Governments of all stripes – autocratic and democratic – rely on citizens to comply with official rules for these edicts to be effective. Yet achieving such compliance is often tricky, in particular where this imposes high costs on individuals. Governments can achieve popular compliance either by force, through sanctions, or by encouraging voluntary obedience. The latter, consensual, route to compliance is widely accepted to be more effective and cost-efficient than the former, coercive, route (Mulder et al., Reference Mulder, van Dijk, De Cremer and WIlke2006; Trinkner and Tyler, Reference Trinkner and Tyler2016). Yet the consensual route relies on citizens self-policing, and risks defection. This raises a question about the conditions in which citizens are likely to self-police and to comply with collective rules. Since the spread of SARS-CoV-2 (henceforth, coronavirus) in 2019, this question has been a major pre-occupation of governments across the world, for whom public compliance with rules around personal hygiene and social distancing represents – alongside a public immunization programme – the principal prophylactic in the fight against the coronavirus.
This study explores the role of a factor widely deemed to be central in encouraging citizens to comply with collective rules, namely political or institutional trust (henceforth ‘trust’). Trust is widely believed to be a central factor in stimulating individual compliance, yet its role during the current pandemic as well as in previous pandemics has sometimes been found to be limited. One reason for this is that trust is but one factor among many likely to shape compliance. When other factors are present and working to stimulate compliance, there may be less of a role for trust. Yet when other motivating conditions are weak or absent, trust may have more of an effect. This suggests that the effect of trust on compliance might be contingent rather than absolute. In the context of the coronavirus, a particularly important motivating factor is likely to be individuals’ fear of exposure to the virus and of contracting coronavirus disease 2019 (COVID-19). Fear may motivate individuals to comply with official rules largely irrespective of whether they trust government. Yet when fear is less widespread, compliance may depend more heavily on trust. These effects are likely to manifest at individual points in time and also over time. At the outset of the pandemic, public fear of the newly identified coronavirus and its effects was likely to have been high. These fears are likely to have stimulated individuals to comply with official restrictions without much need for them to trust the source of these rules. Yet as the pandemic progressed and people became more familiar with the coronavirus, anxieties are likely to have waned and public compliance to have become more dependent on trust.
This study explores the effects of trust and fear on people’s compliance with official coronavirus restrictions over the duration of the pandemic. It extends previous analyses that have identified how fear moderates the effects of trust on compliance at single points in time by exploring how these relationships change over time. In so doing, it extends our understanding about how public compliance with important social rules can be maximized over the course of a crisis like a viral pandemic. The study also examines whether the role of trust in shaping compliance is particularly important for certain types of individuals. In particular, it explores whether the relationship between trust and compliance is most pronounced among people facing the highest costs of compliance. For such individuals, these costs are only likely to be internalized if they trust those responsible for official restrictions and rules. Among individuals for whom official restrictions are less costly, however, compliance is likely to be less dependent on trust. Overall, the study provides valuable new evidence about the association between trust and compliance, both over time and among particular social groups.
Trust and compliance with collective rules
The conditioning role of fear
Individuals comply with collective obligations for a variety of reasons. For the purpose of this study, two factors identified by Feldman (Reference Feldman and Levi-Faur2013) are of particular relevance. The first factor comprises instrumental considerations and suggests that individuals comply with collective obligations primarily due to assessed costs and benefits. The costs include fear of punishment for non-compliance, including sanctions, financial penalties and, in the context of the coronavirus pandemic, infection from a harmful virus (Rosenstock, Reference Rosenstock1974; Brewer et al., Reference Brewer, Chapman, Gibbons, Gerrard, McCaul and Weinstein2007; Bish and Michie, Reference Bish and Michie2010; Cruwys, Reference Cruwys and Jetten2020; Dryhurst et al., Reference Dryhurst, Schneider, Kerr, Freeman, Recchia, van der Bles, Spiegelhalter and van der Linden2020). The second factor comprises normative considerations and suggests that individuals comply with collective obligations primarily due to the rule-making agency’s perceived expertise (Feldman, Reference Feldman and Levi-Faur2013) and/or legitimacy and moral status (Tyler, Reference Tyler2006). On the normative account, compliance arises from individuals’ beliefs that the source of official rules is knowledgeable and holds a compelling claim to obedience.
