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Trust in government and its associations with health behaviour and
prosocial behaviour during the COVID-19 pandemic
Qing Han, Bang Zheng*, Mioara Cristea, Maximilian Agostini, Jocelyn J Belanger, Ben
Gutzkow, Jannis Kreienkamp, Anne Margit Reitsema, Jolien A van Breen, Georgios
Abakoumkin, Jamilah Hanum Abdul Khaiyom, Vjollca Ahmedi, Handan Akkas, Carlos A
Almenara, Anton Kurapov, Mohsin Atta, Sabahat Cigdem Bagci, Sima Basel, Edona Berisha
Kida, Nicholas R Buttrick, Phatthanakit Chobthamkit, Hoon-Seok Choi, Sara Csaba, Kaja
Damnjanović, Ivan Danyliuk, Arobindu Dash, Daniela Di Santo, Karen M Douglas, Violeta
Enea, Daiane Faller, Gavan J Fitzsimons, Alexandra Gheorghiu, Ángel Gómez, Bertus F
Jeronimus, Ding-Yu Jiang, Veljko Jovanović, Zeljka Kamenov, Anna Kende, Shian-Ling
Keng, Tra Thi Thanh Kieu, Yasin Koc, Kamila Kovyazina, Inna Kozytska, Joshua Krause,
Arie W Kruglanski, Maja Kutlaca, Nóra Anna Lantos, Edward P Lemay, Cokorda Bagus J
Lesmana, Winnifred R Louis, Adrian Lueders, Najma Iqbal Malik, Anton P Martinez, Kira O
McCabe, Jasmina Mehulić, Mirra Noor Milla, Idris Mohammed, Erica Molinario, Manuel
Moyano, Hayat Muhammad, Silvana Mula, Hamdi Muluk, Solomiia Myroniuk, Reza Najafi,
Claudia F Nisa, Boglárka Nyúl, Paul Anna O’Keefe, Jose Javier Olivas Osuna, Evgeny N
Osin, Joonha Park, Gennaro Pica, Antonio Pierro, Jonas H Rees, Elena Resta, Marika Rullo,
Michelle K Ryan, Adil Samekin, Pekka Santtila, Edyta Sasin, Birga M Schumpe, Heyla A
Selim, Michael Vicente Stanton, Wolfgang Stroebe, Samiah Sultana, Robbie M Sutton,
Eleftheria Tseliou, Akira Utsugi, Anne Marthe van der Bles, Caspar J Van Lissa, Kees Van
Veen, Michelle R vanDellen, Alexandra Vázquez, Robin Wollast, Victoria Wai-lan Yeung,
Somayeh Zand, Iris Lav Žeželj, Andreas Zick, Claudia Zúñiga, N Pontus Leander
*. Correspondence to: Bang Zheng, Ageing Epidemiology Research Unit, School of Public
Health, Imperial College London, London, UK. E-mail: b.zheng17@imperial.ac.uk.
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Abstract
Previous studies suggested that public trust in government is vital for implementations of
social policies that rely on public's behavioural responses. This study examined associations
of trust in government regarding COVID-19 control with recommended health behaviours
and prosocial behaviours. Data from an international survey with representative samples
(N=23,733) of 23 countries were analysed. Specification curve analysis showed that higher
trust in government was significantly associated with higher adoption of health and prosocial
behaviours in all reasonable specifications of multilevel linear models (median standardised
β=0.173 and 0.244, P<0.001). We further used structural equation modelling to explore
potential determinants of trust in government regarding pandemic control. Governments
perceived as well organised, disseminating clear messages and knowledge on COVID-19,
and perceived fairness were positively associated with trust in government (standardised
β=0.358, 0.230, 0.055, and 0.250, P<0.01). These results highlighted the importance of trust
in government in the control of COVID-19.
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Introduction
In order to address the growing public health crisis created by the COVID-19 pandemic,
governments across the world need to play an essential role in the prevention and control of
the disease while mitigating its economic impact. Numerous countries have introduced
responsive measures and regulations to prevent disease transmission (e.g., social distancing,
handwashing, self-isolation1) and stabilize the economy. However, effective implementation
of these measures depends on a high level of compliance and support from the public2.
Emerging theoretical and empirical evidence suggest that trust in government is crucial to
public’s compliance with social policies that rely on their behavioural responses3-5. As such,
understanding the association between trust in government and the adoption of preventive
behaviours and exploring various determinants of trust in government during the pandemic
are important for the control of COVID-19.
