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High levels of stress in the parenting domain can lead to parental burnout, a condition that has severe consequences for both parents and children. It is not yet clear, however, whether parental burnout varies by culture, and if so, why it might do so. In this study, we examined the prevalence of parental burnout in 42 countries (17,409 parents; 71% mothers; Mage = 39.20) and showed that the prevalence of parental burnout varies dramatically across countries. Analyses of cultural values revealed that individualistic cultures, in particular, displayed a noticeably higher prevalence and mean level of parental burnout. Indeed, individualism plays a larger role in parental burnout than either economic inequalities across countries, or any other individual and family characteristic examined so far, including the number and age of children and the number of hours spent with them. These results suggest that cultural values in Western countries may put parents under heightened levels of stress.
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RESEARCH ARTICLE
Parental Burnout Around the Globe: a 42-Country Study
Isabelle Roskam
1
&Joyce Aguiar
2
&Ege Akgun
3
&Gizem Arikan
4
&Mariana Artavia
5
&Hervé Avalosse
6
&
Kaisa Aunola
7
&Michel Bader
8
&Claire Bahati
9
&Elizabeth J. Barham
10
&Eliane Besson
11
&Wim Beyers
12
&
Emilie Boujut
13
&Maria Elena Brianda
1
&Anna Brytek-Matera
14
&Noémie Carbonneau
15
&Filipa César
2
&
Bin-Bin Chen
16
&Géraldine Dorard
13
&Luciana Carla dos Santos Elias
17
&Sandra Dunsmuir
18
&Natalia Egorova
19
&
Nicolas Favez
20
&Anne-Marie Fontaine
2
&Heather Foran
21
&Julia Fricke
22
&Kaichiro Furutani
23
&Laura Gallée
1
&
Myrna Gannagé
11
&Maria Gaspar
24
&Lucie Godbout
15
&Amit Goldenberg
25
&James J. Gross
26
&Maria Ancuta Gurza
27
&
Ruby Hall
28
&Muhammad Aamir Hashmi
29
&Ogma Hatta
1
&Mai Helmy
30
&Thi Vân Hoang
31
&Mai Trang Huynh
31
&
Emerence Kaneza
32
&Taishi Kawamoto
33
&Goran Knezevic
34
&Bassantéa Lodegaèna Kpassagou
35
&
Ljiljana B. Lazarevic
34
&Sarah Le Vigouroux
36
&Astrid Lebert-Charron
13
&Vanessa Leme
37
&Gao-Xian Lin
1
&
Carolyn MacCann
38
&Denisse Manrique-Millones
39
&Marisa Matias
2
&María Isabel Miranda-Orrego
40
&
Marina Miscioscia
41
&Clara Morgades-Bamba
42
&Seyyedeh Fatemeh Mousavi
43
&Badra Moutassem-Mimouni
44
&
Ana Muntean
45
&Hugh Murphy
21
&Alexis Ndayizigiye
32
&Josué Ngnombouowo Tenkue
46
&Sally Olderbak
47
&
Sophie Ornawka
15
&Fatumo Osman
48
&Daniela Oyarce-Cadiz
49
&Pablo A. Pérez-Díaz
18,50
&Konstantinos V. Petrides
18
&
Claudia Pineda-Marin
51
&Katharina Prandstetter
21
&Alena Prikhidko
52
&Ricardo T. Ricci
53
&Fernando Salinas-Quiroz
54
&
Raquel Sánchez-Rodríguez
55
&Ainize Sarrionandia
56
&Céline Scola
57
&Vincent Sezibera
58
&Paola Silva
59
&
Alessandra Simonelli
60
&Bart Soenens
12
&Emma Sorbring
61
&Matilda Sorkkila
7
&Charlotte Schrooyen
12
&
Elena Stănculescu
62
&Elena Starchenkova
63
&Dorota Szczygiel
64
&Javier Tapia
65
&Thi Minh Thuy Tri
31
&
Mélissa Tremblay
15
&A. Meltem Ustundag-Budak
66
&Maday Valdés Pacheco
67
&Hedwig van Bakel
28
&
Lesley Verhofstadt
12
&Jaqueline Wendland
13
&Saengduean Yotanyamaneewong
68
&Moïra Mikolajczak
1
&
Received: 7 July 2020 /Accepted: 21 December 2020
#The Society for Affective Science 2021
Abstract
High levels of stress in the parenting domain can lead to parental burnout, a condition that has severe consequences for both
parents and children.It is not yet clear, however, whether parental burnout varies by culture, and if so, why it might do so. In this
study, we examined the prevalence of parental burnout in 42 countries (17,409 parents; 71% mothers; M
age
= 39.20) and showed
that the prevalence of parental burnout varies dramatically across countries. Analyses of cultural values revealed that individu-
alistic cultures, in particular, displayed a noticeably higher prevalence and mean level of parental burnout. Indeed, individualism
plays a larger role in parental burnout than either economic inequalities across countries, or any other individual and family
characteristic examined so far, including the number and age of children and the number of hours spent with them. These results
suggest that cultural values in Western countries may put parents under heightened levels of stress.
Keywords Exhaustion .Culture .Individualism .Collectivism .Prevalence
Introduction
At all times and in all cultures, the majority of adults become
parents. The experience is so mundane that, for centuries,
parenthood was considered deserving of little comment.
However, several major sociological changes over the past
few decades (including, but not limited to, the International
Child Convention, 1989, and increased state regulation; Daly,
2007) have profoundly changed parenting, leading to in-
creased parental involvement, more intensive parenting, and
Handling Editor: Seth D. Pollak
*Isabelle Roskam
isabelle.roskam@uclouvain.be
Extended author information available on the last page of the article.
Affective Science
https://doi.org/10.1007/s42761-020-00028-4
child overprotection and optimization (Bristow, 2014;Craig
et al., 2014). It is in this zeitgeist that the notion of parental
burnout has emergeda condition characterized by intense
exhaustion related to parenting, emotional distancing from
ones children, a loss of pleasure and efficacy in onesparental
role, and a contrast between previous and current parental self
(Mikolajczak et al., 2019).
Recent work suggests that parental burnout can be
very damaging. As regards the parents themselves, pa-
rental burnout can give rise to suicidal and escape idea-
tions (Mikolajczak et al., 2019), which are much more
frequent in parental burnout than in job burnout or even
depression (Mikolajczak et al., 2020). This finding is not
surprising considering that one cannot resign from ones
parenting role or be put on sick leave from ones chil-
dren. In addition to increasing the desire to physically
escape from the parenting situation, parental burnout is
also related to psychological forms of escape such as
alcohol use (Mikolajczak et al., 2018). At the biological
level, parental burnout causes a dysregulation in the
hypothalamic-pituitary-adrenal (HPA) axis (Brianda et
al., 2020b), which is most likely causally involved in
the somatic complaints and sleep disorders reported by
burned out parents (Sarrionandia-Pena, 2019) and poten-
tially also in the increase in child-directed violence
(Martorell & Bugental, 2006; Moons et al., 2010).
Indeed,inadditiontoaffectingtheparentsthemselves,
parental burnout has serious repercussions on children
by leading previously good parents (Chen et al., 2019)
to become neglectful or even violent towards their off-
spring (Mikolajczak et al., 2018). All these effects are
causal because when parental burnout is treated via a
targeted psychological intervention, suicidal and escape
ideations and parental violence and neglect decrease pro-
portionally to the decrease in parental burnout, and HPA
axis activity normalizes (Brianda et al., 2020).
What makes parental burnout a worrying condition is not
only the gravity of its consequences but also its prevalence.
Lifelong prevalence data are not available, but studies con-
ducted in European and Anglo-Saxon countries (Belgium,
France, England, and USA) have shown that an alarming
number of parents have parental burnout. Conservative point
prevalence estimates (Roskam et al., 2018) suggest that at
least 5% of parents have burnout. However, in the absence
of cross-cultural studies including non-Western countries, it is
unclear whether this pattern is also evident in the rest of the
world. Given that parenting norms and practices dramatically
vary across cultures (Bornstein, 2013), it seems plausible that
the prevalence of parental burnout would also vary substan-
tially across the globe.
Preliminary studies conducted on parental burnout in vari-
ous parts of the world (i.e.,Belgium, France, The Netherlands,
UK, Sweden, and Japan) suggest important variation in
parental burnout prevalence (with prevalence varying between
1 and 30%, see, e.g., Kawamoto et al., 2018; Lindhal-
Norberg, 2007; Lindhal-Norberg et al., 2014; Lindstrom
et al., 2010; Roskam et al., 2018; Roskam et al., 2017;
Sánchez-Rodríguez et al., 2019;VanBakeletal.,2018).
Yet, this variation in prevalence is admittedly difficult to in-
terpret due to variation in the instruments used to measure
parental burnout, the varying cutoff scores adopted, and the
different target populations (e.g., community samples versus
parents withseverely ill children). It therefore remains unclear
(i) whether the prevalence of parental burnout varies across
the globe and, if so, (ii) whether culture helps to explain these
differences in parental burnout. Based on the literature, we
expected that the prevalence of parental burnout would vary
across countries and that culture would help to explain this
variation.
To address these questions, we assessed parents from 42
countries using the same instrument. Countries were selected
to be geographically distributed across the five continents and
to differ on economic and cultural indicators (Forum., 2018;
Hofstede, 2001; Programme, 2018;seeTable1). To answer
the question (i), we examined the prevalence and the mean
level of parental burnout in each country. To address the ques-
tion (ii), we tested the association between parental burnout
and Hofstedes six cultural values (Hofstede, 2001; i.e., Power
Distance, Individualism, Masculinity, Uncertainty
Avoidance, Long-Term Orientation, and Indulgence) as the
most widely used indicators of cross-cultural differences
(Bleidorn et al., 2016; Taras et al., 2010). Given that the par-
ents came from culturally, economically, and geographically
diverse settings, we controlled for a large set of
sociodemographic characteristics (age, sex, educational level,
number of biological children and children in the household,
age of the youngest and the oldest child, hours spent with
children per day, number of women and men living in the
household and caring for the children on a daily basis, work-
ing status, years spent in the country, ethnicity, family types,
and neighborhood profile).
