Cited by 250Health Literacy and Information AccessibilityMobile Health and mHealth ApplicationsHealth, Technology, Consumer Behavior

The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.

A systematic review of eHealth interventions to improve health literacy

Abstract

Implementation of eHealth is now considered an effective way to address concerns about the health status of health care consumers. The purpose of this study was to review empirically based eHealth intervention strategies designed to improve health literacy among consumers in a variety of settings. A computerized search of 16 databases of abstracts (e.g. Biomedical Reference Collection, Cochrane Central Register of Controlled Trials, Computers & Applied Sciences Complete, Health Technology Assessments, MEDLINE) were explored in a systematic fashion to assess the presence of eHealth applications targeting health literacy. Compared to control interventions, the interventions using technology reported significant outcomes or showed promise for future positive outcomes regarding health literacy in a variety of settings, for different diseases, and with diverse samples. This review has indicated that it is feasible to deliver eHealth interventions specifically designed to improve health literacy skills for people with different health conditions, risk factors, and socioeconomic backgrounds.

Overview

Integrity signals

Registry

Crossref · 10.1177/1460458214534092

Cites

44 of 44 references verified0 citation errors · 0 not checkable

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Citations

Cites

Show all 44 references

Research works printed but not linked: 11

  1. US Department of Health and Human Resources, 2013, Healthy people 2020: improving the health of Americans
  2. Ratzan SC, 2000, National library of medicine current bibliographies in medicine: health literacy
  3. Berkman ND, 2004, Literacy and health outcomes
  4. Garbers S, 2004, Prev Chronic Dis, 1, A07
  5. Rudd R, 2004, Literacy and health in America
  6. Beer BB, 2003, J Gen Intern Med, 18, 169
  7. Eysenbach G, Proceedings/AMIA symposium, 169
  8. Silber D, Presented at the European Commission’s first high-level conference on eHealth
  9. Institute of Medicine (US) Roundtable on Health Literacy. Health literacy, eHealth, and communication: putting the consumer first: workshop summary. Washington, DC: National Academies Press (US), 2009, http://www.ncbi.nlm.nih.gov/pubmed/20662120 (2009, accessed 31 October 2013).
  10. Hibbard JH, 2009, Am J Manag Care, 15, 353
  11. Ownby RL, Proceedings of the 8th international conference on HIV treatment and prevention adherence (IAPAC)

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Metadata

Authors
Jacobs, R. J., Lou, J. Q., Ownby, R. L., & Caballero, J.
Affiliations
Nova Southeastern University (US)
Corresponding author
Jacobs, Robin J
Venue
Health Informatics Journal
Published
2014-06-10
Volume
22
Issue
2
Pages
81-98
ISSN
  • 1355-4743 (ISSN-L)
  • 1460-4582
  • 1741-2811
OpenAlex
W2031942492
Cited by
249
References
44
Citations by year
2026: 17 · 2025: 28 · 2024: 24 · 2023: 25 · 2022: 24 · 2021: 26 · 2020: 26 · 2019: 27 · 2018: 19 · 2017: 15 · 2016: 9 · 2015: 8 · 2014: 1
FWCI
1.86
Type
journal article
Language
en
Open access
closed
Locations
  • Health Informatics Journal (publishedVersion)
  • PubMed (publishedVersion)
  • NSUWorks (Nova Southeastern University) (submittedVersion)
  • AMIA
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
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
Keywords
digital health interventions, health literacy, health information technology, patient education, health care consumers
MeSH terms
Computer Literacy, Health Education, Humans, Databases, Factual, Telemedicine, Internet, Health Literacy

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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.

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