Trust in government represents the confidence and satisfaction of people with government
performance6. It has been identified as a cornerstone of the political system, particularly in
crises such as natural disasters, economic crises, or pandemics. Trust in government produces
spontaneous sociability, which in turn leads to cooperative, altruistic, and extraterritorial
behaviours in social activities7-10. Previous studies demonstrated that the higher level of trust
in government was associated with greater willingness to follow a range of government
recommendations and prosocial behaviours, such as adopting preventive behaviours to avoid
the swine flu11, abiding mandated social distancing policies during the Ebola outbreak12,
getting vaccinated against seasonal influenza13, and making economic sacrifice for the
environment14. More recently, a survey of 2250 residents in the UK during COVID-19
pandemic found that those who trust the government to control the pandemic were slightly
more likely to follow the government regulations imposed during lockdown15.
Compared with the general trust in government which has been shaped over a long time by
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various historical, cultural, or political factors, this specific aspect of trust in government
regarding the ability and efficacy of COVID-19 control could be more dynamic. Given the
importance of maintaining public trust during the pandemic, there is an urgent need to
identify the determinants of trust in government regarding COVID-19 control. The
Organization for Economic Co-operation and Development (OECD) pointed out that
reliability, responsiveness, openness, better regulation, fairness, and inclusive policy making
are key areas for governments to gain public trust5. In the context of the current pandemic,
better regulation and organisation of government in the design and implementation of
responsive measures that are well-adapted to local norms could increase public support and
trust in government16. In addition, the lack of transparency of government has been identified
as one of the major elements that have caused the decline of trust in government17. Lessons
from the SARS pandemic in 2003 also highlighted the importance of transparency and timely
and accurate communication18. Furthermore, trust in government is influenced by the
performance of the national economy and citizens' evaluations of the economy, with negative
perceptions of the economy shown to promote greater distrust19,20. Finally, perceived fairness
which refers to being treated equally as other people in society could also lead to distrust in
government, especially during crises21.
Based on the theoretical background and empirical evidence, we conducted a large-scale
international survey focusing on trust in government and behavioural responses from the
public during the unprecedented COVID-19 pandemic. The aim of this study was twofold: a)
to examine the associations between trust in government on COVID-19 and the adoption of
health and prosocial behaviours that are crucial for pandemic control; and b) to explore
potential determinants of the COVID-19 related trust in government, including government
regulation, clear information or knowledge on COVID-19, economic status, and perceived
fairness during the pandemic.
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Results
Population characteristics and country-level descriptions
We used data from the PsyCorona project (https://psycorona.org/), a web-based survey that
included 23,733 participants from 23 countries who are representative of the population in
their country in terms of age and gender. These participants have completed the survey
during April 10 to May 11, 2020, of whom 51% are women, 32%, 54%, or 14% are aged
between 18-34, 35-64, or over 65 years, and 59%, 29%, or 12% have education level below,
equivalent, or above Bachelor’s degree.
Data on COVID-19 related trust in government (three items, Cronbach’s α = 0.754), adoption
of personal health behaviours (three items, Cronbach’s α = 0.795), and adoption of prosocial
behaviours (eight items, Cronbach’s α = 0.906) were analysed (Table 1). Of the three trust-
related items, one directly measured trust in country government to take the right response
measures, two measured trust of country’s ability to fight COVID-19 or its economic
consequences. Since the government in all 23 sample countries plays a major role in
pandemic control, public’s trust in country could reflect their trust in government towards
COVID-19.
Two scatter plots were generated with country-level mean values of personal health
behaviour items and prosocial behaviour items against mean values of public trust items
(Figure 1). A positive correlation was observed between the country-level trust in
government and prosocial behaviour (r = 0.49, P = 0.017), whereas no correlation was
observed for the country-level health behaviour (r = 0.01, P > 0.05).
Specification curve analysis (SCA) for associations of trust in government with health
behaviour and prosocial behaviour
Given the fact that there are multiple items on each measure and various analytical options
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regarding covariate adjustment, it is difficult to select one optimal model specification
without introducing subjective bias. Therefore, we used specification curve analysis22,23 to
examine the individual-level association between trust in government and health behaviour or
prosocial behaviour, which considers all reasonable model specifications to avoid subjective
analytical decisions. Based on multilevel linear regressions with behaviour measures as
dependent variable and country-level intercepts as random effect, multiple analytical options
were tested. For each of the three constructs (i.e., trust, health behaviour, prosocial
behaviour), relevant items were tested individually and in combination as mean score or
through principal component analysis (PCA, Table 1). Results of PCA showed a single
principal component with eigenvalue greater than 1 for all three constructs, which represents
most variations of corresponding items. In addition, to account for potential confounding
bias, three specifications were considered: no covariates, only adjusting for basic
demographics (age, gender, and education level), or adjusting for a full set of covariates (see
Methods). After combining three model specification factors (dependent variable,
independent variable, and covariate adjustment), the total numbers of model specifications
are 75 for trust in government and adoption of health behaviour (5 for trust × 5 for health
behaviour × 3 for covariates), and 210 for trust in government and prosocial behaviour (5 for
trust × 14 for prosocial behaviour × 3 for covariates).
