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Digital health: a path to validation
Open accessAbstract
Digital health solutions continue to grow in both number and capabilities. Despite these advances, the confidence of the various stakeholders — from patients and clinicians to payers, industry and regulators — in medicine remains quite low. As a result, there is a need for objective, transparent, and standards-based evaluation of digital health products that can bring greater clarity to the digital health marketplace. We believe an approach that is guided by end-user requirements and formal assessment across technical, clinical, usability, and cost domains is one possible solution. For digital health solutions to have greater impact, quality and value must be easier to distinguish. To that end, we review the existing landscape and gaps, highlight the evolving responses and approaches, and detail one pragmatic framework that addresses the current limitations in the marketplace with a path toward implementation.
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“evidence-supported apps are slow to be made publicly accessible due to research-to-practice translational lags and complex regulatory systems (Mathews et al. 2019).”
From Evaluating the quality, safety, and functionality of commonly used smartphone apps for bipolar disorder mood and sleep self-management (2022) · cites this paper as Mathews et al. 2019
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Cites
International Organization for Standardization
(2011) · Springer eBooks · doi:10.1007/springerreference_16847 · Cited by 12,504
2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2019
(2018) · Diabetes Care · doi:10.2337/dc19-s002 · Cited by 2,855
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
Iribarren, S. J., Cato, K., Falzon, L., & Stone, P. W. (2017) · PLOS ONE · doi:10.1371/journal.pone.0170581 · Cited by 519
What It Will Take To Achieve The As-Yet-Unfulfilled Promises Of Health Information Technology
Kellermann, A. L., & Jones, S. S. (2013) · Health Affairs · doi:10.1377/hlthaff.2012.0693 · Cited by 482
Origin and Uses of Primum Non Nocere—Above All, Do No Harm!
Smith, C. M. (2005) · The Journal of Clinical Pharmacology · doi:10.1177/0091270004273680 · Cited by 411
Quinn, C. C., Clough, S. S., Minor, J. M., Lender, D., Okafor, M. C., & Gruber-Baldini, A. (2008) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2008.0283 · Cited by 406
mHealth and Mobile Medical Apps: A Framework to Assess Risk and Promote Safer Use
Lewis, T., & Wyatt, J. C. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3133 · Cited by 281
Boudreaux, E. D., Waring, M. E., Hayes, R. B., Sadasivam, R. S., Mullen, S. P., & Pagoto, S. (2014) · Translational Behavioral Medicine · doi:10.1007/s13142-014-0293-9 · Cited by 281
The GRADE system for rating clinical guidelines
Kavanagh, B. P. (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000094 · Cited by 246
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Shah, D., Rani, S., Shoukat, K., Kalsoom, H., Shoukat, M. U., Almujibah, H. R., & Liao, S. (2024) · Sensors · doi:10.3390/s24216835 · Cited by 34
Distilling the knowledge from large-language model for health event prediction
Ding, S., Ye, J., Hu, X., & Zou, N. (2024) · Scientific Reports · doi:10.1038/s41598-024-75331-2 · Cited by 28
Chen, Z., Hao, J., Sun, H., Li, M., Zhang, Y., & Qian, Q. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-025-02870-7 · Cited by 29
Recommendations for Successful Development and Implementation of Digital Health Technology Tools
Loo, R. T. J., Nasta, F., Macchi, M., Baudot, A., Burstein, F., Bove, R. M., Greve, M., Fröhlich, H., Khalid, S., Küderle, A., et al. (2025) · Journal of Medical Internet Research · doi:10.2196/56747 · Cited by 28
Defining ethical standards for the application of digital tools to population health research
Samuel, G., & Derrick, G. (2019) · Bulletin of the World Health Organization · doi:10.2471/blt.19.237370 · Cited by 24
