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Full Research Report
I feel loved when other
people feel loved: Cultural
congruence in beliefs
on love is related
to well-being
Saeideh Heshmati
1
and Zita Oravecz
2
Abstract
Cultural conformity in psychological constructs has been shown to play a critical role in
people’s health and well-being. The more people’s individual beliefs about a construct
aligns with the cultural norms, their cultural identity is more cultivated, leading to higher
levels of well-being. Considering feeling loved in everyday contexts as a social construct
that people indicate shared beliefs and cultural consensus for, in the current study, we
explored congruency in cultural beliefs on love and its association with well-being in the
United States. 495 participants in the United States evaluated everyday life scenarios in
terms of whether they elicit loving feelings or not. We examined the correspondence
between people’s beliefs about what makes themselves (i.e., self) feel loved compared to
what they think makes others feel loved and the cultural consensus on indicators of love.
We then explored how individual differences in these correspondence measures are
associated with people’s well-being. We reported evidence for the lack as well as for the
existence of these associations using Bayes Factors in the Bayesian statistical framework.
Results indicated that both self-other and self-consensus agreements are meaningfully
associated with individuals’ well-being. Furthermore, when examining disagreements in
self vs. other ratings of love, we found that one type of disagreement (believing other
people feel loved in scenarios that I don’t), is associated with lower levels of well-being.
This meaningful relationship to well-being was not visible in the case where a person
1
Claremont Graduate University, USA
2
Pennsylvania State University, USA
Corresponding author:
Saeideh Heshmati, Department of Psychology, Claremont Graduate University, 175 E. 12th Street, Claremont,
CA 91711, USA.
Email: saida.heshmati@cgu.edu, sa.heshmati@gmail.com
Journal of Social and
Personal Relationships
1–25
ªThe Author(s) 2021
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/02654075211036510
journals.sagepub.com/home/spr
J S P R
would report feeling loved in a scenario while believing that others would not. Impli-
cations for well-being interventions are further discussed.
Keywords
Bayes factor, Bayesian statistical framework, cultural congruence, Cultural Consensus
Theory, everyday life, love, well-being
People evaluate situations and their own identities based on the shared norms of their
culture (Lively & Heise, 2014). These intersubjective norms are usually formed by most
members of a culture agreeing on certain values or opinions (Chiu et al., 2010). The
overlap of one’s own beliefs with the shared beliefs of the culture becomes important in
forming identities. Studies have shown that the amount of overlap in individual emo-
tional patterns and shared cultural beliefs is associated with health and well-being (i.e.,
emotional fit; De Leersnyder et al., 2015). The current study builds on the con-
ceptualization of love as an emotion (Fredrickson, 2013, 2016) by studying emotional fit
in the context of beliefs about love. In particular, we examine cultural congruence in
beliefs on love, that is the overlap in people’s own beliefs on love and the shared cultural
beliefs about love. We also test whether individual differences in cultural congruence on
love are related to psychological well-being.
Building on research that explored culturally embedded indicators of felt love in daily
life (Heshmati et al., 2019, Oravecz et al., 2016), we introduce the idea of cultural
congruence (grounded in the concept of emotional fit) into the study of love. First, we
quantify the cultural congruence on love by assessing the overlap between what makes
the individual feel loved with two other indices: what makes others feel loved, and the
cultural consensus on love. Second, we test whether individual differences in the cultural
congruence in love are systematically related to psychological well-being. With these
inquiries, we hope to extend the current investigation of love from an individual or dyad-
level experience to a more culturally embedded phenomenon, and explore whether the
alignment and fit of beliefs on love with cultural norms could contribute to a happier and
more connected life. This research lays the groundwork for exploring important ques-
tions on the role of cultural assimilation and well-being in the context of daily felt love.
Cultural assimilation and emotional fit
Within a cultural context there exists a plethora of symbolic resources such as schemas,
theories, images, and icons shared among the members of a culture (Kitayama et al.,
2010). These symbolic resources provide meaningful contexts that evoke certain beliefs
and create a “theory of people.” According to Heise and MacKinnon (2010), inter-
subjective norms and cultural identities develop first through individuals’ interpersonal
activities in the micro-sociological level. Once a cultural identity is built within a
community, they then define situations and norms based on their community’s “theory of
people” in the macro-sociological level (Heise & MacKinnon, 2010). However, in any
culture there are people who do not explicitly approve of or necessarily attain the beliefs
2Journal of Social and Personal Relationships XX(X)
and values that are cultural norms, and this might be linked to lower levels of well-being
(De Leersnyder et al., 2015).
The concept of emotional fit (Anderson et al., 2003; De Leersnyder et al., 2011)
introduces a similar idea by stating that people’s emotions tend to synchronize with those
around them over time to foster social and cultural cohesion. People who live closely
together and interact on a daily basis develop shared emotional patterns and are more
emotionally synchronized. For example, in cultures centered on autonomy and indivi-
duality, people are prone to experience emotions reflective of self-worth and autonomy
(e.g., pride, anger), as opposed to emotions related to social alignment and inter-
dependence (e.g., closeness, embarrassment), showing their synchronization with the
shared views of the culture (e.g., Anderson et al., 2003). On a broader scale, when people
interact and engage in a society with a shared cultural context, they develop culture-
specific emotional patterns. This might lead to emotional experiences that align with the
cultural expectations more frequently and predominantly—due to the cultures’
encouragement of those emotions—compared to the emotions that are not consistent to
the underlying cultural practices (e.g., Kitayama et al., 2006; Markus & Kitayama, 1994;
Mesquita, 2003; Mesquita & Leu, 2007).
Because of the dynamic nature of emotions and their role in helping people cope with
the environment, the way emotions covary and assimilate in the context of social rela-
tions plays an important role in people’s mental health and well-being (Heshmati et al.,
2017; Sels et al., 2018). Considering love as an emotion (Fredrickson, 2016) and
recognizing its importance in daily well-being (Heshmati et al., 2020; Oravecz et al.,
2020) leads to questions such as whether having beliefs about love that conform to those
of the society we interact with, care for, and experience interdependencies in our goals,
behaviors and activities with, would help a person to more successfully cope with the
demands of the environment and consequently to higher well-being.
Well-being and cultural congruence
In addition to substantiating the concept of emotional fit and cultural congruence in
various societies, scientists have also investigated its association with individuals’ well-
being. With better assimilation of emotions to others in a social context and within a
culture, individuals are able to better regulate their social interactions and processes to
cope with changes in the environment. This is specifically adaptive for people because
they can coordinate their thoughts and behaviors in response to an environmental threat,
more easily facilitate discussion and interactions, and come together more closely by
having their emotional experiences validated (Anderson et al., 2003).
