The rapid speed at which the COVID-19 pandemic evolved resulted in a situation where the evaluation and validation of novel information was not able to keep up with the speed at which it was disseminated, thus resulting in the potential for errors. News reporters often must summarize or appraise evolving situations in limited time, with the potential risk of incorrect information.

It has been estimated that about 11% of newspaper articles have errors that are brought to the attention of the publisher (Maier, 2007), yet many of these errors are not corrected—only an estimated 2% of erroneous articles receive corrections, many of which are “low-impact” (Shafer, 2007).

Historically, journalists have been viewed as impartial distributors of information, but a recent Pew survey indicated that journalists are less likely to agree with impartiality in journalism than the general public, and people who lean towards a liberal political view are also less likely to agree that journalists should be impartial (Forman‐Katz & Jurkowitz, 2022). Even with these beliefs in impartiality, 60% of people in the US view news outlets as being politically biased (Pew Research Center, 2009).

When errors are large or unidirectional, they may constitute misinformation. The spread of misinformation in addition to correct information during the pandemic has been described by the World Health Organization as an “infodemic”, and the spread of misinformation is believed to have resulted in the hospitalization of thousands and death of hundreds during the first few months of the pandemic (World Health Organization, 2021). Many have attributed the spread of misinformation largely to social media routes, whereas ascribing the reinforcement of public health recommendations to primarily news media (Bridgman et al., 2020).

Indeed, as purveyors of trusted public health information, traditional news media sources have been described as “key” players in combating the misinformation epidemic (Pollack, 2020). Reasons for this include the perception of journalistic integrity and credibility, and having strict editorial standards (Samoylich, 2024), which may lead to an environment where there is coordinated effort between government and local news stations in disseminating public health information (Ardia et al., 2020).

Because of the trusted position of the traditional media, there lies the responsibility to adhere to high-quality, truthful, and transparent reporting. Moreover, there is an obligation to be unbiased when reporting on topics, especially those perceived as polarizing or where there is equipoise. While the majority of information published in traditional media sources is correct, there are occasional mistakes that are made, and these are often corrected. We assume a non-partisan media source will have errors reported non-differentially - meaning that some errors are overstatements, some are understatements, and some do not result in a notable change in meaning.

It is from this perspective that we sought to examine the errors and corrections in NYT and to assess if there is an imbalance toward overstating the severity of the pandemic which may support more extreme restrictions or understating the severity. As a comparator group, we sampled corrections during the same time period that did not specifically pertain to COVID-19 and assessed whether they over- or under-stated the relevant or target problem. Ideally, the findings of our research will encourage more accurate reporting, especially when information has the potential to shape views and policies.

Several frameworks may be relevant to our research. First, framing is often used in communication. This involves selection and salience, and this term conceptualizes and promotes a definition of a problem, a diagnosis of cause(s), making moral judgement(s), and suggesting remedies (Entman, 1993). The framing of journalistic reporting has the potential to influence public perception, and consequently policy preferences. Secondly, objectivity, including factuality and impartiality, in reporting has traditionally been viewed as fundamental to prevent people from making decisions and conclusions based on false premises (Mothes, 2017). Moreover, embodying an objective norm in reporting helps readers have trust in reliable and trustworthy descriptions of reality (Skovsgaard et al., 2013).

It is difficult to determine the exact frequency of errors in news publications, but about 11% of articles have errors that are brought to the attention of an editor (Maier, 2007). An analysis of over 500 randomly generated errors in four major newspapers found that most errors pertained to personal reference, and most errors were objective (Hettinga et al., 2018). However, another analysis found that higher perceptions of trust were inversely related to trust in the news source (Wilner et al., 2022), suggesting that even unbiased errors can lead to less trust in the reporting.

To assess the direction of corrected reporting, we searched the New York Times (NYT) because it was the most circulated news source in the United States (US), as per both digital and print subscriptions (Majid, 2023). We searched the NYT website for articles that had had corrections made. We searched for articles by including the word “COVID” in the search bar of the Corrections page (Corrections ‐ The New York Times, n.d.) on February 21, 2024. The search included all results through this date, with no restriction on start date.

We included articles that specifically discussed the topic of COVID-19 - namely those reporting on epidemiology, vaccines, masks, policy, funding, and/or government reactions to COVID-19. We excluded articles that reported on a singular death from COVID, events that occurred during the COVID-19 pandemic, but were not specifically related to COVID-19, epidemics in general, and governmental agency credibility. We also excluded articles not in English.

