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RESEARCH ARTICLE
‘We are all in the same boat’: How societal
discontent affects intention to help during the
COVID-19 pandemic
Elena Resta
1
| Silvana Mula
1
| Conrad Baldner
1
|
Daniela Di Santo
1
| Maximilian Agostini
2
| Jocelyn J. Bélanger
3
|
Ben Gützkow
2
| Jannis Kreienkamp
2
| Georgios Abakoumkin
4
|
Jamilah Hanum Abdul Khaiyom
5
|VjollcaAhmedi
6
| Handan Akkas
7
|
Carlos A. Almenara
8
| Mohsin Atta
9
| Sabahat Cigdem Bagci
10
|
Sima Basel
11
| Edona Berisha Kida
12
| Allan B. I. Bernardo
13
|
Nicholas R. Buttrick
14
| Phatthanakit Chobthamkit
15
|
Hoon-Seok Choi
16
| Mioara Cristea
17
| Sara Csaba
18
|
Kaja Damnjanovi
c
19
| Ivan Danyliuk
20
| Arobindu Dash
21
|
Karen M. Douglas
22
| Violeta Enea
23
| Daiane Gracieli Faller
24
|
Gavan J. Fitzsimons
25
| Alexandra Gheorghiu
26
|
Angel G
omez
27
|
Ali Hamaidia
28
|QingHan
29
| Mai Helmy
30,76
|
Joevarian Hudiyana
31
| Bertus F. Jeronimus
2
| Ding-Yu Jiang
32
|
Veljko Jovanovi
c
33
| Zeljka Kamenov
34
| Anna Kende
35
|
Shian-Ling Keng
36
| Tra Thi Thanh Kieu
37
| Yasin Koc
2
|
Kamila Kovyazina
38
| Inna Kozytska
20
| Joshua Krause
2
|
Arie W. Kruglanski
39
| Anton Kurapov
20
| Maja Kutlaca
40
|
N
ora Anna Lantos
35
| Edward P. Lemay Jr
39
|
Cokorda Bagus J. Lesmana
41
| Winnifred R. Louis
42
|
Adrian Lueders
43
| Najma Iqbal Malik
9
| Anton P. Martinez
44
|
Kira O. McCabe
45
| Jasmina Mehuli
c
34
| Mirra Noor Milla
31
|
Idris Mohammed
46
| Erica Molinario
47
| Manuel Moyano
48
|
Hayat Muhammad
49
| Hamdi Muluk
31
| Solomiia Myroniuk
2
|
Received: 9 April 2021 Accepted: 27 August 2021
DOI: 10.1002/casp.2572
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and
reproduction in any medium, provided the original work is properly cited.
© 2021 The Authors. Journal of Community & Applied Social Psychology published by John Wiley & Sons Ltd.
J Community Appl Soc Psychol. 2021;1–16. wileyonlinelibrary.com/journal/casp 1
Reza Najafi
50
| Claudia F. Nisa
3
| Boglárka Nyúl
35
|
Paul A. O'Keefe
36,51
| Jose Javier Olivas Osuna
52
|
Evgeny N. Osin
53
| Joonha Park
54
| Gennaro Pica
55
|
Antonio Pierro
1
| Jonas H. Rees
56
| Anne Margit Reitsema
57
|
Marika Rullo
58
| Michelle K. Ryan
59,60
| Adil Samekin
61
|
Pekka Santtila
62
| Edyta Sasin
3
|BirgaM.Schumpe
63
|
Heyla A. Selim
64
| Michael Vicente Stanton
65
| Wolfgang Stroebe
2
|
Samiah Sultana
2
| Robbie M. Sutton
22
| Eleftheria Tseliou
4
|
Akira Utsugi
66
| Jolien A. van Breen
67
| Caspar J. van Lissa
68
|
Kees van Veen
69
| Michelle R. van Dellen
70
|
Alexandra Vázquez
27
| Robin Wollast
71
|
Victoria Wai-lan Yeung
72
| Somayeh Zand
50
|
Iris Lav Žeželj
19
| Bang Zheng
73
| Andreas Zick
74
|
Claudia Zúñiga
75
| N. Pontus Leander
2
1
Department of Developmental and Social Psychology, Sapienza University of Rome, Rome, Italy
2
Department of Psychology, University of Groningen, Groningen, Netherlands
3
Department of Psychology, New York University Abu Dhabi, Abu Dhabi, UAE
4
Laboratory of Psychology, Department of Early Childhood Education, University of Thessaly, Volos, Greece
5
Department of Psychology, International Islamic University Malaysia, Selangor, Malaysia
6
Pedagogy, Pristine University, Kosovo
7
Business Administration Department, Ankara Science University, Ankara, Turkey
8
Faculty of Health Science, Universidad Peruana de Ciencias Aplicadas, Santiago de Surco, Peru
9
Department of Psychology, University of Sargodha, Sargodha, Pakistan
10
Department of Psychology, Sabanci University, Istanbul, Turkey
11
Department of Social Sciences, New York University Abu Dhabi, Abu Dhabi, UAE
12
Faculty of Education, Pristine University, Kosovo
13
Department of Psychology, De La Salle University, Manila, Philippines
14
Department of Psychology, University of Virginia, Charlottesville, Virginia, USA
15
Department of Psychology, Thammasat University, Bangkok, Thailand
16
Department of Psychology, Sungkyunkwan University, Seoul, South Korea
17
Department of Psychology, Heriot Watt University, Edinburgh, Scotland
18
Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
19
Department of Psychology, University of Belgrade, Belgrade, Serbia
20
Department of Psychology, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
21
Department of Social Sciences, International University of Business Agriculture and Technology, Dhaka, Bangladesh
22
School of Psychology, University of Kent, Canterbury, UK
23
Department of Psychology, Alexandru Ioan Cuza University, Iași, Romania
24
Center for global Sea Level Change, New York University Abu Dhabi, Abu Dhabi, UAE
2RESTA ET AL.
