ABSTRACT
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.
ABSTRACT
BACKGROUND: The COVID-19 pandemic prompted safety-net health care systems to rapidly implement telemedicine services with little prior experience, causing disparities in access to virtual visits. While much attention has been given to patient barriers, less is known regarding system-level factors influencing telephone versus video-visit adoption. As telemedicine remains a preferred service for patients and providers, and reimbursement parity will not continue for audio visits, health systems must evaluate how to support higher-quality video visit access. OBJECTIVE: This study aimed to assess health system-level factors and their impact on telephone and video visit adoption to inform sustainability of telemedicine for ambulatory safety-net sites. METHODS: We conducted a cross-sectional survey among ambulatory care clinicians at a hospital-linked ambulatory clinic network serving a diverse, publicly insured patient population between May 28 and July 14, 2020. We conducted bivariate analyses assessing health care system-level factors associated with (1) high telephone adoption (4 or more visits on average per session); and (2) video visit adoption (at least 1 video visit on average per session). RESULTS: We collected 311 responses from 643 eligible clinicians, yielding a response rate of 48.4%. Clinician respondents (N=311) included 34.7% (n=108) primary or urgent care, 35.1% (n=109) medical, and 7.4% (n=23) surgical specialties. Our sample included 178 (57.2%) high telephone adopters and 81 (26.05%) video adopters. Among high telephone adopters, 72.2% utilized personal devices for telemedicine (vs 59.0% of low telephone adopters, P=.04). Video nonadopters requested more training in technical aspects than adopters (49.6% vs 27.2%, P<.001). Primary or urgent care had the highest proportion of high telephone adoption (84.3%, compared to 50.4% of medical and 37.5% of surgical specialties, P<.001). Medical specialties had the highest proportion of video adoption (39.1%, compared to 14.8% of primary care and 12.5% of surgical specialties, P<.001). CONCLUSIONS: Personal device access and department specialty were major factors associated with high telephone and video visit adoption among safety-net clinicians. Desire for training was associated with lower video visit use. Secure device access, clinician technical trainings, and department-wide assessments are priorities for safety-net systems implementing telemedicine.