Health Communication on the Internet: Promoting Public Health and Exploring Disparities in the Generative AI Era
Open accessPublished version of a preprint
Abstract
Health communication and promotion on the internet have evolved over time, driven by the development of new technologies, including generative artificial intelligence (GenAI). These technological tools offer new opportunities for both the public and professionals. However, these advancements also pose risks of exacerbating health disparities. Limited research has focused on combining these health communication mediums, particularly those enabled by new technologies like GenAI, and their applications for health promotion and health disparities. Therefore, this viewpoint, adopting a conceptual approach, provides an updated overview of health communication mediums and their role in understanding health promotion and disparities in the GenAI era. Additionally, health promotion and health disparities associated with GenAI are briefly discussed through the lens of the Technology Acceptance Model 2, the uses and gratifications theory, and the knowledge gap hypothesis. This viewpoint discusses the limitations and barriers of previous internet-based communication mediums regarding real-time responses, personalized advice, and follow-up inquiries, highlighting the potential of new technology for public health promotion. It also discusses the health disparities caused by the limitations of GenAI, such as individuals’ inability to evaluate information, restricted access to services, and the lack of skill development. Overall, this study lays the groundwork for future research on how GenAI could be leveraged for public health promotion and how its challenges and barriers may exacerbate health inequities. It underscores the need for more empirical studies, as well as the importance of enhancing digital literacy and increasing access to technology for socially disadvantaged populations.
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
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?
Racialized and marginalized groups bore the greatest burden of COVID-19, replicating and sometimes widening pre-pandemic health disparities.
“Racialized and marginalized groups bore the greatest burden of COVID-19, replicating and sometimes widening the health disparities that were already evident pre-pandemic (7, 8).”
From The Health Communications Assessment Checklist: a teaching tool for uncovering bias in the age of AI (2026) · cites this paper as [8]
The “Potential Health Disparity Through GenAI” section says disadvantaged groups, including racial and ethnic minorities, experience worse health and greater health risks. The “Digital Divide on the Internet” section notes reduced telemedicine use among some patients during COVID-19. Neither passage establishes that these groups bore the greatest burden of COVID-19 or that the pandemic widened pre-existing health disparities. (LLM, conf=0.75)
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.
Cites
A typology of reviews: an analysis of 14 review types and associated methodologies
Grant, M. J., & Booth, A. (2009) · Health Information & Libraries Journal · doi:10.1111/j.1471-1842.2009.00848.x · Cited by 10,817 · see citing works
Uses and Gratifications Research
Katz, E., Blumler, J. G., & Gurevitch, M. (1973) · Public Opinion Quarterly · doi:10.1086/268109 · Cited by 4,012 · cited 2× · see citing works
“Additionally, health promotion and health disparities are briefly analyzed through the lenses of the Technology Acceptance Model 2 (TAM2) [19], the uses and gratifications theory [20], and the knowledge gap hypothesis [21].”
The Internet of Things for Health Care: A Comprehensive Survey
Islam, S. M. R., Kwak, D., Kabir, M. H., Hossain, M., & Kwak, K.-S. (2015) · IEEE Access · doi:10.1109/access.2015.2437951 · Cited by 3,199 · see citing works
Sallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126 · cited 2× · see citing works
“…advantageous for health communication, enabling it to address various health inquiries, deliver customized health information, provide education, offer consultations, assist in disease diagnosis, simplify complex health reports, and translate health-related questions into multiple languages [5-7].”
The Technology Acceptance Model: Its past and its future in health care
Holden, R. J., & Karsh, B.-T. (2010) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2009.07.002 · Cited by 2,669 · see citing works
eHealth Literacy: Essential Skills for Consumer Health in a Networked World.
