Next Article in Journal
An Examination of the Interaction of Democratic Ideals with Journalism Training Programmes in the Global South: The Case of Cambodia
Next Article in Special Issue
COVID-19-Related Social Media Fake News in India
Previous Article in Journal
Tweets That Matter: Reconsidering Journalistic Sourcing and Framing Processes in the Context of the #Grexit Debate
Previous Article in Special Issue
Media and Misinformation in Times of COVID-19: How People Informed Themselves in the Days Following the Portuguese Declaration of the State of Emergency
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

The Role of Public Trust and Media in Managing the Dissemination of COVID-19-Related News in Switzerland

Institute of Information Systems, University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis), 3960 Sierre, Switzerland
Global Center for Digital Business Transformation, International Institute for Management Development, 1003 Lausanne, Switzerland
Author to whom correspondence should be addressed.
Journal. Media 2020, 1(1), 145-158;
Submission received: 9 November 2020 / Revised: 8 December 2020 / Accepted: 13 December 2020 / Published: 17 December 2020
(This article belongs to the Special Issue Media Freedom in the Age of COVID-19)


Public trust in health information is essential to ensure that preventative strategies to reduce the transmission of COVID-19 are accepted and followed. This study explored the way Swiss people accessed and consumed news and information about the coronavirus from different channels, and the role media plays in public trust during the pandemic. Based on a study of 442 randomly assigned participants in French-speaking regions, we examined the following four questions: (1) What are the news sources and platforms and how are they used? (2) How does the public rate the trustworthiness of these sources and platforms? (3) To what extent does the public perceive that these sources and platforms are provided inaccurate information? (4) What roles do these sources and platforms play in the pandemic? Implications are discussed in the conclusion based on our findings.

1. Introduction

Most people form opinions based on the media’s news coverage, and hence, news consumption might influence perception and opinions (Keersmaecker and Roets 2017). In the past several months, information about the coronavirus’s effect has been provided rapidly, and the consumption of news reports on the internet and the media is at an unprecedented level. At the same time, news consumers’ behavior has changed, and they prefer to get headlines more rapidly through the internet (Chauhan and Shah 2020).
Although the communication channels available today are improving worldwide interactions, the dissemination of uncorroborated information is affecting the content’s credibility adversely. This is particularly true for COVID-19-related news, as it is a novel health-related topic. Our poor knowledge of the virus has favored the development of false news. Indeed, without any empirical research on the subject, newspapers and governments spread information that could contradict each other (Montesi 2020). The World Health Organization (WHO 2020) has emphasized that unverified news and misinformation that spreads rapidly through social media poses a serious threat to the COVID-19 response. An "infodemic”, a term WHO has used during the pandemic, describes “…an over-abundance of information—some accurate and some not—that makes it hard for people to find trustworthy sources”. Thus, “fake news” has become a catch-all term rapidly during the COVID-19 pandemic. Social media have amplified the already rapid dissemination of such misinformation, which could affect the public’s trust in health information seriously and result in people’s failure to adhere to recommended public health measures.
According to a study the Reuters Institute for the Study of Journalism published (Brenner et al. 2020), most misinformation related to COVID-19 involves "various forms of reconfiguration, where existing and often true information is spun, twisted, recontextualized, or reworked", and less “was completely fabricated”. This study also found that the largest category of misinformation was “misleading or false claims about the actions or policies of public authorities, including government and international bodies like the WHO or the UN”. One typical example of misinformation disseminated during the pandemic claimed that electromagnetic fields and the introduction of 5G and wireless technologies were the direct causes of the virus’s spread, which led people to burn 5G network towers that were blamed inaccurately for COVID-19’s dissemination. Misinformation about COVID-19, like the pandemic itself, has become global, and it is inevitable in a country like Switzerland because of its small population. In recent months, the voices of Swiss conspiracy theorists and alternative media have been amplified, as they exploit both the crisis and social media platforms to spread rumors and reach a larger audience. Information overload can also be seen across social media. The COVID-19 Infodemics Observatory, which has collected millions of Tweets worldwide in the past six months, showed a sharp increase in Twitter chatter about COVID-19 in Switzerland early in the outbreak. According to this report, 5 days after the first confirmed case of the disease in Switzerland, COVID-related Tweets increased fivefold, and Twitter activity remained relatively strong throughout the lockdown, never decreasing below 6000 posts per day.
The Swiss public’s trust in the domestic professional information media is high, and the development of journalism’s professionalism, education, and common community orientation are usually considered key dimensions (Meier 2017). In Switzerland, nearly 70% of media professionals have a university degree, and almost half are organized in a professional association or trade union. Further, it was found that the majority of Swiss journalists demonstrate a high commitment to professional codes of ethics (Bonfadelli et al. 2012). These findings contribute to a relatively high public trust in domestic media.
In recent years, when considering media use, the transformation of the Swiss media public sphere and the increase in digital sources’ importance has become clear. According to the Quality of the Media of Switzerland (Eisenegger 2019), similar to radio and television, subscriptions to printed newspapers have dropped from 56% to 32% within 10 years. In contrast, online sources of information have increased their use share from 52% to 61% during the past two years. Social media have now become an important channel for most Swiss people to obtain information, although they feature rarely as the main sources of news. Although active social media users are more likely to engage with false or misleading information as well (Humprecht et al. 2020), the Swiss still have significant trust in the established information media, but low trust in social media (Eisenegger 2019). This public trust has also been reflected during the COVID-19 pandemic. Humprecht et al. (2020) found that Swiss people are more reluctant than others to share false information about COVID-19 on social media. This “resistance to fake news” can be attributed to the Swiss people’s trust in the media and government information sources.
Increasing public trust is particularly important during a pandemic, and therefore, the battle against fake news has continued. News providers are more careful in their news broadcasts, provide reliable COVID-related information from verified sources, and have abandoned the breaking news approach (Lewis and Cushion 2009; Usher 2018). Several agencies are investing efforts to combat fake news dissemination, and WikiTribune, FactCheck, PolitiFact, Snopes, and The Washington Post among others manually fact-check news and verify articles, books, government agency statistics, photographs, and recorded interviews regularly. Their work consists of ranking website pages or writing fact-check evaluations. In Switzerland, as more and more people receive news from social media and online applications, COVID-19-related fake news sources have appeared. A set of Swiss-led research projects have emerged in recent years. Tolmie et al. (2017) provided a social media verification dashboard to control the user-generated content, their findings have a positive effect on journalists’ content. Liu et al. (2019) and Tschiatschek et al. (2018) used technical methods to detect fake news, the former applied machine learning for automated classification, and the latter leveraged crowd signals to discover fake news from social media to minimize the spread of misinformation. Humprecht (2019) summarized the characteristics of fake news by analyzing the different effects of fake news in different countries; his finding argued that online disinformation is not only a technology-driven phenomenon but is also shaped by national information environments. These research projects bring together IT experts, universities, and media to devise technologies that could help both journalists to find online claims and readers to verify uncertain sources.
In this study, we used survey data collected in French-speaking parts of Switzerland from May to July, 2020, to document and understand the way Swiss people in this region accessed and consumed news and information about the coronavirus. In particular, we intended to have a better understanding concerning the role of media in public trust during the pandemic. Four research questions were addressed in this study: (1) What are the COVID-19-related news sources and platforms? (2) How does the public rate these sources’ and platforms’ trustworthiness? (3) To what extent does the public perceive that these sources and platforms are provided inaccurate information? (4) What roles do these sources and platforms play in the pandemic?
The remainder of this paper is organized as follows: The next section provides a summary of the work on COVID-19-related media news management and public trust during the pandemic in Switzerland. The methodology is then presented, which describes the data collection process, sample, and the survey development. Section 4 details the findings from our online survey. Finally, we conclude the work with a discussion of the implications of the study.