25
Marketing and Psychology, Duke University, Durham, North Carolina, USA
26
Center for European Studies, Faculty of Law, Alexandru Ioan Cuza University, Iași, Romania
27
Social and Organizational Psychology, Universidad Nacional de Educaci
on a Distancia, Madrid, Spain
28
Psychology/ Research Unit Human Resources Development, Setif 2 University, Sétif, Algeria
29
The School of Psychological Science, University of Bristol, Bristol, UK
30
Psychology Department, College of Education, Sultan Qaboos University, Muscat, Oman
31
Department of Psychology, Universitas Indonesia, Kota Depok, Indonesia
32
Department of Psychology, National Chung-Cheng University, Chiayi, Taiwan
33
Department of Psychology, University of Novi Sad, Novi Sad, Serbia
34
Faculty of Humanities and Social Sciences, University of Zagreb, Zagreb, Croatia
35
Department of Social Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
36
Division of Social Science, Yale-NUS College, Singapore, Singapore
37
Department of Psychology, HCMC University of Education, Ho Chi Minh City, Vietnam
38
Independent researcher, Kazakhstan
39
Department of Psychology, University of Maryland, College Park, Maryland, USA
40
Department of Psychology, Durham University, Durham, UK
41
Department of Psychiatry, Udayana University, Kuta Selatan, Indonesia
42
School of Psychology, University of Queensland, Brisbane, Australia
43
Department of Psychology, University of Limerick, Limerick, Ireland
44
Department of Psychology, University of Sheffield, Sheffield, UK
45
Department of Psychology, Carleton University, Ottawa, Ontario, Canada
46
Mass Communication, Usmanu Danfodiyo University Sokoto, Sokoto, Nigeria
47
Department of Psychology, Florida Gulf Coast University, Fort Myers, Florida, USA
48
Department of Psychology, University of Cordoba, C
ordoba, Spain
49
Department of Psychology, University of Peshawar, Peshawar, Pakistan
50
Department of Psychology, Islamic Azad University, Rasht Branch, Rasht, Iran
51
Department of Management and Organisation, National University of Singapore Business School, Singapore, Singapore
52
Department of Political Science and Administration, National Distance Education University (UNED), Madrid, Spain
53
Department of Psychology, HSE University, Moscow, Russia
54
Graduate School of Management, NUCB Business School, Nagoya, Japan
55
School of Law, University of Camerino, Camerino, Italy
56
Research Institute Social Cohesion, Institute for Interdisciplinary Research on Conflict and Violence, Department of Social
Psychology, University of Bielefeld, Bielefeld, Germany
57
Department of Developmental Psychology, University of Groningen, Groningen, Netherlands
58
Department of Educational, Humanities and Intercultural Communication, University of Siena, Siena, Italy
59
Psychology, University of Exeter, Exeter, UK
60
Faculty of Economics and Business, University of Groningen, Groningen, Netherlands
61
School of Liberal Arts, M. Narikbayev KAZGUU University, Nur-Sultan, Kazakhstan
62
Department of Psychology, New York University Shanghai, Shanghai, China
63
Faculty of Social and Behavioural Sciences, University of Amsterdam, Amsterdam, Netherlands
64
Department of Psychology, King Saud University, Riyadh, Saudi Arabia
65
Department of Public Health, California State University, San Francisco, California, USA
66
Graduate School of Humanities, Nagoya University, Nagoya, Japan
67
Institute of Governance and Global Affairs, Leiden University, Leiden, Netherlands
RESTA ET AL.3
68
Department of Methodology & Statistics, Utrecht University, Utrecht, Netherlands
69
Sustainable Society, University of Groningen, Groningen, Netherlands
70
Department of Psychology, University of Georgia, Athens, Georgia
71
Laboratoire de Psychologie Sociale et Cognitive, Université Clermont-Auvergne, Clermont-Ferrand, France
72
Department of Applied Psychology, Lingnan University, Tuen Mun, Hong Kong
73
Ageing Epidemiology Research Unit, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
74
Institute for Interdisciplinary Research on Conflict and Violence (IKG), Bielefeld University, Bielefeld, Germany
75
Department of Psychology, Universidad de Chile, Santiago, Chile
76
Psychology Department, Faculty of Arts, Menoufia University, Shebin El-Kom, Egypt
Correspondence
Elena Resta, Department of Developmental
and Social Psychology, Sapienza University of
Rome, Via dei Marsi, 78, Rome 00185, Italy.
Email: elena.resta@uniroma1.it
Funding information
Instituto de Salud Carlos III, Grant/Award
Number: COV20/00086; University of
Groningen; New York University Abu Dhabi,
Grant/Award Number: VCDSF/75-71015
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has cau-
sed a global health crisis. Consequently, many countries have
adopted restrictive measures that caused a substantial
change in society. Within this framework, it is reasonable to
suppose that a sentiment of societal discontent, defined as
generalized concern about the precarious state of society,
has arisen. Literature shows that collectively experienced sit-
uations can motivate people to help each other. Since societal
discontent is conceptualized as a collective phenomenon, we
argue that it could influence intention to help others, particu-
larly those who suffer from coronavirus. Thus, in the present
study, we aimed (a) to explore the relationship between soci-
etal discontent and intention to help at the individual level
and (b) to investigate a possible moderating effect of societal
discontent at the country level on this relationship. To fulfil
our purposes, we used data collected in 42 countries
(N=61,734) from the PsyCorona Survey, a cross-national
longitudinal study. Results of multilevel analysis showed that,
when societal discontent is experienced by the entire com-
munity, individuals dissatisfied with society are more prone
to help others. Testing the model with longitudinal data
(N=3,817) confirmed our results. Implications for those find-
ings are discussed in relation to crisis management. Please
refer to the Supplementary Material section to find this arti-
cle's Community and Social Impact Statement.