Norman, C. D., & Skinner, H. A. (2006) · Journal of Medical Internet Research · doi:10.2196/jmir.8.2.e9 · Cited by 2,643 · see citing works
Webb, T. L., Joseph, J., Yardley, L., & Michie, S. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1376 · Cited by 2,517 · see citing works
Moorhead, S. A., Hazlett, D. E., Harrison, L., Carroll, J. K., Irwin, A., & Hoving, C. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.1933 · Cited by 2,517 · see citing works
Technology acceptance model: a literature review from 1986 to 2013
Marangunić, N., & Granić, A. (2015) · Universal Access in the Information Society · doi:10.1007/s10209-014-0348-1 · Cited by 2,458 · see citing works
A review of wearable sensors and systems with application in rehabilitation
Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2012) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-9-21 · Cited by 2,396 · see citing works
Free, C., Phillips, G., Galli, L., Watson, L., Felix, L., Edwards, P., Patel, V., & Haines, A. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001362 · Cited by 1,766 · see citing works
Consumer health information seeking on the internet: the state of the art
Cline, R. J. W. (2001) · Health Education Research · doi:10.1093/her/16.6.671 · Cited by 1,708 · see citing works
Health disparities and health equity: Concepts and measurement
Braveman, P. (2006) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.27.021405.102103 · Cited by 1,570 · see citing works
Prevalence of health misinformation on social media: systematic review
Suarez-Lledo, V., & Alvarez-Galvez, J. (2021) · Journal of Medical Internet Research · doi:10.2196/17187 · Cited by 1,564 · see citing works
Mass Media Flow and Differential Growth in Knowledge
Tichenor, P. J., Donohue, G. A., & Olien, C. N. (1970) · Public Opinion Quarterly · doi:10.1086/267786 · Cited by 1,537 · see citing works
Virtual Reality in the Assessment, Understanding, and Treatment of Mental Health Disorders
Freeman, D., Reeve, S., Robinson, A., Ehlers, A., Clark, D., Spanlang, B., & Slater, M. (2017) · Psychological Medicine · doi:10.1017/s003329171700040x · Cited by 1,428 · see citing works
Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024) · Business & Information Systems Engineering · doi:10.1007/s12599-023-00834-7 · Cited by 1,409 · cited 2× · see citing works
“GenAI is poised to transform content creation across text, image, audio, and video formats [46].”
Why Youth Heart Social Network Sites: The Role of Networked Publics in Teenage Social LifePreprint
boyd, D. (2017) · doi:10.31219/osf.io/22hq2 · Cited by 1,408 · see citing works
Wearable Sensors for Remote Health Monitoring
Majumder, S., Mondal, T., & Deen, M. (2017) · Sensors · doi:10.3390/s17010130 · Cited by 1,375 · see citing works
Generative AI and ChatGPT: applications, challenges, and AI-human collaboration
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2233814 · Cited by 1,363 · see citing works
Public health and online misinformation: challenges and recommendations
Swire-Thompson, B., & Lazer, D. (2020) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040119-094127 · Cited by 1,170 · see citing works
Effectiveness of telemedicine: A systematic review of reviews
Ekeland, A. G., Bowes, A., & Flottorp, S. (2010) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2010.08.006 · Cited by 1,162 · see citing works
Hamine, S., Gerth-Guyette, E., Faulx, D., Green, B. B., & Ginsburg, A. S. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3951 · Cited by 1,149 · see citing works
Social media use in the United States: implications for health communication
Chou, W.-Y. S., Hunt, Y. M., Beckjord, E. B., Moser, R. P., & Hesse, B. W. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1249 · Cited by 1,082 · see citing works
Social Media Use for Health Purposes: Systematic Review
Chen, J., & Wang, Y. (2021) · Journal of Medical Internet Research · doi:10.2196/17917 · Cited by 1,073 · see citing works
Internet skills and the digital divide
van Deursen, A. J. A. M., & van Dijk, J. A. G. M. (2010) · New Media & Society · doi:10.1177/1461444810386774 · Cited by 997 · see citing works
Harnessing Social Media for Health Promotion and Behavior Change
Korda, H., & Itani, Z. (2011) · Health Promotion Practice · doi:10.1177/1524839911405850 · Cited by 939 · see citing works
Boulos, M. N. K., & Wheeler, S. (2007) · Health Information & Libraries Journal · doi:10.1111/j.1471-1842.2007.00701.x · Cited by 894 · see citing works
Timotheou, S., Miliou, O., Dimitriadis, Y., Sobrino, S. V., Giannoutsou, N., Cachia, R., Monés, A. M., & Ioannou, A. (2023) · Education and Information Technologies · doi:10.1007/s10639-022-11431-8 · Cited by 816 · see citing works
