Social and Demographic Patterns of Health-Related Internet Use Among Adults in the United States: A Secondary Data Analysis of the Health Information National Trends Survey

Abstract

National surveys of U.S. adults have observed significant increases in health-related internet use (HRIU), but there are documented disparities. The study aims to identify social and demographic patterns of health-related internet use among U.S. adults. Using data from the Health Information National Trends Survey (HINTS) 4 cycle 3 and HINTS 5 cycle 1, we examined HRIU across healthcare, health information seeking, and participation on social media. Primary predictors were gender, race/ethnicity, age, education, income, and nativity with adjustments for smoking and survey year. We used multivariable logistic regression with survey weights to identify independent predictors of HRIU. Of the 4817 respondents, 43% had used the internet to find a doctor; 80% had looked online for health information. Only 20% had used social media for a health issue; 7% participated in an online health support group. In multivariable models, older and low SES participants were significantly less likely to use the internet to look for a provider, use the internet to look for health information for themselves or someone else, and less likely to use social media for health issues. Use of the internet for health-related purposes is vast but varies significantly by demographics and intended use.

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey

“…We observed that women in our sample were more likely to report positive attitudes toward using an app or website to track potential COVID-19 exposures or symptoms compared to men. This is consistent with prior studies that focused on disparities in mHealth use among the general population [ 80 , 89 ]. Previous studies have also documented lower rates of using mHealth tools among individuals with lower socioeconomic backgrounds compared to individuals with higher socioeconomic backgrounds [ 81 , 90 ].…”

“…The following covariates were included in the multivariable analyses: age categories (ie, 18-29, 30-44, 45-59, ≥60 years), sex (ie, male or female), race/ethnicity categories (ie, non-Hispanic White, non-Hispanic Black, Hispanic or Latino, Asian, and non-Hispanic other), education categories (ie, no high school diploma, high school graduate, some college, and baccalaureate or above), residence (ie, rural or urban), and household income (ie, <US $50,000, US $50,000-US $100,000, ≥US $100,000). These covariates were chosen based on the review of mHealth disparities literature and COVID-19 disparities literature [ 5 , 80 - 83 ].…”

COVID-19 vaccine hesitancy among persons living in homeless shelters in France

“…In particular, they seem especially concerned about possible side effects, which may reflect overall higher levels of concerns about health [3] . Additionally, women are more likely than men to seek information about health on the Internet and social media [13] , which may put them in contact with negative information regarding vaccines. This suggests that it is necessary to better control information that is disseminated via the Internet, as well as provide persons with accurate information in these much accessed media.…”

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey (Preprint)

“…The following covariates were included in the multivariable analyses: age categories (ie, 18-29, 30-44, 45-59, ≥60 years), sex (ie, male or female), race/ethnicity categories (ie, non-Hispanic White, non-Hispanic Black, Hispanic or Latino, Asian, and non-Hispanic other), education categories (ie, no high school diploma, high school graduate, some college, and baccalaureate or above), residence (ie, rural or urban), and household income (ie, <US $50,000, US $50,000-US $100,000, ≥US $100,000). These covariates were chosen based on the review of mHealth disparities literature and COVID-19 disparities literature [5,[80][81][82][83].…”