2. Related Work

During major crises, the media usually present themselves as observers of the events, become committed actors, practice a certain form of self-criticism, suffer severe public criticism, and discredit themselves quickly (Casero-Ripollés 2020). Sometimes, the media can play multiple roles that are explained in different ways. From surveillance of the environment to the creation of the collective imagination, from social control to entertainment (Voyenne 1979), and from commercial enterprise to the industry of consciousness (Tuchman 1981), multiple facets appear when we try to grasp the reality of the media. These changes make us reflect often on the complexity of the media’s method of operation. In normal times, media are integrated into the social fabric and nearly go unnoticed. However, in times of crisis, the media are more exposed and follow a cycle of behavior that begins with a step-by-step account of the facts and their development that leaves no detail omitted.
The coronavirus disease is the first pandemic in history in which technology and social networks are being used widely to encourage and enable individuals to remain safe, informed, productive, and connected. On the one hand, technology has amplified an infodemic that weakens and compromises the fight against the pandemic, as it creates doubts because much information is erroneous (Zarocostas 2020; Shahi and Nandini 2020; Serrano et al. 2020; Silva et al. 2020; Groza 2020; Dimitrov et al. 2020). Moreover, Rovetta and Bhagavathula (2020) advised the use of monitoring tools, such as Google Trends, to identify the dissemination of, or search for, false information by a population. This makes it possible to adapt the communication and identify areas of dissemination. On the other hand, the technology can be used as tools to access the information. According to the recent study of Nielsen et al. (2020), in six countries, namely Argentina, Germany, South Korea, Spain, England, and the US, the top four technology tools used to disseminate COVID-19-related information are social networks, search engines, video sites, and messaging applications, and the level of education was found to explain the use of certain tools; the lower the level of education, the less likely people are to rely on press organizations to obtain information rather than social networks. Their findings also showed that three-quarters of respondents trust national and international public health organizations, and the majority of people trust the media and their government.
People in Switzerland have demonstrated an exceptionally high level of confidence in government during the past several years (Mabillard and Pasquier 2015). Such trust is reflected in the transparency of information and the sense of participation in political decision-making. Switzerland was the OECD country that ranked first in confidence in government (85%) in 2019, an increase of 3% compared to 2018 (OECD 2019). The OECD average is 45%. Swiss citizens are highly satisfied with, and have confidence in, a wide range of public services, including the education (85%) and judicial (82%) systems, law enforcement (95%), and healthcare (88%). In the face of major crises, Swiss citizens often accept and trust the information the government provides (Freitag and Ackermann 2016). According to a 2020 Reuters Institute report (Reuters Institute 2020), Swiss readers’ level of trust in legacy media is higher than the global average. This study also showed that the Swiss population relies more heavily on traditional news media—including public broadcasters such as TV, radio, and print—than on social media for information on the virus. Swiss people also tend to access modern sources of news via traditional ways (e.g., TV, radio, and print) rather than online (e.g., social media). Take SRF News as an example; over 70% of French-speaking Swiss people accessed it at least three days per week via traditional ways. In contrast, less than a third said they accessed the online version of SRF News with the same frequency.
The roles of media and public trust during the COVID-19 pandemic are relatively new topics and thus have not yet been discussed fully by the research community. Therefore, we aimed to fill this gap by examining the role media plays in public trust in Switzerland during the COVID-19 pandemic.

