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Cross-Cultural Research
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Article
Reasons of Singles for
Being Single: Evidence
from Brazil, China,
Czech Republic, Greece,
Hungary, India, Japan and
the UK
Menelaos Apostolou1, Béla Birkás2,
Caio Santos A. da Silva3, Gianluca Esposito4,5,
Rafael Ming Chi S. Hsu3, Peter Karl Jonason6,7,
Konstantinos Karamanidis1, Jiaqing O8,
Yohsuke Ohtsubo9, Ádám Putz2,
Daniel Sznycer10, Andrew G. Thomas11,
Jaroslava Varella Valentova3,
Marco Antonio Correa Varella3,
Karel Kleisner12, Jaroslav Flegr12,13,
and Yan Wang14
1University of Nicosia, Cyprus
2University of Pécs, Hungary
3University of São Paulo, Brazil
4Nanyang Technological University, Singapore
5University of Trento, Italy
6University of Padova, Italy
7Cardinal Stefan Wyszyński University in Warsaw, Warszawa, Poland
8Aberystwyth University, UK
9University of Tokyo, Japan
10University of Montreal, QC, Canada
11Swansea University, Wales, UK
12Charles University, Prague, Czechia
13National Institute of Mental Health, Klecany, Czechia
14Fudan University, Shanghai, China
Corresponding Author:
Menelaos Apostolou, Department of Social Sciences, University of Nicosia, 46 Makedonitissas
Avenue, Nicosia 1700, Cyprus.
Email: m.apostolou@gmail.com
1021816CCRXXX10.1177/10693971211021816Cross-Cultural ResearchApostolou et al.
research-article2020
2 Cross-Cultural Research 00(0)
Abstract
The current research aimed to examine the reasons people are single, that
is, not in an intimate relationship, across eight different countries—Brazil,
China, Czech Republic, Greece, Hungary, India, Japan, and the UK. We
asked a large cross-cultural sample of single participants (N = 6,822) to rate
92 different possible reasons for being single. These reasons were classified
into 12 factors, including one’s perceived inability to find the right partner,
the perception that one is not good at flirting, and the desire to focus on
one’s career. Significant sex and age effects were found for most factors.
The extracted factors were further classified into three separate domains:
Perceived poor capacity to attract mates, desiring the freedom of choice,
and currently being in between relationships. The domain structure, the
relative importance of each factor and domain, as well as sex and age effects
were relatively consistent across countries. There were also important
differences however, including the differing effect sizes of sex and age effects
between countries.
Keywords
singlehood, evolutionary mismatch, mating, cross-cultural research
Introduction
In most studied human cultures individuals typically form romantic bonds
with another person (Fletcher et al., 2015). Nevertheless, a considerable pro-
portion of people living in contemporary societies are single, that is, they do
not have an intimate partner (Cherlin, 2009; DePaulo & Morris, 2005). To
use one example, it has been found that, between one in four and one in three
Americans were not in an intimate relationship (Pew Research Center, 2013;
Rosenfeld et al., 2015). The relatively high prevalence of singlehood raises
the question about its causes, and the current paper aims to examine the rea-
sons why people are not in any form of romantic relationship, in eight differ-
ent countries. These reasons could be better understood within an evolutionary
theoretical framework that will be discussed next.
Explaining Singlehood
Previous studies have proposed four main reasons why people are single: (1)
fitness advantages (i.e., singlehood could potentially increase one’s repro-
ductive success); (2) the result of evolutionary mismatch; (3) issues due to
Apostolou et al. 3
one’s own constraints; (4) and because one is currently in between relation-
ships (Apostolou, 2015, 2017; Apostolou et al., 2019). In more detail, where
one’s fitness is concerned, it was theorized that it could potentially be benefi-
cial for young people to divert their limited resources in acquiring a good
education and a good job than in attracting and keeping a mate (Apostolou et
al., 2020). As these traits are typically highly valued in the mating market
(Buss, 2017), the proposition was such that they could serve to enhance their
attractiveness to high quality mates at a later stage of their lives. In addition,
individuals who possess traits such as good looks, which are highly valued in
a casual mate (Buss & Schmitt, 2019), can benefit by remaining single and
having casual sex with different partners instead of committing to an intimate
relationship (Perilloux et al., 2013).
Separately, the evolutionary mismatch theorization would suggest that the
psychological mechanisms involved in mating have evolved in a context
where mate choice was regulated or dictated. Anthropological, historical, and
phylogenetic evidence has indicated that, in ancestral pre-industrial societies,
the prevalent mode of long-term mating was arranged marriage (Apostolou,
2007, 2010, 2012). Parents would negotiate with other families the marriage
of their children with limited input from the latter (Coontz, 2005). In addi-
tion, several lines of evidence have likewise indicated that raids and wars
were frequent in ancestral human societies, and they would often result in the
winning males monopolizing access to women in the group that was con-
quered (Puts, 2010, 2016).
Although people generally have relatively unrestricted freedom with
regard to mate choice in contemporary postindustrial societies, the transition
from a preindustrial to a postindustrial context has taken place too rapidly
evolutionarily-speaking, for selection forces to adjust mating-related mecha-
nisms adequately to suit the demands of the free mate choice context. As a
consequence, several of these adaptations fail to produce fitness-enhancing
outcomes. This mismatch problem (Crawford, 1998; Li et al., 2017) has been
proposed to be one of the main reasons for singlehood (Apostolou, 2015,
2017; see also Goetz et al., 2019).
In addition, personal constraints such as poor physical and mental health,
could similarly prevent people from attracting a partner. The presence of such
issues might be regarded as undesirable in a prospective partner (see Buss,
2017), or they could have made it difficult to find a mate because such factors
could deprive people of the resources needed for being successful in the mat-
ing market. Nevertheless, even if people do not face any difficulties in attract-
ing and retaining mates, they may still be single due to a variety of other
reasons. Partners might have been unfaithful, or have passed on, or they
might have decided to terminate a relationship on their own accord because
4 Cross-Cultural Research 00(0)
their mate value has increased, or that their partners’ mate value has decreased
over time and it has prompted them to find a new partner of a higher mate
value (Buss et al., 2017).
Demographic differences. Humans mate predominantly within pair-bonds
where both sexes invest heavily in the relationship and offspring. As a result,
both men and women tend to be highly selective about their partners (Stew-
art-Williams & Thomas, 2013). Thus, we expect pickiness to drive single-
hood in both sexes as part of long-term mating strategy (Buss & Schmitt,
1993). However, while the typical levels of parental investment are high for
both sexes, their obligatory levels of investment are asymmetrical—men can,
and sometimes do, sire children with very little investment (Trivers, 1972).
Over time, this asymmetry has led men to evolve a propensity toward uncom-
mitted sex and sexual variety as part of their short-term mating strategy,
whereas short-term strategies for women emphasize securing investment and
good genes (Buss, 2017; Buss & Schmitt, 1993). Assuming that these reasons
are at least in part cognitively accessible, we may expect men and women
who are drawn to short-term mating to give qualitatively different reasons for
staying single—with men emphasizing that a long-term intimate relationship
causes them to forgo mating opportunities with women.
Some of the reasons for singlehood are also likely to differ with age; in
addition to the greater need of younger individuals to build up their acquisi-
tions first as indicated previously, developing good flirting skills in order to
attract a relatively high value mate also requires having a range of different
romantic experiences over an extended period of time, predicting a greater
tendency among younger individuals to remain single. Nevertheless, because
some older adults might encounter constraints such as a serious health issue
or the existence of children from previous relationships, they might also more
likely to be single.
Current Literature
The first comprehensive study on this topic with Greek-speaking participants
(Apostolou, 2017) identified 76 reasons for being single and, classified them
into 16 broad factors, including “difficulties with relationship initiation,”
“preference for the freedom to flirt around,” and “mistrust of other individu-
als.” Subsequently, these factors were classified into three broader domains
namely, “Difficulties with relationships,” “Freedom of choice,” and
“Constraints.” Consistent with our theoretical framework here, the first factor
reflected the mismatch problem, the second singlehood being beneficial for
one’s fitness, and the third issues due to one’s own constraints. Men were
Apostolou et al. 5
predictably found to desire singlehood for the freedom to flirt around, and
women were more likely to prefer singlehood if they had negative experi-
ences in a previous relationship. As expected, younger people tended to
remain single for the freedom to flirt around, while older people tended to be
single if they had a health problem and/or children from previous
relationships.
