RdjkldRunning head1
FACULTEIT PSYCHOLOGIE EN
PEDAGOGISCHE WETENSCHAPPEN
Academic Year 2015-2016
Second Semester Examination Period
Hugging and Laughing within Families Analyzed with a
Purely Dyadic Social Relations Model: Heterosexual Families
Compared with a Lesbian Family.
Master dissertation II submitted in fulfillment of the requirements for the
degree of Masters in Psychology: Clinical Psychology
Promoter: Prof. Dr. Ann Buysse
Co-promoter: Prof. Dr. Tom Loeys
Mentor: Ph.D. Lara Stas
Michelle Hufkens
01101305
HUGGING AND LAUGHING WITHIN FAMILIES
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Acknowledgements
Writing this thesis would not have been possible without the help and support of several
people, whom I would like to express my sincere gratitude to. First of all, I would like
to thank my mentor Lara Stas and co-promotor Prof. Dr. Tom Loeys for giving me the
opportunity to investigate this interesting and novel topic. They guided me through the
application of a brand-new statistical method and we cooperated in formulating a
research question that fitted the broad investigation in harmony with my personal
interests. Secondly, I would like to thank my partner for our brainstorms that delivered
creative insights considering the topic. Next, I am grateful for the willingness and
honesty of the participating families. It was a pleasure to execute the empirical work
with them. Finally, I would like to thank my parents for all their support during my
studies at university.
HUGGING AND LAUGHING WITHIN FAMILIES
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Abstract
The first aim of the study is to investigate the amount and the components that
determine the amount of hugging and laughing within families. Home visits are
executed with a group of 97 heterosexual families. The data are analyzed with the
Purely Dyadic Social Relations Model (PDSRM; Stas, Cook, & Loeys, In press). The
model offers the opportunity to investigate families on three levels: the family level, the
individual level and the relationship level. Findings show that hugging and laughing
both have a high occurrence within families and the behaviors are determined by a
pattern of the three family levels. The second aim of the study is to investigate a lesbian
family to broaden the empirical field on same-sex families and to contribute to
consistent existing research that encounters sexual prejudice. The lesbian family is
compared with the heterosexual comparison group to compare patterns of hugging and
laughing by calculating Z-scores. Results indicate a lower amount of hugging and a
similar amount of laughing within the lesbian family compared with the heterosexual
comparison group.
HUGGING AND LAUGHING WITHIN FAMILIES
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Abstract
De eerste doelstelling van deze studie is het onderzoeken van de hoeveelheid en de
componenten die de hoeveelheid van knuffelen en lachen binnen gezinnen bepalen.
Huisbezoeken zijn uitgevoerd bij een groep van 97 heteroseksuele gezinnen. De data
zijn geanalyseerd met het Purely Dyadic Social Relations Model (PDSRM; Stas, Cook,
& Loeys, In press). Het model biedt de mogelijkheid om families op drie niveaus te
bestuderen: het familie niveau, het individueel niveau en het relationeel niveau. De
resultaten tonen aan dat knuffelen en lachen vaak voorkomen binnen gezinnen en dat
deze gedragingen verklaard worden door een patroon van deze drie verschillende
gezinsniveaus. De tweede doelstelling van deze studie is het onderzoeken van een
lesbisch gezin om het onderzoeksdomein hieromtrent uit te breiden en om bij te dragen
aan consistent bestaand onderzoek dat homoseksuele vooroordelen weerlegt aan de
hand van optimistische resultaten. Het lesbische gezin wordt vergeleken met de
heteroseksuele vergelijkingsgroep om patronen van knuffelen en lachen te vergelijken
via de berekening van Z-scores. Resultaten tonen een mindere hoeveelheid van
knuffelen en een vergelijkbare hoeveelheid van lachen aan binnen het lesbische gezin in
vergelijking met de heteroseksuele vergelijkingsgroep.
HUGGING AND LAUGHING WITHIN FAMILIES
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Table of contents
Introduction ...................................................................................................................... 6
A Framework for Families ............................................................................................... 7
Hugging and Laughing ............................................................................................... 12
Homosexual Family Households ................................................................................ 17
The Social Relations Model ....................................................................................... 21
Method ............................................................................................................................ 29
Participants ................................................................................................................. 29
Measures ..................................................................................................................... 30
Procedure .................................................................................................................... 31
Analytic Strategy ........................................................................................................ 32
Part I: Analyses of the heterosexual families ......................................................... 32
Part II: Analyses of the same-sex family and the comparison group ..................... 35
Results ............................................................................................................................ 36
Missing Values ........................................................................................................... 36
Part I: Analyses of the Heterosexual Families............................................................ 36
The fit of the PDSRM with the data ....................................................................... 36
PDSRM analyses .................................................................................................... 37
PDSRM analyses: Hugging .................................................................................... 37
PDSRM analyses: Laughing ................................................................................... 39
Part II: Analyses of the Same-sex Family and the Comparison Group ...................... 42
Discussion and Conclusion ............................................................................................. 44
Part I: Hugging and Laughing Within Families Analyzed With a Purely Dyadic
Social Relations Model ............................................................................................... 44
Part II: Heterosexual Families Compared With a Lesbian Family ............................. 47
Limitations .................................................................................................................. 49
General Conclusion .................................................................................................... 51
HUGGING AND LAUGHING WITHIN FAMILIES
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Hugging and Laughing within Families Analyzed with a Purely Dyadic Social Relations
Model: Heterosexual Families Compared with a Lesbian Family.
Families that hug and laugh more are happier, healthier and more connected
(Forsell & Aström, 2012; Gerhardt, 2014; Holt-Lunstad, Birmingham, & Light, 2008;
Light, Grewen, & Amico, 2005; Ripoll & Casado, 2010). The family is the primary
focus to understand behaviors like hugging and laughing (Minuchin, 1985) and most
efficiently by using the Family Systems Theory as a theoretical framework (Bowen,
1966; Cox & Paley, 1997). Families and its members evolve over time within a direct
family environment stimulating this evolution process, primarily early in life but the
influence extends throughout the whole life course (Bronfenbrenner, 1995). The family
is thus interesting to study different kinds of processes (Minuchin, 1985).
Bronfenbrenner (1995) states that enduring reciprocal interactions systematically taken
place over time (e.g., parent-child and child-child activities like hugging and laughing)
are worthwhile to investigate. Families embody a broad range of possible compositions
these days, which makes it irrelevant to describe it as a singular structure (Charles,
Davies, & Harris, 2008; Lamanna, Riedmann, & Stewar, 2014; Lewis, 2003; Popenoe,
1988; Stacey, 1998). Generally, the family is described as a relatively small group of
people living together (Lamanna et al., 2014; Popenoe, 1988) over a longer period of
time (Weeks, Heaphy, & Donovan, 2001). Family members can be related by intimacy
(Lamanna et al., 2014), blood, marriage or adoption (Lamanna et al., 2014; Popenoe,
1988). Within the family there is usually an atmosphere of care, emotional support,
affection and nurturance (Lewis, 2001; Popenoe, 1988; Weeks et al., 2001). Next to
emotional support, material support and sharing economic recourses is also often a
characteristic of families (Popenoe, 1988; Weeks, 2001). Family members often feel
loyal, attached and committed to the group (Lamanna et al., 2014; Weeks, 2001).
Families can contribute to one’s identity (Lamanna et al., 2014) and to the formation of
cultural and symbolic interpretations (Weeks et al., 2001) related to the family narrative
(Fiese & Spagnola, 2005). Within families, hugging and laughing are crucial processes
considering interrelationships, physiological and psychological health (Forsell &
Aström, 2012; Ripoll & Casado, 2010). Surprisingly, these processes are still
underestimated within the context of families as they are ignored in research until now
(Bachorowski & Owren, 2001; Gallace & Spence, 2010; Kurtz & Algoe, 2015). Going
HUGGING AND LAUGHING WITHIN FAMILIES
7
back into history before 1950, the traditional nuclear family consisted of a married
couple (i.e., husband and wife) and dependent children (Lamanna et al., 2014; Popenoe,
1988; Stacey, 1998). Households followed the traditional sequence of first getting
married, then cohabit and then give birth to children (Axinn & Thornton, 1993). This
view on the composition of families is no longer suitable (Popenoe, 1988). Starting
around 1960 and extending to the 21th century, one can speak of a social evolution
leading to massive changes in family compositions and practices (Axinn & Thornton,
1993; Charles et al., 2008; Lewis, 2003; Popenoe, 1988; Stacey, 1988). Especially the
increase in detraditionalization and individualism combined with a decrease in external
control led people to form families in harmony with their personal interests (Charles et
al., 2008; Lewis, 2003). The decrease in the prevalence of traditional families in many
western societies within the past few decades led to the emergence of many different
family forms (Axinn & Thornton, 1993; Lamanna et al., 2014). Stacey (1998)
established the concept of a postmodern family, covering with this term a great
assortment of family household compositions existing equally next to each other. It is
possible to choose whether you want to have children or not (Weeks et al., 2001), to
decide to take care of children as a single parent (Brown, Manning, & Stykes, 2015;
Herek, 2006) or to engage in a stepfamily (Brown et. al. 2015; Herek, 2006). Other
possible family compositions are extended families (e.g., including grandparents or
other kin-related individuals within the family); (Bengtson, 2001; Stacey, 1998), samesex couple households (Regnerus, 2012; Rosenfeld, 2010; Stacey & Biblarz, 2001),
adoption households (Herek, 2006; Miller, Fan, Christensen, Grotevant, & van Dulmen,
2000) or households where children are received through in vitro insemination (Herek,
2006). Within the current research, a focus on the same-sex family is chosen to explore
to a further extend. The first part of the study considers heterosexual families and the
second part includes same-sex families. The Family Systems Theory is considered to
offer a framework to explore and investigate hugging and laughing processes within
families in general (Bowen, 1966; Cox & Paley, 1997; Minuchin, 1985).
A Framework for Families
Multiple different approaches exist to study families (Klein & white, 1996). A
summary of the different frameworks to apply in family research is listed as follows: (a)
The Social Exchange Theory (Emerson, 1976) based on utilitarianism and the reward-
HUGGING AND LAUGHING WITHIN FAMILIES
8
cost balance of exchanges within relationships (Emerson, 1976; Lamanna et al. 2014);
(b) The Symbolic Interaction Theory (Stryker, 1959) based on the idea that behavior is
understood by perceptions of the individual; (c) The Developmental Theory (Elder,
1998) based on the stages of the family life course and systematic changes that come
with it; (d) The Evolutionary Theory (Emlen, 1995) based on the generalization of
parameters explaining family life of birds and mammals to humans (e.g., genetic
relatedness, social dominance, the benefits of group living and the probable success of
independent reproduction); (e) The Conflict Theory (Farrington & Chertok, 1993) based
on self-interest and conflict; (f) The Ecological Theory (Bronfenbrenner, 1979) based
on adaptations through interchanges with the micro – meso – exo and macrosystem and
the last approach mentioned here; (g) The Family Systems Theory (Bowen, 1966; Cox
& Paley, 1997) based on multiple interconnected levels and circular causal processes
within family systems. The approach that views families as systems is chosen as a
framework to base the current research on. Mainly the inclusion of interrelatedness,
multicausality and different interacting levels within family systems convey this choice
(Bowen, 1966; Cox & Paley, 1997). The reasons for why this approach fits the current
research best is clarified more detailed by describing its profound manner to perceive
family processes.
The Family Systems Theory is influenced by Bateson (1972), a pioneer in
introducing the idea of out-thinking i.e., thinking further than the inner world of an
individual. He states that it is crucial to look at situations, messages and systems in a
holistic manner including context. The Family Systems Theory is inspired by this
holistic point of view and conveys that families are systems consisting of individuals
that are interrelated, interdependent and cannot be understood in isolation from their
context, the family system (Bowen, 1966; Cox & Paley, 1997; Minuchin, 1974, 1985;
Watzlawick, Jackson, & Beavin, 1967). Furthermore, family members’ behavior
continuously and reciprocally influences and is influenced by all other members of the
family system implying interrelatedness of behavioral processes (Bowen, 1966; Cox &
Paley, 1997; Hedges, 2005; Minuchin, 1974; Watzlawick et al., 1967). To understand
family members’ processes (e.g., behavior, mental and physical health) one should
always consider context, interaction and communication (Watzlawick et al., 1967).