Electronic Health Records: Then, Now, and in the Future
Evans, R. S. (2016) · Yearbook of Medical Informatics · doi:10.15265/iys-2016-s006 · Cited by 816 · see citing works
The Delivery of Public Health Interventions via the Internet: Actualizing Their Potential
Bennett, G. G., & Glasgow, R. E. (2009) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.031308.100235 · Cited by 800 · see citing works
Tennant, B., Stellefson, M., Dodd, V. J. N., Chaney, B. H., Chaney, D. J., Paige, S. R., & Alber, J. M. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3992 · Cited by 762 · see citing works
Maher, C. A., Lewis, L. K., Ferrar, K., Marshall, S., De Bourdeaudhuij, I., & Vandelanotte, C. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.2952 · Cited by 733 · see citing works
Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial
Meskó, B. (2023) · Journal of Medical Internet Research · doi:10.2196/50638 · Cited by 709 · see citing works
Wearable health devices in health care: narrative systematic review
Lu, L., Zhang, J., Xie, Y., Gao, F., Xu, S., Wu, X., & Ye, Z. (2020) · JMIR mHealth and uHealth · doi:10.2196/18907 · Cited by 701 · see citing works
A meta-analysis of web-delivered tailored health behavior change interventions
Lustria, M. L. A., Noar, S. M., Cortese, J., Van Stee, S. K., Glueckauf, R. L., & Lee, J. (2013) · Journal of Health Communication · doi:10.1080/10810730.2013.768727 · Cited by 689 · see citing works
Blockchain in healthcare and health sciences—A scoping review
Hasselgren, A., Kralevska, K., Gligoroski, D., Pedersen, S. A., & Faxvaag, A. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.104040 · Cited by 676 · cited 1× · see citing works
“The internet has become a vital medium for health communication in the era of Web 2.0 [22], evolving across various domains such as social media [17,23], mobile health [24], the Internet of Things [25], blockchain [26], wearable devices [27,28], and, more recently, GenAI [12].”
InfluentialInternet-based interventions for smoking cessation
Taylor, G. M. J., Dalili, M. N., Semwal, M., Čivljak, M., Sheikh, A., & Car, J. (2017) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd007078.pub5 · Cited by 651 · see citing works
The Internet and Knowledge Gaps
Bonfadelli, H. (2002) · European Journal of Communication · doi:10.1177/0267323102017001607 · Cited by 650 · see citing works
Augmented Reality: An Overview
Carmigniani, J., & Furht, B. (2011) · Springer eBooks · doi:10.1007/978-1-4614-0064-6_1 · Cited by 626 · see citing works
Furht, B. (2011) · Springer eBooks · doi:10.1007/978-1-4614-0064-6 · Cited by 620 · see citing works
Telemedicine in the era of COVID-19
Portnoy, J., Waller, M., & Elliott, T. (2020) · The Journal of Allergy and Clinical Immunology In Practice · doi:10.1016/j.jaip.2020.03.008 · Cited by 616 · see citing works
Editors’ Comment: So, What Is a Conceptual Paper?
Gilson, L. L., & Goldberg, C. B. (2015) · Group & Organization Management · doi:10.1177/1059601115576425 · Cited by 614 · see citing works
Receiving social support online: implications for health education
White, M. (2001) · Health Education Research · doi:10.1093/her/16.6.693 · Cited by 606 · see citing works
Murugesan, S. (2007) · IT Professional · doi:10.1109/mitp.2007.78 · Cited by 605 · see citing works
Internet use and stigmatized illness
Berger, M., Wagner, T. H., & Baker, L. C. (2005) · Social Science & Medicine · doi:10.1016/j.socscimed.2005.03.025 · Cited by 547 · see citing works
Zack, T., Lehman, E., Suzgun, M., Rodriguez, J. A., Celi, L. A., Gichoya, J., Jurafsky, D., Szolovits, P., Bates, D. W., Abdulnour, R.-E. E., et al. (2024) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00225-x · Cited by 510 · see citing works
The Internet of Things: Impact and Implications for Health Care Delivery
Kelly, J. T., Campbell, K. L., Gong, E., & Scuffham, P. (2020) · Journal of Medical Internet Research · doi:10.2196/20135 · Cited by 495 · see citing works
Health literacy in the eHealth era: A systematic review of the literature
Kim, H., & Xie, B. (2017) · Patient Education and Counseling · doi:10.1016/j.pec.2017.01.015 · Cited by 457 · see citing works
Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges
Zhang, P., & Kamel Boulos, M. N. (2023) · Future Internet · doi:10.3390/fi15090286 · Cited by 411 · cited 3× · see citing works
“…advantageous for health communication, enabling it to address various health inquiries, deliver customized health information, provide education, offer consultations, assist in disease diagnosis, simplify complex health reports, and translate health-related questions into multiple languages [5-7].”