When researchers investigated the consequences of emotional fit within cultures, they
found that within each cultural context, subjective well-being was associated with
experiencing the emotions that aligned with cultural beliefs; that is, with “the theory of
people” (Heise & MacKinnon, 2010). For example, Kitayama and colleagues (2006)
found that in Japan, experiencing more engaging emotions (e.g., friendly feelings and
guilt) which were the dominant emotions experienced in that culture, is associated with
increased well-being. On the other hand, for American people higher levels of well-being
were linked with experiencing disengaging emotions (e.g., pride and anger), as these
Heshmati and Oravecz 3
emotions are more dominant in the American culture (Kitayama et al., 2006). In fact,
emotional fit with culture has been demonstrated to play an integral role specifically in
people’s relational well-being (De Leersnyder et al., 2014), an association that is
strengthened for situations related to social relationships rather than self-focused
circumstances.
Self-Determination Theory (SDT; Deci & Ryan, 2000) further highlights the
importance of assimilation with societal and cultural norms in terms of people’s health
and well-being. SDT posits that when people enter a new setting, certain beliefs and
values are prescribed to them by the society. Although non-intrinsically motivated, there
are processes by which people start internalizing and integrating those values and beliefs
to become self-determined and for their behavior to match the new setting’s norms and
values. According to SDT, the internalization of society’s norms and assimilation of its
values and beliefs brings more autonomy for individuals, enhances their feelings of
competence as their beliefs receive validation by the society’s norms, and increases their
sense of relatedness as they experience more belongingness in the society they live in
(Deci & Ryan, 2008). Satisfaction of these psychological needs in turn is linked with
various positive outcomes (Vansteenkiste et al., 2004). For example, improved health
and well-being outcomes such as physical exercise (Chatzisarantis et al., 1997), main-
tenance of healthy weight (Williams et al., 1996), improved intimate relationships (Blais
et al., 1990) and greater subjective well-being (Ryan et al., 1997) have been reported as
positive outcomes of autonomy resulting from assimilation to societal norms. This
improvement in well-being with higher internalization of cultural norms has also been
demonstrated across diverse cultures (see, e.g. De Leersnyder et al., 2014; Kitayama
et al., 2006).
Conceptions of love in daily life
The event of feeling love can occur for people in different situations in daily life. For
example, a child can feel loved when their mother takes time to play with them; a person
can feel loved when a neighbor brings cake to their door; a wife can feel loved when her
husband kisses her; or one could feel loved when a pet licks their face. Although this
feeling does not occur in the same context for everyone, people report a similar sensation
corresponding to a surge of love: a rush of warmth accompanied by fascination and a
desire to be close (Shaver et al., 1996). Fredrickson (2013, 2016) describes these
momentary surges of love as a micro-moment of positivity resonance that occurs in daily
experiences with those with whom we share positive emotions, have mutual care, and
experience biobehavioral synchrony in our interpersonal connections—formally dubbed
“love-the-emotion” (Fredrickson, 2013).
The notion of love has been examined through various lenses by relationship scien-
tists—both from experts’ points of view and from laypeople’s perspective (Heshmati &
Donaldson, 2020). Fehr (1988) adopted a prototype approach to conceptualize and
define love from laypeople’s perspective. Trust, caring, intimacy, and friendship—
indicators of companionate love—were identified as central to love by laypeople,
whereas features of passionate love such as sexual desire were considered non-
prototypical and peripheral. Subsequently, to understand how these 68 features of love
4Journal of Social and Personal Relationships XX(X)
align with other definitions of love, Aron and Westbay (1996) conducted a factor
analysis on all the features. The features loaded on three factors that represented passion,
intimacy, and commitment—the three components of Sternberg’s triangular love
(Sternberg, 1986)—with intimacy being rated the highest relevant feature followed by
commitment and lastly passion. As an antithetical approach to this, the essentialist
approach (Duda & Bergner, 2017; Hegi & Bergner, 2010) conceptualizes love using
what is thought to be the one essential feature that people define as love, “investment in
the wellbeing of the other.”
Apart from research on definitional features of love, Buss (1988) used a prototype
approach to understand the behavioral indicators of love. Findings revealed that people
saw behaviors representing commitment as prototypical to love, in contrast to behaviors
representing sexuality and passion, rated as the least prototypical acts of love. Another
line of research by Shaver and colleagues (1987) took the same prototypical approach to
extract laypeople’s understanding of experiences of love by asking them to describe what
experiences consist as loving. Shaver et al. (1987) concluded that experiences people
described consisted of antecedents to love, responses to love, physiological reactions to
love, and loving behaviors, to name a few. Fitness and Fletcher (1993) then implemented
a similar prototype approach along with cognitive appraisal analysis on marital rela-
tionship contexts to understand what typical experiences are linked with partner-related
love. Thinking about your partner, receiving support from them, and sharing good times
with each other were examples of triggers for feelings of love in marital relationships
which led to feelings of warmth and relaxation.
Following this line of research on understanding love, cultural consensus on daily
love experiences was also studied to examine whether individuals within a specific
culture agree on what makes people feel loved in everyday life (Ellis et al., 2020;
Heshmati et al., 2019; Oravecz et al., 2016). This approach was built on the premise that
cultures are made up of a group of people where there is substantive reason to believe
that its members share common knowledge or beliefs of interest. With topics such as
love, where there is no objective truth to be scientifically verified as a “correct” answer,
Cultural Consensus Theory (CCT; Batchelder & Romney, 1988; Batchelder et al., 2018)
is well suited for examining shared beliefs among members of culture. CCT builds on
quantifying the consensus knowledge for each individual, as well as deriving what the
cultural consensus is on a content domain. The derived cultural consensus represents the
shared agreement on what makes people feel loved while cognitive individual differ-
ences in decision making styles (i.e., knowledge on the consensus and guessing biases)
are accounted for. Using this approach, Heshmati and colleagues (2019) asked partici-
pants living in the United States to respond True/False to the question “Most people feel
loved when ...” followed by 60 daily scenarios that had the potential to make people feel
loved (Felt Love Questionnaire). These scenarios included both romantic and non-
romantic contexts. These items were generated by focus groups and were aligned with
current theories and studies on love (Feeney, 2004; Fredrickson, 2013; Gable et al.,
2004; Hendrick & Hendrick, 2006; Reis et al., 2004). A set of items with a negative
connotation (controlling/possessiveness theme) were included to balance the positive
scenarios on loving actions. Items appeared in a random order. Findings indicated that
people in the US indeed share an agreement on what makes people feel loved and what
Heshmati and Oravecz 5
does not. In particular, receiving support in needs and goals in addition to connecting
with pets and children are among the highest agreed-upon scenarios as loving; while
controlling behaviors were agreed upon as non-loving scenarios.
