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Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes. Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Health Sciences.
Oslo and Akershus University College of Applied Sciences.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Health Sciences.ORCID iD: 0000-0001-7082-6834
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Health Sciences.
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2017 (English)In: Journal of Advanced Nursing, ISSN 0309-2402, E-ISSN 1365-2648Article in journal (Refereed) Epub ahead of print
Abstract [en]

AIM: To validate the European Health Literacy Survey Questionnaire (HLS-EU-Q47) in people with type 2 diabetes mellitus.

BACKGROUND: The HLS-EU-Q47 latent variable is outlined in a framework with four cognitive domains integrated in three health domains, implying 12 theoretically defined subscales. Valid and reliable health literacy measurers are crucial to effectively adapt health communication and education to individuals and groups of patients.

DESIGN: Cross-sectional study applying confirmatory latent trait analyses.

METHODS: Using a paper-and-pencil self-administered approach, 388 adults responded in March 2015. The data were analysed using the Rasch methodology and confirmatory factor analysis.

RESULTS: Response violation and trait violation (multidimensionality) of local independence were identified. Fitting the 'multidimensional random coefficients multinomial logit' model, 1-, 3- and 12-dimensional Rasch models were applied and compared. Poor model fit and differential item functioning were present in some items and several subscales suffered from poor targeting and low reliability. Despite multidimensionality in the data, we did not observe any unordered response categories.

CONCLUSION: Interpreting the domains as distinct but related latent dimensions, the data fit a 12-dimensional Rasch model and a 12-factor confirmatory factor model best. Therefore, the analyses did not support the estimation of one overall 'health literacy score'. To support the plausibility of claims based on the HLS-EU score(s), we suggest: removing the health care aspect to reduce the magnitude of multidimensionality; rejecting redundant items to confine response dependency; adding 'harder' items and applying a six-point rating scale to improve subscale targeting and reliability; and revising items to improve model fit. This article is protected by copyright. All rights reserved.

Place, publisher, year, edition, pages
Oxford: Blackwell Publishing, 2017.
Keyword [en]
HLS-EU-Q47, confirmatory factor analysis, health literacy, multidimensional Rasch modelling, nursing research, type 2 diabetes mellitus
National Category
Nursing
Identifiers
URN: urn:nbn:se:kau:diva-55162DOI: 10.1111/jan.13342PubMedID: 28543754OAI: oai:DiVA.org:kau-55162DiVA: diva2:1111626
Available from: 2017-06-19 Created: 2017-06-19 Last updated: 2017-06-27Bibliographically approved

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The full text will be freely available from 2018-06-01 09:56
Available from 2018-06-01 09:56

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Finbråten, Hanne SøbergWilde-Larsson, BodilNordström, Gun
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