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Expanding estimates of health literacy

Tiffany M. Jones-2014-01-01-DigtalCommons @ Texas Medical Center Library (Texas Medical Center)
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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

Keywords

LiteracyHealth literacyComputer sciencePolitical scienceSociologyEconomic growthHealth carePedagogy

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