The current study
Following this line of research, the current study uses archival data and results from
Heshmati et al. (2019), as well as data not yet analyzed from the same study, to examine
whether cultural congruence in beliefs about everyday life experiences of love are
associated with well-being. Specific to the current study, we examined whether people’s
well-being is associated with cultural congruency of beliefs on love. We operationalized
well-being through the PERMA framework (Donaldson et al., 2020; Seligman, 2011,
2018). The PERMA model explains well-being by incorporating both hedonic and
eudaimonic aspects of well-being through five distinct elements—Positive emotions,
Engagement, Relationships, Meaning, and Accomplishment.
Cultural congruency of beliefs on love was calculated using three indices: a) one’s
beliefs about when others feel loved, b) the cultural consensus on feeling loved, and c)
one’s own perception of when they themselves feel loved (from now on referred to as
“self”). With respect to when others feel loved (a), participants evaluated whether most
people would feel loved in 60 daily love experience scenarios (see details in Heshmati
et al., 2019). These responses therefore indicated one’s beliefs about when others feel
loved. These data were also used in Heshmati et al. (2019) to calculate the shared
agreement, that is the cultural consensus on feeling loved (b) (see list of consensus
answers in Heshmati et al., 2019). Unique to the current study were responses used to
derive the self perspective (c). To indicate one’s own perception of when they feel loved,
participants responded to items that began with “I feel loved when ...” followed by 60
daily love scenarios, by indicating whether each statement was true, false, or they were
uncertain (i.e., don’t know).
Using these three indices, we quantified cultural congruency by two scores: overlap
between “self”and“others” perspectives and the overlap between “self”and
“consensus”perspectives.Wecalculatedtheamountofoverlapbycomparingeach
participant’s answers across the scenarios and summing the number of times they agreed
(“self-other” and “self-consensus”; see details in Method section).
The first aim of the current study was to examine associations between the two
congruency scores on love beliefs (“self-other” and “self-consensus”) and well-being.
We hypothesized that individuals with higher overlap in “self-other” or “self-consensus”
beliefs on love would report higher well-being as measured by the five PERMA ele-
ments. This is also in line with SDT that suggests when people identify with an activity’s
value and integrate it into their sense of self (autonomous motivation), they exhibit
greater well-being (Deci & Ryan, 2000) while also meeting their psychological need for
competence by mastering their environment and their need for relatedness by feeling
belonging and connection to the society in which they live in. With greater inter-
nalization of cultural norms, greater increase in both hedonic and eudaimonic indicators
of well-being are observed in various cultural settings (Chirkov et al., 2003).
6Journal of Social and Personal Relationships XX(X)
The second aim of this study was to explore the nature of self-other disagreements by
breaking them down into two meaningful subparts in terms of individual differences in
(1) the number of scenarios in which one would perceive love, while believing that
others would not (“True for self, False for others”) and (2) the number of scenarios in
which one would not perceive love, while believing that others would (“False for self,
True for others”). By looking at self-other disagreements broken down this way, we aim
to learn about how prone people are to (a) perceiving others capable of feeling loved in
scenarios when they do not (“False for self, True for others”) and (b) perceiving others as
not capable of feeling loved in scenarios where they do (“True for self, False for others”).
Learning the direction in which these discrepancies manifest and whether they relate to
well-being can provide foundations for the development of well-being interventions.
Method
Participants
General study settings are identical to the one described in Heshmati et al. (2019).
Selected details are provided here for convenience. A sample of 500 adults (Mage ¼51
years, SD ¼15.70, range ¼18–93), of which 250 were men, all residing in the United
States, were recruited with approval from the Institutional Review Board at the Penn-
sylvania State University (protocol # STUDY00000987). From the initial 500 partici-
pants, five participants were eliminated from the analysis due to responding “Don’t
Know” to all of the questions of the survey, resulting in a final sample size of N ¼495.
Out of the remaining 495 participants, 80%(n ¼397) of the participants described
themselves as White; 10%(n ¼49) of the participants described themselves as Black;
and 10%(n ¼49) as other races. Fifty-six percent (n ¼275) of the participants reported
being married, cohabiting, or being in stable relationships; 22%(n ¼108) reported being
single or single but dating; 22%(n ¼109) reported being divorced, widowed, or
separated; and the three remaining participants preferred not to answer.
Procedures
Data analyzed in this study (described in detail below) consisted of responses to 60 one-
sentence scenarios framed in the other perspective (archival data used also in Heshmati
et al., 2019), the cultural consensus results from Heshmati et al. (2019), responses to the
60 love scenarios from the self-perspective, and responses to items measuring different
elements of well-being based on the PERMA model. The participants took approxi-
mately 20 minutes to complete the full survey.
Measures
Felt love questionnaire. The Felt Love Questionnaire (Heshmati et al., 2019) consists of 60
one-sentence everyday life scenarios with topics centered around potential loving sig-
nals. It comprises seven categories: (1) trust and acceptance (e.g., “when somebody
confides with them”); (2) support in needs and goals (e.g., “someone celebrates their
accomplishments”); (3) symbolic/physical expressions, e.g. (“they get gifts”); (4)
Heshmati and Oravecz 7
sharing time with others (e.g., “they spend time with their friends”); (5) other possible
sources of love (e.g., religion, pets, nature, patriotism, gratitude, politeness, etc.); (6)
controlling behavior from others (e.g., “someone wants to know where they are at all
times”); and (7) neutral/control items for testing differentiation (e.g., “they eat their
favorite food”).
The current study consisted of answers to each of the 60 everyday life scenarios based
on the participants’ beliefs about the self. Each item began with the prompt “I feel loved
when ...” followed by a daily scenario, for example: “I feel loved when someone
celebrates my accomplishments.” To minimize participant burden, participants were
asked to make a decision about these scenarios by selecting True, False, or Don’t Know.
To avoid hesitation, instructions also noted that because these questions are based on
opinions, there are no right or wrong answers.
We also used archival data from Heshmati et al. (2019) with the same participants’
responses to these items from the “others” perspective where each item began with the
prompt “Most people feel loved when ...” followed by a daily scenario. Moreover, we
used the cultural consensus estimates for these 60 items, derived in the Heshmati et al.
(2019). The cultural consensus estimates were derived using a cognitive psychometric
model based in the Cultural Consensus Theory framework—we refer to this model-
inferred other perspective as the “consensus.” Practically speaking, these estimates
were based on weighting people’s ratings of “what makes others feel loved” by their
cultural competence and cognitive bias tendencies. Because the consensus answers are
based on the responses of all people and psychometric modeling, they provide a model-
based understanding on how the individual and the cultural beliefs overlap. Data from
the current study as well as the archival data and the consensus labels are summarized in
Table 1.
