Nothing Special   »   [go: up one dir, main page]

This paper is in the following e-collection/theme issue:

Theme Issue 2023: Exploring the Intersection Between Health Information, Misinformation, and Generative AI Technologies (4) JMIR Theme Issue: COVID-19 Special Issue (2450) Misinformation and Disinformation Outbreaks and Information Prevalence Studies (43) Infodemiology and Infoveillance (1349)

Published on in Vol 4 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51328, first published .
Descriptions of Scientific Evidence and Uncertainty of Unproven COVID-19 Therapies in US News: Content Analysis Study

Descriptions of Scientific Evidence and Uncertainty of Unproven COVID-19 Therapies in US News: Content Analysis Study

Descriptions of Scientific Evidence and Uncertainty of Unproven COVID-19 Therapies in US News: Content Analysis Study

Authors of this article:

Sara Watson1 Author Orcid Image ;   Tyler J Benning2 Author Orcid Image ;   Alessandro R Marcon3 Author Orcid Image ;   Xuan Zhu4 Author Orcid Image ;   Timothy Caulfield3 Author Orcid Image ;   Richard R Sharp1, 5 Author Orcid Image ;   Zubin Master6, 7, 8, 9 Author Orcid Image
Article Authors Cited by (1) Tweetations (34) Metrics Author Video

    Original Paper

    1Biomedical Ethics Research Program, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States

    2Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, United States

    3Health Law Institute, University of Alberta, Edmonton, AB, Canada

    4Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United States

    5Center for Individualized Medicine, Mayo Clinic, Rochester, MN, United States

    6Department of Social Sciences and Health Policy, Wake Forest University School of Medicine, Winston-Salem, NC, United States

    7Maya Angelou Center for Health Equity, Wake Forest University School of Medicine, Winston-Salem, NC, United States

    8Center for Bioethics, Health and Society, Wake Forest University School of Medicine, Winston-Salem, NC, United States

    9Wake Forest Institute of Regenerative Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, United States

    *these authors contributed equally

    Corresponding Author:

    Zubin Master, PhD

    Department of Social Sciences and Health Policy

    Wake Forest University School of Medicine

    Medical Center Boulevard

    Suite 310

    Winston-Salem, NC, 27157

    United States

    Phone: 1 3367164289

    Fax:1 3667167554

    Email: zmaster@wakehealth.edu


    Background: Politicization and misinformation or disinformation of unproven COVID-19 therapies have resulted in communication challenges in presenting science to the public, especially in times of heightened public trepidation and uncertainty.

    Objective: This study aims to examine how scientific evidence and uncertainty were portrayed in US news on 3 unproven COVID-19 therapeutics, prior to the development of proven therapeutics and vaccines.

    Methods: We conducted a media analysis of unproven COVID-19 therapeutics in early 2020. A total of 479 discussions of unproven COVID-19 therapeutics (hydroxychloroquine, remdesivir, and convalescent plasma) in traditional and online US news reports from January 1, 2020, to July 30, 2020, were systematically analyzed for theme, scientific evidence, evidence details and limitations, safety, efficacy, and sources of authority.

    Results: The majority of discussions included scientific evidence (n=322, 67%) although only 24% (n=116) of them mentioned publications. “Government” was the most frequently named source of authority for safety and efficacy claims on remdesivir (n=43, 35%) while “expert” claims were mostly mentioned for convalescent plasma (n=22, 38%). Most claims on hydroxychloroquine (n=236, 79%) were offered by a “prominent person,” of which 97% (n=230) were from former US President Trump. Despite the inclusion of scientific evidence, many claims of the safety and efficacy were made by nonexperts. Few news reports expressed scientific uncertainty in discussions of unproven COVID-19 therapeutics as limitations of evidence were infrequently included in the body of news reports (n=125, 26%) and rarely found in headlines (n=2, 2%) or lead paragraphs (n=9, 9%; P<.001).

    Conclusions: These results highlight that while scientific evidence is discussed relatively frequently in news reports, scientific uncertainty is infrequently reported and rarely found in prominent headlines and lead paragraphs.

    JMIR Infodemiology 2024;4:e51328

    doi:10.2196/51328

    Keywords

    COVID-19; COVID-19 drug treatment; information dissemination; health communication; uncertainty; content analysis; information sources; therapy; misinformation; communication; scientific evidence; media analysis; news report; COVID-19 therapy; treatment; public awareness; public trepidation; therapeutic; therapeutics; vaccine; vaccines; pandemic; United States; media analysis; safety; efficacy; evidence; news; report; reports 


    The clear and accurate reporting of science to the public is imperative to maintain public trust and ensure that public health precautions are upheld [1]. Reporting science surrounding protective measures and novel unproven COVID-19 therapeutics during the first year of the pandemic was extraordinarily challenging given the hyperpoliticization of COVID-19, the misinformation or disinformation surrounding scientifically unproven and unapproved therapies, and the reliance on unsubstantiated science, for example, preprints or expert opinion [2].

    Despite the number of news sources available to the public including legacy media and social media, many Americans continue to rely on traditional sources of news. Traditional media are forms of communication predating the internet and include newspapers, broadcast, and radio among others. A 2014 survey by the American Press Institute found just over 60% of Americans prefer to find news directly from news organizations compared to social media (4%), word of mouth (2%), and e-sharing with friends (1%) [3]. While social media and interpersonal communications have been implicated in the spread of misinformation and adoption of preventative behaviors, a study published in 2020 on COVID-19 information sources found traditional media sources (including television and newspapers) were the most widely used sources on COVID-19, and that the source of information individuals reported using predicted their beliefs about the virus [4].

    Reviewing the content of traditional media reports is particularly important because broadcast networks, cable networks, and online and print news are viewed as the most trustworthy and reliable sources of information [4-6]. While news media has a pivotal role in communicating credible scientific evidence [7], some mainstream news outlets have propagated inaccuracies and misinformation [8,9]. Misinformation may influence health beliefs and impact compliance with public health recommendations resulting in negative health consequences [10]. The United States has the second highest prevalence of COVID-19 misinformation compared to other countries [11], which likely has impacted the health of millions of Americans [12].

    The rapid release of COVID-19 research disseminated by numerous news sources with shifting health recommendations has left many feeling overwhelmed and frustrated [13,14], which may contribute to reducing trust in public health officials and institutions [15-17]. Accurate news reporting should avoid hype and speculation [18], illuminate scientific uncertainty, and portray science as iterative and evolving [19-21]. Such portrayals may serve to promote public trust and help citizens understand why public health recommendations are susceptible to change [22-24].

    An examination of early COVID-19 therapeutics serves as an ideal case study on which to examine the media portrayal of scientific evidence because it was a time when there were no approved treatments, prior to the development of proven therapeutics and vaccines, and during a period of high public trepidation and scientific uncertainty regarding COVID-19 treatments. In this study, we examined how scientific evidence and uncertainty were portrayed in traditional and online US news about 3 popular and potential COVID-19 therapeutics (hydroxychloroquine, remdesivir, and convalescent plasma [CP]) when no other US Food and Drug Administration–approved treatments or vaccines were available.