It is widely assumed that people’s compliance with official rules is shaped by normative considerations, often involving assessments of official actors’ trustworthiness (Bish and Michie, Reference Bish and Michie2010; Bonell et al., Reference Bonell, Michie, Reicher, West, Bear, Yardley, Curtis, Amlot and Rubin2020; Habersaat et al., Reference Habersaat, Betsch, Danchin, Sunstein, Böhm, Falk, Brewer, Omer, Scherzer, Sah, Fischer, Scheel, Fancourt, Kitayama, Dubé, Leask, Dutta, MacDonald, Temkina, Lieberoth, Jackson, Lewandowsky, Seale, Fietje, Schmid, Gelfand, Korn, Eitze, Felgendreff, Sprengholz, Salvi and Butler2020; van Bavel et al., Reference Van Bavel, Baicker, Boggio, Capraro, Cichocka, Cikara, Crockett, Crum, Douglas, Druckman, Drury, Dube, Ellemers, Finkel, Fowler, Gelfand, Han, Haslam, Jetten, Kitayama, Mobbs, Napper, Packer, Pennycook, Peters, Petty, Rand, Reicher, Schnall, Shariff, Skitka, Smith, Sunstein, Tabri, Tucker, van der Linden, van Lange, Weeden, Wohl, Zaki, Zion and Willer2020; Cairney and Wellstead, Reference Cairney and Wellstead2021). Trust has been found to positively predict observance of official rules during previous viral pandemics (Blair et al., Reference Blair, Morse and Tsai2017) as well as during the current coronavirus pandemic (Brodeur et al., Reference Brodeur, Grigoryeva and Kattan2020; Olsen and Hjorth, Reference Olsen and Hjorth2020; Robinson et al., Reference Robinson, Ripberger, Gupta, Ross, Fox, Jenkins-Smith and Silva2021; Schmelz, Reference Schmelz2021).Footnote 1 These findings have often arisen from studies employing a cross-sectional design, although longitudinal studies of compliance during the coronavirus pandemic have also highlighted a significant positive association with trust, at the individual level (Chan et al., Reference Chan, Brumpton, Macintyre, Arapoc, Savage, Skali, Stedelmann and Torgler2020; Wright et al., Reference Wright, Steptoe and Fancourt2021; Han et al., Reference Han, Zheng, Cristea, Agostini, Belanger, Gutzkow, Kreienkamp and Leander2021; Nivette et al., Reference Nivette, Ribeaud, Murray, Steinhoff, Bechtiger, Hepp, Shanahan and Eisner2021) and at the aggregate level (Bargain and Aminjonov, Reference Bargain and Aminjonov2020). Moreover, specific distrust-inducing events – such as the breaking of official coronavirus rules by high-profile public actors – have been shown to correspond closely with declines in compliance rates among the public (Fancourt et al., Reference Fancourt, Steptoe and Wright2020).
Yet trust does not appear to have a consistently positive association with people’s compliance with collective coronavirus rules. Some studies have found only a modest association, or no association at all, between individual trust and observance of official restrictions (Barrios et al., Reference Barrios, Benmelech, Hochberg, Sapienza and Zingales2020; Brouard et al., Reference Brouard, Vasilopoulos and Becher2020; Guglielmi et al., Reference Guglielmi, Dotti Sani, Molteni, Biolcati, Chiesi, Ladini, Maraffi, Pedrazzani and Vezzoni2020; Weinberg, Reference Weinberg2020; Woelfert and Kunst, Reference Woelfert and Kunst2020). Other studies identify an association between trust and compliance in some countries but not in others (Travaglino and Moon, Reference Travaglino and Moon2021. We can also point to countries – such as Singapore – whose citizens manifest high rates of political trust, yet whose rulers felt the need to impose strict coronavirus regulations when informal restrictions went ignored (Wong and Jensen, Reference Wong and Jensen2020). Conversely, countries such as Italy with low rates of trust experienced high levels of public compliance in the early stages of the pandemic (Guglielmi et al., Reference Guglielmi, Dotti Sani, Molteni, Biolcati, Chiesi, Ladini, Maraffi, Pedrazzani and Vezzoni2020).Footnote 2 A systematic review of public compliance with coronavirus measures found that, among the 19 studies exploring the role of trust in government, just five identified a positive impact on compliance, while three identified a negative impact and 11 no statistically significant impact (Kooistra and van Rooij, Reference Kooistra and van Rooij2020: Table S2).