Agreement and disagreement scores. To quantify the amount of overlap between beliefs
related to “self” and “other,” and beliefs related to “self” and “cultural consensus,” we
derived four types of scores. First, we quantified the number of times people matched
between beliefs for self and cultural consensus, labeled (1) “self-consensus agreement”
for simplicity. Since this indicator involved CCT modeling for deriving the cultural
consensus, it can be seen as a model-based indicator of congruency. Second, we cal-
culated the number of times people matched in their responses to felt love items when the
questions were asked about their self-perspective compared to when they were asked
about the others’ perspective, and derived a score for each person. We labeled this
comparison (2) “self-other agreement” for simplicity. Since calculating this indicator
used raw response data, we can see it as a more data-driven quantification of congruency.
Additionally, we explored the disagreements on self vs. other ratings by focusing on
the patterns of disagreement in participants’ selection of True or False responses for
themselves, compared to others. Specifically, we made disagreement scores based on
how many times a respondent selected False responses for self but True for others which
we labeled (3) “False for self, True for others disagreement.” We then did the same for
when the participants selected True responses for self but False responses for others for
each scenario and labeled it (4) “True for self, False for others disagreement.”
8Journal of Social and Personal Relationships XX(X)
Table 1. Summary of all felt love scenarios and corresponding estimates from the current study
and archival data.
Current Study Archival Data
I feel loved
when ...
Most people feel
loved when ...
Category
Item
# Everyday Scenario
%
True
(Self)
%
False
(Self)
%True
(Other)
%False
(Other)
Consensus
label
B22 Someone cares for them when
they are sick.
0.91 0.05 0.92 0.05 True
B41 Someone shows compassion
toward them in difficult
times.
0.91 0.07 0.96 0.02 True
B1Someonesupportsthem
without expecting anything
in return.
0.89 0.08 0.91 0.07 True
C38 Someone tells them: “I love
you.”
0.89 0.06 0.92 0.05 True
A29 They are made to feel special. 0.88 0.08 0.93 0.05 True
C34 A child snuggles up to them. 0.88 0.07 0.95 0.03 True
D43 They spend quality time with
someone.
0.88 0.08 0.93 0.03 True
D30 They spend time with their
family (e.g., holidays,
vacation).
0.86 0.10 0.88 0.06 True
B39 Someone calls just to check in
on them.
0.86 0.10 0.88 0.09 True
B10 Someone is there just to listen. 0.85 0.10 0.85 0.10 True
B32 Someone does something nice
for them unexpectedly.
0.85 0.12 0.85 0.11 True
C4Theyarehugged. 0.840.11 0.84 0.11 True
E11 They feel appreciated. 0.84 0.13 0.89 0.08 True
B33 Someone is supportive of their
life goals.
0.82 0.13 0.87 0.10 True
C50 They are holding hands. 0.82 0.11 0.80 0.11 True
B2Theyfeelaccepted. 0.810.14 0.85 0.12 True
A44 They feel completely
comfortable around
someone.
0.81 0.15 0.91 0.06 True
C53 When someone sends them
signs of affection (e.g., slight
smile, loving glance).
0.81 0.13 0.87 0.08 True
A23 Someone forgives them for
something they did wrong.
0.80 0.13 0.80 0.13 True
C59 Someone kisses them. 0.80 0.11 0.81 0.11 True
B51 They experience an act of
kindness.
0.79 0.16 0.82 0.14 True
(continued)
Heshmati and Oravecz 9
Table 1. (continued)
Current Study Archival Data
I feel loved
when ...
Most people feel
loved when ...
Category
Item
# Everyday Scenario
%
True
(Self)
%
False
(Self)
%True
(Other)
%False
(Other)
Consensus
label
A13 Someone understands them. 0.78 0.16 0.82 0.12 True
A60 They feel someone has no
expectations and they can
be themselves.
0.78 0.16 0.77 0.15 True
C15 They receive gifts (card,
flowers etc.).
0.77 0.17 0.82 0.12 True
B17 Someone helps them out. 0.76 0.17 0.75 0.19 True
C21 They make love. 0.76 0.13 0.82 0.11 True
B42 Someone celebrates their
accomplishments.
0.75 0.19 0.86 0.10 True
E24 Their pets are happy to see
them.
0.73 0.03 0.93 0.04 True
A49 They can share their opinions
without being judged.
0.73 0.21 0.83 0.09 True
E58 They are recipients of
gratitude.
0.72 0.22 0.72 0.20 True
E6TheyfeelconnectedtoGod. 0.710.20 0.78 0.11 True
B56 Something nice happens to
them unexpectedly.
0.71 0.23 0.66 0.25 True
B18 Someone follows up to ask
how a problem turned out.
0.69 0.22 0.68 0.24 True
D52 They have fun with their
friends.
0.69 0.24 0.68 0.24 True
D16 They spend time with their
child(ren).
0.66 0.03 0.90 0.04 True
D35 They are included in activities. 0.66 0.25 0.69 0.23 True
A5Somebodyconfidesinthem. 0.640.26 0.59 0.29 True
B3Theymakeupafterafight. 0.630.23 0.70 0.18 True
C36 They receive a compliment. 0.62 0.31 0.64 0.28 True
D40 They are around people,
having fun.
0.62 0.30 0.63 0.27 True
B55 A group recognizes their
contribution.
0.55 0.36 0.56 0.32 True
E54 they feel close to nature. 0.54 0.38 0.50 0.34 True
D12 They feel part of a team. 0.53 0.36 0.59 0.27 True
C14 someone is sexually attracted
to them.
0.51 0.34 0.54 0.33 True
A31 Someone can immediately tell
what is on their mind.
0.51 0.36 0.56 0.29 True
(continued)
10 Journal of Social and Personal Relationships XX(X)
Well-Being items. To capture well-being, we used scales aiming to capture the five ele-
ments defined in the PERMA framework (Seligman, 2011). The items corresponded to
the five PERMA dimensions: Positive emotions, Engagement, Relationship, Meaning,
and Accomplishment. Positive emotions capture feelings of happiness like joy and
Table 1. (continued)
Current Study Archival Data
I feel loved
when ...
Most people feel
loved when ...
Category
Item
# Everyday Scenario
%
True
(Self)
%
False
(Self)
%True
(Other)
%False
(Other)
Consensus
label
C48 Someone is polite to them. 0.47 0.42 0.56 0.33 True
G8Thesunisshining. 0.450.44 0.38 0.46 True
E25 They attend a religious
ceremony.