KEYWORDS
COVID-19, intention to help, societal discontent
4RESTA ET AL.
1|INTRODUCTION
The year 2020 saw one of the largest global health crises (Van Bavel et al., 2020). Starting in December 2019, cases
of a new form of pneumonia, coronavirus disease 2019 (COVID-19), surged to the point that on March 11, 2020,
the World Health Organization (WHO) declared the outbreak, a pandemic. To deal with the rapid spread of the dis-
ease, different countries have adopted restrictive measures, such as lockdowns, social distancing and quarantines
(Benke, Autenrieth, Asselmann, & Pané-Farré, 2020). Embracing those preventive behaviours had, among others,
economic and social consequences. For instance, the pandemic has caused a de-globalization, obligating the closure
of national and sub-national borders, decreasing the demand for manufactured products and increasing that of medi-
cal supplies and food (e.g., Nicola et al., 2020; Van Bavel, Baicker, Boggio, et al., 2020). These economic changes and
a reduction in activity, across all economic sectors, have resulted in the widespread loss of jobs and rise of financial
problems. Furthermore, some restrictions and preventive behaviours, such as wearing masks or avoiding crowded
spaces, caused a reduction of individuals' freedom and a substantial change in everyone's routine (Tisdell, 2020).
Within this frame, it is reasonable to assume that people have begun to worry about the present and future of
society. Uncertainty about the future and many unexpected changes in the community could reasonably have
induced the perception that society is in the process of deterioration. This would reflect the perception of societal
discontent, defined by Taggart (2004) as a sense of crisis, which includes the perception that various relevant aspects
of society are about to break down. Accordingly, Steenvoorden (2015) described it as citizens' concern about the
precarious state of society. Literature reports societal discontent as a collective phenomenon in which citizens of the
entire community share a tacit understanding that society is in a predicament (e.g., van der Bles, 2018). In a similar
vein, Steenvoorden and Harteveld (2018) found that societal unease, a specific conceptualization of concern about
the state of society, is strongly associated with broader societal pessimism.
The main characteristic of societal discontent is that it concerns a generalized perception of the community, and,
thus, it can be defined as a negative Zeitgeist: a pervasive, collective-level evaluation that society is in decline
(e.g., Gootjes, Kuppens, Postmes, & Gordijn, 2021; van der Bles, Postmes, & Meijer, 2015). Interestingly, collective
judgements about the present and the future of society can be independent from individual perception of the same
societal issues (van der Bles et al., 2015). Thus, a generalized discontent can be completely distinct from individuals'
personal problems or well-being. In this vein, van der Bles, Postmes, LeKander-Kanis, and Otjes (2018) reported that
even if people thought their country was going in the wrong direction, they were satisfied with their personal lives.
Societal discontent concerns the sense of ‘how we are doing’in the context of society, and, therefore, it deals with
the perception of the situation the entire community is experiencing (van der Bles et al., 2018). Similarly, the term ‘com-
mon fate’refers to the same situation experienced collectively which, by being common, elicits a sense of ‘we-ness’
(Vollhardt, 2009). Literature investigated common fate mainly in context of threat and adversity, reporting that it motivates
prosocial behaviour (Dovidio et al., 1997). Dovidio and Morris (1975) found that common fate, particularly of stressful situ-
ations, increases helping others. In a similar vein, Richardson and Maninger (2016) reported a ‘we were all in the same
boat’effect: citizens who shared the traumatic experience of Hurricane Ike helped each other to recover from the natural
disaster. Thus, a stressful event, when perceived by the entire community, can motivate people to increase prosocial
behaviour. In fact, drawing from empathy–altruism hypothesis of helping behaviour (Batson & Oleson, 1991), similarity to
other people, has been demonstrated to increase helping behaviour (e.g., Dovidio, 1984). In a similar vein, literature
reported of different events in which individuals who felt ‘inthesameboat’after an adverse event were prone to help
each other. For instance, Hernandez (2001) reported that experiences of adversity motivated Colombians to engage in
activism on the side of the community. Furthermore, common fate has been used to explain the increasing of prosocial
behaviour, such as donating money, comforting or volunteering, during stressful and traumatic events experienced collec-
tively (e.g., Yum & Schenck-Hamlin, 2005). In line with this reasoning, since societal discontent is conceptualized as a senti-
ment experienced by the whole country, we argue that it may influence helping behaviour.
However, no previous research has investigated the effect of dissatisfaction with society on prosocial behaviour.
Furthermore, to the best of our knowledge, no study has yet explored the cross-level interaction effect between societal
discontent at the individual level and societal discontent at the country level. In fact, perceptions at the individual level
RESTA ET AL.5
can be discrepant from those at the collective level (Postmes, Branscombe, Spears, & Young, 1999). Thus, we can find
not only different predictive effects of concern about society at the individual or collective level, as agued by van der
Bles et al. (2018), but also interesting findings when those two levels of analysis combine with each other.
2|THE PRESENT RESEARCH
Our aim was to investigate the relationship between societal discontent and the intention to help others, in the con-
text of adversity due to the COVID-19 pandemic. The spread of the disease has affected society worldwide and has
produced consequences at the individual level, such as reduction in personal freedom, but also at the collective level,
such as economic crisis. It seems reasonable that this scenario could have induced a general discontent, which, in
turn, may affect the tendency to help each other. To deal with the consequences of COVID-19, an increasing num-
ber of fundraisings were created (Rajwa et al., 2020). Thus, in the unusual circumstances of the pandemic, it is mean-
ingful to understand if societal discontent can influence the willingness to help others, particularly those who suffer
physically and/or economically from coronavirus.