    Conceptual Framework

    This research examined the portrayal of scientific evidence and uncertainty of 3 unproven COVID-19 therapeutics prior to the development of vaccines and compared its representation among the body (full text or video) of news reports with headlines and lead paragraphs. There are 2 widely understood and generally accepted paradigms of science communication that focus on the unidirectional delivery of information or active engagement with the public [25-27]. These paradigms can further be divided into 4 models of science communication, which are science literacy (also referred to as the deficit model), contextual, lay expertise, and public engagement or public participation [28]. The science literacy model is premised that information transmitted by experts aims to reduce the deficit of science knowledge among the public while the contextual model similarly transmits information, but situates information to specific audiences paying attention to culture, location, and language among other relevant contexts. Both, however, focus on the transmission of scientific information. The lay expertise model acknowledges the limitations of science and endorses “lay” knowledge as equal to scientific knowledge. The public engagement model aims to address science policy issues through active engagement and interaction with the public in a democratic process. These latter 2 models focus on improving engagement between science and society and recognize the limitations of science and refrain from giving science any more authority than other knowledge sources. Several scholars have conceptualized variations or additions to these models and outlined new goals of science communication [26,27,29,30]. However, these models remain largely theoretical and provide little practical direction toward the practice of science communication today, which involves an array of different sources (eg, internet, social media, and legacy media), actors (eg, general and science journalists, bloggers, influencers, and others), and approaches (eg, traditional journalistic norms and a plurality of practices among content contributors in the new media environment) [31]. In addition, the models provide little in terms of approaches to analyze contemporary news reports produced by traditional media outlets reported by journalists because there is no accepted conceptual framework on the public communication of science in the media and best practices to convey scientific evidence and uncertainty to the public [32,33]. Instead, our analytical approach was informed by adopting a lens of a changing science media communication landscape where public reporting of science has moved beyond conveying scientific facts and where journalists use frames to describe science accurately while maintaining audience engagement [31,34]. This, however, results in multiple challenges in accurately reporting science to the public including science hype [35]; errors of omission [36]; failure to report funding sources and conflicts of interest [37]; inadequately detailing methods, risks, and timelines [38-40]; improperly addressing scientific uncertainty; and situating science in particular contexts, for example, politics.

    There is variability in the portrayal of scientific evidence and uncertainty in the news media. Some studies have shown less accurate portrayals where the results are discussed as certain and the benefits overemphasized [41-44], while other studies have demonstrated inaccuracies in reporting evidence when comparing press releases and media articles with scientific publications resulting in oversimplification, absence of quantification, lack of explicitly reporting data sources, and the absence of study limitations [45,46]. On the other hand, scientific uncertainty on climate change among other specific topics has been heightened in news media by journalists framing science as inconclusive or providing equal space for opposing viewpoints, even if one viewpoint is supported by substantial scientific consensus and evidence while the other lacks credible evidence [47-49]. News reports of scientific discoveries aiming to provide balanced perspectives may inadvertently cause a false balance and distort the public’s perception of consensus surrounding scientific evidence [50].

    This research was also informed by the reality that the public often engages with snippets of information including a focus and evaluation of articles based on headlines [51,52]. Our focus on analyzing scientific evidence and uncertainty in headlines and lead paragraphs, and comparing it with the body of news reports was further informed by the primacy effect—a cognitive bias where people recall and place greater emphasis on initial pieces of information [53,54]—which may explain why headlines and lead paragraphs are especially important in shaping the audience’s understanding and judgment of news stories.

    Finally, our conceptual framework was also informed by a media environment with a higher prevalence of COVID-19 health misinformation and an understanding of the efforts to correct news reports by health and scientific experts through media fact-checking and myth-busting approaches [55-58]. While several studies have shown the effectiveness of fact-checking and the correction of misinformation postexposure at altering beliefs [59-63], it remains unclear if such approaches would fully address concerns of reported health misinformation. This is partly due to differences in the focus fact-checkers and myth busters consider when aiming to correct scientific facts, the framing of science news stories by reporters, ambiguity and discordance in the interpretation of scientific facts, and that truth-telling may not always reach intended audiences [64-66]. Such approaches epistemologically rely on the assumption that facts, even in the context of scientific evidence, can always be clearly discerned from nonfactual information and that experts can identify and expose truths from falsehoods; such approaches may minimize or discount completely the complex interplay between beliefs, politics, and science [67]. Being mindful of this context, our analysis focused on how, where, and by whom scientific evidence surrounding unproven COVID-19 therapeutics was portrayed in the news stories themselves and we did not address the veracity of the scientific evidence presented in the news.

    Sampling

    We chose to investigate 3 unproven products—hydroxychloroquine, remdesivir, and CP—based primarily on their popularity in US news among other factors that informed our decision. Several antivirals and immunomodulators were being considered as potential classes of therapeutics used to treat COVID-19 in the early 2020s [68]. An initial set of news database searches (discussed in the next section) identified hydroxychloroquine (4023 publications), remdesivir (2839 publications), azithromycin (416 publications), and CP (372 publications) as the most popular unproven products in US news compared to other products being considered including, lopinavir, interferon beta-1a, dexamethasone, and heparin or low molecular weight heparin. For feasibility reasons, we chose to evaluate 3 products and decided to include CP instead of azithromycin because after removing news reports discussing each product in conjunction with hydroxychloroquine, there were 344 articles discussing CP and only 57 articles discussing azithromycin. Additionally, the choice to examine hydroxychloroquine, remdesivir, and CP was supported because these products were being investigated in registered clinical studies in the United States (hydroxychloroquine, ClinicalTrials.gov NCT04714515; remdesivir, ClinicalTrials.gov NCT04257656; and CP, ClinicalTrials.gov NCT05578391) and permitted to be used to treat patients with COVID-19 by the US Food and Drug Administration (FDA; please see the following paragraphs for details).

    News sources were identified using the Factiva database by the Dow Jones & Company [69]. Factiva is a commonly used research tool that provides full-text coverage of current and archival business and news information from traditional (eg, broadcast and newspaper) media and news available online. The specific news sources selected for our query were determined by popularity and coverage and were compiled based on 3 independent organizations that rank news based on circulation and internet traffic (see Table S1 in Multimedia Appendix 1) [70-72]. Having a diverse venue of sources is important since issues of unproven COVID-19 therapies have become politicized and studies have shown differing levels of depth and misinformation between news organizations.

    After eliminating duplicate news sources listed by these organizations, we queried the terms hydroxychloroquine, Plaquenil, remdesivir, Veklury, and CP in the headline or lead paragraph of articles published from January 1, 2020, to July 30, 2020. The search dates were selected to ensure we captured the portrayal of scientific evidence of early unproven therapeutics to treat COVID-19 in US news. The start date of our search was chosen because a pneumonia-causing novel coronavirus was first announced on January 7, 2020, with the first confirmed US case on January 20, 2020 [73]. The end date was chosen based on clinical investigations and decisions made by the FDA on our 3 therapeutics of interest. Specifically, several clinical investigations examining the 3 potential therapeutics of interest were initiated during the first quarter of 2020, and scientific evidence about the safety and efficacy of the therapeutics was being collected and concluded [68,74,75]. Specifically, large clinical trials of hydroxychloroquine were initiated, paused, and eventually halted from late May to late June [74,76-78]. Based on clinical trial results, the FDA revoked emergency use authorization for hydroxychloroquine on June 15, 2020 [79]. Starting May 28, 2020, participants were being enrolled for a clinical trial on CP and on April 3, 2020, the FDA approved an expanded access protocol for Mayo Clinic to lead an investigation to understand the effects of CP [80]. The FDA also issued an emergency use authorization for remdesivir on May 1, 2020 [81]. Finally, the end date for our search was also chosen for practical reasons as data collection efforts began on July 31, 2020.