Methods
Participants
A total of 17,409 parents (12,364 mothers and 5,045 fathers)
from 42 countries participated in the study. Data collection
started in January 2018 and ended in November 2019 in 40
countries. The two last countries, (i.e., Burundi and Egypt),
collected the data in February and March 2020. Note that all
the data collection took place before the lockdown periods
caused by the Covid-19 pandemic in all the countries in-
volved. The recruitment procedure (e.g., newspaper advertise-
ment, word of mouth, social networks, door-to-door) and the
Affective Science
Table 1 Hofstedes cultural values, growth national product, means and standard deviations of parental burnout, parental burnout prevalence, and reliability in each country
Power
Distance
Individualism Masculinity Uncertainty
Avoidance
Long-Term
Orientation
Indulgence Growth
national
product
Parental
burnout
Parental Burnout
Assessment Reliability
(Cronbach α)
Prevalence
of parental
burnout
(86) %
1
Prevalence
of parental
burnout
(92) %
2
Prevalence of
parental
burnout (92)
% random
sample
3
Prevalence of
parental
burnout (92)
% weighting
sample
4
MSD
Algeria –– 180.44 16.56 20.64 0.92 2.5 1.3 0.6 1.3
Argentina 49 46 56 86 20 62 518.09 20.50 20.85 0.94 1.1 1.1 1.0
Australia 36 90 61 51 21 71 1418.28 24.57 25.07 0.96 3.3 2.4 2.2
Austria 11 55 79 70 60 63 457.64 21.58 19.41 0.94 1.6 1.6 1.8
Belgium 65 75 54 94 82 57 533.15 36.67 31.10 0.97 9.8 8.1 9.2 7.9
Brazil 69 38 49 76 44 59 1868.18 16.01 19.31 0.95 1.3 1.3 1.3
Burundi –– 3.44 30.30 30.38 0.95 6.4 5.9 5.9
Cameroun –– 38.52 19.06 17.26 0.86 0.5 0.5 0.5
Canada 39 80 52 48 36 68 1711.39 32.82 29.48 0.97 6.8 6.5 6.5
Chile 63 23 28 86 31 68 298.17 28.99 25.70 0.96 5.1 3.9 5.8 3.8
China 80 20 66 30 87 24 13,407.40 10.82 17.94 0.95 1.4 1.4 1.0 1.4
Colombia 67 13 64 80 12 83 333.11 17.95 19.71 0.95 2.1 1.1 1.0
Costa Rica 35 15 21 86 ––59.01 24.15 25.12 0.96 4.0 2.0 1.8
Cuba –– 97.00 6.79 9.61 0.85 0.0 0.0 0.0
Ecuador 78 8 63 67 ––107.51 19.47 19.97 0.95 2.1 1.4 1.3
Egypt 70 25 45 80 7 4 249.56 33.43 24.01 0.92 2.6 2.6 2.6
Finland 33 63 23 59 38 57 275.32 31.96 27.37 0.97 6.2 4.9 4.2 4.9
France 68 71 43 86 63 48 275.25 29.25 28.22 0.97 6.2 5.5 5.5 5.3
Germany 35 67 66 65 83 40 4000.39 24.90 21.66 0.95 1.8 1.5 1.5
Iran 58 41 43 59 14 40 452.28 15.49 21.02 0.93 1.5 1.3 1.6 1.2
Italy 50 76 70 75 61 30 2072.20 16.08 17.03 0.94 0.6 0.6 1.1 0.5
Japan 54 46 95 82 88 42 4917.93 12.76 22.63 0.97 2.8 1.8 2.0 1.7
Lebanon 75 40 65 50 14 25 56.41 19.47 26.71 0.98 5.5 5.5 5.3
Pakistan 55 14 50 70 50 0 312.57 17.70 14.68 0.88 0.0 0.9 0.0
Peru 64 16 42 87 25 46 225.20 18.40 18.29 0.93 1.0 1.3 0.5 0.0
Poland 68 60 64 93 38 29 586.02 39.41 30.46 0.97 9.6 7.7 6.8 7.3
Portugal 63 27 31 99 28 33 238.51 17.06 20.70 0.96 2.0 2.0 2.1 1.8
Romania 90 30 42 90 52 20 239.85 22.26 25.71 0.97 5.2 3.8 3.6 3.8
Russia 93 39 36 95 81 20 1630.66 27.51 29.54 0.97 6.6 5.3 5.0 4.9
Rwanda –– 9.51 28.97 21.25 0.88 2.5 2.1 2.2
Serbia 86 25 43 92 52 28 50.65 18.90 18.96 0.94 0.9 0.9 0.4
Spain 57 51 42 86 48 44 1425.87 22.58 25.24 0.96 3.9 3.4 5.0 3.2
Sweden 31 71 5 29 53 78 551.14 20.26 21.97 0.96 2.6 2.0 1.9 2.0
Switzerland 34 68 70 58 74 66 703.75 33.73 28.78 0.97 7.1 4.8 3.2 4.6
Thailand 64 20 34 64 32 45 487.24 5.72 9.13 0.89 0.2 0.3 0.0 0.0
The Netherlands 38 80 14 53 67 69 912.90 19.29 21.31 0.96 2.2 2.2 2.1
Affective Science
presentation of the survey (i.e., paper and pencil or online)
varied from country to country according to local practices.
A summary of the data collection procedures in each country
is provided in Table 2.Table3presents the sociodemographic
characteristics of respondents in each country. In order to
avoid (self-) selection bias, participants were not informed that
the study was about parental burnout. Instead, it was presented
as a study designed to better understand parental satisfaction
and exhaustion around the world. Parents were eligible to
participate only if they had (at least) one child, regardless of
their age, still living at home.
Procedure
The data were collected through the International
Investigation of Parental Burnout (IIPB) Consortium. The
IIPB Consortium was set up by the first and last authors of
the study (I.R. and M.M.) in 2017. The authors aimed to
include in the consortium as many countries as possible that
differed from each other in terms of their geographical posi-
tion, cultural values, and socioeconomic level. Thus, in a first
step, based on the foregoing criteria, the authors contacted a
number of collaborators to invite them to participate in the
project. Twenty-two countries, including Belgium as the co-
ordinating country, joined the consortium through this process
(Australia, Brazil, Cameroun, Chile, Costa Rica, Cuba,
France, Italy, Lebanon, Peru, Poland, Portugal, Romania,
Rwanda, Spain, Switzerland, The Netherlands, Togo, UK,
USA, and Vietnam). In a second step, the first author
contacted well-known experts in parenting in order to supple-
ment this initial pool and to increase the diversity of cultural
values. Eight more countries were recruited through
this process (Algeria, Canada, China, Finland, Germany,
Japan, South Korea, and Sweden). In the last step, to further
extend the number of countries included in the study, when an
author from a non-participating country wrote to I.R. or M.M.
to inquire about parental burnout (e.g., about the Parental
Burnout Assessment-PBA; Roskam et al., 2018),
they invited him/her to join the consortium. Twenty more
countries were invited to join the consortium through that
means (Argentina, Austria, Burundi, Colombia, Congo,
Ecuador, Egypt, Greece, Iran, Israel, Mexico, Morocco,
Norway, Pakistan, Russia, Serbia, Singapore, South Korea,
Thailand, and Uruguay).
