Correction: Twitter and Facebook posts about COVID-19 are less likely to spread misinformation compared to other health topics.

[This corrects the article DOI: 10.1371/journal.pone.0261768.].

Twitter social mobility data reveal demographic variations in social distancing practices during the COVID-19 pandemic.

The COVID-19 pandemic demonstrated the importance of social distancing practices to stem the spread of the virus. However, compliance with public health guidelines was mixed. Understanding what factors are associated with differences in compliance can improve public health messaging since messages could be targeted and tailored to different population segments. We utilize Twitter data on social mobility during COVID-19 to reveal which populations practiced social distancing and what factors correlated with this practice. We analyze correlations between demographic and political affiliation with reductions in physical mobility measured by public geolocation tweets. We find significant differences in mobility reduction between these groups in the United States. We observe that males, Asian and Latinx individuals, older individuals, Democrats, and people from higher population density states exhibited larger reductions in movement. Furthermore, our study also unveils meaningful insights into the interactions between different groups. We hope these findings will provide evidence to support public health policy-making.

Empathic Engagement With the COVID-19 Vaccine Hesitant in Private Facebook Groups: A Randomized Trial.

BACKGROUND: Vaccine misinformation has been widely spread on social media, but attempts to combat it have not taken advantage of the attributes of social media platforms for health education. METHODS: The objective was to test the efficacy of moderated social media discussions about COVID-19 vaccines in private Facebook groups. Unvaccinated U.S. adults were recruited using Amazon's Mechanical Turk and randomized. In the intervention group, moderators posted two informational posts per day for 4 weeks and engaged in relationship-building interactions with group members. In the control group, participants received a referral to Facebook's COVID-19 Information Center. Follow-up surveys with participants (N = 478) were conducted 6 weeks post-enrollment. RESULTS: At 6 weeks follow-up, no differences were found in vaccination rates. Intervention participants were more likely to show improvements in their COVID-19 vaccination intentions (vs. stay same or decline) compared with control (p = .03). They also improved more in their intentions to encourage others to vaccinate for COVID-19. There were no differences in COVID-19 vaccine confidence or intentions between groups. General vaccine and responsibility to vaccinate were higher in the intervention compared with control. Most participants in the intervention group reported high levels of satisfaction. Participants engaged with content (e.g., commented, reacted) 11.8 times on average over the course of 4 weeks. CONCLUSIONS: Engaging with vaccine-hesitant individuals in private Facebook groups improved some COVID-19 vaccine-related beliefs and represents a promising strategy.

Trust in public health institutions moderates the effectiveness of COVID-19 vaccine discussion groups on Facebook.

BACKGROUND: Distrust and partisan identity are theorized to undermine health communications. We examined the role of these factors on the efficacy of discussion groups intended to promote vaccine uptake. METHOD: We analyzed survey data from unvaccinated Facebook users (N = 371) living in the US between January and April 2022. Participants were randomly assigned to Facebook discussion groups (intervention) or referred to Facebook's COVID-19 Information Center (control). We used Analysis of Covariance to test if the intervention was more effective at changing vaccination intentions and beliefs compared to the control in subgroups based on participants' partisan identity, political views, and information trust views. RESULTS: We found a significant interaction between the intervention and trust in public health institutions (PHIs) for improving intentions to vaccinate (P = .04), intentions to encourage others to vaccinate (P = .03), and vaccine confidence beliefs (P = .01). Among participants who trusted PHIs, those in the intervention had higher posttest intentions to vaccinate (P = .008) and intentions to encourage others to vaccinate (P = .002) compared to the control. Among non-conservatives, participants in the intervention had higher posttest intentions to vaccinate (P = .048). The intervention was more effective at improving intentions to encourage others to vaccinate within the subgroups of Republicans (P = .03), conservatives (P = .02), and participants who distrusted government (P = .02). CONCLUSIONS: Facebook discussion groups were more effective for people who trusted PHIs and non-conservatives. Health communicators may need to segment health messaging and develop strategies around trust views.

Inductive detection of influence operations via graph learning.

Influence operations are large-scale efforts to manipulate public opinion. The rapid detection and disruption of these operations is critical for healthy public discourse. Emergent AI technologies may enable novel operations that evade detection and influence public discourse on social media with greater scale, reach, and specificity. New methods of detection with inductive learning capacity will be needed to identify novel operations before they indelibly alter public opinion and events. To this end, we develop an inductive learning framework that: (1) determines content- and graph-based indicators that are not specific to any operation; (2) uses graph learning to encode abstract signatures of coordinated manipulation; and (3) evaluates generalization capacity by training and testing models across operations originating from Russia, China, and Iran. We find that this framework enables strong cross-operation generalization while also revealing salient indicators-illustrating a generic approach which directly complements transductive methodologies, thereby enhancing detection coverage.

