The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Older Adults’ Internet Use for Health Information: Digital Divide by Race/Ethnicity and Socioeconomic Status
Abstract
Building upon literature suggesting low Internet use among racial/ethnic minorities and socioeconomically disadvantaged groups, this study examined how race/ethnicity and socioeconomic status (SES) influence the Internet use for health information, addressing both independent and interactive effects. Using data from 17,704 older adults in the California Health Interview Survey, logistic regression models were estimated with race/ethnicity (Whites, African Americans, Latinos, and Asians), SES index, and the interaction between race/ethnicity and SES index. Overall, approximately 40% of participants were Internet-users for health information. Direct effects of race/ethnicity and SES—and their interactions—were all found to be significant. Minority status combined with the lowest levels of SES substantially reduced the odds of using Internet for health information. Findings suggest the combination of racial/ethnic minority status and low SES as a source of digital divide, and provide implications for Internet technology training for the target population.
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Cites
Constructing socio-economic status indices: how to use principal components analysis
Vyas, S., & Kumaranayake, L. (2006) · Health Policy and Planning · doi:10.1093/heapol/czl029 · Cited by 3,280
Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006) · Psychology and Aging · doi:10.1037/0882-7974.21.2.333 · Cited by 2,113 · cited 2×
“various types of digital technologies (Choi & Dinitto, 2013; Czaja et al., 2006).”
BackgroundUse of the Internet and E-mail for Health Care Information: Results From a National Survey
Baker, L., Wagner, T. H., Singer, S., & Bundorf, M. K. (2003) · JAMA · doi:10.1001/jama.289.18.2400 · Cited by 1,129
Measuring inequality with asset indicators
McKenzie, D. J. (2005) · Journal of Population Economics · doi:10.1007/s00148-005-0224-7 · Cited by 691
Computer use by older adults: A multi-disciplinary review
Wagner, N., Hassanein, K., & Head, M. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.03.029 · Cited by 678
Promoting older adults’ well-being through Internet training and use
Shapira, N., Barak, A., & Gal, I. (2007) · Aging & Mental Health · doi:10.1080/13607860601086546 · Cited by 501
How the internet affects patients' experience of cancer: a qualitative study
Ziebland, S., Chapple, A., Dumelow, C., Evans, J., Prinjha, S., & Rozmovits, L. (2004) · BMJ · doi:10.1136/bmj.328.7439.564 · Cited by 493
Aging in Minority Populations an Examination of the Double Jeopardy Hypothesis
Dowd, J. J., & Bengtson, V. L. (1978) · Journal of Gerontology · doi:10.1093/geronj/33.3.427 · Cited by 409
Internet Use and Well-Being in Older Adults
Heo, J., Chun, S., Lee, S., Lee, K. H., & Kim, J. (2015) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2014.0549 · Cited by 406
Internet Use and Loneliness in Older Adults
Sum, S., Mathews, R. M., Hughes, I., & Campbell, A. (2008) · CyberPsychology & Behavior · doi:10.1089/cpb.2007.0010 · Cited by 384
Research works printed but not linked: 4
- California Health Interview Survey, 2014, CHIS 2011–2012 adult survey
- Hong Y. A., 2017, Journals of Gerontology, Series B: Psychological Sciences & Social Sciences, 72, 856
- Smith D., 2012, Race, Gender & Class, 19, 161
- Sorokin P. A., 1956, Fads and foibles in modern sociology and related sciences
Cited by
Kruse, C., Fohn, J., Wilson, N., Nunez Patlan, E., Zipp, S., & Mileski, M. (2020) · JMIR Medical Informatics · doi:10.2196/20359 · Cited by 295
Gorenko, J. A., Moran, C., Flynn, M., Dobson, K., & Konnert, C. (2021) · Journal of Applied Gerontology · doi:10.1177/0733464820958550 · Cited by 262
The Need for a Mental Health Technology Revolution in the COVID-19 Pandemic
Figueroa, C. A., & Aguilera, A. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00523 · Cited by 227
Eruchalu, C. N., Pichardo, M. S., Bharadwaj, M., Rodriguez, C. B., Rodriguez, J. A., Bergmark, R. W., Bates, D. W., & Ortega, G. (2021) · Journal of Urban Health · doi:10.1007/s11524-020-00508-9 · Cited by 245
Technology and caregiving: emerging interventions and directions for research
Lindeman, D. A., Kim, K. K., Gladstone, C., & Apesoa-Varano, E. C. (2020) · The Gerontologist · doi:10.1093/geront/gnz178 · Cited by 182
Metadata
- Authors
- Yoon, H., Jang, Y., Vaughan, P. W., & Garcia, M.
- Venue
- Journal of Applied Gerontology
- Publisher
- SAGE Publications
- Published
- 2018-04-16
- Volume
- 39
- Issue
- 1
- Pages
- 105-110
- ISSN
- 0733-4648 (ISSN-L)
- 1552-4523
- OpenAlex
- W2800658779
- Cited by
- 391
- References
- 25
- FWCI
- 41.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
- Funders
- National Research Foundation of Korea (2016S1A3A2925399)
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- Yoon, H., Jang, Y., Vaughan, P. W., & Garcia, M. (2020). Older Adults’ Internet Use for Health Information: Digital Divide by Race/Ethnicity and Socioeconomic Status. Journal of Applied Gerontology. https://doi.org/10.1177/0733464818770772
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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