0.45 0.40 0.46 0.35 True
F37 Someone insists to spend all of
their time with them.
0.41 0.47 0.45 0.46 False
E45 They hear or sing their
country’s national anthem.
0.41 0.44 0.45 0.35 True
G46 They eat their favorite food. 0.40 0.51 0.45 0.40 True
C20 They get a compliment from a
stranger.
0.38 0.51 0.36 0.48 True
B19 Someone gives them positive
feedback on the internet
(e.g., a Facebook like, a
retweet, etc.).
0.37 0.52 0.41 0.42 True
G27 They solve a difficult problem. 0.35 0.53 0.33 0.52 False
F57 Someone tries to change their
behavior to be healthier.
0.34 0.51 0.40 0.43 False
F28 Someone else wants to know
where they are at all times.
0.27 0.62 0.26 0.63 False
F9Someonetellsthemwhatis
best for them.
0.26 0.61 0.28 0.61 False
F47 Someone is possessive about
them.
0.24 0.67 0.31 0.59 False
D26 They attend sporting events of
their favorite team.
0.17 0.69 0.22 0.61 False
E7Theyplaysports. 0.130.74 0.17 0.67 False
Note. This table summarizes data from the current study (columns 4–5) and archival data (columns 6–8) used in
Heshmati et al. (2019). The archival data from Heshmati et al. (2019) used the prompt “Most people feel loved
when ...” in the 60-item Felt Love Questionnaire where people’s responses were based what would make
others feel loved. The new data used in the current study began the Felt Love Questionnaire with the prompt “I
feel loved when ...”tocapturewhatpeoplebelievemakesthemselves feel loved. Categories to which scenar-
ios belong to include: A) Trust and acceptance, B) Support in needs and goals, C) Symbolic/physical expres-
sions, D) Sharing time with others, E) Other possible sources of love, F) Controlling behavior from others, and
G) Control scenarios with a neutral connotation in terms of loving signals.
Heshmati and Oravecz 11
contentment. Engagement represents being in a state of flow or immersion into a task or
activity. Meaning captures having a greater purpose in life and feeling that one’s life is
valuable. Relationships refers to positive social connections that make a person feel
supported and cared for. Accomplishment includes having a sense of achievement by
having goals and ambition in life. This theory posits that these five elements have
true value in and of themselves, (e.g., people pursue them each for their own sake),
that each element can be measured independently, and that all of the elements
contribute to individuals’ overall well-being. In order to measure each of the PERMA
elements, we used items from scales that were already established in each of these
domains. For example, in order to measure the element of Positive emotions we used
the Scale of Positive and Negative Experiences (Diener et al., 2009), for Engagement
we used the Flow Short Scale (Rheinberg et al., 2003), for Relationships we used the
Positive Relationships Scale from PERMA profiler (Butler & Kern, 2016), for
Meaning we used the Meaning in Life Questionnaire (Steger et al., 2006), and for
Accomplishment we used items adapted from the Psychological Well-Being Scales
(Ryff & Keyes, 1995), NEF’s National Accounts of Well-Being (Michaelson et al.,
2009), and Missing Dimensions of Poverty (Samman, 2007). The supplemental
material summarizes all items and their corresponding scales. The internal con-
sistency, quantified with Cronbach’s a, was high for all the subscales (Positive
emotions: a¼.93, Engagement: a¼.92, Relationship: a¼.85, Meaning: a¼.84,
Accomplishment:a¼.86).
Data analysis
Hypothesis testing via Bayes factor. We explored how the quantitative summaries of the
self-other and self-consensus agreements correlate and quantified the evidence in favor
or against these correlations in terms of Bayes Factors (BF; Ly et al., 2015). The Bayes
Factor is a tool for hypothesis testing in the Bayesian statistical framework. Bayes Factor
quantifies evidence in favor or against a null or an alternative hypothesis, based on the
data and a prior setting needed for specifying the alternative hypothesis. More specifi-
cally, the null hypothesis in our analysis is no correlation and the alternative hypothesis
is that correlation exists (no directionality assumption). In the classical null hypothesis
significance testing framework, we could only reject or fail to reject the null hypothesis
of “no correlation.” Bayes Factor provides the ability to interpret the weight of evidence
in the data in favor or against a correlation or no correlation.
The Bayes Factor is measured on a continuous scale, expressing the ratio of evidence
between null and alternative hypothesis (or vice versa, by taking the reciprocal). To
summarize BF in terms of discrete categories for interpretation of evidence strength, a
classification scheme was proposed by Jeffreys (1961; shown in Table 2). According to
this classification, a Bayes Factor—either articulated in terms of in favor of the null (lack
of correlation in our case), that is BF
01
, or in favor of the alternative hypothesis (exis-
tence of correlation), that is BF
101
—below 3 shows anecdotal or no evidence for one
hypothesis over the other; BF between 3 and 10 shows moderate evidence; BF greater
than 10 shows strong evidence; BF greater than 30 shows very strong evidence; BF
greater than 100 shows extreme evidence. Bayes Factors in the current analysis were
12 Journal of Social and Personal Relationships XX(X)
calculated in JASP
2
(version 0.7.5; JASP Team, 2016), which is a free and open-source
statistical software package. The JASP output file, containing the analyzed data and
results with the settings of the analysis, as well as the raw data with the data processing
scripts are available as an online supplement on the project’s Open Science Framework
page.
3
Results
Everyday life scenarios of love
First, we identified the everyday life scenarios in which more people showed agreements
in their responses between the self perspective and the other perspective. This com-
parison highlighted that most people’s self-other agreements occurred in scenarios for
which the American cultural consensus on those scenarios was “loving.” For example,
most people believed that both the self and other people would feel loved when
“someone cares for them when they are sick” (91%) or “someone supports them without
expecting anything in return” (90%) or “a child snuggles up to them” (89%). Most of
these scenarios with high overlaps were either centered on the “support in needs and
goals” theme or were “symbolic/physical gestures.”
We also identified the scenarios for which most people showed disagreements in their
beliefs on love for self and other; these items were mostly the items that the cultural
consensus indicated was “non-loving.” The average number of people showing dis-
agreements across the scenarios was 73.59 or 6.73%(SD ¼28.56). Items with the
highest number of disagreements included: “they attend sporting events of their favorite
team” (21%), “they attend a religious ceremony” (21%), or “someone tries to change
their behavior to be healthier” (24%), which people felt were loving indicators for the
self but not for others (“True for self, False for others” disagreement). On the other hand,
more people judged that others might feel loved by scenarios such as “when someone is
possessive about them” (28%), or “someone insists on spending all of their time with
them” (23%), but they themselves wouldn’t (“False for self, True for others” disagree-
ment). These results imply that people’s beliefs about themselves are more aligned with
Table 2. Evidential strength categories for Bayes factor.