    The search yielded 1136 reports including online and print articles, television transcripts, and videos. Application of inclusion or exclusion criteria was conducted by SW and TJB (primary coders). The coders matched the headline and news source of the web link obtained from Factiva for online media. Web-based reports with a video were considered 2 independent reports unless the video was verbatim or substantially similar to the associated article. Reports that were considered substantially similar must have had at least 1 area of similarity on the topic, main theme, concluding points, people quoted, or style (eg, debate). In instances of substantial similarity, only the most up-to-date report was included. Reports that were duplicative, unobtainable, or void of search terms were removed resulting in 1103 reports. If multiple therapeutics were discussed in a single report, the codebook was applied to each therapeutic. We randomly sampled a total of 550 news reports from our population to manage coder effort while allowing the capture of codes and themes among news reports. After random sampling, reports without substantial discussion of the COVID-19 therapeutic were excluded if they failed to satisfy codes 7-16 of the codebook (n=72). When a therapeutic was found only in an image caption, tweets, or graphics within the report, the report was also excluded (n=29). After applying exclusion criteria, a final data set of 479 individual discussions of a therapeutic was found in 449 news reports. See Figure S1 in Multimedia Appendix 1 for a flowchart providing an overview of the sampling strategy.

    Codebook

    A comprehensive codebook was developed based on the literature described. The purpose of the codebook was to ensure that a consistent analytical framework was adopted by both coders and to reduce randomness in the interpretation of themes and codes. Upon developing an initial draft, the codebook was modified through the iterative analysis of 9 written articles (2 hydroxychloroquine, 2 remdesivir, and 5 CP) from different news sources with different word lengths. The draft codebook was then reviewed by a multidisciplinary team of experts in media analysis, bioethics, and health communication. Independent review of 50 reports by 2 coders (SW and TJB) showed good interrater reliability in coding for the full news report for theme and portrayal of scientific evidence. The median Cohen κ for these elements was 0.71 (IQR 0.58-0.74) with simple agreement ranging from 79% to 94%. Interrater reliability was initially poor when identifying sources of authority, with a median κ of 0.17 (IQR 0.06-0.23). Definitions were clarified to address omissions or ambiguities identified during this intercoder check. For example, evidence was defined as a formal demonstration of the effect of a treatment on the COVID-19 disease course, which includes symptoms, outcomes, side effects, or a lack thereof. In the same way, sample size or study design was added as an example of evidence details and a statement of small sample size or nonrandomized design was included in the codebook as an example of evidence limitations. Codes regarding sources of authority were modified to clarify that a subject matter expert who spoke on behalf of a government agency should not be coded as an “expert” but should be coded as a “government” source of authority. Due to poor initial reliability, modified definitions for sources of authority were formally retested by the same 2 coders on a new sample of 20 articles. Sources of authority showed good interrater reliability with a median κ of 0.73 (IQR 0.48-0.86) with simple agreement ranging from 91% to 100%. The general structure of the codebook captures metadata provided by the Factiva database (eg, word count and hyperlink), headline analysis, report analysis, scientific description, sources of authority, social context, qualitative description of video reports, and coder notes (see Multimedia Appendix 2 for final codebook with complete definitions of codes and examples).

    Analysis

    The full text or video (body of news reports) of all discussions was analyzed for theme, scientific evidence, claims of safety or efficacy, and sources of authority. All terms are defined in the tables. The topical themes of news reports were identified inductively during iterative analysis of 9 articles as described above. An inductive approach permits the emergence of themes from the data and allows coders to remain open and exploratory [82]. This qualitative method is ideal for identifying themes when there is no prior knowledge about them [38,83,84]. In cases where more than 1 theme was reflected in the entire news report, the coder selected the theme that most closely resembled the news report. For text-based reports that discussed scientific evidence, details of evidence, or limitations of evidence, we also analyzed the presence of these codes within headlines and lead paragraphs. The lead paragraph was defined as the first paragraph of text with a minimum of 2 complete sentences excluding subtitles or alternate headlines just below the large print title. Coders independently analyzed approximately half the reports and jointly reviewed challenging reports and a random 10% of all reports as preplanned audits. Disagreements were resolved by consensus. Study data were recorded and managed using REDCap (Research Electronic Data Capture).

    Different traits of reports (eg, discussion of evidence and discussion of specific side effects) were summarized for each therapeutic using descriptive statistics. Fisher exact tests were used to compare differences in trait frequencies. If 3×2 Fisher tests returned a P value of <.05, pairwise comparisons between therapeutics (ie, hydroxychloroquine - remdesivir, hydroxychloroquine-CP, and remdesivir-CP) were performed. No corrections were made for multiple comparisons. Analyses were performed in Excel (Microsoft Corp) and R (version 3.5.1; R Core Team).

    Ethical Considerations

    This research study did not involve human subjects and was conducted using publicly available information; thus, ethics approval was not sought.


    The data set included 479 individual discussions of hydroxychloroquine, remdesivir, and CP or a combination of any of the 3 unproven therapeutics among 449 news reports. Among 449 news reports, 191 were print, 172 were online, 52 were television transcripts, and 34 were online videos. Print news reports describe those accessed nonelectronically via PDF files from the Factiva database while online news reports and online videos were accessed by coders digitally via specific website links. News reports mostly discussed hydroxychloroquine (67%, n=299) compared to remdesivir (27%, n=122) and CP (13%, n=58). Safety or efficacy was the main theme among news on hydroxychloroquine (61%, n=182) and remdesivir (47%, n=57), whereas news reports discussing CP focused on the theme of economics, distribution, and allocation (40%, n=23). Many reports discussing hydroxychloroquine often surrounded the theme of politics (20%, n=61; Table 1).

    Scientific evidence was discussed in 67% (n=322) of new discussions and was most common among discussions of hydroxychloroquine (78%, n=233) followed by remdesivir (63%, n=77) and CP (21%, n=12). All pairwise comparisons (P<.05; hydroxychloroquine-remdesivir P=.002; hydroxychloroquine-CP P<.001; remdesivir-CP P<.001; Table 2). Although scientific evidence was found in many news reports, specific publications or journals were seldom mentioned (24%, n=116). Details of scientific evidence and discussions on the limitations of evidence were found in 61% (n=198) and 26% (n=125) of news, respectively.

    Among text-based news reports discussing scientific evidence, 22% (n=51) discussed scientific evidence in the headline and 51% (n=118) in the lead paragraph (Table 3). However, the details of scientific evidence were rarely found in headlines (6%, n=9) and seldom present in lead paragraphs (26%, n=39; P<.001). Among the 99 text-based reports that included limitations of evidence, discussions on limitations were rarely found in headlines (2%, n=2) and lead paragraphs (9%, n=9).

