using the Theory of Planned Behavior
Ajzen, I., & Schmidt, P. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.002 · Cited by 303 · see citing works
Prochaska, J. J., Vogel, E. A., Chieng, A., Kendra, M., Baiocchi, M., Pajarito, S., & Robinson, A. (2021) · Journal of Medical Internet Research · doi:10.2196/24850 · Cited by 257 · see citing works
Zhou, L., Bao, J., Watzlaf, V., & Parmanto, B. (2019) · JMIR mHealth and uHealth · doi:10.2196/11223 · Cited by 246 · see citing works
Wei, Y., Zheng, P., Deng, H., Wang, X., Li, X., & Fu, H. (2020) · Journal of Medical Internet Research · doi:10.2196/21687 · Cited by 238 · see citing works
Lipschitz, J. M., Pike, C. K., Hogan, T. P., Murphy, S. A., & Burdick, K. E. (2023) · Current Treatment Options in Psychiatry · doi:10.1007/s40501-023-00297-3 · Cited by 230 · see citing works
Hui, C. Y., Walton, R., McKinstry, B., Jackson, T., Parker, R., & Pinnock, H. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw143 · Cited by 198 · see citing works
Maximizing the Impact of e-Therapy and Serious Gaming: Time for a Paradigm Shift
Fleming, T. M., de Beurs, D., Khazaal, Y., Gaggioli, A., Riva, G., Botella, C., Baños, R. M., Aschieri, F., Bavin, L. M., Kleiboer, A., et al. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00065 · Cited by 212 · see citing works
Effects of Social Media and Mobile Health Apps on Pregnancy Care: Meta-Analysis
Chan, K. L., & Chen, M. (2018) · JMIR mhealth and uhealth · doi:10.2196/11836 · Cited by 221 · see citing works
Chiu, W., Cho, H., & Chi, C. G.-Q. (2020) · Information Technology and People · doi:10.1108/itp-09-2019-0463 · Cited by 226 · see citing works
Linardon, J., Torous, J. B., Firth, J., Cuijpers, P. J., Messer, M., & Fuller‐Tyszkiewicz, M. (2024) · World Psychiatry · doi:10.1002/wps.21183 · Cited by 231 · see citing works
Use of Mobile Health Applications for Health-Seeking Behavior Among US Adults
Bhuyan, S. S., Lu, N., Chandak, A., Kim, H., Wyant, D., Bhatt, J., Kedia, S., & Chang, C. F. (2016) · Journal of Medical Systems · doi:10.1007/s10916-016-0492-7 · Cited by 210 · see citing works
Lipschitz, J., Miller, C. J., Hogan, T. P., Burdick, K. E., Lippin-Foster, R., Simon, S. R., & Burgess, J. (2019) · JMIR Mental Health · doi:10.2196/11334 · Cited by 183 · see citing works
Huang, G., & Ren, Y. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.09.013 · Cited by 218 · see citing works
Stawarz, K., Preist, C., Tallon, D., Wiles, N., & Coyle, D. (2018) · Journal of Medical Internet Research · doi:10.2196/10120 · Cited by 198 · see citing works
Lau, N., O'Daffer, A., Colt, S., Yi-Frazier, J. P., Palermo, T. M., McCauley, E., & Rosenberg, A. R. (2020) · JMIR mhealth and uhealth · doi:10.2196/17798 · Cited by 174 · see citing works
Schueller, S. M., Neary, M., O'Loughlin, K., & Adkins, E. C. (2018) · Journal of Medical Internet Research · doi:10.2196/10141 · Cited by 167 · see citing works
By the numbers: ratings and utilization of behavioral health mobile applications
Carlo, A. D., Hosseini Ghomi, R., Renn, B. N., & Areán, P. A. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0129-6 · Cited by 164 · see citing works
The history and future of digital health in the field of behavioral medicine
Arigo, D., Jake‐Schoffman, D. E., Wolin, K. Y., Beckjord, E. B., Hekler, E. B., & Pagoto, S. (2019) · Journal of Behavioral Medicine · doi:10.1007/s10865-018-9966-z · Cited by 189 · see citing works
Healthcare 4.0: A review of frontiers in digital health
Jayaraman, P. P., Forkan, A. R. M., Morshed, A., Haghighi, P. D., & Kang, Y. (2019) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1350 · Cited by 191 · see citing works
Liu, K., Xie, Z., & Or, C. K. (2020) · JMIR mHealth and uHealth · doi:10.2196/15779 · Cited by 181 · see citing works