3. Methods

3.1. Sample

A total of 442 participants answered our online survey in this study. Each participant who provided a valid survey was rewarded through an incentive program. Specifically, we randomly invited 600 people to participate in our online survey. In order to cover different backgrounds, these invitees covered different age groups, occupations, and educations. In the next week, the invitees who decided to participate notified us and obtained the online survey address and a participation code. Participants with this code could log in to our online survey to complete the questionnaire. The code was also used to match the user profile for our further analysis in this study. All subjects range in age from 16 to 75 years old and live in the French-speaking part of Switzerland, including six Swiss cantons, Valais, Vaud, Geneva, Neuchâtel, Fribourg, and Jura. As more than half of the participants in this study live in the canton of Valais (57%), we focused on the participants’ consumption behaviors with respect to COVID-19-related information from this canton. The canton of Valais is situated in the southwestern part of Switzerland, which includes two regions; the western part of Valais (Lower Valais) is French-speaking, while the eastern part (Upper Valais) is German-speaking. In this study, we also included participants from Upper Valais and established three groups according to the following geographical features: Lower Valais, Upper Valais, and other cantons.
Thirty-seven percent of the participants hold an apprenticeship diploma, 19% a high school degree, and 15% each have bachelor’s and master’s degrees. Most of the participants (67%) indicated that they read a daily newspaper online or offline to obtain COVID-19-related information, and 15% prefer to obtain news from a specialized magazine. More than half (64%) do not subscribe to a daily printed newspaper. Table 1 provides a summary of the respondents’ demographic and geographic characteristics.

3.2. Survey Development

Our survey was developed to understand the role of different news sources and platforms in the coronavirus pandemic. Most questions were used or adapted from related literature.
After introducing the survey’s scope and purpose, the main body of the questionnaire began with several questions that asked which media or platforms (both online and offline) the respondents used as a way to access news and information about COVID-19 in the past week. We then asked about the trustworthiness of these new sources and platforms upon which they rely. Questions about trustworthiness were answered on a seven-point Likert scale ranging from 1, “not at all trustworthy”, to 7, “completely trustworthy”.
To better understand the role news media and government play in disseminating news during COVID-19, we asked several opinion questions based on a seven-point Likert scale that ranged from 1, “strongly disagree”, to 7, “strongly agree”.
First, to test whether they were able to identify fake news and misinformation about COVID-19, we identified popular fake news and misinformation that was disseminated widely during the pandemic. We then phrased them positively, together with some accurate news related to COVID-19. Finally, we included 7 true or false statements for the respondents to answer. A “don’t know” option was also included to avoid random selections. Further, we asked explicitly how much false or misleading information about the coronavirus they perceived across different news sources and platforms.
To assess whether participants were paying sufficient attention to the instructions and ensure the survey’s quality, we introduced a trap question and asked the participants to choose the largest among 5 numbers ordered randomly. However, some have argued that such a trap question may cause participants to think harder than normally when answering survey questions, thus potentially altering a study’s results. To this end, the trap question was situated after the questions about the news sources and platforms’ trustworthiness and before the opinion questions. As a result, 46 failed to answer the trap question correctly; therefore, we removed them from the final sample.
Finally, we asked several questions about the respondents’ demographics, such as age, gender, education, income range, and job level, as well as their reading habits.

3.3. Procedure

Two experts, one man from a Swiss media association and one woman from a marketing company, reviewed the initial questionnaire. It was then distributed to 6 random participants for a pre-test to ensure that the survey was planned well and executed effectively. An analysis of their feedback revealed that the order of some questions should be reversed, and the questions and options could be grouped. Finally, several items on the questionnaire were revised.
Each participant was asked to answer the questionnaire through the online service Microsoft Teams. All participants were told that there were no right or wrong answers. The response time was recorded, and the survey took an average of 11 min to complete, including reading the instructions and answering the questions.
The experimental manipulations were evaluated in two stages. First, we discarded data from participants who spent less than 2 min answering the questions. Second, we excluded those who provided incomplete or random answers, which were checked using the trap question that asked them what the largest number was in a list of numbers. Of the 520 total questionnaires, 78 were eliminated from the final sample. Finally, 442 participants and their valid answers were considered in the study; 309 of these were females and 133 were males. Given the large difference in the participants’ male to female ratio, we used the weighted arithmetic mean (Fodor et al. 1995) in our analysis to make our sample comparable to these regions’ population of 49.2% males and 50.8% females, according to the Swiss Federal Statistical Office’s population report in 2019.

