Can Mobile Health Technologies Transform Health Care?

The Economic Burden of Non–Influenza-Related Viral Respiratory Tract Infection in the United States

Fendrick, A. M., Monto, A. S., Nightengale, B. S., & Sarnes, M. W. (2003) · Archives of Internal Medicine · doi:10.1001/archinte.163.4.487 · Cited by 865

Effect of telehealth on use of secondary care and mortality: findings from the Whole System Demonstrator cluster randomised trial

Steventon, A., Bardsley, M., Billings, J., Dixon, J., Doll, H., Hirani, S., Cartwright, M., Rixon, L., Knapp, M., Henderson, C., et al. (2012) · BMJ · doi:10.1136/bmj.e3874 · Cited by 583

In Search of Joy in Practice: A Report of 23 High-Functioning Primary Care Practices

Sinsky, C. A., Willard‐Grace, R., Schutzbank, A. M., Sinsky, T. A., Margolius, D., & Bodenheimer, T. (2013) · The Annals of Family Medicine · doi:10.1370/afm.1531 · Cited by 445

Diagnostic Inaccuracy of Smartphone Applications for Melanoma Detection

Wolf, J. A., Moreau, J. F., Akilov, O., Patton, T., English, J. C., Ho, J., & Ferris, L. K. (2013) · JAMA Dermatology · doi:10.1001/jamadermatol.2013.2382 · Cited by 393

What Do Smokers Want in A Smartphone-Based Cessation Application?

Oliver, J. A., Hallyburton, M. B., Pacek, L. R., Mitchell, J. T., Vilardaga, R., Fuemmeler, B. F., & McClernon, F. J. (2017) · Nicotine & Tobacco Research · doi:10.1093/ntr/ntx171 · Cited by 21

Challenges in mobile health app research: Strategies for interprofessional researchers

Birkhoff, S. D., & Moriarty, H. (2020) · Journal of Interprofessional Education & Practice · doi:10.1016/j.xjep.2020.100325 · Cited by 22

Health Tracking via Mobile Apps for Depression Self-management: Qualitative Content Analysis of User Reviews

Polhemus, A. M., Simblett, S. K., Dawe‐Lane, E., Gilpin, G., Elliott, B., Jilka, S., Novák, J. M., Nica, R. I., Temesi, G., & Wykes, T. (2022) · JMIR Human Factors · doi:10.2196/40133 · Cited by 25

The Next Frontier in Sarcoma Care: Digital Health, AI, and the Quest for Precision Medicine

Fuchs, B., Studer, G., Bode‐Lesniewska, B., Heesen, P., & on behalf of the Swiss Sarcoma Network (2023) · Journal of Personalized Medicine · doi:10.3390/jpm13111530 · Cited by 20

A Summary of the American Society of Echocardiography Foundation Value-Based Healthcare: Summit 2014

Byrd, B. F., Abraham, T. P., Buxton, D. B., Coletta, A. V., Cooper, J. H. S., Douglas, P. S., Gillam, L. D., Goldstein, S. A., Graf, T. R., Horton, K. D., et al. (2015) · Journal of the American Society of Echocardiography · doi:10.1016/j.echo.2015.05.007 · Cited by 19

Practical considerations in the design and development of smartphone apps for behavior change

Roth, W. R., Vilardaga, R., Wolfe, N., Bricker, J. B., & McDonell, M. G. (2014) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2014.08.006 · Cited by 19

Integrating enterprise risk management to address AI‐related risks in healthcare: Strategies for effective risk mitigation and implementation

Palma, G. D., Scendoni, R., Tambone, V., Alloni, R., & Micco, F. D. (2025) · Journal of Healthcare Risk Management · doi:10.1002/jhrm.70000 · Cited by 24

AI for mental health: clinician expectations and priorities in computational psychiatry