    Very few discussions portrayed any therapeutic as safe, but 75% (n=91) of news discussions on remdesivir and 66% (n=38) of news discussions on CP were portrayed as efficacious. Only 14% (n=41) of news discussions on hydroxychloroquine portrayed the therapeutic as efficacious, and safety warnings or specific negative side effects were mainly identified in discussions on hydroxychloroquine (56%, n=168) compared to other therapeutics (Table 2). For hydroxychloroquine, most claims about safety and efficacy were offered by prominent persons (79%, n=236), almost exclusively by former US President Trump (97%, n=230). Other examples of prominent persons included Jair Bolsonaro (former president of Brazil) and Nancy Pelosi (US politician). In contrast, the government (35%, n=43) was the most frequently named source of authority for safety and efficacy claims of news on remdesivir while experts mostly made claims on CP (38%, n=22; Table 4).

    Table 1. Thematic analysis of news reports.

    		Hydroxychloroquine, n (%)Remdesivir, n (%)CPa, n (%)
    Novel scientific discovery: a novel result regarding the intervention. Does not include novel results on safety or efficacy0 (0)0 (0)0 (0)
    Safety or efficacy: discussions about ongoing trials, study logistics, and expected results of the intervention182 (61)57 (47)19 (33)
    Issue of scientific integrity: misconduct by individual scientists or scientific community, including research methods, peer review, and publication or dissemination decisions16 (5)0 (0)1 (2)
    Misinformation: analysis of the veracity of claims or reports of fact-checking18 (6)2 (2)0 (0)
    Politics: reports on political figures’ claims, actions, and behaviors61 (20)3 (2)0 (0)
    Hope: feelings of optimism in context of society0 (0)2 (2)0 (0)
    Official recommendation: a statement made by a national or international government agency or governing body3 (1)0 (0)0 (0)
    Economics, distribution, and allocation: discussions of cost, quantity, supplies, or delivery of the intervention12 (4)50 (41)23 (40)
    Human interest story: individual narratives and excluding political figures5 (2)6 (5)15 (26)
    Other2 (1)2 (2)0 (0)
    Totalb299 (67)122 (27)58 (13)

    aCP: convalescent plasma.

    bThe final data set included 479 individual discussions of therapeutics in 449 news reports.

    Table 2. Portrayal of scientific evidence among news report discussions.

    		Hydroxychloroquine, n (%)Remdesivir, n (%)CPa, n (%)Total, n (%)
    Scientific evidenceb: a demonstration of an effect on the disease course or resultant side effects from the intervention.233 (78)77 (63)12 (21)322 (67)
    Details of scientific evidencec: specific details about the design or methodology of evidence.152 (65)40 (52)6 (50)198 (61)
    Limitations of evidence: aspects of evidence or a study presented as shortcomings.104 (35)12 (10)9 (16)125 (26)
    Publication or journalb: identifying a specific publication or journal named.102 (34)11 (9)3 (5)116 (24)
    Portrayed as safe: portrayed therapeutic as safe using keywords, for example, safe or discussing minimal risks or side effects.41 (14)6 (5)8 (14)55 (11)
    Portrayed as efficaciousb: portrayed therapeutic as efficacious by using keywords, for example, effective and helpful.41 (14)91 (75)38 (66)170 (35)
    Safety warnings or side effectsb: discusses specific health or safety risks, for example, death.168 (56)1 (0.8)1 (2)170 (35)

    aCP: convalescent plasma.

    bStatistically significant result for 3×2 Fisher exact test; P<.001.

    cEvidence details were analyzed only if the report included evidence; n=322.

    Table 3. Scientific evidence, details, and limitations in headline or lead paragraphsa.

    		Hydroxychloroquine, n (%)Remdesivir, n (%)CPb, n (%)Total, n (%)
    Scientific evidence in headlinec, n (%)42 (24)8 (13)5 (42)51 (22)
    Scientific evidence in lead paragraphc, n (%)92 (53)26 (43)8 (67)118 (51)
    Total reports with scientific evidence in headline or lead paragraph, n1736112233
    Details of scientific evidence in headlinec, n (%)8 (7)1 (3)0 (0)9 (6)
    Details of scientific evidence in lead paragraphc, n (%)28 (25)10 (30)1 (25)39 (26)
    Total reports with details of scientific evidence in headline or lead paragraph, n113334150
    Limitations of evidence in headlinec, n (%)2 (3)0 (0)0 (0)2 (2)
    Limitations of evidence in lead paragraphc, n (%)5 (6)3 (25)1 (11)9 (9)
    Total reports with limitations of evidence in headline or lead paragraph, n7812999

    aThe following definitions were used. Scientific evidence: a demonstration of an effect on the disease course or resultant side effects from the intervention. Details of scientific evidence: specific details about the design or methodology of evidence. Limitations of evidence: aspects of evidence or a study presented as shortcomings.

    bCP: convalescent plasma.

    cA single news report was included in the analysis of more than 1 therapeutic when the report discussed multiple therapeutics.

    Table 4. Sources of authority among news report discussions.

    		Hydroxychloroquine, n (%)Remdesivir, n (%)CPa, n (%)Total, n (%)
    Prominent personb: a nonmedical, nonscientist person such as celebrities and politicians236 (79)9 (7)1 (2)246 (51)
    Institution: an academic institution, medical center, or hospital22 (7)9 (7)9 (16)40 (8)
    Expertb: a trained professional such as clinician, scientist, or clinician-researcher speaking independently of an institutional affiliation146 (49)31 (25)22 (38)199 (41)
    Governmentb: a federal or state government organization such as the Centers for Disease Control and Prevention, Food and Drug Administration and World Health Organization180 (60)43 (35)12 (21)235 (49)

    aCP: convalescent plasma.

    bStatistically significant result for 3×2 Fisher exact test; P<.001.


    Principal Findings

    As reports spread of a novel coronavirus causing unprecedented hospitalizations and mortality, both medical specialists and everyday persons anxiously scrambled to learn as much and as fast as possible about prevention and potential treatments. Our analysis revealed that much coverage of the off-label use of hydroxychloroquine centered on politics and the safety and efficacy of the product. The politics theme dominated discourse surrounding hydroxychloroquine due to its endorsement by former President Trump as seen in other news media analyses [58,85]. During the months of March and April 2020, former President Donald Trump put forth hydroxychloroquine as a “game changer” after a study suggested efficacy in vitro. Propagation of statements surrounding the safety and efficacy of hydroxychloroquine had far-reaching effects, including increased sales by hospitals and the death of persons who took a similar product as prophylaxis [86]. While safety or efficacy discussions were also found in remdesivir and CP, limited knowledge of its antiviral properties may have played a significant role in shaping public discourse on the potential safety and efficacy of the drug. Conversations about CP instead focused on the human interest theme explicating the need for plasma donors and inspiring potential COVID-19 survivors to donate.