Bauer, M., Glenn, T., Geddes, J., Gitlin, M., Grof, P., Kessing, L. V., Monteith, S., Faurholt-Jepsen, M., Severus, E., & Whybrow, P. C. (2020) · International Journal of Bipolar Disorders · doi:10.1186/s40345-019-0164-x · Cited by 163 · see citing works
A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study
Naughton, F., Hopewell, S., Lathia, N., Schalbroeck, R., Brown, C., Cecilia Mascolo, C., McEwen, A., & Sutton, S. R. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.5787 · Cited by 173 · see citing works
Garrison, K. A., Pal, P., O’Malley, S. S., Pittman, B. P., Gueorguieva, R., Rojiani, R., Scheinost, D., Dallery, J., & Brewer, J. A. (2020) · Nicotine and Tobacco Research · doi:10.1093/ntr/nty126 · Cited by 155 · see citing works
Methods for Evaluating the Content, Usability, and Efficacy of Commercial Mobile Health Apps
Jake-Schoffman, D. E., Silfee, V. J., Waring, M. E., Boudreaux, E. D., Sadasivam, R. S., Mullen, S. P., Carey, J. L., Hayes, R. B., Ding, E. Y., Bennett, G. G., et al. (2017) · JMIR mHealth and uHealth · doi:10.2196/mhealth.8758 · Cited by 165 · see citing works
Awareness and Use of mHealth Apps: A Study from England
Kayyali, R., Peletidi, A., Ismail, M. F., Hashim, Z., Bandeira, P., & Bonnah, J. (2017) · Pharmacy · doi:10.3390/pharmacy5020033 · Cited by 158 · see citing works
Barriers to and Facilitators for Using Nutrition Apps: Systematic Review and Conceptual Framework
König, L. M., Attig, C., Franke, T., & Renner, B. (2021) · JMIR mhealth and uhealth · doi:10.2196/20037 · Cited by 152 · see citing works
Wang, C., & Qi, H. (2021) · Healthcare · doi:10.3390/healthcare9030357 · Cited by 157 · see citing works
Fernández, C. E., Maturana, C. A., Coloma, S. I., Carrasco-Labra, A., & Giacaman, R. A. (2021) · Journal of Dental Research · doi:10.1177/00220345211003828 · Cited by 152 · see citing works
Utilizing Digital Health Technologies for Patient Education in Lifestyle Medicine
Kuwabara, A. M., Su, S., & Krauss, J. (2019) · American Journal of Lifestyle Medicine · doi:10.1177/1559827619892547 · Cited by 156 · see citing works
Attié, E. A., & Meyer‐Waarden, L. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121485 · Cited by 154 · see citing works
Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status
Robbins, R., Krebs, P. M., Jagannathan, R., Jean‐Louis, G., & Duncan, D. T. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.7832 · Cited by 144 · see citing works
Self-citationA Review of the Quality and Impact of Mobile Health Apps
Grundy, Q. (2021) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-052020-103738 · Cited by 153 · see citing works
Changing Behavior Using the Model of Action Phases
Keller, L., Gollwitzer, P. M., & Sheeran, P. (2020) · The Handbook of Behavior Change · doi:10.1017/9781108677318.006 · Cited by 147 · see citing works
Application of Internet of Things and artificial intelligence for smart fitness: A survey
Farrokhi, A., Farahbakhsh, R., Rezazadeh, J., & Minerva, R. (2021) · Computer Networks · doi:10.1016/j.comnet.2021.107859 · Cited by 153 · see citing works
Prevalence of Health App Use Among Older Adults in Germany: National Survey
Rasche, P., Wille, M., Bröhl, C., Theis, S., Schäfer, K., Knobe, M., & Mertens, A. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.8619 · Cited by 142 · see citing works
Understanding and Predicting the Adoption of Fitness Mobile Apps: Evidence from China
Wei, J., Vinnikova, A., Lu, L., & Xu, J. (2020) · Health Communication · doi:10.1080/10410236.2020.1724637 · Cited by 145 · see citing works
Kim, K.-H., Kim, K.-J., Lee, D.-H., & Kim, M.-G. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2018.12.008 · Cited by 140 · see citing works