Fischer, L., Mann, P. A., Nguyen, M.-H. H., Becker, S., Khodadadi, S. H. A., Schulz, A., Thanarajah, S. E., Repple, J., Hahn, T., Reif, A., et al. (2025) · BMC Psychiatry · doi:10.1186/s12888-025-06957-3 · Cited by 23

Digital Connectedness in the Framingham Heart Study

Fox, C. S., Hwang, S., Nieto, K., Valentino, M., Mutalik, K. M., Massaro, J. M., Benjamin, E. J., & Murabito, J. M. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.116.003193 · Cited by 20

Virtual AppLication-supported Environment To INcrease Exercise (VALENTINE) during cardiac rehabilitation study: Rationale and design

Jeganathan, V. S. E., Golbus, J. R., Gupta, K., Luff, E., Dempsey, W., Boyden, T. F., Rubenfire, M., Mukherjee, B., Klasnja, P., Kheterpal, S., et al. (2022) · American Heart Journal · doi:10.1016/j.ahj.2022.02.012 · Cited by 20

Human Behavior with Mobile Health: Smartphone/ Devices, Apps and Cognition

Hilty, D. M., & Chan, S. R. (2018) · Psychology and Cognitive Sciences - Open Journal · doi:10.17140/pcsoj-4-141 · Cited by 21

Validity of a Novel Research-Grade Physical Activity and Sleep Monitor for Continuous Remote Patient Monitoring

McDevitt, B., Moore, L. D., Akhtar, N., Connolly, J., Doherty, R., & Scott, W. (2021) · Sensors · doi:10.3390/s21062034 · Cited by 18

A Model for Assessing Necessary Conditions for Rural Health Care’s Mobile Health Readiness: Qualitative Assessment of Clinician-Perceived Barriers

Weichelt, B., Bendixsen, C., & Patrick, T. (2019) · JMIR mHealth and uHealth · doi:10.2196/11915 · Cited by 16

Beyond the Hype: Mobile Technologies and Opportunities to Address Health Disparities

Hswen, Y., & Viswanath, K. (2015) · Journal of Mobile Technology in Medicine · doi:10.7309/jmtm.4.1.9 · Cited by 20

Examining Potential Barriers to mHealth Implementation and Engagement in Schizophrenia: Phone Ownership and Symptom Severity

Luther, L., Buck, B., Fischer, M. W., Johnson-Kwochka, A. V., Coffin, G., & Salyers, M. P. (2020) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-020-00162-7 · Cited by 18

A Survey of Perceptions and Acceptance of Wearable Technology for Health Monitoring in a Urological Patient Population

Nehra, A. K., Gettman, M. T., Rivera, M., Agarwal, D., O’Neil, D. A., Jenkins, S. M., Tollefson, M. K., & Viers, B. R. (2016) · Urology Practice · doi:10.1016/j.urpr.2016.10.002 · Cited by 18

CardioAI: A Multimodal AI-based System to Support Symptom Monitoring and Risk Prediction of Cancer Treatment-Induced Cardiotoxicity

Wu, S., Cao, W., Fu, S., Yao, B., Yang, Z., Yin, C., Mishra, V., Addison, D., Zhang, P., & Wang, D. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714272 · Cited by 22

Smartphones for musculoskeletal research – hype or hope? Lessons from a decennium of mHealth studies

Beukenhorst, A. L., Druce, K. L., & Cock, D. D. (2022) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-022-05420-8 · Cited by 18

Maternal Well-Being and Stage of Behaviour Change during Pregnancy: A Secondary Analysis of the PEARS Randomised Controlled Trial

Roche, D., Rafferty, A. R., Holden, S., Killeen, S. L., Kennelly, M. A., & McAuliffe, F. M. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20010034 · Cited by 17

Using technological innovation to improve health care utilization in China’s hospitals: the emerging ‘online’ health service delivery

Tu, J., Wang, C., & Wu, S. (2017) · Journal of Asian Public Policy · doi:10.1080/17516234.2017.1396953 · Cited by 17