Drawn from these premises, the present research had two main purposes. First, to explore the relationship between
societal discontent and intention to help at the individual level with the hypothesis that concern about society
(i.e., societal discontent) could influence citizens' intent to help those who suffer from coronavirus. Second, given that
societal discontent is conceptualized as a collective phenomenon, we were particularly interested in investigating
whether and how societal discontent at the country level modulates this relationship. Specifically, the aim of the study
was exploratory. However, the literature we reviewed above, especially that about common fate, suggests that events
experienced by the entire community would have a positive impact on helping behaviour. Thus, we argue that individuals
dissatisfied with society would be more inclined to help those who suffer from COVID-19 when this sentiment of dissat-
isfaction is experienced by the whole country. In addition, to investigate if the effects of societal discontent at the indi-
vidual and country level, and their interaction, had influenced intention to help over time, we tested a longitudinal model.
3|METHOD
3.1 |Procedures, design and participants
This study employed data from the PsyCorona Survey, a cross-national longitudinal study aimed to investigate peo-
ple's responses to the COVID-19 pandemic, both at the individual and country levels (cfr. PsyCorona Project:
https://psycorona.org). The study was approved by the institutional review board at New York University Abu Dhabi
(protocol HRPP-2020-42) and the Ethics Committee of Psychology at Groningen University (protocol PSY-1920-S-
0390). Each participant gave informed consent before beginning the survey. Data were collected online through
Qualtrics' panel management service between 19 March 2020 and 13 March 2021. The PsyCorona Survey, available
in 30 languages, was distributed in 115 countries through a combination of convenience sampling, snowball sampling
and paid procedures, recruiting over 60,000 participants. After completing this initial survey, respondents who pro-
vided contact information were invited to participate in subsequent follow-up surveys, for a total of 20 follow-up
assessments. For the purposes of the present study, we used data collected at the time of the baseline and at the
seventh follow-up assessment (May 16th, 2020). Precisely, we used the measures of societal discontent and inten-
tion to help collected at the baseline and the measure of intention to help collected at the seventh follow-up, which
was assessed with only two items (out of eight) already measured at the baseline. Additionally, we decided to include
only countries that had more than 150 participants, in order to obtain an average degree of reliability for a multilevel
analysis (Kline, 2016). Thus, the final sample of the cross-sectional study included 61,734 participants (61.1% female)
from 42 countries, aged from 18 to over 75 years old. In the final sample, 23.5% of participants had a higher educa-
tion, 30.4% had a bachelor's degree, 16.1% had a master's degree and 5.1% had a PhD degree (see Tables 1 and 2
6RESTA ET AL.
TABLE 1 Descriptive statistics of participants included in the analyses: country, Nper country, gender and age.
N.B. Total percentages may not reach 100% due to missing data that were not included in the table
Country N% Female
Age classes
%18–34 % 35–54 % 55–74 % 75+
Algeria 200 37% 50.5% 47% 2% 0%
Argentina 1,412 56.4% 42.1% 31.3% 25.5% 1%
Australia 1,216 53.5% 29.4% 37.7% 29.5% 3.3%
Bangladesh 156 29.5% 87.2% 9% 2.6% 0.6%
Brazil 1,395 57.6% 39.1% 37.9% 21.9% 1%
Canada 1,538 57.2% 38% 35.1% 24.9% 1.6%
Chile 344 75% 48.3% 38.4% 12.5% 0%
China 1,573 54.3% 54.4% 44.3% 0.5% 0.1%
Croatia 353 79.9% 72.2% 22.1% 4.8% 0.3%
Egypt 1,158 83% 93.4% 4.3% 0.5% 0.3%
France 1801 57.9% 32.5% 34.4% 31% 1.7%
Germany 1,690 56.3% 34.1% 33% 30.5% 2%
Greece 2,875 67.3% 42% 37.7% 19.4% 0.6%
Hong Kong S.A.R. 301 68.4% 70.8% 23.3% 4% 0%
Hungary 445 83.4% 77.1% 16% 5.6% 0.4%
Indonesia 2,410 50.8% 59.9% 30.5% 8.5% 0.2%
Iran 317 53.6% 67.2% 19.9% 5.7% 0%
Italy 2006 60.1% 44.1% 28.4% 25.6% 1.8%
Japan 1,326 47.4% 37.6% 27% 33.2% 2%
Kazakhstan 812 55.9% 51.6% 44.5% 3.3% 0%
Kosovo 830 83.3% 76.3% 21.4% 1.4% 0%
