The Effect of Family Communication Patterns on Adopted Adolescent Adjustment

The Effect of Family Communication Patterns on Adopted
Adolescent Adjustment
Martha A. Rueter and
Department of Family Social Science, 290 McNeal Hall, 1985
Buford Avenue, University of
Minnesota, Saint Paul, MN 55108 ([email protected])
Ascan F. Koerner
Department of Communication Studies, 244 Ford Hall, 224
Church St. S.E., University of Minnesota,
Minneapolis MN 55455
Abstract
Adoption and family communication both affect adolescent
adjustment. We proposed that adoption
status and family communication interact such that adopted
adolescents in families with certain
communication patterns are at greater risk for adjustment
problems. We tested this hypothesis using
a community-based sample of 384 adoptive and 208
nonadoptive families. Adolescents in these
families were, on average, 16 years of age. The results
supported our hypothesis. Adopted adolescents
were at significantly greater risk for adjustment problems
compared to nonadopted adolescents in
families that emphasized conformity orientation without
conversation orientation and in families that
emphasized neither conformity nor conversation orientation.
Adolescents in families emphasizing
conversation orientation were at lower risk for adjustment
problems, regardless of adoption status.

Keywords
adjustment; adolescents; adoption; family communication
patterns
Recent changes in the modern family have led researchers to
pay closer attention to the growing
complexity of family structures, such as step-families, families
formed through assisted
reproduction, and adoptive families. Recent reviews attest to
particular interest in adoptive
families and in adopted child adjustment (cf. Bimmel, Juffer,
van IJzendoorn, & Bakermans-
Kranenburg, 2003; Juffer & van IJzendoorn, 2005; Lee, 2003;
O’Brien & Zamostny, 2003;
van IJ-zendoorn, Juffer, & Klein Poelhuis, 2005). These reviews
compared adopted,
nonadopted, domestically adopted, and internationally adopted
youth on several adjustment
dimensions, including internalizing and externalizing problems,
attachment to parents, and
academic achievement. Overall, these reviews reported that
most adopted children and
adolescents were well adjusted. A small but notable group,
however, experienced significant
behavioral or mental health problems. It is this group that may
account for mean differences
in adjustment that often are observed in studies comparing
adopted to biological children
(Bimmel et al.; Brand & Brinich, 1999).
Differences in adjustment for this small group have generally
been attributed to a number of
factors unique to adopted children. For example, relative to
nonadoptees, adopted children
have more likely experienced early childhood adversity that can

result in developmental delays
Correspondence to: Ascan F. Koerner.
This article was edited by Cheryl Buehler.
NIH Public Access
Author Manuscript
J Marriage Fam. Author manuscript; available in PMC 2009
August 1.
Published in final edited form as:
J Marriage Fam. 2008 August ; 70(3): 715–727.
doi:10.1111/j.1741-3737.2008.00516.x.
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and negatively affect early childhood attachment to parents
(Haugaard & Hazan, 2003). Also,
the identity development process can be particularly challenging
for adopted youth, who may
look and act differently from their parents and siblings and who
may be trying to come to terms
with limited information about their birth parents and cultural
origins (Brodzinsky, Schechter,
& Henig, 1992; Lee, 2003). In regard to mental health
outcomes, there also might be differences
in parental thresholds for making treatment referrals, with
adoptive parents more likely than
nonadoptive parents to refer children for mental health or
behavioral problems (Juffer &
IJzendoorn, 2005).
These factors, however, do not fully explain the adjustment
difficulties observed in some
adopted children. First, they do not apply uniformly to all
adoptive families nor to all adopted
children in the small group with adjustment problems. Second,
the external factors described
above suggest fairly direct cause-effect relationships. Such
simplistic associations are unlikely