4. Results

4.1. Source of Information about the Coronavirus

It is reported widely that the pandemic has prompted a rise in news consumption, particularly in the area of digital news, as people are quarantined, and physical newspapers are distributed less often. The Reuters Institute described in “Digital News Report 2020” that the virus is “…almost certainly accelerating the shift to an all-digital future” (Reuters Institute 2020).
Our results confirmed this trend, as they showed that online sources are the most popular way to obtain news in Switzerland. As illustrated in Table 2, online searching is the dominant media source, and 92.8% of the respondents surveyed indicated that they this source of news in the past week, followed by social media (75.2%) and newspapers (both online and paper format, 72.4%). Television and radio are also important sources of news about COVID-19. Approximately two-thirds of those surveyed used television and 64% used radio in the past week. In the Lower Valais areas, people prefer to access COVID-19 news via traditional media sources. Our results showed that 77.8%, 71.2%, and 70.5% of the respondents surveyed said that they used newspapers, TV, and radio in the past week, respectively. In contrast, respondents from Upper Valais do not use newspapers as often as those from other areas. Only 55.4% of them said they accessed news from newspapers in the past week, which is less than those who received news by word of mouth.
While news organizations are usually seen as the most powerful source of news and information, with respect to COVID-19-related news, national government/national health organizations are the sources used most often (74.1%) as shown in Table 3. This is particularly true for people from Upper Valais, where this percentage is significantly higher than that from other regions (85.9% vs. 74.1%). News organizations/press are the second source of news or information about the coronavirus used most often; 70.9% of those surveyed said they used them in the past week. Other sources, such as scientists, doctors, and health experts, as well as global health organizations collectively, are also used widely, although people from Lower Valais generally do not rely on these groups as much as do those from other French-speaking areas. In contrast, politicians (7.5%) and unknown ordinary people (5.2%) are used least.
With respect to sharing news, nearly 60% respondents said that they have shared news or information about the coronavirus from the Swiss government or national health organizations with others (as shown in Table 3). Approximately half of them indicated that they share news from news organizations, while participants from Upper Valais are more likely to share information about the coronavirus from news sources. As many as 81.2% and 70.4% of people surveyed from that region said that they share coronavirus-related news or information from the national government/national health organizations, and news organizations, respectively, with others.
Social media and messaging applications such as Facebook and WhatsApp have emerged as among the most important tools to disseminate information. They can serve not only as a source of news information like traditional media but also as a fast and effective way to disseminate news and information. In our survey, approximately half of the respondents used Facebook to access news about the coronavirus in the past week (Table 4). However, approximately 42.8% of those surveyed said they did not use social media as a news source in the past week.
When asked about channels used to share news, over 40% of the respondents said they do not share news with others on social media, as shown in Table 5. For those who share news with others on social media, WhatsApp (71.2%) is the online channel used most, followed by Facebook (44.7%). Our results also showed that people from different regions have different preferred channels. For example, a significantly higher percentage of people from Upper Valais shared news about the coronavirus via Facebook in the past week (56% vs. 41%).

4.2. Trust in Sources and Platforms

It is important to note that which source people use could differ from the source they trust, although they are correlated often (e.g., people are more likely to use the sources and platforms they trust). To this end, we asked questions about the level of trust in different news sources and platforms.
The results in Figure 1 suggest that national government and national health organizations are perceived to be the most trustworthy sources, with a mean of approximately 6.0. News organizations are also perceived to be relatively trustworthy, with a mean just below 5.0. Our results demonstrated that during a health crisis, nearly everyone trusts health authorities and expert sources very highly. In contrast, ordinary individuals, either known or unknown, and politicians are perceived to be the least trustworthy.
Unsurprisingly, respondents showed a relatively lower level of trust in online sources: The mean of online sources was less than 4, which indicates only a moderate level of trust. The least trustworthy online sources were social media and messaging apps, both of which had means of approximately 2.9. It is also interesting to note that overall, women in Switzerland reported a higher level of trust than men across all sources, regardless of whether they are online or traditional media, indicating a gender difference.

4.3. Coronavirus-Related Fake News Dissemination Sources

As national government/national health organizations are perceived to be the most trustworthy news sources, they are also perceived to generate the least false or misleading information about COVID-19. In contrast, unknown ordinary people (e.g., on social media) are perceived to provide the most misleading information during the pandemic. While social media are now an important source of information, they are also vehicles for fake news and disinformation. Such a phenomenon is not new—before the coronavirus crisis, research had concluded that people are concerned about whether news on the internet is true or false (Flintham et al. 2018).
During the COVID-19 pandemic when people are in lockdown at home, they tend to use social media more often than ever to access information and communicate with friends. Disinformation and misinformation can be disseminated on the internet quickly, widely, and most importantly, inexpensively.
To test the role news sources play in fake news, we asked respondents first to judge whether seven statements are true or not. Those statements are based on accurate news/fake news related to the coronavirus. The examples are described in Table 6 and include “The coronavirus can be transmitted in areas with hot weather” and “Beef meat is the best vaccine against the coronavirus,” among others. Surprisingly, only 24.7% of the respondents were able to identify fake news in these statements correctly. Further analysis suggested that male respondents and those with a higher education are more likely to be able to discriminate between accurate and fake news.

4.4. The Media’s Role in the Pandemic

The results shown in Table 7 indicated that Swiss people are satisfied overall with the way the government is managing the coronavirus crisis. Of the respondents, 82.5% and 73.6% feel that the Swiss government has explained what they can do in response to the pandemic, and has helped them understand the pandemic, respectively, while 67.7% and 61.4% of them, respectively, believe the same of the role of news media. Still, a relative high percentage of respondents (42.6%) think the news media have exaggerated severity of the pandemic.
When an international or national news organization has certified the news media, nearly 70% of the respondents believe it increases the trustworthiness of the information the media provide—only 7% do not agree.
Interestingly, the results suggested that Swiss people trust local and national media (e.g., Le Nouvelliste, Le Temps, 20 Min) more than international news sources (e.g., CNN, BBC). Approximately 41.7% of respondents think that their local newspaper is a more trustworthy source, while 29.6% of them believe the opposite, and the remainder, 28.7%, do not favor any source over another.