Malaysia 895 70.6% 55.3% 36.1% 7.4% 0.3%
Netherlands 3,045 63.1% 36.9% 34.2% 24.4% 1.8%
Pakistan 216 70.4% 83.3% 14.8% 0.9% 0%
Peru 309 65.4% 68% 26.5% 5.2% 0%
Philippines 1,530 56.3% 53.7% 32.8% 13.1% 0.4%
Poland 718 82% 59.2% 31.2% 7.9% 0.3%
Republic of Serbia 2,122 65.9% 44.5% 33.8% 20.9% 0.5%
Romania 2,701 60.8% 60.6% 24.6% 13.9% 0.6%
Russia 1,438 61.1% 34.2% 37.3% 27.5% 0.9%
Saudi Arabia 1,468 52.5% 56.8% 36.8% 5.5% 0.3%
Singapore 250 70.4% 77.6% 18.8% 3.2% 0%
South Africa 1,422 56.7% 42.9% 33.9% 22.2% 0.9%
South Korea 1,452 57% 51.2% 31.2% 16.3% 1.2%
Spain 3,203 62.6% 35.8% 42.2% 20.8% 1.1%
Taiwan 164 69.5% 62.8% 34.8% 1.8% 0%
Thailand 155 58.1% 64.5% 32.9% 2.6% 0%
Turkey 1826 60.1% 46.7% 35.6% 16.3% 1%
Ukraine 1,433 60.2% 38.2% 37.4% 23.9% 0.2%
United Kingdom 1935 61% 34% 32.6% 29.2% 3.8%
USA 11,045 61.8% 45.1% 36.4% 17.3% 0.9%
Vietnam 249 75.9% 87.6% 10.4% 0.8% 0.4%
Total 61,734
RESTA ET AL.7
TABLE 2 Descriptive statistics of participants included in the analyses: country, Nper country and level of
education. N.B. Total percentages may not reach 100% due to missing data that were not included in the table
Country N
Education
Primary
edu
General
secondary edu
Vocational
edu
Higher
edu B.A. Master PhD
Algeria 200 0.5% 9% 6.5% 20.5% 27.5% 23% 12.5%
Argentina 1,412 1% 23.2% 14.1% 27.9% 24% 5.2% 4.1%
Australia 1,216 1.3% 22% 16.4% 17% 29.5% 10.1% 3.4%
Bangladesh 156 0% 1.9% 3.2% 19.2% 41.7% 26.9% 6.4%
Brazil 1,395 2% 24.1% 9.2% 33.8% 18.1% 9.6% 2.9%
Canada 1,538 2% 17.3% 10.9% 20.4% 30.8% 14% 4.2%
Chile 344 0% 6.1% 4.9% 16.3% 38.4% 21.2% 12.2%
China 1,573 2.2% 10.7% 3.9% 32% 40.6% 8.5% 1.3%
Croatia 353 0% 25.2% 5.9% 4% 15.3% 43.3% 5.7%
Egypt 1,158 0.7% 19.3% 2.6% 46.8% 24.2% 3.4% 1.2%
France 1801 2.7% 14.4% 19.4% 18.5% 11% 18.8% 14.7%
Germany 1,690 1.1% 10.8% 31.2% 17.8% 13.3% 20.1% 5.3%
Greece 2,875 0.6% 1.7% 4.8% 24.9% 37.8% 23.1% 6.8%
Hong Kong S.A.R. 301 0.3% 2.7% 3.3% 15.3% 58.5% 15.3% 3.7%
Hungary 445 0.2% 41.3% 4.5% 0.9% 26.3% 21.6% 4%
Indonesia 2,410 0.9% 34.9% 5.9% 4.7% 36.8% 12.7% 3.4%
Iran 317 2.2% 5.4% 2.2% 11.7% 40.4% 23.3% 7.3%
Italy 2006 0.6% 6.4% 5.2% 50.2% 11.6% 21.5% 4.3%
Japan 1,326 0.2% 17.3% 3.9% 33.3% 37% 5.9% 2%
Kazakhstan 812 0.1% 4.1% 4.1% 30% 26.6% 26.6% 7.9%
Kosovo 830 0.4% 7.7% 4.5% 29.4% 34% 19.2% 3.4%
Malaysia 895 0.2% 5.6% 0.9% 12% 53.1% 22.8% 4.9%
Netherlands 3,045 1.4% 10% 16.1% 24% 12.4% 24.9% 9.3%
Pakistan 216 0.9% 3.2% 0.9% 21.8% 32.4% 31% 9.3%
Peru 309 0% 9.1% 7.1% 37.5% 26.5% 17.8% 1.6%
Philippines 1,530 1% 7.6% 6.5% 10.8% 55.3% 12.5% 5.8%
Poland 718 1.4% 32.7% 5.8% 8.8% 11.8% 32.7% 5.4%
Republic of Serbia 2,122 1.3% 16.9% 26.6% 12.1% 24.6% 14% 3.9%
Romania 2,701 1.3% 24% 3.1% 25.1% 28.2% 15.4% 2.4%
Russia 1,438 0.4% 7.9% 19.5% 44.9% 8.8% 13.3% 5%
Saudi Arabia 1,468 1.5% 19% 6% 10% 48.7% 9.7% 3.9%
Singapore 250 0% 3.6% 0.8% 35.2% 43.6% 12.8% 4%
South Africa 1,422 1.7% 18.8% 7% 35.9% 28.1% 6% 1.8%
South Korea 1,452 0.5% 3% 1.4% 40.1% 41.9% 9.6% 3%
Spain 3,203 1.4% 11.9% 15.8% 29.9% 25.2% 10.6% 5%
Taiwan 164 0% 0% 0.6% 9.1% 48.8% 34.1% 6.7%
Thailand 155 0% 2.6% 0.6% 1.3% 45.2% 37.4% 12.3%
Turkey 1826 0.8% 1.5% 20.6% 10.6% 46.2% 15.2% 4.4%
Ukraine 1,433 0.4% 9% 13.3% 38.4% 10.7% 21.9% 5.7%
United Kingdom 1935 0.8% 19.2% 13.1% 18.9% 25.6% 15.7% 5.9%
USA 11,045 3.3% 9.3% 5.6% 19.6% 38.7% 17.8% 5.3%
Vietnam 249 0% 0.8% 0.4% 19.3% 64.7% 9.6% 3.6%
Total 61,734
8RESTA ET AL.
for descriptive statistics of the sample). It is to note that representative samples in terms of age and gender were col-
lected in 20 –out of 42 –countries and specifically in Argentina, Australia, Brazil, Canada, China, France, Germany,
Italy, Japan, the Netherlands, Philippines, Republic of Serbia, Romania, Russia, South Africa, South Korea, Spain,
Turkey, the United Kingdom and the United States of America. When we considered longitudinal data, we included
only participants who responded to both the measure of societal discontent at the baseline and the measure of
intention to help at the seventh follow-up. In addition, we excluded countries with less than 150 participants, thus,
including in the longitudinal sample 3,817 individuals from 12 countries.
4|MEASURES
In order to investigate our hypotheses, we focused on measures of societal discontent and COVID-related intention
to help.