All 75 model specifications for multilevel linear regression of COVID-19 related health
behaviour on trust in government revealed significant positive association (maximum P for
single test = 6×10-5). The standardised β coefficients and standard errors (SE) obtained for
this association from all specifications are plotted in Figure 2, with a median standardised β
of 0.173 (median SE = 0.007). Similarly, the median standardised β of 15 specifications with
the single-item direct measure of trust in government as independent variable was 0.123
(median SE = 0.007). To test the overall hypothesis that stronger trust in government
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regarding pandemic control was associated with higher compliance with recommended health
behaviours, we used bootstrapping technique to perform joint significance tests. After
creating a pseudo dataset where the null hypothesis is true (i.e., true β = 0; see Methods), the
SCA was repeated on 1000 re-sampled datasets which resulted in the distributions of
estimated median β value and number of significant tests under the null hypothesis. Results
of bootstrapped tests showed that the probability of having a median β > 0.173 or < -0.173
(i.e., stronger than in original SCA), or getting 75 significant tests by chance was below 0.001
when the null hypothesis is true.
Furthermore, the SCA visualised the influences of different analytical options on the effect
estimates (Figure 2). The health behaviour of self-quarantine had a slightly weaker
association with trust (median β = 0.156, median SE = 0.007) than washing hands more
frequently or avoiding crowded space (median β = 0.180 or 0.176, median SE = 0.007). Not
adjusting for covariates or only adjusting for basic demographics yielded similar effect
estimates (median β = 0.208 or 0.201, median SE = 0.007 or 0.006), whereas adjusting for a
full set of covariates showed a weaker independent effect of trust in government on adoption
of health behaviour (median β = 0.115, median SE = 0.007).
As for the association between trust in government and COVID-19 related prosocial
behaviour, all 210 model specifications of multilevel linear regression revealed significant
positive association (maximum P for single test = 2×10-16). The median standardised β
coefficient obtained from all specifications was 0.244 (median SE = 0.006; Figure 3).
Bootstrapped tests with 1000 re-sampled datasets showed that, when the null hypothesis is
true, the possibility of having a median β > 0.244 or < -0.244 (i.e., stronger than in original
SCA), or getting 210 significant tests by chance was below 0.001. Therefore, the null
hypothesis was rejected and the existence of the association between trust in government
regarding pandemic control and willingness to adopt prosocial behaviour was confirmed.
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As shown in Figure 3, trust of country’s ability to fight the economic consequences had a
stronger association with adoption of prosocial behaviour (median β = 0.265, median SE =
0.006) than trust of country's ability to fight the coronavirus or trust in government to take
right response measures (median β = 0.225 or 0.177, median SE = 0.006). Similar to the
situation in SCA for health behaviour, controlling for a full set of covariates resulted in a
weaker independent effect of trust in government on prosocial behaviour (median β = 0.197,
median SE = 0.007).
Structural equation model (SEM) for potential determinants of COVID-19 related trust
in government and behaviour
After establishing the associations between trust in government and health and prosocial
behaviours, we further built an integrated model with multilevel SEM to explore potential
determinants of trust in government in the context of COVID-19 control. In this generalised
SEM, associations of hypothesised determinants with trust in government, and their direct
associations (not through trust in government) with health and prosocial behaviours were
estimated based on multilevel linear regressions, with country-level intercepts as random
effects. Three latent variables were created: overall trust in government regarding pandemic
control which determined the three measured items, willingness to adopt recommended
health behaviour which determined the three health behaviour items, and willingness to adopt
prosocial behaviour which determined the eight prosocial behaviour items (Figure 4).
After controlling for potential confounding variables (age, gender, education level, religion,
citizenship, and close relationship with infected patients), the overall trust in government
regarding pandemic control was positively associated with willingness to adopt
recommended health and prosocial behaviours (standardised β = 0.206 and 0.378, SE = 0.030
and 0.039; P < 0.001), which further supported the findings from the SCA models (Figure 4).
As for the hypothesised determinants, governments being well-organised in response to the
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pandemic, more fairness, more clear messages received on coping with COVID-19, and more
knowledge on COVID-19 were associated with higher level of overall trust in government
(standardised β = 0.358, 0.250, 0.230, and 0.055, SE = 0.019, 0.027, 0.026, and 0.019; P <
0.01). In contrast, employment status and personal financial strain were not significantly
associated with overall trust in government regarding pandemic control (standardised β = -
0.012 and -0.007, SE = 0.009 and 0.013; P > 0.05). The fitting indices demonstrated an
acceptable fit between this SEM and the data (root mean square error of approximation =
0.038, standardised root mean square residual = 0.026, comparative fit index = 0.846). The
sensitivity analyses without adjusting for potential confounding variables or using the single-
item direct measure of trust in government yielded similar results.