The efficacy of Facebook's vaccine misinformation policies and architecture during the COVID-19 pandemic.

Online misinformation promotes distrust in science, undermines public health, and may drive civil unrest. During the coronavirus disease 2019 pandemic, Facebook-the world's largest social media company-began to remove vaccine misinformation as a matter of policy. We evaluated the efficacy of these policies using a comparative interrupted time-series design. We found that Facebook removed some antivaccine content, but we did not observe decreases in overall engagement with antivaccine content. Provaccine content was also removed, and antivaccine content became more misinformative, more politically polarized, and more likely to be seen in users' newsfeeds. We explain these findings as a consequence of Facebook's system architecture, which provides substantial flexibility to motivated users who wish to disseminate misinformation through multiple channels. Facebook's architecture may therefore afford antivaccine content producers several means to circumvent the intent of misinformation removal policies.

Measuring the monetization strategies of websites with application to pro- and anti-vaccine communities.

Anti-vaccine content and other kinds of misinformation are hypothesized to be more heavily monetized than other kinds of online content. We test this hypothesis by applying several novel and scalable measures of website monetization strategies to more than 400,000 links shared by 261 anti-vaccine Facebook pages and 190 pro-vaccine ones. Contrary to expectations, websites promoted in pro-vaccine venues do more to monetize attention than those promoted in anti-vaccine venues. This is a consequence of how intensely monetized news websites are-pro-vaccine venues share more links to news. The specific news sites shared by anti-vaccine venues are rated less credible by fact-checking organizations, but we find little substantive difference in their monetization strategies. These results emphasize the need to interpret measures of monetization within the context of the broader "attention economy".

IQOS marketing strategies in the USA before and after US FDA modified risk tobacco product authorisation.

INTRODUCTION: Given that the US Food and Drug Administration (FDA) authorised reduced exposure messaging to be used in IQOS marketing, we examined: (1) IQOS ad content; (2) advertising media channels and (3) changes in advertising efforts over time. METHODS: We conducted a mixed-methods study regarding IQOS ad content (headlines, themes, images), ad occurrence characteristics (including content, media channels and adspend) in the USA from August 2019 to April 2021 using Numerator advertising/marketing data. RESULTS: Across 24 unique ads and 591 occurrences (84.6% online, 8.0% print, 7.4% mobile), there was $4 902 110 total adspend (98.9% allocated to print). Across unique ads, occurrences and adspend, prominent themes included 'real tobacco' (45.8%, 47.4%, 30.1%, respectively), less odour/ash (29.2%, 21.0%, 29.9%) and switching from cigarettes (25.0%, 19.5%, 69.4%), and images mainly featured the product alone (58.2%, 61.4%, 99.5%) or with women (25.0%, 19.1%, 0.3%). Per occurrences and adspend, the most prominent media channel themes (eg, magazine/website topics) were technology (19.3%, 10.6%), women's fashion (18.1%, 26.2%), weather/news (9.0%, 15.3%) and entertainment/pop culture/gaming (8.5%, 23.1%). Ad themes appearing only post-FDA authorisation included switching from traditional cigarettes, same-day/home-delivery, convenience (eg, use indoors), reduced exposure to some dangerous substances, science/research and distinction from e-cigarettes. Overall adspend per occurrence increased postauthorisation (p=0.016); the highest adspend per unique ad (69.3% of total) focused on ads featuring reduced exposure. CONCLUSIONS: Regulatory efforts must be informed by ongoing surveillance of IQOS marketing efforts and its impacts, particularly how specific consumer subgroups (eg, tobacco non-users, women, young people) are impacted by marketing exposure.

Economic risk framing increases intention to vaccinate among Republican COVID-19 vaccine refusers.

