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Abstract

Trust in public authorities can be crucial for a country to navigate through times of crisis. Such crises put news media into the spotlight as crucial information brokers between authorities and the public. It is argued that media coverage should affect trust in public institutions and that such effects are likely to be conditioned by individuals’ crisis risk perceptions. This article investigates the dynamics of public trust in the government during the COVID-19 pandemic over more than a two-year period. To do so, it draws on panel survey data from thirty-two waves combined with data on news media coverage of salient topics of crisis coverage. The analytical strategy relies on multilevel modeling and assesses the effect of media coverage on citizens’ trust, as well as the effect of risk perceptions and the interaction between them. Among others, the results revealed that risk perceptions related to the economy and exposure to media coverage of economic “costs” negatively impacted trust. Furthermore, it found evidence that when associated with media exposure to “costs,” societal risk perceptions (both health and economy related) had a significant impact on trust in government. The impact varied depending on the level of media exposure, with high exposure leading to higher trust in government. The study concludes by highlighting the practical and theoretical implications of these findings.

Keywords

news media panel survey political trust COVID-19 Austria

Introduction

In times of crises, trust in public institutions is of central importance. Public institutions provide orientation and a sense of security, and trust in their actions is likely to lead to higher acceptance of crisis mitigation measures. During COVID-19, trusted public institutions were important for public compliance with pandemic measures (Blair et al. 2022) and for solidarity (Roblain et al. 2022). Similarly, during natural disasters (Siegrist and Zingg 2014) and economic crises (van der Meer and Hakhverdian 2017), trust in public institutions is crucial for effective response and recovery, as it fosters cooperation and adherence to necessary interventions. This study seeks to understand and explain the dynamics of trust in public institutions during an evolving crisis, specifically focusing on trust in government.

Mass media allegedly play an important role during crisis situations, providing vital information and hence enabling broad sections of the population to stay informed about disruptive events and important policy measures (Boomgaarden et al. 2011). In line with that, there generally is a rise in public reliance on media and in media use during crises (Anwar et al. 2020). The role of the media was arguably of particular relevance during the COVID-19 pandemic, as mediated information became even more important during phases of social distancing, lockdowns, and stay-at-home measures. Relatedly, an increase in information-seeking behaviors during the pandemic, alongside higher media use, was observed (Anagaw and Guadie 2023).

Media act as an important mediator between governments and the public. They act as an information link through which government proposals and actions become transmitted to the public, are critically scrutinized, and through which governments receive feedback from the public domain (e.g., Blumler and Coleman 2015). Given that most people still learn about politics through (more or less) institutionalized mass media, especially as social media are reducing the prominence and role of news on their platforms (Newman et al. 2024)—it is assumed that media affect perceptions of governments, their actors and policies (e.g., Boomgaarden and Schmitt-Beck 2019). Specifically to our interest, some scholars assert that media coverage can shape public trust in government (e.g., Charron and Annoni 2021), while others highlight the nuanced and multifaceted nature of such media effects in general (e.g., Valkenburg and Peter 2013). Our study puts an emphasis on crisis-related risks as an important factor shaping the relationship between media content, use, and trust in government. It is argued that it is particularly those people who receive a high dosage of risks through media consumption may be less inclined to trust the government to mitigate the crisis.

The present study focuses on the role of news media in explaining trust in government during the first months of the pandemic. It seeks to understand whether and to what degree media use (frequency and outlets) and the content patterns of those media contribute to explaining dynamics in trust in government over time. Importantly, the study acknowledges that these media effects are unlikely to be uniform. It is argued that during crisis situations the perceived risk that people hold may condition the effectiveness of media on attitudes toward government institutions. Therefore, this study considers individual differences in terms of risk perceptions (Barrios and Hochberg 2020; Dryhurst et al. 2020; Wachinger et al. 2013). We propose that individuals with heightened risk perceptions may process crisis news differently from those with lower risk perceptions, thereby moderating the relationship between media consumption and trust in government. This study adds to the understanding of the relationship between news media and public trust in government over different phases and stages of crises and introduces individual crisis risk perceptions as a conditioning factor. Given the important role of mass media and the strong public politicization of COVID-19 mitigation measures in Austria (as elsewhere, e.g., in the U.S., see Neumann et al. 2023), we pay particular attention to the effect of media consumption and it being conditional on risk perceptions.

The case of Austria offers a particularly relevant context for investigating news media and government trust during crises. Austria’s political and media landscape—characterized by a coalition government and a strong public broadcaster complemented by diverse commercial news outlets—offers a representative example of Central-West European media systems. This allows for findings that may be generalizable to similar European contexts. An initial boost in trust in the government at the start of the COVID-19 pandemic, attributed to the “rally-around-the-flag” effect (Bækgaard et al. 2020), was followed by a marked and sustained decline, with trust levels by 2023 falling below pre-pandemic baselines. This trend continued throughout 2023 without signs of recovery to pre-pandemic levels. This study explores how media consumption patterns and content influenced these dynamics of trust in government, controlling for other factors such as citizens’ satisfaction with crisis management and their broader satisfaction with democratic functioning. Drawing on a rich tradition of linkage studies that combine survey data with content analysis data (e.g., De Vreese 2014; de Vreese et al. 2017; Schuck et al. 2016; Stier et al. 2020), this study employs a content analysis of major news media combined with data from thirty-two waves of the Austrian Corona Panel Project (ACPP)¹ that measure citizens’ trust in political authorities and citizens’ media consumption during the COVID-19 pandemic in Austria (e.g., Kittel et al. 2021). This temporally sensitive approach allows us to examine trust changes over different crisis stages, providing nuanced insights into the role of media and the moderating effect of individual risk perceptions at different stages of the crisis.