HUGGING AND LAUGHING WITHIN FAMILIES
9
The Family Systems Theory is based on four components. The first component
consists of the switch in reasoning from a linear, unidirectional causality to a circular
and multidirectional causality (Bertalanffy, 1969; Minuchin 1985). This switch conveys
the evolution in studying internal processes of the individual and one-way observations
of the mother-child dyad to an interest in multidirectional interrelationships within the
family system (Bertalanffy, 1969; Bowen, 1966; Minuchin, 1985). Within research, the
traditional unidirectional approach led parenting to be considered as parents shaping
their children (Maccoby, 2003). Bidirectionality can be understood as the recognition of
simultaneous influences of both directions of the relationship partners within a complex
reciprocal system (Kuczynski, Lollis, & Koguchi, 2003). Cox and Paley (1997) state
that the reciprocity of influences within the different levels of the family system (e.g.,
individual level, dyadic level and whole family level) is resonated by circular causal
processes. The family consists of a cycle where at least two individuals create patterns
of interactions and it is irrelevant to hold one individual responsible for behavior or
communication (Minuchin, 1985). The second component of the Family Systems
Theory following the vision of Bowen (1966), Cox and Paley (1997, 2003), Minuchin
(1985), and Watzlawick and colleagues (1967) is that families are systems consisting of
subsystems, that are systems on their own, with a hierarchical structure. The authors
assume individual, parental, marital and sibling subsystems versus the larger family or
community system and continuous, reciprocal interactions within and across the
different levels (e.g., sibling interactions, parent-child interactions, whole family
interactions, etc.). The third component is called wholeness, which means that the
whole is greater than the sum of its parts (Cox & Paley, 2003). Family processes are
influenced by the family’s subsystems and larger systems of which the family system is
part (Bowen, 1966). To describe family processes one should include the characteristics
of the system and the interactional patterns that transcendent the sum of individual
family members’ observations i.e., including wholeness in family analyses (Cox &
Paley, 1997; Watzlawick et al., 1967). The fourth component of the Family Systems
Theory is about homeostatic and adaptive mechanisms to restore balance within the
system as a result of changes in this system (Bowen, 1966; Cox & Paley 1997;
Minuchin, 1985; Watzlawick et al., 1967). For a more comprehensive explanation, the
HUGGING AND LAUGHING WITHIN FAMILIES
10
interested reader is directed to Bowen (1966), Minuchin (1974) and Cox and Paley
(1997) who explain the mechanisms following change within the family system.
The Family Systems Theory stimulates research within social science in new
and important directions (Cox & Paley, 2003) by evolving a better understanding of
multidirectional, regulatory processes of all family members and their relationships
within a dynamic family system (Cox & Paley, 1997; Minuchin, 1985). Dekovic and
Buist (2005) found evidence for the existence of subsystems, boundaries between
subsystems and differences in processes within family relationships and patterns of
interactions within the whole family. This shows the importance of the components of
the Family Systems Theory to study the complexity of the family and encourages
incorporating them in research. The interest in implementing the family system
framework has been growing the past few decades (Cox & Paley, 2003; Dekovic &
Buist, 2005). This is linked with the agreement of professionals within the family
system field to broaden the view on families beyond the mother-child dyad (Cox &
Paley, 1997; Dekovic & Buist, 2005; Minuchin, 1985) and beyond unidirectionality
(Cappa, Begle, Conger, Dumas, & Conger, 2011; Cook, 2001; Kuczynski, 2003;
Padilla-Walker, Carlo, Christensen, & Yorgason, 2012; Rober, 1998).
Within the current research, the family systems framework is assumed to be
adequate to base the investigations on, as it includes the importance of circular causality
of dynamic transactional processes across multiple family levels (Bowen, 1966; Cox &
Paley, 1997). Hugging and laughing are two important, positive and affectionate
processes of this kind influencing emotional and physiological wellbeing of family
members (Forsell & Aström, 2012; Ripoll & Casado, 2010). Based on the dominant
idea within the Family Systems Theory of multidirectional influences within families,
the individual does not solely engage in affective physical contact or positive laughing
interactions but the processes rather take place in a reciprocal family context (Fogel &
Garvey, 2007). Hugging and laughing are not included in family research yet, especially
not by incorporating interrelatedness between different family levels and assuming
multidirectionality (Dunbar et al, 2012; Gallace & Spence, 2010; Kurts & Algoe, 2015).
Therefore, before describing hugging and laughing behaviors as such, research
examples are summarized that include affective processes, interrelatedness and
bidirectionality. Thus, regarding the affective domain, several research examples shed
HUGGING AND LAUGHING WITHIN FAMILIES
11
light on the existence of different patterns within families. The examples include
heterosexual families, do incorporate the bidirectional influences and go beyond the
mother-child dyad (Branje, van Aken, & van Lieshout, 2002; Buist, Dekovic, Meeus, &
van Aken, 2004; Cook, 2000). This is important when implementing the Family
Systems Theory as a framework (Cox & Paley, 1997). Research should then include the
three levels i.e., the family level, the individual level and the relationship level.
Examples are emotional support perception (Branje et al., 2002), comfort in depending
on others (Cook, 2000), quality of affectional bonds (Buist et al., 2004) and warmth
(Manders et al., 2007). When the family is studied as a whole, differences between
families in family climate or culture affect family members’ perceptions on warmth,
quality of attachment and emotional support (i.e., mean family level); (Buist et al.,
2004; Manders et al., 2007). Manders and colleagues (2007) found that families usually
have a highly warm family climate. When the focus is narrowed down to the individual
family members, different patterns are found from family to family (Cook, 2000). Some
mothers, fathers, younger adolescents and older adolescents experience for example
more or less support than in other families. Only mothers do not differ in their
perceptions (Cook, 2000). Within each role, people differ in how comfortable a person
is in depending on the other family members in general. The comfort level and the
quality rating of affectional bonds of younger siblings varied more across families than
the other family roles (Buist et al., 2004; Cook, 2000). Mothers seem to play an
important role considering affectional bonds shown by the evidence that all family
members and especially the youngest adolescent, rate the quality of the affectional bond
and perceived warmth highest for the mother (Buist et al., 2004; Manders et al., 2007).
It would also confirm the idea of prescriptive gender-based parenting expectancies
(Moon & Hoffman, 2008). Feldman, Wentzel, and Gehring (1989) found that individual
family members report less father-child cohesion than mother-child cohesion and
marital cohesion that are equally cohesive. This leads to the assumption that fathers hug
and laugh less with their children than mothers do. Affective processes are in part
relation specific (Branje, et al. 2002; Buist et al., 2004; Cook, 2000). This is for
example the case for comfort in depending on others, quality of affectional bonds and
emotional support (Branje, et al. 2002; Buist et al., 2004; Cook, 2000). Within a
generation (e.g., siblings, parents), relationships are more important to explain processes
HUGGING AND LAUGHING WITHIN FAMILIES
12
than between generations (e.g., child-parent dyad); (Branje et al. 2002; Buist et al.,
2004). This is especially the case between spouses where the unique adjustment is
highest and makes this dyad unique within the family (Branje et al. 2002; Buist et al.,
2004; Cook, 2000). Parents perceive the highest level of emotional support from their
spouse. The second highest level is between parents and adolescents from both sides of
the dyad. The least perceived support is rated among siblings (Branje et al., 2002).
Research shows that siblings give each other the lowest quality of relationship (Buist et
al., 2004) and warmth rating (Manders et al. 2007).
Until now, no research has focused on the occurrence of hugging and laughing
within families with the inclusion of the different interacting levels, especially not with
teenagers. This addresses the first focus of the current research. When investigating a
sample with young children, mothers seem to engage more in personal interactions,
physical caretaking and emotional support showing the influence of gender based
parenting expectancies on parenting (Biblarz & Stacey, 2010b; Moon & Hoffman,
2008). Which conclusions can be drawn from samples with adolescents, measuring the
specific affective processes laughing and hugging, including multiple levels (i.e., going
beyond the mother-child dyad) remains unclear. In the next section, the study focuses
on what is known about hugging and laughing in the existing literature.
Hugging and Laughing
The importance of hugging and laughing is demonstrated by multiple research
examples in the literature (Forsell & Aström, 2012; Ripoll & Casado, 2010). In the next
paragraphs definitions combined with the importance of the considered processes are
clarified. This conveys the underlying goal to encourage the inclusion of these
processes, with a clear-cut definition of its meaning, within family research.
The first process considered within the study is hugging. It can be described as
embracing another person’s body with the arms (Morris, 1977). Forsell and Aström
(2012) state that this movement depends on both the emotional state of the persons and
the intensity of the relationship. The authors also specify that it conveys a need for
closeness and affection and that it shows empathy, support and gratitude. Starker (2002)
states that hugging usually starts with placing the hand on the other body (e.g., the
shoulder), and one chooses then to hug from the front, side or behind. The pressure can
vary from light to strong and bodies can touch just slightly or full body (Starker, 2002).
HUGGING AND LAUGHING WITHIN FAMILIES
13
In this study the following definition based on previous descriptions is used: Individuals
embrace each other with the arms while letting bodies touch, depending on the
emotional state and the intensity of the relationship, and while showing empathy or
affection. Hugging and other affective bodily touches have a positive impact on both
psychological and physiological wellbeing (Forsell & Aström, 2012; Gerhardt, 2014).
The effects are proven by research using (a) parent – child relationships and (b) adults.
Although several examples will be mentioned, the amount of scientific research on
interpersonal touch is still very small scale (Gallace & Spence, 2010). The first research
domain, focusing on the parent-child relationship, shows the importance of hugging
behavior in supporting the wellbeing of children. Parents that gently hold and touch
their babies enhance the development of the social brain that enables individuals’
capacities for social interactions (e.g., understanding and feeling other people’s
behavior and feelings); (Gerhardt, 2014) and self-regulation (e.g., emotion regulation
and exploration); (Gerhardt, 2014; Feldman, Eidelman, & Sirota, 2002). This warm
holding and touching behavior also affects muscle relaxation (Gerhardt, 2014), levels of
heart rate, breathing and stress reactions (Gerhardt, 2014; Feldman et al., 2002), crying
and sleep (Feldman et al., 2002). Bowlby (1969) states that it is the caregiver’s task to
embrace and caress the child combined with encouraging and affectionate language in
order to provide a safe haven for the child that promotes emotion regulation and
exploration. Another example of the importance of interpersonal touch within the
parent-child relationship is the study of Fairhurst, Löken, and Grossman (2014) that
illustrates young infants to respond favorably (e.g., more engagement and less stress) to
gentle, soft brushing. Previously described examples support the idea that affective
physical contact is important for parent-child interactions, child development and
positive emotions (Feldman et al., 2002). Touching, hugging and holding even stimulate
the brain and are a base for intelligence development (Gerhardt, 2014). The second
research domain shows that the impact of hugging is not restricted to childhood but
extends to late adulthood (Field, 2010; Forsell & Aström, 2012; Gerhardt, 2014).
McGlone, Wessberg, and Olausson (2014) and Morrisson, Löken, and Olausson (2010)
state that every individual has neurological vessels that are stimulated through slow,
warm and gentle touching behavior (e.g., hugging, caressing, etc.). The authors interpret
pleasure from hugging in social interactions as the basis for relationships,
HUGGING AND LAUGHING WITHIN FAMILIES
14
communication and empathy. Research that includes adult participants shows that
hugging has the capacity to protect people from illnesses (Cohen, Janicki-Deverts,
Turner, & Doyle, 2014). Participants suffering from a cold in the study of Cohen and
colleagues (2014) that received hugs regularly showed fewer symptoms. Another study
using biomarkers showed the origin of human bonds via social touch mediated by
oxytocin and endorphin (Dunbar, 2010). Beneficial effects of physical contact (e.g.,
warm touch or frequent hugging) between romantic partners result in lower blood
pressure (Ditzen et al., 2007; Grewen, Light, & Amico, 2005; Holt-Lunstad,
Birmingham, & Light, 2008), lower stress reaction (e.g., cortisol level, physiological
reactivity); (Ditzen et al. 2007) and more connectedness (i.e., higher oxytocin levels)
(Grewen et al., 2005; Holt-Lunstad et al., 2008). Flynn and Gow (2015) stressed the
importance of hugging and embracing considering quality of life in late adulthood.
People feel emotionally validated and understood by physically comforting each other
by hugs (Gerhardt, 2014).
