Measuring health literacy in community agencies: a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ)

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Measuring health literacy in community agencies : a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ). / Elsworth, Gerald R.; Beauchamp, Alison; Osborne, Richard H.

In: BMC Health Services Research, Vol. 16, 508, 22.09.2016, p. 1-14.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Elsworth, GR, Beauchamp, A & Osborne, RH 2016, 'Measuring health literacy in community agencies: a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ)', BMC Health Services Research, vol. 16, 508, pp. 1-14. https://doi.org/10.1186/s12913-016-1754-2

APA

Elsworth, G. R., Beauchamp, A., & Osborne, R. H. (2016). Measuring health literacy in community agencies: a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ). BMC Health Services Research, 16, 1-14. [508]. https://doi.org/10.1186/s12913-016-1754-2

Vancouver

Elsworth GR, Beauchamp A, Osborne RH. Measuring health literacy in community agencies: a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ). BMC Health Services Research. 2016 Sep 22;16:1-14. 508. https://doi.org/10.1186/s12913-016-1754-2

Author

Elsworth, Gerald R. ; Beauchamp, Alison ; Osborne, Richard H. / Measuring health literacy in community agencies : a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ). In: BMC Health Services Research. 2016 ; Vol. 16. pp. 1-14.

Bibtex

@article{390942b4fa9449d19c2cc68b51c279eb,
title = "Measuring health literacy in community agencies: a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ)",
abstract = "Background: The development of the Health Literacy Questionnaire (HLQ), reported in 2013, attracted widespread international interest. While the original study samples were drawn from clinical and home-based aged-care settings, the HLQ was designed for the full range of healthcare contexts including community-based health promotion and support services. We report a follow-up study of the psychometric properties of the HLQ with respondents from a diverse range of community-based organisations with the principal goal of contributing to the development of a soundly validated evidence base for its use in community health settings. Methods: Data were provided by 813 clients of 8 community agencies in Victoria, Australia who were administered the HLQ during the needs assessment stage of the Ophelia project, a health literacy-based intervention. Most analyses were conducted using Bayesian structural equation modelling that enables rigorous analysis of data but with some relaxation of the restrictive requirements for zero cross-loadings and residual correlations of 'classical' confirmatory factor analysis. Scale homogeneity was investigated with one-factor models that allowed for the presence of small item residual correlations while discriminant validity was studied using the inter-factor correlations and factor loadings from a full 9-factor model with similar allowance for small residual correlations and cross-loadings. Measurement invariance was investigated scale-by-scale using a model that required strict invariance of item factor loadings, thresholds, residual variances and co-variances. Results: All HLQ scales were found to be homogenous with composite reliability ranging from 0.80 to 0.89. The factor structure of the HLQ was replicated and 6 of the 9 scales were found to exhibit clear-cut discriminant validity. With a small number of exceptions involving non-invariance of factor loadings, strict measurement invariance was established across the participating organisations and the gender, language background, age and educational level of respondents. Conclusions: The HLQ is highly reliable, even with only 4 to 6 items per scale. It provides unbiased mean estimates of group differences across key demographic indicators. While measuring relatively narrow constructs, the 9 dimensions are clearly separate and therefore provide fine-grained data on the multidimensional area of health literacy. These analyses provide researchers, program managers and policymakers with a range of robust evidence by which they can make judgements about the appropriate use of the HLQ for their community-based setting.",
keywords = "Bayesian structural equation modelling, BSEM, Health literacy, Health Literacy Questionnaire, HLQ, Measurement invariance",
author = "Elsworth, {Gerald R.} and Alison Beauchamp and Osborne, {Richard H.}",
year = "2016",
month = sep,
day = "22",
doi = "10.1186/s12913-016-1754-2",
language = "English",
volume = "16",
pages = "1--14",
journal = "BMC Health Services Research",
issn = "1472-6963",
publisher = "BioMed Central Ltd.",

}

RIS

TY - JOUR

T1 - Measuring health literacy in community agencies

T2 - a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ)

AU - Elsworth, Gerald R.

AU - Beauchamp, Alison

AU - Osborne, Richard H.

