Expanding estimates of health literacy
TL;DRAbstract
This study explores the construct and measures of health literacy. It utilizes demographics to predict health literacy for all adults aged 18 years and older in a health literacy validation sub-study (HLVS) and a nationally representative dataset (2010 Medical Expenditure Panel Survey, MEPS). It also examines the construct of health literacy using structural equation modeling. Six hundred thirty-three (n=633) participants reported age, gender, race, ethnicity, preferred survey language, highest degree completed, as well as the shortened Test of Functional Health Literacy in America (s-TOFHLA), three single-item health literacy questions, the revised Rapid Estimate of Adult Literacy in Medicine (REALM-R) for English speakers, and the Short Assessment of Health Literacy for Spanish-speaking adults (SAHL-SA) using a health literacy validation questionnaire. The regression weights for the significant predictors of age, gender, race, and highest degree completed were applied to the HLVS and
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This study explores the construct and measures of health literacy. It utilizes demographics to predict health literacy for all adults aged 18 years and older in a health literacy validation sub-study (HLVS) and a nationally representative dataset (2010 Medical Expenditure Panel Survey, MEPS). It also examines the construct of health literacy using structural equation modeling. Six hundred thirty-three (n=633) participants reported age, gender, race, ethnicity, preferred survey language, highest degree completed, as well as the shortened Test of Functional Health Literacy in America (s-TOFHLA), three single-item health literacy questions, the revised Rapid Estimate of Adult Literacy in Medicine (REALM-R) for English speakers, and the Short Assessment of Health Literacy for Spanish-speaking adults (SAHL-SA) using a health literacy validation questionnaire. The regression weights for the significant predictors of age, gender, race, and highest degree completed were applied to the HLVS and
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