4.1 |Measure of societal discontent
Societal discontent was assessed through a subscale from Gootjes et al. (2020), which previously showed good
reliability. Participants were asked to indicate the extent to which they agreed with the following sentences: (1) I
fear that things will go wrong in society,(2)I feel concerned when I think about the future of society and (3) I am satis-
fied with society (reverse). Items were responded on a five-point scale (2=‘Strongly disagree’;+2=‘Strongly
agree’) and were averaged to form a single individual societal discontent score (Cronbach's alpha =0.69). Since
societal discontent is conceptualized as a collective phenomenon in literature, we also considered discontent at
the group level. Thus, even if societal discontent was measured at the individual level, we aggregated its percep-
tion to the country level, using the within-group average for each group as a whole. To justify the aggregation of
societal discontent at the group level, we previously demonstrated high within-country agreement (r
wg[j]
; James,
Demaree, & Wolf, 1993). In this study, r
wg(j)
for societal discontent was 0.78, providing adequate support for vari-
able aggregation (James et al., 1993). In addition, the ICC(1) value exceeded the recommended cutoff of 0.06 [ICC
(1) =0.09], indicating that 9% of the variance in societal discontent was explained by country and that the societal
discontent scale had high inter-rater reliability. In addition, the ICC(2) value exceeded the recommended cutoff of
0.70 [ICC(2) =0.99], thus indicating that the country-level mean scores of societal discontent scores were highly
reliable.
4.2 |Measure of COVID-related intention to help
Participants' intention to help others who suffer from coronavirus was measured through two different sets of items.
The first set aimed to investigate to what extent people were willing to help others that suffer from COVID-19, for
example, by making donations or personal sacrifices (4 items, for example, ‘I am willing to make personal sacrifices to
prevent the spread of coronavirus’). The second set of items aimed to investigate to what extent participants were
willing to help with the economic and financial consequences of coronavirus (4 items, for example, ‘To help with the
economic and financial consequences of coronavirus, I am willing to make donations to help others that suffer from such
consequences’). Both sets of items were answered using a seven-point scale (3=‘Strongly disagree’;+3=‘Strongly
agree’) and were averaged to form a single intention to help score (Cronbach's alpha =0.89). The helping intention
variables have been previously reported in unrelated tests of age, country and trust in government main effects (Han
et al., 2021; Jin et al., 2021; Romano et al., 2021). All PsyCorona publications are available on the Open Science
Framework, https://osf.io/h6yf5/.
RESTA ET AL.9
4.3 |Covariates
Participants were asked to indicate their age, gender and level of education. Since Romano et al. (2021) found a sig-
nificant effect of age and gender on intention to help, we used these variables, as well as education, as covariates.
5|RESULTS
We conducted the analyses using SPSS Statistic version 25.0. Before testing our hypotheses, we investigated
differences between countries in societal discontent and intention to help. We conducted two analyses of vari-
ances (ANOVA) using Tuckey's-b post-hoc test. Results showed a significant difference between countries in
societal discontent F(41, 61,461) =153.965, p< .001, MSE =84.440, partial η
2
=0.09, revealing that partici-
pants in Hong Kong S.A.R. and Chile were the least satisfied, while those in China and Kosovo were the most sat-
isfied with society. Furthermore, results showed a significant difference between countries in intention to help,
F(41, 61,217) =166.249, p< .001, MSE =213.176, partial η
2
=0.10, revealing that participants in Russia, Japan
and Ukraine were the least motivated to help others whereas those in Philippines, Bangladesh and Pakistan were
the most motivated. Details regarding the mean and standard deviation for each country can be found in the
Data S1.
5.1 |Cross-sectional effects
To test the effect of societal discontent at the individual level on the intention to help others and the possible mod-
erating role of societal discontent at the country level on this relationship, we used multilevel modelling, treating par-
ticipants as nested within countries. Specifically, to test the cross-level interaction effect on intention to help, we
entered in the model societal discontent at the individual and country levels, and their interaction, as fixed effects.
Subsequently, we ran a second model to verify whether results of the first model remain the same while controlling
for covariates, that is, gender, age and education. We ran the models using maximum likelihood (ML) estimation. In
the two models, only the intercept was a random effect, entered at the country level. To remove between-country
variability in the individual-level discontent, we decided to center societal discontent at the individual level to the
mean of each country (Enders & Tofighi, 2007). Furthermore, to facilitate the interpretation of the effects, we cen-
tered societal discontent at the group level to the grand mean (Kenny & Garcia, 2010).
Table 3 summarizes the results obtained. We found a significant negative main effect of societal discontent at
the individual level on intention to help (b=0.023; p< .001). The main effect of societal discontent at the country
level on intention to help was not significant (b=0.012; p=.958). Interestingly, when testing the cross-level
hypothesis, we found a significant positive effect of the interaction on intention to help (b=0.202; p< .001).
TABLE 3 Predictive effects of Societal discontent (at baseline) at individual and country levels and their
interaction on coronavirus disease (COVID)-related intention to help (at baseline)
Fixed effects bSEtpLL 95% CI UL 95% CI
Intercept 0.76 0.07 11.59 <.001 0.63 0.90
Societal discontent (individual level) 0.02 0.01 3.64 <.001 0.03 0.01
Societal discontent (country level) 0.01 0.23 0.05 .958 0.48 0.45
Societal discontent (individual level) societal
discontent (country level)
0.20 0.03 8.06 <.001 0.15 0.25
Abbreviations: CI, confidence interval; LL, lower limit; SE, standard error; UL, upper limit.
10 RESTA ET AL.
Specifically, the relationship between societal discontent at the individual level and intention to help others tended
to be more strongly positive for higher levels of societal discontent at the country level.
