Hide and seek: The connection between false beliefs and perceptions of government transparency

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Implications

Concerns over government transparency (the quantity and quality of information made available to the public by governments and the relevance of that information for evaluating government performance [Williams, 2015]) have gained global currency over the past few decades, with more than half of United Nations members now having access to information laws (McIntosh, 2014). Transparency has come to be considered a norm of democratic governance, an essential ingredient for making informed political decisions and holding governments accountable. In this context, transparency has been offered as a solution to fight misinformation and increase trust in government (OECD, 2020). Yet, the operation of power still appears opaque for many citizens (West & Sanders, 2003) and the current era continues to be described as “the misinformation age” (O’Connor & Weatherall, 2019). We argue that researchers should pay more attention to citizens’ perceptions of transparency and get a better understanding of how these perceptions are related to false beliefs citizens may hold. 

Transparency perceptions are shaped by actual government transparency about the decision-making process, policy content, and policy outcomes. If we take the example of stay-at-home orders, a government being transparent could provide information about (1) the rationale behind the decision to implement this measure (e.g., by making available projections of cases and deaths with and without the measure); (2) what stay-at-home orders mean exactly and how they will be enforced; and (3) how effective they were and other consequences they might have had. However, perceived transparency can be very different from actual transparency because of citizens’ media consumption behaviors and underlying opinions about the governing party or the issue in question. Many studies demonstrate the importance of source credibility [the perceived expertise or trustworthiness of a source of information] on the acceptance of a message (Pornpitakpan, 2004), with citizens who trust the government being more likely to believe that they provide complete and accurate information (Mabillard & Pasquier, 2015). For instance, generalized political mistrust was a common reason for questioning the truthfulness of information provided by governments during the COVID-19 pandemic (Enria et al., 2021). Therefore, it is striking that government transparency is presented as one of the principal ways of fighting misinformation (OECD, 2020) when those holding false and conspiratorial beliefs are the most likely to reject information coming from government agencies (Motta et al., 2020), and information disclosure can increase distrust among already skeptical citizens (Crepaz & Arikan, 2021). 

We define false beliefs as beliefs that are inconsistent with the available evidence (O’Connor & Weatherall, 2019). Conspiratorial beliefs constitute one type of false beliefs. Conspiracy theories are based on the idea that powerful organizations are involved in a secret plan that would have negative consequences for everyday people. As such, citizens holding conspiratorial beliefs tend to perceive powerful groups, including the government, as fundamentally deceptive (Wood et al., 2012). Individuals tend to turn to conspiracy theories when they experience uncertainty or a lack of control, making conspiracy theories particularly salient during crises like a pandemic (van Prooijen, 2018). False and conspiratorial beliefs may lead to more negative perceptions of transparency because they undermine authoritative information and call into question the institutions that spread this information (Connolly et al., 2019; Marietta & Barker, 2018). For example, believing that governments impose lockdowns “when COVID-19 is no worse than the flu” casts doubt on the actions and information disseminated by governments and other authoritative agencies (e.g., health agencies), with negative consequences for perceptions of transparency, trust, and the acceptance of official information. The erosion of these kinds of transparency perceptions, in turn, weakens motivation to comply with public health recommendations (Quinn et al., 2013).

The relationship between false beliefs and perceptions of transparency is often simply assumed or relegated to the background (with the focus being on trust in government) but rarely demonstrated empirically. Using both closed and open-ended questions from a Canadian panel survey, we show that greater endorsement of COVID-19 false beliefs (1) increases the likelihood of having negative perceptions of government transparency; (2) is strongly connected to changes in perceptions of transparency over time; and (3) influences how citizens explain their negative perceptions of transparency. Lastly, we demonstrate the importance of these findings by showing that negative transparency perceptions are associated with a decline in voting intentions, trust in government, and satisfaction with democracy. 

The results have important implications for research on the consequences of misinformation and highlight the need (and provide indications) for improving perceptions of government communication. First, we contribute to existing scholarship by showing that false beliefs can influence government evaluations and, by so doing, can reduce political support. This dynamic is not conducive to effective accountability. Indeed, if transparency perceptions are distorted by misinformation, then governments could be misguidedly punished or rewarded for actions they did not commit. For instance, we find evidence that false beliefs and negative perceptions of transparency are associated with a decline in voting intentions for the governing provincial party.