Our study contributes to theory building by offering new insights into how media consumption and risk perceptions intersect to shape trust in government during crises. It is innovative by combining longitudinal media content data with a unique panel dataset. Finally, it informs journalists and news media organizations to reflect on their practices during crises, as well as public authorities to develop strategies to uphold public trust.

Media, Risk Perceptions, and Trust in Government

The Importance of Media Coverage in a Crisis

In general, mass media are integral in communicating crisis measures and providing an institutionalized channel to disseminate relevant information to a broad audience (e.g., Davidson and Wallack 2004). This holds particularly true for digital outlets of legacy media, due to their immediacy of coverage, strong editorial control, and widespread consumption via websites and their social media channels. Mass media, particularly legacy media known for their credibility and strong editorial oversight, have been frequently described to disseminate information surrounding public (health) crises, including severe events such as mad cow disease, H1N1, influenza, or swine flu (e.g., Meng et al. 2016). In these contexts, mass media were the major source of public information (Anwar et al. 2020). During the COVID-19 pandemic, an observed increase in public reliance on TV and digital news sources was notable as people sought easily available news (Van Aelst et al. 2021), drawn by the credibility and authoritative reporting these outlets provide during uncertain times (Nielsen et al. 2020). Yet international organizations such as the WHO warned of an “infodemic” situation, suggesting that the uncontrolled spread of false or misleading information about the COVID-19 virus had reached dangerous levels (WHO 2020). A cross-national study by Matthes et al. (2022) further demonstrated that perceptions of a high prevalence of misinformation are correlated with significant worries about COVID-19. In such instances, professional journalism and public broadcasting services play essential roles in corrective efforts (Egelhofer et al. 2020; Humprecht et al. 2020).

While mass media serve as a vital source of information for citizens (e.g., providing updates on health and societal situations, as well as informing about important policy and mitigation measures), recent research has also indicated that a considerable proportion of people sometimes deliberately turned away from the news—75 percent, according to the study conducted by Schäfer et al. (2022) based on panel data from April to May 2020. This behavior might be attributed to dissatisfaction with the media’s role, such as a lack of trust in COVID-19 news, feelings of information overload, or emotional distress (termed “news fatigue”). However, there is an expectation that individuals are more likely to consume diverse sources when they find the information useful (Knobloch-Westerwick 2014). Zoizner et al. (2022) conducted a cross-national panel study before and after the COVID-19 outbreak, revealing that citizens concerned about COVID-19 were more exposed to varied information across traditional and social media. The empirical evidence underlines the importance of considering how media coverage may have shaped public perceptions of crisis handling.

Trust in Government and Citizens’ Evaluation of Political Authorities During Crisis

Trust in government is a crucial concept in political science, especially concerning policy compliance and the stability of political systems (Miller 1974). It can be viewed as a measure of citizens’ perceptions regarding the government’s performance and intentions in achieving optimal societal, political, and economic outcomes. Barnes and Gill (2000) defined trust in government as the confidence that citizens have in authorities to do the right thing. Notably, citizens are willing to comply with government-issued policies and promote behavioral guidelines when trust is high (Levi and Stoker 2000). It is widely argued that trust affects the levels of legitimacy citizens attribute to their government, thereby influencing their willingness to comply with policy measures (Norris 2017). The OECD (2013) defines trust in government as “the confidence of citizens and businesses in the actions of government to do what is right and perceived as fair [. . .] Trust in government is essential for social cohesion and well-being as it affects the government’s ability to govern and enables government to act without coercion.” In the framework of the COVID-19 situation, empirical findings have highlighted how trust in government increases citizens’ compliance with mitigation measures and acceptance of policies. For instance, Xu (2021) demonstrated that increased trust in government correlates with greater confidence in governmental actions, while Lazarus et al. (2021) showed that trust positively influenced vaccine acceptance across nineteen countries. These findings emphasize the importance of understanding heterogeneous effects within different contexts, which is crucial for evaluating the external validity of our case study.

Several studies have documented a “rally-around-the-flag” effect (Bækgaard et al. 2020; Devine et al. 2020; Leininger and Schaub 2020), suggesting that citizens tend to positively evaluate governmental performance at the height of a crisis. This effect also led to a substantial increase in incumbent satisfaction and voting immediately after the crisis in several European countries (De Vries et al. 2020; Kritzinger et al. 2021). Under critical or extraordinary circumstances, it becomes crucial for authorities to assess public support and acceptance of policy measures addressing disruptive situations. For instance, citizens often seek to acquire knowledge about a specific crisis by relying on information provided by official bodies (Earle and Siegrist 2008). This dynamic is particularly relevant for exploring the psychological mechanisms at play, such as how risk perceptions contribute to blame attribution or negativity bias toward governmental actions (Kim and Kreps 2020). Risk relates to uncertainty, the mere possibility of danger or the probabilistic calculation of loss versus gain (Rohrmann and Renn 2000). This relationship between strong perceptions of risk and trust is expected to be negative because heightened risk perceptions may lead individuals to view governmental actions as inadequate or ineffective to protect them from harm. We propose the following hypothesis:

Hypothesis 1: Individuals with stronger perceptions of health or economic risks—either personal or societal—will exhibit lower levels of trust in the government.