5. Discussion and Conclusions

Our study provides a better understanding of the way Swiss people access and consume news and information about the coronavirus, as well as the role the media play in public trust during the COVID-19 pandemic. Based on the analysis of 442 responses from our online survey, the findings highlighted that the Swiss national government and health organizations are the sources used most often to obtain COVID-19-related news. At the same time, the Swiss, at least in French-speaking regions, prefer to share news or information about the coronavirus from those sources with others using a mobile application (e.g., WhatsApp). News organizations and the press serve as the second source of news about the coronavirus used and shared most often. The results also suggested that the Swiss national government and national health organizations are seen as the most trustworthy sources, followed by health experts and organizations, as well as the press. In contrast, respondents place relatively less trust in online sources. It is clear that news organizations still have a strong capital in trust, even if it is declining among youth according to some study (e.g., Skjellaug 2018).
Nevertheless, despite the relatively low trust level, online and social media are still the most popular ways to obtain COVID-19-related news in Switzerland, particularly social media, perceived as the format that generates most fake news and/or misleading information during the pandemic. Our further analysis showed that only a small percentage of surveyed respondents were able to identify typical COVID-19-related fake news correctly. While it is difficult to track which sources cause such misunderstanding, it is often believed that social media plays a crucial role. The Financial Times once stated that “… fake news spreads faster and more easily than this virus (coronavirus)” (Venkataramakrishnan 2020). This is where we need to warn about the dark side of social media—the impact of disseminating fake news on it about public health emergencies could be enormous.
Moreover, our results showed that Swiss people are satisfied overall with the way the Swiss government is managing the coronavirus crisis up to the survey time. Most respondents feel that the government has helped them understand the pandemic and has explained what they can do in response to it. This is in line with previous literature revealing that Swiss citizens showed higher public trust in key institutions like government than in their peers. A report in 2017 by the Organization for Economic Cooperation and Development revealed that nearly 80% of Swiss citizens had confidence in the federal government, almost double the OECD average of 42% (Plüss 2018). Our results suggested that in a health emergency situation, Switzerland maintains a high level of public trust in government.
However, it is important to point out that our results did not provide any evidence on sustaining the common narrative of the “infodemia crisis” as a crisis of confidence between ordinary and manipulated people and political or administrative elites and journalists, suspected to be biased and corrupted. While this study confirmed misinformation’s reality, with only 24.7% of people correctly judging whether the basic information offered to them was true or not (Table 6), it hardly confirmed such perception of mistrust in sources.
First, there is a gap between perception (trust) and reality (usage) of information sources. For instance, respondents do not trust politicians, but they have a remarkably high degree of trust in their national government (Figure 1). Respondents use and share the content of their national government much more than that of independent experts and international organizations, as shown in Table 3, even though they say they trust scientific experts and international organizations as well (Figure 1).
Second, while our results confirmed that people trust official journals more than informal communication channels to share and use information (Table 3), we did not control the source of content on social media; the content that is read and shared on social networks may also initially come from newspapers and governmental institutions, as now most of the organizations also have public accounts on leading social media.
These two elements call for a different communication strategy than the one implemented by national governments, newspapers, or even social networks to fight misinformation in Switzerland.
Indeed, during the COVID-19 crisis in Switzerland, journalists and the government tried to inspire more confidence by referring to international and scientific studies on controversies such as the transmission of the virus in the air. Journalists and politicians sought additional legitimacy by utilizing scientific and universal references in their public communication. The Swiss government has often tried to base the legitimacy of its decisions on independent experts’ and organizations’ voices, to appear as a government respectful of science as opposed to a populist government. Although these references are not seen as biased or corrupted for many people in our sample, it unclear whether there was much to be gained from doing so, especially for the government.
Finally, it should be noted that information sources are generally considered more reliable when perceived as more local; the same is true for international organizations versus national government and ordinary known persons versus ordinary, unknown persons (Table 3). Hence, it would be expected that people are more likely to trust information, including scientific results against disinformation, when it is distributed by local public authorities. Our results also demonstrated that the labeling strategy to counter misinformation is likely to be effective. In reality, what we have observed is some content in leading social networks like Twitter or Facebook is now labeled by the WHO or, in the case of the United States, by the Centers for Disease Control and Prevention of Disease (CDC) to counter misinformation. This study suggested that referring to national organizations’ information, or even regional authority’s information in some cases, may prove a more effective strategy.

Author Contributions

Conceptualization, Z.L., N.G.B., M.D. and J.-G.P.; Literature review, Z.L. and M.D.; Methodology, Z.L. and J.S.; Quantitative analysis and results, J.S. and Z.L.; Project coordinator, M.D.; Project administration, N.G.B.; Discussion, J.S. and J.-G.P.; Writing—original draft, Z.L. and J.S.; Writing—review, Z.L., J.S. and J.-G.P. All authors have read and agreed to the published version of the manuscript.


The work described in this paper was part of project COVID and was supported both by the University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) under grant number 103811 and by the Initiative for Media Innovation (IMI) funding from Switzerland under grant number 98313.