Countries that expressed interest received a Call for
participationexplaining the background and aims of
the study, the larger goals of the IIPB Consortium, the
commitments of the IIPB members and coordinators,
and the deadlines that would need to be met for trans-
lating the instrument, obtaining ethical approval, and
collecting the data. Then, countries that confirmed their
wish to join the consortium (i.e., 46 countries out of the
50 countries who received the call; Congo, Israel,
Table 1 (continued)
Power
Distance
Individualism Masculinity Uncertainty
Avoidance
Long-Term
Orientation
Indulgence Growth
national
product
Parental
burnout
Parental Burnout
Assessment Reliability
(Cronbach α)
Prevalence
of parental
burnout
(86) %
1
Prevalence
of parental
burnout
(92) %
2
Prevalence of
parental
burnout (92)
% random
sample
3
Prevalence of
parental
burnout (92)
% weighting
sample
4
MSD
Togo –– 5.36 18.00 20.29 0.91 1.9 1.9 1.7
Turkey 66 37 45 85 46 49 766.43 12.21 14.17 0.90 0.4 0.0 0.0 0.0
UK 35 89 66 35 51 69 2828.64 28.01 24.68 0.96 3.3 3.0 2.9
Uruguay 61 36 38 99 26 53 60.18 12.03 13.58 0.91 0.3 0.3 0.3
USA 35 89 66 35 51 69 20,494.05 32.59 33.02 0.97 8.9 7.9 5.6 8.4
Vietnam 70 20 40 30 57 35 241.27 12.17 16.44 0.94 0.7 0.4 0.4
1
The prevalence was estimated using a cutoff score of 86
2
The prevalence was estimated using a cutoff score of 92
3
To control for sample size differences, prevalence rates were reassessed on samples of approximately 200 randomly selected parents in all samples with more than 299 subjects
4
To control for overrepresentation of mothers in the survey, prevalence rates were reassessed weighting for sex frequencies in each country
Affective Science
Table 2 Data collection procedure in each country
1
Translation and back-translation
2
Survey
Language
Sampling Procedure Location of Data Collection
3
Survey Type
4
(% Online)
Response Rate (%) Attrition
Rate (%)
5
Period of Data
Collection
Algeria Yes Arabic Snowball Oran, Mostaganem,
Tlemcen, Ain
Temouchent, Relizane,
Chlef, El Bayadh,
Annaba, Constantine et
Oum El Bouaghi
0 90 5 March-May 2018
Argentina Yes Spanish Snowball and convenience San Miguel de Tucumán 100 Not applicable
6
29 December
2018-March 2019
Australia Not applicable
7
English Snowball New South Wales, Victoria,
Queensland,
Western Australia, South
Australia,
Tasmania, Australian
Capital Territory
100 Not applicable 45.6 May 2019
Austria Yes German Snowball and convenience Undefined 100 Not applicable 50.8 February-May 2019
Belgium Yes (Dutch version)-Not
applicable (French version)
French
Dutch
Snowball Flanders and Wallonia 100 Not applicable 26 February-June 2018
Brazil Yes Portuguese Snowball and convenience São Paulo and Rio de Janeiro
states:
Amazonas, Ceará, Mato
Grosso do Sul,
Minas Gerais, Paraíba,
Paraná,
Pernambuco, Piauí, Rio de
Janeiro, São
Paulo, Sergipe
65.1 Not applicable Not available November
2018-March 2019
Burundi Not applicable French Stratified Bujumbura Mairie,
Bujumbura rural,
Bururi, and Rutana
0 Not applicable 0 February-March 2020
Cameroun Not applicable French Convenience Yaounde 0 61 11 December 2017-April
2018
Canada Not applicable French Snowball Ontario, Manitoba,
Saskatchewan,
Alberta, Québec,
territoires du Nord-
Ouest
100 Not applicable 55 May-December 2018
Chile Yes Spanish Snowball and convenience Santiago, Los Lagos (Puerto
Montt), Del
Maule (Talca)
100 Not applicable 56 February-October
2018
China Yes Chinese Convenience Zhejiang 100 77 16 January 2018
Colombia Yes Spanish Snowball and convenience Undefined 100 Not applicable Not available December 2017-April
2018
Affective Science
Table 2 (continued)
Translation and back-translation
2
Survey
Language
Sampling Procedure Location of Data Collection
3
Survey Type
4
(% Online)
Response Rate (%) Attrition
Rate (%)
5
Period of Data
Collection
Costa Rica Yes Spanish Snowball and convenience San José, San Ramon,
Heredia, Cartago,
Alajuela
94 Not applicable 88 March-June 2018
Cuba Yes Spanish Snowball and convenience La Havane, Mariel
(Artemesia)
0 98.3 1 September-December
2018
Ecuador Yes Spanish Convenience Quito, Latacunga, Ibarra
Otavalo, Saquisilí, Salcedo,
El corazón,
Guaranda, Tulcán,
Cuenca, Guayaquil,
Portoviejo, Esmeraldas,
Lago
Agrio/Sucumbíos, Puyo
100 Not applicable 40 March-September
2018
Egypt Yes Arabic Snowball and convenience Menoufia regions- 10 cites;
Shebin el
kom, Sadat, Menoufa,
Bagour, Ashmon,
Quessna, Shodaa, sir
elayan, Tala, and
birkt-elsaba
0 90 10 February-March 2020
Finland Yes Finnish Snowball and convenience Hyvinkää, Posio, Jyväskylä 86.3 99.4 Not available February-April 2018
France Not applicable French Snowball and convenience Provence-Alpes-Côte
dAzur, Ile-de-
France
100 Not applicable 33 January-July 2018
Germany Yes German Convenience Ulm, Baden-Württemberg 100 20 49 May-November 2019
Iran Yes Persan Convenience Tehran 0 Not available 3 August-September
2018
Italy Yes Italian Snowball and convenience Padova 98 Not applicable 28 March-December
2018
Japan Yes Japanese Quota sampling (by a
research company)
The 47 prefectures in Japan 100 Not applicable 34 July 2018
Lebanon Yes French
Arabic
Stratified Mont Liban, Beyrouth, Liban
North,
Liban South, Nabatieh,
Beqaa
100 46 Not available August-September
2018
Pakistan Yes Urdu Convenience Lahore 0 98 0 July 2018
Peru Yes Spanish Convenience Lima, Arequipa, Cajamarca,
San Martin,
La Libertad, Lambayeque
46 Not available 19 February-May 2018
Poland Yes Polish Snowball and convenience Warsaw 85 Not available 1 February-June 2018
Portugal Yes Portuguese Snowball and convenience Coimbra, Porto 81 50 (for paper
pencil version)
22 April-December 2018
Affective Science
Table 2 (continued)
Translation and back-translation
2
Survey
Language
Sampling Procedure Location of Data Collection
3
Survey Type
4
(% Online)
Response Rate (%) Attrition
Rate (%)
5
Period of Data
Collection
Romania Yes Romanian Convenience Bucharest, Timisoara 86 Not available 51 December 2017-May
2018
Russia Yes Russian Snowball and convenience Undefined 100 Not applicable <1 April-December 2018
Rwanda Not applicable English
French
Snowball and convenience Undefined 58 90 (for paper
pencil version)
Not available June-July 2019
Serbia Yes Serbian Snowball and convenience Belgrade 100 Not applicable 22 November 2018-June
2019
Spain Yes Spanish Snowball and convenience Spain (undefined) and
Basque Country
(Galdakao and Igorre,
Azpeitia and
Errenteria,
Vitoria-Gasteiz, Leitza)
68 15 23.4 February -September
2018
Sweden Yes Swedish Snowball Undefined 100 Not applicable 27 March-May 2019
Switzerland Not applicable French Snowball and convenience Canton of Vaud 100 Not applicable 44 May-October 2018
Thailand Yes Thai Convenience Chiand Mai 0 Not available 0 July-September 2018
The
Netherla-
nds
Yes Dutch Snowball and convenience Tilburg 100 Not applicable 28 March 2018-February
2019
Togo Not applicable French Convenience Tsévié, Lomé 10 50 33 January
2017-February
2018
Turkey Yes Turkish Convenience Ankara, Istanbul 0 63 5 April-June 2018
UK Not applicable English Snowball and convenience England, Scotland, Wales
and Northern
Ireland
100 Not applicable 41 October 2018-March
2019
Uruguay Yes Spanish Snowball and convenience Montevideo 0 0 0 October 2018
USA Not applicable English Convenience and quota Stanford, Florida 100 Not applicable Not available March
2018-September
2019
Vietnam Yes Vietnamese Snowball and convenience Ho Chi Minh City, Thanh
Hoa, Cam
Ranh province, Lam
Dong, Mekong
Delta area
12.5 Not applicable 11 March-May 2018
1
More information about the data collection procedure in each country is available upon request to the first author.
2
Translation and back-translations were made once for each language. The questionnaire
was translated in a concerted manner by countries using the same version. For example, Spanish-speaking countries coordinated the Spanish translation. Some minor adjustments could however be made by
each country.
3
Location is larger for countries where online survey was used because it has been spread all over the country. The location that is mentioned is where the sampling and data collection started.
4
Survey Type: Online vs. Paper-Pencil.
5
Percentage of participants who did not complete the survey completely.
6
For online surveys, the response rate is impossible to estimate.
7
The French and English