OBJECTIVE: To determine if framing communications about COVID-19 vaccines in economic terms can increase Republicans' likelihood to get vaccinated. METHODS: We examined Twitter posts between January 2020 and September 2021 by Democratic and Republican politicians to determine how they framed the COVID-19 pandemic. Based on these posts, we carried out a survey study between September and November 2021 to examine whether motivations for COVID-19 vaccine uptake matched message frames that were widely used by these politicians. Finally, we conducted a randomized controlled experiment to examine how these frames (economic vs. health) affected intentions to vaccinate by vaccine refusers in both parties. RESULTS: Republican politicians were more likely to frame the pandemic in economic terms, whereas Democrats predominantly used health frames. Accordingly, vaccinated Republicans' choices were more likely to be motivated by economic consideration (ß = 0.25, p = 0.02) and personal financial rationales (ß = 0.24, p = 0.03). Among vaccine refusers, Republicans exposed to messages using economic rationales to encourage vaccination reported higher vaccination intentions compared to those exposed to messages using public health rationales (F1,119 = 4.16, p = 0.04). CONCLUSION: Messages highlighting economic and personal financial risks could increase intentions to vaccinate for vaccine-hesitant Republicans. PUBLIC HEALTH IMPLICATIONS: Agencies should invest in developing messages that are congruent with frames that are already widely used by co-partisans. Social media may be helpful in eliciting these frames.

Gist Representations and Decision-Making Processes Affecting Antibiotic Prescribing for Children with Acute Otitis Media.

Objective. To test the predictions of fuzzy-trace theory regarding pediatric clinicians' decision-making processes and risk perceptions about antibiotics for children with acute otitis media (AOM). Methods. We conducted an online survey experiment administered to a sample of 260 pediatric clinicians. We measured their risk perceptions and prescribing decisions across 3 hypothetical AOM treatment scenarios. Participants were asked to choose among the following options: prescribe antibiotics immediately, watchful waiting ("hedging"), or not prescribing antibiotics. Results. We identified 4 gists based on prior literature: 1) "why not take a risk?" 2) "antibiotics might not help but can hurt," 3) "antibiotics do not have harmful side effects," and 4) "antibiotics might have harmful side effects." All 4 gists predicted risky choice (P < 0.001), and gist endorsements varied significantly between scenarios when antibiotics were indicated, F(2, 255) = 8.53, P < 0.001; F(2, 255) = 5.14, P < .01; and F(2, 255) = 3.56, P < 0.05 for the first 3 factors, respectively. In a logistic regression, more experienced clinicians were less likely to hedge (B = -0.05; P < 0.01). Conclusion. As predicted by fuzzy-trace theory, pediatric clinicians' prescription decisions are associated with gist representations, which are distinct from verbatim risk estimates. Implications. Antibiotic stewardship programs can benefit by communicating the appropriate gists to clinicians who prescribe antibiotics for pediatric patients. Highlights: We found clinicians' antibiotic prescription decisions were driven by gist representations of antibiotic risks for a given hypothetical patient scenario, and clinicians' gist representations and verbatim risk estimates about antibiotic-related risks were distinct from each other.We showed that the effect of patient scenarios on clinicians' antibiotic prescription decisions was mediated by clinicians' gist representations.Less experienced clinicians tend to "hedge" in their antibiotic prescription decisions compared with more experienced clinicians.The broader impact of our study is that antibiotic stewardship programs can benefit by communicating the appropriate gists to clinicians who prescribe antibiotics for pediatric patients, rather than solely focusing on closing potential knowledge deficits of the clinicians.

The impact of Facebook's vaccine misinformation policy on user endorsements of vaccine content: An interrupted time series analysis.

OBJECTIVES: To evaluate the impact of Facebook's vaccine misinformation policy in March 2019 on user endorsements of vaccine content on its platform. METHODS: We identified 172 anti- and pro-vaccine Facebook Pages and collected posts from these Pages six months before and after the policy. Using interrupted time series regression models, we evaluated the policy impact on user endorsements (i.e., likes) of anti- and pro-vaccine posts on Facebook. RESULTS: The number of likes for posts on anti-vaccine Pages had decreased after the policy implementation (policy = 153.2, p < 0.05; policy*day = -0.838, p < 0.05; marginal effect at the mean = -22.74, p < 0.01; marginal effect at the median = -24.56, p < 0.01). When the number of subscribers was considered, the policy effect on the number of likes for anti-vaccine posts was much smaller, but still statistically significant (policy = 4.849, p < 0.05; policy*day = -0.027, p < 0.05; marginal effect at the mean = -0.742, p < 0.01; marginal effect at the median = -0.800, p < 0.01). There was no policy effect observed for posts on pro-vaccine Pages. CONCLUSIONS: Our analysis suggested that Facebook's March 2019 vaccine misinformation policy moderately impacted the number of endorsements of anti-vaccine content on its platform. Social media companies can take measures to limit the popularity of anti-vaccine content by reducing their reach and visibility. Future research efforts should focus on evaluating additional policies and examining policies across platforms.