Furthermore, perceived knowledge and message clarity on COVID-19, fairness, and personal
financial strain also had direct associations with willingness to adopt recommended health
behaviour (standardised β = 0.206, 0.153, -0.120, and 0.047, SE = 0.018, 0.014, 0.014, and
0.012; P < 0.001). Governments being well-organised had direct association with prosocial
behaviour (standardised β = 0.069, SE = 0.026; P < 0.01) but not health behaviour (P > 0.05).
Besides, perceived knowledge and message clarity on COVID-19, fairness, and
unemployment were directly associated with prosocial behaviour (standardised β = 0.068,
0.052, -0.045, and -0.046, SE = 0.020, 0.021, 0.015, and 0.010; P < 0.05).
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Discussion
In this large-scale cross-country study focusing on COVID-19 related trust in government,
we found a robust relationship between trust and personal preventive behaviour. A higher
level of trust in government regarding COVID-19 control was significantly associated with
higher compliance with measures of frequent handwashing, avoiding crowded spaces, and
social isolation/quarantine. This result is consistent with previous findings that public trust
was associated with adherence to public health interventions21,24-27. Two representative
surveys in Liberia and Congo during the Ebola outbreaks also indicated that trust in
government was positively related to compliance with disease control measures12 or adoption
of personal preventive behaviours (e.g., keeping social distance and accepting Ebola
vaccines)28. Conversely, it has been argued that the limited trust in government could make
the control of COVID-19 more difficult, especially in low and middle income countries29.
The reduced acceptance of official information caused by distrust in government fosters the
spread of fake news and misinformation4, which could substantially affect the formation of
people’s health behaviours.
In addition, our results showed a significant positive association between trust in government
and willingness to engage in prosocial behaviours that aid the control of COVID-19
pandemic. This is in line with a number of previous studies where higher levels of trust in
government are related to more support for public welfare policies and willingness to
sacrifice personal material interests30-32. As hypothesised, in a low-trust environment, citizens
will prioritize immediate and partial benefits33, whereas high levels of trust towards the long-
term benefits of public policies could produce spontaneous sociability that motivates the self-
sacrifice of some immediate benefits7,34. Our study further affirmed this statement in the
context of the current public health crisis. Moreover, we found that the trust of fighting the
economic consequences had a stronger association with prosocial behaviour compared with
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trust on disease control, which is plausible because the reduction in people’s financial
concern may increase their altruistic behaviours such as donation.
In the context of this worldwide pandemic, the international cooperation between
governments and people all over the world is the key to stop the spreading of the coronavirus.
Both personal preventive health behaviour and the prosocial behaviour that offers support for
others are essential for fighting the COVID-19. In this regard, building public trust in
government regarding disease control could serve as an effective strategy to achieve a better
cooperation and compliance of COVID-19 related policies and interventions, and ultimately
improve the prevention and control of this disease.
Given the importance of trust in government on COVID-19, we further explored its
determinants which are modifiable for a better translation into public policies. Results
showed that government that was perceived as well organised in response to COVID-19,
clear messages and perceived knowledge on COVID-19, and perceived fairness were
positively associated with trust in government. This implies that clear information such as the
number of infected cases, the capacity of the healthcare system, and unambiguous health
instructions that represent government transparency and effective communication are
important in terms of maintaining public trust35,36. In fact, a recent survey in the UK revealed
a significant increase in the percentage of people who were concerned about false or
misleading information about coronavirus from the government from April to May, 202037.
Our result on perceived fairness is in line with previous studies that linked feelings of social
inequality with less trust in government or public health institutes21,38. Therefore, the fairness
in the pandemic control should be treated with caution.
The strength of this study lies in its large and representative samples from diverse geographic
regions worldwide, which is especially important in the investigation of trust in government.
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Moreover, we collected information on potential confounding variables, as well as potential
determinants of trust in government to shed light on practical implications. From a
methodological perspective, this study expanded the application of SCA in a dataset with
hierarchical structure by employing multilevel linear regressions with random intercept in all
model specifications. In consideration that this is a cross-country survey, such
methodological development is useful to avoid intra-group correlations while increasing
statistical power for individual-level variables39 in SCA models.
Nevertheless, this study has several limitations. Due to the cross-sectional design of this
study, causal inferences for the hypothesised determinants of trust in government and its
behavioural impact on pandemic control need to be confirmed by future longitudinal studies
with follow-up data. Furthermore, a more detailed investigation on different aspects or
dimensions of COVID-19 related trust in government or health institutes, such as the trust of
detection capacity, clinical pathways, or vaccination, is needed for a comprehensive
understanding of this topic.
In conclusion, this study demonstrates that stronger trust in government on COVID-19
control is associated with higher willingness to adopt recommended health and prosocial
behaviours. In addition, governments being better organised in response to the pandemic,
more unambiguous messages received and perceived knowledge on COVID-19, and higher
perceived fairness are associated with higher level of trust in government. Relevant public
policies targeting to improve public trust in fighting the coronavirus and dealing with
secondary consequences could hugely facilitate the control of the pandemic.