Patient-Centric Strategies in Digital Health

Chu, L. F., Shah, A. G., Rouholiman, D., Riggare, S. S., & Gamble, J. G. (2018) · Health informatics · doi:10.1007/978-3-319-61446-5_4 · Cited by 17

Monitoring heart rate in the delivery room

Dawson, J. A., Schmölzer, G. M., & Wyllie, J. P. (2018) · Seminars in Fetal and Neonatal Medicine · doi:10.1016/j.siny.2018.07.001 · Cited by 17

Use of the Consumer-Based Meditation App Calm for Sleep Disturbances: Cross-Sectional Survey Study

Huberty, J., Puzia, M., Larkey, L., Irwin, M. R., & Vranceanu, A. (2020) · JMIR Formative Research · doi:10.2196/19508 · Cited by 17

Managing hemophilia: the role of mobile technology

Khair, K., & Holland, M. (2014) · Smart Homecare Technology and TeleHealth · doi:10.2147/shtt.s40961 · Cited by 17

An Introduction to Personalized eHealth

Sebri, V., & Savioni, L. (2019) · Springer eBooks · doi:10.1007/978-3-030-27994-3_4 · Cited by 18

Long‐term effectiveness of an mHealth‐tailored physical activity intervention in youth with congenital heart disease: A randomized controlled trial

Lin, P., Fanjiang, Y., Wang, J., Lu, C., Lin, K., Cheong, I., Pan, K., & Chen, C. (2021) · Journal of Advanced Nursing · doi:10.1111/jan.14924 · Cited by 16

Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

Swain, S., Muduli, K., Kumar, A., V, & Luthra, S. (2023) · International Journal of Industrial Engineering and Operations Management · doi:10.1108/ijieom-12-2022-0067 · Cited by 19

Health Providers’ Perceptions and Experiences of Using mHealth for Chronic Noncommunicable Diseases: Qualitative Systematic Review and Meta-Synthesis

Gu, Y., Guan, Y., & Meng, Z. (2023) · Journal of Medical Internet Research · doi:10.2196/45437 · Cited by 16

The evolution and mapping trends of mobile health (m-Health): a bibliometric analysis (1997–2023)

Alanzi, T. M., Rehman, S. U., Khan, M. A., & Istepanian, R. S. H. (2024) · mHealth · doi:10.21037/mhealth-23-20 · Cited by 16

Video‐based eye tracking for neuropsychiatric assessment

Adhikari, S., & Stark, D. E. (2017) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13305 · Cited by 16

mHAT app for automated malaria rapid test result analysis and aggregation: a pilot study

Moore, C. P., Scherr, T., Matoba, J., Sing’anga, C., Lubinda, M., Thuma, P. E., & Wright, D. W. (2021) · Malaria Journal · doi:10.1186/s12936-021-03772-5 · Cited by 16

Innovation in Healthcare Organizations: Concepts and Challenges to Consider

Chaves, B. G., Briand, C., & Bouabida, K. (2021) · International journal of health research and innovation · doi:10.47260/ijhri/911 · Cited by 16

Prejudices and perceptions: patient acceptance of mobile technology use in health care

Alexander, S., Nerminathan, A. A., Harrison, A. A., Phelps, M., & Scott, K. M. (2015) · Internal Medicine Journal · doi:10.1111/imj.12899 · Cited by 16

Evaluation of a digital stethoscope in transitioning term infants after birth

Gaertner, V. D., Kevat, A., Davis, P. G., & Kamlin, C. O. F. (2017) · Archives of Disease in Childhood Fetal & Neonatal · doi:10.1136/archdischild-2016-312316 · Cited by 16

Real world usage characteristics of a novel mobile health self-monitoring device: Results from the Scanadu Consumer Health Outcomes (SCOUT) Study