An Investigation of Influential Users in the Promotion and Marketing of Heated Tobacco Products on Instagram: A Social Network Analysis.

While an increasing body of the literature has documented the exposure to emerging tobacco products including heated tobacco products (HTPs) on social media, few studies have investigated the various stakeholders involved in the generation of promotional tobacco content. This study constructed a social network of Instagram users who posted IQOS content, a leading HTP brand, between 1 January and 5 April 2021 and identified users who positioned near the center of the network. We identified 4526 unique Instagram users who had created 19,951 IQOS-related posts during the study period. Nearly half of the users (42.1%) were business accounts authorized by Instagram, among which 59.0% belonged to Personal Goods and General Merchandise Stores and 18.1% belonged to Creators and Celebrities. For users with higher in-degree, out-degree, betweenness, and closeness centrality in the network, the majority of them were accounts directly associated with IQOS (e.g., containing "iqos" in username) or related to tobacco business as self-identified in the bio. Our findings further refine the social media marketing presence of tobacco products and suggest that the current self-regulatory efforts led by social media platforms are far from enough.

Twitter and Facebook posts about COVID-19 are less likely to spread misinformation compared to other health topics.

The COVID-19 pandemic brought widespread attention to an "infodemic" of potential health misinformation. This claim has not been assessed based on evidence. We evaluated if health misinformation became more common during the pandemic. We gathered about 325 million posts sharing URLs from Twitter and Facebook during the beginning of the pandemic (March 8-May 1, 2020) compared to the same period in 2019. We relied on source credibility as an accepted proxy for misinformation across this database. Human annotators also coded a subsample of 3000 posts with URLs for misinformation. Posts about COVID-19 were 0.37 times as likely to link to "not credible" sources and 1.13 times more likely to link to "more credible" sources than prior to the pandemic. Posts linking to "not credible" sources were 3.67 times more likely to include misinformation compared to posts from "more credible" sources. Thus, during the earliest stages of the pandemic, when claims of an infodemic emerged, social media contained proportionally less misinformation than expected based on the prior year. Our results suggest that widespread health misinformation is not unique to COVID-19. Rather, it is a systemic feature of online health communication that can adversely impact public health behaviors and must therefore be addressed.

Viruses, Vaccines, and COVID-19: Explaining and Improving Risky Decision-making.

Risky decision-making lies at the center of the COVID-19 pandemic and will determine future viral outbreaks. Therefore, a critical evaluation of major explanations of such decision-making is of acute practical importance. We review the underlying mechanisms and predictions offered by expectancy-value and dual-process theories. We then highlight how fuzzy-trace theory builds on these approaches and provides further insight into how knowledge, emotions, values, and metacognitive inhibition influence risky decision-making through its unique mental representational architecture (i.e., parallel verbatim and gist representations of information). We discuss how social values relate to decision-making according to fuzzy-trace theory, including how categorical gist representations cue core values. Although gist often supports health-promoting behaviors such as vaccination, social distancing, and mask-wearing, why this is not always the case as with status-quo gist is explained, and suggestions are offered for how to overcome the "battle for the gist" as it plays out in social media.

OPEX: Development of a novel overall patient experience measure to facilitate interpretation of comparison effectiveness studies.

OBJECTIVES: A measure that encompasses both benefits and harms at the individual patient level may facilitate comparisons between treatment options and improve shared decision-making. The objective of this study was to develop a patient reported measure to capture overall experience (including both benefits and harms) of treatment using rheumatoid arthritis (RA) as a case example. METHODS: Hierarchies for treatment benefits are known. Therefore, we developed a hierarchy of adverse events (AEs) using a series of trajectory mapping and paired comparison surveys. We subsequently used these data to construct a paired comparison survey, asking patients to compare options including both a specified level of benefit and an AE. These data were used to generate a hierarchy of overall experience on treatment. RESULTS: 782 participants completed a series of three surveys. The trajectory mapping procedure and a paired comparison survey led to the generation of a hierarchy of AEs with nine levels ranging from No AEs to irreversible serious complications. In a third survey, in which AEs were paired with benefits, participants' ratings generated a 6-level hierarchy of overall experiences ranging from Major improvement + No, mild or manageable AEs (Level 1) to No improvement + Irreversible AEs (Level 6). CONCLUSIONS: Using a trajectory mapping approach, we developed a patient reported measure representing the distribution of patients' overall experiences on treatment. The intent of this measure is to enable patients and their physicians to compare the percentage of patients experiencing each level of outcome, from most to least desirable, across treatments.