The second process considered within the study that also characterizes positive
interactions is laughing. Ripoll and Casado (2010) define it as behavior that usually
occurs as a reaction to positive stimuli such as humor or pleasant thoughts and feelings.
Laughing involves both psychological and physiological processes (e.g., facial
expression, body movements, neurological changes, etc.); (Ripoll & Casado, 2010) and
mostly appears in social circumstances (Kurtz & Algoe, 2015). In a group (e.g., a
family) people also tend to laugh more solid and energetically then when they are alone
(i.e., laughing is related to social control); (Hayworth, 1928). Laughing indicates that a
person experiences a positive emotion (Ripoll & Casado, 2010) but on the other hand is
it also a form of tension release (Hayworth, 1928). When laughing occurs after the body
is in an accumulated tensed state it is followed by relaxation. Laughing is then
experienced as delight. Both positive emotions and delight are outcomes of the
awareness of safety (Hayworth, 1928; Wooten, 1996). In this study the following
definition is used: Laughing is a reaction to positive stimuli or a form of tension release
and indicates mainly positive experiences, often occurring within social interactions.
Being aware of the importance of laughing in boosting the wellbeing of people
and its positive mental and physical health outcomes, one should include this process in
research (Ripoll & Casado, 2010). Laughter is a valuable part of nonverbal
HUGGING AND LAUGHING WITHIN FAMILIES
15
communication with a notable impact on a person’s most essential relationships
(Dunbar et al., 2012; Kurtz & Algoe, 2015). Although the characteristics of laughing
behavior itself (e.g., vocality) are investigated (Bachorowski & Owren, 2001), research
on links with psychology or social outcomes (e.g., family interactions) is very rare
(Dunbar et al., 2012; Kurtz & Algoe, 2015). The distinction in research focusing on (a)
childhood and (b) adulthood is made similarly to the hugging section, albeit keeping in
mind the lack of research examples that prevent an extensive review (Bachorowski &
Owren, 2001; Kurtz & Algoe, 2015). To address the first research domain focusing on
childhood, Bowlby (1969) is again an important reference stating that it is the
caregiver’s task to use encouraging and affectionate language with children while
embracing and caressing the child to provide a safe haven for the child that promotes
emotion regulation and exploration. Even very young babies’ brains respond to the
sound of happily laughing people, making them feel cheerful (Gerhardt, 2014). Children
that see their parents laughing or expressing joy visually or vocally experience positive
vitality e.g., feel joyful, energized and stimulated (Schore, 2015; Termine & Izard,
1988). Studies including adult participants show many advantages of laughing,
indicating its importance. The first example focuses on the effect of laughing on
relaxation, proving that true laughter leads to more muscle relaxation (Overeem, Taal,
Gezici, Lammers, & Van Dijk, 2004). Bennet, Zeller, Rosenberg, and McCann (2003)
and Berk and colleagues (1989) underline the second advantage of laughing on the
immune system, explaining how it can contribute to an individual’s resilience. The
authors show that laughing improves the immune system (i.e., decreasing the stress
hormone called cortisol and increasing auto-immune cells) by reducing harmful effects
of stress on the body. The third advantage of laughing is demonstrated by an experiment
using comedy video clips executed by Sakuragi, Sugiyama, and Takeuchi (2002)
suggesting that laughing improves positive mood and self-efficacy and it decreases
anger and hostility. The researchers also point out that laughing has an impact on the
autonomic nervous system while increasing heart rate. It is important to mention that
these effects are transient which is not the case with unpleasant emotions. The fourth
advantage of laughing is the usefulness in therapy (Ripoll & Casado, 2010; Sutorius,
1995) and self-care (Stein & Reeder, 2009; Wooten, 1996). Laughing at one’s own
problems is an effective self-care tool to manage stress in daily life (e.g., nervousness,
HUGGING AND LAUGHING WITHIN FAMILIES
16
exhaustion, unpleasant feelings, etc.) to feel more positive and empowered while giving
unpleasant feelings no chance to biochemically change and damage the body (Stein &
Reeder, 2009; Wooten, 1996). Bennet and colleagues (2003) conclude that laughter
should be implemented in therapeutic interventions because the immune system is
linked to several severe diseases (e.g., cancer, HIV, etc.). Laughing is a bidirectional
social phenomenon embedded within interaction because (a) observers are affected by
laughing as they respond more positive to melodic than whispering unvoiced laughter
(Bachorowski & Owren, 2001); and (b) vocalizations of the laugher are unconsciously
tuned considering the emotional state of the listener (e.g., enhancing positive affect), the
connection to the listener and unconscious intentions (e.g., acknowledgement and a
favorable attitude from the listener); (Bachorowski & Owren, 2003). Several
researchers stress the social value of laughing by viewing it as a possibility to groom at
a distance, constituting the sixth advantage. Grooming leads to social bonding and
laughing would thus have a similar effect (Dunbar et al., 2012; Dezecache & Dunbar,
2012; Provine, 2013). Social bonding could be influenced by the positive affect that is
derived from laughing (e.g., due to the release of feel good neurotransmitters in the
brain); (Dunbar et al., 2012). The seventh advantage is explained by research done by
Dunbar and colleagues (2012) showing that social laughing increases pain tolerance
(i.e., laughing leads to an enhanced endorphin uptake known to decrease pain). The last
advantage of laughing mentioned here concerns positive global evaluations of
relationship quality, relational closeness and perceptions of partner supportiveness when
partners laugh synchronically (Kurtz & Algoe, 2015). This research shows that laughing
plays an important role in stimulating social contact and relationships (Kurtz & Algoe,
2015). None of the examples include the family system as the research focus, because
this research does not exist yet (Dunbar et al, 2012; Kurtz & Algoe, 2015). Anyway, the
importance of laughing within close, social interactions, which are present within a
family (Lewis, 2001; Popenoe, 1988; Weeks et al., 2001), is made clear.
Previously described research shows the importance of hugging or affectionate
physical contact and laughing within multiple relationships (e.g., parent-child dyad,
romantic partners, social acquaintances). Because of the premise that a family is usually
a context of important experiences for the developing individual, an interest is raised in
the occurrence of these processes within the family context (Bronfenbrenner, 1995).
HUGGING AND LAUGHING WITHIN FAMILIES
17
Research focusing on the family context, mainly restricted to the parent-child dyad,
shows the importance of emotional socialization behavior of parents in a child’s
emotional and social development and that this process is bidirectional (Eisenberg,
Cumberland, & Spinrad, 1998). Evidence is found for a difference in the parent-child
expression of emotions within families (Cassidy, Parke, Butkovsky, & Braungart,
1992). Van der Pol and colleagues (2015) report that emotional and social competence
(i.e., the regulation, understanding and expression of emotions) is based on emotion
socialization via emotion talk. Hugging and laughing can be viewed as examples of
these kind of affective expressions within families. For example, Bowlby (1969)
described the importance of affectionate touch and vocals in order to help the child in
developing adaptive emotion regulation and exploration. If the processes are viewed
like suggested here these studies enhance further interest to study the processes directly
within a family context. As previously described, families can exist in several different
forms. In what follows next, the same-sex family composition is considered.
Homosexual Family Households
The second focus of this study concerns homosexual family prejudice (Herek,
2006; Patterson, 2000) despite of consistent research findings when comparing
heterosexual and homosexual families (Fedewa, Black, & Ahn, 2014; Patterson, 2000;
Perrin, 2002; Stacey & Biblarz, 2001). The decrease in the prevalence of traditional
families in many western societies within the past few decades led to the emergence of
many different family forms (Axinn & Thornton, 1993; Lamanna et al., 2014). Within
this part of the study, same-sex households are considered. Recent statistics show that
same-sex families increasingly conceive and raise children (Patterson, 2000; Gates,
2013). One in five same-sex couples are raising children under 18 years old, which is
not ignorable next to a 43.5% of heterosexual families with children under 18 years old
(Gates, 2013). The traditional family structure has been evolving but social science
research on this topic has only started to grow in the last few decades (Patterson, 2000;
Stacey & Biblarz, 2001). This is when same-sex couples started to have equal family
rights as heterosexual couples considering marriage, adoption, fertility services etc.
(Stacey & Biblarz, 2001). Before 1990, same-sex marriage and family formation was
not recognized anywhere in the world, resulting in intolerance and discrimination
(Biblarz & Savci, 2010). Since the first decade of the 21st century, more and more
HUGGING AND LAUGHING WITHIN FAMILIES
18
countries began to acknowledge legal rights for marriage and adoption for same-sex
couples but still prejudice, homophobia and discrimination are present (Herek, 2006;
Patterson, 2000).
Same-sex families are a topic of debate, which makes it relevant to investigate
differences between different-sex and same-sex families (Fedewa et al., 2014; Patterson,
2000). Antagonists of same-sex families often claim that children growing up in these
kinds of families are at a higher risk for negative developmental outcomes (Stacey &
Biblarz, 2001). They state that children simply need a mother and a father (Biblarz &
Savci, 2010; Biblarz & Stacey, 2010b; Vinjamuri, 2015; Ryan & Berkowitz, 2009).
This is probably the result of commonness in society (Vinjamuri, 2015; Ryan &
Berkowitz, 2009). Some research found negative outcomes within same-sex families in
that parents have a defending and justifying parenting attitude (Bos, van Balen, van den
Boom, & Sandfort, 2004) and children express more behavioral problems (Bos et al.,
2004), alcohol and drug abuse, cognitive impairments, emotional disturbances
(Zimbardo & Coulombe, 2015), gender dissatisfaction, inappropriate relationships,
affected sexual orientation and experiences (Cameron & Cameron, 1996; Wardle,
1997), less security, physical health, educational attainment and more smoking and
negative impact (Regnerus, 2012). Effects that are found can probably be partly
explained by homophobia and discrimination (Stacey & Biblarz, 2001) but Cheng and
Powell (2015) and Marks (2012) reassured an optimistic view on same-sex parenting by
showing that problems in selecting measurements and models largely impacted the
results. There are several methodological issues contributing to the difficulty in
comparing same-sex and different-sex families: (a) small sample size (e.g., outcomes
are sensitive to researcher’s analytical choices, trust in researchers because of past
discrimination); (Cheng & Powell, 2015; Regnerus, 2012; Umberson, Thomeer,
Kroeger, Lodge, & Xu, 2015); (b) greater heterogeneity in same-sex samples resulting
in more differences (e.g., due to marital status instead of sexual orientation); (Herek,
2006); (c) inclusion of same-sex households that have been through transitions and
failed heterosexual unions (i.e., unplanned, post-divorce); (Biblarz & Savci, 2010;
Regnerus, 2012); (d) homogenous sampling (Marks, 2012); (e) non-probability
sampling and a risk of self-selection bias (Herek, 2006; Umberson et al., 2015); (f)
limited scope of children’s outcomes (Marks, 2012); and (g) comparison group
HUGGING AND LAUGHING WITHIN FAMILIES
19
challenges (e.g., no comparison group or comparison group characteristics); (Marks,
2012; Rekers & Kilgus, 2001; Umberson et al., 2015). Comparisons are often made
with single parents or the study focuses on fatherlessness (Biblarz & Stacey, 2010b;
Zimbardo & Coulombe, 2015). Studies including planned lesbian co-mother families
are assumed to be different (Regnerus, 2012) and expansion of data on same-sex
research showed a remarkable improvement including planned lesbian co-mother
families showing that ideal parenting comes in many forms (Biblarz & Savci, 2010). A
study using probability sampling instead of convenience sampling supported the nodifference hypotheses considering psychological wellbeing, school adjustment and
family and relationship processes (Wainright, Russel, & Patterson, 2004).
Many researches question the gender exclusivity of parenting capabilities and
the need of both genders within a family (Biblarz & Stacey, 2010a; Fedewa et al.,
2014). The available body of research until now mainly shows no pronounced
differences between children reared by same-sex parents compared with heterosexual
parents (Biblarz & Stacey, 2010a; Colombok & Badger, 2010; Fedewa et al., 2014;
MacCallum & Golombok, 2004; Marks, 2012; Rosenfeld, 2010; Stacey & Biblarz,
2001). Same-sex parents are as competent in rearing their children as heterosexual
parents (Fedewa et al., 2014; Patterson, 2000; Perrin, 2002; Stacey & Biblarz, 2001).
