Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Measuring health literacy: Evaluating psychometric properties of the HLS-EU-Q47 and the FCCHL, suggesting instrument refinements and exploring health literacy in people with type 2 diabetes and in the general Norwegian population
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Health Sciences (from 2013). Høgskolen i Innlandet.ORCID iD: 0000-0001-8911-2102
2018 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Måling av health literacy : Evaluering av psykometriske egenskaper av HLS-EU-Q47 og FCCHL, forslag til instrumentforbedringer og kartlegging av health literacy blant personer med diabetes type 2 og generell norsk befolkning (Norwegian)
Abstract [en]

Aim: The overall aim was to measure health literacy (HL) in people with type 2 diabetes (T2DM) and in the general Norwegian population.

Methods: Sampling 388 people with T2DM (papers I, II and IV) and 900 individuals (III) in the general Norwegian population a cross-sectional design was applied. Rasch modelling and confirmatory factor analysis were used to evaluate the psychometric properties of the 47 items HLS-EU-Q47 questionnaire (I and III) and the 14 items FCCHL scale (II), and to develop and evaluate a 12 item short version, HLS-N-Q12 (III and IV), based on HLS-EU-Q47. Descriptive and inferential statistics were used to describe HL and to investigate associations between HL and various independent variables.

Main results: The HLS-EU-Q47 displayed psychometric shortcomings in both populations (I and III). A 12-dimensional model described the data best. Several items showed misfit to the Rasch model and statistical dependence. Aiming at meeting the requirements of objective measurement, the HLS-N-Q12 was suggested (III and IV). Evaluating the FCCHL in people with T2DM, the data fitted a three-dimensional model best (II). Several items showed misfit to the Rasch model and unordered response categories. However, a three-dimensional 12-item version of the FCCHL had acceptable psychometric properties. Education, good general health and empowerment were positively associated with HL in people with T2DM, explaining about 17% of the total variance in HL (IV).

Conclusions: In both populations, the HLS-N-Q12 displayed solid psychometric properties and might therefore be used as a measure of HL for both clinical and research purposes. Nurses and other health professionals must be aware that HL influence individuals’ proficiency in managing their health. Hence, nurses and other health professionals should map HL in individuals and adapt health information accordingly.

Abstract [no]

Hensikt: Avhandlingens overordnede hensikt var å måle health literacy (HL) blant personer med diabetes type 2 (T2DM) og generell norsk befolkning.

Metode: Kvantitativ tverrsnittsstudie hvor 388 personer med T2DM (I, II og IV) og 900 personer fra norsk befolkning (III) var inkludert. Rasch modellering og konfirmatorisk faktoranalyse ble anvendt for å evaluere de psykometriske egenskapene til instrumentene HLS-EU-Q47 (I og III) og FCCHL (II), som består av henholdsvis 47 og 14 spørsmål, og for å utvikle og evaluere en kortversjon av HLS-EU-Q47, HLS-N-Q12, bestående av 12 spørsmål (III og IV). Deskriptiv og inferensiell statistikk ble anvendt for å beskrive HL i utvalgene og for å studere sammenhenger mellom HL og ulike uavhengige variabler.

Hovedresultater: HLS-EU-Q47 viste psykometriske svakheter i begge utvalgene (I og III). HLS-EU-Q47 data viste best tilpasning til en 12-dimensjonal modell. Flere spørsmål viste dårlig tilpasning til Rasch modellen, samt statistisk avhengighet. Med hensikt i å oppnå kravene for objektive målinger, ble HLS-N-Q12 foreslått (III og IV). I evalueringen av FCCHL blant personer med T2DM viste data best tilpasning til en tredimensjonal modell (II). Spørsmål med dårlig tilpasning til Rasch modellen og uordnede svarkategorier ble avdekket. Imidlertid viste en tredimensjonal versjon av FCCHL bestående av 12 spørsmål akseptable psykometriske egenskaper. Utdanning, god generell helse og empowerment, var positivt assosiert med HL blant personer med T2DM, og forklarte rundt 17% av den totale variansen av HL (IV).

Konklusjoner: HLS-N-Q12 viste solide psykometriske egenskaper i begge populasjonene og kan derfor anvendes for å måle HL både i praksis og innen forskning.  Sykepleiere må være oppmerksomme på at HL påvirker den enkeltes muligheter for å håndtere egen helse. Sykepleiere bør dermed kartlegge HL hos den enkelte og tilpasse helseinformasjon deretter.