A more recent study combined the reasons identified by Apostolou (2017)
with the reasons identified by a qualitative study that analyzed Reddit
responses (Apostolou, 2019) into a comprehensive list of 92 reasons for sin-
glehood (Apostolou et al., 2020). Based on the responses of a sample of
American participants, it classified these reasons in 18 broad factors. In turn,
these factors were classified in four broader domains, namely “Low capacity
for courtship,” “Freedom,” “Constraints from previous relationships,” and
“Personal constraints.” Consistent with our theoretical framework, the first
domain reflected the mismatch problem, the second the fitness benefits of
being single, and the third and fourth factors people’s constraints. It was also
found that men were more likely than women to indicate that they were single
in order to be free to flirt around, and because they were not into family-
making. Younger were more likely than older people to indicate that they
were single because they had poor flirting skills, and because they did not
like commitment. Finally, studies conducted in the Greek and Chinese cul-
tural contexts, have found that about one in five people who were single,
were between relationships; that is, they have recently exited a relationship
and had not found yet another partner (Apostolou & Wang, 2019; Apostolou
et al., 2019).
The Present Research
Taken together, the existing literature has thus far provided broad support for
the leading theorizations of singlehood, while at the same time reinforcing
the notion that singlehood is a complex phenomenon with many facets. To
our knowledge, Apostolou et al. (2020) study, is the only one conducted to
date that was based on an attempt to understand the reasons for singlehood
among people who were actually single. The current study, aims to advance
this line of work by examining the reasons for being single in different cul-
tural contexts. Such endeavor is important in light of the possibility that cul-
tural variations across nations might exist, and hence a cross-cultural
examination of the factor structure is imperative in order to ascertain if the
findings are generalizable universally. Examining differences and similarities
between disparate cultures also allow us to understand to what extent aspects
6 Cross-Cultural Research 00(0)
of our mating psychology are static or highly canalized, and which are more
sensitive to local cues (Thomas et al., 2020).
We predict that the main reasons for being single would be largely consis-
tent across cultures. On the other hand, cultural factors are expected to affect
the reasons for singlehood in some respects. For instance, some cultures tend
to place more emphasis on getting a good education and having a good career
than others, and we would thus expect that, people would be more likely to
be single in those cultures so as to pursue education and career goals. On this
basis, we predict that differences in the reasons for being single would arise
between cultures.
Methods
Participants
Overall, 6,822 men and women from eight different countries (Brazil, China,
Czech Republic, Greece, Hungary, India, Japan, and the UK) took part in the
study. All studies were conducted online, and participants were recruited
using a variety of different survey platforms including MTurk (India), the
Cross Marketing Inc. (Japan), Prolific Inc., a University’s participants’ pool,
and by word of mouth (UK), Facebook and other social media platforms
(Brazil, China, Czech Republic, Greece, and Hungary), and through lists of
participants from previous studies who have agreed to be contacted for future
studies, and via a call for participants that was published in the university’s
journal (Brazil). Participants in the Indian and Japanese samples, and some
from the UK sample who participated via Prolific, did receive monetary
reimbursement for their participation. UK participants who were recruited
through the participants’ pool received course credits, while those that were
recruited through word of mouth did not receive any reimbursement just like
those from Brazil, China, Czech Republic, Greece, and Hungary.
All participants were at least 18 years old, and they had to be single (i.e.,
not currently in any form of romantic relationship) in order to be eligible to
participate. The entries of those participants who indicated that they were not
single, were not retained. The demographic information for each sample is
presented in Table 1.
Materials
In order to measure the reasons for singlehood, we employed the 92-item
instrument developed by Apostolou et al. (2020). For the Indian and the UK
samples, the English version of the instrument was used. For the samples in
7
Table 1. Demographic Information for the Eight Samples.
Countries
Sample size Age Sexual orientation
Total Women Men Women Men
Heterosexual
(%)
Heterosexual with
same-sex attraction (%)
Bisexual
(%)
Homosexual with
opposite-sex attractions (%)
Homosexual
(%)
Total 6,822 4,007 2,815 27.20 (9.14) 28.29 (9.82)
Brazil 2,285 1,493 792 27.19 (8.24) 25.32 (7.13) 65.5 19.8 4.2 4.4 6.1
China 1,247 753 494 21.72 (3.26) 22.03 (4.21) 86.8 — 8.0 — 5.2
Czech Republic 909 552 357 28.94 (8.84) 30.14 (8.87) 71.0 20.1 2.9 1.8 4.3
Greece 708 379 329 30.01 (9.63) 31.08 (9.77) — — — —
Hungary 393 267 126 25.72 (8.37) 25.21 (6.36) 81.2 12.7 2.8 1.8 1.5
India 465 315 150 27.13 (4.97) 28.27 (4.73) 69.2 6.2 17.8 1.9 4.7
Japan 478 225 253 42.05 (13.01) 46.26 (10.76) 88.9 5.2 3.6 2.7 3.9
UK 337 188 149 22.98 (5.87) 26.50 (7.51) 70.0 21.1 2.4 0.8 1.5
Note. The Chinese study did not distinguish between heterosexual and heterosexual with same-sex attractions, and homosexual and homosexual with opposite-sex
attraction. In addition, the Greek study did not record sexual orientation.
8 Cross-Cultural Research 00(0)
Brazil, China, Czech Republic, Greece, Hungary, and Japan, the instrument
was translated into the native language. Back translation method was used, in
the Chinese, Greek, and Japanese sample. The survey consisted of two parts.
In the first part, participants were asked to indicate to what extent each of the
92 reasons contributed to their singlehood, using a five-point Likert scale
(1—Strongly agree, 5—Strongly disagree). The order of presentation was
randomized across participants. In the second part, demographic characteris-
tics were collected.
Result
Factor Structure
Our first step was to classify the 92 reasons into broader factors. For this
purpose, we employed principal components analysis on the pooled sample
using the direct oblimin as the rotation method. The KMO statistic indicated
that our sample was very good for principal components analysis to be per-
formed (KMO = 0.98). On the basis of the Kaiser criterion (Eigenvalue > 1),
12 factors were extracted (see Table 2). In order to classify these factors into
broader domains, second-order principal components analysis was per-
formed. In particular, 12 new variables were created, which reflected the
mean of each extracted factor. Subsequently, principal components analysis
was performed on these variables, using direct oblimin as the rotation method.
Using the Kaiser criterion (Eigenvalue > 1), three domains have been
extracted (see Table 2).
Next, we examined whether the domain structure was similar across coun-
tries. For this purpose, we ran confirmatory factor analysis using the maxi-
mum likelihood method separately on each sample. In Table 3 we present
three goodness of fit estimates, namely the RMSEA, the CFI, and the SRMR.
The RMSEA indicated that the model did not make a good fit, while the CFI
and SRMR indicated that in most cases the model was a good fit. For instance,
the SRMR was above 0.9 in six cases, and very close to it in two cases.
The “Poor capacity to attract mates” was the first domain to emerge, which
included the “I am not good at flirting” factor—people indicated that they
were single because they felt they were having difficulties attracting prospec-
tive mates due to their shyness, lack of flirting skills, introversion, and their
perceived inability to detect clues of interest. The next factor to load on this
domain was the “Poor achievement record,” which highlighted people’s rea-
sons for their singlehood status in relation to their perceived lack of achieve-
ments and poor financial health. The “Poor looks” and the “Sexual and
psychological problems” were two other factors that made up this domain.
9
Table 2. Classification of the Reasons for Staying Single in Factors and Domains Using the Pooled Sample.
