Evidence map›Paper›PMID 34647897›Full record

ArticleJournal of medical Internet research2021

Validity Evidence Based on Relations to Other Variables of the eHealth Literacy Questionnaire (eHLQ): Bayesian Approach to Test for Known-Groups Validity.

Christina Cheng, Gerald Elsworth, Richard H Osborne

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 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

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3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

3 authors.

Christina Cheng *Centre for Global Health and Equity, School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia.ORCID 0000-0002-8950-7689
Gerald Elsworth *Centre for Global Health and Equity, School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia.ORCID 0000-0001-6306-7593
Richard H Osborne *Centre for Global Health and Equity, School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia.ORCID 0000-0002-9081-2699

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs health resources and services are increasingly delivered through digital platforms, eHealth literacy is becoming a set of essential capabilities to improve consumer health in the digital era. To understand eHealth literacy needs, a meaningful measure is required. Strong initial evidence for the reliability and construct validity of inferences drawn from the eHealth Literacy Questionnaire (eHLQ) was obtained during its development in Denmark, but validity testing for varying purposes is an ongoing and cumulative process.

objectiveThis study aims to examine validity evidence based on relations to other variables-using data collected with the known-groups approach-to further explore if the eHLQ is a robust tool to understand eHealth literacy needs in different contexts. A priori hypotheses are set for the expected score differences among age, sex, education, and information and communication technology (ICT) use for each of the 7 eHealth literacy constructs represented by the 7 eHLQ scales.

methodsA Bayesian mediated multiple indicators multiple causes model approach was used to simultaneously identify group differences and test measurement invariance through differential item functioning across the groups, with ICT use as a mediator. A sample size of 500 participants was estimated. Data were collected at 3 diverse health sites in Australia.

resultsResponses from 525 participants were included for analysis. Being older was significantly related to lower scores in 4 eHLQ scales, with 3. Ability to actively engage with digital services having the strongest effect (total effect -0.37; P<.001), followed by 1. Using technology to process health information (total effect -0.32; P<.001), 5. Motivated to engage with digital services (total effect -0.21; P=.01), and 7. Digital services that suit individual needs (total effect -0.21; P=.02). However, the effects were only partially mediated by ICT use. Higher education was associated with higher scores in 1. Using technology to process health information (total effect 0.22; P=.01) and 3. Ability to actively engage with digital services (total effect 0.25; P<.001), with the effects mostly mediated by ICT use. Higher ICT use was related to higher scores in all scales except 2. Understanding health concepts and language and 4. Feel safe and in control. Either no or ignorable cases of differential item functioning were found across the 4 groups.

conclusionsBy using a Bayesian mediated multiple indicators multiple causes model, this study provides supportive validity evidence for the eHLQ based on relations to other variables as well as established evidence regarding internal structure related to measurement invariance across the groups for the 7 scales in the Australian community health context. This study also demonstrates that the eHLQ can be used to gain valuable insights into people's eHealth literacy needs to help optimize access and use of digital health and promote health equity.

Indexed as

Health LiteracyTelemedicineAustraliaBayes TheoremHealth PromotionHumansReproducibility of ResultsSurveys and Questionnairesdigital healtheHealthhealth equityhealth literacyhealth literacy questionnairemediation effectmobile phonequestionnaire designvalidity evidence

Identifiers

PMID34647897
PMCPMC8554672

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LicenceCC BY
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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.