One reason for these varied findings is that analyses often differ in the account they take of factors that might confound the relationship between trust and compliance and which, if incorporated into empirical models, might weaken or eliminate the independent effect of trust. One such factor is fear of the coronavirus – an instrumental source of compliance – measured in terms of perceived personal or communal susceptibility to infection and/or illness. Indeed, some studies which model public compliance as a function of individual fear of COVID-19 have found that attitudes such as trust and respect for authority exert no significant independent effects on the outcome (Clark et al., Reference Clark, Davila, Regis and Kraus2020; Harper et al., Reference Harper, Satchell, Fido and Latzman2020; Jørgensen et al., Reference Jørgensen, Bor and Petersen2021; Murphy et al., Reference Murphy, Williamson, Sargeant and McCarthy2020). These findings corroborate the results of data collected among Dutch citizens in 2009 during the H1H1 influenza pandemic, which showed that people’s engagement with protective behaviour was predicted by their fear of the virus rather than by how much they trusted government (van der Weerd et al., Reference Van der Weerd, Timmermans, Beaujean, Oudhoff and van Steenbergen2011).
We might use these results to incorporate measures of fear into our models of compliance, and more particularly to specify a conditional relationship between the core variables. In this conditional model, compliance rests primarily on fear or trust. Where fear is high there is less of a role for trust in stimulating compliance; yet where fear is low, trust may ‘take up the slack’ in encouraging compliance. Hence, compliance with COVID-19 rules is likely to be weakly associated with trust among individuals who are fearful of the coronavirus. Yet among less fearful individuals, compliance is likely to be more strongly associated with trust. Existing studies have corroborated these intuitions, showing that trust is associated with compliant behaviour particularly among individuals perceiving a low level of risk from the coronavirus. Among individuals perceiving a greater risk, compliance is less closely associated with trust (Jørgensen et al., Reference Jørgensen, Bor and Petersen2021; Lalot et al., Reference Lalot, Heering, Rullo, Travaglino and Abrams2021; Kittel et al., Reference Kittel, Kalleitner and Schiestl2021a).Footnote 3
To date, however, analysts have predominantly explored the conditional relationship between trust, fear, and compliance in a static perspective and by focusing on differences between individuals. Yet we anticipate the effects of trust and fear on compliance as likely to change over time, and it is these dynamics on which this study focuses. The factors associated with individual compliance with coronavirus rules have been shown to have shifted as the pandemic progressed (Wright and Fancourt, Reference Wright and Fancourt2021), although little is known about whether the association between trust, fear, and compliance has altered over time. The primary purpose of this study is to fill this gap by identifying how the effects of trust on compliance conditional on fear have changed over the course of the pandemic.
Individual variation in the role of trust
One conditionality in the association between trust and compliance thus concerns the presence and role of other factors, notably fear. A second conditionality concerns differences between individuals. Here, we assume that the association between trust and compliance depends on the costs an individual faces from complying with official rules. This assumption draws on Hetherington’s (Reference Hetherington2005: 49–50, 87–98) research, which shows that the effect of trust on people’s agreement with government decisions varies according to the individual costs entailed by those decisions. Hetherington finds that trust is particularly closely associated with people’s acceptance of official decisions where these entail high individual costs. In such cases, citizens will only internalize these costs if they trust officials to have taken the decision wisely and for good reason. In the context of the coronavirus pandemic, this intuition suggests that trust will be most closely associated with compliance among people for whom official restrictions are particularly costly or onerous. Among individuals less adversely affected by the restrictions, compliance is less costly and thus less likely to depend on trust.