version of the IIPB survey were already available for use.
Affective Science
Table 3 Sociodemographic characteristics of respondents in each country (standard deviations are in brackets)
Sample
size
Age Sex (%
mothers)
Educational
level
Working
status
(% paid
professional
activity)
Ethnicity
(%
natives)
Family types
1
Two
opposite-sex
parents
Two
same-sex
parents
Single
parent
Step-family Multigenerational Polygamous
Algeria 318 41.62 (10.43) 60.4 14.02 (4.89) 70.1 89.9 68.2 0 1.6 0 30.2 0
Argentina 177 40.02 (9.88) 66.7 16.45 (4.08) 87.6 98.9 65.0 0 13.6 9.6 9.6 0.6
Australia 212 44.80 (10.60) 51.4 13.17 (2.78) 56.6 79.2 69.3 0 17.9 7.5 3.3 0
Austria 185 33.81 (6.47) 89.2 13.27 (3.08) 70.8 91.4 86.5 0.5 6.5 3.8 2.7 0
Belgium 1689 38.41 (7.53) 86.3 16.55 (2.61) 90.9 86.5 79.2 0.8 10.7 7.9 0.4 0
Brazil 301 42.03 (9.09) 63.5 15.89 (4.22) 75.4 97.6 90.6 0 3.4 4.0 1.0 0
Burundi 187 38.9 (9.51) 49.7 10.78 (5?31) 67.4 97.3 86.6 0 12.8 0.5 0 0
Cameroun 208 38.31 (9.72) 50 14.35 (3.20) 72.6 99.0 69.2 0 16.3 3.4 5.8 1.4
Canada 279 34.08 (6.66) 92.1 15.89 (2.80) 84.2 95.7 91.4 0.4 9.0 8.4 0.7 0
Chile 431 36.57 (6.56) 85.6 17.93 (3.36) 76.3 93.3 72.4 0.5 11.1 8.1 6.5 0
China 722 38.75 (4.68) 55.5 10.28 (2.87) 91.4 66.9 82.8 0.3 3.7 2.4 9.7 0
Colombia 95 74.7 84.2 93.7 63.2 0 23.2 4.2 8.4 0
Costa Rica 248 37.79 (8.15) 58.9 16.41 (4.47) 84.7 93.5 74.5 0.4 6.9 7.7 7.3 0
Cuba 241 40.09 (10.24) 57.3 13.69 (3.09) 83.8 99.2 51 0 7.1 11.6 28.6 0.4
Ecuador 146 32.45 (7.50) 69.9 17.21 (3.03) 85.6 91.8 65.1 0 11.6 6.8 15.1 0.7
Egypt 267 47.99 (6.47) 56.2 11.30 (3.54) 98.5 89.5 79.0 0.4 12.7 0.7 7.1 0
Finland 1730 36.47 (6.49) 90.7 17.69 (3.40) 75.5 98.7 78.7 0.5 8.7 9.7 0.3 0
France 1357 38.06 (8.42) 81.4 15.01 (2.83) 83.0 90.3 75.9 0.7 11.6 10.1 0.8 0.1
Germany 204 35.63 (7.90) 68.6 13.49 (4.89) 74.0 85.3 72.5 1.0 13.2 8.8 2.9 0
Iran 448 40.33 (8.71) 50.4 13.73 (3.45) 67.6 98.2 85.4 0 10.1 2.9 0.9 0
Italy 350 43.53 (8.97) 71.4 14.99 (3.93) 85.7 90.0 87.4 0 4.9 4.6 2.0 0
Japan 500 54.36 (14.65) 50.0 14.29 (2.49) 59.6 100 80.6 0.4 7.4 1.2 5.0 0
Lebanon 201 37.44 (8.43) 67.2 16.17 (3.67) 67.7 96.0 93.5 0 5.0 1.0 0.5 0
Pakistan 228 50.5 (10.27) 56.1 11.95 (3.68) 40.7 91.4 75.5 0 8.8 2.0 5.9 1.0
Peru 312 40.18 (10.68) 69.9 14.88 (4.78) 84.6 92.6 65.4 0.6 14.7 8.3 10.6 0
Poland 457 34.76 (6.89) 71.1 17.52 (3.51) 75.5 96.1 86.4 0 5.0 3.5 4.8 0
Portugal 407 41.85 (8.12) 50.4 14.85 (3.83) 92.8 84.0 88.8 0 3.3 6.3 1.5 0.3
Romania 344 37.15 (5.58) 62.5 16.78 (2.86) 90.7 96.2 91.6 0 3.2 2.6 2.3 0
Russia 365 34.41 (6.71) 72.1 14.45 (4.19) 83.6 92.1 78.1 0 6.6 9.0 4.9 0
Rwanda 240 37.54 (10.02) 52.5 13.17 (5.18) 78.8 83.3 71.3 0.4 19.2 0.8 4.6 1.3
Serbia 228 38.10 (5.70) 77.2 14.90 (5.16) 86.0 79.8 92.5 0 3.9 0 1.8 0
Spain 696 40.91 (8.13) 76.7 15.14 (4.11) 82.3 89.8 80.6 0 8.4 6.2 2.9 0.1
Sweden 796 40.66 (5.04) 93.0 15.35 (3.16) 87.3 90.3 73.2 0.8 12.?2 9.3 0.5 0
Switzerland 419 40.18 (6.86) 64.7 16.42 (3.58) 92.1 67.8 81.6 0.5 10.7 6.9 0.2 0
Thailand 398 43.08 (5.99) 52 3.32 (1.05) 97.2 99.2 69.4 0.3 2.3 1.3 25.8 0.3
The Netherlands 221 37.21 (8.82) 71.9 16.31 (2.40) 93.2 93.6 88.2 0.5 5.4 3.6 0.5 0.5
Togo 103 37.80 (8.75) 35.9 13.62 (2.99) 86.4 95.1 68.0 0 21.4 1.9 1.0 7.8
Turkey 452 36.77 (6.51) 59.7 16.67 (3.56) 74.8 99.1 86.2 0 6.4 0.4 0 6.7
UK 271 39.15 (8.52) 60.1 15.41 (3.32) 83.4 76.0 89.3 0 7.4 2.6 0.4 0
Uruguay 299 35.09 (6.37) 62.9 12.86 (4.77) 89.6 94.6 77.3 0 9.7 5.4 5.4 0
USA 406 38.20 (9.03) 68.7 15.42 (3.51) 76.1 91.1 72.4 0.2 16.5 5.7 3.9 0.2
Affective Science
Table 3 (continued)
Vietnam 271 36.83 (7.81) 55.7 14.12 (4.14) 95.5 95.9 77.4 0.8 1.9 0.4 18.5 0
Pooled sample 17,409 39.20 (8.90) 71.0 14.89 (4.34) 80.2 90.8 78.7 0.3 9.0 5.9 4.6 0.3
Number of
biological
children
Number of children
in the household
Age of the
youngest
child
Age of the
oldest child
Number of women
caring for children
Number of men
caring for children
Years in the
country
Hours with
children
Neighborhood profiles
%
disadvantaged
%
average
%
prosperous
Algeria 2.67 (1.65) 2.66 (1.64) 7.71 (7.90) 12.61 (10.38) 1.58 (1.06) 1.42 (.97) 39.97 (11.92) 8.67 (6.17) 5.0 83.3 11.6
Argentina 2.34 (1.48) 2.20 (1.11) 9.30 (8.07) 13.67 (10.04) 1.65 (.93) 1.15 (.73) 39.25 (10.60) 10.28 (5.18) 2.3 72.9 24.9
Australia 2.05 (1.03) 1.75 (0.86) 9.74 (7.49) 14.27 (9.18) .99 (0.49) .92 (0.55) 40.15 (14.79) 6.49 (3.81) 5.7 74.1 20.3
Austria 1.61 (.92) 1.58 (.82) 2.49 (3.98) 4.52 (5.69) 1.08 (0.36) 0.96 (0.39) 32.37 (8.12) 10.68 (5.83) 2.7 69.2 28.1
Belgium 2.07 (.96) 2.09 (1.06) 5.98 (5.92) 8.87 (7.11) 1.19 (.67) .98 (.54) 35.13 (11.09) 5.65 (3.39) 3.1 47.5 49.4
Brazil 1.61 (0.81) 1.52 (0.76) 8.82 (7.54) 11.10 (7.94) 1.19 (0.56) 1.01 (0.48) 5.70 (4.57) 14.5 66.6 18.9
Burundi 3.61 (2.03) 3.94 (2.24) 4.97 (5.50) 12.71 (8.11) 1.57 (1.01) 1.41 (1.03) 37.61 (11.19) 5.84 (4.33) 20.3 44.9 19.8
Cameroun 3.08 (2.22) 3.74 (2.90) 5.39 (6.64) 14.19 (9.36) 1.57 (1.15) 1.19 (0.88) 37.94 (10.12) 8.57 (5.33) 21.2 71.2 7.7
Canada 2.08 (0.87) 2.12 (0.86) 3.70 (4.21) 7.04 (5.81) 1.05 (.69) .98 (0.51) 33.04 (8.08) 8.90 (6.70) 7.5 60.6 31.9
Chile 1.74 (0.91) 1.80 (1.33) 4.70 (5.86) 8.23 (7.33) 1.51 (0.80) .99 (0.57) 34.40 (9.34) 10.54 (7.45) 2.6 59.6 37.8
China 1.48 (0.59) 1.49 (0.59) 8.64 (4.48) 14.18 (3.29) 1.78 (0.94) 1.62 (0.88) 29.75 (12.75) 3.84 (2.60) 5.3 89.6 5.1
Colombia 1.62 (0.76) 1.57 (0.72) 8.31 (7.22) 12.28 (8.57) 1.57 (0.95) .98 (.77) 36.40 (13.51) 7.58 (6.02) 3.2 63.2 33.7
Costa Rica 1.62 (0.88) 1.51 (0.72) 7.31 (6.90) 9.16 (8.33) 1.50 (0.83) 1.16 (0.71) 36.35 (9.60) 9.28 (6.30) 4.4 64.9 30.6
Cuba 1.70 (0.61) 1.51 (0.58) 10.20 (7.26) 14.17 (9.33) 1.66 (0.74) 1.27 (0.70) 40.07 (10.21) 10.93 (4.39) 9.5 61.4 29.0
Ecuador 1.64 (0.78) 1.63 (0.74) 5.92 (4.71) 8.23 (6.68) 1.97 (1.05) 1.39 (0.89) 29.62 (10.26) 7.57 (4.92) 2.7 70.5 26.7
Egypt 3.33 (1.34) 3.00 (1.38) 13.96 (6.41) 23.19 (7.02) 1.34 (0.98) 1.05 (1.10) 43.57 (14.61) 8.33 (3.51) 16.1 62.9 21.0
Finland 2.15 (1.18) 2.24 (1.29) 4.34 (4.24) 7.52 (5.31) .92 (0.37) .87 (0.43) 35.54 (7.12) 7.71 (3.72) 0.0 99.9 0.1
France 1.97 (0.90) 1.85 (0.85) 6.47 (5.99) 9.66 (7.64) 1.38 (1.18) .97 (0.69) 34.81 (11.37) 8.30 (5.22) 2.9 57.0 40.0
Germany 1.79 (1.01) 1.70 (0.89) 4.97 (4.89) 7.97 (6.76) 1.01 (0.49) .90 (0.53) 33.16 (10.78) 7.31 (4.13) 4.9 74.5 20.6
Iran 1.88 (1.01) 1.73 (0.77) 9.74 (7.30) 13.98 (9.24) 1.08 (0.40) 1.00 (0.31) 39.94 (8.74) 5.84 (3.49) 11.7 59.7 28.6
Italy 1.78 (0.75) 1.74 (0.74) 9.44 (7.12) 12.48 (8.86) 1.13 (0.52) 1.02 (0.39) 41.55 (11.83) 7.30 (5.21) 2.0 74.9 23.1
Japan 1.96 (0.76) 1.56 (0.73) 15.00 (11.64) 23.23 (14.36) 1.07 (0.47) .92 (.48) 53.27 (15.77) 4.80 (4.15) 1.6 83.0 15.4
Lebanon 2.33 (1.15) 2.18 (1.03) 7.74 (6.24) 10.51 (8.02) 1.22 (0.49) 1.00 (0.28) 35.00 (11.51) 7.45 (3.11) 6.5 69.7 23.9
Pakistan 4.48 (1.91) 4.78 (2.86) 14.62 (7.79) 21.69 (10.45) 2.83 (2.39) 2.40 (1.43) 45.94 (9.77) 7.12 (5.64) 29.4 57.5 13.1
Peru 1.96 (.89) 1.95 (1.05) 9.08 (8.49) 13.20 (9.96) 1.86 (1.14) 1.36 (1.06) 37.37 (13.74) 8.35 (5.58) 6.4 66.0 27.6
Poland 1.72 (0.95) 1.71 (0.93) 4.85 (4.86) 6.44 (5.78) 1.20 (0.84) .98 (0.62) 33.73 (8.70) 7.97 (4.82) 4.4 76.1 19.5
Portugal 1.73 (0.84) 1.66 (0.71) 8.30 (6.47) 11.14 (8.18) .99 (0.44) .88 (0.41) 29.31 (16.84) 4.86 (2.84) 1.2 62.9 35.9
Romania 1.56 (0.64) 1.56 (0.62) 4.00 (4.04) 7.02 (5.17) 1.4 (0.73) 1.10 (0.61) 36.01 (8.09) 7.32 (6.17) 2.6 26.7 70.6
Russia 1.69 (0.82) 1.71 (0.83) 4.04 (3.88) 8.01 (6.25) 1.27 (0.65) 1.04 (0.53) 32.70 (8.75) 7.63 (5.25) 0.5 59.7 39.7
Rwanda 2.83 (2.08) 3.12 (2.03) 6.37 (5.99) 13.83 (9.50) 1.40 (0.83) .90 (0.95) 34.32 (10.80) 6.31 (6.08) 14.6 54.2 31.3
Affective Science
Norway, and Singapore did not confirm their participa-
tion) received the English and French versions of the
study protocol which was approved by the Ethics
Committee of the Psychological Sciences Research
Institute at UCLouvain in Belgium (Reference 2017-
24; January 25, 2018). This protocol included the in-
formed consent, demographic questions, and a few
questionnaires (see the Measuressection below) mea-
suring the variables of interest in this study. Countries
were free to add other measures at the end of the study
protocol if they wish. In the end, 42 countries out of
the 46 completed the data collection. Researchers from
Greece, Mexico, Morocco, and South Korea withdrew
from the consortium due to unforeseen personal or pro-
fessional circumstances.