Domains
Factor loadings-first order Factor loadings-second order
Factors
Reasons
Poor capacity to attract mates
I am not good at flirting 0.938
I am shy 0.830
I am not good in flirting 0.766
I am very introverted 0.742
I am terrible at picking up on signals 0.726
I am socially awkward 0.647
I do not know how to start a relationship 0.625
I do not feel confident 0.561
I do not make any effort or make any moves to attract a potential partner 0.532
I get high anxiety around women/men 0.463
I am a boring individual 0.452
I am not good in relationships 0.415
I am single because I believe that nobody wants to be with me 0.381
Poor achievement record 0.820
I have not achieved much in life and I do not think I am attractive as a mate 0.497
My financial situation prevents me from having a relationship 0.455
Poor looks 0.767
Because of my weight −0.488
I am not good looking −0.401
I had many failures and I have given up trying −0.398
I do not feel ready to start a relationship 0.358
I have not accumulated enough experiences to commit to a relationship 0.313
Sexual and psychological problems 0.674
Sometimes I face sexual difficulties −0.584
(continued)
10
Domains
Factor loadings-first order Factor loadings-second order
Factors
Reasons
I have psychological problems −0.567
I am not doing very well in the sexual domain −0.537
I am going through a period of intense stress and anxiety −0.429
Personal constraints 0.339
I have children from a previous relationship 0.729
I want to devote my attention to my children 0.682
I have a disability 0.681
I need some time to decide about my sexual orientation 0.670
Because of my sexual orientation 0.669
I cannot have children 0.641
I have a serious health issue 0.579
Because of my addictions (alcohol, drugs, etc.) 0.552
My relationship may not be socially acceptable 0.549
I move often so it is not easy to keep a relationship 0.533
I believe that I am too old to start a relationship 0.459
I am grieving 0.340
Freedom
I want to be free to do whatever I want −0.929
I want to be able to be myself 0.698
I want to be able to dress the way I want without having to answer to anyone 0.651
I want to not have to answer to anyone about what I am doing 0.581
I want to be able to go wherever I want without needing to answer to anyone 0.577
I do not tolerate restrictions 0.545
I like to have my own space 0.528
I am single because I want to not get bored 0.509
(continued)
Table 2. (continued)
11
Domains
Factor loadings-first order Factor loadings-second order
Factors
Reasons
I do not want to lose my freedom 0.473
I am single because I want to have more time to spend with my friends 0.394
I want to avoid conflict 0.371
I am single because I do not want to be alienated from my friends 0.368
I want to not feel under pressure 0.348
I want to be free to flirt around −0.880
I want to be able to have many casual relationships 0.779
I want to be free to flirt with whoever I want 0.721
I want to have a freer sexual life 0.652
I want to have more choices 0.501
I want to be able to go out more often 0.491
I want to avoid the responsibilities that a relationship entails 0.436
I do not like commitment 0.436
I want to have fewer obligations 0.416
Commitment scares me 0.375
Career focus −0.879
I want to focus on my career 0.839
I worry that a relationship is going to be damaging for my career 0.693
I have different priorities 0.678
I do not have enough time to devote to a relationship 0.622
I want to be free to chase my own goals 0.516
I feel that I need some time alone 0.429
I am doing well right now 0.406
I prefer to be alone −0.854
(continued)
Table 2. (continued)
12
Domains
Factor loadings-first order Factor loadings-second order
Factors
Reasons
I do not feel the emotional need to start a relationship 0.551
I prefer to be alone 0.519
I believe that being in a relationship will not make me happier than I am right now 0.473
I got used to be alone 0.448
I do not want to have a family 0.406
I am not the family type 0.382
I am not willing to make compromises and concessions 0.276
Between relationships
I am between relationships 0.925
I recently broke up 0.754
I have not gotten over my previous relationship 0.725
Bad experiences from previous relationships 0.455
I cannot find the right one 0.617
I cannot find someone interesting 0.814
I cannot find the right one 0.793
I am very picky 0.556
I have no avenues for meeting available men/women 0.389
I am attracted to the wrong men/women 0.359
I fear I will get hurt 0.411
I am afraid that the relationship will fail 0.770
I am afraid that my partner will stop loving me 0.710
I am afraid that my partner will cheat on me 0.707
I am afraid that I will be disappointed 0.704
I am afraid that what I will give to the relationship will be wasted 0.636
Table 2. (continued)
(continued)
13
Table 2. (continued)
Domains
Factor loadings-first order Factor loadings-second order
Factors
Reasons
I am afraid that I will get hurt again 0.612
I am single because love scares me 0.540
I do not trust men/women 0.530
I am single because I fear rejection 0.478
I do not trust easily 0.473
I am single because change scares me 0.417
I want to avoid jealousy 0.373
I am single because I fear that my negative aspects will be revealed 0.361
I would not have to worry about where my partner is and what he/she is doing 0.357
14 Cross-Cultural Research 00(0)
The “Freedom” was the next domain in line, and it encompassed the “I
want to be free to do whatever I want” factor, which included reasons such as
wanting to be single so as to be themselves, to do things without having to
answer to anyone, and because of one’s intolerance of restrictions. The
domain also encompassed other factors such as “I want to be free to flirt
around” factor, the “Career focus” factor, and the “I prefer to be alone” factor.
The third domain to emerge was the “Between relationships.” Other than the
“I am between relationships” factor, the domain was composed of factors
such as the “I cannot find the right one,” and the “I fear I will get hurt.”
In order to assess their relative importance, the means and standard devia-
tions for each domain and factor were assessed. The percentage of partici-
pants who obtained a mean score that was greater than “3” (i.e., the middle
point of each Likert scale assessing one’s response to an item) was calculated
in order to evaluate the importance of each factor and domain. The results
(see Table 4) indicated that the highest mean was obtained for the “I cannot
find the right one” factor (59.2%), followed by the “I am not good at flirting”
factor (47.3%). In terms of domains, the highest means were obtained for the
“Between relationships” (33.9%) and the “Freedom” (33.8%).
Age and Sex Differences
In order to identify sex and age effects across factors, we performed a series
of MANCOVAs, where the reasons composing each factor were entered as
the dependent variables, and the participants’ sex and age were entered as the
categorical independent and continuous independent variable respectively.
The analysis was performed 12 times, once for each factor, and the results are
presented in Table 4. In order to avoid the problem of alpha inflation,
Bonferroni correction could be applied—hence, any effects stemming from
Table 3. Goodness of Fit Indexes from Confirmatory Factor Analysis.
Countries RMSA CFI SRMR
Brazil 0.097 0.904 0.0709
China 0.144 0.845 0.0825
Czech Republic 0.102 0.915 0.0722
Greece 0.084 0.933 0.0637
Hungary 0.106 0.903 0.0846
India 0.150 0.931 0.0455
Japan 0.162 0.850 0.0915
UK 0.117 0.868 0.0873
15
Table 4. Significant Sex and Age Effects for the 12 Extracted Factors.
Domains/factors
Overall Frequencies* Sex** Age*** Country Country*sex Country*age
Mean (SD) % p-value ηp
2p-value ηp
2p-value ηp
2p-value ηp
2p-value ηp
2
Between relationships 2.74 (0.72) 33.9 <.001 .015 <.001 .008 <.001 .014 <.001 .007 <.001 .007
I am between relationships 2.23 (1.08) 20.1 (w) <.001 .007 (+) <.001 .004 <.001 .009 <.001 .006 <.001 .005
I cannot find the right one 3.23 (0.84) 59.2 (w) <.001 .020 (+) .001 .003 <.001 .010 <.001 .007 <.001 .023
I fear I will get hurt 2.75 (0.91) 39.4 (w) <.001 .037 (−) <.001 .018 <.001 .009 <.001 .008 <.001 .005
Freedom 2.60 (0.86) 33.8 <.001 .026 <.001 .031 <.001 .014 <.001 .004 <.001 .006
I want to be free to do whatever I want 2.71 (1.02) 40.4 (w) <.001 .013 (−) <.001 .027 <.001 .013 .001 .003 <.001 .005
I want to be free to flirt around 2.30 (0.95) 21.7 (m) <.001 .018 (−) <.001 .012 <.001 .010 <.001 .004 <.001 .003
Career focus 2.81 (1.01) 42.0 (w) <.001 .013 (−) <.001 .015 <.001 .007 <.001 .003 <.001 .004
I prefer to be alonea2.57 (0.94) 29.5 (1) <.001 .006 (+) .001 .005 <.001 .007 .059 .001 <.001 .003
Poor capacity to attract mates 2.34 (0.74) 17.2 <.001 .036 <.001 .021 <.001 .008 <.001 .004 <.001 .011
I am not good at flirting 2.96 (0.96) 47.3 (m) <.001 .025 (−) <.001 .027 <.001 .009 <.001 .006 <.001 .004
Poor achievement record 2.43 (1.16) 24.1 (m) <.001 .025 (+) <.001 .008 <.001 .016 <.001 .003 <.001 .007
Poor looksb2.50 (0.84) 21.9 (m) <.001 .011 (−) <.001 .033 <.001 .010 <.001 .004 <.001 .006
Sexual and psychological problems 2.25 (0.97) 18.8 (m) <.001 .013 (+) <.001 .011 <.001 .008 <.001 .002 <.001 .004
Personal constraintsc1.54 (0.71) 5.2 (m) <.001 .027 (+) <.001 .058 <.001 .030 <.001 .006 <.001 .016
*The percentage of the participants who had a mean score above “3.”