Abstract [en]

In today’s health care, we are accountable for our own health and responsible for making cautious health-related decisions based on available information. Health literacy is a vital competence in accomplishing this. Knowledge about people’s health literacy is therefore central to nurses aiming at adapting health information to target groups. The overall aim of this thesis was to measure health literacy in people with type 2 diabetes and in the general Norwegian population.

This thesis demonstrates the usefulness of Rasch modelling as an addition to confirmatory factor analysis in evaluating psychometric properties of health-related scales, such as the HLS-EU-Q47 and the FCCHL. The results indicate that the short form of HLS-EU-Q47, the HLS-N-Q12, meet the assumptions and the requirements of fundamental measurements and could be used to measure health literacy in both people with type 2 diabetes and in the general Norwegian population.

Judging whether health information from various sources are valid and reliable was found to be the most difficult health-literacy task in both populations. Explaining variance in health literacy in people with type 2 diabetes, health literacy stood out as being positively associated with education, good general health and empowerment.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2018. , p. 96
Series
Karlstad University Studies, ISSN 1403-8099 ; 2018:15
Keywords [en]
confirmatory factor analysis, FCCHL, health literacy, health-promotion nursing, HLS-EU-Q47, HLS-N-Q12, measurement, Norwegian population, psychometric evaluation, Rasch modelling, type 2 diabetes, validation
Keywords [no]
FCCHL, health literacy, helsefremmende sykepleie, HLS-EU-Q47, HLS-N-Q12, konfirmatorisk faktor analyse, måling, norsk befolkning, personer med diabetes type 2, psykometrisk evaluering, Rasch modellering, validering
National Category
Health Sciences
Research subject
Nursing Science
Identifiers
URN: urn:nbn:se:kau:diva-66928ISBN: 978-91-7063-846-6 (print)ISBN: 978-91-7063-941-8 (print)OAI: oai:DiVA.org:kau-66928DiVA, id: diva2:1195725
Public defence
2018-05-25, Lagerlöfsalen 1A305, Karlstad, 10:00 (Swedish)
Opponent
Supervisors
Available from: 2018-05-04 Created: 2018-04-06 Last updated: 2018-05-04Bibliographically approved
List of papers
1. Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes. Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.
Open this publication in new window or tab >>Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes. Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.
Show others...
2017 (English)In: Journal of Advanced Nursing, ISSN 0309-2402, E-ISSN 1365-2648, Vol. 73, no 11, p. 2730-2744Article in journal (Refereed) Published
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
Keywords
HLS-EU-Q47, confirmatory factor analysis, health literacy, multidimensional Rasch modelling, nursing research, type 2 diabetes mellitus
National Category
Nursing
Research subject
Nursing Science
Identifiers
urn:nbn:se:kau:diva-55162 (URN)10.1111/jan.13342 (DOI)28543754 (PubMedID)
Available from: 2017-06-19 Created: 2017-06-19 Last updated: 2018-06-12Bibliographically approved
2. Validating the functional, communicative and critical health literacy scale using rasch modeling and confirmatory factor analysis
Open this publication in new window or tab >>Validating the functional, communicative and critical health literacy scale using rasch modeling and confirmatory factor analysis
Show others...
2018 (English)In: Journal of Nursing Measurement, ISSN 1061-3749, E-ISSN 1945-7049, no 2, p. 341-363Article in journal (Refereed) Published
National Category
Nursing
Research subject
Nursing Science
Identifiers
urn:nbn:se:kau:diva-62598 (URN)10.1891/1061-3749.26.2.341 (DOI)000444621700010 ()
Available from: 2017-08-09 Created: 2017-08-09 Last updated: 2018-10-04Bibliographically approved
3. Establishing the HLS-Q12 short version of the European Health Literacy Survey Questionnaire: Latent trait analyses using Rasch modelling and confirmatory factor modelling
Open this publication in new window or tab >>Establishing the HLS-Q12 short version of the European Health Literacy Survey Questionnaire: Latent trait analyses using Rasch modelling and confirmatory factor modelling
Show others...
2018 (English)In: BMC Health Services Research, ISSN 1472-6963, E-ISSN 1472-6963, Vol. 18, no 506Article in journal (Other academic) Published
Abstract [en]