Waalen, J., Peters, M., Ranamukhaarachchi, D. G., Li, J., Ebner, G. S., Senkowsky, J., Topol, E. J., & Steinhubl, S. R. (2019) · PLoS ONE · doi:10.1371/journal.pone.0215468 · Cited by 16

The transformative power of mHealth apps: empowering patients with obesity and diabetes – a narrative review

Mladin, O. A., Spinean, A., Carniciu, S., & Serafinceanu, C. (2024) · Journal of Medicine and Life · doi:10.25122/jml-2024-0340 · Cited by 15

Comparison of On-Site Versus Remote Mobile Device Support in the Framingham Heart Study Using the Health eHeart Study for Digital Follow-up: Randomized Pilot Study Set Within an Observational Study Design

Spartano, N. L., Lin, H., Sun, F. X., Lunetta, K. L., Trinquart, L., Valentino, M., Manders, E. S., Pletcher, M. J., Marcus, G. M., McManus, D. D., et al. (2019) · JMIR mhealth and uhealth · doi:10.2196/13238 · Cited by 13

Use of smartphones and mobile devices in hospitalized patients: Untapped opportunities for inpatient engagement

Ludwin, S. M., & Greysen, S. R. (2015) · Journal of Hospital Medicine · doi:10.1002/jhm.2365 · Cited by 15

Governing health data across changing contexts: A focus group study of citizen’s views in England, Iceland, and Sweden

Shah, N., Johansson, J. V., Haraldsdóttir, E., Bentzen, H. B., Coy, S., Mascalzoni, D., Jónsdóttir, G. A., & Kaye, J. S. (2021) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2021.104623 · Cited by 18

Mobile-based technologies to support healthcare provider to healthcare provider communication and management of care

Gonçalves, D. C., Buckley, B. S., Fønhus, M. S., Glenton, C., Henschke, N., Lewin, S. A., Maayan, N., Mehl, G. L., Tamrat, T., & Shepperd, S. (2018) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd012927 · Cited by 15

Behavioral Activation–Based Digital Smoking Cessation Intervention for Individuals With Depressive Symptoms: Randomized Clinical Trial

Dahne, J., Wahlquist, A. E., Kustanowitz, J., Natale, N., Fahey, M. C., Graboyes, E. M., Díaz, V. A., & Carpenter, M. J. (2023) · Journal of Medical Internet Research · doi:10.2196/49809 · Cited by 15

Exploring physical therapists’ perceptions of mobile application usage utilizing the FITT framework

Noblin, A. M., Shettian, M., Cortelyou-Ward, K. H., & Dugre, J. S. (2016) · Informatics for Health and Social Care · doi:10.1080/17538157.2016.1178118 · Cited by 13

Combining Wireless Technology and Behavioral Economics to Engage Patients (WiBEEP) with cardiometabolic disease: a pilot study

Angellotti, E., Wong, J. B., Pierce, A. Z., Hescott, B. J., & Pittas, A. G. (2019) · Pilot and Feasibility Studies · doi:10.1186/s40814-019-0395-8 · Cited by 13

Ubiquitous healthcare: a systematic mapping study

Saleemi, M., Anjum, M., & Rehman, M. (2020) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-020-02513-x · Cited by 14

Role and challenges of internet of things and informatics in Healthcare research

Jha, A., Athanerey, A., & Kumar, A. (2022) · Health technology · doi:10.1007/s12553-022-00661-y · Cited by 9

Economic Evaluation of Pharmacist-Led Digital Health Interventions: A Systematic Review

Park, T., Kim, H. M., Song, S., & Griggs, S. K. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph191911996 · Cited by 15

Activity Theory as a Lens for Developing and Applying Personas and Scenarios in Learning Experience Design

Schmidt, M., & Tawfik, A. A. (2022) · doi:10.59668/354.5904 · Cited by 13

Acceptability of a Text Message‐Based Mobile Health Intervention to Promote Physical Activity in Cardiac Rehabilitation Enrollees: A Qualitative Substudy of Participant Perspectives