No-difference findings include quality of the parent-child relationship (Stacey &
Biblarz, 2001), parent characteristics such as quality of parenting (e.g., expressed
warmth, sensitive responding and comfort with secure base role); (MacCallum &
Golombok, 2004; Colombok & Badger, 2010), parental involvement and skills (Stacey
& Biblarz, 2001). Examples of child characteristics that did not differ include
relationship with mother (e.g., getting along and being comfortable), attachment, quality
of relationships with peers (MacCallum & Golombok, 2004; Colombok & Badger,
2010), global and physical self-esteem (MacCallum & Golombok, 2004), cognitive
development (Stacey & Biblarz, 2001; Fedewa et al., 2014), school progress
(Rosenfeld, 2010), psychological wellbeing and social adjustment (Stacey & Biblarz,
2001; Biblarz & Stacey, 2010a), social and emotional development (MacCallum &
Golombok, 2004), gender identity and sexual orientation (Fedewa et al., 2014).
Some studies do show different parent-child relationships and psychological
adjustment depending on family structure (Biblarz & Stacey, 2010a; Golombok &
HUGGING AND LAUGHING WITHIN FAMILIES
20
Badger, 2010; Fedewa et al., 2014). The small differences are in favor of lesbian
families and are mainly found within positive affective interactions (e.g., closer parentchild relationship); (Biblarz & Stacey, 2010a; Bos et al., 2007; Fedewa et al., 2014;
Golombok & Badger 2010; MacCallum & Golombok, 2004). Examples come from
Golombok and Badger (2010) that found lesbian parents to show more emotional
involvement with their young adults. The young adults show less depression, anxiety,
hostility and problem drinking. They show more global self-worth, sense of humor and
better romantic relationships (Golombok & Badger, 2010). Bos and colleagues (2007)
confirm the higher emotional involvement within lesbian households. Children of
lesbian parents rate their mothers to be more available, dependable and to share more
interest and activities with them compared to children having parents of both gender
(MacCallum & Golombok, 2004). In the end, all parents report close and warm
relationships regardless of the family structure (Fedewa et al., 2014). This means that
family members within homosexual households fare well, and sometimes even better,
as in heterosexual families. Whether this could be due to social desirability bias because
of societal homophobia (Bos et al., 2007; Fedewa et al., 2014) or compensation for
social stigma in parenting is not yet clear (Stacey & Biblarz, 2001). On the other hand,
the lack of social support for same-sex parents and stress exposure due to persistent
stigma could also work in the opponent way showing lower adjustment (Regnerus,
2012).
Previously described examples on the comparison of affective interactions
within heterosexual and homosexual families provide a global impression about
affectivity. Nevertheless, the positive affective interactions hugging and laughing are
not yet acknowledged appropriately in experimental and observational research (Dunbar
et al, 2012; Gallace & Spence, 2010; Kurts & Algoe, 2015). This is remarkable
knowing the pronounced effects in social interactions of interpersonal touch (Gallace &
Spence, 2010) and laughter (Bachorowski & Owren, 2001; Kurtz & Algoe, 2015), the
effects of both behaviors on physical and psychological health at all ages (Forsell &
Åström, 2012; Ripoll & Casado, 2010) and the importance in emotional socialization
development in children (Eisenberg et al., 1998; Gerhardt, 2014).
The research examples that do take into account affective processes within
families (a) do not directly address hugging or laughing as such (e.g., Deater-Deckard,
HUGGING AND LAUGHING WITHIN FAMILIES
21
Atzaba-Poria, and Pike (2004) included laughing in the dyadic positivity concept but
nothing is reported about the laughing component as such); (b) do not include
measurements reflecting all levels of the family system; (c) do not include the dynamic
interplay of influences within the system by not including the interrelatedness and
bidirectionality of measurements within a family system (e.g., the interdependence
between the marital dyad and the parent-child dyad); (Cook, 1994; Cox & Paley, 2003)
and (d) do not go beyond a separate dyad and do not include several relationships within
a single model (e.g., in a family consisting of two children and two parents, twelve
relationships should be included); (Cook, 1994). Aforementioned problems contribute
to the first aim of the study and will be explained in detail later. The second aim of the
study considers the last problem discussed here; (e) the inclusion and recognition of
same-sex families within research. Kurtz and Algoe (2015) already pointed out that
same-sex relationships should be included in future research on laughing. Many
research examples encountered prejudice on homosexual families (Fedewa et al., 2014;
Patterson, 2000; Perrin, 2002; Stacey & Biblarz, 2001) but a lack of acknowledgement
of this family structure still exists (Herek, 2006; Patterson, 2000). Within the current
research, a Social Relations Model (SRM; Kenny & La Voie, 1984) is proposed to
dissolve aforementioned problems contributing to the first aim of the current study.
The Social Relations Model
The interest in implementing the family system framework has been growing the
past few decades (Cox & Paley, 2003; Dekovic & Buist, 2005). This is linked with the
agreement of professionals within the family system field to broaden the view on
families beyond the mother-child dyad (Cox & Paley, 1997; Dekovic & Buist, 2005;
Minuchin, 1985) and beyond unidirectionality (Cappa et al., 2011; Cook, 2001;
Kuczynski, 2003; Padilla-Walker et al., 2012; Rober, 1998). Researchers are becoming
aware of the importance of considering other family relationships than the mother-child
relationship and bidirectionality (Cox & Paley, 1997) but this raises the question on
how to measure processes within the family as a systemic whole (Cox & Paley, 2003).
Traditional statistical models (e.g., analyses of variance) are not sufficient in analyzing
the outcomes of family systems (Cook, 1994). There is a need for advanced statistical
techniques within the family system field (Cox & Paley, 2003). Scarcity of processoriented family research that includes multiple levels (i.e., individual, dyadic and whole
HUGGING AND LAUGHING WITHIN FAMILIES
22
family level measurements) and its interplay (Cox & Paley, 1997; Cox & Paley, 2003)
is due to methodological shortfall of traditional top-down research methods (Minuchin,
1985) that ignore the bidirectional nature of relationships and aren’t capable to measure
the multiple levels simultaneously within families (Cook, 2012; Cox & Paley, 2003;
Dekovic & Buist, 2005). Traditional family research used to emphasize the internal
processes of the individual (Minuchin, 1985) and one specific one-on-one relationship
(e.g., parent-child or marital dyad). Anyway, relationships are interconnected and may
be influenced by other dyadic relationships following the family system framework
(Cox & Paley, 2003; Dekovic & Buist, 2005). Thus, a more holistic view and extension
to bigger units i.e., from the individual up to the mother-child dyad, other dyads within
the family, all dyads together, and whole family level, is necessary in order to
understand family processes and capture the complex reality of family members’
behavior (Cox & Paley, 1997; Cox & Paley, 2003; Minuchin, 1985). Viewed from the
family system perspective, studying just the parent-child dyad is an observation of just
one subsystem and does not reflect the full complexity of the system (Minuchin, 1985).
Relationships should thus be studied as a whole (Dekovic & Buist, 2005). The Family
Systems Theory encourages the study of family processes beyond separate dyads (e.g.,
observing parents both as parents and spouses in the same context), and all relationships
simultaneously within the same family, to obtain more valuable information about the
quality of processes within a family system (Cox & Paley, 1997; Dekovic & Buist,
2005). Anyhow, this theoretical framework has rarely been empirically tested (Dekovic
& Buist, 2005). The SRM is proposed as a solution for this gap and aforementioned
problems because (a) it includes measurements reflecting all levels of the family
system; (b) it includes the dynamic interplay of influences within the system thus
includes the interrelatedness and bidirectionality of measurements within a family
system (e.g., the interdependence between the marital dyad and the parent-child dyad)
(Cook, 1994; Cox & Paley, 2003) and (c) it goes beyond the mother-child dyad and
includes several relationships within a single model (e.g., in a family consisting of two
children and two parents, twelve relationships should be included); (Cook, 1994). The
model is embedded within The Family Systems Theory and measures family relations
on three different levels: the family, individual and dyadic level (Kenny & La Voie,
1984). The SRM is already used to study family relationships within the affective
HUGGING AND LAUGHING WITHIN FAMILIES
23
domain incorporating bidirectional influences. Examples of variables measured with
this model are: emotional support (Branje et al., 2002), attachment (Cook, 2000; Buist
et al., 2004), parental affective style (Cook, Kenny & Goldstein, 1991), and reciprocity
during parent-child and sibling play (Stevenson, Leavitt, Thompson, & Roach, 1988).
Until now, hugging and laughing are not yet included in the research domain using the
SRM where multiple levels and bidirectional causality is recognized.
The SRM is based on the idea that relationships in families are influenced by
and can be disentangled in different sources of variance (Cook, 2005) and means (Stas,
Loeys, & Schönbrodt, 2015). Following this model, observations result from each
member reporting separately on their relationship with every other member of the group
(Cook, 2005; Dekovic & Buist, 2005; Kenny, 1994) i.e., directed-relationships data
(Cook, 2005). This is called a round-robin design (Cook, 2001) and is visualized in
figure 1.
Figure 1. The round-robin design in line with Cook (2005).
For example, when a four-person family is observed, all twelve different
relationships are included (e.g., marital relationship, sibling relationship and parentchild relationships) and are studied from the perspectives of all members involved. This
would offer information about family processes not obtained by observing only one
individual family member’s responses (Dekovic & Buist, 2005). The SRM is
characterized by examining three interrelated levels simultaneously: the family level,
the individual level and the dyadic level (Cook, 1994). Each level of the family system
affects family members’ behavior, feelings and cognitions in their family relationships
(De Mol, Buysse, & Cook, 2010). This means that all levels are important to consider
when investigating families (Branje et al. 2002). Understanding the contribution of the
HUGGING AND LAUGHING WITHIN FAMILIES
24
different levels of the system is of both clinical and scientific importance (Manders et
al., 2007).
On the individual level, actor and partner effects are described. The dyadic level
comprises relationship effects and the family level represents a group or family effect
(Eichelsheim, Dekovic, Buist, & Cook, 2009). The actor effect refers to the general
tendency of an individual to show certain behavior in the presence of a variety of
relationship partners (De Mol et al., 2010). This effect is also called rater effect because
it is about the continuous perception of one person in rating all other individuals
(Eichelsheim et al., 2009). Actor effects could appear through characteristics of the rater
as this leads people to behave or perceive similarly across multiple relationships (Cook,
1994). For example, in some families, mothers experience more emotional support in
relation to all other family members than in other families. The partner effect refers to
how other people perceive the partner (Eichelsheim et al., 2009). For example, families
differ in how mothers’ emotional support behavior is experienced by the other family
members. The relationship effect refers to the unique adjustments that individuals make
to specific relationship partners. For example, within the mother and father dyad the
amount of emotional support is influenced by the specific relationship these two
individuals have with each other. The family or group effect refers to the similarity
among family members. If families are internally homogenous and different across
families then this effect will be important in determining family relationship outcomes
(Eichelsheim et al., 2009). At family level, social status, ethnicity and family norms are
possible influences (Cook, 1994). The effect can be interpreted as the mean family
member (Cook, 2005; Kenny & La Voie, 1984). For example, families differ in general
in the amount of emotional support behavior.
The first purpose of the model is to isolate and measure the different sources of
variance (i.e., SRM components). Variances indicate the relative importance of the
observed relationship measure (e.g., the relationship component is important in
explaining the observed score) and indicate whether families differ from each other
(e.g., some families hug or laugh more than other families); (Cook, 2005; Eichelsheim
et al., 2009; Stas et al., 2015). The second purpose of the model is to measure means
(Eichelsheim et al., 2011; Stas et al., 2015) that indicate how often a behavior occurs
within families (e.g., siblings hug or laugh a lot).