Silven, A. V., van Peet, P. G., Boers, S. N., Tabak, M., de Groot, A., Hendriks, D., van Os, H. J. A., Bonten, T. N., Atsma, D. E., de Graaf, et al. (2022) · BMC Health Services Research · doi:10.1186/s12913-021-07316-0 · Cited by 35
A smart hospital-driven approach to precision pharmacovigilance
Pretis, F. D., van Gils, M., & Forsberg, M. (2022) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2022.03.009 · Cited by 29
Werner, N. E., Campbell, N. L., Boustani, M., Ganci, A., & Holden, R. J. (2022) · Research in Social and Administrative Pharmacy · doi:10.1016/j.sapharm.2022.03.014 · Cited by 27
Challenges for remote patient monitoring programs in rural and regional areas: a qualitative study
Tagne, J. F., Burns, K., O’Brein, T., Chapman, W. W., Cornell, P. Y., Huckvale, K., Ameen, I., Bishop, J. L., Buccheri, A., Reid, J., et al. (2025) · BMC Health Services Research · doi:10.1186/s12913-025-12427-z · Cited by 36
Lee, J.-S., Kang, M.-A., & Lee, S. (2020) · Journal of Medical Internet Research · doi:10.2196/17031 · Cited by 27
A Future of Smarter Digital Health Empowered by Generative Pretrained Transformer
Miao, H., Li, C., & Wang, J. (2023) · Journal of Medical Internet Research · doi:10.2196/49963 · Cited by 26
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Johnson, E. L., & Miller, E. (2022) · Diabetes Spectrum · doi:10.2337/dsi21-0015 · Cited by 25
Mobile Health Application for Patients Undergoing Breast Cancer Surgery: Feasibility Study
Ponder, M., Venkatraman, V., Charalambous, L. T., Ansah-Yeboah, A. A., Adil, S. M., Antezana, L. A., Dharmapurikar, R., Gellad, Z. F., Lad, S. P., Hwang, E. S., et al. (2021) · JCO Oncology Practice · doi:10.1200/op.20.01026 · Cited by 27
Ehn, M., Richardson, M. X., Stridsberg, S. L., Redekop, K., & Andersson, S. W. (2021) · Journal of Medical Internet Research · doi:10.2196/27267 · Cited by 25
Digital innovations for retinal care in diabetic retinopathy
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Lin, C., Huang, Z., Feng, Q., Chang, X., & Yan, K. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20010760 · Cited by 25
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Shaw, J., & Glover, W. J. (2024) · Journal of Medical Internet Research · doi:10.2196/46971 · Cited by 27
Issom, D.-Z., Henriksen, A., Woldaregay, A. Z., Rochat, J., Lovis, C., & Hartvigsen, G. (2020) · JMIR Human Factors · doi:10.2196/14599 · Cited by 26
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Ji, Y., Park, S. M., Kwon, S., Leem, J. W., Nair, V. V., Tong, Y., & Kim, Y. L. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgad111 · Cited by 24
Quality assessment of mHealth apps: a scoping review
Giebel, G. D., Speckemeier, C., Schrader, N. F., Abels, C., Plescher, F., Hillerich, V., Wiedemann, D., Börchers, K., Wasem, J., Blase, N., et al. (2024) · Frontiers in Health Services · doi:10.3389/frhs.2024.1372871 · Cited by 31
Buchan, M. L., Goel, K., Schneider, C., Steullet, V., Bratton, S. L., & Basch, E. (2024) · JCO Clinical Cancer Informatics · doi:10.1200/cci.24.00085 · Cited by 23
Colombo, G., Minta, K., Grübel, J., Tai, W. L. E., Hölscher, C., & Schinazi, V. R. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108349 · Cited by 25
Unraveling overoptimism and publication bias in ML-driven science
Saidi, P., Dasarathy, G., & Berisha, V. (2025) · Patterns · doi:10.1016/j.patter.2025.101185 · Cited by 33
Alon, N., Stern, A. D., & Torous, J. B. (2020) · JMIR mhealth and uhealth · doi:10.2196/20482 · Cited by 23
Digital health & low-value care
O’Reilly-Jacob, M., Mohr, P. E., Ellen, M., Petersen, C. C., Sarkisian, C. A., Attipoe, S., & Rich, E. C. (2021) · Healthcare · doi:10.1016/j.hjdsi.2021.100533 · Cited by 23
Digital Health in Diabetes and Cardiovascular Disease
Avoke, D., Elshafeey, A., Weinstein, R. A., Kim, C. H., & Martin, S. S. (2024) · Endocrine Research · doi:10.1080/07435800.2024.2341146 · Cited by 24