To examine the interaction effect, we conducted simple slopes analysis using the web page ‘Simple inter-
cepts, simple slopes and regions of significance in HLM 2-way interactions’(http://www.quantpsy.org/
interact/hlm2.htm). When societal discontent at the country level was low (1 SD below the mean), the rela-
tionship between societal discontent at the individual level and intention to help was negative (b=0.2241,
SE =0.0254, p< .001), whereas when societal discontent at the country level was high (1 SD above the
mean), this relationship was positive (b=0.1719, SE =0.0261, p< .001). Controlling for age, gender and edu-
cation did not change these patterns.
5.2 |Longitudinal effects
To investigate the cross-level hypothesis over time, we used the measure of COVID-related intention to help at the
seventh follow-up, which was composed by two items, already measured at the baseline (‘I am willing to help others
who suffer from coronavirus’,‘I am willing to protect vulnerable groups from coronavirus even at my own expense’;
Cronbach's alpha =0.82). We tested the longitudinal model using data from 12 countries, specifically from Canada,
France, Germany, Greece, Italy, the Netherlands, Republic of Serbia, Romania, Spain, Ukraine, the United Kingdom
and the United States of America. Using the same analysis strategy of cross-sectional effects, we examined the pre-
dictive effects of societal discontent at the individual level, societal discontent at the country level and their interac-
tion, at the baseline, on the intention to help others, measured at the seventh follow-up.
Table 4 summarizes the results obtained in the longitudinal model. We found a significant negative main effect
of societal discontent at the individual level on intention to help (b=0.054; p< .05). The main effect of societal
discontent at the country level on intention to help was not significant (b=0.07; p=.753). However, for the pur-
pose of the present study, the most important result was that relating to the cross-level hypothesis. We found a sig-
nificant positive effect of the interaction between societal discontent at the individual level and societal discontent
at the country level on the intention to help those who suffer from coronavirus at the seventh follow-up (b=0.289;
p< .05). Thus, the relationship between societal discontent at the individual level and intention to help at the sev-
enth follow-up tended to be more strongly positive for higher levels of societal discontent at the country level. All
results were obtained controlling for outcome variable measured at the baseline.
To examine the interaction effect, we conducted simple slope analysis. When societal discontent at the country
level was low (1 SD below the mean), the relationship between societal discontent at the individual level and inten-
tion to help at seventh follow-up was negative (b=0.3434, SE =0.1229, p=.0052), whereas when societal dis-
content at the country level was high (1 SD above the mean), this relationship was positive (b=0.2355,
SE =0.1204, p=.0505). Controlling for age, gender and education did not change these patterns.
TABLE 4 Predictive effects of societal discontent (at baseline) at individual and country levels and their
interaction on coronavirus disease (COVID)-related intention to help at seventh follow-up
Fixed effects bSEtpLL 95% CI UL 95% CI
Intercept 0.10 0.04 2.35 .035 0.01 0.19
Societal discontent (individual level) 0.05 0.02 2.27 .023 0.10 0.01
Societal discontent (country level) 0.07 0.22 0.32 .753 0.54 0.40
Societal discontent (individual level) Societal
discontent (country level)
0.29 0.12 2.43 .015 0.06 0.52
Intention to help (baseline) 0.69 0.01 53.34 <.001 0.67 0.72
Abbreviations: CI, confidence interval; LL, lower limit; SE, standard error; UL, upper limit.
RESTA ET AL.11
6|DISCUSSION
Within the framework of the COVID-19 pandemic, the main purposes of the present research were to investigate
the cross-sectional effects of societal discontent at the individual level, societal discontent at the country level and,
particularly, their interaction, on COVID-related intention to help. Given the correlational nature of the data, we also
tested the model with longitudinal data to verify the effect of the cross-level interaction on intention to help
over time.
Before testing our hypotheses, we investigated differences between countries in societal discontent and inten-
tion to help. The results showed that participants from Hong Kong S.A.R. reported the lowest level of satisfaction,
while those from China reported the highest level of satisfaction with society. Furthermore, participants from Russia
reported the lowest level of intention to help whereas those from Philippines reported the highest level of intention
to help. However, it is important to note that responses to both constructs' variables may have been affected by
social desirability. In fact, to maintain a socially favourable self-image, ‘participants tend to underreport socially unde-
sirable behavior and overreport socially desirable behavior’(Krumpal, 2013 p. 2028). Moreover, literature suggests
that social desirability can vary across cultures. Lalwani, Shavitt, and Johnson (2006) reported that collectivistic indi-
viduals tend to appear more normatively appropriate, whereas individualistic people tend to emphasize personal
skills and abilities.
Concerning the two main aims of the present study, we wanted to examine the influence of societal discontent
at the individual level on willingness to help and a hypothetical moderating effect of societal discontent at the coun-
try level on this relationship. We used multilevel modelling and found a negative main effect of societal discontent at
the individual level on intention to help. Thus, the more individuals were dissatisfied with society, the less they were
willing to help others who suffer from coronavirus. This result is in line with research showing that individuals dissat-
isfied with society (i.e., low political trust) are less prone to act pro-socially (Mariën & Hooghe, 2011). Similarly, a
work by Tyler (2006) proposed that distrust in societal structures is related to uncooperativeness (i.e., intention
to help).
Moreover, we did not find a predictive effect of societal discontent at the country level on intention to help. As
argued by Postmes et al. (1999), perceptions at the individual level can be discrepant from those at the collective
level. In fact, individual and group dimensions represent different facets of personal identity (Turner, 1987). This
implies that personal-level judgements are different from group-level judgements (Major, 1994). Thus, not finding a
predictive effect of societal discontent at the country level, yet finding it at the individual level, is theoretically con-
sistent (van der Bles et al., 2018).
Finally, we found a moderating effect of societal discontent at the country level on the relationship between
societal discontent at the individual level and intention to help. When people are dissatisfied with society, but this
sentiment is not perceived by the community, the willingness to help decreases. However, when people are con-
cerned about the state of society and, at the same time, this sentiment is experienced by the whole country, indi-
viduals are prone to act pro-socially. We found the same results when testing the model with longitudinal data.