HUGGING AND LAUGHING WITHIN FAMILIES
25
An important punctuation here is that hugging and laughing are not perceptions
but acts. Two members of the same dyad are expected to have the same score on
questions measuring the amount of laughing or hugging. For example, mother reports
on the amount of hugging with all other family members and the other members report
on how much mother hugged or laughed with them. This will generally result in the
same score, as the question is how much they really hugged or laughed together instead
of how they perceive it (i.e., personal perception is not completely absent but fairly
reduced). This implies that a traditional directed SRM is not suitable. So instead of
having the scores where the mother rates the child and the child rates the mother, a
purely dyadic score of mother and child would be better. Therefore an adapted version
of the traditional model is used: The Purely Dyadic Social Relations Model (PDSRM,
Stas, Cook, & Loeys, In press), which is recently designed. In the current study,
consensus data are obtained during a home visit where two people forming the dyad
strive to give the same response. Two individuals of the same dyad work towards a
consensus score which is called a purely dyadic score. There are several reasons for the
choice of this new model and the use of purely dyadic consensus scores: (a) acts are not
the same as perceptions so a more objective measure is required; (b) consensus data
convey facts and are closer to the truth for all family members compared with meanings
of singular family members; (c) observing dyads is ideal but very time consuming and
expensive, so dyads working towards a consensus accompanied by an objective
observer is assumed to be the second best choice. Within this study, the family effects
on the three different levels are analyzed with this model. The actor effect and partner
effect are now a single individual effect. The relationship effect is comparable to
relationship effects in the traditional SRM. The difference is that only six purely dyadic
relationship effects are obtained instead of 12 directed relationship effects in the
traditional SRM. The family effect is the same as described in the traditional SRM. An
effect can indicate significant variances and means. Considering variances the
individual effect is interpreted as follows: when the effect is significant, it is important
in explaining the observed score and it indicates a difference between families. For
example, hugging or laughing is explained by characteristics of the child. Considering
means, the individual effect says something about how much a family member hugged
or laughed with all other members in general, not directed to one person in specific. For
HUGGING AND LAUGHING WITHIN FAMILIES
26
example, mothers hugged or laughed a lot. Considering variances the relationship effect
says something about how important a certain dyad is in explaining the observed
hugging or laughing score and whether this is different across families. Considering
means, the relationship effect says something about how much a specific dyad hugged
or laughed together. For example, parents reported a high hugging or laughing score
together. This makes a high rate of hugging or laughing behavior specific for the parent
dyad. A significant variance on the family level indicates that family culture is
important in explaining how often dyads hug or laugh together and that this differs
across families. The mean family effect says something about how often families hug or
laugh. It is the mean of all consensus scores.
The first aim of the current study is to investigate the amount of hugging and
laughing and what determines the amount of hugging and laughing of family members
in dyadic family relationships (e.g., characteristics of the individual, a specific
relationship or family culture) in a group of heterosexual families. It is interesting to
disentangle how family members experience hugging and laughing as they are proven
to be so crucial for all individuals’ health and wellbeing. Furthermore, the study
includes bidirectional influences within families on multiple levels and goes beyond the
mother-child dyad by including multiple family relationships. This aim is accomplished
by using the PDSRM. Traditional methods do not incorporate these bidirectional
influences nor different levels and multiple family relationships (Cook, 1994; Cox &
Paley, 2003). Researchers using these traditional methods assume that reports of a
single family member are sufficient to make valuable conclusions on a specific family
dyad or the whole family (Cook, 2012). The Family Systems Theory is used as a
framework to conceptualize hypotheses within this context (Cox & Paley, 1997).
Hypotheses considering the first aim of the study are as follows:
1. Based on previous research within the affective domain (Branje et al., 2002; Cook,
2001; Buist et al., 2004), findings considering the amount of hugging and laughing
behavior are expected to be a combination of characteristics of the family (i.e., family
effect), individual characteristics (i.e., individual effect) and the specific family
relationship (i.e., relationship effect).
a. On the family level, it is expected that the amount of hugging and laughing is
relatively high. This assumption is based on research stating a general warm
HUGGING AND LAUGHING WITHIN FAMILIES
27
climate within families (Manders et al., 2007). It is also expected that the
amount of hugging and laughing behavior will vary across families (i.e., some
families hug or laugh often, other families less often). This assumption is based
on research showing that the family climate explains in part perceptions on
warmth, quality of attachment and emotional support (Buist et al., 2004;
Manders et al., 2007).
b. On the individual level, it is expected that mothers hug and laugh more with all
other family members. The individual effect of mothers is expected to be
important in explaining the amount of hugging and laughing within families
suggesting a variation across families. This assumption is based on research
showing an important role of mothers considering affection as all family
members rate warmth (Manders et al., 2007), and quality of the affectional bond
(Buist et al., 2004) highest for the mother.
c. On the relationship level, it is expected that the amount of hugging is highest
within the parent-dyad. This means that apart from the individual characteristics
of the spouses, hugging and laughing will be higher within this specific
relationship. It is expected that this relationship is important in explaining the
amount of hugging and laughing within families suggesting a variation across
families. Hugging and laughing is expected to be second highest in the parentchild dyad and the lowest amount of hugging is expected within the sibling
dyad. Again, it is expected that the amount of hugging and laughing within these
specific relationships is important in explaining the amount of hugging and
laughing within families and that the amounts within the relationships vary
across families. The assumptions of the specific relationship effects are
supported by research on comfort in depending on others (Cook, 2000), quality
of affectional bonds (Branje et al., 2002) and emotional support (Buist et al.,
2004). Considering the mother-child dyad, a relatively high amount of hugging
and laughing is expected consistent across families (i.e., second highest
compared to the parent-dyad and higher that the father-child dyad). This
assumption comes from research stating that mothers seem to engage more in
personal interactions, physical caretaking and emotional support showing the
HUGGING AND LAUGHING WITHIN FAMILIES
28
influence of gender based parenting expectancies on parenting (Biblarz &
Stacey, 2010b; Moon & Hoffman, 2008).
The second aim of the current study is to focus on same-sex families to (a)
broaden the empirical field on homosexual families and (b) supplement consistent
existing research proposing optimal family outcomes to encounter sexual prejudice. The
current study includes a lesbian family that is highly comparable to heterosexual nuclear
family households considering several components. The lesbian family is a long-lasting
household that was already together during pregnancy and is still together. The couple
bore their children via in vitro insemination and the social mother adopted the children
immediately. The age range of the children fitted the range the study decided to use for
the heterosexual group.
1. Previous research states that mainly there are no differences between different-sex
and same-sex families implying that family members in both households fare well
(Biblarz & Stacey, 2010a; Colombok & Badger, 2010; Fedewa et al., 2014; MacCallum
& Golombok, 2004; Rosenfeld, 2010; Stacey & Biblarz, 2001). Based on this research
it is expected that mainly the same pattern will appear within the lesbian family. As
some research supports that considering affectivity the amount is higher within lesbian
families, it is expected that amounts of hugging and laughing are slightly higher within
the lesbian family (Biblarz & Stacey, 2010a; Bos et al., 2007; Fedewa et al., 2014;
Golombok & Badger 2010; MacCallum & Golombok, 2004).
a. On the family level, it is expected that compared to the heterosexual comparison
group the amount of hugging and laughing will be slightly higher in the samesex family. This assumption is based on previous research suggesting amounts
of affectivity are higher within lesbian families (Biblarz & Stacey, 2010a; Bos et
al., 2007; Fedewa et al., 2014; Golombok & Badger 2010; MacCallum &
Golombok, 2004) and because there are two mothers within the family and
mothers are expected to be important considering the affectivity level within
families (Manders et al., 2007).
b. On the individual level, it is expected that the individual effects of both
biological mother and adoption mother will be higher. This assumption is based
on research showing an important role of mothers considering affection as all
HUGGING AND LAUGHING WITHIN FAMILIES
29
family members rate warmth (Manders et al., 2007), and quality of the
affectional bond (Buist et al., 2004) highest for the mother.
c. On the relationship level, it is expected that hugging and laughing within the
adoption mother-child dyad within the same-sex family is higher than the fatherchild dyad within the heterosexual comparison group. This assumption comes
from research stating that mothers seem to engage more in personal interactions,
physical caretaking and emotional support showing the influence of gender
based parenting expectancies on parenting (Biblarz & Stacey, 2010b; Moon &
Hoffman, 2008).
To investigate these two aims, data will be obtained via a home visit method and
will be analyzed with the Purely Dyadic Social Relation Model.
Method
Participants
For this study 88 regular four-person (two-parent-two-children) families in
Flanders (i.e., Belgium) are recruited (N=88). To be included in the study, families
should consist of (a) two biological parents; (b) at least two children between 11 and 18
years old and (c) the four people participating in the study must all be permanently
living at home. Exclusion criteria are for example, stepfamilies, families with adopted
children, and families with children studying in another city and living at home only
during the weekend. The mean age of the parents was 44.24 (SD = 3.15, range 37-52
year) for the mothers and 46.24 (SD = 3.92, range 37-58 year) for the fathers. Most of
the mothers had a bachelor’s degree (47. 83%) or went to university (25.00%). The
other mothers went to secondary school (16.30%), primary school (2.17%) or indicated
‘other’ (8.70%). Most of the fathers went to university (36.96%) or had a bachelor’s
degree (32.61%). The other fathers went to secondary school (20.65%), primary school
(3.26%) or indicated ‘other’ (6.52%). The sample of older siblings consisted of 44 boys
and 44 girls (mean age 15.88, SD = 1.97, range 11-20). Most of the older children went
to secondary school (89.13%), the others had an indenture (6.52%) or went to primary
school (4.32%). The sample of younger siblings consisted of 42 boys and 46 girls (mean
age 13.21, SD = 1.80). Most of the younger children went to secondary school
(72.83%). The others went to primary school (22.83%), had an indenture (3.26%) or
indicated ‘other’ (1.09).
HUGGING AND LAUGHING WITHIN FAMILIES
30
The same-sex family that is compared with the heterosexual family group
consists of a family with lesbian parents and four children (N=1). The biological mother
is 41 years old and the social mother is 45 years old. The couple is together since 1994
(i.e., 21 years) and both have an academic diploma. The couple gave birth to four
children via artificial insemination by donor. One of the two women went through the
procedure every time so that makes her the biological mother of the four children. From
the time that adoption was legalized in Belgium, the couple started the adoption
procedure so that the social mother (i.e., the second parent) of the couple was able to
adopt the four children. Currently the children are 11, 13, 15 and 16 years old. For the
purpose of this study only two of the children participate so that the family size is the
same as the four-person family standard of the traditional families. The youngest child
that participates is 13 years old, the oldest child is 16 years old and both are female.
Measures
The study takes part within a broader study considering co-activity. Both online
survey and home visits are executed to investigate the research questions. The current
study only implements data obtained by the home visits. The main goal of a visit is to
manage the family in creating a consensus about the amount of hugging or laughing
together. The same answer given by two partners in a dyad serves as a consensus and
objective measurement of this dyad. When applying the PDSRM (i.e., the model
described in the introduction), the objective measurements represent a purely dyadic
score. There are several reasons for the choice of this new model and the use of purely
dyadic consensus scores. This method offers more objective measurements in strictly
dyadic relationships. Online questionnaires offer valuable information about perceptions
but these are subjective and possibly biased. Hugging and laughing are acts so a more
objective measure is required. Consensus data convey facts and are closer to the truth
for all family members compared to meanings of singular family members. The
observation of dyads would be ideal but very time consuming and expensive, so dyads
working towards a consensus accompanied by an objective observer is assumed to be
the second best choice. If there are conflicting opinions between partners in a certain
relationship they could discuss the topic to reach a compromise. In this study, only the
questions about hugging and laughing will be discussed. Questions are formulated in a
dyadic way. Family members should thus logically give the same answer as the other
HUGGING AND LAUGHING WITHIN FAMILIES
31
partner in the dyad (e.g., when one of the children is asked how often he or she hugged
with his or her mother, the mother should give the same answer when you ask her this
question about her child). In general, questions are formulated to gain information about
how often family members usually hug and laugh, perceived over a broader period of
time. For example, ‘How typical is this (e.g., hugging or laughing), how often does this
generally occur with ... (i.e., indicate a score for all other family members)?’. Every
member of the family answers the questions for all the other three participating family
members (i.e., round-robin design described in the introduction). The questions should
be rated on a six-point scale (from 1 = this never happens until 6 = this happens very
often). The structure of the question is important to control for several variables that can
bias the results (e.g., seasons, illness, holidays). By selecting this method, two important
advantages are attained. Firstly, it is possible to investigate dyadic relationships1.
Secondly, hugging and laughing components are measured within and across families.
The questionnaire that is used is the Nonshared Environment in Adolescent
Development (NEAD; Neiderhiser, Reiss, & Hetherington, 2007). This questionnaire is
translated from English to Dutch and retranslated by Lara Stas, Tom Loeys and Bill
Cook. An objective researcher and a native speaker were involved within the translation
process. A pilot study in a subgroup of this study is done and appeared valid.
Cronbach’s alpha for hugging is .83 and for laughing .79.