Online Health Information Seeking: A Review and Meta-Analysis
Wang, X., Shi, J. J., & Kong, H. (2020) · Health Communication · doi:10.1080/10410236.2020.1748829 · Cited by 403 · see citing works
The Relationship between Health Literacy and Health Disparities: A Systematic Review
Mantwill, S., Monestel-Umaña, S., & Schulz, P. J. (2015) · PLOS ONE · doi:10.1371/journal.pone.0145455 · Cited by 395 · see citing works
Estacio, E. V., Whittle, R., & Protheroe, J. (2017) · Journal of Health Psychology · doi:10.1177/1359105317695429 · Cited by 315 · see citing works
Bickmore, T. W., Trinh, H., Olafsson, S., O'Leary, T. K., Asadi, R., Rickles, N. M., & Cruz, R. (2018) · Journal of Medical Internet Research · doi:10.2196/11510 · Cited by 308 · see citing works
Augmented reality in healthcare education: an integrative review
Zhu, E., Hadadgar, A., Masiello, I., & Zary, N. (2014) · PeerJ · doi:10.7717/peerj.469 · Cited by 298 · see citing works
Augmented reality and mixed reality for healthcare education beyond surgery: an integrative review
Gerup, J., Soerensen, C. B., & Dieckmann, P. (2020) · International Journal of Medical Education · doi:10.5116/ijme.5e01.eb1a · Cited by 291 · see citing works
Health Communication on the Internet: An Effective Channel for Health Behavior Change?
JACKS, M. M. C. C. (1998) · Journal of Health Communication · doi:10.1080/108107398127517 · Cited by 283 · see citing works
Seeking and sharing health information online
Choudhury, M. D., Morris, M. R., & White, R. W. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557214 · Cited by 251 · see citing works
Eruchalu, C. N., Pichardo, M. S., Bharadwaj, M., Rodriguez, C. B., Rodriguez, J. A., Bergmark, R. W., Bates, D. W., & Ortega, G. (2021) · Journal of Urban Health · doi:10.1007/s11524-020-00508-9 · Cited by 245 · see citing works
ChatGPT is not all you need. A state-of-the-art review of large generative AI models
Gozalo-Brizuela, R., & Garrido-Merchan, E. C. (2023) · arXiv · doi:10.48550/arxiv.2301.04655 · Cited by 245 · see citing works
Chung, J. E. (2013) · Journal of Health Communication · doi:10.1080/10810730.2012.757396 · Cited by 240 · see citing works
Health promotion and health education: advancing the concepts
Whitehead, D. (2004) · Journal of Advanced Nursing · doi:10.1111/j.1365-2648.2004.03095.x · Cited by 238 · see citing works
Using Online Health Communities to Deliver Patient-Centered Care to People With Chronic Conditions
van der Eijk, M., Faber, M. J., Aarts, J. W., Kremer, J. A., Munneke, M., & Bloem, B. R. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2476 · Cited by 238 · see citing works
Rains, S. A. (2007) · Journal of Health Communication · doi:10.1080/10810730701619992 · Cited by 236 · see citing works
The mobile revolution—using smartphone apps to prevent cardiovascular disease
Neubeck, L., Lowres, N., Benjamin, E. J., Freedman, S. B., Coorey, G., & Redfern, J. (2015) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2015.34 · Cited by 232 · see citing works
Social support in a wired world: Use of online mental health forums in Norway
Kummervold, P. E., Gammon, D., Bergvik, S., Johnsen, J.-A. K., Hasvold, T., & Rosenvinge, J. H. (2002) · Nordic Journal of Psychiatry · doi:10.1080/08039480252803945 · Cited by 223 · see citing works
Health on the Internet: implications for health promotion
Korp, P. (2005) · Health Education Research · doi:10.1093/her/cyh043 · Cited by 222 · see citing works
Johnston, A. C., Worrell, J. L. “., Gangi, P. M. D., & Wasko, M. M. (2013) · Information Technology and People · doi:10.1108/itp-02-2013-0040 · Cited by 210 · see citing works
E-mail in patient–provider communication: A systematic review
Ye, J., Rust, G. S., Fry-Johnson, Y. W., & Strothers, H. (2009) · Patient Education and Counseling · doi:10.1016/j.pec.2009.09.038 · Cited by 198 · see citing works
Health-Related On-Line Forums: What's the Big Attraction?