Atluri, N., Mishra, S. R., Anderson, T. M., Stevens, R., Edwards, A. M., Luff, E., Nallamothu, B. K., & Golbus, J. R. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.123.030807 · Cited by 14

Big Data in Healthcare – Defining the Digital Persona through User Contexts from the Micro to the Macro

Monkman, H., Petersen, C. C., Weber, J., Borycki, E. M., Adams, S., Collins, S., & Kuziemsky, C. E. (2014) · Yearbook of Medical Informatics · doi:10.15265/iy-2014-0014 · Cited by 14

The Quality of Indian Obesity-Related mHealth Apps: PRECEDE-PROCEED Model–Based Content Analysis

Selvaraj, S. N., & Arulchelvan, S. (2022) · JMIR mhealth and uhealth · doi:10.2196/15719 · Cited by 13

Technology-based interventions in health care

Kane, J. M. (2014) · Epidemiology and Psychiatric Sciences · doi:10.1017/s2045796014000444 · Cited by 13

Internet-Based Unobtrusive Tele-Monitoring System for Sleep and Respiration

Choi, A., Noh, S., & Shin, H. (2020) · IEEE Access · doi:10.1109/access.2020.2989336 · Cited by 14

Telemedicine, Telehealth, and e-Health Technologies in Cancer Prevention

López, A. M. (2019) · Springer eBooks · doi:10.1007/978-3-030-15935-1_10 · Cited by 13

Smartphone-Enabled versus Conventional Otoscopy in Detecting Middle Ear Disease: A Meta-Analysis

Chen, C., Huang, C.-Y., Cheng, H.-L., Lin, H. H., Chu, Y.-C., Chang, C., Lai, Y.-H., Wang, M.-C., & Cheng, Y. (2022) · Diagnostics · doi:10.3390/diagnostics12040972 · Cited by 12

A Survey of Precision Medicine Strategy Using Cognitive Computing

(2018) · International Journal of Machine Learning and Computing · doi:10.18178/ijmlc.2018.8.6.741 · Cited by 12

Technologies for Managing the Health of Older Adults with Multiple Chronic Conditions: A Systematic Literature Review

Cajamarca, G., Proust, V., Herskovic, V., Cádiz, R. F., Verdezoto, N. X., & Medina, F. J. F. (2023) · Healthcare · doi:10.3390/healthcare11212897 · Cited by 12

An evaluation of mHealth adoption and health self-management in emerging adulthood.

Drake, C., Cannady, M., Howley, K., Shea, C. M., & D, R. S. M. (2019) · PubMed Central · Cited by 12

E-santé, digitalisation ou transformation numérique : impact sur les soins de support en oncologie

Seguin, L., & Tassy, L. (2022) · Bulletin du Cancer · doi:10.1016/j.bulcan.2021.08.015 · Cited by 16

Customization of the TRU-PBMT App (Technology Recordings to better Understand Pediatric Blood and Marrow Transplant)

Vaughn, J., Jonassaint, J., Summers-Goeckerman, E., Shaw, R. J., & Shah, N. (2018) · Journal of Pediatric Nursing · doi:10.1016/j.pedn.2018.07.007 · Cited by 12

Exploring the need for interventions to manage weight and stress during interconception

Huberty, J., Leiferman, J. A., Kruper, A., Jacobson, L. T., Waring, M. E., Matthews, J. L., Wischenka, D. M., Braxter, B., & Kornfield, S. L. (2016) · Journal of Behavioral Medicine · doi:10.1007/s10865-016-9813-z · Cited by 14

A Multimodal mHealth Intervention (FeatForward) to Improve Physical Activity Behavior in Patients with High Cardiometabolic Risk Factors: Rationale and Protocol for a Randomized Controlled Trial

Agboola, S., Palacholla, R. S., Centi, A., Kvedar, J., & Jethwani, K. (2016) · JMIR Research Protocols · doi:10.2196/resprot.5489 · Cited by 11

Perceptions of Mobile Health Technology in Elective Surgery

Panda, N., Sinyard, R. D., Margo, J. N., Henrich, N. J., Cauley, C. E., Onnela, J.-P. “., Haynes, A. B., & Brindle, M. E. (2021) · Annals of Surgery · doi:10.1097/sla.0000000000005208 · Cited by 11

Community hypertension programs in the age of mobile technology and social media.