    The results showed substantial heterogeneity in the sources of authority asserting claims of safety or efficacy of the COVID-19 therapeutics among the 449 reports. On many occasions, scientific claims of the safety and efficacy of a therapeutic were portrayed by prominent persons and were compared to the evidence discussed by experts. Contrary opinions on evidence of hydroxychloroquine delivered by politicians and experts may have inadvertently contributed to a false sense of scientific disagreement as news reports most frequently reported on claims made by a single prominent person but also mentioned the lack of scientific evidence supporting such claims. Presenting directly opposing viewpoints as equal when evidence or a scientific consensus is actually weighted is referred to as a false balance that can cause public uncertainty [87]. False-balance has been shown to distort public perceptions of consensus among experts resulting in people identifying greater disagreement and controversy than what is actually present [50]. Making such comparisons is problematic because nonscientific experts may interpret data toward a political advantage and their influence could have troubling downstream consequences when disseminated, for example, physicians prescribing unproven products and reduced intentions to adopt health behaviors [88-90]. Though the majority of news reports on hydroxychloroquine published the safety or efficacy claims made by prominent persons, very few reports actually portrayed hydroxychloroquine as efficacious, and safety warnings or specific side effects were frequently included.

    While we found scientific evidence of therapeutics was portrayed in the body of news reports, mostly on hydroxychloroquine, limitations of evidence outlining scientific uncertainty were seldom seen, and rarely found in prominent locations (headlines and lead paragraphs) of news reports. With only about 40% of the public delving past headlines or lead paragraphs when reading articles [3,91], it is unlikely readers would grasp the scientific uncertainty associated with an unproven therapeutic. The dissemination of evolving science without expressing scientific uncertainty and the knowledge gap created by the iterative scientific process may have indirectly resulted in public confusion and minimized how large of a threat individuals believed the virus posed [92,93]. This confusion and doubt permitted some actors to promote disinformation surrounding the safety and efficacy of unproven therapeutics [8,21]. Journalists may be reluctant to express uncertainty of evidence in their reports out of fear their audience may react negatively toward such ambiguity [94] or the journalist may not be equipped to address a study’s findings, especially its limitations. Scientists on the other hand are reportedly reluctant to express uncertainty fearing reporters may lose interest and that the public might misinterpret the science or doubt scientists [95,96]. However, empirical studies have shown that neither conveying uncertainty nor presenting scientific limitations affect a person’s understanding of a topic, beliefs, or trust in science [97-99]. This data, along with our findings, suggest that uncertainty should be explained more frequently in news reports and placed in headlines and lead paragraphs to adequately support the public’s understanding of scientific evidence and uncertainty [30,87]. Further research comparing scientific evidence and expressions of uncertainty between the body of news reports versus headlines and lead paragraphs on different scientific topics is needed. Research examining key factors influencing journalists’ and news editors’ decision-making process regarding news headlines and lead paragraphs is important to inform updated journalistic guidelines and editorial policies aimed at reducing false balance. Research collaboration between journalists, scientists, and communication researchers to identify effective communication strategies and journalistic practices to ensure accurate and nuanced representation of scientific information in news reporting would be valuable.

    The accurate reporting of scientific evidence and uncertainty is the collective responsibility of multiple professionals including reporters, editors, public health officials, and medical and scientific experts. While evidence from experts may be based on scientific facts, expert correspondents should make clear scientific uncertainty, avoid hyperbolic statements, and explain how the state of knowledge may change [22]. Medical doctors and scientists should not express unjustified certainty when forecasting the safety and efficacy of unproven therapeutics [100]. Despite the lack of consensus, reporters should offer greater context or altogether avoid framing unsubstantiated claims by prominent people alongside evidence-based claims from experts as it may provide a false impression of genuine scientific uncertainty. Editors should refrain from sensationalizing headlines or framing lead paragraphs that do not reflect evidence or study limitations. Instead, journalists and experts alike should focus on the accurate portrayal of the scientific studies presented in the report and aim to provide an accurate reflection of the safety and efficacy of unproven products to help the public understand why there is incomplete evidence and a lack of definitive recommendations. Prioritizing the accurate portrayal of science may help to rebuild public trust in experts, minimize risky behaviors, and ensure compliance with public health recommendations.

    Limitations

    Our study has several limitations worth mentioning. First, the analysis included only news sources within the United States, all of which were written in English and thus may not cater to news outside of the country and written in different languages. Second, the analysis focused on traditional, mainstream news sources and we excluded social media. Although much COVID-19 information and misinformation were disseminated through social media contributing to an infodemic, traditional news remains the major form of information transfer, especially among older Americans, which is why we focused on evaluating traditional news sources [101]. Third, we chose to analyze approximately half the news reports in our population and the sample may not be representative of the entire news discourse within the full data set. Fourth, the data collection and analysis was restricted to the 3 most popular unproven COVID-19 therapeutics and other therapeutics during that period may be portrayed differently in US news. Finally, the results were not stratified based on different political leaning of news sources included in our analysis, which could affect how scientific evidence and uncertainty were portrayed in our data set.

    Conclusions

    News media plays a significant role in informing the public by serving as a crucial link between public health authorities interpreting scientific evidence and determining its implications and the public. Rapid publication of peer-reviewed and nonreviewed science allowed the media to bring breaking news about discoveries of COVID-19 therapeutics to the public and convey public health recommendations [18]. Prioritizing the accurate portrayal of science can help shape the impact of a public health emergency by influencing public perceptions and activities such as minimizing risky behaviors and encouraging compliance with public health recommendations. Publicizing that the news media source is likely to share frequent updates from scientific findings and communicating information as the best-known information at the time may help build public trust in scientific experts and decrease feelings of doubt and anxiety. The accurate reporting of scientific evidence and uncertainty is the collective responsibility of journalists and science communicators. Public trust in science can be strengthened by acknowledging evidentiary limitations, avoiding a false sense of disagreement, and portraying science as an iterative, self-corrective process that generates reliable knowledge.

    Acknowledgments

    The authors would like to thank Dr Christen Rachul, Dr Karen Meagher, and Jordan Richardson for input on the original codebook. The authors would like to thank the anonymous reviewers for helpful feedback on the manuscript. Funding support for this paper was provided by the National Center for Advancing Translational Sciences (UL1TR002377), National Institutes of Health, US Department of Health and Human Services or United States.

    Conflicts of Interest

    XZ offers scientific input to research studies through a contracted services agreement between Mayo Clinic and Exact Sciences. The other authors declare no conflicts of interest.

    Multimedia Appendix 1

    Methods.

    DOCX File , 107 KB
    Multimedia Appendix 2

    Codebook.