Tanis, M. (2008) · Journal of Health Communication · doi:10.1080/10810730802415316 · Cited by 198 · see citing works
Wang, X., Zhao, K., & Street, N. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6834 · Cited by 182 · see citing works
Nguyen, A., Mosadeghi, S., & Almario, C. V. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.04.008 · Cited by 180 · see citing works
Santarossa, S., Kane, D., Senn, C. Y., & Woodruff, S. J. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8480 · Cited by 172 · see citing works
Esmaeilzadeh, P., & Mirzaei, T. (2019) · Journal of Medical Internet Research · doi:10.2196/14184 · Cited by 148 · see citing works
Telemedicine: Its Effects on Health Communication
Matusitz, J., & Breen, G.-M. (2007) · Health Communication · doi:10.1080/10410230701283439 · Cited by 146 · see citing works
A scoping review to assess the effects of virtual reality in medical education and clinical care
Dhar, E., Upadhyay, U., Huang, Y., Uddin, M., Manias, G., Kyriazis, D., Wajid, U., Alshawaf, H., & Syed-Abdul, S. (2023) · Digital Health · doi:10.1177/20552076231158022 · Cited by 138 · see citing works
The Application of Virtual Reality in Patient Education
Pandrangi, V. C., Gaston, B., Appelbaum, N., Albuquerque, F. C., Levy, M., & Larson, R. A. (2019) · Annals of Vascular Surgery · doi:10.1016/j.avsg.2019.01.015 · Cited by 132 · see citing works
Addressing social determinants of health inequities through settings: a rapid review
Newman, L., Baum, F. E., Javanparast, S., OʼRourke, K., & Carlon, L. (2015) · Health Promotion International · doi:10.1093/heapro/dav054 · Cited by 129 · see citing works
Benefits and harms from Internet use: A differentiated analysis of Great Britain
Blank, G., & Lutz, C. (2016) · New Media & Society · doi:10.1177/1461444816667135 · Cited by 127 · see citing works
Public Health Messaging in an Era of Social Media
Merchant, R. M., South, E. C., & Lurie, N. (2021) · JAMA · doi:10.1001/jama.2020.24514 · Cited by 121 · see citing works
Shi, J. J., Poorisat, T., & Salmon, C. T. (2016) · Health Communication · doi:10.1080/10410236.2016.1242035 · Cited by 118 · see citing works
Shang, L., Zhou, J., & Zuo, M. (2020) · Internet Research · doi:10.1108/intr-12-2019-0512 · Cited by 116 · see citing works
Health Benefits and Risks of the Internet
Levy, J. A., & Strombeck, R. D. (2002) · Journal of Medical Systems · doi:10.1023/a:1020288508362 · Cited by 112 · see citing works
Digital health promotion: promise and peril
Koh, A., Swanepoel, D. W., Ling, A. M. C., Ho, B. L., Tan, S. Y., & Lim, J. F. Y. (2021) · Health Promotion International · doi:10.1093/heapro/daab134 · Cited by 104 · see citing works
Researching the 'Informed Patient
Kivits, J. (2004) · Information Communication & Society · doi:10.1080/1369118042000305629 · Cited by 92 · see citing works
Lin, T. T. C., & Bautista, J. R. (2017) · Journal of Health Communication · doi:10.1080/10810730.2017.1296508 · Cited by 89 · see citing works
An Empirical Study of Older Adult’s Voice Assistant Use for Health Information Seeking
Brewer, R., Pierce, C., Upadhyay, P., & Park, L. (2022) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3484507 · Cited by 89 · see citing works
Enhancing learning through use of interactive tools on health-related websites
Stout, P. A. (2001) · Health Education Research · doi:10.1093/her/16.6.721 · Cited by 82 · see citing works
Where people look for online health information
LaValley, S. A., Kiviniemi, M. T., & Gage‐Bouchard, E. A. (2016) · Health Information & Libraries Journal · doi:10.1111/hir.12143 · Cited by 81 · see citing works
A Comparative Analysis of Generative Artificial Intelligence Tools for Natural Language Processing