Hypotheses
Two key hypotheses arise from the preceding discussion, relating to the association between trust and compliance (a) conditional on fear and (b) conditional on individuals.
The first hypothesis concerns the over-time effect of trust on compliance conditional on fear. Ex ante, we might expect fear to have been strongly associated with compliance at the start of the pandemic, since people’s risk perceptions tend to be high when faced with a new, unknown threat (Slovic et al., Reference Slovic, Fischhoff, Lichtenstein and Slovic2000). As threats become more familiar, people’s perceptions of risk adjust (Sandman, Reference Sandman2012), suggesting that the association between fear and compliance might have declined over time. Assuming a conditional relationship between trust, fear, and compliance – such that at high levels of fear, the association between trust and compliance is weaker, while at low levels of fear, the association is stronger – we might expect waning levels of fear over time to be associated with a strengthened association over time between trust and compliance. In essence, as the association between fear and compliance lessens over the course of the pandemic, greater space opens up for trust, whose association with compliance is likely to strengthen. This suggests the following hypotheses about the dynamic relationship between trust, fear, and compliance:
H1a: At the start of the pandemic, individual compliance was predominantly shaped by fear rather than by trust. H1b: As the pandemic progressed, the association between fear and compliance weakened, and the association between trust and compliance strengthened.
The second hypothesis concerns variation in the association between trust and compliance between individuals. In particular, based on differences in individual costs of compliance with official restrictions, we expect trust to be particularly strongly associated with compliance among individuals facing high costs, and less associated with compliance among individuals facing low costs. Compliance costs take various forms, although we assume these are primarily economic. We assume, in particular, that official restrictions are particularly costly for economically deprived individuals, many of whom found it difficult to comply with rules on staying at home and avoiding travelling to work (Templeton et al., Reference Templeton, Guven, Hoerst, Vestergren, Davidson, Ballentyne, Madsen and Choudhury2020).Footnote 4 By contrast, compliance is likely to be less costly for affluent individuals who possess the financial reserves to cushion them from stay-at-home restrictions.Footnote 5 , Footnote 6 This suggests the following hypothesis about the types of individuals for whom trust is likely to be particularly important for compliance:
H2: The association between trust and compliance will be greater for low economic status individuals than for high economic status individuals.
Data, measures and method
Data
These hypotheses are explored on populations in three west European countries: Austria, Germany, and the United Kingdom (UK). While a previous study found the associations between trust and compliance with COVID-19 rules to be largely consistent across countries (Jørgensen et al., Reference Jørgensen, Bor and Petersen2021), another study identified variations in these associations (Travaglino and Moon, Reference Travaglino and Moon2021). Moreover, the finding of national invariance arose from a study conducted at a single point in time, towards the start of the pandemic. Given subsequent differences between countries in coronavirus infection and mortality rates, it makes sense to explore the association between trust and compliance across cases. Using the Oxford Supertracker, an online directory of population surveys on COVID-19 (Daly et al., Reference Daly, Ebbinghaus, Lehner, Naczyk and Vlandas2020), Austria, Germany, and the UK were identified as three of the few countries covered at the time by longitudinal surveys containing measures of all the key concepts.
The Austrian data derive from the Austrian Corona Panel Project (ACPP), which conducted surveys from late March 2020 (Kittel et al., Reference Kittel, Kritzinger, Boomgaaden, Prainsack, Eberl, Kalleitner, Lebernegg, Partheymuller, Plescia, Schiestl and Schlogl2021b).Footnote 7 Data were collected from an existing online panel, among citizens aged 14 years and above, using a quota sample.Footnote 8 The sample takes a panel format, with additional participants recruited at each wave to overcome attrition effects. Samples at each wave were ∼1,500. The German data derive from the COVID-19 Snapshot Monitoring (COSMO) project, which conducted surveys from early March 2020.Footnote 9 Data were collected from an existing online panel, among citizens aged 18 years and above, using a quota sample. Each wave comprises an independent cross section. Sample sizes at each wave were ∼1,000. The UK data derive from the COVID-19 Social Study, which conducted surveys from late March 2020.Footnote 10 Data were collected online, using convenience sampling and other targeted recruitment methods. The sample takes a panel format, with additional participants recruited at each wave to overcome attrition effects. Analytical samples at each wave vary in size from ∼6,000 to ∼38,000 participants.Footnote 11 Basic details of the methods employed by each country survey are provided in online Appendix 1.