Second, our results imply that governments need to do more to attain the desirable result of having a population that believes that their decisions are made transparently and in an informed way. Perceptions of government transparency are particularly important because those who believe the government is acting transparently are more likely to trust government actions and feel empowered to act, increasing the likelihood that they adopt preventive health behaviors during major crises like a pandemic (Lieberoth et al., 2021; Quinn et al., 2013). The high prevalence of false beliefs (see Appendix A for descriptive statistics on belief in COVID-19 misinformation) and the fact that citizens with low levels of trust and high levels of conspiratorial thinking are inclined to selectively look for information that confirms their beliefs (Romer & Jamieson, 2021) make the task of improving perceptions of transparency harder but no less important. To effectively reach the misinformed public, fight misinformation, and bolster trust in government, an effective communication strategy needs to consider both the framing and delivery of messages. In terms of framing, clear and empowering messages might be particularly effective in transforming the negative emotions that often cause conspiratorial beliefs, such as uncertainty and a lost sense of control, into a more constructive mindset (van Prooijen, 2018). Because misinformed populations are more likely to reject any information coming from authorities, delivering messages or engaging in counter speech with a diversity of sources that are trusted among populations vulnerable to misinformation, including officials who share group characteristics, scientists, co-partisans, community leaders, or even social media influencers, makes it more likely the message will be encountered, be accepted, and increase trust in government actions (Connolly et al., 2019). 

Findings

Finding 1: COVID-19 false beliefs increase the likelihood of having negative perceptions of government transparency.

Using ordinary least squares regression, we examined the association between the average perceived truthfulness of six COVID-19 false statements (e.g., “hydroxychloroquine is an effective treatment against COVID-19”), grouped into a false beliefs index, and two outcome variables measuring perceptions of transparency. The two regression models control for trust in scientists, partisan identification, ideology, news consumption, and socio-demographic characteristics (age, gender, education, region). The stronger one held COVID-19 false beliefs, the more likely they were to report that the government is not transparent about what influences its decisions (β = .34, 95% CI = [.24, .45], p < .001) and governments are hiding information about the pandemic (β = .65, 95% CI = [.57, .74], p < .001) (see Figure 1). The stronger connection between false beliefs and perceptions that governments are hiding information could be explained by the fact that hiding information is more clearly intentional than a lack of transparency, which can be caused by negligence or a deficient communication strategy. Citizens thus seem to draw a distinction in their evaluations between lack of transparency and information hiding, a more extreme form of non-transparency. These results have important implications for political support, given that false beliefs and negative transparency perceptions are associated with a decline in voting intentions for the provincial governing party, political trust, and satisfaction with democracy over time (see Appendix B for more information about these supplementary analyses). 

It is likely that those who believe the information provided by governments is insufficient or not truthful will seek alternative information sources and be more susceptible to misinformation, especially in a context of uncertainty like a pandemic. Consequently, the relationship between false beliefs and negative perceptions of transparency could be mutually reinforcing over time. To increase our confidence in the findings, we examined how false beliefs are associated with changes in perceptions of transparency (next subsection) and used entropy balancing to estimate the effect of holding false beliefs among people comparable on the relevant covariates. Doing so does not alter our conclusions, as shown in Appendix C.

Finding 2: COVID-19 false beliefs are associated with changes in perceptions of transparency over time.

While perceptions of transparency have slightly improved during the pandemic, those endorsing three or more false statements out of six consistently believed that information is being hidden (Figure 2), contributing to the polarization of perceptions of government transparency over time. Using OLS regression, we examined the relationship between the average perceived truthfulness of COVID-19 false statements and changes in perceptions that governments are hiding information between June 2020 and January 2021, controlling for the same set of variables as above (with trust, partisan identification, and ideology measured at t-1). We find that individuals holding false beliefs were significantly more likely to start or continue to believe that governments are hiding information throughout the pandemic (β = 4.13, 95% CI = [3.10, 5.16], p < .001). The model explains 28% of the variance (R2=.28, F(16,518)=8.25, p<.001), almost twice as much as the same model without the false beliefs index (R =.17, F(15,519)=5.25, p<.001). The relationship between false beliefs and changes in perceptions of transparency holds when controlling for changes in political trust or in evaluations of governments’ pandemic response (Appendix B). Perceptions of transparency thus seem to be distinct from trust and general government evaluations and to be associated with false beliefs citizens hold about the pandemic. 