**m = men higher than women, w = women higher than men.
***The sign in the parenthesis indicates the sign of the regression coefficient of age.
aMen gave significantly higher scores for the “I do not want to have a family” and the “I am not the family type” reasons, while women gave higher scores for the “I
believe that being in a relationship will not make me happier than I am right now” reason.
bWith respect to the age, the “I had many failures and I have given up trying” had a positive sign.
cThe “I need some time to decide about my sexual orientation,” the “Because of my sexual orientation,” and the “My relationship may not be socially acceptable” had a
negative sign. For Greece, the “I need some time to decide about my sexual orientation” had a negative sign.
16 Cross-Cultural Research 00(0)
the current and subsequent analyses that has a p-value larger than .004
(.05/12) would not be considered to be statistically significant. The same pro-
cedure was repeated in order to estimate sex and age effects across domains.
Significant main effects of sex and age were found for all domains. Female
participants rated the “Between relationships” domain higher than males in
general, with the largest sex difference being observed for the “I fear I will
get hurt” and the “I cannot find the right one” factors. With respect to age, the
largest effect was found for the “I fear I will get hurt” factor, with younger
individuals more likely to rate it higher than older ones. With respect to the
“Freedom” domain, the largest sex difference was observed for the “I want to
be free to flirt around” factor, with men rating it higher than women, while
the reverse was true for the “I want to be free to do whatever I want” factor.
With respect to age, the largest effect was for the “I want to be free to do
whatever I want” factor, with younger participants rating it higher than older
ones, while the reverse was true for the “Career focus” factor. Within the
“Poor capacity to attract mates” domain, men were found to consistently rate
factors such as the “Personal constraints,” the “I am not good at flirting,” and
the “Poor achievement record” more highly than women, while older partici-
pants were more likely to consider the “Personal constraints” as a more
important factor than younger ones, although the converse was found where
the “Poor looks” factor was concerned.
Country Differences
The means of factors and domains were first evaluated separately for each
country. Subsequently, we ranked factors by placing the one with the highest
mean first and the one with the lowest mean last (see Tables 5 and 6). Next,
we ran an ANCOVA where the mean scores for a given factor (i.e., the aver-
age of the reasons making up the domain) were entered as the dependent
variables, and the country and the participants’ sex were entered as the inde-
pendent categorical variables. Participants’ age was entered as the continuous
independent variable. Post hoc analysis using Bonferroni was performed in
order to find any differences between countries. The procedure was per-
formed 12 times, once for each factor. The results are presented in Table 5. A
similar procedure was followed in order to estimate differences between
countries across domains, but this time the mean scores of the factors com-
posing each domain were entered as the dependent variables. The procedure
was performed three times, once for each factor. The results are presented in
Table 6, where we can see that significant main effects of the country of ori-
gin of the sample were found for all domains.
17
Table 5. Mean Differences in Factors and Sex and Age Effects Across Countries.
Factors
Overall
Sex
p-value ηp
2
AgeWomen Men
Mean (SD) Rank Mean (SD) Mean (SD)p-value ηp
2
I cannot find the right one
Brazil 3.36 (0.86) C, H, I, J, UK 1 3.52 (0.81) 3.04 (0.86) <.001 .095 (+) <.001 .016
China 3.01 (0.77) B, Cz, I, G 3 3.11 (0.75) 2.86 (0.79) <.001 .072 (+) <.001 .021
Czech Republic 3.33 (0.82) C, H, I, J, UK 1 3.45 (0.78) 3.14 (0.85) <.001 .065 (+) <.001 .035
Greece 3.24 (0.84) C, I, J 1 3.35 (0.85) 3.12 (0.82) .001 .032 (+) <.001 .058
Hungary 3.15 (0.83) B, Cz, I, J 1 3.22 (0.81) 3.03 (0.85) .010 .038 .059 .027
India 3.48 (0.91) B, C, Cz, G, H, J, UK 5 3.59 (0.82) 3.42 (0.95) .132 .018 (−) <.001 .094
Japan 2.95 (0.74) B, C, Cz, G, H, I 2 2.99 (0.75) 2.90 (0.73) .320 .012 (+) .008 .032
UK 3.12 (0.82) B, Cz, I 1 3.24 (0.76) 2.98 (0.86) <.001 .111 .066 .031
I am not good at flirting
Brazil 3.13 (1.00) C, Cz, G, H, I 2 3.02 (0.96) 3.33 (1.04) <.001 .076 (−) <.001 .069
China 2.82 (0.76) B, Cz, I, J, UK 5 2.84 (0.76) 2.79 (0.77) <.001 .065 (+) .001 .026
Czech Republic 2.97 (0.95) C, G, H, I, J 2 2.84 (0.94) 3.18 (0.94) <.001 .051 (−) <.001 .049
Greece 2.58 (0.93) B, C, Cz, I, J, UK 4 2.45 (0.91) 2.74 (0.93) <.001 .098 (−) <.001 .055
Hungary 2.53 (1.01) B, I, J, UK 2 2.41 (0.97) 2.76 (1.04) <.001 .125 (−) .044 .054
India 3.37 (0.97) B, C, Cz, G, H, UK 8 3.39 (0.92) 3.35 (0.99) .480 .025 (−) <.001 .145
Japan 2.96 (0.89) C, Cz, G 3 2.85 (0.88) 3.02 (0.90) .002 .065 (−) .004 .061
UK 3.09 (1.01) C, G, H, I 2 2.86 (0.95) 3.38 (1.00) <.001 .131 (−) .001 .095
Career focus
Brazil 2.81 (1.07) C, Cz, G, H, I, UK 3 2.92 (1.07) 2.61 (1.07) <.001 .029 (−) <.001 .049
China 2.33 (0.70) B, Cz, G, H, I, J, UK 2 3.41 (0.68) 3.19 (0.72) <.001 .037 .715 .004
Czech Republic 2.38 (0.92) B, C, H, I, J 4 2.46 (0.92) 2.26 (0.90) .074 .014 (−) <.001 .094