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Methods
Data source. This study was based on cross-sectional data from the PsyCorona Survey on
COVID-19 (Project website: https://psycorona.org). This 20-minute web-based survey,
translated into 30 languages, aimed to investigate the psychological impact of the coronavirus
spread. During April 10 to May 11, 2020, the PsyCorona Survey actively recruited
representative samples from 23 countries. Participants were sampled online through
Qualtrics’ panel management service, so that they are representative of the country’s general
population in terms of gender and age. About 1000 participants were selected for each of the
23 countries (Argentina, Australia, Brazil, Canada, France, Germany, Greece, Indonesia,
Italy, Japan, Netherlands, Philippines, Romania, Russia, Saudi Arabia, Serbia, South Africa,
South Korea, Spain, Turkey, the United Kingdom, Ukraine, and the United States of
America).
Ethical review. PsyCorona Survey was approved by the Ethical Committee of the University
of Groningen and New York University Abu Dhabi: ecp@rug.nl (study code: PSY-1920-S-
0390); irbnyuad@nyu.edu (study code: HRPP-2020-42). All participants gave informed
consent before taking the survey.
Measures. This study focused on the measures of trust in government regarding COVID-19
control, adoption of recommended health behaviours, and willingness to engage in COVID-
19 related prosocial behaviours (Table 1). Of the three items on trust in government, one was
rated in 5-point scale from 1 (not at all) to 5 (a great deal) and two were in 7-point scale from
-3 (strongly disagree) to 3 (strongly agree). All three items on health behaviour and eight
items on prosocial behaviour were in 7-point scale from -3 (strongly disagree) to 3 (strongly
agree).
In addition, information on a set of covariates were collected in the survey, including age
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group, gender, education level, citizenship, religion, close relationship with infected patients,
employment status, personal financial strain, perceived fairness, knowledge on COVID-19,
clear messages received on COVID-19, and government being well-organised in response to
the pandemic. Details of relevant items are displayed in Supplementary Table 1.
Eligible participants. A total of 24,261 participants selected from 23 countries completed
the survey. We excluded participants with any missing values in items on trust in
government, health and prosocial behaviours, age group, and gender, which resulted in a
sample of 23,733 participants for this study (sample size of each country varies from 738 to
1159). Complete case analysis was used to deal with missing values on covariates in relevant
analyses (each covariate had 0 to <1% missing values).
Specification curve analysis (SCA). Associations of trust in government with health and
prosocial behaviours were examined. Since there are multiple items for each construct and
various analytical options for testing the association, SCA was adopted which covers all
reasonable model specifications22,23. Three model specification factors were considered: 1)
Dependent variable (health behaviour and prosocial behaviour were analysed separately;
items on each construct were tested individually, or in combination as mean score or
principal component score based on PCA); 2) Independent variable (items on trust in
government were used individually, or in combination as mean score or principal component
score); 3) Covariate adjustment (no covariates; only adjusting for age, gender, education
level; or adjusting for a full set of covariates as mentioned above).
SCA was implemented based on multilevel linear regression, with country-level intercept as
random effect. All variables in the regression models were standardised before
implementation. After testing all model specifications, the median standardised β and median
SE were used as summary statistics. Due to missing values in covariates, the sample sizes
15
were 23,733, 23,693, and 23,406 for models with no covariates, with adjustment for age,
gender, education level, and fully adjusted models, in SCAs for health behaviour as well as
for prosocial behaviour.
For the overall statistical inferences of SCA, a bootstrapping technique was used. A pseudo-
dataset was created by replacing the original dependent variable with the residuals in each
model specification, where the null hypothesis holds. Using random sampling with
replacement, 1000 bootstrapped datasets of equal size as the pseudo-dataset were generated,
on which 1000 repeated SCAs were conducted. The null hypothesis (i.e., no association
between trust in government and behaviour) was rejected if the possibility of re-sampled
median standardised β being larger in magnitude than observed value in original SCA was
below 0.05, or the possibility of getting an equal or larger number of significant tests as in
original SCA by chance was below 0.05.
Structural equation model (SEM) analysis. Associations between potential determinants of
trust in government, latent variable of trust in government, and latent variables of health and
prosocial behaviours were tested in generalised SEM analysis. Hypothesised determinants of
trust in government regarding pandemic control include employment status (employed, not
employed, or other), personal financial strain (in 5-point scale from -2 [strongly disagree] to 2
[strongly agree]), perceived fairness (in 5-point scale from -2 [strongly disagree] to 2
[strongly agree]), knowledge on COVID-19 (in 5-point scale from 1 [not at all
knowledgeable] to 5 [extremely knowledgeable]), receiving clear messages on coping with
COVID-19 (in 6-point scale from 1 [messages are completely unclear/ambiguous] to 6
[messages are very clear/unambiguous]), and government being well-organised in response to
pandemic (in 6-point scale from 1 [not at all] to 6 [very much]; Supplementary Table 1). In
addition, the SEM also serves as a complementary analysis to SCA by estimating the
associations between latent variables of overall trust in government and willingness to adopt
16
health and prosocial behaviours.