    DOCX File , 33 KB
    1. Tukachinsky Forster R, Vendemia MA. Effects of news and threat perceptions on Americans’ COVID-19 precautionary behaviors. Commun Rep. 2021;34(2):65-77. [CrossRef]
    2. La Bella E, Allen C, Lirussi F. Communication vs evidence: what hinders the outreach of science during an infodemic? A narrative review. Integr Med Res. 2021;10(4):100731. [FREE Full text] [CrossRef] [Medline]
    3. How Americans get their news. American Press Institute. 2014. URL: https://americanpressinstitute.org/how-americans-get-news/ [accessed 2024-08-03]
    4. Ali SH, Foreman J, Tozan Y, Capasso A, Jones AM, DiClemente RJ. Trends and predictors of COVID-19 information sources and their relationship with knowledge and beliefs related to the pandemic: nationwide cross-sectional study. JMIR Public Health Surveill. 2020;6(4):e21071. [FREE Full text] [CrossRef] [Medline]
    5. Ballew M, Bergquist P, Goldberg M, Gustafson A, Kotcher J, Marlon J, et al. American Public Responses to COVID-19. New Haven. Yale University and George Mason University; 2020.
    6. What Americans Think of the News? and What that Means for Democracy. Santa Monica, California. Rand Corporation; 2020.
    7. Erikainen S, Stewart E. Credibility contests: media debates on do-it-yourself coronavirus responses and the role of citizens in health crises. Front Sociol. 2020;5:592666. [FREE Full text] [CrossRef] [Medline]
    8. Hall Jamieson K, Albarracín D. The relation between media consumption and misinformation at the outset of the SARS-CoV-2 pandemic in the US. HKS Misinfo Review. 2020;1(2). [CrossRef]
    9. Motta M, Stecula D, Farhart C. How right-leaning media coverage of COVID-19 facilitated the spread of misinformation in the early stages of the pandemic in the U.S. Can J Pol Sci. 2020;53(2):335-342. [CrossRef]
    10. Enders AM, Uscinski JE, Klofstad C, Stoler J. The different forms of COVID-19 misinformation and their consequences. HKS Misinfo Review. 2020;1(8). [CrossRef]
    11. Al-Zaman M. Prevalence and source analysis of COVID-19 misinformation in 138 countries. IFLA J. 2021;48(1):189-204. [FREE Full text] [CrossRef]
    12. Loomba S, de Figueiredo A, Piatek SJ, de Graaf K, Larson HJ. Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA. Nat Hum Behav. 2021;5(3):337-348. [CrossRef] [Medline]
    13. Van Scoy LJ, Miller EL, Snyder B, Wasserman E, Chinchilli VM, Zgierska AE, et al. Knowledge, perceptions, and preferred information sources related to COVID-19 among Central Pennsylvania adults early in the pandemic: a mixed methods cross-sectional survey. Ann Fam Med. 2021;19(4):293-301. [FREE Full text] [CrossRef] [Medline]
    14. Van Scoy LJ, Snyder B, Miller EL, Toyobo O, Grewel A, Ha G, et al. Public anxiety and distrust due to perceived politicization and media sensationalism during early COVID-19 media messaging. J Commun Healthc. 2021;14(3):193-205. [CrossRef]
    15. Freeman D, Waite F, Rosebrock L, Petit A, Causier C, East A, et al. Coronavirus conspiracy beliefs, mistrust, and compliance with government guidelines in England. Psychol Med. 2022;52(2):251-263. [FREE Full text] [CrossRef] [Medline]
    16. Price D, Bonsaksen T, Ruffolo M, Leung J, Chiu V, Thygesen H, et al. Perceived trust in public authorities nine months after the COVID-19 outbreak: a cross-national study. Soc Sci. 2021;10(9):349. [CrossRef]
    17. The public's perspective on the United States public health system. Robert Wood Johnson Foundation. 2021. URL: https:/​/www.​hsph.harvard.edu/​wp-content/​uploads/​sites/​94/​2021/​05/​RWJF-Harvard-Report_FINAL-051321.​pdf [accessed 2024-08-06]
    18. Caulfield T, Bubela T, Kimmelman J, Ravitsky V. Let’s do better: public representations of COVID-19 science. FACETS. 2021;6(1):403-423. [CrossRef]
    19. Bagdasarian N, Cross GB, Fisher D. Rapid publications risk the integrity of science in the era of COVID-19. BMC Med. 2020;18(1):192. [FREE Full text] [CrossRef] [Medline]
    20. Managing the COVID-19 infodemic: promoting healthy behaviours and mitigating the harm from misinformation and disinformation. World Health Organization. 2020. URL: https:/​/www.​who.int/​news/​item/​23-09-2020-managing-the-covid-19-infodemic-promoting-healthy-behaviours-and-mitigating-the-harm-from-misinformation-and-disinformation [accessed 2024-08-06]
    21. The Lancet Infectious Diseases. The COVID-19 infodemic. Lancet Infect Dis. 2020;20(8):875. [FREE Full text] [CrossRef] [Medline]
    22. Saitz R, Schwitzer G. Communicating science in the time of a pandemic. JAMA. 2020;324(5):443-444. [CrossRef] [Medline]
    23. Jensen J. Scientific uncertainty in news coverage of cancer research: effects of hedging on scientists' and journalists' credibility. Hum Commun Res. 2008;34(3):347-369.
    24. Ratcliff C, Wicke R. How the public evaluates media representations of uncertain science: an integrated explanatory framework. Public Underst Sci. 2023;32(4):410-427. [CrossRef] [Medline]
    25. Akin H, Scheufele D. Overview of the science of science communication. In: Jamieson KH, Kahan DM, Scheufele DA, editors. The Oxford Handbook of the Science of Science Communication. New York. Oxford University Press; 2017:25-33.
    26. Kappel K, Holmen SJ. Why science communication, and does it work? A taxonomy of science communication aims and a survey of the empirical evidence. Front Commun. 2019;4. [CrossRef]
    27. Schmid-Petri H, Bürger M. Modeling science communication: from linear to more complex models. In: Leßmöllmann A, Dascal M, Gloning T, editors. Science Communication. Berlin, Boston. De Gruyter Mouton; 2020:105-122.
    28. Brossard D, Lewenstein BV. A critical appraisal of models of public understanding of science: using practice to inform theory. In: Kahlor L, Stout PA, editors. Communicating Science New Agendas in Communication. New York, New York. Routledge; 2010:11-39.
    29. Trench B. Towards an analytical framework of science communication models. In: Cheng D, Claessens M, Gascoigne T, Metcalfe J, Schiele B, Shi S, editors. Communicating Science in Social Contexts: New Models, New Practices. Netherlands. Springer, Dordrecht; 2008:119-135.
    30. Nisbet M, Fahy D. New models of knowledge-based journalism. In: Jamieson KH, Kahan DM, Scheufele DA, editors. The Oxford Handbook of the Science of Science Communication. Oxford. Oxford University Press; 2017:273-281.
    31. Schäfer MS. How changing media structures are affecting science news coverage. In: Jamieson KH, Kahan DM, Scheufele DA, editors. The Oxford Handbook of the Science of Science Communication. Oxford. Oxford University Press; 2017:50-59.
    32. Secko DM, Amend E, Friday T. Four models of science journalism. Journal Pract. 2013;7(1):62-80. [CrossRef]
    33. Amend E, Capurro G, Secko DM. Grasping scientific news. Journal Pract. 2014;8(6):789-808. [CrossRef]