Non-English speaking or non-French speaking countries first
translated (and back-translated) the study protocol. The Call for
participationrecommended following the WHO standards for
the process of translation and adaptation of instruments (http://
www.who.int/substance_abuse/research_tools/translation/en/).
Translation and back-translations were made once for each of the
21 different languages, (i.e., Arabic, Basque, Chinese, Dutch,
English, Finnish, French, German, Japanese, Persian, Polish,
Portuguese, Romanian, Russian, Serbian, Spanish, Swedish,
Thai, Turkey, Urdu, and Vietnamese). All countries submitted
the study to the local Ethics committee for approval except where
ethics approval was not mandatory (see Table 2) and started the
recruitment once the study was approved. As shown in Table 2,
the recruitment mode varied according to local practices: the
study was completed online in 19 countries, mostly online in 7
countries, exclusively on paper and pencil in 11 countries, mostly
on paper and pencil in 2 countries, and a mix of both in 3 coun-
tries. The majority of the countries in which the study was con-
ducted fully online included three attentional check questions to
enable researchers to identify people who did not respond seri-
ously to the study. These questions were randomly inserted in the
survey and the instruction had the same length as the other items.
They required participants to select, for instance, every dayfor
that particular question. Participants who failed to select the right
answer to the three attentional check questions were removed.
Measures
We measured the sociodemographic characteristics of the par-
ents. While reporting sex, age, or number of years in the country
seemed very simple, asking about household/family composi-
tion, occupational status, or ethnicity in a cross-cultural study
involving very diverse countries was much more difficult. In
order to formulate the best items, we used a twofold strategy.
First, we discussed with several consortium members to approve
this specific part of the IIPB protocol to ensure that the questions
captured the sociodemographic characteristics of respondents in
a way that was valid in all countries. For example, working status
Table 3 (continued)
Serbia 1.61 (0.64) 1.63 (0.69) 4.20 (4.38) 6.81 (5.63) 1.14 (0.63) 1.03 (0.53) 33.36 (11.04) 7.67 (4.58) 2.6 48.2 49.1
Spain 1.72 (0.71) 1.72 (0.77) 8.06 (7.24) 9.95 (8.37) 1.42 (0.94) 1.14 (0.70) 38.74 (11.45) 8.92 (6.47) 6.4 78.5 15.1
Sweden 2.17 (0.95) 2.14 (0.94) 6.42 (4.79) 11.17 (6.16) 1.00 (0.55) .98 (0.57) 38.06 (8.71) 6.41 (3.14) 4.8 75.2 20.1
Switzerland 1.93 (0.82) 1.96 (0.81) 6.08 (5.37) 8.96 (6.30) 1.10 (0.54) .95 (0.46) 31.24 (14.28) 6.66 (4.14) 0.2 49.6 50.1
Thailand 1.78 (0.65) 1.79 (0.74) 8.76 (3.90) 12.51 (4.89) 1.82 (0.99) 1.47 (0.84) 42.55 (6.63) 5.94 (3.66) 1.0 51.7 47.3
The Netherlands 1.83 (0.84) 1.71 (0.83) 5.76 (5.78) 6.76 (6.85) 1.50 (1.04) 1.14 (0.62) 35.64 (11.20) 6.43 (3.08) 2.3 53.4 44.3
Togo 2.46 (1.59) 2.93 (1.69) 4.45 (5.48) 11.12 (8.64) 1.38 (0.70) 1.20 (1.14) 35.52 (10.76) 9.10 (6.38) 20.6 73.5 5.9
Turkey 1.71 (0.72) 1.65 (0.65) 4.41 (3.64) 7.54 (5.92) 1.15 (0.52) 1.00 (0.42) 36.44 (6.88) 6.64 (3.80) 4.6 73.0 22.3
UK 1.88 (0.92) 1.72 (0.73) 6.96 (6.64) 9.32 (7.91) 1.01 (0.25) .95 (0.40) 33.22 (14.79) 6.59 (3.88) 4.4 52.0 43.5
Uruguay 1.62 (0.75) 1.62 (0.73) 2.72 (1.69) 6.14 (5.09) 1.41 (0.75) 1.06 (0.55) 33.60 (8.85) 11.78 (5.37) 11.7 59.7 28.6
USA 1.95 (1.06) 1.90 (1.03) 6.20 (5.79) 10.55 (7.47) 1.12 (0.79) .93 (0.72) 35.29 (11.73) 7.55 (5.13) 9.6 68.5 21.9
Vietnam 1.68 (0.79) 1.66 (1.05) 5.74 (5.47) 8.21 (7.48) 1.46 (0.82) 1.18 (0.72) 36.37 (8.36) 4.63 (3.01) 5.2 48.5 46.3
Pooled sample 2.00 (1.12) 1.98 (1.19) 6.67 (6.42) 10.55 (8.42) 1.29 (0.85) 1.07 (0.69) 36.39 (11.54) 7.23 (4.92) 5.0 67.3 27.6
Note:
1
The total frequency may be lower than 100% when some participants in the country checked otheras family type
Affective Science
was assessed by the notion of paid professional activity,be-
cause the meaning of work(i.e., what is considered a profes-
sional activity) varies considerably across cultures. Since we
wanted to focus on work as a source of financial support for
the family (i.e., the breadwinner function), we referred to the
notion of paid work activityrather than simply work.Next,
we consulted the literature. For example, the way we measured
ethnicity drew on previous research, particularly that of Jacobs
et al. (2009).
Beyond demographic measures, the common protocol in-
cluded several measures designed to address different research
questions and goals (e.g., comparing the prevalence of parental
burnout across countries; investigating the relations between
parental burnout and perceived ideal parental self-
discrepancies; examining the contribution of different parental
duties to parental burnout). Because these questions are too
diverse to be addressed in the same article, we describe below
only the measures used in the current article. The full protocol is
available on Open Science Framework (OSF) at https://osf.io/
94w7u/?view_only=a6cf12803887476cb5e7f17cfb8b5ca2.
Demographic Questions Participants were first asked about
their sex (Are you a father/a mother?); age (How old are
you? [in years; e.g., 45; just write the number]); educational
level (What is your level of education? [number of successful-
ly completed school years from the age of 6; e.g., 5; just write
the number]); number of biological children (How many bio-
logical children do you have? [e.g., 2; just write the number]);
number of children living in the household (How many chil-
dren live in your household [your biological children and/or
children of your partner in case of a step-family and/or chil-
dren of relatives in case of a multigenerational family and/or
children of your spouses other partners in case of polyga-
my]? (e.g., 5; just write the number]); age of the youngest
child (How old is the youngest? [in years; e.g., 15; just write
the number; if the child is less than 12-month-old, write 0]);
age of the oldest child (How old is the oldest? [in years; e.g.,
15; just write the number; if the child is less than 12-month-
old, write 0]); number of hours spent with children per day
(On average, how many hours a day do you spend with your
child[ren] [without taking the night into account]? [in hours;
e.g., 5; justwrite the number]); number of women living in the
household/direct entourage and caring for the children on a
daily basis (How many women [e.g., co-wife, grandmother,
servant, etc.] live in your household/direct entourage and
care for the children on a daily basis [including yourself if
youareawoman]?(e.g., 3; just write the number]); number
of men living in the household/direct entourage and caring for
the children on a daily basis (How many men [e.g., grandfather,
uncles, etc.] live in your household/direct entourage and care
for the children on a daily basis [including yourself if you are a
man]? [e.g., 3; just write the number]); working status (Do you
have a paid professional activity? Yes/No); years spent in the
country (How long have you lived in this country? [in years;
e.g., 25; just write the number]); ethnicity (Are you born in your
current country of residence? Yes/No; Are your parents born in
your current country of residence? Both my mother and my
father are born in my current country of residence/Either my
mother or my father is born in my country of residence/Neither
my mother nor my father are born in my country of residence);
family type (What type is your family? Two-parent [you are
raising your children with a partner who is the parent of the
children]/Single parent [you are raising your children alone]/
Step-family [you are raising your children with a partner who
is not necessarily the parent of the children and who may have
children from another union, whether living in your household
or not]/Homo-parental [you are raising your children with a
same-sex parent]/Multigenerational [parents, grandparents,
uncles or aunts and their children are living together]/
Polygamous [multiple partners with children in the same
household]/Other); and neighborhood profile (In what kind of
neighborhood is your home? In a relatively disadvantaged
neighborhood/In an average neighborhood/In a relatively
prosperous neighborhood).
Parental Burnout Parental burnout was assessed with the
Parental Burnout Assessment (PBA; Roskam et al., 2018), a
23-item questionnaire assessing the four core symptoms of
parental burnout: emotional exhaustion (9 items; e.g., Ifeel
completely run down by my role as a parent), Contrast with
previous parental self (6 items; e.g., ItellmyselfImnolonger
the parent I used to be), loss of pleasure in onesparentalrole
(5 items; e.g., I do not enjoy being with my children), and
emotional distancing from ones children (3 items; e.g., Iam
no longer able to show my childrenthat I love them)usinga7-
point frequency scale from 0 to 6 (never, a few times a year,
once a month orless, a few times a month, once a week, a few
times a week, every day). The parental burnout score is com-
puted by summing the item scores: higherscores reflect higher
parental burnout levels. The internal consistency (Cronbachs
alpha) of the scale in each country is figured in Table 1(range:
0.85 to 0.97).