Understanding this baseline is critical for assessing subsequent media effects. Indeed, both trust in institutions and compliance with policy measures can be affected by one’s ability and knowledge about an issue (Devine et al. 2020). In this regard, information provided by the media arguably plays a crucial role in shaping citizens’ perceptions of risks and benefits associated with policy measures. Media coverage not only informs the public but also influences the level of trust in government actions and decisions. Supporting and positive media portrayals can enhance public confidence in government strategies, whereas critical, negative, or biased coverage can undermine trust and compliance. Furthermore, media framing of government actions can affect public opinion, either bolstering support for policy measures or fostering skepticism and resistance (Van Aelst et al. 2017). Effective communication through the media is therefore essential for maintaining public trust and encouraging adherence to government directives during crises.

At a contextual level, higher media freedom enhances political knowledge and participation (Leeson 2008). However, it is also been found that frequent negative news in the media can undermine public trust in government and political figures (Newton 2017). Consequently, the direct influence of the media on government trust is ambiguous. This is evident considering the news often discussing countries with vastly different policies in tackling the pandemic, ranging from very strict (e.g., China) to more relaxed (e.g., Sweden), and the reported discrepancies in government performances worldwide in this scenario. Concerning the COVID-19 crisis more specifically, Rieger and Wang (2022) investigated people’s perceptions of the government’s ability to handle the crisis situation in fifty-seven countries and found that media freedom is related to lower government trust and indirectly affects a more negative assessment of government reactions as either insufficient or too strict. Furthermore, an important approach is to examine levels of trust in the context of framed messages used to enhance citizen engagement and compliance with policies (Goren et al. 2022; Han and Baird 2022). In particular, we are interested in messages about health and economic risks, which constituted one of the main trade-offs highlighted in the mass media that governments had to face when promoting mitigation measures (Carrieri et al. 2021). Since the media significantly contributed to highlighting and framing risks associated with health crises (Meng et al. 2016) and spreading and promoting mitigation measures (Anwar et al. 2020), it is crucial to discern whether media exposure affects citizens’ attitudes of trust toward the government differentially for different audience members (Valkenburg and Peter 2013). It is reasonable to presume that media portrayals that frequently highlight challenges or failures in government response, would foster audience perceptions of inefficiency or lack of competence in government actions and hence relate to lower levels of trust. We thus propose to test the following hypothesis:

Hypothesis 2: Higher exposure to news media content emphasizing health and economic risks is associated with lower levels of trust in the government.

In addition to a possible direct effect of media content and exposure on trust in public institutions, it has been argued that risk perceptions may shape this relationship. A direct relationship between public trust and risk perceptions has been studied in the context of crisis situations (e.g., natural disasters, health crises, and other hazards). Yet, a potential conditioning effect of risk perceptions on the relationship between media use and trust is of particular interest to the present study. For instance, people with low-risk perceptions but who strongly oppose stringent government measures (e.g., social distancing during COVID-19) are most likely to see their trust in the government decline (Kim and Kreps 2020). Effective communication through the media is therefore essential for maintaining public trust and encouraging adherence to government directives during crises.

For the purpose of this study, we focus on two types of risk perceptions that were prominent during the COVID-19 pandemic: Health and economic risk perceptions. Kam and Simas (2010) looked at the moderating effect of risk acceptance on media framing effects across different framing scenarios, showing that an individual’s level of risk acceptance affected responses to frames, even across multiple scenarios (but see Gottlob and Boomgaarden 2022). For our study, we assume that media coverage of risks would have a stronger negative impact on government trust if it is consumed by audience members who hold strong perceptions of risk already. These people are more likely to accept and integrate the risk-emphasizing media coverage and hence may show stronger media effects. We thus explore the interaction between citizens’ risk perception and their exposure to risk-related media content on trust, and test the following hypothesis:

Hypothesis 3: The impact of media exposure on trust in government is moderated by individuals’ risk perceptions. Specifically, for individuals with high health and economic risk perceptions, greater media exposure to risk-related content will be associated with a stronger decrease in trust in government.

Figure 1 summarizes our conceptual framework a. In a nutshell, we hypothesize (Hypothesis 1) that individuals more strongly perceiving the crisis as posing personal or societal health or economic risks are likely to exhibit lower levels of trust in the government. Furthermore, considering the critical role played by mass media in informing the public about the COVID-19 crisis and related policy measures, we assume (Hypothesis 2) that higher exposure to news media content concerning health and economic concerns is associated with lower levels of trust in the government. Furthermore, we assume that (Hypothesis 3) the impact of media exposure on trust in government is moderated by individuals’ risk perceptions.

Figure 1.

Conceptual framework of the present study.

Media and Trust During COVID-19 in Austria

In Austria, daily government press conferences became the primary platform to announce COVID-19-related measures starting from March 2020. At that time, monitoring the evolution of infections and hospitalization cases in Austria became a central focus of crisis management.² The mass media played a pivotal role in reporting these developments. Moreover, the “ORF Pressestunde” (ORF press hour), a Sunday morning interview program featuring a political figure responding to a journalist from a print medium and the ORF, emerged as a popular information source. For instance, on November 15, 2020, Sebastian Kurz, former Austrian Chancellor, announced during the ORF press hour his intention to conduct mass tests in Austria shortly before Christmas. This sparked diverse reactions—some welcomed the mass tests for providing a comprehensive snapshot of the epidemic, while others questioned their usefulness due to various reasons, including their limited medium-term significance.

