Evidence map›Paper›PMID 25363660›Full record

ArticleHealth expectations : an international journal of public participation in health care and health policy2015

Literacy disparities in patient access and health-related use of Internet and mobile technologies.

Stacy C Bailey, Rachel O'Conor, Elizabeth A Bojarski, Rebecca Mullen, Rachel E Patzer, Daniel Vicencio, Kara L Jacobson, Ruth M Parker, Michael S Wolf

Abstract readMulticenter Study
In one paragraph

Article in Health expectations : an international journal of public participation in health care and health policy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

70 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  9. Racial and immunologic disparities impact access to kidney rewaitlisting and retransplantation.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2026
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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Stacy C BaileyDivision of Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
Rachel O'ConorHealth Literacy and Learning Program, Division of General Internal Medicine, Feinberg School of Medicine at Northwestern University, Chicago, IL, USA.
Elizabeth A BojarskiHealth Literacy and Learning Program, Division of General Internal Medicine, Feinberg School of Medicine at Northwestern University, Chicago, IL, USA.
Rebecca MullenHealth Literacy and Learning Program, Division of General Internal Medicine, Feinberg School of Medicine at Northwestern University, Chicago, IL, USA.
Rachel E PatzerEmory University School of Medicine, Atlanta, GA, USA.
Daniel VicencioMercy Hospital and Medical Center, Chicago, IL, USA.
Kara L JacobsonSchool of Public Health, Emory University, Atlanta, GA, USA.
Ruth M ParkerEmory University School of Medicine, Atlanta, GA, USA.
Michael S WolfHealth Literacy and Learning Program, Division of General Internal Medicine, Feinberg School of Medicine at Northwestern University, Chicago, IL, USA.

Funding

Supplement to LitCog III: Health Literacy and Cognitive Function among Older AdultsR01AG030611 · NIA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI WOLF, MICHAEL S · 2007 to 2024
$11.6M
UNC Center for Diabetes Translation Research to Reduce Health DisparitiesP30DK093002 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVIS, RICHARD M · 2011 to 2015
$3.0M
NIA NIH HHS R01 AG030611NIA NIH HHS R01AG030611NIDDK NIH HHS P30 DK093002NIDDK NIH HHS P30DK093002
6 · The paper itself

Abstract

backgroundAge and race-related disparities in technology use have been well documented, but less is known about how health literacy influences technology access and use.

objectiveTo assess the association between patients' literacy skills and mobile phone ownership, use of text messaging, Internet access, and use of the Internet for health-related purposes.

methodsA secondary analysis utilizing data from 1077 primary care patients enrolled in two, multisite studies from 2011-2013. Patients were administered an in-person, structured interview.

resultsPatients with adequate health literacy were more likely to own a mobile phone or smartphone in comparison with patients having marginal or low literacy (mobile phone ownership: 96.8 vs. 95.2 vs. 90.1%, respectively, P < 0.001; smartphone ownership: 70.6 vs. 62.5 vs. 40.1%, P < 0.001) and to report text messaging (78.6 vs. 75.2 vs. 53.1%, P < 0.001). They were also more likely to have access to the Internet from their home (92.1 vs. 74.7 vs. 44.9%, P < 0.001) and to report using the Internet for email (93.0 vs. 75.7 vs. 38.5%, P < 0.001), browsing the web (93.9 vs. 80.2 vs. 44.5%, P < 0.001), accessing health information (86.3 vs. 75.5 vs. 40.8%, P < 0.001), and communicating with providers (54.2 vs. 29.8 vs. 13.0%, P < 0.001). Relationships remained significant in multivariable analyses controlling for relevant covariates.

conclusionsResults reveal that literacy-related disparities in technology access and use are widespread, with lower literate patients being less likely to own smartphones or to access and use the Internet, particularly for health reasons. Future interventions should consider these disparities and ensure that health promotion activities do not further exacerbate disparities.

Indexed as

Access to InformationHealth LiteracyInternetMedical InformaticsSmartphoneAgedFemaleHealthcare DisparitiesHealth SurveysHumansMaleMiddle AgedText Messaginghealth disparitieshealth information technologyhealth literacy

Identifiers

PMID25363660
PMCPMC4417455

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.