Cultural Values Cultural values were assessed by the six di-
mensions identified by (Hofstede et al., 2016;Hofstede,2001;
Taras et al., 2010). Cultural value scores range between 0 and
100 (retrieved from https://www.hofstede-insights.com/
product/compare-countries/). Power Distance expresses the
degree to which less powerful members of a society accept
and expect that power is distributed unequally. In the present
sample, power distance scores ranged between 11 (Austria)
and 93 (Russia). Individualism describes a preference for a
loosely knitsocial framework in which individuals are expect-
ed to take care of only themselves and their immediate fami-
lies (as opposed to Collectivism, which describes a preference
for a tightly knit framework in society in which individuals are
Affective Science
integrated into strong, cohesive in-groups). In the present sam-
ple, Individualism scores ranged between 8 (Ecuador) and 90
(Australia). Masculinity describes a preference in society for
achievement, heroism, assertiveness, and material rewards for
success (as opposed to Femininity, which refers to a prefer-
ence for cooperation, modesty, caring for the weak, and qual-
ity of life). In the present sample, Masculinity scores ranged
between 5 (Sweden) and 95 (Japan). Uncertainty Avoidance
describes the degree to which the members of a society feel
uncomfortable with uncertainty and ambiguity. In the present
sample, Uncertainty Avoidance scores ranged between 29
(Sweden) and 99 (Uruguay). Long-Term Orientation relates
to how a society deals with the challenges of the present and
the future. In the present sample, Long-Term Orientation
scores ranged between 7 (Egypt) and 87 (China). Indulgence
describes a society that allows relatively free gratification of
basic and natural human drives related to enjoying life and
having fun. In the present sample, Indulgence scores ranged
between 0 (Pakistan) and 83 (Colombia).
Statistical Analyses
Before merging samples, we conducted a number of checks
on the individual database of each country. In concrete terms,
when we received a database, we first checked whether people
responded seriously: participants who failed to select the right
answer to the three attentional check questions (see the
Proceduresection) were removed from the database. We
then searched for the presence of outliers. For instance, the
level of education (i.e., number of successfully completed
school years from the age of 6) cannot be higher than the
participants age minus 6; the number of hours spent with
children per day cannot be greater than 24; the number of years
spent in the country cannot be greater than the age of the parent,
etc. Outlier values were removed. Then, missing data (identi-
fied as 99 or 999 in some countries) were all set to system
missing.Finally, in order to avoid mixing apples and oranges,
we ensured that all variables were coded according to the grid
provided by the consortium coordinator (I.R.). For instance, the
PBA had to be coded from 0 to 6 and not from 1 to 7. Sex had to
be coded 1 for fathers and 2 for mothers. Family types had to be
coded the same way even if some family types were removed in
some countries (see the Measuressection). We made the
corrections when necessary.
After proceeding to these preliminary checks, we per-
formed the statistical analyses. All syntax is available
on OSF at https://osf.io/94w7u/?view_only=
a6cf12803887476cb5e7f17cfb8b5ca2.
We first examined the internal consistency of the PBA in
each country separately via Cronbachs alpha coefficients.
One country had a very low internal consistency coefficient
(0.29), which led us to suspect a problem with the data, espe-
cially as all other countries had internal consistencies above
0.85 (which is well above the widely used threshold of 0.70).
The authors of the country in question asked us to disregard
this database and put another person in charge of the data
collection. We received a new database from this country
6 months later. The reliability of the PBA was 0.88, suggest-
ing that this database was indeed more reliable and could be
merged with the others. After ensuring that all variables were
encoded in the exact same way and that they were inthe exact
same order in all the databases, we merged the data from all
countries.
Next, we tested the first-order four-factor model and the
higher-order factor structure of the PBA on the pooled sample,
in the mothersand the fatherssubsamples, and in each of the
21 languages, through confirmatory factor analyses (CFA)
using structural equation modeling Lisrel software.
Skewness and kurtosis values indicated that several items
displayed deviations from normality. Conceptually, these de-
viations from normality make sense: like most mental health
indicators, burnout is expected to present an asymmetric dis-
tribution (i.e., to be positively skewed). The estimation meth-
od used was diagonally weighted least squares (DWLS) with
asymptotic covariance and polychoric correlation matrices.
We then tested the factorial invariance (including metric and
scalar invariance) of the PBA across sex and languages. We
used several goodness-of-fit indices to determine the accept-
ability of the models: Satorra-Bentler scaled chi-square statis-
tics (S-Bχ
2
; Satorra & Bentler, 1994), the root mean square
error of approximation (RMSEA), the standardized root mean
square residual (SRMR), the comparative fit index (CFI), and
the Tucker-Lewis index (TLI). For CFI and TLI, values close
to 0.90 or greater are acceptable to good. RMSEA and SRMR
should preferably be less than or equal to 0.08 (Hu & Bentler,
1999). For measurement invariance, we implemented a set of
nested models with gradually increasing parameters and con-
straints using a stepwise multiple group confirmatory factor
analysis or MG-CFA. In the first step, we tested the parental
burnout model for configural invariance as the basic level of
measurement invariance. In the second step, we assessed item
factor loadings in a metric invariance model. In the third step,
we tested scalar invariance with the intercepts set as equal
across groups. Finally, we verified the invariance of measure-
ment errors for a model in which all error variances were
constrained to be equal across groups. For measurement in-
variance, we reported change in S-Bχ
2
and we applied a cri-
terion of a 0.01 change in CFI, paired with a change in
RMSEA of 0.015 (Cheung & Rensvold, 2002;Rutkowski&
Svetina, 2014).
We examined the mean level and prevalence of parental
burnout in each country. Comparing prevalence across coun-
tries requires a common cutoff score on the PBA. Since the
choice of diagnostic thresholds is always debatable, we
worked with two cutoff scores and we estimated parental
burnout prevalence twice. The first cutoff score was based
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on the response scale: parents were judged to have parental
burnout if their score was equal to or greater than 92 (i.e., if
they experience all 23 parental burnout symptoms at least
once a week or if they experience at least 16 symptoms daily).
The second cutoff score was derived from the combination of
several parental burnout indicators, based on a preregistered
multi-method and multi-informant analysis strategy (i.e., self-
reported measures [provided by participants], clinical judg-
ments [completed by external judges based on a 5-min speech
provided by participants on their parenting experience], and a
biological measure of stress [the analysis of cortisol levels
contained in participantshair]): parents were judged to have
parental burnout if their score was equal to or greater 86 (see
https://osf.io/ujfb3 for more details about the analysis strategy).
We then considered the most stringent cutoff, (i.e., the most
conservative prevalence scores), for subsequent analyses. The
idea to use the most conservative prevalence values stems from
our wish to avoid overdiagnosis of parental burnout.
Because country samples were unequal in size and in sex
distribution, we then reassessed prevalence rates after control-
ling for these inequities. We dealt with sample size inequity by
randomly selecting 200 parents in all samples with more than
299 subjects. To control for overrepresentation of mothers in
the survey (and the related risk of overestimating the preva-
lence of parental burnout in countries where mothers report
more burnout), we used a post-stratification weight by adding
a value to each case in the data file which indicates how much
each case will count in the statistical procedure. The value was
obtained by dividing the sex proportion in the general popu-
lation (i.e., the sex distribution in the population is 50% fe-
males) by the sex distribution in each sample (e.g., in the
Algerian sample, the sex distribution is 60% mothers). Thus,
the weight value of 0.50/0.60 = 0.83 was obtained for
Algerian mothers and the corresponding weight obtained for
fathers was 0.50/0.40= 1.25. The prevalence rates were then
estimated using mothersand fathersweights in each country
with the SVY procedure in Stata15.
We examined the Pearson moment correlations between
both the prevalence and mean level of parental burnout in each
country and the six cultural values. We then performed mul-
tilevel random coefficient modeling analyses in Stata 15. We
first ran the unconditional model. After checking for the ab-
sence of multicollinearity, individual- and country-level vari-
ables were entered in three steps. In step 1 (conditional model
1), we controlled for sociodemographic variables (age, sex,
educational level, and type of neighborhood [disadvantaged,
average, prosperous], working status [having or not a paid
professional activity]; all of these being measured at the indi-
vidual level). In step 2 (conditional model 2), we introduced
variables influencing parental workload (number of children,
family type [single parent, two parents, multigenerational],
age of the youngest child, number of women taking care of
the children on a daily basis, number of men taking care of the
children on a daily basis, average number of hours spent with
the child[ren] on a daily basis; all these variables being mea-
sured at the individual level). In step 3 (conditional model 3),
we included the growth national product (GNP; database,
2019) and the six cultural values (i.e., Power Distance,
Individualism, Masculinity, Uncertainty Avoidance, Long-
Term Orientation, and Indulgence), all of these being obtained
at the country level. The multilevel random coefficient model-
ing analyses take into account that many covariates vary both
within and between countries. Thus, the effect of all
sociodemographic characteristics that we entered in the two
first steps was controlled for when we introduced cultural
values in the third model.
For the readability of the results, we translated the estimates
of the standard deviation between ( ffiffiffi
ψ
p) and within ( ffiffi
θ
p)
countries into R
2
as the percentage of variance explained by
the covariates considered in each of the three steps. Following
the suggestion of Raudenbush and Bryk Raudenbush & Bryk,
(2002), we considered the proportional reduction in each of
the variance components separately. R2
2;referring to the per-
centage of explained variance between countries, was com-
puted with the formula R2
2¼ψ0ψ1
ψ0, where ψ
0
is the between
countries variance estimated under the unconditional model
and ψ
1
is the between countries variance estimated under the
model of interest (i.e., conditional models 1 to 3). R2
1;referring
to the percentage of explained variance within countries, was
computed with the formula R2
1¼θ0θ1
θ0,whereθ
0
is the within
countries variance estimated under the unconditional model
and θ
1
is the within countries variance estimated under the
model of interest (i.e., conditional models 1 to 3). Greater
values indicate greater explanatory power.
