New technologies, new disparities: The intersection of electronic health and digital health literacy
Open accessAbstract
Mobile health, or mHealth, is the implementation of digital health services with mobile and wearable devices, and has ample potential to enhance self-management of chronic conditions, especially cardiovascular risk factors (e.g., blood pressure control and supporting tobacco cessation and physical activity). It remains ambiguous, however, whether such technologies can improve cardiovascular outcomes. More importantly, mHealth carries the additional challenge of digital health literacy, which demands particular skills complementary to general and health literacy. Populations at risk for limited health literacy are similarly vulnerable to having challenges with digital health literacy. We identify such challenges and outline solutions to improve access to digital health services and their use for individuals with limited digital health literacy. We present an 18-point "Digital Universal Precautions" as a mandate for health care organizations committed towards addressing and facilitating eHealth literacy. As health care institutions increasingly advance mHealth through delivery of on-line material and patient portals, they face the challenge of ensuring that digital health services and content are available to all patients.
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?
The influence of digital literacy on the use of mHealth apps becomes much stronger when combined with experience with mHealth apps.
“In other words, the influence of individuals’ digital literacy on the use of mHealth apps becomes much stronger when combined with their experience with mHealth apps.80,81”
From The influence of digital literacy on mHealth app usability: The mediating role of patient expertise (2024) · cites this paper as [81]
The Abstract and “Limited digital health literacy: disparities in access and guidance” section link digital literacy challenges to difficulty using digital health services and apps. They do not say that experience with mHealth apps makes digital literacy’s influence on app use stronger; searches for app experience and an interaction found no such finding. Page numbers were not available in our copy. (LLM, conf=0.77)
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
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
Havranek, E. P., Mujahid, M. S., Barr, D. A., Blair, I. V., Cohen, M. S., Cruz-Flores, S., Davey-Smith, G., Dennison-Himmelfarb, C. R., Lauer, M. S., Lockwood, D. W., et al. (2015) · Circulation · doi:10.1161/cir.0000000000000228 · Cited by 1,472 · see citing works
Health App Use Among US Mobile Phone Owners: A National Survey
Krebs, P., & Duncan, D. T. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.4924 · Cited by 1,274 · see citing works
The impact of mHealth interventions: systematic review of systematic reviews
Marcolino, M. S., Oliveira, J. A. Q., D'Agostino, M., Ribeiro, A. L., Alkmim, M. B. M., & Novillo-Ortiz, D. (2018) · JMIR mHealth and uHealth · doi:10.2196/mhealth.8873 · Cited by 1,163 · see citing works
Kontos, E., Blake, K. D., Chou, W.-Y. S., & Prestin, A. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3117 · Cited by 917 · see citing works
eHealth Literacy: Extending the Digital Divide to the Realm of Health Information
Neter, E., & Brainin, E. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.1619 · Cited by 863 · see citing works
Magnani, J. W., Mujahid, M. S., Aronow, H. D., Cené, C. W., Dickson, V. V., Havranek, E. P., Morgenstern, L. B., Paasche‐Orlow, M. K., Pollak, A. W., & Willey, J. Z. (2018) · Circulation · doi:10.1161/cir.0000000000000579 · Cited by 597 · see citing works
Self-citationTen Attributes of Health Literate Health Care Organizations
Brach, C., Keller, D., Hernandez, L. M., Baur, C., Parker, R. M., Dreyer, B. P., Schyve, P. M., The Joint Commission, Lemerise, A. J., & Schillinger, D. (2012) · NAM Perspectives · doi:10.31478/201206a · Cited by 501 · see citing works
Gordon, N. P., & Hornbrook, M. C. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5105 · Cited by 369 · see citing works
Kampmeijer, R., Pavlova, M., Tambor, M., Golinowska, S., & Groot, W. (2016) · BMC Health Services Research · doi:10.1186/s12913-016-1522-3 · Cited by 328 · see citing works
Readability of online health information: implications for health literacy
Mcinnes, N., & Haglund, B. J. A. (2011) · Informatics for Health and Social Care · doi:10.3109/17538157.2010.542529 · Cited by 293 · 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
Thies, K., Anderson, D., & Cramer, B. (2017) · JMIR Human Factors · doi:10.2196/humanfactors.7709 · Cited by 118 · see citing works
Defining a Mobile Health Roadmap for Cardiovascular Health and Disease
Eapen, Z. J., Turakhia, M. P., McConnell, M. V., Graham, G. N., Dunn, P. J., Tiner, C., Rich, C., Harrington, R. A., Peterson, E. D., & Wayte, P. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.115.003119 · Cited by 51 · see citing works
Horvath, K. J., & Bauermeister, J. A. (2017) · AIDS Education and Prevention · doi:10.1521/aeap.2017.29.1.14 · Cited by 37 · see citing works
Janiak, E., Rhodes, E., & Foster, A. M. (2013) · Contraception · doi:10.1016/j.contraception.2013.09.004 · Cited by 17 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [18]Health Literacy Online: 2nd Edition Office of Disease Prevention and Health Promotion; 2018.