Iorliam, A., & Ingio, J. A. (2024) · Journal of Computing Theories and Applications · doi:10.62411/jcta.9447 · Cited by 74 · see citing works
Edney, S. M., Bogomolova, S., Ryan, J. C., Olds, T., Sanders, I., & Maher, C. A. (2018) · Journal of Medical Internet Research · doi:10.2196/10911 · Cited by 69 · see citing works
Jiang, S. (2019) · Health Communication · doi:10.1080/10410236.2018.1563030 · Cited by 67 · see citing works
Health Literacy and Clear Communication Best Practices for Telemedicine
Coleman, C. (2020) · HLRP Health Literacy Research and Practice · doi:10.3928/24748307-20200924-01 · Cited by 57 · see citing works
Friedman, V. J., Wright, C. C. J., Molenaar, A., McCaffrey, T. A., Brennan, L. L., & Lim, M. S. C. (2022) · Journal of Medical Internet Research · doi:10.2196/28063 · Cited by 57 · see citing works
Generative AI for Visualization: Opportunities and Challenges
Basole, R. C., & Major, T. (2024) · IEEE Computer Graphics and Applications · doi:10.1109/mcg.2024.3362168 · Cited by 52 · see citing works
Can ChatGPT improve communication in hospitals?
Calonge, D. S., Aguerrebere, P. M., Hultberg, P. T., & Shah, M. A. (2023) · El Profesional de la Informacion · doi:10.3145/epi.2023.mar.19 · Cited by 43 · see citing works
3D Elevation Program supports broadband internet access
Thatcher, C. A., & Lukas, V. (2021) · Fact sheet · doi:10.3133/fs20213056 · Cited by 41 · see citing works
Jiang, S., Hong, Y., & Liu, P. L. (2019) · Journal of Cancer Survivorship · doi:10.1007/s11764-019-00742-4 · Cited by 41 · see citing works
eHealth patient-provider communication in the United States: interest, inequalities, and predictors
Spooner, K. K., Salemi, J. L., Salihu, H. M., & Zoorob, R. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw087 · Cited by 38 · see citing works
An, J., Kwak, H., Qureshi, H. M., & Weber, I. G. (2021) · JMIR Formative Research · doi:10.2196/22313 · Cited by 37 · see citing works
Chiswell, M., Smissen, A., Ugalde, A., Lawson, D., Whiffen, R., Brockington, S., & Boltong, A. G. (2016) · Journal of Cancer Education · doi:10.1007/s13187-016-1138-7 · Cited by 37 · see citing works
Characteristics and efficacy of digital health education: An overview of systematic reviews
McCall, M., Spencer, E. A., Owen, H., Roberts, N. W., & Heneghan, C. J. (2018) · Health Education Journal · doi:10.1177/0017896918762013 · Cited by 33 · see citing works
Oh, S. W., Kim, K. K., Kim, S. S., Park, S.-K., & Park, S. (2021) · JMIR mhealth and uhealth · doi:10.2196/27192 · Cited by 32 · see citing works
Voice Assistants and Cancer Screening: A Comparison of Alexa, Siri, Google Assistant, and Cortana
Hong, G., Folcarelli, A., Less, J., Wang, C., Erbasi, N., & Lin, S. (2021) · The Annals of Family Medicine · doi:10.1370/afm.2713 · Cited by 32 · see citing works
Vilaro, M. J., Wilson-Howard, D. S., Zalake, M. S., Tavassoli, F., Lok, B. C. L., Modave, F. P., George, T. J., Odedina, F. T., Carek, P. J., & Krieger, J. L. R. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01549-z · Cited by 28 · see citing works
Liu, P. L., & Yeo, T. E. D. (2021) · Health Communication · doi:10.1080/10410236.2021.1961971 · Cited by 28 · see citing works
Pew Internet & American Life Project
(2013) · Choice Reviews Online · doi:10.5860/choice.51-2434 · Cited by 26 · see citing works
Yang, G., Long, J., Luo, D., Xiao, S., & Kaminga, A. C. (2019) · JMIR mhealth and uhealth · doi:10.2196/12573 · Cited by 24 · see citing works
Use of podcasts for health education: a scoping review
Amador, F. L. D., Alves, G. C. G., dos Santos, V. R., & Moreira, R. S. L. (2024) · Revista Brasileira de Enfermagem · doi:10.1590/0034-7167-2023-0096pt · Cited by 22 · see citing works