To maximize comparability between the three cases, the analysis draws on data from the same number of waves (seven), stretching from April 2020 to February 2021, and selected to be broadly coterminous in timing (see Appendix 1). Individuals with missing data on any of the variables were excluded from the analysis. Post-stratification weights are employed on the Austrian and UK data (but are not available for the German survey) to correct for differential sampling and non-response rates.
Measures
Across the three national samples, similar, although not always identical, survey indicators were used to measure each of the central concepts. Question wordings are given in online Appendix 2, with descriptive statistics provided in Appendix 3.
Compliance is measured in the UK through a single question asking respondents whether they are following official recommendations to prevent COVID-19. Responses are recorded on a seven-point scale (1 = not at all, 7 = very much so). Compliance is measured in Austria and Germany through questions asking respondents about their behaviour over the past week in relation to wearing a protective mask when in public, keeping a distance from other people and staying at home except for necessities (Austria) or avoiding public places (Germany).Footnote 12 Responses were recorded on a five-point scale (1 = never behave in this way, 5 = always behave in this way). To test H1a/b, the responses to these three items are summed into a single compliance scale. To test H2 – which suggests that individual economic status is likely to moderate the effect of trust on compliance particularly when it comes to restrictions on travelling to work – the analysis employs the single item measuring whether people stayed at home (Austria) or avoided public places (Germany).
Political trust is measured through evaluations of national governments. In Austria, this is measured by a question on how much respondents trust the federal government ‘in the context of the corona crisis’.Footnote 13 Responses were recorded on an 11-point scale (0 = no trust at all, 10 = a lot of trust). In Germany, the question asks how much trust respondents have in the government ‘that they are capable of handling the new coronavirus well and properly’. Responses were recorded on a seven-point scale (1 = very low trust, 7 = very high trust). While in Austria the prime responsibility for dealing with the coronavirus pandemic rests with the federal government, in Germany this responsibility lies with the state governments (länder), although the federal government is closely involved in decision-making (Hegele and Schnabel, Reference Hegele and Schnabel2021). Consequently, when it comes to Germany, we anticipate that trust in the federal government will be important for public compliance, although we also explore the role of people’s trust in the state government. In the UK, respondents were asked about their ‘confidence’ in the UK government ‘that they can handle COVID-19 well’. Responses were recorded on a seven-point scale (1 = none at all, 7 = lots).Footnote 14
Fear of COVID-19 is measured in Austria by respondents’ estimate of the health hazard posed by the coronavirus to them personally and, separately, to the nation as a whole. Responses were recorded on a five-point scale (1 = very small, 5 = very large). Fear is measured in Germany by questions on the likelihood of infection (‘What do you consider to be your own probability of getting infected with COVID-19?’; seven-point response scale, 1 = extremely unlikely, 7 = extremely likely) and the consequences of infection (‘How severe would contracting COVID-19 be for you [how seriously ill do you think you will be]?’; seven-point response scale, 1 = not severe, 7 = very severe). Responses to the two questions were multiplied together to create a ‘risk’ variable.Footnote 15 In the UK, fear is measured by a question on whether ‘catching COVID-19’ and ‘becoming seriously ill from COVID-19’ were sources of worry over the past week (binary ‘yes/no’ response categories). Responses were combined to create a three-point (0 = no worry, 1 = some worry, 2 = very worried) risk scale.
Socio-economic status is measured by self-reported household income (measured monthly in net form in Austria and Germany; measured weekly or annually in the UK). In Austria, income was measured on a 10-point scale, in Germany, income was measured on a seven-point scale, while in the UK income was measured on a six-point scale. We retain these interval scales in our models (running from low income to high income), since measuring income in binary form would raise the question of where to draw the dividing point.