In the SEM analysis, country was controlled as random-intercept effects and other covariates
were modelled as fixed effects. Standardised regression coefficients were estimated and
tested in all linear regression models. Multiple fitting indices were calculated to evaluate the
overall model fit.
All statistical analyses were conducted using R software (version 4.0.0). Codes for SCA were
adapted from functions developed by Orben and Przybylski23. The sem function of lavaan
package was used for the SEM analysis. Where applicable, P < 0.05 indicates statistical
significance.
Acknowledgments
We would like to thank all respondents of the PsyCorona Survey for providing the valuable
data on COVID-19.
This study was funded by the University of Groningen (Sustainable Society & Ubbo Emmius
Fund), the New York University Abu Dhabi (VCDSF/75-71015), and the Government of
Spain (COV20/00086). The funders had no role in study design, data collection and analysis,
decision to publish or preparation of the manuscript.
Competing Interests
The authors declare no competing interests.
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Tables and figures
Table 1. Items on trust in government, health behaviour, and prosocial behaviour with
possible model specifications (analytical options)
Constructs
Items
Analytical decisions
Trust in
government
In general, how much do you trust the government of
your country to take the right measures to deal with the
coronavirus pandemic?
Each item individually; mean of
the three items; the first
principal component of three
items (which represents 68% of
total variability).
I think that this country is able to fight the coronavirus.
I think that this country is able to fight the economic
and financial consequences of coronavirus.
Personal health
behaviour
To minimize my chances of getting coronavirus, I
wash my hands more often.
Each item individually; mean of
the three items; the first
principal component of three
items (which represents 69% of
total variability).
To minimize my chances of getting coronavirus, I
avoid crowded spaces.
To minimize my chances of getting coronavirus, I put
myself in quarantine.
Prosocial
behaviour
I am willing to help others who suffer from
coronavirus.
Each item individually; mean of
the first four items (prosocial
behaviour on disease control),
the last four items (prosocial
behaviour on economic
consequence), or all eight items;
the first principal component of
the first four items, the last four
items, or all eight items (which
represents 60%, 72%, or 58% of
total variability, respectively).
I am willing to make donations to help others that
suffer from coronavirus.
I am willing to protect vulnerable groups from
coronavirus even at my own expense.
I am willing to make personal sacrifices to prevent the
spread of coronavirus.
To help with the economic and financial consequences
of coronavirus, I am willing to help others who suffer
from such consequences.
To help with the economic and financial consequences
of coronavirus, I am willing to make donations to help
others that suffer from such consequences.
To help with the economic and financial consequences
of coronavirus, I am willing to protect vulnerable
groups from such consequences, even at my own
expense.
To help with the economic and financial consequences
of coronavirus, I am willing to make personal
sacrifices.
18
Figure 1. Scatter plots of country-level mean values of personal health behaviour items
(A) and prosocial behaviour items (B) against mean values of trust in government items.
23 countries from the five continents are displayed as circles in each plot. Each colour
corresponds to a particular continent. Three items on trust in government were harmonised
into 7-point scale from -3 (strongly disagree) to 3 (strongly agree); three items on health
behaviour and eight items on prosocial behaviour were in similar scale from -3 to 3.
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Figure 2. Results of specification curve analysis for trust in government and adoption of
personal health behaviour.
The standardised β coefficients for the association of trust in government with health
behaviour obtained from all 75 specifications (listed on x axis) are plotted at the upper half of
the graph. Each point represents the β coefficient of one specification, and the error bar (in
grey) represents the corresponding standard error. The dotted line indicates the median
standardised β coefficient (median β = 0.173, median standard error = 0.007, median sample
size = 23,693). At the lower half of the graph, the corresponding specifications for each level
of the three model specification factors are displayed as squares.
20
Figure 3. Results of specification curve analysis for trust in government and adoption of
prosocial behaviour.
The standardised β coefficients for the association of trust in government with prosocial
behaviour obtained from all 210 specifications (listed on x axis) are plotted at the upper half
of the graph. Each point represents the β coefficient of one specification, and the error bar (in
grey) represents the corresponding standard error. The dotted line indicates the median
standardised β coefficient (median β = 0.244, median standard error = 0.006, median sample
size = 23,693). At the lower half of the graph, the corresponding specifications for each level
of the three model specification factors are displayed as squares.
21
Figure 4. Results of structural equation model analysis.