We thank the contributors from ESH Media Switzerland, Sébastien Hersant and Frédéric Gris, for sharing their experiences in the domain of press and media. Finally, we thank the anonymous reviewers for their careful reading of our manuscript and their many insightful comments and suggestions.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Bonfadelli, Heinz, Guido Keel, Mirko Marr, and Vinzenz Wyss. 2012. Journalists in Switzerland: Structures and attitudes. Studies in Communication Sciences 11: 7–26. [Google Scholar]
  2. Brennen, J. Scott, Felix Simon, Philip N. Howard, and Rasmus Kleis Nielsen. 2020. Types, sources, and claims of COVID-19 misinformation. Reuters Institute 7: 3–1. [Google Scholar]
  3. Casero-Ripollés, Andreu. 2020. Impact of Covid-19 on the media system. Communicative and democratic consequences of news consumption during the outbreak. El Profesional de la Informacioón 29: e290223. [Google Scholar] [CrossRef]
  4. Chauhan, Vilas, and Ms Heer Shah. 2020. An Empirical Analysis into Sentiments, Media Consumption Habits, and Consumer Behaviour during the Coronavirus (COVID-19) Outbreak. Purakala with ISSN, 2020. [Google Scholar] [CrossRef]
  5. Dimitrov, Dimitar, Erdal Baran, Pavlos Fafalios, Ran Yu, Xiaofei Zhu, Matthäus Zloch, and Stefan Dietze. 2020. TweetsCOV19-A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic. Paper presented at the 29th ACM International Conference on Information & Knowledge Management, Galway, Ireland, October 19–23; pp. 2991–98. [Google Scholar]
  6. Eisenegger, Mark. 2019. Main findings. The Quality of the Media—Switzerland. Yearbook 2019. Zürich: fög—Forschungsinstitut Öffentlichkeit und Gesellschaft/UZH. [Google Scholar]
  7. Flintham, Martin, Christian Karner, Khaled Bachour, Helen Creswick, Neha Gupta, and Stuart Moran. 2018. Falling for fake news: Investigating the consumption of news via social media. Paper presented at the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada, April 21–26; pp. 1–10. [Google Scholar]
  8. Fodor, Janos, J. -L. Marichal, and Marc Roubens. 1995. Characterization of the ordered weighted averaging operators. IEEE Transactions on Fuzzy Systems 3: 236–40. [Google Scholar] [CrossRef] [Green Version]
  9. Freitag, Markus, and Maya Ackermann. 2016. The impact of associational life on trust in local institutions: A comparison of 57 Swiss municipalities. Local Government Studies 42: 616–36. [Google Scholar] [CrossRef]
  10. Groza, Adrian. 2020. Detecting fake news for the new coronavirus by reasoning on the Covid-19 ontology. arXiv arXiv:2004.12330. [Google Scholar]
  11. Humprecht, Edda. 2019. Where ‘fake news’ flourishes: A comparison across four Western democracies. Information, Communication & Society 22: 1973–88. [Google Scholar]
  12. Humprecht, Edda, Frank Esser, and Peter Van Aelst. 2020. Resilience to online disinformation: A framework for cross-national comparative research. The International Journal of Press/Politics 25: 493–516. [Google Scholar] [CrossRef] [Green Version]
  13. Keersmaecker, Jonas De, and Roets Arne. 2017. Fake news: Incorrect, but hard to correct. the role of cognitive ability on the impact of false information on social impressions. Intelligence 65: 107–110. [Google Scholar] [CrossRef]
  14. Lewis, Justin, and Stephen Cushion. 2009. The thirst to be first: An analysis of breaking news stories and their impact on the quality of 24-h news coverage in the UK. Journalism Practice 3: 304–18. [Google Scholar] [CrossRef]
  15. Liu, Zhan, Shaban Shabani, Nicole Glassey Balet, and Maria Sokhn. 2019. Detection of satiric news on social media: Analysis of the phenomenon with a French dataset. Paper presented at 2019 28th International Conference on Computer Communication and Networks (ICCCN), Valencia, Spain, July 29–August 1; pp. 1–6. [Google Scholar]
  16. Mabillard, Vincent, and Martial Pasquier. 2015. Transparency and trust in government: A two-way relationship. Yearbook of Swiss Administrative Sciences, 23–34. Available online: (accessed on 13 December 2020). [CrossRef]
  17. Meier, Werner A. 2017. Media landscape: Switzerland. Available online: (accessed on 9 November 2020).
  18. Montesi, Michela. 2020. Understanding fake news during the Covid-19 health crisis from the perspective of information behaviour: The case of Spain. Journal of Librarianship and Information Science. [Google Scholar] [CrossRef]
  19. Nielsen, Rasmus Kleis, Richard Fletcher, Nic Newman, Scott J. Brennen, and Philip N. Howard. 2020. Navigating the ‘Infodemic’: How People in Six Countries Access and Rate News and Information about Coronavirus. Oxford: Reuters Institute. [Google Scholar]
  20. OECD. 2019. Government at a Glance 2013. Paris: OECD Publishing, Available online: (accessed on 9 November 2020).
  21. Plüss, Jessica Davis. 2018. As Trust Declines Globally, Can Switzerland Remain an Exception? Swissinfo. Available online: (accessed on 1 December 2020).
