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10.2196/20472

http://scihub22266oqcxt.onion/10.2196/20472
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32568726!7340161!32568726
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suck abstract from ncbi


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pmid32568726      J+Med+Internet+Res 2020 ; 22 (7): e20472
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  • Racial and Ethnic Digital Divides in Posting COVID-19 Content on Social Media Among US Adults: Secondary Survey Analysis #MMPMID32568726
  • Campos-Castillo C; Laestadius LI
  • J Med Internet Res 2020[Jul]; 22 (7): e20472 PMID32568726show ga
  • 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.
  • |*Betacoronavirus[MESH]
  • |*Coronavirus Infections/epidemiology[MESH]
  • |*Digital Divide[MESH]
  • |*Pandemics[MESH]
  • |*Pneumonia, Viral/epidemiology[MESH]
  • |*Surveys and Questionnaires[MESH]
  • |Adolescent[MESH]
  • |Age Factors[MESH]
  • |Aged[MESH]
  • |Black or African American/statistics & numerical data[MESH]
  • |COVID-19[MESH]
  • |Ethnicity/*statistics & numerical data[MESH]
  • |Female[MESH]
  • |Hispanic or Latino/statistics & numerical data[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Minority Groups/statistics & numerical data[MESH]
  • |Odds Ratio[MESH]
  • |Racial Groups/*statistics & numerical data[MESH]
  • |SARS-CoV-2[MESH]
  • |Sex Factors[MESH]
  • |Social Media/*statistics & numerical data/supply & distribution[MESH]
  • |Socioeconomic Factors[MESH]
  • |United States/epidemiology[MESH]
  • |White People/statistics & numerical data[MESH]


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