Miller‐Rosales, C., Morden, N. E., Brunette, M. F., Busch, S. H., Torous, J. B., & Meara, E. R. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.23741 · Cited by 24
Morton, E., Nicholas, J., Yang, L., Lapadat, L., Barnes, S. J., Provencher, M. D., Depp, C., Chan, M., Kulur, R., & Michalak, E. E. (2022) · International Journal of Bipolar Disorders · doi:10.1186/s40345-022-00256-6 · Cited by 20
The Digital Neurologic Examination
Cohen, A. B., & Nahed, B. V. (2021) · Digital Biomarkers · doi:10.1159/000515577 · Cited by 22
Self-citationCascini, F., Gentili, A., Causio, F. A., Altamura, G., Melnyk, A., Beccia, F., Pappalardo, C., Lontano, A., & Ricciardi, W. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1147210 · Cited by 21
Systematic Review of mHealth Applications That Interface with Inhaler Sensors in Asthma
Nguyen, E., Miao, B., Pugliese, N., Huang, D., & Sobieraj, D. M. (2020) · The Journal of Allergy and Clinical Immunology In Practice · doi:10.1016/j.jaip.2020.08.049 · Cited by 21
(2020) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2020.19418 · Cited by 21
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Vuong, Q., Le, T.-T., La, V., & Nguyen, M. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4003161 · Cited by 20
Idrees, A. R., Kraft, R., Mutter, A., Baumeister, H., Reichert, M., & Pryss, R. C. (2024) · PLOS Digital Health · doi:10.1371/journal.pdig.0000498 · Cited by 20
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Ataguba, G., & Orji, R. (2025) · ACM Transactions on Computing for Healthcare · doi:10.1145/3712709 · Cited by 24
Gray, C. S. (2020) · Journal of Medical Internet Research · doi:10.2196/17987 · Cited by 20
Silva, G. S., & Schwamm, L. H. (2020) · Stroke · doi:10.1161/strokeaha.120.033239 · Cited by 20
Krick, T. (2021) · BMC Nursing · doi:10.1186/s12912-021-00654-8 · Cited by 18
Quality of Mobile Apps for Child Development Support: Search in App Stores and Content Analysis
Dewitt, A., Kientz, J. A., & Liljenquist, K. S. (2022) · JMIR Pediatrics and Parenting · doi:10.2196/38793 · Cited by 20
Baltaxe, E., Cano, I., Risco, R., Sebio, R., Dana, F., Laxe, S., Martínez, R., Ozores, F., Roca, J., & Martínez‐Palli, G. (2022) · International Journal of Integrated Care · doi:10.5334/ijic.6503 · Cited by 20
Conceptualizing socially-assistive robots as a digital therapeutic tool in healthcare
Stanojević, Č., Bennett, C. C., Šabanović, S., Collins, S., Henkel, K. B., Henkel, Z., & Piatt, J. A. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1208350 · Cited by 20
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Abdullah, N. N. B., Grundy, J., McIntosh, J., How, Y. C., Saharuddin, S., Tat, K. K., ShinYe, E., Rastom, A. J. A., & Othman, N. L. (2020) · doi:10.1109/rewbah51211.2020.00007 · Cited by 20
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Raoof, S., Kennedy, C. J., Wallach, D. A., Bitton, A., & Green, R. C. (2021) · Nature Medicine · doi:10.1038/s41591-021-01431-5 · Cited by 19
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Tamburis, O., & Benis, A. (2022) · Methods of Information in Medicine · doi:10.1055/a-1938-0533 · Cited by 19
El rol de enfermería en la salud digital: oportunidades y desafíos para la ciencia del cuidado
Benavente-Rubio, A. (2022) · Revista Médica Clínica Las Condes · doi:10.1016/j.rmclc.2022.11.004 · Cited by 19
User experience research in the development of digital health products: Research letter
Blanchard, M. (2023) · Health Policy and Technology · doi:10.1016/j.hlpt.2023.100753 · Cited by 19
Jacob, C., Lindeque, J. P., Müller, R., Klein, A., Metcalfe, T., Connolly, S. L., Koerber, F., Maguire, R., Denis, F., Heuss, S., et al. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00982-w · Cited by 17
Health systems as venture capital investors in digital health: 2011–2019
Safavi, K. C., Cohen, A. B., Ting, D., Chaguturu, S. K., & Rowe, J. S. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-00311-5 · Cited by 19