to represent the complex causal processes that underlie adopted
children’s adjustment
problems. To better understand adjustment among adopted
children, we need a more thorough
understanding of the complex underlying processes as they
occur in most, if not all, adoptive
families.
Adolescent Adjustment and Family Communication
In general population studies, more than three decades of
research has established a strong
association between parent-child interactions and adolescent
adjustment (Reiss, 2000;
Steinberg, 2001). Research on parent-child communication has
consistently demonstrated that
parent-child interactions characterized by open communication,
warm and supportive
behavior, and firm, consistent enforcement of developmentally
appropriate expectations
positively influence child adjustment. Hostile, angry, and
conflictual interactions, on the other
hand, are associated with poorer adjustment. Various labels
have been employed to describe
these different types of parenting, including Baumrind’s (1971)
authoritarian, authoritative,
permissive, and neglecting parenting, Burleson, Delia, and
Applegate’s (1995) person-versus
position-centered parenting, and Koerner and Fitzpatrick’s
(2002b) conversation orientation
and conformity orientation.
Drawing from this overwhelming evidence, we expect that
parent-child interaction plays a
similarly relevant role in adopted children’s adjustment. We
argue that family interaction is a
proximate influence on child and adolescent adjustment,

regardless of adoption status. Further,
family structure and the factors already identified as associated
with adopted children’s
adjustment are, compared to family interaction, more distal
factors whose impact on adjustment
is moderated by family interaction. That is, adoption and its
correlates define a particular
context that interacts with family interaction processes to
determine child adjustment.
Family Communication Patterns Theory
A theoretical framework that expands upon existing theories
(e.g., Baumrind, 1971; Burleson
et al., 1995; Reiss, 1981) to provide a stronger explanation of
the association between family
interactions and child adjustment in complex families like
adoptive families is Koerner and
Fitzpatrick’s (2002a, 2002b, 2004b, 2006) Family
Communication Patterns Theory (FCPT).
FCPT is based on the fundamental insight that creating a shared
social reality is central to
family functioning. Shared reality exists when family members’
cognitions about an object are
accurate, congruent, and in agreement. Sharing social reality
with others makes understanding
and being understood easier, leading to more efficiency and
coordination and fewer
misunderstandings and conflict. Consequently, families that
share social reality should
communicate with one another more accurately and with less
conflict, supporting child
adjustment.
Rueter and Koerner Page 2

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According to FCP Theory, families create a shared reality
through two processes, conversation
orientation and conformity orientation. Conversation orientation
is characterized by frequent,
spontaneous, unconstrained interactions that allow family
members to codiscover the meaning
of symbols and objects. This orientation encourages all family
members to participate in
defining social reality. Conformity orientation is characterized
by uniformity of beliefs and
attitudes. Family interactions focus on maintaining harmonious
relationships that reflect
obedience to parents, often manifest in pressure to agree and
maintain the family hierarchy.
This orientation allows family members in authority roles (i.e.,
parents) to define social reality.
Theoretically orthogonal, these two orientations define four
family types: consensual,
pluralistic, protective, and laissez-faire. Consensual families are
high in both conformity and
conversation orientation. Communication in consensual families
reflects a tension between
exploring ideas through open communicative exchanges and a
pressure to agree in support of
the existing family hierarchy. Pluralistic families are low in
conformity orientation and high
in conversation orientation. Family communication is
characterized as open and unrestrained,
focusing on producing independent ideas and fostering
communication competence in
children. Protective families are high in conformity orientation
and low in conversation
orientation. Communication in these families functions to
maintain obedience and enforce
family norms; little value is placed on the exchange of ideas or

the development of
communication skills. Laissez-faire families are low in both
conversation orientation and
conformity orientation. Family members do not often engage
each other in conversation, and
they place little value on communication or the maintenance of
a family unit.
Sharing Reality in Complex Families
The concept of a shared reality among family members is not
new. Others describe similar
concepts using similar terms. Reiss (1981) described shared
reality as a family paradigm
guiding how members respond to challenges from the external
world and Eccles et al.
(1993) used stage-environment fit theory to explain the
importance of compatibility between
parental control attempts and adolescents’ growing desire for
autonomy. Deater-Deckard and
Petrill (2004) used dyadic mutuality to describe synchronized,
mutually warm, and responsive
parent-child interactions and Grotevant, Wrobel, van Dulmen,
and McRoy (2001), referring
specifically to adoptive families, used parent-child
compatibility or goodness of fit to refer to
the similarity between parental expectations and actual or
perceived child behavior. The
connection between these conceptualizations of shared reality
and FCP Theory is that in each
case, increased shared reality is expected to relate to improved
family functioning or child
adjustment or both.
Several sources suggest that, compared to genetically related
families, sharing social reality is
likely to be more challenging in adoptive families (Brodzinsky,