  22. Reuters Institute. 2020. Reuters Institute Digital News Report. June 2020. Available online: (accessed on 9 November 2020).
  23. Rovetta, Alessandro, and Akshaya Srikanth Bhagavathula. 2020. Covid-19-related web search behaviors and infodemic attitudes in italy: Infodemiological study. JMIR Public Health and Surveillance 6: e19374. [Google Scholar] [CrossRef] [PubMed]
  24. Serrano, Juan Carlos Medina, Orestis Papakyriakopoulos, and Simon Hegelich. 2020. NLP-based Feature Extraction for the Detection of COVID-19 Misinformation Videos on YouTube. Paper presented at the 1st Workshop on NLP for COVID-19 at ACL 2020, Seattle, WA, USA, July 9. [Google Scholar]
  25. Shahi, Gautam Kishore, and Durgesh Nandini. 2020. FakeCovid—A Multilingual Cross-domain Fact Check News Dataset for COVID-19. arXiv arXiv:2006.11343. [Google Scholar]
  26. Silva, Lucas, Dalson Figueiredo Filho, and Antônio Fernandes. 2020. The effect of lockdown on the COVID-19 epidemic in Brazil: Evidence from an interrupted time series design. Cadernos de Saúde Pública 36: e00213920. [Google Scholar] [CrossRef] [PubMed]
  27. Skjellaug, Aïna. 2018. Young People’s Trust in the Media Is Crumbling. Le Temps. Available online: (accessed on 30 November 2020).
  28. Tolmie, Peter, Rob Procter, David William Randall, Mark Rouncefield, Christian Burger, Geraldine Wong Sak Hoi, Arkaitz Zubiaga, and Maria Liakata. 2017. Supporting the use of user generated content in journalistic practice. Paper presented at the 2017 Chi Conference on Human Factors in Computing Systems, Denver, CO, USA, May 6–11; pp. 3632–44. [Google Scholar]
  29. Tschiatschek, Sebastian, Adish Singla, Manuel Gomez Rodriguez, Arpit Merchant, and Andreas Krause. 2018. Fake news detection in social networks via crowd signals. In Paper presented at the Companion Proceedings of the Web Conference 2018, Lyon, France, April 23–27; pp. 517–24. [Google Scholar]
  30. Tuchman Gaye. 1981. Myth and the consciousness industry: A new look at the effects of mass media. In Mass Media and Social Change. Sage Studies in International Sociology. Edited by E. Katz, E. and T. Szecskö, T. Beverly Hills: Sage, vol. 22, pp. 83–100. [Google Scholar]
  31. Usher, Nikki. 2018. Breaking news production processes in US metropolitan newspapers: Immediacy and journalistic authority. Journalism 19: 21–36. [Google Scholar] [CrossRef] [Green Version]
  32. Venkataramakrishnan, Siddharth. 2020. The Real Fake News about Covid-19. The Financial Times. Available online: (accessed on 28 November 2020).
  33. Voyenne, Bernard. 1979. L’information Aujourd’hui. Paris: Armand Colin. [Google Scholar]
  34. WHO. 2020. Managing the COVID-19 Infodemic: Promoting Healthy Behaviours and Mitigating the Harm from Misinformation and Disinformation. Available online: (accessed on 9 November 2020).
  35. Zarocostas, John. 2020. How to fight an infodemic. The Lancet 395: 676. [Google Scholar] [CrossRef]
LS: Likert scale.
Figure 1. Level of trust in different COVID-19-related news sources and platforms.
Figure 1. Level of trust in different COVID-19-related news sources and platforms.
Journalmedia 01 00010 g001
Table 1. Respondents’ demographics (n = 442).
Table 1. Respondents’ demographics (n = 442).
under 1710.2%
65 and over132.9%
Compulsory education296.6%
Hight school graduate8218.6%
Bachelor’s degree6715.2%
Master’s degree6715.2%
Doctoral degree51.1%
Job level
No occupation8218.6%
Daily newspaper15835.7%
Non-daily newspapers28464.2%
Table 2. COVID-19-related information channels.
Table 2. COVID-19-related information channels.
(n = 442)
Lower Valais
(n = 183)
Upper Valais
(n = 69)
Other Cantons
(n = 190)
Online (e.g., search, webpage, email, etc.) Journalmedia 01 00010 i001 Journalmedia 01 00010 i002 Journalmedia 01 00010 i003 Journalmedia 01 00010 i004
TV Journalmedia 01 00010 i005 Journalmedia 01 00010 i006 Journalmedia 01 00010 i007 Journalmedia 01 00010 i008
Social media (e.g., Facebook, Twitter, WhatsApp, etc.) Journalmedia 01 00010 i009 Journalmedia 01 00010 i010 Journalmedia 01 00010 i011 Journalmedia 01 00010 i012
Radio Journalmedia 01 00010 i013 Journalmedia 01 00010 i014 Journalmedia 01 00010 i015 Journalmedia 01 00010 i016
Newspaper (online and print) Journalmedia 01 00010 i017 Journalmedia 01 00010 i018 Journalmedia 01 00010 i019 Journalmedia 01 00010 i020
Word of mouth Journalmedia 01 00010 i021 Journalmedia 01 00010 i022 Journalmedia 01 00010 i023 Journalmedia 01 00010 i024
Table 3. Source of news about the coronavirus used and shared.
Table 3. Source of news about the coronavirus used and shared.
Used SourceShared Source
News organizations/press Journalmedia 01 00010 i025 Journalmedia 01 00010 i026
National government/national health organizations Journalmedia 01 00010 i027 Journalmedia 01 00010 i028
Scientists, doctors, health experts Journalmedia 01 00010 i029 Journalmedia 01 00010 i030
