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      Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model

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          Abstract

          Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward–backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was ‘Social support for health’, and the hardest were ‘Navigating the healthcare system’ and ‘Appraisal of health information’. CFA of the individual scales showed acceptably high loadings (range 0.49–0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach’s α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes.

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          Bayesian structural equation modeling: a more flexible representation of substantive theory.

          This article proposes a new approach to factor analysis and structural equation modeling using Bayesian analysis. The new approach replaces parameter specifications of exact zeros with approximate zeros based on informative, small-variance priors. It is argued that this produces an analysis that better reflects substantive theories. The proposed Bayesian approach is particularly beneficial in applications where parameters are added to a conventional model such that a nonidentified model is obtained if maximum-likelihood estimation is applied. This approach is useful for measurement aspects of latent variable modeling, such as with confirmatory factor analysis, and the measurement part of structural equation modeling. Two application areas are studied, cross-loadings and residual correlations in confirmatory factor analysis. An example using a full structural equation model is also presented, showing an efficient way to find model misspecification. The approach encompasses 3 elements: model testing using posterior predictive checking, model estimation, and model modification. Monte Carlo simulations and real data are analyzed using Mplus. The real-data analyses use data from Holzinger and Swineford's (1939) classic mental abilities study, Big Five personality factor data from a British survey, and science achievement data from the National Educational Longitudinal Study of 1988.
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            The Causal Pathways Linking Health Literacy to Health Outcomes

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              Distribution of health literacy strengths and weaknesses across socio-demographic groups: a cross-sectional survey using the Health Literacy Questionnaire (HLQ)

              Background Recent advances in the measurement of health literacy allow description of a broad range of personal and social dimensions of the concept. Identifying differences in patterns of health literacy between population sub-groups will increase understanding of how health literacy contributes to health inequities and inform intervention development. The aim of this study was to use a multi-dimensional measurement tool to describe the health literacy of adults in urban and rural Victoria, Australia. Methods Data were collected from clients (n = 813) of 8 health and community care organisations, using the Health Literacy Questionnaire (HLQ). Demographic and health service data were also collected. Data were analysed using descriptive statistics. Effect sizes (ES) for standardised differences in means were used to describe the magnitude of difference between demographic sub-groups. Results Mean age of respondents was 72.1 (range 19–99) years. Females comprised 63 % of the sample, 48 % had not completed secondary education, and 96 % reported at least one existing health condition. Small to large ES were seen for mean differences in HLQ scales between most demographic groups. Compared with participants who spoke English at home, those not speaking English at home had much lower scores for most HLQ scales including the scales ‘Understanding health information well enough to know what to do’ (ES −1.09 [95 % confidence interval (CI) -1.33 to −0.84]), ‘Ability to actively engage with healthcare providers’ (ES −1.00 [95 % CI −1.24, −0.75]), and ‘Navigating the healthcare system’ (ES −0.72 [95 % CI −0.97, −0.48]). Similar patterns and ES were seen for participants born overseas compared with those born in Australia. Smaller ES were seen for sex, age group, private health insurance status, number of chronic conditions, and living alone. Conclusions This study has revealed some large health literacy differences across nine domains of health literacy in adults using health services in Victoria. These findings provide insights into the relationship between health literacy and socioeconomic position in vulnerable groups and, given the focus of the HLQ, provide guidance for the development of equitable interventions.
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                Author and article information

                Contributors
                htm@ph.au.dk
                lk@sund.ku.dk
                ole@norgaard.dk
                anne.bo@ph.au.dk
                gerald.elsworth@deakin.edu.au
                richard.osborne@deakin.edu.au
                Journal
                Springerplus
                Springerplus
                SpringerPlus
                Springer International Publishing (Cham )
                2193-1801
                2 August 2016
                2 August 2016
                2016
                : 5
                : 1
                : 1232
                Affiliations
                [1 ]Department of Public Health, Section of Health Promotion and Health Services Research, Aarhus University, Bartholins Alle 2, 8000 Aarhus C, Denmark
                [2 ]Steno Diabetes Center, Health Promotion Research, Gentofte, Denmark
                [3 ]Department of Public Health, University of Copenhagen, Copenhagen, Denmark
                [4 ]Research and Knowledge Centre, Danish Veteran Centre, Ringsted, Denmark
                [5 ]Health Systems Improvement Unit, Deakin University Centre for Population Health Research, School of Health and Social Development, Geelong, VIC Australia
                Author information
                http://orcid.org/0000-0003-0525-7254
                http://orcid.org/0000-0002-0909-4088
                http://orcid.org/0000-0002-1681-4338
                http://orcid.org/0000-0001-6306-7593
                http://orcid.org/0000-0002-9081-2699
                Article
                2887
                10.1186/s40064-016-2887-9
                4971008
                27536516
                2832b072-0506-4aad-b36c-174c8a9bfd09
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 7 January 2016
                : 20 July 2016
                Funding
                Funded by: Danish Strategic Research Council
                Funded by: Nordea Foundation
                Funded by: Australian National Health and Medical Research Council
                Award ID: 1059122
                Award Recipient :
                Funded by: MSD Denmark
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

                Uncategorized
                health literacy,questionnaire,measurement,validation,psychometrics,hlq
                Uncategorized
                health literacy, questionnaire, measurement, validation, psychometrics, hlq

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