Lang, & Smith, 1995; Deater-
Deckard & Petrill, 2004; Grotevant et al., 2001). Among the
possible reasons for the added
challenge is that the cognitive processes involved in perceiving
the social world are at least
partially a function of genetic predispositions. Research
supporting this contention has shown
medium to large effects of genetics on attitudes ranging from
taste for sweets, preferences for
leisure activities, endorsement of moral and ethical positions,
and political attitudes (Alford,
Funk, & Hibbing, 2005; Olson, Vernon, Harris, & Jang, 2001;
Tesser, 1993). Abrahamson,
Baker, and Caspi (2002) have shown that these effects are not
limited to adults. They reported
significant genetic effects on political attitudes in children as
young as 12 years old.
This research suggests that although genetically related family
members can sometimes rely
on similar cognitive processes to achieve a shared reality,
genetically unrelated family
members must rely on other processes. We and others
(Brodzinsky et al., 1995; Grotevant et
al., 2001; Stein & Hoopes, 1985) suggest that how family
members communicate with one
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another is particularly important to creating a shared social
reality among adoptive family
members.
Adoption, Family Communication Patterns, and Child
Adjustment

To date, studies of adoptive family communication mostly have
examined adoption-specific
communication (e.g., parents talking with an adopted child
about his or her adoption;
Brodzinsky, 2006; Wrobel, Kohler, Grotevant, & McRoy, 2003)
or examined the direct effect
of adoption status on family communication. Direct-effect
studies have compared various
aspects of communication (e.g., levels of conflict, amount of
verbal interaction) across adoptive
and nonadoptive families (Lansford, Ceballo, Abby, & Stewart,
2001; Lanz, Ifrate, Rosnati,
& Scabini, 1999; Rosnati, & Marta; 1997). For the most part,
these studies reported few
differences in communication on the basis of adoption status.
In contrast to direct-effect studies, the FCPT suggests that
adoption status and communication
pattern interact to influence child adjustment. On the basis of
research of parent-child
communication in the general population (Baumrind, 1971;
Burleson et al., 1995; Koerner &
Fitzpatrick, 2004; Steinberg, 2001), we expect that family
communication patterns directly
affect child adjustment. On the basis of the greater challenges to
creating a shared reality among
adoptive family members, we also expect that in adoptive
families the effects of family
communication on adjustment will be amplified in specific
ways. The purpose of the current
study, then, was to test the application of the FCP Theory to
explain adolescent adjustment
among adopted adolescents. To accomplish this, we tested a
series of hypotheses:
H1: Adopted children will have more adjustment problems than

nonadopted children.
H2: Adoption status is not associated with a family’s FCP.
H3: FCP is associated with child adjustment.
H3a: Consensual families will experience the fewest, Laissez-
Faire families the most, and Protective and Pluralistic
families a moderate level of child adjustment problems.
H4: Adoption status and FCP interact to influence child
adjustment.
H4a: FCPs that favor conversation orientation (Consensual and
Pluralistic) will have similar levels of adjustment
problems across adoptive and nonadoptive families.
H4b: FCPs that favor control over conversation (Protective) or
use neither orientation (Laissez-Faire) will show more
child adjustment problems in adoptive families relative to
nonadoptive families.
Method
Sample
Participants were 592 families recruited to a longitudinal
research project designed to
investigate sibling influences on adolescent drug and alcohol
use (McGue et al., 2007). All
study families included two parents, the target child (referred to
as the adolescent; M age =
16.01 years, SD = 1.44), and a younger sibling (referred to as
the sibling; M age = 13.69 years,
SD = 1.57) who was within 5 years of the adolescent’s age. In
284 families, both children were
adopted, in 100 families, the adolescent was adopted and the