Results
The analyses first revealed that the measure of parental burnout
used in this research (i.e., the Parental Burnout Assessment
Roskam et al., (2018) has excellent reliability across all 42
countries (all Cronbachs alphas > 0.85; see Table 1). Both
the original four-factor structure (Roskam et al., 2018)andthe
second-order factor model fitted the data, not only in the pooled
sample, but also in fathersand motherssubsamples and in the
21 languages separately (see Table 4). Because we used the
total score of parental burnout in the current study, we tested
measurement invariance of the second-order factor model
across both sex and the 21 languages. As shown in Table 5,
adequate model fit indices, ΔRMSEA, and ΔCFI indicated the
same number and pattern of dimensions across sex and lan-
guages. Metric and scalar invariances were supported as well,
and measurement errors in item responses were also equivalent
across sex and languages.
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Table 4 Model fit indices for the first-order and the second-order factor models ofthe PBA in thepooled sample, in fathersand motherssubsamples,
and in each language
First-order factor model Second-order factor model
S-Bχ
2
(224) RMSEA SRMR CFI TLI S-Bχ
2
(226) RMSEA SRMR CFI TLI
Pooled sample 17,112.04 0.066 0.040 0.99 0.99 17,498.05 0.067 0.041 0.99 0.99
Fathers 2955.05 0.050 0.036 0.99 0.99 2982.63 0.050 0.037 0.99 0.99
Mothers 14,350.72 0.072 0.043 0.99 0.99 14,768.63 0.073 0.044 0.99 0.99
Arabic 1095.04 0.073 0.056 0.99 0.99 1128.02 0.074 0.056 0.99 0.99
Basque 373.08 0.055 0.085 0.99 0.99 386.29 0.056 0.090 0.99 0.99
Chinese 514.98 0.042 0.042 1.00 0.99 519.52 0.042 0.042 1.00 1.00
Dutch 980.76 0.081 0.054 0.99 0.98 1000.73 0.082 0.055 0.99 0.98
English 1407.82 0.074 0.046 0.99 0.99 1435.99 0.074 0.046 0.99 0.99
Finnish 2559.54 0.078 0.048 0.99 0.98 2616.29 0.079 0.048 0.99 0.98
French 5826.92 0.078 0.047 0.99 0.98 5864.95 0.078 0.049 0.99 0.98
German 616.87 0.067 0.064 0.99 0.98 622.14 0.067 0.064 0.99 0.98
Japanese 428.98 0.043 0.037 1.00 1.00 432.80 0.043 0.037 1.00 1.00
Persian 729.47 0.077 0.076 0.99 0.98 733.33 0.077 0.076 0.99 0.98
Polish 984.56 0.086 0.056 0.98 0.98 1020.15 0.088 0.056 0.98 0.98
Portuguese 882.32 0.068 0.060 0.99 0.99 904.21 0.069 0.062 0.99 0.99
Romanian 979.58 0.099 0.059 0.98 0.98 1015.13 0.10 0.059 0.98 0.98
Russian 1025.38 0.071 0.051 0.99 0.98 1051.40 0.072 0.053 0.99 0.99
Serbian 559.55 0.081 0.082 0.98 0.98 582.40 0.083 0.085 0.98 0.98
Spanish 3098.03 0.074 0.051 0.99 0.99 3300.00 0.076 0.058 0.99 0.98
Swedish 782.65 0.056 0.046 0.99 0.99 797.42 0.057 0.046 0.99 0.99
Thai 379.47 0.043 0.077 1.00 1.00 383.47 0.043 0.079 1.00 1.00
Turkey 575.76 0.060 0.074 0.99 0.99 583.36 0.060 0.074 0.99 0.99
Urdu 842.07 0.110 0.110 0.95 0.95 902.46 0.12 0.12 0.95 0.94
Vietnamese 326.51 0.042 0.050 1.00 1.00 329.06 0.042 0.050 1.00 1.00
Table 5 Measurement invariance
of the Parental Burnout
Assessment across samples
Model S-Bχ
2
(df) RMSEA CFI ΔS-Bχ
2
(Δdf) ΔRMSEA ΔCFI
Across languages
Configural 17,654.51 (4662) 0.058 0.992 ––
Metric 21,804.88 (4746) 0.066 0.989 4150.37 (84) 0.008 0.003
Scalar 33,829.65 (5206) 0.082 0.982 12,824.77 (460) 0.016 0.007
Error 34,264.78 (5742) 0.078 0.982 435.13 (536) 0.004 0.000
Across sex
Baseline 14,899.43 (444) 0.062 0.992
Metric 17,671.10 (452) 0.067 0.990 2771.67 (8) 0.005 0.002
Scalar 27,570.08 (475) 0.082 0.984 9898.98 (23) 0.015 0.006
Error 31,879.86 (498) 0.086 0.982 4309.78 (23) 0.004 0.002
Note. Baseline invariance modeltests equivalence form of all the relationships by imposing configural invariance,
(i.e., the same indictors loading on the latent variables for each group). Metric model is a model where only the
factor loadings are equal across groups but the intercepts are allowed to differ between groups. This is called
metric invariance and tests whether respondents across groups attribute the same meaning to the latent construct
under study. Scalar model is a model where the loadings and interceptsare constrained to be equal. This is called
scalar invariance and implies that the meaning of the construct (the factor loadings), and the levels of the
underlying items (intercepts)are equal inboth groups. Error model is the most restrictive invariance measurement.
This is achieved when both loadings and the error variances are invariant across groups. It is considered as the
ideal level
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This allowed us to examine the mean level and prevalence
of parental burnout in each country (cutoff scores: 92 and 86
on a scale from 0 to 138). The resulting prevalence rates
corrected for inequities in sample size and sex, respectively,
are figured in the penultimate and last column of Table 1.As
shown in Fig. 1and Table 1, the prevalence of parental burn-
out greatly varies from country to country. This is true even
when we control for sample size or sex imbalance (see
Table 1). These differences between countries are also
reflected in the mean level of parental burnout in each country
(see Table 1). There is a difference of 33 points between the
country with the lowest mean level (i.e., Thailand) and the
country with the highest mean level of parental burnout (i.e.,
Poland).
Figure 1Percentage of parents who have parental burnout
(i.e., scoring 92 or above on the Parental Burnout Assessment)
in each country
The size of the differences in parental burnout between
countries suggested that cultural factors might be operative.
To investigate whether cultural values are associated with pa-
rental burnout, and knowing that there is no cultural indicator
specifically related to parenting that would be available for the
majority of the countries included in this study, we obtained
the position of each country on the six cultural values defined
by (Hofstede, 2001; i.e., Power Distance, Individualism,
Masculinity, Uncertainty Avoidance, Long-Term
Orientation, and Indulgence). The correlations between each
cultural value and both the prevalence and mean level of
Fig. 1 Prevalence of parental burnout across countries
Table 6 Bivariate correlations between Hofstedes cultural values and parental burnout
Prevalence of parental
burnout
Mean level of parental
burnout
Individualism Masculinity Uncertainty
Avoidance
Long-Term
Avoidance
Indulgence
Mean level of parental
burnout
0.83***
Power Distance 0.03 0.22 0.58*** 0.04 0.38* 0.03 0.60***
Individualism 0.53*** 0.50*** 0.16 0.33 0.21 0.49**
Masculinity 0.09 0.03 0.07 0.24 0.09
Uncertainty
Avoidance
0.02 0.10 0.07 0.26
Long-Term
Orientation
0.07 0.00 0.10
Indulgence 0.12 0.14
Note. Correlations are computed at the country level. *p<0.05,**p< 0.01, ***p<0.001
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parental burnout in each country are displayed in Table 6.
Individualism was the sole value to be significantly associated
with both the mean level and prevalence of parental burnout.
We represented the association between Individualism and the
mean level of parental burnout on the scatter plot depicted in
Fig. 2. As shown in this figure, the higher the individualism of
a given country, the higher the mean level of parental burnout
in that same country. The effect size is large (d= 1.16) accord-
ing to Cohens norms. As also shown in Fig. 2, the over-
whelming majority of individualistic countries are Euro-
American countries.
Figure 2Correlation between the level of parental burnout
in a country and the position of that country on the level of
individualism. Five countries Algeria, Cameroon, Cuba,
Rwanda, Togo are not represented in Fig. 2because the level
of individualism in these countries has not been reported by
Hofstede Individualistic countries exhibit much higher levels
of parental burnout.
To examine whether individualism predicted parental
burnout over and above sociodemographic variables, parental
workload, economic inequalities across countries, and the oth-
er cultural values (i.e., Power Distance, Masculinity,
Uncertainty Avoidance, Long-Term Orientation, and
Indulgence), we used the multilevel random coefficient
modeling analyses. We found significant effects for several
sociodemographic variables. In particular, parental burnout
was higher among younger parents, mothers, parents in dis-
advantaged neighborhoods, non-working parents, parents
with more children, parents with younger children, parents
in two-parent families (compared to those in multigenerational
families), single parents (compared to those in both two-parent
and multigenerational families), and parents in step families
(compared to those in both two-parent and multigenerational
families). The findings (Table 7) confirm that individualism is
significantly predictive of parental burnout beyond
sociodemographic variables, parental workload, economic in-
equalities across countries, and the five other cultural values
(B=0.24,p<0.001).
Discussion
The results of this study demonstrate that the prevalence of
parental burnout varies across the globe and that parental
burnout is linearly related to individualism. This relation held
even when sociodemographic variables (i.e., age, sex, educa-
tional level, type of neighborhood, and working status), pa-
rental workload (i.e., number of children, family type, age of
the youngest child, number of women and men taking care of
the children on a daily basis, and hours spent with the chil-
d[ren]), economic inequalities across countries, and the other
cultural values (i.e., Power Distance, Masculinity, Uncertainty
Avoidance, Long-Term Orientation, and Indulgence) were
controlled for in the multilevel random coefficient modeling
analyses. The strength of this study follows from the use of
data on a large number of parents (N= 17,409) from cultural-
ly, economically, and geographically diverse settings includ-
ing many diverse non-Western countries. This study is the first
ever to examine the role played by culture in parental burnout
and, as such, constitutes an important extension of previous
studies focused on individual and family predictors
(Mikolajczak & Roskam, 2018).