In Austria, economic inequalities and groups newly exposed to economic hardship became visible as early as the gradual reopening of May 2020 (e.g., restrictions on family movements, homeschooling, loss of income, etc.). Rising (and newly generated) inequalities can contribute to political skepticism. Peaks in the level of unemployment were also prominent in 2020³ Furthermore, the fear of infecting others fostered practices of solidarity but also led to situations of loneliness and spurred new political and societal divisions.

Kittel et al. (2021) demonstrate that, in Austria, at the height of the crisis at the end of March 2020, citizens’ positive evaluations of governmental performance reached a maximum peak and steadily decreased thereafter. Although the study reveals high satisfaction levels with governmental performance, it also indicates a constant decrease in support for measures since then. This decline can be explained by intense public debates concerning trade-offs between health measures and economic well-being, as well as the balance between the restriction of liberties and the preservation of individual rights (e.g., movements), which have come to the forefront. Similar debates have been prevalent in many countries (Cheek et al. 2022), and the mass media played a pivotal role in informing citizens while highlighting different political stances (Thomas et al. 2020). Therefore, governments worldwide faced challenging trade-offs in responding appropriately to this health crisis. In this study, we investigate how perceived health and economic risks, as well as media exposure to these risks, affect trust in government.

Linking Strategy: Survey and Media Data

In addition to (amount and pattern) of news consumption, it is important to consider the concrete framing of the crisis in the news media, in terms of topical content. In this view, panel data can be well combined with media content data to investigate behavioral and attitudinal changes. The visibility (or salience) of some topic or entity can be a central aspect of questions related to public attention, and the tonality of the news (in relation to specific topics and entities) can be usefully combined with survey data to understand public evaluations, support, and acceptance. For instance, De Vreese and Semetko (2004) analyzed the voters’ choice in the 2000 Danish euro referendum by measuring media exposure in the panel survey. By doing so, they can measure the impact of media exposure on the outcome of the vote by weighing the exposure of specific media outlets in terms of salience and tone of news and by controlling for the voters’ intention during the first survey wave.

Research about linking strategy often relies on the combination of panel survey data and content analysis (Scharkow and Bachl 2016). De Vreese (2014) provides a good introduction to the topic and an explanation of the idea (Schuck et al. 2016), while Scharkow and Bachl (2016) assess the identification of problems and solutions with respect to measurement error. De Vreese et al. (2017) further review the rationales and types of linkage studies, discuss which survey and content items to use in an analysis, and provide a step-by-step example. More recently, Stier et al. (2020) reviewed how digital trace data, including online news consumption, can be combined with survey data.

Data and Method

Austrian Corona Panel Project

This article relies on the ACPP, a publicly available dataset that has been recording information from late March 2020 and onwards (the data set included thirty-two waves in total at the time of authoring this paper). The survey is designed to capture the social, political, and economic impact of the COVID-19 crisis on the Austrian population on a weekly (from waves 1 to 10), biweekly (from waves 11 to 13), and monthly (from waves 14 to 32) basis. The thematic scope of the survey covers several core dimensions which are repeated every wave in addition to other rotating or unique modules. The panel survey has a sample size of approximately 1500 respondents per wave.⁴ Data collection started on March 27th, 2020, precisely 14 days after the announcement of the lockdown by the Austrian government on March 13th, 2020. In our study, we used the first thirty-two recorded waves of the ACPP (see Table 1 for the description of the survey dates and response rates).

Table 1.

Description of the Panel Waves.

Wave	Start Date	End Date	Basis	Response Rate (%)	Replacement (Dropouts)	Event Chronology
1:	March 27, 2020	March 30, 2020	Weekly	35.20		Face masks mandatory
2:	April 3, 2020	April 8, 2020	Weekly	86.20	5.20%	Random testing
3:	April 10, 2020	April 16, 2020	Weekly	81.30	4.30%	Reopening
4:	April 17, 2020	April 21, 2020	Weekly	78.10	5.60%
5:	April 24, 2020	April 29, 2020	Weekly	73.80	5.40%
6:	May 1, 2020	May 6, 2020	Weekly	74.30	8.10%
7:	May 8, 2020	May 13, 2020	Weekly	70.80	4.30%
8:	May 15, 2020	May 20, 2020	Weekly	69.10	5.90%
9:	May 23, 2020	May 27, 2020	Weekly	67.60	3.10%
10:	May 29, 2020	June 3, 2020	Weekly	65.50	3.20%	Stabilization of cases
11:	June 12, 2020	June 17, 2020	Biweekly	65.70	3.00%
12:	June 26, 2020	July 1, 2020	Biweekly	61.30	4.50%
13:	July 10, 2020	July 15, 2020	Biweekly	62.50	2.40%
14:	August 14, 2020	August 19, 2020	Monthly	55.80	6.50%	Cases rise (second wave)
15:	September 11, 2020	September 18, 2020	Monthly	59.00	4.00%
16:	October 16, 2020	October 23, 2020	Monthly	63.60	5.30%
17:	November 13, 2020	November 20, 2020	Monthly	60.40	4.00%	Second lockdown
18:	December 11, 2020	December 18, 2020	Monthly	56.40	6.40%	Third lockdown
19:	January 15, 2021	January 22, 2021	Monthly	58.90	4.00%
20:	February 12, 2021	February 19, 2021	Monthly	58.20	—/—	Partial release
21:	March 12, 2021	March 19, 2021	Monthly	58.10	—/—	Vaccination
22:	April 16, 2021	April 23, 2021	Monthly	55.80	4.00%
23:	May 21, 2021	May 28, 2021	Monthly	54.10	4.50%
24:	June 25, 2021	July 2, 2021	Monthly	50.30	5.90%
25:	September 24, 2021	October 1, 2021	Monthly	48.40	3.40%
26:	October 22, 2021	October 29, 2021	Monthly	50.90	—/—	Fourth wave
27:	November 26, 2021	December 3, 2021	Monthly	51.80	4.30%
28:	January 14, 2022	January 21, 2022	Monthly	49.50	3.10%
29:	February 18, 2022	February 25, 2022	Monthly	48.90	4.00%	Release of measures
30:	March 18, 2022	March 25, 2022	Monthly	48.40	3.60%
31:	April 22, 2022	April 29, 2022	Monthly	47.00	3.90%
32:	May 20, 2022	May 29, 2022	Monthly	46.00	3.40%