Only paths with significant regression coefficients (P < 0.05) are plotted. Standardised β
coefficients are displayed on the lower-right side of the corresponding paths. Trust 01-03
refer to the three items of trust in government; HB 01-03 refer to the three items of health
behaviour; PB 01-08 refer to the eight items of prosocial behaviour.
22
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25
Affiliations:
Author names
Affiliations
Qing Han
School of Psychological Science, University of Bristol, Bristol, UK
Bang Zheng
Ageing Epidemiology Research Unit, School of Public Health, Imperial College London,
London, UK
Mioara Cristea
Department of Psychology, Heriot Watt University, Edinburgh, UK
Maximilian Agostini
Department of Psychology, University of Groningen, Groningen, Netherlands
Jocelyn J Belanger
Department of Psychology, New York University Abu Dhabi, Abu Dhabi, United Arab
Emirates
Ben Gutzkow
Department of Psychology, University of Groningen, Groningen, Netherlands
Jannis Kreienkamp
Department of Psychology, University of Groningen, Groningen, Netherlands
Anne Margit Reitsema
Department of Developmental Psychology, University of Groningen, Netherlands
Jolien A van Breen
Department of Psychology, University of Exeter, UK
Georgios Abakoumkin
Laboratory of Psychology, Department of Early Childhood Education, University of Thessaly,
Greece
Jamilah Hanum Abdul
Khaiyom
Department of Psychology, International Islamic University Malaysia, Malaysia
Vjollca Ahmedi
Department of Pedagogy, Pristine University, Kosovo
Handan Akkas
Organizational Behavior, Ankara Science University, Turkey
Carlos A Almenara
Faculty of Health Science, Universidad Peruana de Ciencias Aplicadas, Peru
Anton Kurapov
Department of Psychology, Taras Shevchenko National University of Kyiv, Ukraine
Mohsin Atta
Department of Psychology, University of Sargodha, Pakistan
Sabahat Cigdem Bagci
Department of Psychology, Sabancı University, Turkey
Sima Basel
Department of Social Sciences, New York University Abu Dhabi, United States
Edona Berisha Kida
Faculty of Education, Pristine University, Kosovo
Nicholas R Buttrick
Department of Psychology, University of Virginia, United States
Phatthanakit
Chobthamkit
Department of Psychology, University of Kent, UK
Hoon-Seok Choi
Department of Psychology, Sungkyunkwan University, Korea
Sara Csaba
Doctoral School of Psychology, ELTE Eötvös Loránd University, Hungary
Kaja Damnjanović
Department of Psychology, University of Belgrade, Serbia
Ivan Danyliuk
Department of Psychology, Taras Shevchenko University, Ukraine
Arobindu Dash
Department of Psychology, International University of Business Agriculture & Technology
(IUBAT), Bangladesh
Daniela Di Santo
Department of Social and Developmental Psychology, University "La Sapienza", Rome, Italy
Karen M Douglas
School of Psychology, University of Kent, UK
Violeta Enea
Department of Psychology, Alexandru Ioan Cuza University, Iasi, Romania
Daiane Faller
Center for global Sea Level Change, New York University Abu Dhabi, United Arab Emirates
Gavan J Fitzsimons
Marketing and Psychology, Duke University, United States
Alexandra Gheorghiu
Center for European Studies, Faculty of Law, Alexandru Ioan Cuza University, Romania
Ángel Gómez
Social and Organizational Psychology, Universidad Nacional de Educación a Distancia, Spain
Bertus F Jeronimus
Department of Psychology, University of Groningen, Netherlands
Ding-Yu Jiang
Department of Psychology, National Chung-Cheng University
26
Veljko Jovanović
Department of Psychology, University of Novi Sad, Serbia
Zeljka Kamenov
Faculty of Humanities and Social Sciences, University of Zagreb, Croatia
Anna Kende
Department of Social Psychology, Eötvös Loránd University, Hungary
Shian-Ling Keng
Division of Social Science, Yale-NUS College, Singapore
Tra Thi Thanh Kieu
Department of Psychology, HCMC University of Education, Vietnam
Yasin Koc
Department of Psychology, University of Groningen, Netherlands
Kamila Kovyazina
Independent researcher, Kazakhstan
Inna Kozytska
Department of Psychology, Taras Shevchenko University, Ukraine
Joshua Krause
Department of Psychology, University of Groningen, Netherlands
Arie W Kruglanski
Department of Psychology, University of Maryland, United States
Maja Kutlaca
Department of Psychology, Durham University, University of Osnabrück, UK
Nóra Anna Lantos
Department of Social Psychology, ELTE Eötvös Loránd University, Hungary
Edward P Lemay
Department of Psychology, University of Maryland, United States
Cokorda Bagus J
Lesmana
Department of Psychiatry, Udayana University, Indonesia
Winnifred R Louis