Our empirical models also control for demographic features identified in previous studies as shaping compliance with health-related behaviours (e.g. Bish and Michie, Reference Bish and Michie2010; Wright and Fancourt, Reference Wright and Fancourt2021; Kooistra and van Rooij, Reference Kooistra and van Rooij2020) and which are also frequently found to be associated with trust, namely age, education, and gender. Age is particularly important, since older people are more vulnerable to illness and mortality after contracting COVID-19.
Method
The association between trust and compliance conditional on fear (H1a/b) is analysed in two ways. The first uses individual survey waves to identify associations at particular points in time. The second uses data pooled across waves to identify the effects of trust and fear on compliance over the course of the pandemic. In the German case – where the data represent repeated cross sections of the population – dynamic effects are identified by fitting time interaction terms to the key variables. The pooled models fitted to the Austrian and UK data take advantage of their panel structure by specifying fixed-effects equations, which enable identification of the effects of time-variant factors – namely trust and fear – while eliminating the effects of potentially confounding time-invariant factors, such as demographic characteristics. The variation in levels of trust and fear over the period (see Figure 1) means that fixed-effects models are likely to provide efficient estimation of relationships (Allison, Reference Allison2009). Since we are concerned to identify temporal trajectories in our core relationships – which we anticipate being subject to fluctuation, given changes in infection and mortality levels and associated shifts in official restrictions (online Appendix 4) – the fixed-effects models include time interaction terms.
Figure 1. Trends in key variables.
When it comes to gauging the effects of trust on compliance among different economic status individuals (H2), cross-sectional models are employed using data from individual waves and pooled across waves. All data are normalized, to facilitate comparisons between countries.
Results
Distributions on the three key variables – compliance, trust, and perceived risk – over the eleven months from April 2020 are set out in Figure 1. When it comes to compliance, in Austria there is a dip immediately after the onset of the pandemic and the lockdown in March 2020, before a pickup from late summer. A similar U-shaped pattern of compliance is evident in the UK, and in Germany with the exception of mask-wearing (which increases over time). These trends broadly match changes in the nature of official restrictions (Appendix 4).Footnote 16 In the case of perceived risk, Austria and the UK see a decline immediately after the pandemic’s start, before levels of risk pick up from late summer and autumn. Levels of perceived risk in Germany are more stable over time. When it comes to trust in government, there is a stark decline in each country, although a pickup at the end of the period in the UK.Footnote 17
At the outset of the pandemic, then, governments in each country were presented with auspicious conditions for encouraging compliance with official restrictions: high levels of both trust and perceived risk among their populations. However, as the pandemic developed, people’s trust in government fell while, in Austria and the UK, the perceived risks of the coronavirus initially declined, before increasing from summer and autumn 2020.
To identify the effects of these factors on compliance, and in particular the effects of trust at different levels of fear, identical regression equations are fitted to the data from each country for each of the seven survey waves. The full results from these equations are shown in online Appendix 5. The key result relates to the interaction of trust and fear. In each country, and across almost all waves, this term yields a negative coefficient indicating that the effect of trust on compliance declines as individuals’ perceptions of risk increase.Footnote 18 To examine the separate effects of trust and fear on compliance over time, identical cross-sectional equations (omitting the interaction terms) are fitted to the data. The results (see online Appendix 6) show that, in Austria and the UK, the association between fear and compliance strengthened somewhat from spring 2020. The association between trust and compliance in both countries, and between both variables and compliance in Germany, remained broadly consistent over the period. There is little evidence from these repeated cross-sectional models that the effect of fear on compliance has waned over time.
To more robustly identify over-time changes in the effects of trust and fear on compliance, we pool observations across waves. The results from fixed-effects (Austria and UK) and ordinary least-squares (Germany) models are shown in online Appendix 7 and in graphic form in Figure 2.Footnote 19 The graphs highlight differences between countries both in the magnitude of the associations between trust and compliance and fear and compliance, and in the changes of these associations over the course of the pandemic. The German data suggest little obvious strengthening or weakening in the associations between trust and compliance and between fear and compliance; instead, we see trendless fluctuation in these associations. Yet the data from Austria and the UK – which represent within-individual change – provide clearer evidence of a strengthening association between trust and compliance, particularly during the pandemic’s early stages (April–June 2020). In Austria, within-individual increases in trust between April and June were associated with an 8.9 percentage point increase in compliance (the predicted probability of compliance associated with an increase in trust over the period rose from 0.02 to 0.11); the equivalent figure for the UK sample was 5.4 percentage points. The stronger association between trust and compliance does not arise, however, from a weakening association between fear and compliance. In fact this association also strengthened during the early stages of the pandemic, particularly in Austria.Footnote 20 Here, within-individual increases in fear between April and June 2020 were associated with a 16.4 percentage point increase in compliance; the equivalent figure for the UK sample was 2.3 percentage points.