sibling was biologically related
to the parents, and in 208 families both children were
biologically related to the parents.
Adoptive families were identified through records from three
large adoption agencies (600 and
700 placements each year). Biological families were identified
using state birth records.
Researchers located 90% of the identified adoptive families and
85% of the identified
biological families. Once located, a parent in each family was
interviewed to establish study
eligibility. In addition to the children’s age requirement, study
eligibility was limited to families
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living within driving distance of the research lab and to children
with no physical or mental
handicap that would preclude completing the day-long intake
assessment, and all adopted
children had to have been placed for adoption prior to 2 years of
age (M = 4.7 months, SD =
3.4 months).
Participating were 63% of the eligible adoptive families and
57% of the eligible biological
families. To determine the representativeness of participating
families, a brief phone interview
assessing parents’ education, occupational status, marital status,
and the number of parent-
reported behavioral disorders in the participating children was
administered to 73% of
nonparticipating but eligible families. Results showed that the
study sample is generally

representative of the population of eligible families from which
it was drawn and is not
markedly different from families with parents living with two or
more children in the
metropolitan region where the university is located (McGue et
al., 2007).
Procedures
Participating family members visited the research lab to
complete informed consent forms,
self-report surveys, two 5-minute videotaped family
interactions, and the revised Diagnostic
Interview for Children and Adolescents (DICA-R) (Welner,
Reich, Herjanic, Jung, & Amado,
1987). Self-report surveys were independently completed by
each family member. Among
other things, these surveys assessed adolescent externalizing
behavior and family and
individual demographic characteristics. The videotaped family
interactions were designed to
elicit family interactions, including conversation and control
behaviors. Videotaping took place
in a room decorated to look like a living room or dining room,
with family members seated
around a dining table. Although the video camera was
inconspicuously placed in a bookcase,
family members were aware that they were being videotaped. A
trained interviewer explained
the tasks to the family members, but left the room for
videotaping. For the first task, families
were presented with a novel object, a Rorschach inkblot, and
asked to come to a consensus
about what the inkblot resembled. For the second task, families
were presented with a moral
dilemma (Kohlberg, 1981). In the story, a man whose wife has
been diagnosed with a fatal

disease but cannot afford to buy the only drug that can save her
life. Families were asked to
decide (a) whether the man should steal the drug for his wife
and (b) whether he should also
steal the drug for a stranger in need.
Trained interviewers administered the DICA-R (Welner et al.,
1987) to the adolescents and
their mothers. The DICA-R had been modified to include
additional questions and probes
necessary for complete coverage of DSM-IV childhood
disorders. Adolescents’ symptoms
were reported by themselves and by their mothers. All interview
data were reviewed by at least
two individuals with advanced clinical training who were blind
to other family members’
symptoms and diagnoses. These reviewers coded every symptom
and diagnostic criterion. A
symptom was considered present if either the adolescent or the
mother reported it. Kappa co-
efficients for disorders are as follows: Attention deficit
hyperactivity disorder (ADHD, .77),
Conduct Disorder (CD, .80), and Oppositional Defiant Disorder
(ODD, .73).
During their visit, the adolescents also nominated teachers to
provide information about the
child’s behavior at school. Nominated teachers were mailed a
rating form, and teacher reports
were received for 69% of the adolescents. Participants were
compensated for their travel
expenses and given a modest honorarium as compensation for
their time.
Measures
FCP—A family’s communication pattern is determined by

observing the extent to which the
family relies on conversation orientation and conformity
orientation to create a shared reality.
We used Latent Class Analysis to estimate each family’s most
likely communication pattern
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(see Analysis Plan, below). The measures used to assess
conversation orientation and
conformity orientation, which are described below, were used as
indicators of a FCP latent
factor.
Trained observers viewed the two family interaction tasks and
globally rated 12 family
interaction characteristics using the Sibling Interaction and
Behavior Study Rating Scales,
adapted from the Iowa Family Interaction Rating Scales (Melby
et al., 1998). Each family
member’s behavior toward each of the other family members
was rated using a scale ranging
from 1 (not at all characteristic of the person) to 9 (mainly
characteristic of the person). Before
viewing study videotapes, observers received 100 hours of
training and were required to pass
written and observation examinations. Trained observers
attended biweekly coder meetings
for ongoing training and to prevent “rater drift.” Observer
reliability was assessed by randomly
assigning 25% of all tapes to be rated by a second observer, and
then comparing the primary
and secondary ratings using intraclass correlations (Shrout &
Fleiss, 1979; Suen & Ary,
1989). Intraclass correlations for scales used in this study