Logan, A. (2014) · American Journal of Hypertension · doi:10.1093/ajh/hpu125 · Cited by 18

Evaluating the Usability and Acceptability of Communication Tools Among Older Adults

Nilsen, M. L., Morrison, A. S., Lingler, J. H., Myers, B. A., Johnson, J. T., Happ, M. B., Sereika, S. M., & Dabbs, A. D. (2018) · Journal of Gerontological Nursing · doi:10.3928/00989134-20180808-07 · Cited by 11

Smartphone-based Mental State Estimation: A Survey from a Machine Learning Perspective

Fukazawa, Y., Yamamoto, N., Hamatani, T., Ochiai, K., Uchiyama, A., & Ohta, K. (2020) · Journal of Information Processing · doi:10.2197/ipsjjip.28.16 · Cited by 13

Promoting access to COVID-19 Information by underserved communities through the development of a mHealth app

Maphosa, V. (2022) · Cogent Public Health · doi:10.1080/27707571.2022.2095722 · Cited by 13

Implementation of Mobile Health Tools

Huckvale, K., & Car, J. (2014) · JAMA · doi:10.1001/jama.2014.1106 · Cited by 11

Complex Event Processing of Health Data in Real-time to Predict Heart Failure Risk and StressPreprint

Sandha, S. S., Kachuee, M., & Darabi, S. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.04364 · Cited by 11

Artificial intelligence in cardiology: an updated systematic review with ethical considerations and challenges in implementing artificial intelligence models

Patel, D., Kantamneni, R., John, J. D., Patel, T., Shukla, A., Salma, A., & Anand, N. (2025) · Annals of Medicine and Surgery · doi:10.1097/ms9.0000000000004607 · Cited by 14

Selfie Dental Plaque Index: A New Tool for Dental Plaque Assessment

Azevedo, C. L., Henriques, P. S. G., Pannuti, C. M., & Michel‐Crosato, E. (2022) · Journal of Clinical and Experimental Dentistry · doi:10.4317/jced.59908 · Cited by 10

Using Wear Time for the Analysis of Consumer-Grade Wearables’ Data: Case Study Using Fitbit Data

Baroudi, L., Zernicke, R. F., Tewari, M., Carlozzi, N. E., Choi, S. W., & Cain, S. M. (2024) · JMIR mhealth and uhealth · doi:10.2196/46149 · Cited by 10

The effectiveness of remote interventions based on digital health technology in kidney transplant recipients: a systematic review

Kuang, M., Yao, Z., Chen, J., Yan, Y., & Li, Z. (2025) · World Journal of Urology · doi:10.1007/s00345-025-05582-9 · Cited by 10

Developing an App for Improving Access to COVID-19 Information in Underserved Communities

Maphosa, V. (2022) · International Journal of Information Engineering and Electronic Business · doi:10.5815/ijieeb.2022.03.03 · Cited by 12

Mobile health (mHealth) technologies

Gagneja, A. P. S., & Gagneja, K. K. (2015) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2015.7454470 · Cited by 10

Mobile-based technologies to support client to healthcare provider communication and management of care

Gonçalves, D. C., Buckley, B. S., Fønhus, M. S., Glenton, C., Henschke, N., Lewin, S. A., Maayan, N., Mehl, G. L., Tamrat, T., & Shepperd, S. (2018) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd012928 · Cited by 11

