11
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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 (χ 2 = 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 (χ 2: 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.

          Related collections

          Most cited references 23

          • Record: found
          • Abstract: found
          • Article: not found

          Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals.

           V. Smith (2001)
          The purpose of this research is twofold. First is to extend the work of Smith (1992, 1996) and Smith and Miao (1991, 1994) in comparing item fit statistics and principal component analysis as tools for assessing the unidimensionality requirement of Rasch models. Second is to demonstrate methods to explore how violations of the unidimensionality requirement influence person measurement. For the first study, rating scale data were simulated to represent varying degrees of multidimensionality and the proportion of items contributing to each component. The second study used responses to a 24 item Attention Deficit Hyperactivity Disorder scale obtained from 317 college undergraduates. The simulation study reveals both an iterative item fit approach and principal component analysis of standardized residuals are effective in detecting items simulated to contribute to multidimensionality. The methods presented in Study 2 demonstrate the potential impact of multidimensionality on norm and criterion-reference person measure interpretations. The results provide researchers with quantitative information to help assist with the qualitative judgment as to whether the impact of multidimensionality is severe enough to warrant removing items from the analysis.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Rapid assessment of literacy levels of adult primary care patients.

            Health education materials, medical instructions, consent forms, and self-report questionnaires are often given to patients with little regard for their ability to read them. Reading ability is rarely tested in medical settings. The Rapid Estimate of Adult Literacy in Medicine (REALM) was developed as a quick screening tool to assist physicians in identifying patients with limited reading skills and in estimating patient reading levels. This information can be used to tailor materials and instructions to patients' abilities. The REALM and the reading sections of the Peabody Individual Achievement Test-Revised and the Slosson Oral Reading Test were used to test reading ability in 207 adults in six public and private primary care clinics. REALM scores correlated highly with those of the standardized reading tests. The REALM, which takes three to five minutes to administer and score, appears to be a practical instrument to estimate patient literacy in primary care, patient education, and medical research.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Testing reliability and validity of the eHealth Literacy Scale (eHEALS) for older adults recruited online.

              Currently, vast amounts of health information and health management tools are available to the public online. To maximize the benefits of these e-health technologies, it is important to assess the e-health literacy of individuals. The eHealth Literacy Scale has been used widely in the past several years, but mainly in younger populations. The purpose of this study was to test the psychometric aspects of the eHealth Literacy Scale for older adults using a secondary data analysis (N=866; mean age, 62.8±8.5 years). Reliability of the eHealth Literacy Scale was examined by calculating α coefficients and conducting test-retest procedures. Its validity was assessed using exploratory factor analysis and the hypothesis testing procedure. Findings demonstrated that eHealth Literacy Scale was internally consistent (α=.94) and stable (t244=-1.48, P=.140). The exploratory factor analysis yielded a single factor structure explaining 67.3% of the variance. The hypothesis testing also supported the validity of eHealth Literacy Scale. In recent years, there have been great efforts to use e-health interventions to engage patients in healthcare and to help them manage their own health. Our study suggests that the eHealth Literacy Scale, a short screening tool for e-health literacy, can be successfully used for older adults.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                27 April 2017
                2017
                : 12
                : 4
                Affiliations
                [1 ]The George Institute for Global Health, Sydney, NSW, Australia
                [2 ]Hôpitaux Universitaires de Genève, Université de Genève, Geneva, Switzerland
                [3 ]School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
                [4 ]Department of Physiotherapy, Monash University, Melbourne, Victoria, Australia
                [5 ]Sydney Nursing School, Charles Perkin Centre, University of Sydney, Sydney, NSW, Australia
                [6 ]School of Health and Social Care, Edinburgh Napier University, Edinburgh, Scotland, United Kingdom
                [7 ]Sydney Medical School, University of Sydney, NSW, Sydney, Australia
                [8 ]Westmead Hospital, Sydney, NSW, Sydney, Australia
                University Of São Paulo, BRAZIL
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: SSR JR.

                • Data curation: SSR RM SES AB.

                • Formal analysis: SSR RM SES.

                • Funding acquisition: JR.

                • Investigation: SSR RM SES AB JR.

                • Methodology: SSR RM SES AB JR.

                • Project administration: JR.

                • Resources: SSR RM SES AB JR.

                • Software: RM SES AB.

                • Supervision: AB JR.

                • Validation: SSR RM SES AB JR.

                • Visualization: SSR RM SES AB JR.

                • Writing – original draft: SSR RM SES JR.

                • Writing – review & editing: SSR RM SES AB FB LN GC JM JC TU DP CKC JR.

                Article
                PONE-D-16-18163
                10.1371/journal.pone.0175372
                5407817
                28448497
                © 2017 Richtering et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 3, Tables: 4, Pages: 14
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award Recipient :
                Funded by: Sydney Medical Foundation Chapman Fellowship
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1054754
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1067236
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1061793
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001030, National Heart Foundation of Australia;
                Award ID: G160523
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1047508
                Funded by: funder-id http://dx.doi.org/10.13039/501100001030, National Heart Foundation of Australia;
                Award Recipient :
                CKC is funded by a Career Development Fellowship co-funded by the National Health and Medical Research Council and National Heart Foundation and Sydney Medical Foundation Chapman Fellowship. DP is supported by a NHMRC-postdoctoral Fellowship (1054754). AB’s salary was funded by a Career Development Fellowship from the National Health and Medical Research Council (APP1067236). JR is funded by a National Health and Medical Research Council Career Development Fellowship (1061793) co-funded with a National Heart Foundation Future Fellowship (G160523). The Consumer Navigation of Electronic Cardiovascular Tools (CONNECT) study is funded by a National Health and Medical Research Council Project Grant (APP1047508).
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Health Education and Awareness
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Academic Skills
                Literacy
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Academic Skills
                Literacy
                Social Sciences
                Psychology
                Cognitive Psychology
                Academic Skills
                Literacy
                Biology and Life Sciences
                Psychology
                Psychometrics
                Social Sciences
                Psychology
                Psychometrics
                Medicine and Health Sciences
                Health Care
                Health Services Administration and Management
                Medicine and Health Sciences
                Health Care
                Health Care Policy
                Health Systems Strengthening
                Computer and Information Sciences
                Computer Networks
                Internet
                Medicine and Health Sciences
                Cardiovascular Medicine
                Cardiovascular Diseases
                Medicine and Health Sciences
                Health Care
                Health Statistics
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized

                Comments

                Comment on this article