Evidence map›Paper›PMID 39908081›Full record

ArticleJournal of medical Internet research2025

Measuring Digital Health Literacy in Older Adults: Development and Validation Study.

SungMin Kim, Choonghee Park, Sunghyeon Park, Dai-Jin Kim, Ye-Seul Bae, Jae-Heon Kang, Ji-Won Chun

Abstract readValidation Study
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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

7 authors.

SungMin KimDepartment of Medical Informatics, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-0597-7414
Choonghee ParkDepartment of Medical Informatics, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0009-0005-1782-4844
Sunghyeon ParkDepartment of Medical Informatics, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-2235-4358
Dai-Jin KimDepartment of Psychiatry, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-9408-5639
Ye-Seul BaeBig Data Research Center, School of Medicine, Kangbuk Samsung Hospital Sungkyunkwan University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0003-0763-5458
Jae-Heon KangDepartment of Family Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-5209-0824
Ji-Won ChunDepartment of Medical Informatics, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-0629-0358

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNew health care services such as smart health care and digital therapeutics have greatly expanded. To effectively use these services, digital health literacy skills, involving the use of digital devices to explore and understand health information, are important. Older adults, requiring consistent health management highlight the need for enhanced digital health literacy skills. To address this issue, it is imperative to develop methods to assess older adults' digital health literacy levels.

objectiveThis study aimed to develop a tool to measure digital health literacy. To this end, it reviewed existing literature to identify the components of digital health literacy, drafted preliminary items, and developed a scale using a representative sample.

methodsWe conducted a primary survey targeting 600 adults aged 55-75 years and performed an exploratory factor analysis on 74 preliminary items. Items with low factor loadings were removed, and their contents were modified to enhance their validity. Then, we conducted a secondary survey with 400 participants to perform exploratory and confirmatory factor analyses.

resultsA digital health literacy scale consisting of 25 items was developed, comprising 4 subfactors: use of digital devices, understanding health information, use and decision regarding health information, and use intention. The model fit indices indicated excellent structural validity (Tucker-Lewis Index=0.924, comparative fit index=0.916, root-mean-square error of approximation=0.088, standardized root-mean-square residual=0.044). High convergent validity (average variance extracted>0.5) and reliability (composite reliability>0.7) were observed within each factor. Discriminant validity was also confirmed as the square root of the average variance extracted was greater than the correlation coefficients between the factors. This scale demonstrates high reliability and excellent structural validity.

conclusionsThis study is a significant first step toward enhancing digital health literacy among older adults by developing an appropriate tool for measuring digital health literacy. We expect this study to contribute to the future provision of tailored education and treatment based on individual literacy levels.

Indexed as

Health LiteracyAgedFactor Analysis, StatisticalFemaleHumansMaleMiddle AgedSurveys and Questionnairesconfirmatory factor analysisdigital health caredigital health literacyexploratory factor analysismobile phoneolder adults

Identifiers

PMID39908081
PMCPMC11840366

What OpenQuestion holds

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LicenceCC BY
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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.