Our findings are consistent with research reporting that the experience of ‘being in the same boat’increases help-
ing behaviour (e.g., Richardson & Maninger, 2016). The most relevant examples of such attempts have been inves-
tigated during natural disasters, wars or fight against chronic illness, situations in which different individuals
encounter specific negative events (e.g., Coyne & Smith, 1994; Kaniasty & Norris, 1993; Khalaf, 2002). Under
those circumstances, being all affected by the same adversity increases the perception that the problem is com-
mon to everyone, and that people should stay together to cope with it, rather than facing the event alone (Afifi,
Hutchinson, & Krouse, 2006). Therefore, the perception of shared adversity motivates individuals to act pro-
socially in order to alleviate negative outcomes. In fact, as suggested by Midlarsky (1991), helping each other can
be an effective coping strategy for people under a stressful situation (i.e., concern and dissatisfaction with the
state of society). Similarly, a study conducted by Piferi, Jobe, and Jones (2006), reported that the exposure to a
collective stressful event increased helping behaviour, such as donating money. As literature suggests, shared
12 RESTA ET AL.
experience, or a common fate affecting individuals, indeed plays a key role in promoting mutual aid. In this regard,
Zhang (2019) demonstrated that shared experience of risk promotes more cooperation in public goods provision
compared to individual experience of risk. Thus, an adverse event, that is also perceived by the community, can
motivate people to increase prosocial behaviour. In line with this reasoning, our findings show that individuals dis-
satisfied with society, who lived in a country with high levels of discontent, were more prone to help others who
suffered from coronavirus.
As with every research, this study has limitations. In the present research, we measured the intention to help
others rather than the actual behaviour. Thus, future studies should address this issue by considering real helping
behaviour. Moreover, our data come from a cross-sectional study, which is susceptible to common method/sources
biases. However, common method/sources bias can inflate the entity of relationships between variables (i.e., ‘main
effects’), but simulation studies suggest that it may lead to an underestimation of interaction effects (Evans, 1985;
McClelland & Judd, 1993). This evidence reduces concerns about the possibility that the results for the interactive
effect of societal discontent at the individual level and societal discontent at the country level may be explained by
common method variance. Furthermore, in our analyses, we aggregated the perception of societal discontent to the
country level, thus, reducing possible biases at the individual level, such as previous experiences, personality charac-
teristics and personal background (Seibert, Silver, & Randolph, 2004). In addition, the confirmation of our results with
longitudinal data should be considered a further evidence that common method variance has unlikely explained our
findings (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Another limitation we might consider concerns the repre-
sentativeness of the countries we included in the present study. In fact, in the cross-sectional analysis, only 20 out
of 42 countries had a representative sample, while in the longitudinal analysis, none of the countries had a represen-
tative sample. However, following Kline's (2016) guidelines, both in cross-sectional and longitudinal models, we
included only countries that had more than 150 participants, in order to guarantee an average degree of reliability
for multilevel analysis. Following this reasoning, in the longitudinal analysis, we considered only 12 countries. Thus,
the results of the longitudinal model should be referred just to those countries and cannot be generalized to coun-
tries worldwide.
In conclusion, our study showed that societal discontent at the individual level decreases the willingness to
help others. However, when the societal discontent is experienced by the entire community, citizens dissatis-
fied with society are more prone to act pro-socially. Those are interesting results for policies aimed to manage
situation of social crisis, such that of the COVID-19 pandemic, that can induce societal discontent. When citi-
zens are dissatisfied with the state of society, highlighting the fact that ‘we are all in the same boat’can pro-
mote helping behaviour.
ACKNOWLWDGEMENTS
This research received support from the New York University Abu Dhabi (VCDSF/75–71,015), the University of
Groningen (Sustainable Society & Ubbo Emmius Fund) and the Instituto de Salud Carlos III (COV20/00086).
CONFLICT OF INTEREST
The authors have no conflicts of interest to disclose.
ETHICS APPROVAL STATEMENT
The study was approved by the Institutional Review Board at New York University Abu Dhabi (protocol HRPP-
2020-42) and the Ethics Committee of Psychology at Groningen University (protocol PSY-1920-S-0390).
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable
request.
RESTA ET AL.13
ORCID
Elena Resta https://orcid.org/0000-0001-7964-9985
Silvana Mula https://orcid.org/0000-0002-8391-630X
Conrad Baldner https://orcid.org/0000-0003-0168-6617
Daniela Di Santo https://orcid.org/0000-0002-1438-5832
Georgios Abakoumkin https://orcid.org/0000-0002-1671-3561
Mioara Cristea https://orcid.org/0000-0002-2944-3791
Arobindu Dash https://orcid.org/0000-0003-4642-512X
Robin Wollast https://orcid.org/0000-0001-5395-9969
Victoria Wai-lan Yeung https://orcid.org/0000-0002-3479-3198
Somayeh Zand https://orcid.org/0000-0002-4414-1724
Iris Lav Žeželj https://orcid.org/0000-0002-9527-1406
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How to cite this article: Resta, E., Mula, S., Baldner, C., Di Santo, D., Agostini, M., Bélanger, J. J., Gützkow, B.,
Kreienkamp, J., Abakoumkin, G., Khaiyom, J. H. A., Ahmedi, V., Akkas, H., Almenara, C. A., Atta, M., Bagci, S.
C., Basel, S., Kida, E. B., Bernardo, A. B. I., Buttrick, N. R., …Leander, N. P. (2021). ‘We are all in the same
boat’: How societal discontent affects intention to help during the COVID-19 pandemic. Journal of
Community & Applied Social Psychology,1–16. https://doi.org/10.1002/casp.2572
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