Evaluation of COVID-19 Information Provided by Digital Voice Assistants
Goh, A. S. Y., Wong, L. L., & Yap, K. Y. (2021) · International Journal of Digital Health · doi:10.29337/ijdh.25 · Cited by 18 · see citing works
Rajagopal, S., Sohn, J. H., Subramonyam, H., & Mohan, S. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2402.00234 · Cited by 3 · see citing works
Communication Skills of Gynaecological Medical Staff Concerning the Patient
Latifi, H., & Latifi, D. (2023) · Journal of Health Sciences and Medical Development · doi:10.56741/hesmed.v2i03.358 · Cited by 1 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
He, F., Yang, M., Li, J., Gong, T., Ma, J., Yang, T., Zhao, D., Li, S., & Tian, D. (2025) · BMC Public Health · doi:10.1186/s12889-025-22963-2 · Cited by 46 · see citing works
The role of personality traits in predicting educational use of generative AI in higher education
Arpacı, İ., Kuşci, İ., & Gibreel, O. (2025) · Scientific Reports · doi:10.1038/s41598-025-16339-0 · Cited by 30 · see citing works
Artificial intelligence applications and pedagogical challenges in music education
Mazlan, C. A. N., Hanafi, H. F., Sarifin, M. R., Noor, A. R. M., Sadykova, S., Hidayatullah, R., & Jamnongsarn, S. (2026) · Discover Education · doi:10.1007/s44217-026-01127-3 · Cited by 14 · see citing works
Raza, S., Goel, R., Erikstrup, C., D'Alessandro, A., Custer, B., Li, N., & Party, T. I. B. D. W. (2026) · Vox Sanguinis · doi:10.1111/vox.70236 · Cited by 5 · see citing works
Khalifa, A., & Hussein, R. (2026) · Journal of Medical Systems · doi:10.1007/s10916-026-02391-4 · Cited by 5 · see citing works
Owens-Young, J. L., & Leider, J. P. (2025) · Journal of Public Health Management and Practice · doi:10.1097/phh.0000000000002250 · Cited by 3 · see citing works
Gu, C., & Zhang, J. (2025) · Current Psychology · doi:10.1007/s12144-025-08899-1 · Cited by 4 · see citing works
Application of Gemini in Public Health Amid the Artificial Intelligence Era
Tatar, M., Farokhi, S., Foumani, A. A., Uzunlar, E., & Araz, Ö. M. (2025) · IEEE Engineering Management Review · doi:10.1109/emr.2025.3577913 · Cited by 4 · see citing works
Al-Naser, Y., Sharma, S., Niure, K., Ibach, K., Khosa, F., & Yong-Hing, C. J. (2025) · Journal of medical imaging and radiation sciences · doi:10.1016/j.jmir.2025.102122 · Cited by 2 · see citing works
Liu, T., Pang, P., Luo, Y. T., McKay, D., Buchanan, G. R., & Chang, S. (2026) · JMIR Aging · doi:10.2196/88005 · Cited by 2 · see citing works
Gu, C., Zhuo, X., & Jiang, K. (2026) · Journal of Health Communication · doi:10.1080/10810730.2026.2681655 · Cited by 2 · see citing works
Radó, N., Németh, O., & Békási, S. (2025) · JMIR Formative Research · doi:10.2196/68316 · Cited by 1 · see citing works
Uddin, J. (2025) · Journal of Communications In Healthcare · doi:10.1080/17538068.2025.2594768 · Cited by 1 · see citing works
Self-citationAnbari, A. B., Maturino, K., Goth, O., Jesudasan, G. H., & Bautista, J. R. (2026) · Public Health · doi:10.1016/j.puhe.2026.106278 · Cited by 1 · see citing works
Chen, X., 駱旭琛, & Deng, J. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2026.1817890 · Cited by 1 · see citing works
Zhu, H., & Ding, J. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1827765 · Cited by 1 · see citing works
The Health Communications Assessment Checklist: a teaching tool for uncovering bias in the age of AI
Ofrane, R. H., Canada, T., & Birnbaum, A. S. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1872506
“Racialized and marginalized groups bore the greatest burden of COVID-19, replicating and some-times widening the health disparities that were already evident pre-pandemic (7, 8).”