Procedure
Families are recruited through contacting schools, youth movements and child
minders. Within these organizations an information letter is spread next to oral
explanation. Four master students are responsible to find and contact the families. The
families are asked to participate in the investigation physically but also by telephone or
e-mail. Informed consent has to be confirmed by the participants in the beginning of the
online survey. Data will be used only for scientific research and will be approached with
respect for the participants. To guarantee anonymity of data, all families and family
1
The aim of the study is to investigate strictly dyadic relations who are statistically
analyzed using the Purely Dyadic Social Relations Model (PD SRM, Stas, Cook, &
Loeys, In press).
HUGGING AND LAUGHING WITHIN FAMILIES
32
members are given a code. Participants can quit the investigation at any time. After the
investigation, more information is given about what the goal of the study is and what
will happen with the results. A summary of the research results can be obtained if a
participant requests. When a family confirms to participate, an appointment is made to
plan the home visit. Not too much information is given about the home visit to avoid
negotiation between family members while filling in the online survey. When the
master student visits the families, information is given about the process. Family
members are told that the same questions as in the survey will be asked again and that
they should try to create consensus about their answers. The master student represents
the objective observer and indicates the answer the two partners in a dyad agree with.
To record the conversations of the home visit approval is asked orally. The duration of
the visits is not fixed because of the opportunity to discuss, but approximately it will
take 40 minutes.
Analytic Strategy
Part I: Analyses of the heterosexual families.
PDSRM analyses.
Design and parameter estimates. Analyses are based on the PDSRM. In this
design, two people of the same dyad work towards a consensus score which is called a
purely dyadic score. The model is illustrated in Figure 2.
HUGGING AND LAUGHING WITHIN FAMILIES
33
Figure 2. Boxes represent dyadic measurements, circles latent variables. Parameters that
are fixed are indicated by ‘1’, free parameters by an asterisk. Every indicator is
connected with the corresponding latent variables by an arrow.
In order to measure family relationships on three different levels, the individual
level, relationship level and family level, an SRM analysis is necessary. The effects on
the different levels are components of the PDSRM and are specified as latent variables
in a Confirmatory Factor Analyses (CFA). In a two-parent two-children family, one
family effect, four individual effects and six relationship effects are estimated. In total,
six dyadic measurements will be obtained within one family. The PDSRM components
(i.e., latent variables) are derived from the six observed scores. The observed dyadic
measurements on the different family relationship variables are forced to load on the
latent variables and all factor loadings are fixed to 1. In this way, information about the
amount of variance explained by the different PDSRM effects (i.e., latent variables) can
be obtained (Eichelsheim et al. 2011). Considering the group analyses, variances and
means are estimated via PDSRM with the R package Lavaan (Rosseel, 2012). With this
package, also latent variables and model fit measures can be obtained. Effects consist of
variances and means. The mathematic formula of variance includes a square, therefore
always positive values are obtained. For this reason, double-sided tests for significance
are unnecessary (i.e., values are always positive) and one-way tests are sufficient to
compare the PDSRM model with the variance-covariance matrix of the data. This also
implies that p-values are significant when p < .10 instead of p <. 05. An observed purely
dyadic score is the sum of the PDSRM components and the mathematic formula is
represented in Equation 1.
Xijk = νk + θik + θjk + κijk + εijk
(1)
Xijk represents a purely dyadic score of person i (i.e., the first person in the
dyad) and person j (i.e., the second person in the dyad) of family k, this score is a
dependent variable. This represents a relationship measurement of a certain family on
hugging or laughing between two individuals of the same dyad. The first component in
the equation is νk and represents the group average, which is the family effect. A
significant variance on the family level indicates that family culture is important in
explaining how often dyads hug or laugh together and that this differs across families.
The mean family effect says something about how often families hug or laugh. It is the
HUGGING AND LAUGHING WITHIN FAMILIES
34
mean of all consensus scores. The second component is θik and represents the
individual effect of person i in family k. The third component is θjk and represents the
individual effect of person j in family k. The individual effect indicates how important
characteristics of the individual are in explaining the observed score and it indicates a
difference between families. For example, hugging or laughing is explained by
characteristics of the child. Considering means, the individual effect says something
about how much a family member hugs or laughs with all other family members in
general, not directed to one person in specific. For example, the average mother hugs or
laughs more than average with all other family members. The fourth component is κijk
and represents the relationship effect of person i and person j of the same dyad in family
k. The relationship effect says something about how important a certain dyad is in
explaining the observed hugging or laughing score and whether this is different across
families. Considering means, the relationship effect says something about how much a
specific dyad hugs or laughs together. For example, parents together reported a high
hugging or laughing score apart from their individual scores. This makes a high rate of
hugging or laughing behavior specific for the parent dyad. The last component is εijk
and represents measurement error. In conclusion, via PDSRM analyses one family
effect, four individual effects and six relationship effects are obtained for both hugging
and laughing. These measures are useful to make comparisons with the same-sex family
by means of Z-scores in the second part of the analyses.
The fit of the PDSRM with the data. In order to study family relationships
considering the different SRM components, the model should be adequate and should
fit the data. To assess the fit of PDSRM, a CFA is used. The first step is to specify a
factor structure (i.e., a purely dyadic model with latent variables). This model is
illustrated in Figure 2. where all the dyadic measures (i.e., dependent variables) are
forced to load on the PDSRM components (i.e., independent variables). For example, a
purely dyadic measurement is expected to be explained by the family effect, individual
effect and relationship effect. The second step is to collect the data. The third step is to
estimate the model (i.e., the PDSRM parameters) with SEM software (i.e., Lavaan in
R). The fourth step is to evaluate the fit of the model. The last step is to specify the
model again if necessary. Measures to evaluate model fit are chi-square (χ2); (Kenny,
Kashy, & Cook, 2006), Comparative Fit Index (CFI); (Bentler, 1983), TLI (Tucker-
HUGGING AND LAUGHING WITHIN FAMILIES
35
Lewis Index) and Root Mean Square Error of Approximation (RMSEA); (Steiger,
1998). The chi-square test indicates the difference between the observed and the modelimplied variance-covariance matrix (Hu & Bentler, 1999). When the test is not
significant (p >.05), the model fits the data (Kenny, Kashy, & Cook, 2006). Chi-square
is influenced by sample size and correlations of the model (i.e., worse fit when bigger
correlations). The CFI is less sample size sensitive than chi-square and for the SRM,
CFI should be higher than .90 (Bentler, 1983; Cook, 1994). The standard for the TLI is
also that outcomes should be higher than .90 (Boelen & Van Den Bout, 2005). For the
RMSEA, outcomes should ben lower than .10 and the closer to zero, the better the fit.
Boelen and colleagues (2005) state that RMSEA values lower than .08 indicate an
acceptable fit. Kenny (2011) states that .01 is an excellent fit, .04 is a good fit and .08 is
an acceptable fit. It is suggested to adjust the model when a bad fit is present to decrease
problems with type I error (i.e., probability of falsely rejecting the null hypothesis) and
type II errors (i.e., the probability of falsely accepting the null hypothesis); (Hu &
Bentler, 1999).
Part II: Analyses of the same-sex family and the comparison group.
Z-scores. The comparison group of the same-sex family is the group of
heterosexual families. Via PDSRM analyses one family effect, four individual effects
and six relationship effects are obtained for both hugging and laughing. When scores of
the individual same-sex family are compared with the comparison group, Z-scores can
be calculated. To obtain meaningful measures, PDSRM effects of the single family
must be compared to the same PDSRM factors of the comparison sample (Cook, 2005).
The first step is to calculate the PDSRM components with formulas adapted to the
PDSRM. The second step is to subtract from this score the mean of the comparison
group. This score is then divided by the standard deviation of the comparison group
(i.e., standardizing). Z-scores can only be interpreted for SRM factors with significant
variance in the normative sample (Cook & Kenny, 2004). A Z-score is a measure that
contains information about how a single score compares to the sample mean of the
comparison data. The outcome of this statistical procedure can be interpreted with
reference to standard deviations. When a Z-score reaches two or more above or below
the sample mean, this measure is described as extreme and meaningful (Cook, 2005).
HUGGING AND LAUGHING WITHIN FAMILIES
36
Results
Missing Values
The current study includes consensus data of home visit interviews with 97
families. In three families, not all family members were present during the home visit.
These families were excluded from the analyses. Descriptive values are obtained for 88
two-parent two-children (M = 2.60, SD = .79) families that participated both parts of the
broader study considering co-activity (i.e., online survey and home visit). Apart from
attendance during home visits, the survey data was incomplete in several families.
When one member of the family did not fill in the online survey completely, the family
was excluded. This results in an unequal sample size of the family group for PDSRM
analyses including consensus data and the analysis for descriptive values. All
missingness is assumed to be at random and there are no missing values in the case
family. Missing data is dealt with using Full Information Maximum Likelihood (FIML).
Part I: Analyses of the Heterosexual Families
The fit of the PDSRM with the data.
The fit of the PDSRM with the data: Hugging. The first model fit of the model
for hugging indicates a bad fit: χ2 (10, N = 97) = 52,09, p = .001; CFI = .82; TLI = .72;
RMSEA= .21. Because of the bad fit, post hoc modification indices are examined. The
indices enter changes in the model that lead to a better fit. The change is that to define
the family effect, the loading of the observed score of mother-father is not fixed on 1 in
the SEM (i.e., this loading is freely estimated). The second model has a perfect fit: χ2 (9,
N = 97) = 9,71, p = .375; CFI = 1.00; TLI = 1.00; RMSEA= .03.
The fit of the PDSRM with the data: Laughing. The basic PDSRM model
indicates a bad fit: χ2 (13, N = 97) = 34.76, p = .001; CFI = .92; TLI = .91; RMSEA=
.13. The first problem that occurred is the presence of negative variances of the
individual effects of the father, the youngest child and the oldest child. These are
constrained on zero. The second problem is a bad fit. Only the CFI and TLI indicate an
acceptable fit. After constraining the individual effects the fit is better but still not very
good: χ2 (12, N = 97) = 25.89, p = .011; CFI = .95; TLI = .94; RMSEA= .110. The CFI
and TLI indicate an improvement of the model but χ2 and RMSEA indicate a bad fit.
Modification indices suggest setting the loading of the observed score of youngest
child-oldest child free. This modification does not lead to a notable better fit so the fit
HUGGING AND LAUGHING WITHIN FAMILIES
37
indices of the previous model fit will be used and it is accepted that two fit
measurements indicate a bad fit and two indicate a satisfactory fit.
PDSRM analyses.
The first aim of the current study is to investigate the amount of hugging and
laughing (i.e., means), which components are important in explaining the amount of
hugging and laughing of family members (e.g., characteristics of the individual, a
specific relationship or family culture) and whether there are differences across families
(i.e., variances). This is investigated in dyadic family relationships in a group of
heterosexual families. Findings of the amount of hugging and laughing behavior are
expected to be a combination of characteristics of the family (i.e., family effect),
individual characteristics (i.e., individual effect) and the specific family relationship
(i.e., relationship effect).
PDSRM analyses: Hugging.
Means. All mean effects are significant (p < .001) and are found in Table 1.
Family effect. The family effect indicates a high amount of hugging within
families (M = 5.46, p < .001). The result lies between ‘this happens sometimes’ and
‘this happens often’. This measure is used as a baseline to interpret the other effects, as
it is a measure for the average amount of hugging within families (i.e., mean consensus
score). That is, the individual and relationship effects are expressed in terms of
deviations from the overall family mean.
Individual effect. The individual effect of the mother indicates that the average
mother continuously hugs more frequently with all other members (M = 2.13, p < .001).
The individual effect of fathers also indicates a higher hugging percentage but less high
(M = 1.63, p < .001). The individual effects of the oldest child (M = -2.12, p < .001) and
the youngest child (M = -1.64, p < .001) indicate that on average, children hug less with
all other family members.
Relationship effect. The relationship effect of the mother-father dyad indicates
that apart from the individual effects of both mother and father (i.e., personal
characteristics), they hug more together (M = 1.33, p < .001). This is specific for this
relationship. The relationship effects of the mother-oldest child dyad (M = -.67, p <
.001), the mother-youngest child dyad (M = -.66, p < .001), the father-oldest child dyad
(M = -.66, p < .001), and the father-youngest child dyad (M = -.67, p < .001) indicate
HUGGING AND LAUGHING WITHIN FAMILIES
38
that apart from their individual characteristics they hug less with their specific
relationship partner. The relationship effect of the oldest child-youngest child dyad
indicates that apart from the individual characteristics of both children, they hug more
often together (M = 1.33, p < .001).