On the Utility of Audiovisual Dialog Technologies and Signal Analytics for Real-time Remote Monitoring of Depression Biomarkers

Neumann, M., Roesler, O., Suendermann‐Oeft, D., & Ramanarayanan, V. (2020) · doi:10.18653/v1/2020.nlpmc-1.7 · Cited by 10

Designing a Remote Closed-Loop Automatic Oxygen Control in Preterm Infants

Moradi, M. R., Kalhori, S. R. N., Saeedi, M. G., Zarkesh, M. R., Habibelahi, A., & Panahi, A. H. (2020) · Iranian Journal of Pediatrics · doi:10.5812/ijp.101715 · Cited by 9

A wearable alcohol biosensor: Exploring the accuracy of transdermal drinking detection

Fairbairn, C. E., Han, J., Caumiant, E. P., Benjamin, A. S., & Bosch, N. (2024) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2024.112519 · Cited by 9

Economic evaluation of an integrated virtual care programme for people with chronic illness who are frequent users of health services in Australia

Carter, H. E., Wallis, S., McGowan, K., Graves, N., Pitt, R., Coffey, S., Phillips, R., & Parcell, M. (2023) · BMJ Open · doi:10.1136/bmjopen-2022-066016 · Cited by 11

Design and Implementation of Behavioral Informatics Interventions

Laranjo, L., Lau, A. Y. S., & Coiera, E. W. (2017) · Health informatics · doi:10.1007/978-3-319-51732-2_2 · Cited by 8

Evaluating Network Readiness for mHealth Interventions Using the Beacon Mobile Phone App: Application Development and Validation Study

Scherr, T., Moore, C. P., Thuma, P. E., & Wright, D. W. (2020) · JMIR mhealth and uhealth · doi:10.2196/18413 · Cited by 9

Mobile Integrated Assistance to Empower People Coping with Parkinson's Disease

Pereira, C. M., Macedo, P., & Madeira, R. N. (2015) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/2700648.2811394 · Cited by 9

Technology applications to improve health outcomes and self-management in patients with arthritis

Iversen, M. D., Connors, M. E., Menapace, M. R., Samson, A. J., & Tessitore, E. (2014) · International Journal of Clinical Rheumatology · doi:10.2217/ijr.14.35 · Cited by 8

Improving Italian Healthcare Service Quality Using Analytic Hierarchy Process Methodology

Felice, F. D., & Petrillo, A. (2014) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-319-11128-5_245 · Cited by 9

Implementation of Direct-to-Patient Mobile Teledermatology in VA

Peracca, S. B., Lachica, O., Lamkin, R. P., Jackson, G. L., Mohr, D. C., King, H. A., Whited, J. D., Fonseca, A. S., Morris, I. J., Gifford, A. L., et al. (2024) · Journal of General Internal Medicine · doi:10.1007/s11606-023-08480-1 · Cited by 8

Effectiveness of Walking Prescription Using Mobile Health Technology on the Changes in Daily Steps in Older Adults With Cognitive Impairment: Randomized Controlled Study

Kim, H. J., Hwang, Y. J., Park, J. E., & Lee, D. Y. (2025) · JMIR Aging · doi:10.2196/63081 · Cited by 8

Artificial intelligence in interventional cardiology: a review of its role in diagnosis, decision-making, and procedural precision

Nzeako, T. R., Elendu, C., Echefu, G. C., Olanisa, O., Kiladejo, A., & Bob-Manuel, E. D. (2025) · Annals of Medicine and Surgery · doi:10.1097/ms9.0000000000003602 · Cited by 9

Evaluation of TRANSFoRm Mobile eHealth Solution for Remote Patient Monitoring during Clinical Trials

Jankowski, J., Saganowski, S., & Bródka, P. (2016) · Mobile Information Systems · doi:10.1155/2016/1029368 · Cited by 8