Mutinta, G. (2025) · Springer eBooks · doi:10.1007/978-3-032-04508-9_8
Brunelli, L. D. L., Fonda, F., & Brusaferro, S. (2026) · JMIR Medical Education · doi:10.2196/92246
GenAI Agent for Automated Analysis and Personalization of Drug Prevention Campaigns
Aljaafari, M. A. H., & Sorour, S. E. (2026) · Scientific Journal of King Faisal University Humanities and Management Sciences · doi:10.37575/h/mng/250075
Zhao, L., & Sui, F. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2026.106361
Can ChatGPT-5 educate the public about vasectomy?: a Google Trends–based expert panel assessment
Albaz, A. C., Erbatu, O., Yigit, O., Üçer, O., Temeltaş, G., & Müezzi̇noğlu, T. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1726517
Liu, V., Wong, A. H. K., Wang, P., & de Cruz, N. P. (2026) · Services Marketing Quarterly · doi:10.1080/15332969.2026.2653485
Graziosi, A., Santoni, M., Cari, L., Gozzo, L., Crucitta, S., Sotto, A. D., Altamura, C., Giacomo, S. D., Rizzi, L., Ruocco, C., et al. (2026) · JMIR Formative Research · doi:10.2196/93245
Wang, X., Li, L., Cai, X., Luo, W., Shen, M., Zuo, Y., Zhang, J., Bai, Z., Yao, Y., Zhang, M., et al. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1779200
Xie, Q., Ye, D., Ren, R., & Hua, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29596-5_16
MacKay, M., Gosselin, S., Sonier, K., Wong, J., Zamani, S., Zarrinkalam, F., & McWhirter, J. E. (2026) · Journal of Health Communication · doi:10.1080/10810730.2026.2709807
Dığış, M., Kaya, K., Demir, B., Cicek, I. N., Akdağ, D., & Akdağ, Ş. (2026) · Cutaneous and Ocular Toxicology · doi:10.1080/15569527.2026.2711643 · Cited by 1 · see citing works
Voices from Reddit: Users’ Experiences and Opinions with Generative AI for Health Problems
庞远英, Atrinawati, L., Li, R., He, Z., & Lustria, M. L. A. (2026) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi69079.2026.00091
Wang, X., & Liu, W. (2026) · Science & Sports · doi:10.1016/j.scispo.2026.05.003
Xue, Z., Fu, K., Zhang, Y., Wu, B., & Wu, J. (2026) · Journal of Medical Internet Research · doi:10.2196/97852
- Authors
- Uddin, J., Feng, C., & Xu, J.
- Affiliations
- Cornell University (US)
- Tsinghua University (CN)
- Second Affiliated Hospital of Zhejiang University (CN)
- Corresponding author
- Xu, Junfang
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2025-03-06
- Volume
- 27
- Pages
- e66032
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC11926442
- OpenAlex
- W4408185357
- Cited by
- 31
- References
- 112
- Citations by year
- 2026: 22 · 2025: 9
- FWCI
- 39.11
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Fundamental Research Funds for the Central Universities
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Social Sciences › Health › Social Media in Health Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- health communication, health promotion, health disparities, generative AI, internet-based communication, Technology Acceptance Model 2, uses and gratifications theory, knowledge gap hypothesis, digital literacy, access to technology, personalized health advice
- MeSH terms
- Artificial Intelligence, Health Promotion, Humans, Public Health, Internet, Health Communication
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
