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      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

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          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.

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          The evolving concept of health literacy.

          The relationship between poor literacy skills and health status is now well recognized and better understood. Interest in this relationship has led to the emergence of the concept of health literacy. The concept has emerged from two different roots - in clinical care and in public health. This paper describes the two distinctive concepts that reflect health literacy, respectively, as a clinical "risk", or a personal "asset". In the former case a strong science is developing to support screening for poor literacy skills in clinical care and this is leading to a range of changes to clinical practice and organization. The conceptualization of health literacy as an asset has its roots in educational research into literacy, concepts of adult learning, and health promotion. The science to support this conceptualization is less well developed and is focused on the development of skills and capacities intended to enable people to exert greater control over their health and the factors that shape health. The paper concludes that both conceptualizations are important and are helping to stimulate a more sophisticated understanding of the process of health communication in both clinical and community settings, as well as highlighting factors impacting on its effectiveness. These include more personal forms of communication and community based educational outreach. It recommends improved interaction between researchers working within the two health literacy perspectives, and further research on the measurement of health literacy. The paper also emphasizes the importance of more general strategies to promote literacy, numeracy and language skills in populations.
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            Predictors of eHealth Usage: Insights on The Digital Divide From the Health Information National Trends Survey 2012

            Background Recent eHealth developments have elevated the importance of assessing the extent to which technology has empowered patients and improved health, particularly among the most vulnerable populations. With noted disparities across racial and social groups in chronic health outcomes, such as cancer, obesity, and diabetes, it is essential that researchers examine any differences in the implementation, uptake, and impact of eHealth strategies across groups that bear a disproportionate burden of disease. Objective The goal was to examine eHealth use by sociodemographic factors, such as race/ethnicity, socioeconomic status (SES), age, and sex. Methods We drew data from National Cancer Institute’s 2012 Health Information National Trends Survey (HINTS) (N=3959) which is publicly available online. We estimated multivariable logistic regression models to assess sociodemographic predictors of eHealth use among adult Internet users (N=2358) across 3 health communication domains (health care, health information–seeking, and user-generated content/sharing). Results Among online adults, we saw no evidence of a digital use divide by race/ethnicity. However, there were significant differences in use by SES, particularly for health care and health information–seeking items. Patients with lower levels of education had significantly lower odds of going online to look for a health care provider (high school or less: OR 0.50, 95% CI 0.33-0.76) using email or the Internet to communicate with a doctor (high school or less: OR 0.46, 95% CI 0.29-0.72), tracking their personal health information online (high school or less: OR 0.53, 95% CI 0.32-0.84), using a website to help track diet, weight, and physical activity (high school or less: OR 0.64, 95% CI 0.42-0.98; some college: OR 0.67, 95% CI 0.49-0.93), or downloading health information to a mobile device (some college: OR 0.54, 95% CI 0.33-0.89). Being female was a consistent predictor of eHealth use across health care and user-generated content/sharing domains, whereas age was primarily influential for health information–seeking. Conclusions This study illustrates that lower SES, older, and male online US adults were less likely to engage in a number of eHealth activities compared to their counterparts. Future studies should assess issues of health literacy and eHealth literacy and their influence on eHealth engagement across social groups. Clinical care and public health communication efforts attempting to leverage Web 2.0 and 3.0 platforms should acknowledge differential eHealth usage to better address communication inequalities and persistent disparities in health.
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              Racial and Ethnic Disparities in Cancer Survival: The Contribution of Tumor, Sociodemographic, Institutional, and Neighborhood Characteristics

              Purpose Racial/ethnic disparities in cancer survival in the United States are well documented, but the underlying causes are not well understood. We quantified the contribution of tumor, treatment, hospital, sociodemographic, and neighborhood factors to racial/ethnic survival disparities in California. Materials and Methods California Cancer Registry data were used to estimate population-based cancer-specific survival for patients diagnosed with breast, prostate, colorectal, or lung cancer between 2000 and 2013 for each racial/ethnic group (non-Hispanic black, Hispanic, Asian American and Pacific Islander, and separately each for Chinese, Japanese, and Filipino) compared with non-Hispanic whites. The percentage contribution of factors to overall racial/ethnic survival disparities was estimated from a sequence of multivariable Cox proportional hazards models. Results In baseline models, black patients had the lowest survival for all cancer sites, and Asian American and Pacific Islander patients had the highest, compared with whites. Mediation analyses suggested that stage at diagnosis had the greatest influence on overall racial/ethnic survival disparities accounting for 24% of disparities in breast cancer, 24% in prostate cancer, and 16% to 30% in colorectal cancer. Neighborhood socioeconomic status was an important factor in all cancers, but only for black and Hispanic patients. The influence of marital status on racial/ethnic disparities was stronger in men than in women. Adjustment for all covariables explained approximately half of the overall survival disparities in breast, prostate, and colorectal cancer, but it explained only 15% to 40% of disparities in lung cancer. Conclusion Overall reductions in racial/ethnic survival disparities were driven largely by reductions for black compared with white patients. Stage at diagnosis had the largest effect on racial/ethnic survival disparities, but earlier detection would not entirely eliminate them. The influences of neighborhood socioeconomic status and marital status suggest that social determinants, support mechanisms, and access to health care are important contributing factors.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                19 September 2020
                September 2020
                : 17
                : 18
                : 6856
                Affiliations
                [1 ]Department of Community Health and Social Medicine, CUNY School of Medicine, New York, NY 10031, USA; rcalixte@ 123456med.cuny.edu (R.C.); tobi.oridota@ 123456gmail.com (O.O.); wbeauch000@ 123456citymail.cuny.edu (W.B.)
                [2 ]Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10027, USA; argelis.rivera@ 123456mountsinai.org
                [3 ]Department of Community Health Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
                Author notes
                Author information
                https://orcid.org/0000-0002-2020-5906
                https://orcid.org/0000-0003-2343-2941
                Article
                ijerph-17-06856
                10.3390/ijerph17186856
                7559701
                32961766
                32c55e97-a310-454c-9ace-5d6b0f8354a1
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 August 2020
                : 17 September 2020
                Categories
                Article

                Public health
                mobile health,health communication,internet use
                Public health
                mobile health, health communication, internet use

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