Greece 2.42 (0.91) B, C, H, I, J 6 2.51 (0.90) 2.32 (0.91) .001 .039 (−) <.001 .054
(continued)
18
Factors
Overall
Sex
p-value ηp
2
AgeWomen Men
Mean (SD) Rank Mean (SD) Mean (SD)p-value ηp
2
Hungary 2.17 (0.89) B, C, Cz, G, I, J, UK 5 2.23 (0.86) 2.05 (0.92) .002 .056 (−) <.001 .079
India 3.71 (0.79) B, C, Cz, G, H, J, UK 1 3.75 (0.93) 3.69 (0.81) .062 .029 (−) <.001 .090
Japan 2.57 (0.79) C, Cz, G, H, I 7 2.59 (0.84) 2.55 (0.75) .070 .027 (+) .008 .039
UK 2.63 (0.96) B, C, H, I, J 4 <.001 .109 .393 .022
I fear I will get hurt
Brazil 2.78 (0.94) C, Cz, H, I, UK 4 2.90 (0.94) 2.54 (0.89) <.001 .141 (−) <.001 .046
China 2.96 (0.77) B, Cz, G, H, I, UK 4 3.00 (0.75) 2.89 (0.78) <.001 .082 .097 .017
Czech Republic 2.43 (0.82) 3 2.48 (0.81) 2.36 (0.82) <.001 .083 (−) <.001 .071
Greece 2.61 (0.87) 3 2.60 (0.90) 2.62 (0.83) <.001 .080 (−) <.001 .062
Hungary 2.31 (0.84) B, C, Cz, G, I, J, UK 3 2.38 (0.83) 2.17 (0.84) <.001 .175 (−) .012 .072
India 3.45 (0.92) B, C, Cz, G, H, J, UK 7 3.56 (0.85) 3.40 (0.95) .824 .020 (−) <.001 .130
Japan 2.62 (0.82) C, Cz, H, I 6 2.63 (0.85) 2.61 (0.80) .070 .047 .106 .044
UK 2.68 (0.88) C, Cz, H, I 3 2.84 (0.86) 2.47 (0.86) <.001 .190 .004 .092
I want to be free to do whatever I wanta
Brazil 2.44 (0.99) C, Cz, G, H, I, J 7 2.52 (1.00) 2.28 (0.95) <.001 .038 (1) <.001 .055
China 3.46 (0.72) B, Cz, G, H, I, J, UK 1 2.56 (0.67) 3.31 (0.75) <.001 .056 (2) .004 .023
Czech Republic 2.29 (0.89) B, C, G, H, I, J, UK 7 2.34 (0.86) 2.22 (0.91) .001 .035 (−) <.001 .093
Greece 2.68 (0.98) B, C, Cz, H, I, UK 2 2.70 (0.99) 2.66 (0.97) .007 .042 (1) <.001 .081
Hungary 2.08 (0.88) B, C, Cz, G, I, J, UK 8 2.15 (0.88) 1.91 (0.86) .076 .050 (−) .002 .076
India 3.61 (0.81) B, C, Cz, G, H, J, UK 2 3.67 (0.77) 3.58 (0.83) .990 .008 (−) <.001 .136
Japan 2.66 (0.80) B, C, Cz, H, I, J 5 2.69 (0.84) 2.62 (0.75) .005 .058 (+) .002 .063
UK 2.47 (0.90) C, Cz, G, H, I 6 2.58 (0.77) 2.33 (0.91) .053 .063 (−) <.001 .123
I prefer to be alone
Brazil 2.45 (0.91) C, G, H, I, J 6 2.49 (0.91) 2.36 (0.91) <.001 .017 (+) <.001 .023
Table 5. (continued)
(continued)
19
Table 5. (continued)
Factors
Overall
Sex
p-value ηp
2
AgeWomen Men
Mean (SD) Rank Mean (SD) Mean (SD)p-value ηp
2
China 2.74 (0.80) B, Cz, G, H, I, UK 6 2.79 (0.80) 2.65 (0.78) .013 .014 (+) .002 .018
Czech Republic 2.36 (0.93) B, C, H, I, J 5 2.39 (0.93) 2.33 (0.92) .204 .011 (+) .005 .022
Greece 2.34 (0.90) B, C, H, I, J 7 2.37 (0.88) 2.31 (0.91) .463 .010 (+) <.001 .059
Hungary 2.10 (0.91) B, C, Cz, G, I, J, UK 6 2.13 (0.93) 2.05 (0.86) .366 .020 (+) .053 .035
India 3.52 (0.97) B, C, Cz, G, H, J, UK 4 3.56 (0.80) 3.50 (0.91) .279 .019 (−) <.001 .111
Japan 2.97 (0.86) B, Cz, G, H, I, J, UK 1 2.95 (0.88) 2.99 (0.84) .142 .023 (+) <.001 .059
UK 2.42 (0.81) C, H, I, J 7 2.36 (0.70) 2.51 (0.93) <.001 .076 .476 .020
Poor looksb
Brazil 2.51 (0.83) Cz, G, H, I, J, UK 5 2.46 (0.82) 2.61 (0.85) <.001 .045 (−) <.001 .070
China 2.56 (0.70) Cz, G, H, I, J 9 2.56 (0.66) 2.55 (0.74) <.001 .047 (−) <.001 .018
Czech Republic 2.31 (0.78) B, C, G, I, J, UK 6 2.25 (0.79) 2.41 (0.75) <.001 .062 (−) <.001 .093
Greece 2.14 (0.76) B, C, Cz, I, J, UK 8 2.10 (0.74) 2.19 (0.79) <.001 .047 (−) <.001 .086
Hungary 2.23 (0.79) B, C, I, J, UK 4 2.22 (0.78) 2.25 (0.81) .037 .030 (−) .004 .044
India 3.29 (1.01) B, C, Cz, G, H, J, UK 9 3.34 (0.96) 3.26 (1.04) .830 .005 (−) <.001 .119
Japan 2.54 (0.77) B, C, Cz, G, H, I, UK 8 2.47 (0.80) 2.61 (0.74) .153 .017 (−) <.001 .066
UK 2.56 (0.76) C, Cz, G, H, I, J 5 2.58 (0.70) 2.52 (0.83) .060 .032 (−) <.001 .044
Poor achievement record
Brazil 2.39 (1.22) Cz, G, H, I, J 8 2.21 (1.15) 2.73 (1.23) <.001 .040 (−) <.001 .012
China 2.58 (0.98) Cz, G, H, I, J, UK 8 2.47 (0.95) 2.75 (0.99) <.001 .024 (+) .016 .007
Czech Republic 2.07 (1.00) B, C, H, I, J, UK 9 1.90 (0.91) 2.33 (1.08) <.001 .045 (−) .004 .012
Greece 2.07 (1.06) B, C, I, J, UK 11 1.82 (0.93) 2.36 (1.13) <.001 .062 (+) <.001 .069
Hungary 1.83 (0.97) B, C, Cz, I, J, UK 10 1.65 (0.85) 2.19 (1.11) <.001 .098 (+) .004 .028
(continued)
20
Factors
Overall
Sex
p-value ηp
2
AgeWomen Men
Mean (SD) Rank Mean (SD) Mean (SD)p-value ηp
2
India 3.53 (1.07) B, C, Cz, G, H, J, UK 3 3.52 (0.99) 3.54 (1.11) .596 .002 (−) <.001 .093
Japan 2.89 (1.09) B, C, Cz, G, H, I, UK 4 2.64 (1.07) 3.11 (1.06) <.001 .071 .177 .007
UK 2.34 (1.10) C, Cz, G, H, I, J, UK 8 2.08 (0.94) 2.67 (1.19) <.001 .086 (−) .001 .042
I want to be free to flirt around
Brazil 2.10 (0.95) C, Cz, H, I, J 11 2.08 (0.94) 2.15 (0.97) <.001 .049 (−) <.001 .042
China 2.67 (0.90) B, Cz, G, H, I, UK 7 2.64 (0.68) 2.70 (0.73) <.001 .078 .761 .005
Czech Republic 1.99 (0.83) C, G, H, I, J 11 1.95 (0.80) 2.04 (0.88) .001 .032 (−) <.001 .033
Greece 2.13 (0.91) C, Cz, H, I, J 10 2.03 (0.83) 2.25 (0.97) <.001 .107 (−) <.001 .055
Hungary 1.80 (0.84) B, C, Cz, G, H, I, J, UK 11 1.80 (0.82) 1.80 (0.88) .845 .013 (−) .047 .013
India 3.47 (0.90) B, C, Cz, G, H, J, UK 6 3.52 (0.89) 3.45 (0.91) .221 .026 (−) <.001 .102
Japan 2.44 (0.76) B, Cz, G, H, I, UK 9 2.40 (0.78) 2.47 (0.74) <.001 .074 .211 .025
UK 2.18 (0.86) C, H, I, J 11 2.28 (0.88) 2.05 (0.82) <.001 .107 (−) <.001 .92
Sexual and psychological problems
Brazil 2.29 (0.97) C, H, I, J 9 2.26 (0.97) 2.35 (0.98) <.001 .023 (−) <.001 .027
China 2.05 (0.80) B, Cz, G, I, J, UK 11 2.01 (0.78) 2.10 (0.83) .035 .008 .265 .004
Czech Republic 2.17 (0.92) C, Cz, H, I, J 8 2.13 (0.94) 2.23 (0.88) .005 .016 (−) <.001 .035
