Evidence map›Paper›PMID 41332797›Full record

ReviewJugan geon-gang gwa jilbyeong2024

[Concept of Digital Health Literacy: A Scoping Review].

Junghee Yoon, Mangyeong Lee, Juhee Cho

Abstract readEnglish AbstractReview
In one paragraph

Review in Jugan geon-gang gwa jilbyeong, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. eHealth literacy in emergency care: a scoping review.BMC health services research · 2026
    Article
  2. Article
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

3 authors.

Junghee Yoon성균관대학교 삼성융합의과학원 임상연구설계평가학과.ORCID https://orcid.org/0000-0003-1228-7435
Mangyeong Lee성균관대학교 삼성융합의과학원 디지털헬스학과.ORCID https://orcid.org/0000-0003-1228-7435
Juhee Cho성균관대학교 삼성융합의과학원 임상연구설계평가학과.ORCID https://orcid.org/0000-0003-1228-7435

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital health literacy (DHL) has become important for individuals to take on the responsibility to manage their health for chronic disease. However, few studies have investigated what is DHL and its associated factors. Thus, we conducted a scoping review to to address the above knowledge gaps, and to identify the concept of DHL designed to counter these impacts for clinical application. A systematic review was conducted of studies published in MEDLINE, Embase, Cochrane Library, Web of Science from January 2011 to October 2019 using PRISMA-ScR guideline. Articles eligible for inclusion focused on the conceptualization of DHL or electronic health (eHealth) literacy (EHL) including new digital health technologies, and clinical application reported on factors of DHL and Included newly developed measurement instruments referred to as DHL, and EHL including new digital health technologies. In 26 studies, various terms and definitions of DHL were used, and most articles described a concept of eHealth literacy as e-Health focused the use of information communication technologies. We defined 3 thematic categories as DHL: 1) advanced health literacy, 2) digital skills-based and multidimensional literacy and 3) others consisting of internal or external factors for the users' engagement in digital health. The findings from our study confirm that the basic approaches of DHL share the same scope with health literacy, but DHL included a broader context and new concepts such as technology-related ability. This study provides an integrated perspective on the status and influencing factors of DHL.

Indexed as

Digital healthDigital health literacyHealth literacyScoping review

Identifiers

PMID41332797
PMCPMC12479817

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.