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Objective Widespread technological changes, like the rapid uptake of telehealth in the U.S. during the COVID-19 pandemic, risk creating or widening racial/ethnic disparities. We conducted a secondary analysis of a cross-sectional, nationally representative survey of Internet users to evaluate whether there were racial/ethnic disparities in self-reported telehealth use early in the pandemic. Materials and Methods The Pew Research Center fielded the survey March 19-24, 2020. Telehealth use because of the pandemic was measured by asking whether respondents (N = 10,624) “used the internet or email to connect with doctors or other medical professionals as a result of the coronavirus outbreak.” We conducted survey-weighted logistic regressions, adjusting for respondents’ socioeconomic characteristics and perceived threat of the pandemic to their own health (no threat, minor, major). Results Approximately 17% of respondents reported using telehealth because of the pandemic, with significantly higher unadjusted odds among Blacks, Latinos, and those identified with other race compared to White respondents. The multivariable logistic regressions and sensitivity analyses show Black respondents were more likely than Whites to report using telehealth because of the pandemic, particularly when perceiving the pandemic as a minor threat to their own health. Discussion Black respondents are most likely to report using telehealth because of the COVID-19 pandemic, particularly when they perceive the pandemic as a minor health threat. Conclusion The systemic racism creating health and health care disparities has likely raised the need for telehealth among Black patients during the pandemic. Findings suggest opportunities to leverage a broadly defined set of telehealth tools to reduce health care disparities post-pandemic.

Clinicians should leverage the EHR's value in quality of care and discuss patients' privacy concerns during clinic visits, while policy makers should consider how to address the real and perceived privacy and security risks of EHRs.

Background Public health surveillance experts are leveraging user-generated content on social media to track the spread and effects of COVID-19. However, racial and ethnic digital divides, which are disparities among people who have internet access and post on social media, can bias inferences. This bias is particularly problematic in the context of the COVID-19 pandemic because due to structural inequalities, members of racial and ethnic minority groups are disproportionately vulnerable to contracting the virus and to the deleterious economic and social effects from mitigation efforts. Further, important demographic intersections with race and ethnicity, such as gender and age, are rarely investigated in work characterizing social media users; however, they reflect additional axes of inequality shaping differential exposure to COVID-19 and its effects. Objective The aim of this study was to characterize how the race and ethnicity of US adults are associated with their odds of posting COVID-19 content on social media and how gender and age modify these odds. Methods We performed a secondary analysis of a survey conducted by the Pew Research Center from March 19 to 24, 2020, using a national probability sample (N=10,510). Respondents were recruited from an online panel, where panelists without an internet-enabled device were given one to keep at no cost. The binary dependent variable was responses to an item asking whether respondents “used social media to share or post information about the coronavirus.” We used survey-weighted logistic regressions to estimate the odds of responding in the affirmative based on the race and ethnicity of respondents (white, black, Latino, other race/ethnicity), adjusted for covariates measuring sociodemographic background and COVID-19 experiences. We examined how gender (female, male) and age (18 to 30 years, 31 to 50 years, 51 to 64 years, and 65 years and older) intersected with race and ethnicity by estimating interactions. Results Respondents who identified as black (odds ratio [OR] 1.29, 95% CI 1.02-1.64; P=.03), Latino (OR 1.66, 95% CI 1.36-2.04; P<.001), or other races/ethnicities (OR 1.33, 95% CI 1.02-1.72; P=.03) had higher odds than respondents who identified as white of reporting that they posted COVID-19 content on social media. Women had higher odds of posting than men regardless of race and ethnicity (OR 1.58, 95% CI 1.39-1.80; P<.001). Among men, respondents who identified as black, Latino, or members of other races/ethnicities were significantly more likely to post than respondents who identified as white. Older adults (65 years or older) had significantly lower odds (OR 0.73, 95% CI 0.57-0.94; P=.01) of posting compared to younger adults (18-29 years), particularly among those identifying as other races/ethnicities. Latino respondents were the most likely to report posting across all age groups. Conclusions In the United States, members of racial and ethnic minority groups are most likely to contribute to COVID-19 content on social media, particularly among groups traditionally less likely to use social media (older adults and men). The next step is to ensure that data collection procedures capture this diversity by encompassing a breadth of search criteria and social media platforms.

What are, and what should be, the boundaries between self and society, individuals and groups? To address these questions, we synthesize research on privacy that is relevant for two foundational sociological issues: social order and inequality. By synthesizing work on a narrow yet fundamental set of issues, we aim to improve our understanding of privacy as well as provide a foundation for understanding contemporary privacy issues associated with information and communication technology. We explore the role of privacy in maintaining social order by examining the connections of privacy with social control and with group cohesion. We also discuss how inequality produces variation in privacy and how this variation in turn contributes to inequality. Throughout the review we identify potential directions for sociological research on privacy generally and in the context of new technologies. Our discussion highlights implications of privacy that extend beyond individual-level concerns to broader social, structural impacts.

With the narrowing of Internet access divide, researchers have focused on Internet usage, taking for granted access issues. However, questions remain regarding who has Internet access in the United States: What is the status of the racial divide? Is there still a gender divide? How do Latinos compare to other racial and ethnic minority groups? How does gender intersect with race and ethnicity? I analyze nationally representative data to compare Internet access among adults from 2007 to 2012. I find that women are more likely to report having Internet access than men. Blacks and Latinos are equally likely to report having Internet access, and both groups are less likely to report having Internet access than Whites. Finally, Black men exhibited the greatest increase in access. This research complements Internet usage studies with a recent assessment of Internet access trends, important trends to monitor as policies and technological innovations aim for universal access.

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Copresence, the sense of ''being together'' with others, is at the center of theories about social interaction. It is an intra-individual sense that stems from and shapes the social context. Recent research on copresence in virtual environments (VEs), synthetic simulations of existing experiences (e.g., desktop computer environments, ''virtual reality''), demonstrates the variability in which people experience copresence with others who are not sharing in the same time or space. At the same time, experimental researchers in sociology are using VEs as a methodological tool, yet remain unaware about the ramifications of varying levels of copresence for the social processes under investigation. The goal of this review is to introduce sociologists to the research on copresence, specifically highlighting findings and gaps important for those who use VEs in their research practice. An understanding of how copresence occurs in VEs can improve how well sociologists design experiments to advance theories about interpersonal behavior.