PURPOSE: Examine the relationship between race, use of assistive technology (AT), gender, educational attainment, income, employment status and access to health care. METHODS: Data were analyzed from the national Behavioral Risk Factor Surveillance System (BRFSS) collected in USA in 2007. Descriptive statistics and logistic regression were performed. RESULTS: Among those who used AT, more European Americans (EAs) were educated, employed, made >$25,000 per year and had better access to health coverage. In contrast, more African Americans (AAs) who used AT were less educated, unemployed, made <$25,000 per year and had worse health coverage. Overall, AAs used AT more than EAs. The trend was consistent with predictive factors. AAs were 29% more likely to use AT compared to EAs. For EAs and AAs, predictors for use of AT were age, gender, education, employment status, income, health coverage and medical costs. CONCLUSIONS: Racial differences between AAs and EAs were observed in the use of AT by persons with physical disabilities based on age, gender, education, employment status, income levels, health care coverage and medical costs. Even though EAs and AAs had the same predictors, there were racial differences in the magnitude of the predictors.
PURPOSE: Examine the relationship between race, use of assistive technology (AT), gender, educational attainment, income, employment status and access to health care. METHODS: Data were analyzed from the national Behavioral Risk Factor Surveillance System (BRFSS) collected in USA in 2007. Descriptive statistics and logistic regression were performed. RESULTS: Among those who used AT, more European Americans (EAs) were educated, employed, made >$25,000 per year and had better access to health coverage. In contrast, more African Americans (AAs) who used AT were less educated, unemployed, made <$25,000 per year and had worse health coverage. Overall, AAs used AT more than EAs. The trend was consistent with predictive factors. AAs were 29% more likely to use AT compared to EAs. For EAs and AAs, predictors for use of AT were age, gender, education, employment status, income, health coverage and medical costs. CONCLUSIONS: Racial differences between AAs and EAs were observed in the use of AT by persons with physical disabilities based on age, gender, education, employment status, income levels, health care coverage and medical costs. Even though EAs and AAs had the same predictors, there were racial differences in the magnitude of the predictors.
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Keywords:
Assistive technology; disability disparities; educational attainment; race; socioeconomic status