Bayes Factor BF
10
Interpretation
>100 Extreme evidence for H
10
30–100 Very Strong evidence for H
10
10–30 Strong evidence for H
10
3–10 Moderate evidence for H
10
1–3 Anecdotal evidence for H
10
1No evidence
1/3–1 Anecdotal evidence for H
01
1/10–1/3 Moderate evidence for H
01
1/30–1/10 Strong evidence for H
01
1/100–1/30 Very Strong evidence for H
01
<1/100 Extreme evidence for H
01
Heshmati and Oravecz 13
their beliefs about others on indicators of love as opposed to non-loving indicators. More
importantly, the scenarios with the most agreements fall within the “support in needs and
goals” category. On the other hand, the scenarios with the most disagreement fall either
within the “controlling behavior” category or the neutral items.
Agreements on indicators of love and well-being
Table 3 displays selected Bayesian Pearson correlation coefficients calculated in JASP
among the agreement and disagreement scores described above and the five well-being
measures. We selected the correlation coefficient for which there was evidence in favor
or against correlation (full report of the analysis is provided online as a JASP file on
the project’s OSF page [https://osf.io/g6mqe/?view_only¼b54bd0e176844f8ca776963
4c22b0159.]).
Self-consensus agreement. We explored the degree to which participants’ responses to felt
love items from the self-perspective matched with the general consensus on indicators of
felt love (self-consensus agreement) and its association with indicators of well-being.
Results are shown in the first column of Table 3. Our findings indicated that people were
more likely to have matching beliefs between what makes them feel loved (self) and the
cultural consensus on indicators of felt love (consensus) if they scored high on the
following indicators of well-being: Positive emotions (r¼0.27, BF
10
>100),Engage-
ment (r¼0.17, BF
10
¼49.62), Positive Relationship (r¼0.36, BF
10
> 100), Meaning
(r¼0.31, BF
10
>100),andAccomplishment(r¼0.26, BF
10
> 100).
Self-other agreement. Results showed that there is a correlation between “self-other
agreement” and positive emotions (r¼0.23), with a corresponding BF
10
> 100, indi-
cating extremely strong evidence for this correlation’s existence. This means that there
was substantial support in our data for the claim that people who experience higher rates
Table 3. Pearson correlation coefficients of well-being with agreement and disagreement scores.
Self-
consensus
agreement
Self-other
agreement
True for self, False for
others disagreement
False for self, True
for others disagree-
ment
Positive Emotion 0.272**** 0.225**** "0.119 "0.151**
Engagement 0.165*** 0.096 0.002
~~
"0.118
Positive
Relationship
0.360**** 0.325**** "0.125 "0.319****
Meaning 0.308**** 0.285**** "0.128* "0.216****
Accomplishment 0.260**** 0.246**** "0.119 "0.190****
Note: The asterisk(s) next to the coefficients indicate the degree of strength of evidence in favor of the
existence of a correlation based on the Bayes Factor (BF): *BF
10
:3–10(moderate),**BF
10
:10–30(strong),
***BF
10
:30–100(verystrong),****BF
10
>100(extreme).Thetriangle(s)nexttothecoefficientsindicatethe
degree of strength of evidence in favor of the null hypothesis (non-existence of a correlation) based on the
Bayes Factor (BF):
~
BF
01
: 3–10 (moderate),
~~
BF
01
: 10–30 (strong).
14 Journal of Social and Personal Relationships XX(X)
of positive emotions have more overlap between their self and other beliefs on indicators
of love. As seen in Table 3, there was also positive correlation with substantial evidence
between self-other agreement and Positive Relationship (r¼0.33, BF
10
> 100), Meaning
in life (r¼0.29, BF
10
> 100), and Accomplishment (r¼0.25, BF
10
> 100). Overall, the
results showed that four PERMA well-being measures—having positive relationships, a
meaningful life, feeling accomplished, and experiencing positive emotions—were
positively related to correspondence between people’s beliefs about indicators of love
that make the self feel loved and indicators that make others feel loved. Engagement was
the only well-being component that was not meaningfully associated with overlaps in
beliefs on love for others compared to the self.
Disagreements on indicators of love and well-being. We broke down the self-other dis-
agreement variable into two meaningful subparts. First, we wanted to see if there were
meaningful individual differences associated with the number of settings in which a
person would perceive love, while believing that others would not (“True for self, False
for others” disagreement). Generally speaking, we did not find strong evidence sup-
porting correlations between the “True for self, False for other” variable and well-being
measures (Table 3, column 3), except some moderate evidence for Meaning: lower
levels of disagreement was associated with higher Meaning (r¼"0.13, BF
10
: 3–10).
However, there was strong evidence supporting the null hypothesis of no correlation
between the “True for self, False for others” variable and Engagement (r¼0.002,
BF
01
¼17.73).
Second, we wanted to assess whether people who systematically differed in terms of
everyday life settings in which they themselves would not perceive love, while believing
that others would (“False for self, True for others” disagreement; higher values mean
more discrepancy) would show differences in well-being. Generally speaking, the data
showed evidence for associations between the “False for self, True for others” measure
and the well-being variables (Table 3, column 4). More specifically, the results indicated
that people with low levels of discrepancy tended to report having a more meaningful life
(r¼"0.22, BF
10
> 100), felt more accomplished (r¼"0.19, BF
10
>100),hadhigher
positive relationships (r¼"0.32, BF
10
> 100), and positive emotions (r¼"0.15,
BF
10
¼16.32) scores, with strong evidence for the latest and extreme evidence for the
rest of the associations. These findings suggest that people who are less prone to perceive
others capable of feeling loved in scenarios in which they themselves would not, report
higher levels of well-being.
We also investigated the predictive power of the four congruency indicators for well-
being by using Bayesian regression analysis. For every well-being measure, we used
different combinations of the four congruency indicators and compared their out-of-
sample prediction power
4
via comparing their corresponding Bayes Factors. Results
indicated that from our current set of congruency indicators (1) Positive Emotions are
most optimally predicted by self-consensus agreement (R
2
¼0.07, BF ¼30);
(2) Engagement is most optimally predicted by self-consensus agreement (R
2
¼0.03, BF
¼23); (3) Positive Relationships are most optimally predicted by a combination of self-
consensus agreement and “false for self, true for other” disagreement scores (R
2
¼0.15,
BF ¼12); (4) Meaning of life is most optimally predicted from self-other and
Heshmati and Oravecz 15
self-consensus agreements (R
2
¼0.11, BF ¼20); and (5) Accomplishment is most
optimally predicted from self-other agreement and self-consensus agreements(R
2
¼0.08,
BF ¼14). Detailed result tables and a corresponding JASP file with analyses (also con-
taining the data) are available as Online Supplement.