School of Psychology, University of Queensland, Australia
Adrian Lueders
Laboratoire de Psychologie Sociale et Cognitive, Université Blaise Pascal, France
Najma Iqbal Malik
Department of Psychology, University of Sargodha, Pakistan
Anton P Martinez
Department of Psychology, University of Sheffield, Argentina/UK
Kira O McCabe
Psychology and Human Development,, Vanderbilt University, United States
Jasmina Mehulić
Faculty of Humanities and Social Sciences, University of Zagreb, Croatia
Mirra Noor Milla
Department of Psychology, Universitas Indonesia, Indonesia
Idris Mohammed
Mass Communication, Usmanu Danfodiyo University Sokoto, Nigeria
Erica Molinario
Department of Psychology, University of Maryland, United States
Manuel Moyano
Department of Psychology, University of Cordoba, Spain
Hayat Muhammad
Department of Psychology, University of Peshawar, Pakistan
Silvana Mula
Dipartimento dei Processi di Sviluppo e Socializzazione, University "La Sapienza", Rome, Italy
Hamdi Muluk
Department of Psychology, Universitas Indonesia, Indonesia
Solomiia Myroniuk
Department of Psychology, University of Groningen, Netherlands
Reza Najafi
Department of Psychology, Islamic Azad University Of Rasht, Iran
Claudia F Nisa
Department of Psychology, New York University Abu Dhabi, United Arab Emirates
Boglárka Nyúl
Department of Social Psychology, ELTE Eötvös Loránd University, Hungary
Paul Anna O’Keefe
Division of Social Sciences, Department of Management and Organisation, Yale-NUS College,
Singapore
Jose Javier Olivas
Osuna
Department of Political Science and Administration , National Distance Education University
(UNED), United Kingdom/Spain
Evgeny N Osin
Department of Psychology, National Research University Higher School of Economics, Russia
Joonha Park
Graduate School of Management, NUCB Business School, Japan
Gennaro Pica
Dipartimento dei Processi di Sviluppo e Socializzazione, University "La Sapienza", Rome, Italy
Antonio Pierro
Department of Social and Developmental Psychology, University "La Sapienza", Rome, Italy
Jonas H Rees
Research Institute Social Cohesion, Institute for Interdisciplinary Research on Conflict and
Violence, and Department of Social Psychology, University of Bielefeld, Germany
Elena Resta
Dipartimento dei Processi di Sviluppo e Socializzazione, University "La Sapienza", Rome, Italy
27
Marika Rullo
Department of Educational, Humanities and Intercultural Communication, University of Siena,
Italy
Michelle K Ryan
1) Department of Psychology, University of Exeter, UK; 2) Faculty of Economics and Business,
University of Groningen, Netherlands
Adil Samekin
Department of Psychology and Pedagogy, S. Toraighyrov Pavlodar State University,
Kazakhstan
Pekka Santtila
Department of Psychology, New York University Shanghai, United States
Edyta Sasin
Department of Psychology, New York University Abu Dhabi, United Arab Emirates
Birga M Schumpe
Department of Psychology, New York University Abu Dhabi, United Arab Emirates
Heyla A Selim
Department of Psychology, King Saud University, Saudi Arabia
Michael Vicente
Stanton
Health Sciences, California State University, East Bay, United States
Wolfgang Stroebe
Department of Psychology, University of Groningen, Netherlands
Samiah Sultana
Department of Psychology, University of Groningen, Netherlands
Robbie M Sutton
School of Psychology, University of Kent, UK
Eleftheria Tseliou
Laboratory of Psychology, Department of Early Childhood Education, University of Thessaly,
Greece
Akira Utsugi
Graduate School of Humanities, Nagoya University, Japan
Anne Marthe van der
Bles
Department of Psychology, University of Groningen, Netherlands
Caspar J Van Lissa
Department of Methodology & Statistics, Utrecht University, Netherlands
Kees Van Veen
Sustainable Society, University of Groningen, Netherlands
Michelle R vanDellen
Department of Psychology, University of Georgia, United States
Alexandra Vázquez
Social and Organizational Psychology, Universidad Nacional de Educación a Distancia, Spain
Robin Wollast
Laboratoire de Psychologie Sociale et Cognitive, Université Blaise Pascal, France
Victoria Wai-lan Yeung
Department of Psychology, Lingnan University, Hong Kong, China
Somayeh Zand
Department of Psychology, Islamic Azad University Of Rasht, Iran
Iris Lav Žeželj
Department of Psychology, University of Belgrade, Serbia
Andreas Zick
Institute for Interdisciplinary Research on Conflict and Violence (IKG), University of Bielefeld,
Germany
Claudia Zúñiga
Department of Psychology, Universidad de Chile, Chile
N Pontus Leander
Department of Psychology, University of Groningen, Groningen, Netherlands