APA Media Data

The media data are available to researchers and have been collected by the Computational Communication Science Lab at the University of Vienna.⁵ The data collection was done using a scraping strategy of the major newspapers in Austria. This included both the print versions and their corresponding online platforms, ensuring comprehensive coverage. This study uses a selection of news articles that match a list of search queries referring to parliamentary and governmental positions and figures.⁶ The total number of retrieved articles is 66,378. To maximize the inclusivity of the dataset, the collection encompassed articles published across both traditional offline sources (e.g., print editions) and their digital counterparts (as shown in Table 2), reflecting the broad consumption habits of the public and the significant role of digital legacy media. Each article was split into paragraphs using the default line break of the article. This enables us to have documents that are more comparable in size and also provides better results when extracting the main topic of each document (see topic modeling below). Table 2 provides the list of search queries:

Table 2.

Selected News Outlets and Search Queries to Retrieve the Articles.

Date	Offline Sources	Online Sources	Queries
2020-03-01–2022-02-01	PRESSE STANDARD KRONEKURIERSN	WWW.DIEPRESSE.AT WWWSTANDARD.AT WWWKRONE.AT WWW.KURIER.AT WWW.OMOESN.AT WWWOMOEKRONE.AT	(bundeskanzler* OR bundesregierung* OR bundespräsident* OR bundesrat* OR nationalrat* OR parlament OR bundesversammlung* OR abgeordneter OR delegierter OR politiker OR minister OR partei OR koalition) AND österreichAND (covid OR corona OR sarscov OR sars-cov OR pandemie OR maske OR lockdown OR lock-down OR lockerung OR impf OR quarantän OR distanzierung OR distanzregel OR infektion OR pcr test OR pcr-test OR antigen test OR antigen-test)
2020-03-01–2022-02-01		OE24	idem

Measures

The multidisciplinary approach of the ACPP engenders questions that can be grouped into six main themes: Health, economic situation, social situation, psychological conditions, political attitudes, and media and information. These themes were selected based on their comprehensive representation of societal concerns during the COVID-19 pandemic, drawing from established literature on crisis response and public trust dynamics (e.g., Dryhurst et al. 2020). The grouping ensures that the study captures the multifaceted impact of the crisis on public perception and behavior.

In our study, we concentrate on public trust toward political authorities as our dependent variables (see Block G of the questionnaire). The survey’s 10-point scale items (going from 1 “not at all” to 10 “completely”) “Do you have a great deal of trust, a fair amount of trust, a little trust, or no trust at all in each of the institutions mentioned in the context of the Corona crisis?” for the parliament and the government are used as dependent variables.

In an additional analytical step, the study investigates the importance of the content of media coverage (in terms of topics) on public trust. To extract relevant topics, LDA is used to perform topic modeling using the topicmodel package (Grün and Hornick 2011) from the R programming language. The most suitable number of topics is identified using the function FindTopicsNumber from the package ldatuning (Nikita and Nikita 2016), also verifying the coherence and interpretability of topics through robustness checks. Topics are manually labeled based on the thirty top words for each topic and are then regrouped into a reduced set of umbrella categories, including costs associated with the pandemic, political debates, cases reporting (infections, vaccination rate, hospitalizations, etc.), public information and research content (e.g., reports and statistics), mitigation measures, comparisons with other countries, specialized expert content, targeting of population groups (e.g., women and children), and planification. To improve reliability, a coding framework was established, and topics were cross-verified with two independent coders to ensure consistency (Cohen’s Kappa intercoder reliability score of 0.73, which shows substantial agreement).

To assess respondents’ exposition to these topics, we rely on the frequency of reliance on each of the major newspapers (including Kronen Zeitung, Kurier, Die Presse, Der Standard, Salzburger Nachrichten, and OE24) over the last week (scale from 1 “never” to 5 “several times a day”). While this measure provides an estimate of potential exposure, it does not confirm actual attention to specific content (De Vreese et al. 2017). This limitation is acknowledged, and a justification for this approach includes existing constraints in accurately tracking individual content consumption without invasive methods. Nevertheless, it constitutes a robust way to approximate exposure and assess its potential influence on public trust. For instance, if the main source of information of a respondent is Kronen Zeitung, then the exposure to the different topics will reflect the proportion of these topics in the news coverage of this newspaper the week before the respondent’s reply to the survey (see data linking strategy under Section “Data linking strategy”).