Finding 3: Citizens use their false beliefs to justify their negative perceptions of transparency. 

We used a multinomial logistic regression to examine how the average perceived truthfulness of COVID-19 false statements predicts the type of answers that respondents provided to the following open-ended question “Can you briefly explain what you think governments are hiding about the coronavirus pandemic?”. Responses were coded into four categories: positive perceptions of transparency, the handling of the pandemic, a general mistrust of government, and government manipulation of the public. Respondents who fell into the “manipulation” category mostly provided explanations that contained misinformation, including: (1) COVID-19 was planned or purposely created in a laboratory; (2) the coronavirus does not exist, is benign, or severely exaggerated; or (3) the pandemic is a means for elites to make money, control the population, or impose an agenda on the general population.

The results suggest that false beliefs shape how respondents rationalize their perception that governments are hiding information. As shown in Figure 3, a change from being certain that all false statements are false (score of 0 on the perceived truthfulness index) to being certain that all the false statements are true (score of 1) increases by 55.06 percentage points (95% CI = [39.65, 69.27], p < .001) the predicted probability of providing an answer that falls into the manipulation category. As explained, that category mostly included misinformation-based explanations, showing that those who confidently endorse COVID-19 false statements tend to justify their negative perceptions of transparency based on the false beliefs they hold. 

Robustness

Some of the findings might seem tautological, given that the idea that elites have a secret agenda is core to the definition of a conspiracy theory. However, complementary results presented in Appendix C suggest that some items that are not expressly conspiratorial are independently associated with perceptions that governments are hiding information about the pandemic. We also show that our items contribute differently to different subdimensions (origin vs. severity of the pandemic), each of which significantly contributes to negative perceptions of transparency. When asking respondents about the perceived truthfulness of statements, we also included true statements to avoid the bias associated with only asking about false statements. The results hold when including these statements and measuring false beliefs in terms of the difference between the perceived truthfulness of true and false statements (i.e., when considering the acceptance or rejection of true information, see Appendix C). They also hold when using the number of false beliefs held as our main independent variable and when accounting for uncertainty (number of statements with a perceived truthfulness of 5/10). Changing how we measure perceptions of transparency, by coding perceptions that governments are hiding information into “yes,” “no,” and “unsure” categories, for example, also does not alter our conclusions. 

Given that there exist many defensible ways to analyze the same data, we used specification curve analysis to make sure that our results would have been similar had we made different analytical choices. Specifically, we tested whether the relationship between false beliefs and perceptions of transparency depends on the variables included in the model by simulating the results of 50,000 linear regressions of perceptions that governments are hiding information on false beliefs and a subset of control variables randomly drawn from the controls presented in Figure 1, plus trust in government, identification with opposition parties, generalized social trust, perceived threat of becoming unemployed, life satisfaction, and emotions caused by COVID-19 (fear, anger). The regression coefficients for false beliefs range from 0.56 to 0.77, showing that, across all specifications, there is a strong positive relationship between false beliefs and perceptions that governments are hiding information (Appendix C). 

Our research design does not allow to completely rule out the possibility that the main relationship goes in the other direction (i.e., that perceptions of transparency cause false beliefs) or that an omitted variable might explain the results. The analysis is correlational in nature, and the statistical techniques we use to better isolate the effect of false beliefs by making individuals who hold false beliefs more comparable to those who do not (entropy balancing) and to show that the results are similar when making different analytic choices (specification curve analysis) are limited by the variables included. We nevertheless believe that individuals using their false beliefs to justify their negative perceptions of transparency constitutes evidence that false beliefs do shape perceptions of transparency.