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Albanese, G. A., Bucchieri, A., Podda, J., Tacchino, A., Buccelli, S., Momi, E. D., Laffranchi, M., Mannella, K., Holmes, M. W. R., Zenzeri, J., et al. (2024) · Frontiers in Robotics and AI · doi:10.3389/frobt.2024.1335147 · Cited by 18
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Cohen, A. B., Stump, L. S., Krumholz, H. M., Cartiera, M., Jain, S., Sussman, L. S., Hsiao, A., Lindop, W., Ying, A. K., Kaul, R. L., et al. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00608-7 · Cited by 19
Self-citationLazarevic, N., Lecoq, M., Bœhm, C., & Caillaud, C. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20021012 · Cited by 20
Voorheis, P., Bhuiya, A. R., Kuluski, K., Phạm, Q., & Petch, J. (2023) · Journal of Medical Internet Research · doi:10.2196/45095 · Cited by 23
Prentice, C., Peven, K., Zhaunova, L., Nayak, V., Radović, T., Klepchukova, A., POTTS, H. W. W., & Ponzo, S. (2024) · BMC Digital Health · doi:10.1186/s44247-024-00092-x · Cited by 17
The Role of a Smart Health Ecosystem in Transforming the Management of Chronic Health Conditions
Nourse, R. A., Dingler, T., Kelly, J. T., Kwaśnicka, D., & Maddison, R. (2023) · Journal of Medical Internet Research · doi:10.2196/44265 · Cited by 17
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Singh, H., Armas, A., Law, S., Tang, T., Gray, C. S., Cunningham, H., Thombs, R., Ellen, M., Sritharan, J., Nie, J. X., et al. (2021) · BMJ Open · doi:10.1136/bmjopen-2020-045596 · Cited by 17
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Clay, I., Peerenboom, N., Connors, D. E., Bourke, S., Keogh, A., Wac, K., Arieh, T. G., Baker, J. T., Bull, C., Cereatti, A., et al. (2023) · Digital Biomarkers · doi:10.1159/000530413 · Cited by 16
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Wei, X., Cao, Y., Peng, X., & Prybutok, V. R. (2024) · Health Marketing Quarterly · doi:10.1080/07359683.2024.2316425 · Cited by 16
Silburn, P. A., DeBates, S., Tomlinson, T., Schwark, J., Creek, G., Patel, H., Punnoose, A., Cheeran, B., Ross, E., Lautner, D., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-06098-7 · Cited by 16
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Mather, J. D., Hayes, L. D., Mair, J. L., & Sculthorpe, N. F. (2024) · Frontiers in Digital Health · doi:10.3389/fdgth.2024.1326511 · Cited by 17
Yeung, A. W. K., Litvinova, O., Bragazzi, N. L., Khader, Y. S., Rahman, M. M., Said, Z., Istepanian, R. S. H., Koulaouzidis, A., Aremu, A. O., Flanagan, J. M., et al. (2024) · Exploration of Digital Health Technologies · doi:10.37349/edht.2024.00013 · Cited by 15
Tea, F., Groh, A. M. R., Lacey, C., & Fakolade, A. O. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01162-0 · Cited by 20
Shin, H. J., Cho, I. T., Choi, W., Kim, H. R., Kang, M.-B., & Yang, W. (2024) · Journal of Yeungnam Medical Science · doi:10.12701/jyms.2024.01004 · Cited by 15
Londral, A., Azevedo, S., Dias, P., Ramos, C., Santos, J., Martins, F., Silva, R., Semedo, H., Vital, C., Gualdino, A., et al. (2022) · BMC Health Services Research · doi:10.1186/s12913-022-08073-4 · Cited by 15
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Silvera‐Tawil, D., Higgins, L., Packer, K., Bayor, A. A., Walker, J. G., Li, J., Niven, P., Khanna, S., Byrnes, J., Bradford, D., et al. (2025) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2025.2479838 · Cited by 17
Hourani, D., Darling, S. J., Cameron, E., Dromey, J. A., Crossley, L. H., Kanagalingam, S., Muscara, F., Gwee, A., Gell, G., Hiscock, H., et al. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.661708 · Cited by 14
Wang, P., Leong, Q. Y., Lau, N. Y., Ng, W. Y., Kwek, S. P., Tan, L. W. J., Song, S.-W., You, K., Chong, L. M., Zhuang, I., et al. (2024) · Singapore Medical Journal · doi:10.4103/singaporemedj.smj-2023-243 · Cited by 14
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Li, Z. (2023) · Journal of Personalized Medicine · doi:10.3390/jpm13020292 · Cited by 13