From included articles, we abstracted information on the author names of the article, the date the article was originally published, the correction information, the date of correction, and how many corrections were made. We classified the correction as a topic type (e.g., deaths, cases, vaccine or mask policy, spelling, date, etc.). We also classified the corrections as to whether they pertained specifically to COVID-19 or not and whether the error pertained to a number or statistic. We calculated the time interval between the date when the article was originally published and the date when the correction was made. If corrections were made on multiple days, we used the date of first correction. We abstracted data on author title/affiliation. If the writer was from the NYT, we classified them as a reporter, editor, columnist, correspondent, visual report/editor, bureau chief, opinion reporter/editor, or other (food critic, fashion editor, fellow). If the author was not one of these (e.g., academic professor, writer for another journal/newspaper/book), we classified it as independent. If more than 5 journalists contributed to an article, we classified these as being written by a single group (e.g., NYT), and we did not include them in the author analysis since it would be hard to determine who was responsible for the correction.

From the correction information, we classified it as having originally overstated the information, understated the information, or had no effect. If there wasn’t enough information to determine the original statement, we coded it as being unknown. In general, we classified statements originally reporting a more dire or more extreme situation as being overstatements. This included numbers that were higher than corrected numbers, in the instances of hospitalization, cases, or deaths, or lower numbers for vaccination status. Conceptually, more closures, later re-opening dates, or more resources invested into fighting COVID-19 in the original reporting were considered overstatements. The direction of the correction was coded by two blinded reviewers ([blinded for review]), and discordant coding was discussed for consensus.

For authors with one or more corrections, we searched to see how many total COVID-19 articles listed them as an author or coauthor between the dates of 02/01/2020 - 02/21/2024. This was done by searching the author’s name (in quotes) and the term “covid” in the general search bar, filtered by the specified dates. We then calculated a rate of corrections for each author.

We found 2393 articles with corrections and having the term “COVID” in them, of which 486 reported specifically on COVID or a COVID-related topic. Three articles were written by the “editorial board” so the author number could not be determined, and one article did not report any information about the correction - only that there was a correction made.

There were 576 total corrections for the included 486 articles, indicating that some articles had more than one correction (Table). Each article had a median of one author (range: 1-56) and one error (range: 1-9). One article did not give specifics on the correction, only that there was a correction made. Corrections made by NYT reporters comprised 47.6% (n=274) of all corrections, followed by columnists (10.6%, n-61) and independent authors (10.4%, n=60). Forty-three percent (n=245) corrections specifically pertained to COVID-19. The most common types of corrections pertained to spelling (n=78; 13.5%), location (n=57; 9.9%), date/time (n=53; 9.2%), and vaccine/vaccination information (n=53; 9.2%). Overall, 25% (n=144) pertained to a statistical number. The median number of days from when the article was first published and when the correction was made was 1 day (range: 0-91). Most corrections were equivocal in their tone (n=408, 59.1%), while 27.7% (n=191) were overstated in the original text, 11.3% (n=78) were understated in the original text, and 1.9% (n=13) of corrections did not provide enough information to determine the direction of the correction.

Compared to corrections not pertaining to COVID-19, corrections pertaining to COVID-19 were less likely to be about spelling (0% vs 23.6%), locations (1.2% vs 16.3%), or title/degree (0% vs 10.6%), and more likely to be about a vaccine/vaccination (21.2% vs 0.3%), incidence/cases of conditions (12.2% vs 0.3%), or disease testing (7.8% vs 0.3%; p<0.001).

Compared to corrections not pertaining to COVID-19, corrections pertaining to COVID-19 were less likely to result in an equivocal tone (16.7% vs 88.8%), but they were more likely to both overstate (54.7% vs 8.5%) and understate (23.7% vs 2.4%) the situation in the original text (p<0.001). Examples of overstatements, understatements, and equivocal statements are listed in the supplemental table.

The kappa statistic for determining the level of agreement in the direction of the correction was 0.61 (p<0.001), indicating substantial agreement between raters.

There were 349 unique authors, if not considering unspecified authors or papers with more than 5 authors (e.g., “editorial board”, “NYT”, “The Daily”, etc.). The median correction by each author was one (range: 1-55). Thirty-three percent of corrections made by NYT reporters had the original information overstated, whereas it was 26.0% for other NYT authors and 16.7% for independent authors (p=0.07; Table and Figure 1). Figure 2 shows the distribution of the number of overstated and understated corrections for authors. The median percentage of COVID-19 corrections per author was 2% (range: 0.3% to 100%), and the median percentages of overstatements and understatements were 0% (range: 0% to 100%) and 0% (range: 0% to 50%). Ten reporters (of 346) accounted for 24% of the corrections. The reporter with the single most corrections accounted for 7%. Figure 3 shows the distribution of the percentage of COVID-19 corrections indicating an overstatement and understatement of the original information for NYT reporters with at least 50 NYT COVID-19 articles.

