Evidence mapPaperPMID 36978033Full record

SynthesisBMC geriatrics2023

Diagnostic accuracy of eHealth literacy measurement tools in older adults: a systematic review.

Yu Qing Huang, Laura Liu, Zahra Goodarzi, Jennifer A Watt

Full text readSystematic Review
In one paragraph

Synthesis in BMC geriatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  8. Review
  9. Understanding Health Information Needs: An Evaluation of Co-Design Video-Assisted Education.Journal of cancer education : the official journal of the American Association for Cancer Education · 2025
    Article
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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

4 authors.

Yu Qing HuangDivision of Geriatric Medicine, Department of Medicine, University of Toronto, 190 Elizabeth Street, R. Fraser Elliott Building, 3-805, Toronto, ON, M5G 2C4, Canada.
Laura LiuTemerty Faculty of Medicine, University of Toronto, 6 Queen's Park Crescent West, Third Floor, Toronto, ON, M5S 3H2, Canada.
Zahra GoodarziDepartment of Medicine, University of Calgary, Foothills Medical Centre - North Tower, 9Th Floor, 1403 - 29th Street NW, Calgary, AB, T2N 2T9, Canada.
Jennifer A WattDivision of Geriatric Medicine, Department of Medicine, University of Toronto, 190 Elizabeth Street, R. Fraser Elliott Building, 3-805, Toronto, ON, M5G 2C4, Canada. jennifer.watt@utoronto.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn Canada, virtual health care rapidly expanded during the COVID-19 pandemic. There is substantial variability between older adults in terms of digital literacy skills, which precludes equitable participation of some older adults in virtual care. Little is known about how to measure older adults' electronic health (eHealth) literacy, which could help healthcare providers to support older adults in accessing virtual care. Our study objective was to examine the diagnostic accuracy of eHealth literacy tools in older adults.

methodsWe completed a systematic review examining the validity of eHealth literacy tools compared to a reference standard or another tool. We searched MEDLINE, EMBASE, CENTRAL/CDSR, PsycINFO and grey literature for articles published from inception until January 13, 2021. We included studies where the mean population age was at least 60 years old. Two reviewers independently completed article screening, data abstraction, and risk of bias assessment using the Quality Assessment for Diagnostic Accuracy Studies-2 tool. We implemented the PROGRESS-Plus framework to describe the reporting of social determinants of health.

resultsWe identified 14,940 citations and included two studies. Included studies described three methods for assessing eHealth literacy: computer simulation, eHealth Literacy Scale (eHEALS), and Transactional Model of eHealth Literacy (TMeHL). eHEALS correlated moderately with participants' computer simulation performance (r = 0.34) and TMeHL correlated moderately to highly with eHEALS (r = 0.47-0.66). Using the PROGRESS-Plus framework, we identified shortcomings in the reporting of study participants' social determinants of health, including social capital and time-dependent relationships.

conclusionsWe found two tools to support clinicians in identifying older adults' eHealth literacy. However, given the shortcomings highlighted in the validation of eHealth literacy tools in older adults, future primary research describing the diagnostic accuracy of tools for measuring eHealth literacy in this population and how social determinants of health impact the assessment of eHealth literacy is needed to strengthen tool implementation in clinical practice. PROTOCOL REGISTRATION: We registered our systematic review of the literature a priori with PROSPERO (CRD42021238365).

Indexed as

COVID-19Health LiteracyTelemedicineAgedComputer SimulationCOVID-19 TestingElectronicsHumansInternetPandemicsSurveys and QuestionnairesComputer literacyDiagnostic accuracyDigital literacyE-health literacyElectronic health literacyElectronic health literacy toolsElectronic information literacyOlder adultsSystematic review

Identifiers

PMID36978033
PMCPMC10049781

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read24
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 Socratic graph.