    34. Bubela T, Nisbet MC, Borchelt R, Brunger F, Critchley C, Einsiedel E, et al. Science communication reconsidered. Nat Biotechnol. 2009;27(6):514-518. [CrossRef] [Medline]
    35. Caulfield T. Biotechnology and the popular press: hype and the selling of science. Trends Biotechnol. 2004;22(7):337-339. [CrossRef] [Medline]
    36. Mountcastle-Shah E, Tambor E, Bernhardt B, Geller G, Karaliukas R, Rodgers J, et al. Assessing mass media reporting of disease-related genetic discoveries. Sci Commun. 2016;24(4):458-478. [CrossRef]
    37. Cook DM, Boyd EA, Grossmann C, Bero LA. Reporting science and conflicts of interest in the lay press. PLoS One. 2007;2(12):e1266. [FREE Full text] [CrossRef] [Medline]
    38. Kamenova K, Caulfield T. Stem cell hype: media portrayal of therapy translation. Sci Transl Med. 2015;7(278):278ps4. [CrossRef] [Medline]
    39. Holtzman NA, Bernhardt BA, Mountcastle-Shah E, Rodgers JE, Tambor E, Geller G. The quality of media reports on discoveries related to human genetic diseases. Community Genet. 2005;8(3):133-144. [CrossRef] [Medline]
    40. Bubela TM, Caulfield TA. Do the print media "hype" genetic research? A comparison of newspaper stories and peer-reviewed research papers. CMAJ. 2004;170(9):1399-1407. [FREE Full text] [CrossRef] [Medline]
    41. Claassen L, Smid T, Woudenberg F, Timmermans DRM. Media coverage on electromagnetic fields and health: content analysis of Dutch newspaper articles and websites. Health Risk Soc. 2012;14(7-8):681-696. [CrossRef]
    42. Moynihan R, Bero L, Ross-Degnan D, Henry D, Lee K, Watkins J, et al. Coverage by the news media of the benefits and risks of medications. N Engl J Med. 2000;342(22):1645-1650. [CrossRef] [Medline]
    43. MacKenzie R, Chapman S, Barratt A, Holding S. "The news is [not] all good": misrepresentations and inaccuracies in Australian news media reports on prostate cancer screening. Med J Aust. 2007;187(9):507-510. [CrossRef] [Medline]
    44. Heidmann I, Milde J. Communication about scientific uncertainty: how scientists and science journalists deal with uncertainties in nanoparticle research. Environ Sci Eur. 2013;25(1):25. [CrossRef]
    45. Brechman J, Lee C, Cappella JN. Lost in translation? A comparison of cancer-genetics reporting in the press release and its subsequent coverage in lay press. Sci Commun. 2009;30(4):453-474. [FREE Full text] [CrossRef] [Medline]
    46. Kuriya B, Schneid EC, Bell CM. Quality of pharmaceutical industry press releases based on original research. PLoS One. 2008;3(7):e2828. [FREE Full text] [CrossRef] [Medline]
    47. Olausson U. Global warming—global responsibility? Media frames of collective action and scientific certainty. Public Underst Sci. 2009;18(4):421-436. [CrossRef]
    48. Zehr SC. Public representations of scientific uncertainty about global climate change. Public Underst Sci. 2016;9(2):85-103.
    49. Boykoff M, Boykoff J. Balance as bias: global warming and the US prestige press. Global Environ Change. 2004;14(2):125-136. [FREE Full text] [CrossRef]
    50. Koehler DJ. Can journalistic "false balance" distort public perception of consensus in expert opinion? J Exp Psychol Appl. 2016;22(1):24-38. [CrossRef] [Medline]
    51. Gabielkov M, Ramachandran A, Chaintreau A, Legout A. Social Clicks: what and who gets read on Twitter? ACM SIGMETRICS Perform Eval Rev. 2016;44(1):179-192. [CrossRef]
    52. Janét K, Richards O, Landrum AR. Headline format influences evaluation of, but not engagement with, environmental news. J Pract. 2020;16(1):35-55. [CrossRef]
    53. Asch SE. Forming impressions of personality. J Abnorm Psychol. 1946;41:258-290. [CrossRef] [Medline]
    54. Haugtvedt CP, Wegener DT. Message order effects in persuasion: an attitude strength perspective. J Consum Res. 1994;21(1):205-218.
    55. Larson HJ. The biggest pandemic risk? Viral misinformation. Nature. 2018;562(7727):309. [CrossRef] [Medline]
    56. Suarez-Lledo V, Alvarez-Galvez J. Prevalence of health misinformation on social media: systematic review. J Med Internet Res. 2021;23(1):e17187. [FREE Full text] [CrossRef] [Medline]
    57. Al Khaja KAJ, AlKhaja AK, Sequeira RP. Drug information, misinformation, and disinformation on social media: a content analysis study. J Public Health Policy. 2018;39(3):343-357. [CrossRef] [Medline]
    58. Mohammadi E, Tahamtan I, Mansourian Y, Overton H. Identifying frames of the COVID-19 infodemic: thematic analysis of misinformation stories across media. JMIR Infodemiology. 2022;2(1):e33827. [FREE Full text] [CrossRef] [Medline]
    59. Walter N, Cohen J, Holbert R, Morag Y. Fact-checking: a meta-analysis of what works and for whom. Polit Commun. 2019;37(3):350-375. [CrossRef]
    60. Porter E, Wood TJ. The global effectiveness of fact-checking: evidence from simultaneous experiments in Argentina, Nigeria, South Africa, and the United Kingdom. Proc Natl Acad Sci U S A. 2021;118(37):e2104235118. [FREE Full text] [CrossRef] [Medline]
    61. Chan MS, Jones CR, Hall Jamieson K, Albarracín D. Debunking: a meta-analysis of the psychological efficacy of messages countering misinformation. Psychol Sci. 2017;28(11):1531-1546. [FREE Full text] [CrossRef] [Medline]
    62. Walter N, Murphy S. How to unring the bell: a meta-analytic approach to correction of misinformation. Commun Monogr. 2018;85(3):423-441. [CrossRef]
    63. Ecker UKH, Lewandowsky S, Cook J, Schmid P, Fazio LK, Brashier N, et al. The psychological drivers of misinformation belief and its resistance to correction. Nat Rev Psychol. 2022;1(1):13-29. [CrossRef]
    64. Marietta M, Barker D, Bowser T. Fact-checking polarized politics: does the fact-check industry provide consistent guidance on disputed realities? The Forum. 2015;13(4):577-596. [FREE Full text]
    65. Lee S, Xiong A, Seo H, Lee D. “Fact-checking” fact checkers: a data-driven approach. Harvard Kennedy School Misinformation Review. 2023. URL: https://doi.org/10.37016/mr-2020-126 [accessed 2024-08-06]
    66. Nieminen S, Rapeli L. Fighting misperceptions and doubting journalists' objectivity: a review of fact-checking literature. Polit Stud Rev. 2018;17(3):296-309. [CrossRef]
    67. Uscinski JE, Butler RW. The epistemology of fact checking. Crit Rev. 2013;25(2):162-180. [CrossRef]
    68. Salasc F, Lahlali T, Laurent E, Rosa-Calatrava M, Pizzorno A. Treatments for COVID-19: lessons from 2020 and new therapeutic options. Curr Opin Pharmacol. 2022;62:43-59. [FREE Full text] [CrossRef] [Medline]
    69. Johal R. Factiva: gateway to business information. J Bus Finance Librarianship. 2009;15(1):60-64. [CrossRef]
    70. Top 100 USA news websites. FeedSpot. URL: https://blog.feedspot.com/ [accessed 2024-08-03]
    71. Top 10 U.S. newspapers by circulation. Agility PR Solutions. URL: https://www.agilitypr.com/resources/top-media-outlets/top-10-daily-american-newspapers/ [accessed 2021-07-01]