Global health organizations (e.g., WHO) Journalmedia 01 00010 i031 Journalmedia 01 00010 i032
Ordinary people I know personally Journalmedia 01 00010 i033 Journalmedia 01 00010 i034
Politicians Journalmedia 01 00010 i035 Journalmedia 01 00010 i036
Ordinary people I do not know personally Journalmedia 01 00010 i037 Journalmedia 01 00010 i038
Table 4. Channels used to share the news about the coronavirus.
Table 4. Channels used to share the news about the coronavirus.
Facebook Journalmedia 01 00010 i039
Twitter Journalmedia 01 00010 i040
YouTube Journalmedia 01 00010 i041
Instagram Journalmedia 01 00010 i042
None of them Journalmedia 01 00010 i043
Table 5. Respondents’ demographics (n = 442).
Table 5. Respondents’ demographics (n = 442).
OverallUpper Valais
Facebook Journalmedia 01 00010 i044 Journalmedia 01 00010 i045
WhatsApp Journalmedia 01 00010 i046 Journalmedia 01 00010 i047
Instagram Journalmedia 01 00010 i048 Journalmedia 01 00010 i049
Twitter Journalmedia 01 00010 i050 Journalmedia 01 00010 i051
Table 6. Respondents’ judgment about coronavirus (COVID-19) statements.
Table 6. Respondents’ judgment about coronavirus (COVID-19) statements.
COVID-19-Related StatementPercentage of True Answers (Male)Percentage of True Answers (Female)Mean
The coronavirus can be transmitted in areas with hot weather. Journalmedia 01 00010 i052 Journalmedia 01 00010 i053 Journalmedia 01 00010 i054
Eating garlic can help prevent infection with the coronavirus. Journalmedia 01 00010 i055 Journalmedia 01 00010 i056 Journalmedia 01 00010 i057
Older people are more susceptible to becoming seriously ill from the coronavirus. Journalmedia 01 00010 i058 Journalmedia 01 00010 i059 Journalmedia 01 00010 i060
Antibiotics are effective in treating the coronavirus. Journalmedia 01 00010 i061 Journalmedia 01 00010 i062 Journalmedia 01 00010 i063
The new coronavirus can survive in the air and remain infectious. Journalmedia 01 00010 i064 Journalmedia 01 00010 i065 Journalmedia 01 00010 i066
The new coronavirus can be transmitted through mosquito bites. Journalmedia 01 00010 i067 Journalmedia 01 00010 i068 Journalmedia 01 00010 i069
Beef meat is the best vaccine against the coronavirus. Journalmedia 01 00010 i070 Journalmedia 01 00010 i071 Journalmedia 01 00010 i072
Respondents who answered all the questions correctly Journalmedia 01 00010 i073 Journalmedia 01 00010 i074 Journalmedia 01 00010 i075
Table 7. Respondents’ agreement with coronavirus (COVID-19) statements.
Table 7. Respondents’ agreement with coronavirus (COVID-19) statements.
COVID-19-Related StatementDisagree
(LS 1 1–3)
(LS 4)
(LS 5–7)
The news media has helped me understand the pandemic. Journalmedia 01 00010 i076 Journalmedia 01 00010 i077 Journalmedia 01 00010 i078
The news media has explained what I can do in response to the pandemic. Journalmedia 01 00010 i079 Journalmedia 01 00010 i080 Journalmedia 01 00010 i081
The news media has exaggerated the pandemic. Journalmedia 01 00010 i082 Journalmedia 01 00010 i083 Journalmedia 01 00010 i084
The government has helped me understand the pandemic. Journalmedia 01 00010 i085 Journalmedia 01 00010 i086 Journalmedia 01 00010 i087
The government has explained what I can do in response to the pandemic. Journalmedia 01 00010 i088 Journalmedia 01 00010 i089 Journalmedia 01 00010 i090
The government has exaggerated the pandemic. Journalmedia 01 00010 i091 Journalmedia 01 00010 i092 Journalmedia 01 00010 i093
News media being certified by an international or national news organization increases my trust in the information this news media provides. Journalmedia 01 00010 i094 Journalmedia 01 00010 i095 Journalmedia 01 00010 i096
I trust local newspapers (e.g., Le Nouvelliste, Le Temps, 20 Min) more than international news sources (e.g., CNN, BBC). Journalmedia 01 00010 i097 Journalmedia 01 00010 i098 Journalmedia 01 00010 i099
I trust information in news articles written by famous journalists. Journalmedia 01 00010 i100 Journalmedia 01 00010 i101 Journalmedia 01 00010 i102
I trust subscription news articles more than free ones. Journalmedia 01 00010 i103 Journalmedia 01 00010 i104 Journalmedia 01 00010 i105
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Liu, Z.; Shan, J.; Delaloye, M.; Piguet, J.-G.; Glassey Balet, N. The Role of Public Trust and Media in Managing the Dissemination of COVID-19-Related News in Switzerland. Journal. Media 2020, 1, 145-158.

AMA Style

Liu Z, Shan J, Delaloye M, Piguet J-G, Glassey Balet N. The Role of Public Trust and Media in Managing the Dissemination of COVID-19-Related News in Switzerland. Journalism and Media. 2020; 1(1):145-158.

Chicago/Turabian Style

Liu, Zhan, Jialu Shan, Matthieu Delaloye, Jean-Gabriel Piguet, and Nicole Glassey Balet. 2020. "The Role of Public Trust and Media in Managing the Dissemination of COVID-19-Related News in Switzerland" Journalism and Media 1, no. 1: 145-158.

Article Metrics

Back to TopTop