Samantha R Paige1, Janice L Krieger2, Michael Stellefson3, Julia M Alber4. 1. University of Florida, Department of Health Education and Behavior, PO Box 118210, Gainesville, FL 32611, USA. Electronic address: paigesr190@ufl.edu. 2. University of Florida, STEM Translational Communication Center, 2024 Weimer Hall, Gainesville, FL 32611, USA. Electronic address: janicekrieger@jou.ufl.edu. 3. University of Florida, Department of Health Education and Behavior, PO Box 118210, Gainesville, FL 32611, USA. Electronic address: mstellefson@ufl.edu. 4. University of Pennsylvania, Center for Health Behavior Research, 110 Blockley Hall, Philadelphia, PA 19104, USA. Electronic address: alberj@mail.med.upenn.edu.
Abstract
BACKGROUND: Chronic disease patients are affected by low computer and health literacy, which negatively affects their ability to benefit from access to online health information. OBJECTIVE: To estimate reliability and confirm model specifications for eHealth Literacy Scale (eHEALS) scores among chronic disease patients using Classical Test (CTT) and Item Response Theory techniques. METHODS: A stratified sample of Black/African American (N=341) and Caucasian (N=343) adults with chronic disease completed an online survey including the eHEALS. Item discrimination was explored using bi-variate correlations and Cronbach's alpha for internal consistency. A categorical confirmatory factor analysis tested a one-factor structure of eHEALS scores. Item characteristic curves, in-fit/outfit statistics, omega coefficient, and item reliability and separation estimates were computed. RESULTS: A 1-factor structure of eHEALS was confirmed by statistically significant standardized item loadings, acceptable model fit indices (CFI/TLI>0.90), and 70% variance explained by the model. Item response categories increased with higher theta levels, and there was evidence of acceptable reliability (ω=0.94; item reliability=89; item separation=8.54). CONCLUSION: eHEALS scores are a valid and reliable measure of self-reported eHealth literacy among Internet-using chronic disease patients. PRACTICE IMPLICATIONS: Providers can use eHEALS to help identify patients' eHealth literacy skills.
BACKGROUND:Chronic diseasepatients are affected by low computer and health literacy, which negatively affects their ability to benefit from access to online health information. OBJECTIVE: To estimate reliability and confirm model specifications for eHealth Literacy Scale (eHEALS) scores among chronic diseasepatients using Classical Test (CTT) and Item Response Theory techniques. METHODS: A stratified sample of Black/African American (N=341) and Caucasian (N=343) adults with chronic disease completed an online survey including the eHEALS. Item discrimination was explored using bi-variate correlations and Cronbach's alpha for internal consistency. A categorical confirmatory factor analysis tested a one-factor structure of eHEALS scores. Item characteristic curves, in-fit/outfit statistics, omega coefficient, and item reliability and separation estimates were computed. RESULTS: A 1-factor structure of eHEALS was confirmed by statistically significant standardized item loadings, acceptable model fit indices (CFI/TLI>0.90), and 70% variance explained by the model. Item response categories increased with higher theta levels, and there was evidence of acceptable reliability (ω=0.94; item reliability=89; item separation=8.54). CONCLUSION: eHEALS scores are a valid and reliable measure of self-reported eHealth literacy among Internet-using chronic diseasepatients. PRACTICE IMPLICATIONS: Providers can use eHEALS to help identify patients' eHealth literacy skills.
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