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Examination of an eHealth literacy scale and a health literacy scale in a population with moderate to high cardiovascular risk: Rasch analyses.

TitleExamination of an eHealth literacy scale and a health literacy scale in a population with moderate to high cardiovascular risk: Rasch analyses.
Publication TypeJournal Article
Year of Publication2017
AuthorsRichtering, SS, Morris, R, Soh, S-E, Barker, A, Bampi, F, Neubeck, L, Coorey, G, Mulley, J, Chalmers, J, Usherwood, T, Peiris, D, Chow, CK, Redfern, J
JournalPLoS One
Volume12
Issue4
Paginatione0175372
Date Published04/2017
ISSN1932-6203
Abstract

INTRODUCTION: Electronic health (eHealth) strategies are evolving making it important to have valid scales to assess eHealth and health literacy. Item response theory methods, such as the Rasch measurement model, are increasingly used for the psychometric evaluation of scales. This paper aims to examine the internal construct validity of an eHealth and health literacy scale using Rasch analysis in a population with moderate to high cardiovascular disease risk.

METHODS: The first 397 participants of the CONNECT study completed the electronic health Literacy Scale (eHEALS) and the Health Literacy Questionnaire (HLQ). Overall Rasch model fit as well as five key psychometric properties were analysed: unidimensionality, response thresholds, targeting, differential item functioning and internal consistency.

RESULTS: The eHEALS had good overall model fit (χ2 = 54.8, p = 0.06), ordered response thresholds, reasonable targeting and good internal consistency (person separation index (PSI) 0.90). It did, however, appear to measure two constructs of eHealth literacy. The HLQ subscales (except subscale 5) did not fit the Rasch model (χ2: 18.18-60.60, p: 0.00-0.58) and had suboptimal targeting for most subscales. Subscales 6 to 9 displayed disordered thresholds indicating participants had difficulty distinguishing between response options. All subscales did, nonetheless, demonstrate moderate to good internal consistency (PSI: 0.62-0.82).

CONCLUSION: Rasch analyses demonstrated that the eHEALS has good measures of internal construct validity although it appears to capture different aspects of eHealth literacy (e.g. using eHealth and understanding eHealth). Whilst further studies are required to confirm this finding, it may be necessary for these constructs of the eHEALS to be scored separately. The nine HLQ subscales were shown to measure a single construct of health literacy. However, participants' scores may not represent their actual level of ability, as distinction between response categories was unclear for the last four subscales. Reducing the response categories of these subscales may improve the ability of the HLQ to distinguish between different levels of health literacy.

DOI10.1371/journal.pone.0175372
Alternate JournalPLoS ONE
PubMed ID28448497
English
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