UbMed: A ubiquitous system for monitoring medication adherence

da Silva, V. J., Rodrigues, M. A. S., Barreto, R., & de Lucena, V. F. (2016) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2016.7749419 · Cited by 8

Description and Validation of TAVIApp: A Novel Mobile Application for Support of Physicians in the Management of Aortic Stenosis—Management of Aortic Stenosis with TAVIApp

Indolfi, C., Sabatino, J., Rosa, S. D., Mongiardo, A., Ricci, P., & Spaccarotella, C. (2017) · BioMed Research International · doi:10.1155/2017/9027597 · Cited by 8

Use of a Meter With Color-Range Indicators and a Mobile Diabetes Management App Improved Glycemic Control and Patient Satisfaction in an Underserved Hispanic Population: “Tu Salud”—A Randomized Controlled Partial Cross-Over Clinical Study

Katz, L. B., Aparicio, M., Cameron, H., & Ceppa, F. (2021) · Diabetes Spectrum · doi:10.2337/ds20-0101 · Cited by 8

A qualitative analysis of communication workflows between adult day service centers and primary care providers

Zhong, J., Boafo, J., Brody, A. A., Wu, B., & Sadarangani, T. R. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab284 · Cited by 8

mHealth, Health, and Mobility: A Culture-Centered Interrogation

Dutta, M. J., Kaur‐Gill, S., Tan, N. Q. P., & Lam, C. (2017) · Mobile communication in Asia · doi:10.1007/978-94-024-1251-2_6 · Cited by 8

mHealth and Health Information Technology Tools for Diverse Patients with Diabetes

Lyles, C. R., Ratanawongsa, N., Bolen, S. D., & Samal, L. (2017) · Journal of Diabetes Research · doi:10.1155/2017/1704917 · Cited by 8

Probabilistic Machine Learning for Healthcare

Chen, I. Y., Joshi, S. D., Ghassemi, M., & Ranganath, R. (2021) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-092820-033938 · Cited by 68

Content Analysis: First-Time Patient User Challenges with Top-Rated Commercial Diabetes Apps

Fu, H. N. C., Jin, D., & Adam, T. J. (2021) · Telemedicine and e-Health · doi:10.1089/tmj.2020.0128 · Cited by 10

Цифрова трансформація системи охорони здоров’я: фактори впливу на якість життя населення

Kvitka, S. A., & Миргородська, М. (2024) · Public administration aspects · doi:10.15421/152402 · Cited by 49

Perspectives of Kidney Transplant Recipients on eHealth: Semistructured Interviews

Tang, J., Howell, M., Roger, S. D., Wong, G., & Tong, A. (2022) · Transplantation Direct · doi:10.1097/txd.0000000000001404 · Cited by 7

Patient Work Methods: Current Methods of Engaging Patients in Systems Design in Clinical, Community and Extraterrestrial Settings

Valdez, R. S., Holden, R. J., Khunlerkit, N., Marquard, J. L., McGuire, K., Nathan-Roberts, D., Ozkaynak, M., & Ramly, E. (2017) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213601641 · Cited by 7

Digital Healthcare and Expertise

Egher, C. (2022) · Health, technology and society · doi:10.1007/978-981-16-9178-2 · Cited by 11

Health Insurance and Mobile Health Devices

Raber, I., McCarthy, C. P., & Yeh, R. W. (2019) · JAMA · doi:10.1001/jama.2019.3353 · Cited by 30

This Week in JAMA

(2012) · JAMA · doi:10.1001/jama.2012.2988 · Cited by 1

Mobile Health Technology

Golbus, J. (2023) · JACC Case Reports · doi:10.1016/j.jaccas.2023.101898 · Cited by 19

Mobile health: real game-changer.

Levin-Epstein, M. (2013) · PubMed · Cited by 2

Implementation of Mobile Health Tools

Huckvale, K., & Car, J. (2014) · JAMA · doi:10.1001/jama.2014.1106 · Cited by 11