The findings suggest that culture has a major impact on
parental burnout and that parents from individualistic coun-
tries seem particularly exposed. The mechanisms that link
individualism and parental burnout remain to be studied. But
R = 0.503
R2 = 0.254
Fig. 2 Parental burnout and
individualism across countries
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the current results dovetail with sociologistsobservation that
parenting norms in Euro-American countries, (i.e., the most
individualistic ones), have become increasingly demanding
over the last 50 years (Geinger et al., 2014; Nelson, 2010),
resulting in intensification of parental investment (Faircloth,
2014;Glausiusz,2016;Hays,1996; Nelson, 2010) and grow-
ing psychological pressure on parents (Rizzo et al., 2013).
Whereas parenting is the subject of relatively little social or
political discourse in some parts of the world, in Euro-
American countries, parenting has become a matter of increas-
ing public interest and normative prescriptions (Faircloth,
2014). What parents feed their children, how they discipline
them, where they put them to bed, how they play with them:
all of these havebecome politically and morally charged ques-
tions (Faircloth, 2014, p. 27). The expectations towards par-
ents have drastically evolved over the last 50 years, to such an
extent that parents who would have been considered as good
and attentive parents 50 years ago would now be viewed as
neglectful at best (Nelson, 2010). According to many scholars,
Euro-American countries have entered the era of what Hays
called intensive motherhood/parenting,a child-centered, ex-
pert-guided, emotionally absorbing, labor-intensive, and fi-
nancially expensive view of parenting (Hays, 1996, p. 8).
Parents are expected to both reduce the slightest risks to
Table 7 Multilevel unconditional and conditional models predicting parental burnout
Unconditional model Conditional model 1 Conditional model 2 Conditional model 3
Estimate SE Estimate SE Estimate SE Estimate SE
Fixed part
Intercept 21.79*** 1.23 16.84*** 2.09 14.92*** 2.82 0.12.01*** 10.28
Individual level
Age 0.20*** 0.02 0.10* 0.04 0.08 0.05
Sex 6.83*** 0.45 7.42*** 0.57 7.58*** 0.64
Educational level 0.01 0.05 0.01 0.07 0.12 0.08
Neighborhood 2.06*** 0.38 2.75*** 0.46 3.04*** 0.53
Working status 4.78 0.51 5.01*** 0.68 5.26*** 0.75
Number of children 0.72* 0.21 0.69* 0.29
Family type 0.74*** 0.21 0.73** 0.24
Age youngest child 0.36*** 0.06 0.45*** 0.06
Number of women in household 0.03 0.34 0.11 0.40
Number of men in household 0.43 0.40 0.97 0.49
Number of hours with children 0.01 0.06 0.03 0.06
Country level
Growth National Product (GNP) 0.00 0.00
Power Distance 0.12 0.09
Masculinity 0.04 0.06
Uncertainty Avoidance 0.06 0.06
Long-Term Orientation 0.01 0.09
Indulgence 0.01 0.05
Individualism 0.24*** 0.06
Random part
ffiffiffi
ψ
p(between countries)
ffiffi
θ
p(within countries)
7.86
24.44
7.25
24.15
7.49
24.93
5.47
25.40
Derived estimates
R2
2(between countries) 15% 9% 52%
R2
1(within countries) 2% 4% 8%
ρ0.09 0.08 0.08 0.04
Note. The first model is the unconditional model with no predictor. This baseline model is useful to estimate the reduction in prediction error variance
comparing the model without covariates (unconditional model) with the model of interest (i.e., conditional models 1 to 3). Since many covariates vary
both within and between countries,the estimate of the standard deviation between countries ( ffiffiffi
ψ
p)and within counties ( ffiffi
θ
p)in a conditional model can
increase by the addition of some covariates resulting in a negative R
2
.R2
2refers to the percentage of explained variance between countries; R2
1refers to
the percentage of explained variance within countries. ρrefers to intraclass correlations
Affective Science
offspring and to optimize their childrens physical, intellectu-
al, social, and emotional development. The distinction be-
tween what children need and what might enhance their de-
velopment has disappeared, and anything less than optimal
parenting is framed as perilous (Wolf, 2011, p. XV).
Implication for Science and Practice
The current results have important implications for both science
and practice. Regarding science, these findings illustrate the
richness and importance of large-scale cross-cultural studies
whichgobeyondthelargelyWesternsamples. This is im-
portant in all domains of psychological science, and also in the
parenting domain, where 90% of the studies have been con-
ducted on US parents (Arnett, 2008; Bornstein, 2013;Mistry&
Dutta, 2015; see Keller et al., 2006; Super & Harkness, 1986 for
notable exceptions). Regarding the implications for practice,
our findings show the limits of individualism and invite reflec-
tion on solutions to counter its adverse effects on parents. The
much lower prevalence of parental burnout in collectivistic
countrieseven when socioeconomic inequalities and other
factors are controlledsuggests that strengthening the social
network of mutual aid and solidarity around families might well
help to decrease the prevalence of parental burnout in individ-
ualistic countries. This accords with recent findings obtained in
Poland (a rather individualistic country) showing that the avail-
ability of social support is a very strong protective factor vis-a-
vis parental burnout (Szczygiel et al., 2020). This is clearly not
the only potential pathway, and further studies are needed to
clarify why parents in more individualistic countries are more
exposed to parental burnout than those from less individualistic
countries. Such research will provide much-needed prevention
or treatment avenues that can be tailored to specific individual
and cultural contexts.
Limitations
In interpreting our findings, several limitations bear noting.
First, sample sizes vary across countries from 95 (Colombia)
to 1,730 (Finland). However, when prevalence rates were
reassessed on samples of approximately 200 randomly select-
ed parents in all samples with more than 299 participants, the
resulting prevalence remained essentially unchanged. Second,
mothers were overrepresented in the survey in almost all
countries. Again, when prevalence rates were reassessed
weighting for sex frequencies in each country, the resulting
prevalence remained essentially unchanged. Third, although
we adjusted for several potential confounding factors, residual
confounding by unmeasured factors cannot be ruled out.
Finally, we cannot rule out the possibility that the measure
of parental burnout used in this study captures a type of par-
enting that is more relevant to individualistic cultures than to
collectivistic cultures. However, this would not fully explain
the correlation found between parental burnout and
individualism.
These limitations do not diminish the robustness of our
main finding that individualism is associated with a much
higher risk of exhaustion in the parental role. Raising a child
in Euro-American countries, (i.e., the most individualistic
countries), represents a risk factor for parental burnout. This
42-country study provides the first window onto the role of
culture in parental burnout. It points to the importance of con-
sidering parental burnout not only at the level of the individual
but also at the level of the culture, highlighting its relevance to
world psychiatry.
Supplementary Information The online version contains supplementary
material available at https://doi.org/10.1007/s42761-020-00028-4.
AuthorsContribution Original idea of the study: I.R. Study design: I.R.,
M.M., and M.V.P. Data collection: all authors. Data management and
data analysis: I.R. and D.M.. Writing of the first draft of the paper:
M.M., I.R., and J.J.G. Comments and approval of final version: all
authors.
Data Availability The full protocol, database, and syntaxes are available
on OSF https://osf.io/94w7u/?view_only=a6cf12803887476cb5e7
f17cfb8b5ca2.
Additional Information
Conflict of Interest The authors declare no competing financial interests
or funding source that could have influenced the data collection, analysis,
or conclusions. M.M. and I.R. have now founded a training institute
(name currently masked for blind review) which delivers training on
parental burnout to professionals. The institute did not participate in the
funding of this study nor did it influence the process, the results, or their
interpretation in any manner.
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Affiliations
Isabelle Roskam
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&Joyce Aguiar
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&Ege Akgun
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&Gizem Arikan
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&Mariana Artavia
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&Hervé Avalosse
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&
Kaisa Aunola
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&Michel Bader
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&Noémie Carbonneau
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&Filipa César
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&Bin-Bin Chen
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Géraldine Dorard
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&Luciana Carla dos Santos Elias
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&Sandra Dunsmuir
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&Natalia Egorova
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&Nicolas Favez
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Anne-Marie Fontaine
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&Julia Fricke
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&Laura Gallée
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Maria Gaspar
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&James J. Gross
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&Ruby Hall
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Muhammad Aamir Hashmi
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&Ogma Hatta
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&Mai Helmy
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Emerence Kaneza
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Carolyn MacCann
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Lesley Verhofstadt
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Parenting is a precious experience and also a very hard task, which could result in parental burnout for some parents. The present study sought to validate a Japanese version of the Parental Burnout Inventory (PBI-J) by replicating and extending the pioneering work of Roskam et al. (2017). We conducted a web survey (N = 1200) to first validate the PBI-J and second to investigate the association between the PBI-J and perfectionism as a new interrelation. Similar to the prior study of Roskam et al. (2017), confirmatory factor analysis supported a model of three-factor structure of the PBI-J: emotional exhaustion, lack of personal accomplishment, and emotional distancing. In addition, we found low to moderate correlations of parental burnout with job burnout, parental stress, and depression. These findings provided initial evidence for validity of the PBI-J and suggested that parental burnout appeared to be different from job burnout. Our further evaluation of perfectionism confirmed such a difference between parental and job burnout by showing that parental perfectionism [i.e., combination of parental personal standards (PS) and parental concern over mistakes (CM)] has a unique contribution to parental burnout than does job perfectionism (i.e., combination of job PS and job CM). In addition, CM was positively correlated with burnout in both domains whereas the associations between PS and burnout were more complex. Finally, the proportion of parents experiencing burnout was estimated to lie somewhere between 4.2 and 17.3% in Japan. Overall, the present study confirmed preliminary validity of the PBI-J and found that parental perfectionism is one of the vulnerability factors in parental burnout.
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Preprint
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