PY - 2016/9/22

Y1 - 2016/9/22

N2 - Background: The development of the Health Literacy Questionnaire (HLQ), reported in 2013, attracted widespread international interest. While the original study samples were drawn from clinical and home-based aged-care settings, the HLQ was designed for the full range of healthcare contexts including community-based health promotion and support services. We report a follow-up study of the psychometric properties of the HLQ with respondents from a diverse range of community-based organisations with the principal goal of contributing to the development of a soundly validated evidence base for its use in community health settings. Methods: Data were provided by 813 clients of 8 community agencies in Victoria, Australia who were administered the HLQ during the needs assessment stage of the Ophelia project, a health literacy-based intervention. Most analyses were conducted using Bayesian structural equation modelling that enables rigorous analysis of data but with some relaxation of the restrictive requirements for zero cross-loadings and residual correlations of 'classical' confirmatory factor analysis. Scale homogeneity was investigated with one-factor models that allowed for the presence of small item residual correlations while discriminant validity was studied using the inter-factor correlations and factor loadings from a full 9-factor model with similar allowance for small residual correlations and cross-loadings. Measurement invariance was investigated scale-by-scale using a model that required strict invariance of item factor loadings, thresholds, residual variances and co-variances. Results: All HLQ scales were found to be homogenous with composite reliability ranging from 0.80 to 0.89. The factor structure of the HLQ was replicated and 6 of the 9 scales were found to exhibit clear-cut discriminant validity. With a small number of exceptions involving non-invariance of factor loadings, strict measurement invariance was established across the participating organisations and the gender, language background, age and educational level of respondents. Conclusions: The HLQ is highly reliable, even with only 4 to 6 items per scale. It provides unbiased mean estimates of group differences across key demographic indicators. While measuring relatively narrow constructs, the 9 dimensions are clearly separate and therefore provide fine-grained data on the multidimensional area of health literacy. These analyses provide researchers, program managers and policymakers with a range of robust evidence by which they can make judgements about the appropriate use of the HLQ for their community-based setting.

AB - Background: The development of the Health Literacy Questionnaire (HLQ), reported in 2013, attracted widespread international interest. While the original study samples were drawn from clinical and home-based aged-care settings, the HLQ was designed for the full range of healthcare contexts including community-based health promotion and support services. We report a follow-up study of the psychometric properties of the HLQ with respondents from a diverse range of community-based organisations with the principal goal of contributing to the development of a soundly validated evidence base for its use in community health settings. Methods: Data were provided by 813 clients of 8 community agencies in Victoria, Australia who were administered the HLQ during the needs assessment stage of the Ophelia project, a health literacy-based intervention. Most analyses were conducted using Bayesian structural equation modelling that enables rigorous analysis of data but with some relaxation of the restrictive requirements for zero cross-loadings and residual correlations of 'classical' confirmatory factor analysis. Scale homogeneity was investigated with one-factor models that allowed for the presence of small item residual correlations while discriminant validity was studied using the inter-factor correlations and factor loadings from a full 9-factor model with similar allowance for small residual correlations and cross-loadings. Measurement invariance was investigated scale-by-scale using a model that required strict invariance of item factor loadings, thresholds, residual variances and co-variances. Results: All HLQ scales were found to be homogenous with composite reliability ranging from 0.80 to 0.89. The factor structure of the HLQ was replicated and 6 of the 9 scales were found to exhibit clear-cut discriminant validity. With a small number of exceptions involving non-invariance of factor loadings, strict measurement invariance was established across the participating organisations and the gender, language background, age and educational level of respondents. Conclusions: The HLQ is highly reliable, even with only 4 to 6 items per scale. It provides unbiased mean estimates of group differences across key demographic indicators. While measuring relatively narrow constructs, the 9 dimensions are clearly separate and therefore provide fine-grained data on the multidimensional area of health literacy. These analyses provide researchers, program managers and policymakers with a range of robust evidence by which they can make judgements about the appropriate use of the HLQ for their community-based setting.

KW - Bayesian structural equation modelling

KW - BSEM

KW - Health literacy

KW - Health Literacy Questionnaire

KW - HLQ

KW - Measurement invariance

UR - http://www.scopus.com/inward/record.url?scp=84995407505&partnerID=8YFLogxK

U2 - 10.1186/s12913-016-1754-2

DO - 10.1186/s12913-016-1754-2

M3 - Journal article

C2 - 27659559

AN - SCOPUS:84995407505

VL - 16

SP - 1

EP - 14

JO - BMC Health Services Research

JF - BMC Health Services Research

SN - 1472-6963

M1 - 508

ER -

ID: 174895607