At the individual level, we considered additional independent variables that are related to respondents’ risk perceptions for themselves and for society with respect to the health and economic situation (see Block C of the questionnaire). The question matrix “How great do you estimate the health risks posed by the coronavirus for you personally and for the Austrian population? (Translated from German)” on a 5-point scale (going from 1 [“very big”] to 5 [“very small”]) was used for assessing health risks perceptions. A similar matrix question, “How great do you think the economic danger posed by the coronavirus is for you personally and for the Austrian population? (Translated from German),” was used for economic risk perceptions.

We also include several control variables including gender, education level, age cohort, and political orientation. We also added the perceptions of the government COVID policies by including the item “Would you consider the reaction of the government against coronavirus as sufficient, appropriate or extreme” with a 5-point scale answer option from 1 “not at all sufficient” to 5 “too extreme”. This item was asked several positions after the measure of trust in government in the questionnaire, ensuring it reflects perceptions post-assessment of trust. Finally, a variable accounting for the different Covid-19 waves in Austria (wave 1: March 27, 2020–August 13, 2020; wave 2: August 14, 2020–December 10, 2020; wave 3: December 11, 2020–October 21, 2021; wave 4: October 22, 2021 onwards) was added as a control variable to capture the temporal phases of the crisis, allowing for an analysis of trust dynamics.

Data Linking Strategy

The data linking strategy is done on the week before the individuals’ survey response in each panel wave. To link to specific newspapers, the study considers the media preferences of survey respondents. To do so, it relies on the survey items measuring the news consumption for the following Austrian newspapers (see Block K of the questionnaire): Kronen Zeitung or www.krone.at, Der Standard or derstandard.at, Die Presse or diepresse.com, Österreich or oe24.at, Kurier or kurier.at, Salzburger Nachrichten or salzburg.at, Sonstige österreichische Tageszeitungen. More precisely, the item asks each respondent “How often did you read about political events in the respective newspaper last week (on the internet or in print)?” and the answer options go from 1 (“several times a day”) to 5 (“never”). We reversed the scale so that 5 corresponds to frequent consumption and 1 to no consumption. Therefore, the content of news media is linked to individual survey responses for each wave of the panel based on the media that respondents most frequently read. If a respondent mentioned consulting two media sources with the same frequency, we computed the mean for the two media sources. The question is asked at every wave for new respondents. When not asked for incumbent respondents, we hypothesize that their media consumption practice remained the same for the subsequent survey waves (see also Figure 4 below). This also means that respondents who never consume any of the media are excluded from the analysis.

Analytical Strategy: Exploratory Analysis and Multilevel Modeling

Multilevel modeling is conducted to investigate the effect of risk perception, media exposure, and other individual-level variables on trust in government over time. We rely on the function lmer from the lme4 R package (Bates et al. 2009). Since we rely on longitudinal data where multiple observations are collected from the same individual, we used the respondent id as the clustering variable. Observations from the same individuals are usually more like each other than observations from different individuals. The ratio of the between-cluster variance to the total variance is called the Intraclass Correlation Coefficient (ICC) and tells us the proportion of the total variance in Y that is accounted for by the clustering. We use the function icc for the performance R package to calculate the ICC, and we obtain a value of 0.7.

Results

Descriptive Analyses

Figure 2 shows a continuous decline in the level of trust in the government over the survey waves (the decline between the first and the last wave is about 3.8 points). An interactive PowerBi dashboard⁷ can be accessed online to visualize the consumption of traditional newspapers (especially Kronenzeitung, Kurier, Die Presse, and OE24) and social media.

Figure 2.

Mean level of trust in government over survey waves.

We also perform robustness check analyses to improve the interpretability of the findings:

First, we plotted density curves of media coverage of the different umbrella topics. Figure 3 shows that the amount of coverage does not differ significantly across news outlets.

Figure 3.

Density curves of each umbrella topic across the news outlets.

Second, we rely on Sankey diagrams to assess individual changes of media consumption patterns over the survey waves. We selected four waves (1, 10, 22, and 31, see related events or phase in Table 1) and detected media consumption profiles using hierarchical clustering on the top of the consumption level of the different media sources for each of the wave (note that respondent not consuming any news are also included in this analysis). Five profiles consistently described the consumption of the respondents over the survey waves (the number of profiles is decided visually based on the dendrogram output). Figure 4 shows that media consumption patterns are very stable over time. The Kronenzeitung is the most-read newspaper. Furthermore, the proportion of “news-deprived” respondents remains stable over time. These respondents are characterized by using none of the mentioned media or only with a very minimal frequency.

Figure 4.

Evolution of news consumption profiles (obtained from hierarchical clustering) over time.

Multivariate Analyses

Figure 5 displays the results from the multilevel linear regressions explaining the level of trust in government. The results are discussed in relation to the research questions and hypotheses outlined earlier. Hypothesis 1 (H1) posits that individuals with stronger perceptions of health or economic risks—whether personal or societal—will exhibit lower levels of trust in the government. Hypothesis 2 (H2) suggests that higher exposure to news media content emphasizing health and economic risks is associated with lower trust in government. Hypothesis 3 (H3) states that the impact of media exposure on trust in government is moderated by individuals’ risk perceptions, with those holding high-risk perceptions experiencing a stronger decline in trust with greater media exposure.