Desveaux, L., Shaw, J., Saragosa, M., Soobiah, C., Marani, H., Hensel, J. M., Agarwal, P., Onabajo, N., Bhatia, R. S., & Jeffs, L. P. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8712 · Cited by 132 · see citing works
User Engagement and Abandonment of mHealth: A Cross-Sectional Survey
Mustafa, A. S., Ali, N. B., Dhillon, J. S., Alkawsi, G. A., & Baashar, Y. M. (2022) · Healthcare · doi:10.3390/healthcare10020221 · Cited by 135 · see citing works
Mahmood, A., Kedia, S., Wyant, D. K., Ahn, S., & Bhuyan, S. S. (2019) · Digital Health · doi:10.1177/2055207619882181 · Cited by 132 · see citing works
Dao, K. P., Cocker, K. A. D., Tong, H. L., Kocaballi, A. B., Chow, C. K., & Laranjo, L. (2021) · JMIR mhealth and uhealth · doi:10.2196/22890 · Cited by 133 · see citing works
Health Literacy in African-American Communities: Barriers and Strategies
Muvuka, B., Combs, R. M., Ayangeakaa, S., Ali, N. M., Wendel, M. L., & Jackson, T. (2020) · HLRP Health Literacy Research and Practice · doi:10.3928/24748307-20200617-01 · Cited by 133 · see citing works
Alhammad, N. J., Alajlani, M., Abd-Alrazaq, A. A., Epiphaniou, G., & Arvanitis, T. N. (2024) · Journal of Medical Internet Research · doi:10.2196/50715 · Cited by 145 · see citing works
The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition
Limketkai, B. N., Mauldin, K., Manitius, N., Jalilian, L., & Salonen, B. R. (2021) · Current Surgery Reports · doi:10.1007/s40137-021-00297-3 · Cited by 128 · see citing works
Feng, W., Tu, R., & Hsieh, P.-S. (2020) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102229 · Cited by 130 · see citing works
Birkhoff, S. D., & Smeltzer, S. C. (2017) · Journal of Nursing Scholarship · doi:10.1111/jnu.12298 · Cited by 121 · see citing works
Rosen, K. D., Paniagua, S. M., Kazanis, W., Jones, S., & Potter, J. S. (2018) · Psycho-Oncology · doi:10.1002/pon.4764 · Cited by 106 · see citing works
Smartphone apps and the nutrition care process: Current perspectives and future considerations
Chen, J., Gemming, L., Hanning, R. M., & Allman-Farinelli, M. A. (2017) · Patient Education and Counseling · doi:10.1016/j.pec.2017.11.011 · Cited by 116 · see citing works
Wong, C. A., Madanay, F. L., Ozer, E. M., Harris, S. K., Moore, M., Master, S. O., Moreno, M. A., & Weitzman, E. R. (2020) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2019.10.018 · Cited by 119 · see citing works
Stawarz, K., Preist, C., & Coyle, D. (2019) · JMIR Mental Health · doi:10.2196/12546 · Cited by 107 · see citing works
Uptake and usage of IntelliCare: A publicly available suite of mental health and well-being apps
Lattie, E. G., Schueller, S. M., Sargent, E., Stiles-Shields, C., Tomasino, K. N., Corden, M. E., Begale, M., Karr, C. J., & Mohr, D. C. (2016) · Internet Interventions · doi:10.1016/j.invent.2016.06.003 · Cited by 113 · see citing works
Studying health-related internet and mobile device use using web logs and smartphone records
Bach, R. L., & Wenz, A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0234663 · Cited by 114 · see citing works
Understanding the quality, effectiveness and attributes of top-rated smartphone health apps
Wisniewski, H., Liu, G., Henson, P., Vaidyam, A., Hajratalli, N. K., Onnela, J.-P., & Torous, J. (2019) · Evidence Based Mental Health · doi:10.1136/ebmental-2018-300069 · Cited by 112 · see citing works
Robillard, J. M., Feng, T. L., Sporn, A. B., Lai, J.-A., Lo, C., Ta, M., & Nadler, R. (2019) · Internet Interventions · doi:10.1016/j.invent.2019.100243 · Cited by 111 · see citing works
Lobelo, F., Kelli, H. M., Tejedor, S. C., Pratt, M., McConnell, M. V., Martin, S. S., & Welk, G. J. (2016) · Progress in Cardiovascular Diseases · doi:10.1016/j.pcad.2016.02.007 · Cited by 113 · see citing works
Exploring Digital Health Use and Opinions of University Students: Field Survey Study