Variances. The PDSRM variance estimates are found in Table 1.
Family effect. The family effect indicates that families vary in how often family
members hug with each other i.e., some families hug often, other families less often (V
= .73, p < .001). This means that family culture is important in explaining how often
dyads hug together and that this differs across families.
Individual effect. The individual effects of mother (V = .23, p < .001), father (V=
.28, p < .001) and oldest child (V = .87, p < .001) indicate that characteristics of these
three family members are important in explaining the amount of hugging within
families and that amounts differ across families. For example, in some families mothers
hug often with all other family members and in other families mothers hug less often
with all other family members. The individual effect of the youngest child is not
significant, its amount of hugging is consistent across families and its characteristics do
not explain why people differ in the amount of hugging within families (V = .16, p =
.115).
Relationship effect. The relationship effects of the mother-father dyad (V = .04, p
= .722) and the mother-youngest child dyad (V = .04, p = .62) are not significant. This
means that hugging within these dyads is consistent across families. The dyads do not
account for the difference in the amount of hugging between families. The relationship
effects of the mother-oldest child (V = .26, p = .026), the father-oldest child dyad (V =
.58, p < .001), the father-youngest child dyad (V = .55, p < .001) and the oldest childyoungest child dyad (V = 2.27, p < .001) are significant. This means that the
relationship effects are important in explaining the amount of hugging within families.
For example, the specific relationship between father and the oldest child is important in
explaining the observed amount of hugging and it varies across families.
HUGGING AND LAUGHING WITHIN FAMILIES
39
Table 1.
PDSRM Component Means, PDSRM Raw Variance Estimates for Hugging
PDSRM effects
PDSRM mean
Variance estimate
Family effect
5.46***
.73***
M
2.13***
.23***
F
1.63***
.28***
O
-2.12***
.87***
Y
-1.64***
.16
M-F
1.33***
.04
M-O
-.67***
.26*
M-Y
-.66***
.04
F-O
-.66***
.58***
F-Y
-.67***
.55***
O-Y
1.33***
2.27***
Individual effects
Relationship effects
Significant variances: * p < .10. ** p < .01. *** p < .001
Significant means: * p < .05. ** p < .01. *** p < .001
Note. M = mother; F = father; O = oldest child; Y = youngest child; M-F = mother
father dyad.
PDSRM analyses: Laughing.
Means. The mean PDSRM effects are found in Table 2.
Family effect. The family effect indicates a high amount of laughing within
families (M = 5.40, p < .001). The result lies between ‘this happens sometimes’ and
‘this happens often’. This measure is used as a baseline to interpret the other effects, as
it is a measure for the average amount of laughing within families (i.e., mean consensus
score).
Individual effect. The individual effect of the mother is not significant (M = -.02,
p = 497) but indicates less laughing with all other family members. When a mean effect
is not significant, there is no significant difference with the family effect. The individual
HUGGING AND LAUGHING WITHIN FAMILIES
40
effect of the father indicates that the average father continuously laughs less frequently
with all other family members (M = -.07, p = .015). The individual effect of the oldest
child indicates that on average, the oldest children laugh more than average (M = .07, p
= .008). The individual effect of the youngest child is not significant but indicates more
laughing with all other family members (M = .02, p = .594).
Relationship effect. The relationship effect of the mother-father dyad indicates
that apart from the individual effects of both mother and father (i.e., personal
characteristics), they laugh more together (M = .07, p = .004). This is specific for this
relationship. The relationship effects of the mother-oldest child dyad (M = -.06, p =
.029) and the father-youngest child dyad (M = -.06, p = .029) indicate that apart from
their individual characteristics they laugh less within these specific dyads apart from
their individual characteristics. For example, apart from the individual effects of the
mother and the oldest child, they laugh less in this specific relationship. The
relationship effects of the mother-youngest child dyad (M = -.007, p = .789) and the
father-oldest child dyad (M = -.007, p = .789) are not significant. Both effects indicate
less laughing within the specific relationship apart from individual characteristics. The
relationship effect of the oldest child-youngest child dyad indicates that apart from the
individual characteristics of both children, siblings laugh more often together (M = .07,
p = .004).
Variances. Variance estimates are found in Table 2.
Family effect. The family effect indicates that families vary in how often family
members laugh with each other i.e., some families laugh often, other families less often
(V = .21, p < .001). This means that family culture is important in explaining how often
dyads laugh together and that this differs across families.
Individual effect. The individual effect of the mother is not significant (V = .03,
p = .22). This means that mother’s laughing behavior is consistent across families. This
means that characteristics of the mother do not explain differences in the amount of
laughing within families. The individual effect of the father, the oldest child and the
youngest child are fixed on zero due to negative variances discovered during model fit.
Relationship effect. All relationship effects are significant. This means that the
mother-father dyad (V = .154, p < .001), the mother-oldest child dyad (V = .164, p <
.001), the mother-youngest child dyad (V= .174, p < .001), the father-oldest child dyad
HUGGING AND LAUGHING WITHIN FAMILIES
41
(V = .156, p < .001), the father-youngest child dyad (V = .347, p < .001) and the oldest
child-youngest child dyad (V = .106, p < .001) are all important in explaining the
amount of laughing within families. The amount of laughing within these specific
relationships varies across families.
Equation 1. illustrates the decomposition of the observed purely dyadic
measurements. It indicates that it is possible to analyze what determines the observed
dyadic score. Table 3. presents the observed purely dyadic measurements for hugging
and laughing in the heterosexual family group. For example, the observed purely dyadic
score of the mother-father dyad for laughing is the sum of the family effect, both their
individual effects and their relationship effect (5.38 = 5.4 -.02 - .07 + .07). This
decomposition exists for all observed measures except for the mother-father score of
hugging because the loading of this score is freely estimated (i.e., this was suggested by
modification indices during model fit).
Table 2.
PDSRM Component Means, PDSRM Raw Variance Estimates for Laughing
PDSRM effects
PDSRM mean
Variance estimate
Family effect
5.40***
.21***
M
-.02
.03
F
-.07*
0
O
.07**
0
Y
.02
0
M-F
.07**
.15***
M-O
-.06*
.16***
M-Y
-.007
.17***
F-O
-.007
.16***
F-Y
-.06*
.35***
O-Y
.07**
.11***
Individual effects
Relationship effects
Significant variances: * p < .10. ** p < .01. *** p < .001
Significant means: * p < .05. ** p < .01. *** p < .001
Notes. M = mother; F = father; O = oldest child; Y = youngest child; M-F = mother
HUGGING AND LAUGHING WITHIN FAMILIES
42
father dyad. The individual effects of F, O and Y are constrained to zero.
Table 3.
Observed Purely Dyadic Measurements of Hugging and Laughing
Family dyads
Hugging
Laughing
M-F
5.55
5.38
M-O
4.80
5.39
M-Y
5.30
5.40
F-O
4.33
5.41
F-Y
4.78
5.29
O-Y
3.03
5.55
Notes. The observed measurements are the sum of the PDSRM effects of a dyad within
the family. M = mother; F = father; O = oldest child; Y = youngest child; M-F = Purely
dyadic score of mother and father.
Part II: Analyses of the Same-sex Family and the Comparison Group
The second aim of the current study is to focus on same-sex families to (a)
broaden the empirical field on homosexual families and (b) supplement consistent
existing research proposing optimal family outcomes to encounter sexual prejudice.
Therefore a comparison between a same-sex family and a heterosexual comparison
group is executed by calculating Z-scores.
Z-scores. The outcome of this statistical procedure can be interpreted with
reference to standard deviations. When a Z-score reaches two or more above or below
the sample mean, this measure is described as extreme and meaningful (Cook, 2005).
Only PDSRM components with significant variance in the comparison group are
presented. Z-scores of the PDSRM effects are presented in Table 4. Z-scores for
hugging are interpreted as follows: The same-sex family effect is significantly lower
than the family effect of the heterosexual comparison group (Z = -3.21). This means that
hugging occurs less often within the lesbian family. On the individual level, three
effects are significant. The individual effect of the biological mother (i.e., M1) indicates
that she hugs less often with all other family members compared with the average
mother within the heterosexual comparison group (Z = -5.13). The individual effect of
the adoption mother (i.e., M2) indicates that she hugs less often with all other family
HUGGING AND LAUGHING WITHIN FAMILIES
43
members compared with the average father within the heterosexual comparison group
(Z = -3.43). The individual effect of the oldest child indicates that compared to the older
children within the comparison group, hugging occurs more often with all other family
members (Z = 2.71). On the relationship level, only the relationship effect of the
biological mother-oldest child dyad indicates a meaningful difference with the
comparison group. Their relationship effect indicates that apart from their individual
characteristics, they hug more often together compared with the heterosexual
comparison group (Z = 2.18). The relationship effects of the adoption mother-oldest
child dyad (Z = 1.12), the adoption mother-youngest child dyad (Z = 1.11) and the
oldest child-youngest child dyad (Z = -.91) do not differ significantly from the
comparison group. This is presented by Z-scores that do not go above or below two
standard deviations. The amount of hugging is thus similar between the two types of
families considering these dyads. Z-scores for laughing are interpreted as follows: The
same-sex family effect is not significantly higher or lower than the family effect of the
heterosexual comparison group (Z = -.96). This means that laughing occurs in a similar
amount within the two types of families. Z-scores of the individual effects are not
interpretable because the PDSRM effects for the heterosexual comparison group are not
significant (i.e., it is not a factor that differs families in general). Z-scores of the
relationship effects indicate that laughing does not differ significantly between the
same-sex family and the heterosexual comparison group: biological mother-adoption
mother dyad (Z = -.20), biological mother-oldest child dyad (Z = .19), biological
mother-youngest child dyad (.002), adoption mother-oldest child dyad (Z = .003),
adoption mother-youngest child dyad (Z = .11) and the oldest child-youngest child dyad
(Z = -.23).
HUGGING AND LAUGHING WITHIN FAMILIES
44
Table 4.
Z-scores for Hugging and Laughing
PDSRM effect
Hugging
Laughing
Family effect
-3.21
-.96
Individual effects
M1
-5.13
M2
-3.43
O
2.71
Y
Relationship effects
M1-M2
-.20
M1-O
2.18
M1-Y
.19
.002
M2-O
1.12
.003
M2-Y
1.11
.11
OY
-.91
-.23
Notes. M1 = biological mother; M2 = adoption mother; O = oldest child; Y = youngest
child; M1-M2 = biological mother adoption mother dyad. Only Z-scores for PDSRM
effects with significant variance (p < .10) in the larger sample are reported. Z scores
plus or minus two are in italics.
Discussion and Conclusion
Part I: Hugging and Laughing Within Families Analyzed With a Purely Dyadic
Social Relations Model
The first aim of the current study is to investigate the amount of hugging and
laughing and what determines the amount of hugging and laughing of family members
in dyadic family relationships (e.g., characteristics of the individual, a specific
relationship or family culture) in a group of heterosexual families. It is interesting to
disentangle how family members experience hugging and laughing as they are proven
to be so crucial for all individuals’ health and wellbeing. Furthermore, the study
includes bidirectional influences within families on multiple levels and goes beyond the
HUGGING AND LAUGHING WITHIN FAMILIES
45
mother-child dyad. This aim is accomplished by using the PDSRM with the Family
Systems Theory as a framework to investigate families. An observed purely dyadic
score of two family members within a family is composed of the sum of the three
different PDSRM components (i.e., the family effect, two individual effects and the
relationship effect). In what follows will be discussed how important the components
are in explaining the occurrence of hugging and laughing within families.
Family level. A high amount of hugging and laughing within families is found.
The family climate seems to be important in explaining the amount of hugging and
laughing within families as the amount varies across different families. Some families
thus hug and laugh often while other families hug and laugh less often. This confirms
the hypothesis based on research that studies the family as a whole and suggests a
general warm climate within families (Manders et al., 2007) and now this finding can be
specified for hugging and laughing too.