The European Health Literacy Survey Questionnaire (HLS-EU-Q47) is widely used in assessing health literacy (HL). There has been some controversy whether the comprehensive HLS-EU-Q47 data, reflecting a conceptual model of four cognitive domains across three health domains (i.e. 12 subscales), fit unidimensional Rasch models. Still, the HLS-EU-Q47 raw score is commonly interpreted as a sufficient statistic. Combining Rasch modelling and confirmatory factor analysis, we reduced the 47 item scale to a parsimonious 12 item scale that meets the assumptions and requirements of objective measurement while offering a clinically feasible HL screening tool. This paper aims at (1) evaluating the psychometric properties of the HLS-EU-Q47 and associated short versions in a large Norwegian sample, and (2) establishing a short version (HLS-Q12) with sufficient psychometric properties.MethodsUsing computer-assisted telephone interviews during November 2014, data were collected from 900 randomly sampled individuals aged 16 and over. The data were analysed using the partial credit parameterization of the unidimensional polytomous Rasch model (PRM) and the 'between-item' multidimensional PRM, and by using one-factorial and multi-factorial confirmatory factor analysis (CFA) with categorical variables.ResultsUsing likelihood-ratio tests to compare data-model fit for nested models, we found that the observed HLS-EU-Q47 data were more likely under a 12-dimensional Rasch model than under a three- or a one-dimensional Rasch model. Several of the 12 theoretically defined subscales suffered from low reliability owing to few items. Excluding poorly discriminating items, items displaying differential item functioning and redundant items violating the assumption of local independency, a parsimonious 12-item HLS-Q12 scale is suggested. The HLS-Q12 displayed acceptable fit to the unidimensional Rasch model and achieved acceptable goodness-of-fit indexes using CFA.ConclusionsUnlike the HLS-EU-Q47 data, the parsimonious 12-item version (HLS-Q12) meets the assumptions and the requirements of objective measurement while offering clinically feasible screening without applying advanced psychometric methods on site. To avoid invalid measures of HL using the HLS-EU-Q47, we suggest using the HLS-Q12. Valid measures are particularly important in studies aiming to explain the variance in the latent trait HL, and explore the relation between HL and health outcomes with the purpose of informing policy makers.

Place, publisher, year, edition, pages
BioMed Central, 2018
Keywords
Confirmatory factor analysis of categorical data; Health literacy; HLS-EU-Q47; HLS-Q12; Rasch modelling; Short version; Validation
National Category
Health Sciences Nursing
Research subject
Nursing Science
Identifiers
urn:nbn:se:kau:diva-66962 (URN)10.1186/s12913-018-3275-7 (DOI)000436841600003 ()
Note

I avhandlingen publicerad med manuskripttiteln: Proposing the HLS-N-Q12 based on a review of the European Health Literacy Survey Questionnaire and associated short versions : Latent trait analyses using Rasch modelling and confirmatory factor modelling

Available from: 2018-04-10 Created: 2018-04-10 Last updated: 2019-12-20Bibliographically approved
4. Manuscript: Psychometric properties of the HLS-N-Q12 in people with type 2 diabetes and the association between health literacy and demographic variables, general health, health behaviour and empowerment
Open this publication in new window or tab >>Manuscript: Psychometric properties of the HLS-N-Q12 in people with type 2 diabetes and the association between health literacy and demographic variables, general health, health behaviour and empowerment
(English)Manuscript (preprint) (Other academic)
National Category
Health Sciences
Research subject
Nursing Science
Identifiers
urn:nbn:se:kau:diva-66963 (URN)
Available from: 2018-04-10 Created: 2018-04-10 Last updated: 2019-04-25Bibliographically approved

Open Access in DiVA

fulltext(1318 kB)239 downloads
File information
File name FULLTEXT02.pdfFile size 1318 kBChecksum SHA-512
0f65e161a72faf0aac436fe0fd4570069b31e9d8d67d2907faddd402216b010ba478dee6510a2ba6d48fa2fce2b6d6bc5b3abba10b83d46534698abe25bfb09e
Type fulltextMimetype application/pdf

Authority records BETA

Finbråten, Hanne Søberg

Search in DiVA

By author/editor
Finbråten, Hanne Søberg
By organisation
Department of Health Sciences (from 2013)
Health Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 239 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 1453 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf