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JMIR Infodemiology ; 3: e40575, 2023.
Article in English | MEDLINE | ID: covidwho-2296561


Background: Social media has emerged as a critical mass communication tool, with both health information and misinformation now spread widely on the web. Prior to the COVID-19 pandemic, some public figures promulgated anti-vaccine attitudes, which spread widely on social media platforms. Although anti-vaccine sentiment has pervaded social media throughout the COVID-19 pandemic, it is unclear to what extent interest in public figures is generating anti-vaccine discourse. Objective: We examined Twitter messages that included anti-vaccination hashtags and mentions of public figures to assess the connection between interest in these individuals and the possible spread of anti-vaccine messages. Methods: We used a data set of COVID-19-related Twitter posts collected from the public streaming application programming interface from March to October 2020 and filtered it for anti-vaccination hashtags "antivaxxing," "antivaxx," "antivaxxers," "antivax," "anti-vaxxer," "discredit," "undermine," "confidence," and "immune." Next, we applied the Biterm Topic model (BTM) to output topic clusters associated with the entire corpus. Topic clusters were manually screened by examining the top 10 posts most highly correlated in each of the 20 clusters, from which we identified 5 clusters most relevant to public figures and vaccination attitudes. We extracted all messages from these clusters and conducted inductive content analysis to characterize the discourse. Results: Our keyword search yielded 118,971 Twitter posts after duplicates were removed, and subsequently, we applied BTM to parse these data into 20 clusters. After removing retweets, we manually screened the top 10 tweets associated with each cluster (200 messages) to identify clusters associated with public figures. Extraction of these clusters yielded 768 posts for inductive analysis. Most messages were either pro-vaccination (n=329, 43%) or neutral about vaccination (n=425, 55%), with only 2% (14/768) including anti-vaccination messages. Three main themes emerged: (1) anti-vaccination accusation, in which the message accused the public figure of holding anti-vaccination beliefs; (2) using "anti-vax" as an epithet; and (3) stating or implying the negative public health impact of anti-vaccination discourse. Conclusions: Most discussions surrounding public figures in common hashtags labelled as "anti-vax" did not reflect anti-vaccination beliefs. We observed that public figures with known anti-vaccination beliefs face scorn and ridicule on Twitter. Accusing public figures of anti-vaccination attitudes is a means of insulting and discrediting the public figure rather than discrediting vaccines. The majority of posts in our sample condemned public figures expressing anti-vax beliefs by undermining their influence, insulting them, or expressing concerns over public health ramifications. This points to a complex information ecosystem, where anti-vax sentiment may not reside in common anti-vax-related keywords or hashtags, necessitating further assessment of the influence that public figures have on this discourse.

J Womens Health (Larchmt) ; 30(4): 514-524, 2021 04.
Article in English | MEDLINE | ID: covidwho-1147921


Objectives: The coronavirus disease 2019 (COVID-19) pandemic has presented extreme challenges for health care workers. This study sought to characterize challenges faced by physician mothers, compare differences in challenges by home and work characteristics, and elicit specific needs and potential solutions. Methods: We conducted a mixed-methods online survey of the Physician Moms Group (PMG) and PMG COVID19 Subgroup on Facebook from April 18th to 29th, 2020. We collected structured data on personal and professional characteristics and qualitative data on home and work concerns. We analyzed qualitative data thematically and used bivariate analyses to evaluate variation in themes by frontline status and children's ages. Results: We included 1,806 participants in analysis and identified 10 key themes. The most frequently identified need/solution was for Community and Government Support (n = 545, 47.1%). When comparing frontline and nonfrontline physicians, those on the frontline more frequently raised concerns about Personal Health and Safety (67.8% vs. 48.4%, p < 0.001), Organizational Communication and Relationships (31.8% vs. 23.8%, p < 0.001), and Family Health and Safety (27.2 vs. 16.6, p < 0.001), while nonfrontline physicians more frequently addressed Patient Care and Safety (56.4% vs. 48.2%, p < 0.001) and Financial/Job Security (33.8% vs. 46.9%, p < 0.001). Participants with an elementary school-aged child more frequently raised concerns about Parenting/Homeschooling (44.0% vs. 31.1%, p < 0.001) and Work/Life Balance (28.4 vs. 13.7, p < 0.001), and participants with a preschool-aged child more frequently addressed Access to Childcare (24.0 vs. 7.7, p < 0.001) and Spouse/Partner Relationships (15.8 vs. 9.5, p < 0.001), when compared to those without children in these age groups. Conclusions: The physician workforce is not homogenous. Health care and government leaders need to understand these diverse challenges in order to meet physicians' professional and family needs during the pandemic.

COVID-19/psychology , Mothers/psychology , Occupational Stress/psychology , Pandemics , Physicians, Women/psychology , Work-Life Balance , Adult , COVID-19/epidemiology , COVID-19/prevention & control , Child , Child, Preschool , Female , Humans , Mental Health , Middle Aged , SARS-CoV-2 , Young Adult