Evidence map›Paper›PMID 36081750›Full record

ArticleDigital health

Comparative study of different SES neighborhood clinics for health literacy and internet access.

William C Livingood, Maria A B Bautista, Carmen Smotherman, Daidre Azueta, Jeremy Coleman, Reetu Grewal, Eric Stewart, Lori A Orlando, Christopher Scuderi

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–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

16 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
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  5. Factors impacting electronic patient-generated data use in safety-net systems: a qualitative study.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
  6. Assessing health literacy and diversity within the All of Us Research Program.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
  7. Article
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  15. Review
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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.

William C LivingoodOffice of Research Affairs, University of Florida College of Medicine-Jacksonville, USA.ORCID https://orcid.org/0000-0003-1851-4985
Maria A B BautistaOffice of Research Affairs, University of Florida College of Medicine-Jacksonville, USA.
Carmen SmothermanOffice of Research Affairs, University of Florida College of Medicine-Jacksonville, USA.
Daidre AzuetaDepartment of Community Health and Family Medicine, University of Florida College of Medicine-Jacksonville, USA.
Jeremy ColemanDepartment of Community Health and Family Medicine, University of Florida College of Medicine-Jacksonville, USA.
Reetu GrewalDepartment of Community Health and Family Medicine, University of Florida College of Medicine-Jacksonville, USA.
Eric StewartDepartment of Community Health and Family Medicine, University of Florida College of Medicine-Jacksonville, USA.
Lori A OrlandoDuke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, USA.
Christopher ScuderiDepartment of Community Health and Family Medicine, University of Florida College of Medicine-Jacksonville, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As healthcare services are increasingly dependent on patient utilization of technology to effectively deliver services, the digital divide has the potential to exacerbate health disparities if health literacy and internet access present formidable barriers to patient use of technology. Methods: We examined the differences in health literacy and internet access between lower and upper SES neighborhood primary-care clinics in Northeast Florida. The REALM-SF for health literacy was used to assess health literacy and census survey questions were used to assess internet and technology access, during the Fall, 2020. The clinics were affiliated with a safety-net hospital in a major city in Southeastern U.S. Results: Analysis of key demographic data confirmed that the responding patients from economically disadvantaged neighborhood clinics resided in economically disadvantaged zip codes (307 responding patients lived in lower SES neighborhoods) and did have lower education levels (3% of the patients from Upper SES clinics had 11 grade or lower education, compared to 21%-29% of patients from Lower SES clinics). Patient health literacy significantly differed between clinics located in economically disadvantaged neighborhoods and clinics located in more affluent neighborhoods, with Upper SES clinics being 2.4 times more likely to have 9th grade or higher reading level. Access to internet technology was also higher in the Upper SES clinics, with 59% of respondents from Upper SES clinics versus 32%-40% from Lower SES clinics owning a computer or an IPAD. Conclusion: Results of this study have important implications for patient-engaged use of digital technology for health. Healthcare and public health clinics should be aware of the difference in health literacy and internet access when implementing technology-based services, so that advances in medicine, including precision medicine and telehealth, can be disseminated and implemented with broad populations, including disadvantaged groups.

Indexed as

digital dividehealth disparityhealth equityHealth literacyinternet accessprecision medicineprimary care practice

Identifiers

PMID36081750
PMCPMC9445524

What OpenQuestion holds

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Registered trials

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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.