Greece 2.13 (0.85) C, H, I, J 9 2.04 (0.78) 2.24 (0.92) <.001 .056 (−) .006 .022
Hungary 1.95 (0.89) B, Cz, G, H, I, J, UK 9 1.90 (0.88) 2.04 (0.92) .038 .026 (−) .028 .028
India 3.10 (1.19) B, C, Cz, G, H, J, UK 12 3.18 (1.15) 3.06 (1.21) .673 .005 (−) <.001 .105
Japan 2.34 (0.93) B, C, Cz, G, H, I, UK 10 2.26 (0.92) 2.41 (0.93) .004 .032 (−) .018 .025
UK 2.20 (0.91) C, H, I, J 9 2.05 (0.83) 2.39 (0.97) <.001 .081 .362 .013
I am between relationships
Brazil 2.19 (1.05) Cz, G, I, J 10 2.27 (1.04) 2.02 (1.05) <.001 .026 (+) .006 .005
China 2.11 (1.00) Cz, G, I, J 10 2.00 (0.98) 2.27 (1.00) <.001 .019 (+) .002 .012
Table 5. (continued)
(continued)
21
Table 5. (continued)
Factors
Overall
Sex
p-value ηp
2
AgeWomen Men
Mean (SD) Rank Mean (SD) Mean (SD)p-value ηp
2
Czech Republic 2.04 (0.96) B, C, G, I 10 2.08 (0.96) 1.96 (0.94) .008 .013 (+) .058 .008
Greece 2.54 (1.13) B, C, Cz, H, I, J, UK 5 2.65 (1.14) 2.41 (1.11) .003 .021 (+) .005 .019
Hungary 2.08 (1.06) G, I 7 2.24 (1.08) 1.75 (0.94) <.001 .056 (−) .004 .034
India 3.17 (1.24) B, C, Cz, G, H, J, UK 10 3.22 (1.19) 3.15 (1.26) .943 .001 (−) <.001 .086
Japan 1.88 (0.78) B, C, G, I, UK 12 1.82 (0.79) 1.94 (0.77) .206 .010 .062 .015
UK 2.18 (1.11) C, G, I, J 10 2.38 (1.14) 1.93 (1.01) <.001 .065 .124 .017
Personal constraintsc
Brazil 1.27 (0.34) C, Cz, G, H, I, J 12 1.26 (0.34) 1.29 (0.36) <.001 .036 (+) <.001 .156
China 1.69 (0.65) B, Cz, G, H, I, UK 12 1.58 (0.55) 1.87 (0.74) <.001 .063 (+) <.001 .101
Czech Republic 1.39 (0.39) B, C, H, I, J 12 1.39 (0.38) 1.41 (0.40) <.001 .087 (+) <.001 .268
Greece 1.37 (0.38) B, C, H, I, J 12 1.38 (0.37) 1.37 (0.39) <.001 .062 (+) <.001 .352
Hungary 1.17 (0.25) B, C, Cz, G, I, J, UK 12 1.18 (0.26) 1.16 (0.23) .005 .071 (+) <.001 .228
India 3.12 (1.13) B, C, Cz, G, H, J, UK 11 3.24 (1.09) 3.07 (1.15) .039 .047 (−) <.001 .126
Japan 1.89 (0.69) B, Cz, G, H, I, UK 11 1.75 (0.63) 2.01 (0.73) <.001 .123 (+) <.001 .140
UK 1.34 (0.39) C, H, I, J 12 1.34 (0.39) 1.34 (0.39) <.001 .107 (+) <.001 .171
aThe trend was to have a positive sign with the exception of the “I am single because I want to have more time to spend with my friends” and the “I am single because I
do not want to be alienated from my friends” reasons.
bFor Brazil, China, Czech Republic, Greece, Hungary, and UK the “I had many failures and I have given up trying” had a positive sign.
cFor Brazil and Czech Republic the “I need some time to decide about my sexual orientation,” the “Because of my sexual orientation,” and the “My relationship may
not be socially acceptable” had a negative sign. For Greece, the “I need some time to decide about my sexual orientation” had a negative sign. For Japan, the “My
relationship may not be socially acceptable” had a negative sign. For the UK the “I need some time to decide about my sexual orientation” and the “Because of my
sexual orientation” had a negative sign.
22
Table 6. Mean Differences in Domains and Sex and Age Effects Across Countries.
Domains
Overall
Sex
p-value ηp
2
AgeWomen Men
Mean (SD) Rank Mean (SD) Mean (SD)p-value ηp
2
Between relationships
Brazil 2.77 (0.70) Cz, H, I, J 1 2.90 (0.67) 2.54 (0.68) <.001 .083 <.001 .025
China 2.69 (0.67) G, H, I, J 2 2.71 (0.65) 2.67 (0.71) <.001 .065 .001 .014
Czech Republic 2.60 (0.63) B, C, G, I 1 2.67 (0.61) 2.49 (0.64) <.001 .034 .001 .018
Greece 2.81 (0.71) C, Cz, H, I, J, UK 1 2.87 (0.73) 2.73 (0.68) <.001 .036 <.001 .049
Hungary 2.52 (0.67) B, C, G, I, UK 1 2.61 (0.66) 2.32 (0.65) <.001 .052 .624 .005
India 3.37 (0.94) B, C, Cz, G, H, J, UK 2 3.45 (0.87) 3.32 (0.97) .301 .008 <.001 .109
Japan 2.48 (0.60) B, C, G, I 3 2.48 (0.60) 2.48 (0.60) .281 .008 .066 .015
UK 2.66 (0.71) G, H, I 1 2.82 (0.70) 2.46 (0.67) <.001 .058 .012 .032
Freedom
Brazil 2.45 (0.85) C, Cz, H, I, J 2 2.50 (0.85) 2.35 (0.86) <.001 .064 <.001 .096
China 3.05 (0.60) B, Cz, G, H, I, J, UK 1 3.10 (0.58) 2.96 (0.63) <.001 .063 .576 .002
Czech Republic 2.26 (0.79) B, C, G, H, I, J 2 2.29 (0.78) 2.21 (0.81) <.001 .044 <.001 .117
Greece 2.39 (0.79) C, Cz, H, I, J 2 2.40 (0.77) 2.38 (0.81) <.001 .086 <.001 .068
Hungary 2.04 (0.78) B, C, Cz, G, H, I, J, UK 2 2.08 (0.78) 1.95 (0.79) <.001 .052 <.001 .065
India 3.58 (0.79) B, C, Cz, G, H, J, UK 1 3.63 (0.73) 3.56 (0.81) .903 .002 <.001 .092
Japan 2.66 (0.71) B, C, Cz, G, H, I, UK 1 2.66 (0.75) 2.66 (0.68) .001 .038 .002 .036
UK 2.43 (0.76) C, H, I, J 2 2.52 (0.72) 2.30 (0.79) <.001 .154 <.001 .073
Poor capacity to attract mates
Brazil 2.32 (0.66) Cz, G, H, I, J 3 2.90 (0.67) 2.54 (0.68) <.001 .049 <.001 .060
China 2.34 (0.62) G, H, I, J 3 2.71 (0.65) 2.67 (0.71) <.001 .110 .004 .014
Czech Republic 2.18 (0.65) B, G, H, I, J 3 2.67 (0.61) 2.49 (0.64) <.001 .060 <.001 .102
Greece 2.06 (0.63) B, C, Cz, G, I, J, UK 1 2.87 (0.73) 2.74 (0.68) <.001 .088 <.001 .188
Hungary 1.94 (0.62) B, C, Cz, H, I, J, UK 3 1.87 (0.59) 2.09 (0.65) <.001 .100 <.001 .103
India 3.28 (0.99) B, C, Cz, G, H, J, UK 3 2.45 (0.87) 3.32 (0.97) .264 .014 <.001 .127
Japan 2.52 (0.71) B, C, Cz, G, H, I, UK 2 2.48 (0.60) 2.48 (0.60) <.001 .086 <.001 .052
UK 2.31 (0.64) C, G, H, I, J 3 2.82 (0.70) 2.46 (0.67) <.001 .171 .006 .049
Apostolou et al. 23
From Table 6 we can see that significant interactions between country and
sex and between country and age were produced for all domains and the
majority of factors. These findings suggest that the main effects of sex and
age uncovered for each domain and factor, were different across countries.