Montagni, I., Cariou, T., Feuillet, T., Langlois, E., & Tzourio, C. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9131 · Cited by 110 · see citing works
Zhang, Y., Li, X., Luo, S., Liu, C., Xie, Y., Guo, J., Liu, F., & Zhou, Z. (2019) · JMIR mhealth and uhealth · doi:10.2196/12658 · Cited by 109 · see citing works
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Schwarzer, R., & Hamilton, K. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.007 · Cited by 107 · see citing works
Samoggia, A., & Riedel, B. (2019) · Food Research International · doi:10.1016/j.foodres.2019.108766 · Cited by 116 · see citing works
Knowledge and Attitude Regarding Telemedicine Among Doctors in Karachi
Ashfaq, A., Memon, S. F., Zehra, A., Barry, S., Jawed, H., Akhtar, M., Kirmani, W., Malik, F., Khawaja, A. M., Barry, H., et al. (2020) · Cureus · doi:10.7759/cureus.6927 · Cited by 108 · see citing works
The Determinants of M-Health Adoption in Developing Countries: An Empirical Investigation
Alaiad, A., Alsharo, M., & Alnsour, Y. (2019) · Applied Clinical Informatics · doi:10.1055/s-0039-1697906 · Cited by 115 · see citing works
Carreiro, S., Newcomb, M., Leach, R., Ostrowski, S. J., Boudreaux, E. D., & Amante, D. J. (2020) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2020.108201 · Cited by 108 · see citing works
Bry, L. J., Chou, T., Miguel, E. M., & Comer, J. S. (2017) · Behavior Therapy · doi:10.1016/j.beth.2017.07.008 · Cited by 103 · see citing works
Cho, H., Chi, C. G.-Q., & Chiu, W. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101429 · Cited by 114 · see citing works
Digital interventions to improve adherence to maintenance medication in asthma
Chan, A., De Simoni, A., Wileman, V., Holliday, L., Newby, C. J., Chisari, C., Ali, S., Zhu, N., Padakanti, P., Pinprachanan, V., et al. (2022) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd013030.pub2 · Cited by 105 · see citing works
Torous, J., Firth, J., Huckvale, K., Larsen, M. E., Cosco, T. D., Carney, R., Chan, S., Pratap, A., Yellowlees, P., Wykes, T., et al. (2018) · Journal of Nervous & Mental Disease · doi:10.1097/nmd.0000000000000864 · Cited by 101 · see citing works
A review of mobile apps for epilepsy self-management
Escoffery, C., McGee, R. E., Bidwell, J., Sims, C., Thropp, E. K., Frazier, C., & Mynatt, E. D. (2018) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2017.12.010 · Cited by 102 · see citing works
Crane, D., Garnett, C., Brown, J., West, R., & Michie, S. (2017) · Frontiers in Public Health · doi:10.3389/fpubh.2017.00039 · Cited by 82 · see citing works
Li, K., Urteaga, I., Wiggins, C. H., Druet, A., Shea, A. A., Vitzthum, V. J., & Elhadad, N. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0269-8 · Cited by 100 · see citing works
Understanding People’s Use of and Perspectives on Mood-Tracking Apps: Interview Study
Schueller, S. M., Neary, M., Lai, J., & Epstein, D. A. (2021) · JMIR Mental Health · doi:10.2196/29368 · Cited by 102 · see citing works
Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach
König, L. M., Sproesser, G., Schupp, H. T., & Renner, B. (2018) · JMIR mHealth and uHealth · doi:10.2196/mhealth.8261 · Cited by 98 · see citing works
A mobile app–based intervention for depression: end-user and expert usability testing study
Fuller-Tyszkiewicz, M., Richardson, B., Klein, B., Skouteris, H., Christensen, H., Austin, D., Castle, D., Mihalopoulos, C., O'Donnell, R., Arulkadacham, L., et al. (2018) · JMIR Mental Health · doi:10.2196/mental.9445 · Cited by 98 · see citing works
Common Barriers to the Use of Patient-Generated Data Across Clinical Settings
West, P. A., Kleek, M. G. V., Giordano, R., Weal, M. J., & Shadbolt, N. (2018) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3174058 · Cited by 95 · see citing works
Mental health apps in a college setting: openness, usage, and attitudes.
