Evidence map›Paper›PMID 35836363›Full record

ArticleJournal of public health dentistry2022

A psychometric network perspective to oral health literacy: Examining the replicability of network properties across the general community and older adults from Brazil.

Gustavo Hermes Soares, Fernanda Maria Rovai Bado, Carla Fabiana Tenani, Pedro Henrique Ribeiro Santiago, Lisa M Jamieson, Fábio Luiz Mialhe

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Article in Journal of public health dentistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Validation of Health Literacy in Dentistry (HeLD-14) in Peruvian Adults: A Cross-Sectional Study.Journal of International Society of Preventive & Community Dentistry
    Article
4 · The record

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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

6 authors.

Gustavo Hermes SoaresAustralian Research Centre for Population Oral Health, The University of Adelaide, Adelaide, South Australia, Australia.ORCID 0000-0001-6122-4399
Fernanda Maria Rovai BadoCommunity Dentistry, Universidade de Campinas, Piracicaba, Brazil.ORCID 0000-0002-7974-5456
Carla Fabiana TenaniCommunity Dentistry, Universidade de Campinas, Piracicaba, Brazil.
Pedro Henrique Ribeiro SantiagoAustralian Research Centre for Population Oral Health, The University of Adelaide, Adelaide, South Australia, Australia.
Lisa M JamiesonAustralian Research Centre for Population Oral Health, The University of Adelaide, Adelaide, South Australia, Australia.
Fábio Luiz MialheCommunity Dentistry, Universidade de Campinas, Piracicaba, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate the replicability of oral health literacy (OHL) network models across the general community and a sample of older adults from Brazil.

methodsData were obtained from two oral health surveys conducted with a total of 1138 participants. OHL was measured using the short form Health Literacy in Dentistry scale (HeLD-14). A regularized partial correlation network was estimated for each sample. Dimensionality and structural stability were examined via exploratory graph analysis. Network properties compared included global strength, edge weights, and centrality estimates. Model replicability was examined fitting the general community model to the older participants' data.

resultsSix dimensions with the exact same item composition were detected in both network models. Only the Receptivity domain in the older adults sample yielded low structural stability. Strong correlations were observed between edge weights (τ: 0.68; 95% CI: 0.62-0.74) and between node strength estimates (τ: 0.63; 95% CI: 0.36-0.89). No statistically significant differences were found for global strength. The fit of the older adults sample to the HeLD-14 network structure of the general community sample was satisfactory.

conclusionNetwork models OHL replicated across the general community and a sample of older adults. The psychometric network approach is a useful tool to evaluate the measurement equivalence of OHL instruments across populations.

Indexed as

Health LiteracyAgedBrazilCross-Sectional StudiesHumansOral HealthPsychometricsReproducibility of ResultsSurveys and Questionnaireshealth literacynetwork analysisoral healthpsychometrics

Identifiers

PMID35836363
PMCPMC9545626

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LicenceCC BY-NC-ND
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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.