We found that corrections made by NYT authors often led to meaningful differences in how information was portrayed, particularly when corrections pertained to COVID-19, where the original information more often overstated the COVID-19 pandemic and gave the impression that the situation was more dire than it actually was.

Overall, the majority of all corrections led to no meaningful difference in the tone of the article, unless the correction was about COVID-19. In these instances, the majority of corrections indicated a more exaggerated tone or more dire situation in the original text. This is noteworthy considering that much of the research and discussion on misinformation during the COVID-19 pandemic has centered around social media’s role and not mainstream media’s role (Ferreira Caceres et al., 2022). Conversely, mainstream media has been viewed minimally as a mediator of truth and more generously as a guardian of truth (Benham, 2020; Michailidou & Trenz, 2021). Prior to the COVID-19 pandemic, it was estimated that only a part of fake news was disseminated through social media (Tsfati et al., 2020), although trust even in the mainstream media had been declining in recent years (Benham, 2020).

While most COVID-19 corrections indicated an overstatement of the originally reported information, another notable finding is that there was heterogeneity in whether authors routinely under or overstated the original information. Balanced reporting should lead to non-differential differences in the percentages of overstatements and understatements. We found that while a few authors had a similar percentage of both overstatements and understatements, most corrections by authors indicated a bias in one direction or another, and of those, most indicated an overstatement of the original information. Moreover, almost one-quarter of the corrections were made by fewer than 3% of all authors.

When corrections were made, the time between reporting and the information being corrected was short (median of one day). While it is understood that mistakes are made in reporting, credible, upstanding sources will make corrections quickly, although even quickly made corrections can lead to public distrust (Farhi, 2013). Additionally, transparent journalism should also include information on the correction. While most corrections contained information about both the correction and the original reporting, 2% of articles did not, and one did not provide any information about the correction, only the date that a correction was made.

In 2017, the NYT revised their editing process to a more “streamlined” process. As a result, the number of corrections decreased slightly, but a higher number of corrections were made in the front section, where readers are more likely to get information on world, national, and political news (Hettinga & Smith, 2021). It is unknown how this process could have affected the corrections made in regards to reporting on the COVID pandemic. If the errors were in these sections, it could have had more influence on public perception than errors contained in other sections.

The differential tone in reporting suggests a need for better objectivity in reporting. Some solutions to more objective reporting include the incorporation of future orientation (e.g., “what next” or “what now”) to encourage goal-directed behavior, addition of inclusivity and diversity in perspectives, placing events in their broader context, and allowing input of others (van Antwerpen & Fielding, 2023). As our results suggest bias in reporting errors, journalists and editors should, ideally, be more diligent and implement editorial checks to make sure that errors are not differentially made. Additionally, given the perception of the NYT leaning liberal, those in positions to develop policy may want to also consider using information from conservative-leaning publications, in addition to information from liberal sources, when making public decisions.

First, our results may not be generalizable to all media sources or newspapers. NYT is believed to lean liberal, and this does not reflect the leanings of other news sources. We only selected one news source because it had the largest number of subscribers. Because it has the most subscribers, it could have more influence on readers’ opinions. As a result of the way that searches are done on the NYT, we had to use a different search strategy for identifying the denominator, but because the same method for determining the number of author papers was used for all authors, this would likely lead to non-differential bias in determining the percentage of corrections. While this may affect the exact rate of corrections, our focus was to show comparative trends in rates. Second, classification of author tone could be subjective, so we used two reviewers to code the tone. We used a commonly used way to measure author agreement, but this method has not been formally validated. Furthermore, even if both reviewers were in agreement, there could still be some residual subjectivity Finally, because some studies had more than one author, and we were not able to determine which author actually made the error, the corrections from these articles were attributed to each author of the article.

We examined both COVID-19 specific and COVID-19 non-specific corrections in NYT articles covering COVID-19 topics. When compared to non-COVID-19 corrections, we found COVID-19 corrections were six times more likely to overstate the magnitude of the problem. In other words, when reporters erred, it was towards engendering greater fear and panic. Future research should be done to assess the impact of reporting errors on understanding and behavior. We also found that individual reporters had different patterns of error. Eleven percent tended to underemphasize the pandemic, while 28% tended to overemphasize it before it was corrected. Less than 3% of authors were responsible for almost one-quarter of all corrections, and the reporter with the single most corrections accounted for 7% of all corrections. Our results suggest that corrections may plague some reporters more than others, warranting a more careful review of information prior to disseminating to the public.