Figure 2. Association of trust and fear on compliance, over time.
Note: Dotted lines show marginal effects from regression models in Appendix 7. Grey area indicates 95% Cls.
Overall, the results from both between-individual (Germany) and within-individual (Austria, UK) analyses do not suggest conditionalities in the effects of trust and fear on compliance over time; indeed, across the three countries, the dynamic effects of trust and fear on compliance appear fairly similar. We find no evidence that compliance was initially driven more by fear than by trust or that increases in the association between trust and compliance over time arise from weaker associations between fear and compliance.
We now turn to examine the conditionalities of trust between individuals, in particular between people facing different costs of compliance. We explore these conditionalities through repeated cross-sectional models, in which individual socio-economic status (measured by household income) serves as the key moderator. The results from these models are laid out in online Appendix 9. H2 anticipated that the interaction term for trust x income would be negative, indicating a stronger association between trust and compliance at low, than at high, levels of household income. In Austria, however, the relevant coefficients are all positive, although only in three of the seven waves do they achieve statistical significance (p < 0.05). The equivalent coefficients from the German and UK data are more mixed. Fitting the equations to data pooled across waves (Appendix 9, final column) shows that, in all three cases, the relationship between trust and compliance strengthens at higher levels of household income (Figure 3), although only in the Austrian case is the effect statistically significant (p < 0.05).
Figure 3. Effects on trust on compliance, by income.
Note: Dotted lines show marginal effects derived from regression models in Appendix 9. Grey areas indicate 95% Cls.
To confirm this result, we employed different indicators of economic status to proxy compliance costs. The first indicator involved employment security; in Austria, this was measured through respondents’ assessed likelihood of losing their job, while in Germany and the UK this was measured through respondents’ worry about losing their job. The second form involved financial hardship; in Austria, this was measured through respondents’ assessments of their household finances in three months, while in the other two countries this was measured through respondents’ worry about running into financial difficulties (Germany) and about their finances (UK).
The results from models incorporating these alternative indicators of economic status (reported in online Appendix 10) are somewhat mixed. In the job insecurity models, the across-wave interaction term with trust is positively signed in Austria, although negatively signed in Germany and the UK (none of the coefficients is statistically significant at p < 0.05). The financial concern models show a positive cross-wave interaction term with trust in Austria (significant at p < 0.05), suggesting that trust is more closely associated with compliance among financially optimistic, not financially pessimistic, individuals (the coefficient for the German sample is also positive, although not statistically significant). Among UK citizens, however, the interaction term is negatively signed (significant at p < 0.05), suggesting that trust is more closely associated with compliance among financially concerned individuals. These results are somewhat uneven yet, with the exception of the UK result on financial concern, they provide little clear evidence of trust being most closely associated with compliance among people facing the greatest economic cost from official restrictions.Footnote 21
Discussion
Numerous studies have explored which factors shape individual compliance with collective obligations at particular points in time. Less scholarly attention, however, has been paid to the effects of these factors over the course of a crisis like a viral pandemic. This study has sought to fill this gap by exploring how changes in two key factors – political trust and fear – are associated with changes in compliance across the course of the coronavirus pandemic among three national populations. We hypothesized a ‘substitutability’ effect for these two factors: at the outset of the pandemic, high levels of fear would do much of the work in motivating compliant behaviour, leaving less of a role for trust. As the pandemic progressed and people became accustomed to the coronavirus, fear would do less work in motivating compliance, allowing trust to ‘take up the slack’.