Individual level. Mothers and fathers seem to hug more often with all other
family members, their personal characteristics are important in explaining the amount of
hugging within families and this varies across families. Considering laughing, although
the individual effect of mothers is not significant, it indicates that mothers laugh less
with all other family members and this is consistent across families. Fathers laugh less
often with all family members. No information on the variation of this effect across
families could be obtained.2 The individual effects of the oldest child and the youngest
child are also different for hugging and laughing. Children seem to hug less often with
all other family members and this varies across families only for the oldest child, which
makes its personal characteristics important in explaining the amount of hugging.
Considering laughing, children seem to laugh more with all other family members, but
the individual effect of the youngest child is not significant. For these two individual
effects, also no variance information obtained. The individual effect of the mother
confirms the hypothesis that mothers are expected to hug more with all other family
members in general and that their characteristics are important in explaining the amount
of hugging within families. This is supported by research stating the important role of
mothers considering affection within families (Buist et al., 2004; Manders et al., 2007).
For laughing, this is not confirmed. It is remarkable that the individual effects show a
2
During model fit, negative variances were constrained to zero. HUGGING AND LAUGHING WITHIN FAMILIES
46
different pattern for hugging and laughing, this was not assumed while formulating the
hypothesis and this indicates that these are distinct processes.
Relationship level. Apart from their individual characteristics, mothers and
fathers hug and laugh more together i.e., particularly more within their specific
relationship. This finding confirms the hypothesis stating that hugging and laughing is
higher between spouses. It also contributes to existing literature on affection within
families that didn’t include hugging and laughing as such, by pointing in the same
direction stating more perceived affection between spouses (Branje et al., 2002; Buist et
al., 2004; Cook, 2000). For hugging, this amount is even consistent across all families.
Laughing between spouses varies across families and is thus important in explaining
how people differ in the amount of laughing within families. The relationship effect of
the mother-oldest child dyad indicates that apart from their individual characteristics,
they hug and laugh less often together and this varies across families. Considering the
mother-youngest child dyad, hugging and laughing occurs less often but for laughing,
this effect is not significant. For hugging this is consistent across families, for laughing
this varies across families. The findings are different from the proposed hypothesis
considering the mother-child dyad. A high occurrence of hugging and laughing within
this dyad was expected. This hypothesis was influenced by gender based parenting
expectancies (Biblarz & Stacey, 2010b; Moon & Hoffman, 2008). A possible
explanation for this finding could be that in the current study, children’s age range is
between 11 and 18 years old and hugging or laughing could be higher between mothers
and younger children. The relationship effect of the father-oldest child dyad indicates
less hugging and laughing within their specific dyad apart from their individual
characteristics. For laughing this is not significant. The relationship effect of the fatheryoungest child dyad indicates less hugging and laughing within this specific
relationship apart from their individual characteristics. Father-child dyads vary across
families, which makes this dyad important in explaining differences in amounts of
hugging and laughing across families. The relationship effects of the parent-child dyads
are similar to the proposed hypothesis. It was expected that hugging and laughing would
occur less often within the parent-child dyad than within the parent-dyad. The sibling
relationship appeared to be different as the proposed hypothesis. Siblings seem to hug
and laugh more often with each other apart from their individual characteristics and this
HUGGING AND LAUGHING WITHIN FAMILIES
47
varies across families. The hypothesis considering the sibling-dyad stated that within
their relationship hugging and laughing would have the lowest occurrence compared to
the other dyads. Research suggested lower perceived affection between siblings (Branje
et al., 2002; Buist et al., 2004; Cook, 2000) but the findings indicate that they hug and
laugh more together, within their specific relationship in particular. The relationship
outcomes of the marital and sibling relationship indicate that within a generation of
equal status hugging and laughing is more frequent. It is important to note that results
considering laughing have to be interpreted with caution because of model fit issues. An
implication following the results is that when hugging or laughing varies across families
and appears to be low, attention should be paid to certain individuals or relationships to
boost these behaviors and therefore improving their wellbeing.
Part II: Heterosexual Families Compared With a Lesbian Family
The second aim of the current study is to focus on same-sex families to (a)
broaden the empirical field on homosexual families and (b) supplement consistent
existing research proposing optimal family outcomes to encounter sexual prejudice.
Within this study a same-sex family is investigated by calculating Z-scores while
comparing the same-sex family with the heterosexual comparison group. Unfortunately
not all PDSRM effects could be calculated due to constraining variances to zero for
model fit and insignificant variances in the heterosexual comparison group. For
hugging, Z-scores of several PDSRM effects indicate a meaningful difference between
the same-sex family and the comparison group (i.e., the family effect, three individual
effects and one relationship effect). On the family level, the amount of hugging
appeared to be lower in the same-sex family. The outcome of this particular same-sex
family is the opposite of what was expected because based on previous research: (a)
amounts of affectivity should be higher within lesbian families (Biblarz & Stacey,
2010a; Bos et al., 2007; Fedewa et al., 2014; Golombok & Badger 2010; MacCallum &
Golombok, 2004) and (b) the same-sex family includes two mothers and mothers are
expected to be important considering the affectivity level within families (Buist et al.,
2004; Manders et al., 2007). Considering the individual level, the biological mother of
the lesbian family (compared with the mother of the comparison group) and the
adoption mother of the lesbian family (compared with the father of the comparison
group) seem to hug less often with all other family members. These findings are
HUGGING AND LAUGHING WITHIN FAMILIES
48
contradictive with the proposed hypothesis. It was expected that both mothers within
the lesbian family would hug more with all other family members in general. This
assumption was based on research indicating the important role of mothers considering
affection within families (Buist et al., 2004; Manders et al., 2007). The oldest child
within the lesbian family hugs more often with all other family members compared with
the average oldest child of the heterosexual comparison group. Considering the
relationship level, more hugging occurs within the biological mother-oldest child dyad
compared with the mother-oldest child dyad of the heterosexual comparison group,
apart from their individual characteristics. The relationship effects of the adoption
mother-oldest child dyad, the adoption mother-youngest child dyad and the sibling dyad
indicate similar amounts of hugging between the two types of families. The proposed
hypothesis considering relationship effects stated that hugging is higher between the
adoption mother-child dyad than between the father-child dyad in the comparison group
but no such effect was found. This assumption comes from research stating that mothers
seem to engage more in personal interactions, physical caretaking and emotional
support showing the influence of gender based parenting expectancies on parenting
(Biblarz & Stacey, 2010b; Moon & Hoffman, 2008). For laughing, Z-scores of family
and relationship PDSRM effects indicate no meaningful difference between the samesex family and the comparison group. Z-scores of individual effects are not interpretable
because the variances of the effects are not significant in the comparison group.
Similar patterns of the PDSRM components as in the heterosexual comparison group
were expected with a slightly higher level of hugging and laughing within the same-sex
family in general. A similar pattern is found for laughing, with no slightly higher
amount of laughing in the same-sex family. At first glance, these findings are not as
optimistic as we expected them to be. Hugging behavior within families is important for
relationships and psychological and physiological wellbeing (Forsell & Aström, 2012;
Gerhardt, 2014; Holt-Lunstad et al., 2008; Light et al., 2005; Ripoll & Casado, 2010). A
low occurrence of hugging could possibly influence wellbeing in a negative manner.
The results encourage elaborating on the study of same-sex parenting. Several
explanations are possible for the results. Future research should explore the topic more
to ensure a decent explanation. Firstly, same-sex families experience stigmatization and
therefore express less affectivity. Several studies show that homophobia and
HUGGING AND LAUGHING WITHIN FAMILIES
49
stigmatization are still present nowadays (Herek, 2006; Patterson, 2000) and this could
lead to lower psychological adjustment within same-sex families (Regnerus, 2012;
Stacey & Biblarz, 2001). Secondly, the main difference between the two family
compositions is parents of the same gender versus parents of different genders. Within
the study findings show that the average father hugs more with all other family
members and fathers hug more within the parent-dyad specifically, apart from
individual characteristics. Within the father-child dyad less hugging occurs. Fathers do
not hug more than mothers, so it doesn’t seem to be a problem of fatherlessness. Gender
alone however could not be the only possible explanation. Thirdly, A negative outlook
is not necessary because hugging in heterosexual families is high. A lower amount of
hugging is therefore not alarming and a decent amount can still be present so it seems
that both families fare well. Additionally, the case family is not a clinical family.
Fourthly, the research method used (i.e., comparing a case family with a comparison
group) within the study is not ideal to compare same-sex families with heterosexual
families.
Limitations
The first limitation considers the questions asked during the home visits. Social
desirability could possibly influence responses considering hugging and laughing as
families want to represent a warm family climate. For other biases that could influence
responses (e.g., season, illness and holiday) is controlled by asking the questions in a
way that family members consider how typical hugging and laughing is within their
family and how often it generally occurs over a broader period of time. The second
limitation considers defining hugging and laughing. It is possible that participants
interpret these processes differently (e.g., laughing can be interpreted as giggling versus
shouting). The observer during the home visit could help participants that asked for a
definition but a generally accepted definition was not yet present. In the introduction of
this study a definition for hugging and laughing is proposed. Executing home visits also
conveys one of the strengths of the study by supplementing questionnaire research in
previous studies. The third issue is that when distinguishing the four family roles (i.e.,
mother, father, youngest child, oldest child) an influence of gender of the children is
overlooked. This influence should be considered in relation to the parents (e.g.,
daughters prefer being hugged more often than sons) and between siblings (e.g., sisters
HUGGING AND LAUGHING WITHIN FAMILIES
50
hug each other more than brothers). The fourth limitation considers the inclusion of
only one same-sex family. This is a problem for external validity. The same-sex family
is highly comparable with the heterosexual comparison group considering several
components. The lesbian family is a long-lasting household (i.e., 21 years) that was
already together during pregnancy and is still together. The couple bore their children
via in vitro insemination and the social mother adopted the children immediately. The
age range of the children fitted the range the study decided to use for the heterosexual
group. Nevertheless, generalizability is still an issue (i.e., we cannot generalize on the
basis of one family). Cheng and Powell (2015) and Marks (2012) reassured an
optimistic view on same-sex parenting by showing that problems in selecting
measurements and models largely impact results. This study did not aim to investigate
the topic with the best existing model but tried to explore the topic, as hugging and
laughing were not yet investigated within same-sex families. Anyway, statistical issues
need to be considered in future research. The fifth limitation also considers the
comparison with the same-sex family. In the current study, Z-scores are calculated for
the comparison of the lesbian family with the heterosexual comparison group. We made
the choice to compare the biological mother of the lesbian family with the mother of the
comparison group and the adoption mother with the father of the comparison group.
This choice relies mainly on the fact that both mothers have in common that they are the
biological mothers within the two types of families. From a certain point of view,
matching dyads in this particular way is random, unsatisfying and groundless. It is
definitely possible that the adoption mother fulfills the role of the mother and the
biological mother the role of the father, or that both mothers fulfill the role of the
mother. It would be interesting to disentangle the comparison of these relationships
considering family roles in future research. Furthermore, it is also recommended to
execute in future research a multigroup comparison with two groups of a decent sample
size including a same-sex family group and a heterosexual group (i.e., is included in the
current study). Lubke and Muthén (2004) present multigroup confirmatory factor
models to make meaningful comparisons and suggest groups of at least 100
participants. This is a decent amount of participants to estimate SRM effects and would
increase generalizability. For example, Eichelsheim and colleagues (2011) performed a
multigroup SRM analysis with structured means to compare family processes between
HUGGING AND LAUGHING WITHIN FAMILIES
51
two types of families. Small sample sizes also make outcomes more vulnerable to the
researcher’s analytical choices (Cheng & Powell, 2015; Regnerus, 2012; Umberson et
al., 2015). When bigger samples are used, comparison group challenges should be
considered (e.g., marital status, families that have been through transitions, long-term
relationships, age of children, scope of outcomes, etc.)
General Conclusion
The current findings extend our understanding of hugging and laughing within
families. We accomplished studying these processes within families with a PDSRM for
the first time in empirical research. The results within the heterosexual family group
indicate that hugging and laughing behaviors have a high occurrence within
heterosexual families. The model offered the opportunity to invest patterns of hugging
and laughing within the family on the family level, individual level and relationship
level. The second part of the study focuses on a same-sex family to broaden the
empirical field on homosexual families. We did not completely accomplish the aim to
supplement consistent research that encounters sexual prejudice. A similar pattern of
hugging and laughing was expected with a slightly higher occurrence within the lesbian
family but results show that hugging occurred less often and laughing occurred in
similar amounts.
HUGGING AND LAUGHING WITHIN FAMILIES
52
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