We further explored how well our congruency indicators perform in terms of pre-
dicting Positive Relationships. We included a predictor on relationship status (being in a
relationship or not), and its interactions with the four congruency measures. The rela-
tionship variable was a binary variable distinguishing people who reported as being
single (coded as 0) and others who were grouped as being in a relationship (coded as1).
Specific relationship categories that were coded as “in a relationship” were: “Married,”
“Cohabiting,” and “In stable relationship (but not married/cohabiting).” Categories that
were coded as “single” were: “Single,” “Widowed,” “Divorced,” “Separated,” and
“Single but dating.” We found that the most optimal model (in terms of out-of-sample
predictive power) now included not only the predictors of “self-consensus agreement”
and “False for self, True for others disagreement” scores as in the analysis described
above, but also interaction effects with relationship status on self-other agreement and
“False for self, True for others” disagreement scores (with being in a relationship pre-
dicting higher Relationship scores) and the predictive power increased (R
2
¼0.25, BF ¼
170). This suggests that relationship status is a reliable moderator of congruency.
Discussion
Scientific studies of love have spanned a wide variety of approaches in both the rela-
tionship sciences (e.g., prototype, essentialist, taxonomy approaches) and emotion sci-
ence (affective perspective). More recently, through a cultural consensus theory
approach, Heshmati and colleagues (2019) examined the cultural consensus on indica-
tors of love in daily life, showing evidence that people in the U.S. shared an agreement
on what makes most people feel loved and what daily scenarios are non-loving. Yet,
there has been a gap in our knowledge on whether overlaps in people’s individual beliefs
about love and the cultural consensus around love is associated with their psychological
well-being. Therefore, the current study introduced cultural congruence to capture this
overlap into the study of love for the purpose of understanding love as a culturally
embedded phenomenon.
To this end, in the current study, we first examined the level of congruence in
intersubjective cultural norms of love with beliefs about love for the self. We then
explored how this cultural congruence on beliefs on love related to people’s well-being.
How much people internalize the cultural ideas about love was quantified by two
measures: the overlap between (1) what makes people feel loved and what they think
makes others feel loved (self-other agreement) and (2) what makes people feel loved and
the cultural consensus (self-consensus agreement). We performed correlation analysis in
the Bayesian framework to gain information on how much evidence there is in favor or
against the relationship between cultural congruence on love and well-being in terms of
correlations and corresponding Bayes Factors.
In examining the congruence on people’s beliefs about love for others compared to
their beliefs for themselves, we found that indicators of love that showed the most
16 Journal of Social and Personal Relationships XX(X)
overlap were centered on themes such as “support in needs and goals” and aspects of
“symbolic/physical gestures.” Support and care for others—as one of the indicators of
compassionate love as opposed to romantic and passionate love (Berscheid, 2010)—
along with indicators of companionate love were indicated as central features of love by
laypeople in Fehr and colleagues’ prototype studies (Fehr, 1988; Fehr & Russell, 1984,
1991). Showing support and care for others is also in line with the “essential” feature of
love, investment in the well-being of the other, as part of the essentialist approach to the
meaning of love (Duda & Bergner, 2017; Hegi & Bergner, 2010). Moreover, the sce-
narios centered on “symbolic/physical gestures” fit with loving behaviors identified as
experiences of love by laypeople extracted through the prototypical approach by Shaver
and colleagues (Shaver et al., 1987). To summarize, our finding suggests that the
components of love that have previously been shown to be essential and central features
of love are the aspects of love that people display cultural congruency, conveying that
people tend to be more in agreement with the cultural norms around these central fea-
tures. Moreover, it is the less central aspects of love on which people displayed dis-
agreements in their beliefs for themselves and others in the current study.
Next, we examined the association between cultural congruence on love and
people’s well-being, using the PERMA model of well-being (Seligman, 2011). PERMA
identifies five components—Positive emotions, Engagement, Relationships, Meaning,
and Accomplishment—that are theorized as the building blocks of well-being. As
hypothesized, we found that all five well-being components were related to people’s
“self-consensus” agreement on indicators of love. In other words, having positive
relationships, experiencing positive emotions, having a meaningful life, feeling
accomplished in life, and experiencing engagement (often referred to as flow) in daily
activities is related to how much people’s perception of loving signals for themselves
match culturally shared beliefs. This finding supports the concept of emotional fit
between self and cultural surrounding and its correlation with well-being (De Leersnyder
et al., 2014). The reasoning behind this may be because people with higher subjective
well-being are those who conform to the cultural expectations of the society and show
high internalization of cultural norms (Chirkov et al., 2003; Deci & Ryan, 2000) and
hence, they feel loved by the same indicators that the cultural belief about indicators of
felt love are; that is to say that they are one with their cultural society. Furthermore, one’s
identification with an embedded social value and integrating it into their sense of self—
in this case displaying overlapping beliefs on love with the cultural beliefs—might lead
to satisfaction of basic psychological needs of competence, autonomy, and relatedness
which generate greater well-being (SDT; Deci & Ryan, 2000).
Similarly, “self-other” agreements on felt love and well-being components were
meaningfully associated. The only PERMA component that was not meaningfully
associated with self-other agreements was Engagement, which might stem from a lim-
itation of the measure—Engagement items were not general but referred to the current
day. It would be interesting for future research to use another method of measuring
engagement to explore this relationship further.
Next, we examined self-other disagreements on indicators of love and how they
related to well-being components. Namely, we looked at the patterns of disagreement in
participants’ selection of True or False responses for themselves, compared to other.
Heshmati and Oravecz 17
First, we found that showing more disagreement in responses by responding to a scenario
with “True for self, False for others” was not associated with well-being components. In
other words, there were no meaningful individual differences in the number of scenarios
in which a person would perceive feeling loved while believing that others would not.
However, discrepancies in responses displayed by choosing “False for self, True for
others,” or in other words, believing that other people would feel loved in scenarios when
the respondent would not, was associated with well-being components. More specifi-
cally, people who showed lower levels of this type of disagreement (“False for self, True
for others”) displayed having a more meaningful life, feeling more accomplished, having
positive relationships, and experiencing more positive emotions. People have a funda-
mental need to belong, and feelings of exclusion might result in “social pain” (Novembre
et al., 2015)—a threat to their social relationships and their attachment system (Bowlby,
1982; Hazan & Shaver, 1994). Thus, when people acknowledge that the society to which
they belong has certain norms around love, in order to feel included in the society, they
are inclined to want the same norms for themselves—in this case wanting to feel loved
by the same indicators that they think others in their cultural group would feel loved.