Methods

This study used Canadian opinion data drawn from the Citizens’ Attitudes Under the COVID-19 Pandemic project. Surveys were administered in April 2020, June 2020, and January 2021 to a sample of adult Canadians drawn from Léger’s Internet panel of participants, the largest proprietary panel in Canada. A quota-based sample (age, gender, education, region, language) of around 1,000 respondents answered each wave. The second and third waves include respondents who answered the previous wave(s) and additional respondents to meet the target sample size. 600 respondents answered both Wave 2 and 3, on which most of the results are based. All our analyses were run on data weighted to age, gender, education, and province of residence as provided by the Canadian census.  

We estimated the relationship between false beliefs and perceptions of transparency using ordinary least squares (OLS) regression (closed-ended responses) and multinomial logistic regression (open-ended responses). Building on the literature on political support and information processing (see Appendix E), we controlled for socio-demographic variables (age, sex, education, region), identification with the governing party at the federal and provincial levels, ideology, trust in scientists, and frequency of exposure to information about COVID-19 on traditional and social media. Descriptive statistics and details about the construction of the dependent and independent variables are respectively presented in Appendices A and D. All independent variables have been rescaled from 0 to 1 in all analyses. 

False beliefs were only measured in the third wave (January 2021) using respondents’ evaluations of the truthfulness of six false statements about the COVID-19 pandemic, on a scale from 0 (not likely at all to be true) to 10 (extremely likely to be true). Three statements shared characteristics of conspiracy theories: (1) the government is exaggerating the risks of the coronavirus to be able to restrict people’s rights and freedoms; (2) the virus was created by China to increase its power in the world; and (3) the virus was created by large corporations because some of them can directly profit from it. The three other statements constituted health-related misinformation: (1) the prolonged use of masks can lead to CO₂ intoxication or oxygen deficiency; (2) hydroxychloroquine is an effective treatment against COVID-19; and (3) coronavirus figures are inflated because a significant number of people who tested positive were not infected with the virus. While health-related misinformation does not necessarily constitute conspiracy theories, some of these statements (e.g., inflated numbers) have been included as part of various conspiracy theories during the pandemic. The percentage of people endorsing each statement varies from 15.5% (hydroxychloroquine) to 26.6% (false positives). The false beliefs items are highly correlated (Pearson’s r ranging from r(1003) = .54, p < .001 to r(1003) = .78, p < .001, as detailed in Appendix A), and the Cronbach’s alpha is 0.91, also indicating that these items are closely related. We thus created a false beliefs index by averaging the perceived truthfulness of the false statements.

We measured perceptions of transparency using (1) the level of agreement with the statement that the provincial government lacks transparency on what drives its decisions (4-point agree-disagree scale); (2) the perceived probability that governments are hiding information about the pandemic (0-10 scale); (3) changes in perceptions that governments are hiding information about the pandemic (-10 to 10); and (4) responses to an open-ended question about what governments are hiding about the pandemic. The open-ended question was only asked to those who rated the probability that governments are hiding information at least a 4 out of 10, given that one needs to believe that governments are hiding information to explain this belief. Open-ended questions are particularly useful for understanding how people rationalize their attitudes and behaviors, as this type of question elicits a broad range of answers and “[…] do not cue respondents to think of particular causes or treatments” (Iyengar, 1996, p. 64). Respondents were exposed to the false statements after answering the open-ended question, so any priming effect is very unlikely. The responses were manually coded by two coders (Cohen’s kappa = 0.88, suggesting that there was a high level of agreement between the two raters) to distinguish between those who think governments are manipulating the public (misinformation-based answers), those who express a general mistrust of government, those who question the handling of the pandemic, and those who have positive perceptions of government transparency. Responses were coded into a single category. When answers overlapped with multiple response options, respondents referring to a conspiracy theory were automatically coded into the manipulation category. The mistrust category was used as a residual category when no other explanation was provided (e.g., answers expressing mistrust and discussing the handling of the pandemic were coded into the handling category). When there was disagreement between the coders (less than 12% of answers), we randomly kept the code of one of the two coders. Using another method for dealing with disagreement does not change the results, as reported in Appendix C.