At particular time points, this substitutability effect is exactly what we find. High levels of fear among individuals are associated with weaker associations between trust and compliance. Yet when we move to a dynamic picture, the substitutability of trust and fear on compliance is less evident. At the very least, in the case of Germany, the associations between trust, fear and compliance increase and decline in parallel rather than diverging. And in Austria and the UK – where the data allow more rigorous modelling of within-individual variation – we find that increases in both trust and fear have become more strongly associated with compliant behaviours, at least in the early stages of the pandemic. The strengthened association between fear and compliance identified in Austria and the UK accords with a similar exercise conducted on a sample of the British population, which found a close link between perceived risk and compliance as the pandemic progressed (Schneider et al., Reference Schneider2021). What our study shows, in addition, is that this increased over-time effect of fear on compliance does not co-exist with a decreased over-time effect of trust on compliance. On a longitudinal perspective at least, fear of the coronavirus does not appear to crowd out the stimulating role of trust.
Trust is widely seen as an important consideration for individuals in deciding whether to comply with official rules, particularly where these entail significant individual costs. Our findings partly confirm the first intuition while casting doubt on the second. In particular, we find little empirical support for the hypothesis that trust is most associated with compliance among individuals for whom staying at home involves high costs. Although the results provided by different measures of economic status are not wholly consistent, those obtained from income suggest that trust may be most closely associated with compliance among people facing the lowest, not the highest, financial costs from coronavirus restrictions. It would be valuable to study these relationships across different countries, across different forms of compliance and utilizing different measures of compliance costs (by examining behaviour among people who occupy confined living areas or who have out-of-home care duties, for example).
Conclusion
Individuals comply with official restraints on their actions for a number of reasons. Among these, trust is an important contributory factor. Yet as previous studies have shown, trust may play less of a role in stimulating compliance when people hold more instrumental reasons for abiding by collective rules, notably fear – for themselves and for wider society – of the consequences of defecting. This suggests that governments which fail to command public trust may, nonetheless, secure high rates of public compliance if individuals are sufficiently fearful of a social threat. In the countries studied here – Austria, Germany, and the UK – levels of compliance among the population maintained or even rose between 2020 and 2021 in spite of declining aggregate levels of trust. This suggests that factors like fear may indeed be doing much of the ‘heavy lifting’ in sustaining pro-social forms of behaviour among the population. Over the period, however, we have shown that increases in compliance arising from individual feelings of fear do not diminish the effects of individual feelings of trust, which also appear to boost compliance. This testifies to the importance of public trust in government in the event of a social threat like a viral pandemic. The importance of trust also applies to other forms of compliance, notably to people’s receptiveness to official recommendations about the coronavirus vaccination (e.g. Lazarus et al., Reference Lazarus, Ratzan, Palayew, Gostin, Larson, Rabin, Kimpball and El-Mohandes2020). People may behave in socially optimal ways out of an instrumental concern for the consequences of not doing so. Yet they also comply because, in more normative terms, the source of collective rules is deemed trustworthy. Over the course of a crisis like the coronavirus pandemic, public compliance with official rules arises not only from the severity of social threats, but also from the perceived qualities of collective rule-makers.
Supplementary material
To view supplementary material for this article, please visit https://doi.org/10.1017/S1755773922000078.
Acknowledgments
Previous versions of this paper were presented at the ‘Behavioral and Experimental Public Management’ section of the International Research Society for Public Management annual conference, the Elections, Public Opinion and Parties (EPOP) annual conference, the COVID-19 Public Health and Social Measures Research Outcome conference and a workshop at the Blavatnik School of Government, University of Oxford. The first named author would like to thank participants at these events, in particular Jane Green and Michael Ganslmeier, for helpful comments. He would also like to thank Amanda Gosling for invaluable methodological advice, and the Austrian ACPP and German COSMO projects for granting access to their data. Both authors would like to thank the journal reviewers for their helpful comments.
Data availability
The Austrian and German data employed in this analysis are publicly available; details are provided in the footnotes. The UK data are not publicly available; but details of the data are provided in the footnotes.
Competing interests
The authors declare none.
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