Accordingly, we examined significant sex and age effects across domains
and factors separately for each country. Starting with factors, we ran a
MANCOVA, where the reasons composing a factor were entered as the
dependent variables, and the participants’ sex was entered as the categorical
independent variable; participants’ age was entered as the continuous inde-
pendent variable. The analysis was performed separately for each country.
The procedure was performed 12 times, once for each factor, and the results
are presented in Table 5. Similarly, in terms of domains, we ran a MANCOVA
where the factors composing a domain were entered as the dependent vari-
ables, and the participants’ sex was entered as the categorical independent
variable; participants’ age was entered as the continuous independent vari-
able. The analysis was also performed separately for each country. The pro-
cedure was performed three times, once for each domain, and the results are
presented in Table 6.
With respect to factors, there were consistencies but also variations in
terms of sex and age effects (Table 5). For example, for the “I prefer to be
alone” factor, significant positive age effects were found for almost all coun-
tries. However, age did not play a significant role for the UK sample, while
the effect was negative for the Indian sample. In the same vein, similarities
and differences were found across domains. For instance, for the “Between
relationships” domain, significant sex differences were found for most
domains. Nevertheless, the size of these differences varied across countries,
while there was no significant main effect of sex for both the Indian and the
Japanese samples.
Discussion
In the current research, we asked a large cross-cultural sample of single par-
ticipants to rate how 92 different reasons have led them not to be in a roman-
tic relationship. On the basis of their responses, we classified these reasons in
12 factors. The highest rated factor, was not be able to find the right one,
followed by not being good at flirting, and career focus. Significant sex and
age effects were found for most factors. The 12 factors were classified in
three domains. The first domain reflected poor capacity to attract mates, the
second freedom of choice, and the third being between relationships. The
domain structure, the relative importance of each factor and domain, as well
24 Cross-Cultural Research 00(0)
as sex and age effects were relative consistent across countries, but there
were also important differences.
Consistent with the predictions of our theoretical framework, one of the
broad explanations (i.e., domains) for singlehood, was one’s perceived poor
capacity to attract mates, while one of the highest rated factors (reported by
47% of the respondents) found to reduce this capacity, was the difficulties
people encountered in flirting. This domain had the lowest mean score among
the three domains, mainly due to low ratings for the personal constraints fac-
tor. This is expected, as there were likely to be relatively few people who
have constraints such as a serious health problem or a handicap that have
restricted their mating endeavors as a whole. The specific domain emerged
also in the Greek (Apostolou, 2017) and in the American (Apostolou et al.,
2020) cultural contexts, suggesting that difficulties to attract mates consti-
tutes a universal main reason for singlehood in post-industrial societies.
Similarly, in accordance with our predictions, “Freedom,” where one indi-
cated that they were single in order to be free to do whatever they wanted,
including flirting around with different partners and focusing on their careers,
was also found to be an important domain for singlehood. This domain was
rated as the second most important, with about 40% of the participants indi-
cating that they were single in order to be free to do whatever they wanted,
and about 42% of them choosing to do so in order to focus on their careers.
Studies in the Greek (Apostolou, 2017) and in the American (Apostolou et
al., 2020) cultural contexts have likewise reported comparable findings.
In line with our theoretical predictions, the “Between relationships” was
another domain that emerged in the present study. Respondents indicated that
they were single because they have recently broken up and/or they have not
gotten over their previous partner. The period of being between relationships
was also extended by participants facing difficulties in finding someone they
liked, one reason being that they were very picky. The “Between relation-
ships” domain, received the highest mean score, and its sub-factor the “I
cannot find the right one,” was reported as a reason for being single by about
59% of the participants. However, the scores in this domain may also reflect
a bias. People might have felt more comfortable saying to themselves that
they were single because they have not yet found the right one, as compared
to other factors such as perceived poor flirting skills or looks. Previous stud-
ies have identified being in between relationships as a factor, but not as a
separate domain (Apostolou et al., 2020). Thus, further research is required in
order to determine whether it actually constitutes a separate domain.
Contrary to our original prediction, a fourth domain, reflecting personal
constraints such as health issues, did not emerge. Two factors, namely
“Personal constraints” and “Sexual and psychological problems” did emerge,
Apostolou et al. 25
but they were not classified in separate domains, but under the “Poor capacity
to attract mates” domain. One possible explanation is that, these factors were
important in terms of impairing individuals’ capacity to attract mates.
Nevertheless, previous research has classified similar factors in a separate
domain (Apostolou et al., 2020), and thus, further research is necessary in
order to determine if these factors do indeed constitute facets of perceived
poor capacity to attract mates or a separate domain altogether.
Where sex differences are concerned, men were predictably found to be
more likely than women to indicate that they were single in order to be able
to flirt around, while women indicated that they were more likely than men to
be single because they were choosy and that they could not find the right one.
The largest sex difference was with regard to the factor pertaining to the
apprehension about getting hurt, where women gave higher scores than men.
In terms of domains, the largest sex difference, as predicted by the evolution-
ary mismatch problem, pertains to one’s perceived poor capacity to attract
mates, with men giving higher scores than women. Although sex differences
were found in all factors and domains, the effect sizes indicated that these
differences were generally small, indicating that men and women were single
for similar reasons.
In terms of age, younger people were predictably more likely than older
ones to report that they were single because they wanted to flirt around, to be
free to do what they have desired to do, and because they felt they lacked
good flirting skills. The largest age effect was for the “Personal constraints”
factor. This is expected, as this factor is composed of reasons such as having
offspring from former relationships and health problems, which are strongly
predicted by age. Among the largest effects was in regard to the “Poor looks”
factor, where younger participants gave higher scores than older ones. This
finding suggests that younger people possibly ascribe more importance to the
appearance of a prospective partner, and hence, younger people who felt they
were not attractive, might report it to be a more relevant reason for being
single than older ones.
Moving on, there were apparent similarities in the importance attributed to
the reasons for singlehood across different countries. Both the domain struc-
ture and the hierarchy of reasons were relatively similar across different cul-
tural samples. For instance, the “I am not good at flirting” factor, ranked near
the top of the hierarchy of reasons for most countries, while the “Personal
constraints” factor was found at the bottom of the hierarchy in most coun-
tries. There were also general consistencies in the direction and the signifi-
cance of all the sex and age effects. For instance, in relation to the “Poor
looks” factor, age was significant in all countries, while a significant sex
26 Cross-Cultural Research 00(0)
difference was found in all countries in relation to the “Poor achievement
record” factor, with men giving higher scores than women.
Nonetheless, there were also notable country differences in the level of
importance attributed to each domain and factor. For instance, participants in
Greece and Brazil, were similar with regard to the attribution of higher scores
to the “Between relationships” domain, but participants in China and Japan
were more similar to each other in assigning the highest scores to the
“Freedom” domain. In contrast to participants in other countries, participants
in Japan gave the highest score for the “Poor capacity to attract mates”
domain. There was also considerable variation in the effect sizes of the sex
and age differences. As indicated earlier, the largest sex differences were
found over the “Poor capacity to attract mates” domain, and these were
observed from participants from countries like the UK, China, and Japan, but
only relatively moderate sex differences were found for participants in Brazil
and Czech Republic. Similarly, the largest age effects were found for the
“Poor capacity to attract mates” domain, with the largest difference observed
in respondents in Greece, and the smallest in respondents in China.
The differences between different cultural groups, are most probably a
reflection of both sample and actual cultural differences. We could use China
as an example. Chinese participants were more likely to indicate the
“Freedom” domain as the most important reasons for singlehood than those
of other countries with the exception of India. One possible reason is that this
domain is perceived to be more important for younger individuals than for
older ones, and the Chinese sample is younger than those of other samples in
this current study. In addition, Chinese parents are believed to be more hands-
on where their children’s daily activities and issues are concerned, than those
of other countries, and this is arguably where many parents-children conflicts
arise (Chen-Gaddini et al., 2020). Consequently, when young adults reach an
age when they are ready to enter a university, they might try to seek more
personal space than people from other cultures.
Although the current study has sought to examine cross-cultural similari-
ties and consistencies in regard to the reasons for singlehood, it is beyond its
scope to identify the cultural factors responsible for the observed differences.