Kern, A., Hong, V., Song, J., Lipson, S., & Eisenberg, D. (2018) · mHealth · doi:10.21037/mhealth.2018.06.01 · Cited by 96 · see citing works
Use of eHealth and mHealth technology by persons with multiple sclerosis
Marrie, R. A., Leung, S., Tyry, T. M., Cutter, G., Fox, R. J., & Salter, A. R. (2018) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2018.09.036 · Cited by 95 · see citing works
Wykes, T., & Schueller, S. M. (2019) · Journal of Medical Internet Research · doi:10.2196/12390 · Cited by 95 · see citing works
A mixed methods exploratory study of women’s relationships with and uses of fertility tracking apps
Gambier-Ross, K., McLernon, D. J., & Morgan, H. M. (2018) · Digital Health · doi:10.1177/2055207618785077 · Cited by 94 · see citing works
GUILeak: Tracing Privacy Policy Claims on User Input Data for Android Applications
Wang, X.-Y., Qin, X., Hosseini, M., Slavin, R., Breaux, T., & Niu, J.-W. (2018) · International Conference on Software Engineering · doi:10.1145/3180155.3180196 · Cited by 128 · see citing works
Lordon, R. J., Mikles, S. P., Kneale, L., Evans, H. L., Munson, S. A., Backonja, U., & Lober, W. B. (2020) · Health Informatics Journal · doi:10.1177/1460458220928184 · Cited by 93 · see citing works
Eaton, C. K., Vallejo, N., McDonald, X., Wu, J., Rodríguez, R., Muthusamy, N., Mathioudakis, N. N., & Riekert, K. A. (2024) · Journal of Medical Internet Research · doi:10.2196/50508 · Cited by 108 · see citing works
mHealth and telemedicine apps: in search of a common regulation
Crico, C., Renzi, C., Graf, N., Buyx, A., Kondylakis, H., Koumakis, L., & Pravettoni, G. (2018) · ecancermedicalscience · doi:10.3332/ecancer.2018.853 · Cited by 83 · see citing works
Byambasuren, O., Beller, E., Hoffmann, T., & Glasziou, P. (2020) · JMIR mhealth and uhealth · doi:10.2196/17447 · Cited by 92 · see citing works
Factors Influencing Continued Usage Behavior on Mobile Health Applications
Wu, P., Zhang, R., Zhu, X., & Liu, M. (2022) · Healthcare · doi:10.3390/healthcare10020208 · Cited by 100 · see citing works
Molina‐Recio, G., Molina‐Luque, R., Jiménez-García, A. M., Ventura-Puertos, P. E., Hernández-Reyes, A., & Romero‐Saldaña, M. (2020) · JMIR mhealth and uhealth · doi:10.2196/14376 · Cited by 89 · see citing works
- Authors
- Krebs, P., & Duncan, D. T.
- Affiliations
- VA NY Harbor Healthcare System (US)
- New York University (US)
- Corresponding author
- Krebs, Paul
- Venue
- JMIR mHealth and uHealth
- Publisher
- JMIR Publications Inc.
- Published
- 2015-11-04
- Volume
- 3
- Issue
- 4
- Pages
- e101
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC4704953
- OpenAlex
- W2126335261
- Cited by
- 1,274
- References
- 11
- Citations by year
- 2026: 47 · 2025: 98 · 2024: 101 · 2023: 128 · 2022: 127 · 2021: 156 · 2020: 211 · 2019: 140 · 2018: 151 · 2017: 85 · 2016: 28
- FWCI
- 160.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Verizon Foundation
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- health apps, mobile health, app adoption, fitness apps, nutrition apps, data privacy concerns, app cost, obesity
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