    72. Leading daily newspapers in the United States in September 2017 and January 2019, by circulation. Statista. URL: https://www.statista.com/statistics/184682/us-daily-newspapers-by-circulation/ [accessed 2024-08-03]
    73. Holshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, Bruce H, et al. Washington State 2019-nCoV Case Investigation Team. First case of 2019 novel coronavirus in the United States. N Engl J Med. 2020;382(10):929-936. [FREE Full text] [CrossRef] [Medline]
    74. Coronavirus disease (COVID-19): solidarity trial and hydroxychloroquine. WHO. 2020. URL: https:/​/www.​who.int/​news-room/​questions-and-answers/​item/​coronavirus-disease-covid-19-hydroxychloroquine [accessed 2024-08-03]
    75. RECOVERY Collaborative Group. Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial. Lancet. 2021;397(10289):2049-2059. [FREE Full text] [CrossRef] [Medline]
    76. Beaubien J. WHO halts hydroxychloroquine trial over safety concerns. NPR. 2020. URL: https:/​/www.​npr.org/​sections/​coronavirus-live-updates/​2020/​05/​25/​861913688/​who-halts-hydroxychloroquine-trial-over-safety-concerns [accessed 2024-08-03]
    77. NIH halts clinical trial of hydroxychloroquine. National Institutes of Health. Bethesda, Maryland, U.S. National Institutes of Health; Jun 20, 2020. URL: https://www.nih.gov/news-events/news-releases/nih-halts-clinical-trial-hydroxychloroquine [accessed 2024-08-02]
    78. No clinical benefit from use of hydroxychloroquine in hospitalised patients with COVID-19. Randomised Evaluation of COVid-19 thERapY (RECOVERY). Headington, Oxford OX3 7LF, United Kingdom. Nuffield Department of Population Health; Jun 05, 2020. URL: https://tinyurl.com/2rm4d2jr [accessed 2024-08-01]
    79. Coronavirus (COVID-19) update: FDA revokes emergency use authorization for chloroquine and hydroxychloroquine. U.S. Food and Drug Administration. U.S. Food and Drug Administration; 2020. URL: https://tinyurl.com/26ckkvtj [accessed 2024-08-06]
    80. Coronavirus (COVID-19) update: FDA coordinates national effort to develop blood-related therapies for COVID-19. U.S. Food and Drug Administration. 2020. URL: https://tinyurl.com/4sypwp72 [accessed 2024-08-06]
    81. Coronavirus (COVID-19) update: FDA issues emergency use authorization for potential COVID-19 treatment. U.S. Food and Drug Administration. 2020. URL: https://tinyurl.com/5yp6bvts [accessed 2024-08-06]
    82. Fereday J, Muir-Cochrane E. Demonstrating rigor using thematic analysis: a hybrid approach of inductive and deductive coding and theme development. Int J Qual Methods. 2016;5(1):80-92. [CrossRef]
    83. Marcon A, Master Z, Ravitsky V, Caulfield T. CRISPR in the North American popular press. Genet Med. 2019;21(10):2184-2189. [FREE Full text] [CrossRef] [Medline]
    84. Marcon AR, Bieber M, Caulfield T. Representing a "revolution": how the popular press has portrayed personalized medicine. Genet Med. 2018;20(9):950-956. [FREE Full text] [CrossRef] [Medline]
    85. Evanega S, Lynas M, Adams J, Smolenyak K. Coronavirus misinformation: quantifying sources and themes in the COVID-19 'infodemic'. URL: http:/​/allianceforscience.​cornell.edu/​wp-content/​uploads/​2020/​10/​Evanega-et-al-Coronavirus-misinformation-submitted_07_23_20-1.​pdf [accessed 2024-08-03]
    86. Miller B. Arizona man dies after ingesting fish tank cleaner to prevent coronavirus infection. URL: https:/​/www.​fox10phoenix.com/​news/​arizona-man-dies-after-ingesting-fish-tank-cleaner-to-prevent-coronavirus-infection [accessed 2020-03-23]
    87. Dixon GN, Clarke CE. Heightening uncertainty around certain science: media coverage, false balance, and the autism-vaccine controversy. Sci Commun. 2012;35(3):358-382. [CrossRef]
    88. Barnett ML, Gaye M, Jena AB, Mehrotra A. Association of county-level prescriptions for hydroxychloroquine and ivermectin with county-level political voting patterns in the 2020 US presidential election. JAMA Intern Med. 2022;182(4):452-454. [FREE Full text] [CrossRef] [Medline]
    89. Dixon G, Clarke C. The effect of falsely balanced reporting of the autism-vaccine controversy on vaccine safety perceptions and behavioral intentions. Health Educ Res. 2013;28(2):352-359. [CrossRef] [Medline]
    90. Chung M, Jones-Jang SM. Red media, blue media, Trump briefings, and COVID-19: examining how information sources predict risk preventive behaviors via threat and efficacy. Health Commun. 2022;37(14):1707-1714. [CrossRef] [Medline]
    91. Lagun D, Lalmas M. Understanding user attention and engagement in online news reading. 2016. Presented at: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining; 2016 February 08; New York, NY, United States.
    92. Aven T, Bouder F. The COVID-19 pandemic: how can risk science help? J Risk Res. 2020;23(7-8):849-854. [CrossRef]
    93. Kalaichandran A. Uncertainty in a Time of Coronavirus. New York, NY. Scientific American Magazine; 2020.
    94. LaFountain C. Health risk reporting. Society. 2004;42(1):49-56. [CrossRef]
    95. Post S, Maier M. Stakeholders' rationales for representing uncertainties of biotechnological research. Public Underst Sci. 2016;25(8):944-960. [CrossRef] [Medline]
    96. Maier M, Milde J, Post S, Günther L, Ruhrmann G, Barkela B. Communicating scientific evidence: scientists', journalists' and audiences' expectations and evaluations regarding the representation of scientific uncertainty. Communications. 2016;41(3).
    97. Hendriks F, Jucks R. Does scientific uncertainty in news articles affect readers' trust and decision-making? Media Commun. 2020;8(2):401-412.
    98. Gustafson A, Rice RE. A review of the effects of uncertainty in public science communication. Public Underst Sci. 2020;29(6):614-633. [CrossRef] [Medline]
    99. Retzbach A, Maier M. Communicating scientific uncertainty: media effects on public engagement with science. Commun Res. 2014;42(3):429-456. [CrossRef]
    100. Ho A, Huang V. Unmasking the ethics of public health messaging in a pandemic. J Bioeth Inq. 2021;18(4):549-559. [FREE Full text] [CrossRef] [Medline]
    101. Forman-Katz N, Matsa K. News platform fact sheet. Pew Research Center. URL: https://www.pewresearch.org/journalism/fact-sheet/news-platform-fact-sheet/ [accessed 2024-08-02]

    ‎
    CP: convalescent plasma
    FDA: US Food and Drug Administration
    REDCap: Research Electronic Data Capture

    Edited by T Mackey; submitted 28.07.23; peer-reviewed by M Mackert, SH Hong; comments to author 09.11.23; revised version received 17.01.24; accepted 15.07.24; published 29.08.24.

    Copyright

    ©Sara Watson, Tyler J Benning, Alessandro R Marcon, Xuan Zhu, Timothy Caulfield, Richard R Sharp, Zubin Master. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 29.08.2024.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Infodemiology, is properly cited. The complete bibliographic information, a link to the original publication on https://infodemiology.jmir.org/, as well as this copyright and license information must be included.