Cited by
Sorted by citations
Understanding and Responding to Health Literacy as a Social Determinant of Health
Nutbeam, D., & Lloyd, J. E. (2021) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-090419-102529 · Cited by 1,178 · see citing works
The Digital Health Competencies in Medical Education Framework
Car, J., Ong, Q. C., Erlikh Fox, T., Leightley, D., Kemp, S. J., Švab, I., Tsoi, K. K. F., Sam, A. H., Kent, F. M., Hertelendy, A. J., et al. (2025) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.53131 · Cited by 155 · see citing works
Fernandes, L. G., Devan, H., Fioratti, I., Kamper, S. J., Williams, C. M., & Saragiotto, B. T. (2022) · Pain · doi:10.1097/j.pain.0000000000002364 · Cited by 118 · see citing works
Sundell, E., Wångdahl, J., & Grauman, Å. (2022) · BMC Public Health · doi:10.1186/s12889-022-14751-z · Cited by 56 · see citing works
Impact of a Digital Lifestyle Intervention on Diabetes Self-Management: A Pilot Study
Bretschneider, M. P., Klásek, J., Karbanová, M., Timpel, P., Herrmann, S., & Schwarz, P. E. H. (2022) · Nutrients · doi:10.3390/nu14091810 · Cited by 39 · see citing works
The influence of digital literacy on mHealth app usability: The mediating role of patient expertise
Durmuş, A. (2024) · Digital Health · doi:10.1177/20552076241299061 · Cited by 30 · see citing works
Geana, M. V., Anderson, S., Lipnicky, A., Wickliffe, J. L., & Ramaswamy, M. (2021) · Journal of Health Care for the Poor and Underserved · doi:10.1353/hpu.2021.0053 · Cited by 18 · see citing works
A Roadmap to an Equitable Digital Diabetes Ecosystem
Kerr, D., Klonoff, D. C., Bergenstal, R. M., Choudhary, P., & Ji, L. (2023) · Endocrine Practice · doi:10.1016/j.eprac.2022.12.016 · Cited by 10 · see citing works
Equity and AI Governance at Academic Medical Centers
(2024) · The American Journal of Managed Care · doi:10.37765/ajmc.2024.89555 · Cited by 8 · see citing works
- Authors
- Smith, B., & Magnani, J. W.
- Affiliations
- University of Pittsburgh Medical Center (US)
- Corresponding author
- Magnani, Jared W.
- Venue
- International Journal of Cardiology
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 292
- Pages
- 280-282
- ISSN
- 0167-5273 (ISSN-L)
- PMC
- PMC6660987
- OpenAlex
- W2947323400
- Cited by
- 446
- References
- 16
- Citations by year
- 2026: 39 · 2025: 86 · 2024: 104 · 2023: 96 · 2022: 56 · 2021: 42 · 2020: 20 · 2019: 2
- FWCI
- 40.88
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- International Journal of Cardiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Heart, Lung, and Blood Institute (R61HL144669, R01HL143010)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Demography › Technology Use by Older Adults
- Keywords
- mobile health, digital health literacy, health literacy, e-health, digital divide, cardiovascular risk factors, chronic disease self-management, patient portals, wearable devices
- MeSH terms
- Humans, Telemedicine, Healthcare Disparities, Health Literacy
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