Figure 5.

Multilevel linear regression with unstandardized coefficients.

The findings indicate that risk perceptions related to societal and individual health do not significantly influence trust in government, contrary to H1. However, economic risk perceptions at the societal level do show a significant negative impact (estimate = −0.54, p < .001), supporting H1 in part. This suggests that while health risk perceptions did not affect trust as expected, economic concerns were more influential, aligning with theories of economic anxiety impacting political attitudes.

Referring back to RQ2 from Figure 1, the analysis shows that exposure to media coverage emphasizing the “costs” of the pandemic negatively impacts trust in government (estimate = −0.26, p < .001), supporting H2. However, exposure to media content on COVID-19 “cases” does not show a significant effect, indicating that not all types of pandemic-related media content have the same influence on trust. This underscores the selective impact of media exposure depending on the content type.

In line with H3, interactions between media exposure and risk perceptions were examined. The results show limited significant interaction effects, except for the interaction between economic risk perceptions and exposure to “costs” (estimate = −0.02, p < .05). This finding partially supports H3, indicating that for individuals with higher economic risk perceptions, greater media exposure to cost-related content correlates with a stronger decrease in trust. This highlights how personal concerns about economic stability can intensify the negative impact of certain media narratives on trust in government.

Among the sociodemographic variables, political orientation (left-right self-positioning) and age cohort have notable impacts on trust. More right-leaning respondents exhibit lower trust in government (estimate = −0.03, p < .001), which reflects broader patterns of political polarization influencing trust. In addition, older respondents show higher trust compared to younger cohorts, supporting literature on generational differences in trust levels during crises. The analysis also incorporates control variables for the different COVID-19 waves, which reveal significant effects on trust in government. Specifically, the findings indicate that trust levels decreased progressively across successive waves, with the most substantial decline observed during wave 4 (estimate = −2.44, p < .001). This trend highlights how public trust in government eroded as the pandemic continued.

Looking at the interaction effects, Figure 5 shows that, when associated with media exposure to “costs,” the focus on societal risks (both health and economy related) has a significant impact on trust in government. Figure 6 illustrates the interaction effects between risk perceptions at the societal level (economy on the left and health on the right) and exposure to “costs” related news. It shows a different impact of risk perceptions about societal economy on the level of trust in government by the level of media exposure to “costs” (left pane). For instance, respondents with a high exposure to “costs” related media content display higher levels of trust in the government with each unit increase in societal economy risks perception, whereas respondents with a low media exposure are less trusty of the government with each unit increase in societal economy risks perception (left pane). Figure 6 also shows that increasing media exposure to “costs” is associated with higher levels of trust in government for each unit increase in risk perceptions about societal health (right pane).

Figure 6.

Interaction effects between societal risk perceptions and exposure to costs on trust in government.

Discussion and Concluding Remarks

Descriptive findings reveal a consistent decline in trust toward the government over time, indicating a growing sense of skepticism or diminished confidence in political institutions among the surveyed population. A similar but less pronounced trend is evident in trust toward parliament. In addition, they indicate a decrease in overall media consumption over time, yet the selection of news outlets remains relatively unchanged. This decline could be attributed to factors such as news avoidance and news fatigue (de Bruin et al. 2021). Moreover, the coverage of the pandemic notably does not vary strongly across different media outlets, suggesting a high coherence among outlets when it comes to topical coverage of the crisis. The Kronenzeitung emerged as the most-read newspaper, while a consistent group identified as “news deprived” consumed very little or no news. These segments exhibited differing levels of trust in government, with the “news-deprived” group displaying the lowest trust. This is mirroring literature showing that those with the least support of government and mainstream politics are also most likely to turn away from legacy media outlets (Udris et al. 2022).

The first hypothesis posited that individuals concerned about the future, especially regarding health and the economy on both personal and societal levels, would exhibit reduced levels of trust in government. The results highlight the direct impact of economic concerns on trust in government but show no significant direct influence of other concerns, particularly no discernible impact from individuals’ personal concerns. Furthermore, in line with hypothesis 2, exposure to media coverage regarding the economic “costs” of the pandemic negatively affected trust. A similar pattern is, however, not confirmed for the coverage of “cases.”

The third hypothesis proposed that high exposure to news media content about health and economic concerns would correlate with lower levels of trust in government. However, the findings demonstrate a contrary pattern, indicating that increased media exposure generally is related to higher trust in government across different levels of risk perception (related to the economy and health). There is one exception: Respondents with low media exposure to aspects related to the economic costs of the pandemic exhibit less trust in the government with each unit increase in societal economic risk perception. In other words, the more the economy is seen at risk and not strongly exposed to economic COVID-19 coverage relates to low levels of trust. One plausible reason for the contrary pattern observed is that media coverage may have included elements of reassurance or balanced reporting, leading to a more nuanced effect on trust. In addition, high media exposure could correlate with an informed public, which may interpret government actions more favorably depending on the context of the reporting.

