Evidence map›Paper›PMID 39099193›Full record

ArticleJournal of public health (Oxford, England)2024

Measuring health literacy to inform actions to address health inequities: a cluster analysis approach based on the Australian national health literacy survey.

Christina Cheng, Shandell Elmer, Roy Batterham, Melanie Hawkins, Richard H Osborne

Abstract read
In one paragraph

Article in Journal of public health (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

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

  1. Pooled it
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  4. Health Literacy and Type 1 Diabetes Mellitus: A Mixed Method Study.Health literacy research and practice · 2026
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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

5 authors.

Christina ChengCentre for Global Health and Equity, School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Victoria, Australia.ORCID 0000-0002-8950-7689
Shandell ElmerSchool of Nursing College of Health and Medicine, College of Health and Medicine, University of Tasmania, Launceston 7250, Tasmania, Australia.
Roy BatterhamGlobal Health Program, Faculty of Public Health, Thammasat University, Bangkok 10200, Thailand.
Melanie HawkinsCentre for Global Health and Equity, School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Victoria, Australia.
Richard H OsborneCentre for Global Health and Equity, School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Victoria, Australia.

Funding

National Health and Medical Research Council of Australia Principal Research Fellowship APP1155125
6 · The paper itself

Abstract

backgroundMeasuring health literacy can inform interventions to address health inequities. This study used cluster analysis to examine health literacy data to determine if it can provide more insightful information than standard descriptive analysis to better inform intervention development.

methodsUsing data from the Australian National Health Survey (2018), this study compared descriptive analysis and cluster analysis results of two states-New South Wales (NSW) and Victoria-generated from the Health Literacy Questionnaire (HLQ). Based on the nine scale scores of the HLQ, a hierarchical cluster analysis using Ward's method for linkage was undertaken.

resultsThe number of NSW and Victoria respondents was 1018 and 923, respectively. The nine HLQ scale full sample mean scores from both states were similar. However, the cluster analyses identified 11 clusters for NSW and 12 clusters for Victoria. While six clusters from each state presented similar health literacy patterns, five and six clusters from NSW and Victoria, respectively, displayed unique health literacy patterns.

conclusionsThe results demonstrate that descriptive analysis only provides an overview and may lead to one-size-fits-all interventions. The varying health literacy patterns among subgroups resulting from the cluster analysis pave the way to inform tailored actions to improve health equity.

Indexed as

Health LiteracyAdolescentAdultAgedCluster AnalysisFemaleHealth Status DisparitiesHealth SurveysHumansMaleMiddle AgedNew South WalesSurveys and QuestionnairesVictoriaYoung Adultcluster analysishealth equityhealth literacymeasurementmethods

Identifiers

PMID39099193
PMCPMC11637599

What OpenQuestion holds

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LicenceCC BY
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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.