This notion of social inclusion is in part aligned with the concept of Fear of Missing Out
(FoMO), “a pervasive apprehension that others might be having rewarding experiences
from which one is absent” (Przybylski et al., 2013, p. 1841). With FoMO comes a desire
to be similar to others and be a part of what they are engaged in (e.g., usage of social
media in youth). Hence, in the context of norms and beliefs on indicators of love, people
may also experience FoMO when they realize that what makes others feel loved is not
what makes them feel loved (captured by our “False for self, True for others” dis-
agreement), and might be linked with lower levels of well-being, consistent with our
findings. However, when one can experience loving feelings even when others do not
(captured by our “True for self, False for others” disagreement), the same FoMO
mechanisms are not in play, leading to an asymmetry in terms of links with well-being.
Additionally, we conducted regression analyses to examine the predictive relation-
ship of cultural congruence in beliefs on love and the five well-being indicators. All in
all, we concluded the predictive power was relatively small. Although the overlap
between beliefs about the self and the cultural consensus were predictive of all five
PERMA elements, this congruence in beliefs on love was most predictive for Rela-
tionships and Meaning components. These stronger associations may be expected as
love—particularly experienced in everyday life—has been related to higher levels of
perceived support and care and higher relationship satisfaction (Graham, 2011), as well
as being a source of meaning and purpose in people’s lives (O’Donnell et al., 2014).
Moreover, we found being in a relationship or not moderates the association between
cultural congruency on beliefs on love and the Relationships component of well-being.
In other words, people who were in a relationship were more likely to experience higher
levels of positive relationships when their own beliefs on love overlapped with the
cultural consensus on love. This finding is in line with the results in Heshmati et al.
(2019) which demonstrated that people who were in a relationship had higher ability to
know the consensus on love, hence the higher likelihood of this knowledge being
associated with positive outcomes in their relationships.
18 Journal of Social and Personal Relationships XX(X)
Learning about these discrepancies and their relation to well-being can provide
foundations for the development of well-being interventions in the future. For instance,
future research might examine whether emotional fit and FoMO are a mediator of self-
other alignments in beliefs on love in relation to well-being. Practitioners can then use
this finding to target and resolve those self-beliefs that are not aligned with the cultural
beliefs and beliefs about others to cultivate emotional fit and alleviate social pain.
The current study had the following limitations: First, self-other and self-consensus
overlaps of beliefs on loving signals were only examined in relation to well-being. Future
studies could extend this investigation to other individual differences such as exploring
associations with attachment styles and communal orientations. Second, our measure-
ment of the engagement component of well-being was limited in the sense that it only
asks about how engaged individuals were the day they took the survey, whereas other
elements of well-being were measured in a more general sense. We used the engagement
items in this format because it is difficult to ask individuals about their sense of
engagement in general, given that engagement can be better assessed with experience
sampling design (i.e., multiple repeated measurement in everyday life context, e.g.
Csikszentmih´alyi, 1996). Third, because the sample was from the United States, the
external validity of the findings is limited, and cross-cultural investigations would be
useful in future studies.
Conclusion
This study aimed to elucidate links between cultural congruency in beliefs on love and
psychological well-being. For this, we introduced two novel indicators of congruency in
the context of love in daily life: a model-based indicator that contrasted beliefs related to
self with the cultural consensus (based on CCT modeling) and a more data-driven
indicator that contrasted beliefs related to self with beliefs related to others. Results
showed that both indicators related meaningfully to different aspects of psychological
well-being. Specifically, we found that people whose own beliefs on love had higher
overlap with their beliefs about others as well as the cultural consensus, also reported
higher positive emotions, positive relationships, meaning in life, and accomplishment in
daily life. This association was even stronger for people who were in a romantic rela-
tionship versus those who were single. On the other hand, when people displayed dis-
crepancies in their own beliefs and the cultural consensus, particularly when they
believed that other people would feel loved in scenarios when they themselves would
not, lower levels of well-being were reported.
To our knowledge, this study was the first to examine cultural congruency in beliefs
on love and relate it to psychological well-being. By exploring different ways that
cultural congruency in beliefs on love can be conceptualized—agreements and dis-
agreements in self versus other beliefs as well as self versus cultural consensus—we
were able to test these different conceptualizations of cultural congruency on love in
relation to psychological well-being in adults in the United States.
Future studies might test the direction of these associations in interventions where
individuals are made aware of cultural norms—specifically cultural norms of loving
feelings—while monitoring their well-being in this process. Furthermore, future research
Heshmati and Oravecz 19
can examine possible causal directions or mediation models that explore the relationship
between, perceptions of love, and daily well-being and how one might predict the other.
Moreover, as discussed elsewhere (e.g., Heshmati et al., 2019), future studies should
pursue a cross-cultural examination of beliefs on love and its relation to well-being as
these cross-cultural differences have been seen in differential emotional patterns
between cultures such as American and Asian cultures (e.g., European Americans have a
tendency toward pride and anger while East Asians have a tendency toward closeness
and embarrassment; Boiger et al., 2013; Kitayama et al., 2006; Markus & Kitayama,
1994). Due to lack of past research on love as an everyday experience and the cultural
consensus on what makes people feel loved, we hope that our findings will generate
hypotheses for future research on love.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/
or publication of this article: This work was supported by the John Templeton Foundation under
grant number 48192 (http://templeton.org/).
ORCID iD
Saeideh Heshmati https://orcid.org/0000-0003-4002-128X
Open research statement
As part of IARR’s encouragement of open research practices, the author(s) have provided the
following information: This research was not pre-registered. The data used in the research
are available. The data can be obtained at: https://osf.io/g6mqe/?view_only¼b54bd0e
176844f8ca7769634c22b0159. The materials used in the research are available. The materials
can be obtained at: https://osf.io/g6mqe/?view_only¼b54bd0e176844f8ca7769634c22b0159.
Notes
1. Note that these are reciprocal, that is BF10 ¼1/ BF01.
2. The JASP software can be downloaded from this website: https://jasp-stats.org/download/.
3. Supplemental files are available on the Open Science Framework: https://osf.io/g6mqe/? view_
only¼b54bd0e176844f8ca7769634c22b0159.
4. We chose to evaluate out-of-sample prediction power in an attempt to quantify generalizability
of predictive power to new data sets. The more traditional “in-sample” prediction power (which
is always higher than out-of-sample), via including all available predictors, would only quantify
the fit to the current data, which would carry the risk of overfitting. This means that we
eliminated from this model those predictors that we conclude to have a regression weight of
zero, and that only contribute noise to the prediction.
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