This study contributes significantly to our understanding of trust in government and media consumption in several ways. First, it offers valuable insights into the longitudinal trends of trust in government and media consumption patterns, providing a better understanding of the evolving dynamics over time. Second, it highlights the stability in media consumption even during crisis situations, which can be valuable for targeted communication strategies and policy making. Third, while the study highlights the relationship between risk perceptions, media exposure, and trust in government, the findings point to areas that need more in-depth analysis. Specifically, the lack of significant effects from health risk perceptions suggests that trust in government may be shaped by broader contextual factors, such as economic or political dynamics, rather than individual health concerns alone. Future research should explore why economic concerns have a more pronounced impact compared to health-related worries. Overall, this study enriches the literature on trust in government and media consumption and holds practical implications for policymakers, media organizations, and those seeking to comprehend the dynamics of public trust in political institutions.

Several methodological challenges emerge when integrating survey and media data, with two particularly crucial for this paper. First, research has indicated that survey respondents might not always accurately recall their visits to specific websites or the frequency of their visits (Revilla et al. 2017). In addition, there is a tendency for respondents to overreport visits to online news websites (Guess 2015) and political articles (Vraga and Tully 2021). Nevertheless, it is plausible to assume that respondents accurately identify their preferred news sources. However, estimating the actual attention respondents allocate to news content remains challenging. It is unrealistic to assume that respondents consume the entirety of their preferred news sources (Wüest 2018). Moreover, Nelson and Webster (2017) highlight that news websites spanning the political spectrum attract ideologically diverse audiences.

The second challenge pertains to the integration of survey and content data, involving specific content features such as visibility, topics, tonality, and entities. Studies have utilized these features individually or in combination, applying various weights (e.g., adjusting recent/old content). While these features can be merged, adopting a theory-based approach is vital in making suitable choices (De Vreese 2014; De Vreese et al. 2017). The selection of media features should align with the specific research question (Hopmann et al. 2011) and the formal theory underpinning the research (e.g., agenda-setting, selective attention, and priming).

Another challenge relates to the effect of external events on public trust in government. Indeed, Austria experienced various political scandals that had undermined public trust in political authorities already before the COVID-19 pandemic. For instance, the so-called Ibiza-Affäre (or Ibiza-gate) was a political scandal in Austria involving the former vice chancellor of Austria and the leadership of the Freedom Party (FPÖ) on May 17, 2019 by the publication of a secretly recorded video showing opposition politicians discussing their party’s intentions, notably for receiving positive news coverage in return for government contracts (Eisele et al. 2022). Such exogenous events can influence public opinion and perceptions about (political and media) institutions strongly, notably by leading to latent political mistrust and defiance.

There exist several potential future research trajectories that could extend upon the findings and contributions of this study. First, researchers could persist in tracking and analyzing long-term trends in trust toward government and media consumption. This exploration could specifically investigate reasons behind potential rises or sustained low levels of trust in government within public opinion. Second, future research could delve deeper into establishing the causal relationship between media exposure and trust in government, as well as examining its impact on political behavior. Third, with the evolving media landscape, it would be beneficial to conduct a more detailed exploration of how online and social media platforms influence trust in government. This could encompass examining the role of misinformation, echo chambers, and algorithmic biases in shaping public perceptions. Fourth, forthcoming research could scrutinize the strategies adopted by governments to either rebuild or uphold trust during periods of crisis or declining trust. This could involve content analysis of government communications or surveys targeting government spokespersons. Fifth, to consider potential political and socio-economic divisions, the study could focus on different subgroups within the population. For instance, examining people’s willingness or status regarding vaccination (especially pertinent after February 2022 for Austria).

Regardless of these limitations and potentials for future research avenues, this study makes important steps forward in longitudinal perspectives on media and government support based on multiple data sources and suggests in important ways how such analysis may inform media and government practices in future crisis situations.

Footnotes

Data Availability Statement

The panel survey data used for this study are available at https://viecer.univie.ac.at/en/projects-and-cooperations/austrian-corona-panel-project/. The media data from the Austria Press Agency (APA) can be accessed for scientific purposes here via an Application Programming Interface (API).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Maud Reveilhac

Hajo Boomgaarden

Notes

Author Biographies

Dr. Maud Reveilhac has a background in political science, social psychology, and survey research. The integration and complementarity of various data sources for the study of public opinion, as well as the transferability and adaptability of computational (social) research methods, are at the center of her research. She is currently Post-doc at the Department of Communication and Media Research at Zurich University. She is also involved in research to enhance the reproducibility and replicability of research methods and processes.

Hajo Boomgaarden (Ph.D University of Amsterdam) is Professor for Empirical Social Science Methods at the Department of Communication, University of Vienna. He co-leads the Computational Communication Lab. His expertise is in various aspects of political communication and in computational social science methods.

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News media and citizens’ trust toward authorities in times of crisis

Abstract

Keywords

Introduction

Media, Risk Perceptions, and Trust in Government

The Importance of Media Coverage in a Crisis

Trust in Government and Citizens’ Evaluation of Political Authorities During Crisis

Media and Trust During COVID-19 in Austria

Linking Strategy: Survey and Media Data

Data and Method

Austrian Corona Panel Project

APA Media Data

Measures

Data Linking Strategy

Analytical Strategy: Exploratory Analysis and Multilevel Modeling

Results

Descriptive Analyses

Multivariate Analyses

Discussion and Concluding Remarks

Footnotes

Data Availability Statement

Declaration of Conflicting Interests

Funding

ORCID iDs

Notes

Author Biographies

References