The complexity of the phenomenon, along with the many cultural differences
that are likely to exist between countries, mean that additional research dedi-
cated to this endeavor is needed.
One limitation of the current work is that it was based on self-report data,
which tended to be susceptible to several biases. For instance, in order to
protect their self-esteem, people may be unwilling to admit, even to them-
selves, that they were single because they have experienced some difficulties
with flirting, and they might be more likely to indicate that they were single
Apostolou et al. 27
because they have preferred it to be that way instead. In addition, our analysis
was based on non-probability samples, so our findings may not readily gen-
eralize to the wider population. Moreover, although we have employed a
large list of possible reasons for being single, there may well be other more
culture-specific reasons which have not been adequately captured by the cur-
rent scale. For instance, people may be taking time to select a mate so as to
make better choices, and the length of this time period can be affected by
cultural factors.
Furthermore, many different factors are likely to play a moderating role,
but in the current research we have assessed only the effects of sex and age.
For example, spending long hours at work where there may be institutional
constraints on romantic encounters may be such a factor. Similarly, parents
may impose selection limitations on mate choice, especially on daughters,
even in developed countries (Apostolou et al., 2015). Such limitations may
effectively reduce the pool of available mates, increasing the probability of
being single. Accordingly, it would be fruitful for future research to examine
how the degree of parental influence over mating affects the reasons for being
single. Such degree is also influenced by cultural factors, and considerable
cross-cultural variation is expected. For instance, in our sample, parents are
more likely to interfere and impose limitations to their children in India and
in China than in the UK and the Czech Republic.
In addition, another important factor which is likely to affect the reasons
for being single is sexual orientation. More specifically, across cultures,
same-sex attraction is generally not socially approved (Fone, 2000), so homo-
sexual people may prefer to be single rather than enter into a socially accept-
able relationship. This reason is captured by the “Personal constraints” factor,
which includes reasons such as “Because of my sexual orientation” and
because “My relationship may not be socially acceptable.” However, other
reasons may be affected by sexual orientation. For example, heterosexual
people are more likely to have children than homosexual people, so children
from previous relationships may be less likely to be a constraint for the latter
in forming an intimate relationship. Accordingly, future research needs to
specifically examine the effect of sexual orientation on the reasons for being
single.
Singlehood is a fascinating and complex phenomenon, with many facets
and contingencies. Although future research should expectedly add to this
gradually expanding body of evidence by exploring other yet-to-examined
aspects of singlehood, the current findings does provide more clarity about
a phenomenon that has enormous implications on a societal (e.g., given the
chronic issue of low birth rates in many high-income countries) and
28 Cross-Cultural Research 00(0)
economical level (e.g., the financial implications of a gradually shrinking
local population) for countries across the globe.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research,
authorship, and/or publication of this article: Dr. Peter Karl Jonason’s research was
supported by a grant from the National Science Centre of Poland (2019/34/B/
HS6/00682).
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Author Biographies
Professor Menelaos Apostolou is currently working at the University of Nicosia,
Cyprus. He was born in Athens, Greece, and he completed his post-graduate and
graduate studies in the United Kingdom. He has published several peer-reviewed
papers, books, and chapters in books in the area of evolutionary psychology.
Béla Birkás, PhD, is an associate professor in the Department of Behavioural
Sciences at the Medical School of University of Pécs, Hungary. His research interests
focus on the study of personality correlates of life history strategies and associations
between time perspectives and personality traits. He also conducted studies on mal-
adaptive personality traits and personality functioning.
Caio Santos Alves da Silva is a Psychologist, with a master’s degree in theory and
behavior research from the Federal University of Pará, Brazil. He is currently a PhD
student in Experimental Psychology at the University of São Paulo, Brazil, focusing
on the study of female sexuality and orgasm through an evolutionary perspective.
Gianluca Esposito is an Associate professor with a joint appointment at the Nanyang
Technological University (Singapore) and the University of Trento (Italy). He is a
Developmental Clinical Psychologist qualified to advance the ongoing investigations
on child socio-cognitive development contributing strengths in human electrophysiol-
ogy and neuroimaging, complex data modeling, and comparative physiological
assessment with the aim of studying Social Interaction.
Rafael Ming Chi Santos Hsu is a PhD Student in the Institute of Psychology at the
University of São Paulo, Brazil. His research interests focus on the study of
Evolutionary Psychology and Anthropology, and Human Ethology. His research
interests are mainly for (and also related topics): non-verbal behavior, psychology of
physical activities—sports, exercises, and body/movement practices (mainly in moti-
vations for practice—currently working on), neuroscience and physical activities
(mainly relations with social isolation)
Peter Karl Jonason is an Associate Professor at the University of Padua (Italy) and
the University of Cardinal Stefan Wyszynski (Poland) where he leads researchers
from around the world in understanding how the dark side of human nature might be
adaptive and decision-making in the initial stages of courtship. He specializes in the
adoption of psychometric and evolutionary approaches to his research. In 2014 he
won the igNobel award in Psychology for his work on the dark side of personality and
lives in Italy with his dog (and master) Pedro.
Konstantinos Karamanidis has recently graduated from the University of Nicosia,
and he currently aims to pursue post-graduate studies. His research interests include
individual differences, mating behavior, and cognitive processes.
Apostolou et al. 31
Jiaqing O is a Lecturer at the Department of Psychology at Aberystwyth University.
Trained in clinical psychology, he is also regarded as an evolutionary-focused
researcher who is primarily involved in research work concerning mental wellbeing
and relationship functioning, while also demonstrating a preference for cross-cultural
examination of such topics.
Yohsuke Ohtsubo is an associate professor of social psychology at the University of
Tokyo. His research interests include cooperation (via reputation and punishment),
reconciliation (via apology and forgiveness), and emotions.
Ádám Putz, PhD, is a Senior Lecturer in the Institute of Psychology at the University
of Pécs, Hungary. His research interests focus on the study of human mate choice
preferences from an evolutionary perspective; as well as on the effect of beauty-ste-
reotypes on social cognition in both economic decision making and juristic judgments
of sexual assault crimes.
Daniel Sznycer is assistant professor of psychology at the University of Montreal.
His work focuses on emotion, cooperation, and morality. He has conducted research
on shame, pride, compassion, and envy, and their roles in altruism, cooperation, social
exclusion, and conflict.
Andrew G. Thomas is a Senior Lecturer at Swansea University, UK. His research
focuses on using evolutionary perspectives to understand sex differences, mate pref-
erences, and romantic relationship wellbeing.
Jaroslava Varella Valentova obtained her PhD in Anthropology at the Charles
University in Prague, Czech Republic, and is now an assistant professor at the
Department of Experimental Psychology, University of Sao Paulo, Brazil. Her
research is focused on human sexuality, mate preferences, sexual orientation, rela-
tionship satisfaction, personality, and cross-cultural comparisons.
Marco A. C. Varella is a biologist, with MSc and PhD in Experimental Psychology;
currently as postdoctoral researcher and visiting professor at the Institute of
Psychology from University of São Paulo, Brazil. His research interests focus on
evolution of human sexuality and mating mind, evolution of human artisticality, evo-
lution of psychological roadblocks to Evolution education, and evolution of pandemic
leadership and (non)compliance with pandemic pro-health measures. In 2020 had
coauthored articles awarded with “The Margo Wilson Award” and the Ig Nobel Prize
in Economics.
Karel Kleisner is an associate professor of theoretical biology at the Charles
University (Prague, Czechia). His theoretical and empirical research focuses on a
broad span of eco-morphological phenomena from cross-cultural perception of human
faces to ecology of ultraviolet patterns on butterfly wings.
Jaroslav Flegr is an evolutionary biologist and evolutionary psychologist affiliated to
Faculty of Science Charles University and National Institute of Mental Health,
Czechia. He is a discoverer of the effects of latent toxoplasmosis and Rh factor on
human behavior, personality, and mental and physical health, as well as an author of
32 Cross-Cultural Research 00(0)
theories of frozen plasticity and frozen evolution. He has published five books and
about 170 research articles.
Yan Wang is a professor in Fudan University, China. She obtained the PhD from the
Chinese University of Hong Kong. Her current research mainly focuses on young
people’s mating behaviors and parenting in Chinese family.