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Pfitzer, E., Bitomsky, L., Nißen, M., Kausch, C., & Kowatsch, T. (2024) · Journal of Medical Internet Research · doi:10.2196/60473 · Cited by 17
Systematic Evaluation of Smartphone Applications for the Medical Management of Nephrolithiasis
Winoker, J. S., Koo, K., Huang, M. M., Bhanji, Y., & Matlaga, B. R. (2020) · Journal of Endourology · doi:10.1089/end.2020.1005 · Cited by 13
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Banimfreg, B. H., Shamayleh, A., & Alshraideh, H. A. (2022) · Metabolites · doi:10.3390/metabo12101002 · Cited by 13
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Purnamayanti, N. K. D., & Wicaksana, A. L. (2021) · Indian Journal of Endocrinology and Metabolism · doi:10.4103/ijem.ijem_153_21 · Cited by 13
Digitale Transformation deutscher Gesundheitseinrichtungen
Petzold, T., & Steidle, O. (2023) · Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz · doi:10.1007/s00103-023-03743-y · Cited by 12
Largent, E. A., Karlawish, J. H., & Wexler, A. (2024) · BMC Digital Health · doi:10.1186/s44247-024-00098-5 · Cited by 12
Badareu, G., Cârstina, S., Militaru, F., Siminică, M. I., & Cîrciumaru, D. (2025) · Healthcare · doi:10.3390/healthcare13020093 · Cited by 13
Ukaegbu, O. C., & Fan, M. (2025) · Health Policy and Technology · doi:10.1016/j.hlpt.2025.101024 · Cited by 12
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Labiris, G., Panagiotopoulou, E.-K., Delibasis, K. K., Duzha, E., Bakirtzis, M., Panagis, C., Boboridis, K. G., Mokka, A., Balidis, M., Damtsi, C., et al. (2023) · Journal of Cataract & Refractive Surgery · doi:10.1097/j.jcrs.0000000000001176 · Cited by 12
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Islam, B., McElwain, N. L., Li, J., Davila, M. I., Hu, Y., Hu, K., Bodway, J. M., Dhekne, A., Choudhury, R. R., & Hasegawa‐Johnson, M. (2024) · Sensors · doi:10.3390/s24030901 · Cited by 11
Queiroz, C., Guerreiro, C., Santos, M. O., Ferreira, D., Fontes‐Carvalho, R., & Ladeiras‐Lopes, R. (2024) · Revista Portuguesa de Cardiologia · doi:10.1016/j.repc.2023.10.014 · Cited by 11
Oudbier, S. J., Smets, E. M. A., Nieuwkerk, P. T., Neal, D. P., Nurmohamed, A. S., Meij, H. J., & Peute, L. (2024) · JMIR Medical Informatics · doi:10.2196/63703 · Cited by 13
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Gaeta, E., Haleem, M. S., Lopez-Perez, L., Manea, M., Cabrera-Umpiérrez, M. F., Arredondo, M. T., Pecchia, L., & Fico, G. (2025) · IEEE Access · doi:10.1109/access.2025.3539559 · Cited by 11
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Sharma, V., Piscoran, O., Summers, A., Woywodt, A., van der Veer, S. N., Ainsworth, J. D., & Augustine, T. (2021) · Transplantation Reviews · doi:10.1016/j.trre.2021.100607 · Cited by 10
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Goodman, W., Bagnall, A., Ashley, L., Azizoddin, D. R., Muehlensiepen, F., Blum, D., Bennett, M., & Allsop, M. J. (2022) · JMIR Cancer · doi:10.2196/33355 · Cited by 12
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Kim, S., Eom, J., & Shim, J. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19159556 · Cited by 11
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Metadata
- Authors
- Mathews, S. C., McShea, M. J., Hanley, C. L., Ravitz, A., Labrique, A. B., & Cohen, A. B.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Mathews, Simon C.
- Venue
- npj Digital Medicine
- Published
- 2019-05-13
- Volume
- 2
- Issue
- 1
- Pages
- 38-38
- ISSN
- 2398-6352 (ISSN-L)
- PMC
- PMC6550273
- OpenAlex
- W2946661638
- Cited by
- 508
- References
- 24
- Citations by year
- 2026: 52 · 2025: 81 · 2024: 107 · 2023: 85 · 2022: 73 · 2021: 60 · 2020: 44 · 2019: 6
- FWCI
- 8.41
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- npj Digital Medicine (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- digital health, validation framework, end-user needs, clinical evaluation, usability, cost evaluation, standards-based evaluation, stakeholder confidence
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