This paper is in the following e-collection/theme issue:

E-Health / Health Services Research and New Models of Care (517) Adoption and Change Management of eHealth Systems (712) Demographics of Users, Social & Digital Divide (739) Health Care Quality and Health Services Research (271) Health Services Research (482)

Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25809, first published .
Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study

Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study

Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study

Authors of this article:

Xin Yang1 Author Orcid Image ;   Ning Yang2 Author Orcid Image ;   Dwight Lewis1, 3 Author Orcid Image ;   Jason Parton1, 2 Author Orcid Image ;   Matthew Hudnall1, 2 Author Orcid Image
Article Authors Cited by (12) Tweetations (3) Metrics

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  2. Sun E, Alvarez C, Callahan L, Sheikh S. The Disparities in Patient Portal Use Among Patients With Rheumatic and Musculoskeletal Diseases: Retrospective Cross-sectional Study. Journal of Medical Internet Research 2022;24(8):e38802 View
  3. Meron A, Barber K, Stokes D, Churchill L, LeDoux C, Akuthota V. Feasibility and acceptability of a telemedicine triage model among Medicaid patients with low back pain referred to a spine center. North American Spine Society Journal (NASSJ) 2023;14:100200 View
  4. Zhu X, Tao Y, Zhu R, Wu D, Ming W. Impact of Hospital Characteristics and Governance Structure on the Adoption of Tracking Technologies for Clinical and Supply Chain Use: Longitudinal Study of US Hospitals. Journal of Medical Internet Research 2022;24(5):e33742 View
  5. Chagpar A. Sociodemographic factors affecting telemedicine access: A population-based analysis. Surgery 2022;171(3):793 View
  6. An B, Prabu V, Wallace L. Accessibility, Readability, and Document Complexity of Medicaid Enrollment Materials and Resources. American Journal of Health Education 2022;53(1):16 View
  7. Barrett M, Gondalia R, Vuong V, Kaye L, Hill A, Attisha E, Holtrop T. Retrospective assessment of a collaborative digital asthma program for Medicaid-enrolled children in southwest Detroit: reductions in short-acting beta-agonist (SABA) medication use. Asthma Research and Practice 2023;9(1) View
  8. Liu P, Yeo T, Ye J. Examining the Intervening Roles of Patient-Centered Care and Patient Activation in the Health Impacts of Offline Healthcare Obstacles and Online Health Consultations Among Deaf and Hard-of-Hearing Patients. Health Communication 2024;39(11):2366 View
  9. Wu Q, Ngien A, Jiang S. Descriptive Norms and eHealth Use Among Older Adults: A Cross-Country Comparative Study. Health Communication 2024;39(12):2971 View
  10. Chen Y, Turkson-Ocran R, Koirala B, Davidson P, Commodore-Mensah Y, Himmelfarb C. Association Between the Composite Cardiovascular Risk and mHealth Use Among Adults in the 2017-2020 Health Information National Trends Survey: Cross-Sectional Study. Journal of Medical Internet Research 2024;26:e46277 View
  11. Nwagwu W. A citation study of global research on e-Health literacy. Global Knowledge, Memory and Communication 2024 View
  12. Liu P. Online patient–provider communication and healthy ageing: the roles of health literacy and health self-efficacy. Health Promotion International 2024;39(5) View