Abstract
BackgroundThe 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.MethodsData 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.ResultsAll 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.ConclusionsThe 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.
Highlights
The development of the Health Literacy Questionnaire (HLQ), reported in 2013, attracted widespread international interest
The aims of the paper are to: (a) replicate the homogeneity and reliability of the individual HLQ scales in a new sample of respondents from a diverse range of community health settings; (b) replicate the 9-factor structure of the HLQ in this sample; (c) investigate further the discriminant validity of the HLQ scales; and (d) establish the measurement invariance of the scales across different types of agencies and the gender, language background, age and educational level of respondents
Bayesian fit statistics for 9 single factor models that either: (a) fixed residual correlations to zero, or (b) allowed residual correlations to be estimated with a small variance prior to give a 95 % probability that the correlations were within the range of ±0.2 ([14], p. 317) are shown in Table 1 together with the factor loadings and the range of residual correlations resulting from the ‘wiggle room’ analysis
Summary
The development of the Health Literacy Questionnaire (HLQ), reported in 2013, attracted widespread international interest. 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 Researchers frequently present their findings from questionnaire development protocols and subsequent psychometric analyses as establishing that the questionnaire is ‘valid’. It is incumbent upon questionnaire developers to generate sound evidence for fellow researchers and evaluators that enables them to make judgments about the relevance and robustness of the questionnaire in different settings This is important as the interpretation of scale scores may vary with new contexts and “...each interpretation of the scores needs to be validated...” by a “...program of research to support the ...application of the tool in relation to an increasing range of interpretations...” This is important as the interpretation of scale scores may vary with new contexts and “...each interpretation of the scores needs to be validated...” by a “...program of research to support the ...application of the tool in relation to an increasing range of interpretations...” ([5], p. 2)
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