ranged from .5 to .8, a level of
reliability considered acceptable for these types of data (Kenny,
1991; Mitchell, 1979).
The present study used three observational scales to assess
conversation orientation,
Communication, Listening, and Warmth. Because observers
rated a family member’s behavior
toward each of the other three family members, every family
member received three scores for
each scale. For example, using the Communication scale,
observers rated the mother’s ability
to clearly and appropriately express her own point of view,
needs, and desires when speaking
to the father, to the adolescent, and to the sibling. Family
members who expressed their views
in a manner that encouraged conversation with other family
members received higher scores
than those who did not. The Listening scale assessed the extent
to which a family member
verbally or nonverbally or both verbally and nonverbally
attended to each of the other family
members when the other member was speaking. Here again,
each family member received
three Listening scores. The Warmth scale assessed each family
member’s verbal and nonverbal
expressions of caring, concern, and support toward each of the
other family members, for a
total of three Warmth ratings per family member. The Control
scale was used to assess
conformity orientation. This scale measured the extent to which
a family member attempted
or succeeded in controlling or influencing the attitudes,
behavior, and interactions of other
family members.

Adolescent externalizing behavior—Adolescent adjustment
problems were
operationalized as externalizing behavior in a variety of
contexts including general
delinquency, symptoms of behavioral disorders, conflictual
relations with parents, and trouble
at school. To obtain this broad assessment of adolescent
externalizing behavior, we used five
measures derived from multiple information that were combined
as a latent factor with five
indicators. Because we were primarily interested in the small
subset of adolescents who
experience significant adjustment problems as compared to
adolescents who experience
relatively few problems, we used Latent Class Analysis (see
Analysis Plan) to identify two
groups differing in externalizing characteristics.
For the first indicator, we used the Delinquent Behavior
Inventory (DBI; Gibson, 1967). This
self-report questionnaire contains a list of 36 behaviors. For
each behavior, adolescents
reported if they had never (1), once (2), or more than once (3)
engaged in the behavior. Example
DBI items included “smashing, slashing, or damaging things,”
“cutting classes at school,”
“stealing things,” and “using any kind of weapon in a fight.”
DBI responses were summed to
create a self-report externalizing behavior measure (α = .89).
Symptom counts obtained from the ADHD, CD, and ODD
sections of the DICA-R (Welner
et al., 1987) were used to create an externalizing symptoms
measure (range = 0 – 28 symptoms).

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As described above, adolescents and mothers completed the
DICA-R. A symptom was
considered present if either the adolescent or the mother
reported it.
Trained observers rated adolescent behavior toward each parent,
as described above, to create
the third and fourth externalizing behavior measures. Using the
hostility scale, observers
assessed the extent to which the adolescent’s behavior toward
the mother and toward the father
was characterized by conflict, anger, defiance, and contempt.
Teacher ratings of adolescent in-class behavior were used to
create the final externalizing
measure. Using a 67-item behavior checklist adapted from the
Conners’ Teacher Rating Scale
(Conners, 1969) and the Rutter Child Scale B (Rutter, 1967),
teachers compared the adolescent
to the average student and rated how characteristic a behavior
was of the adolescent (1 = not
at all characteristic to 4 = very much characteristic). Example
checklist items included “is
defiant,” “has difficulty concentrating on school-work,” “is
often truant,” “initiates physical
fights,” and “obeys the rules” (reverse coded). Responses were
summed (α = .97, Spearman-
Brown interteacher reliability = .82).
Analysis Plan
Testing our study hypotheses required that we develop two
categorical latent variables, the
FCP variable and the Adolescent Externalizing Behavior
variable, and examine associations

between these two variables and adoption status. Both
categorical latent variables were created
through Latent Class Analysis (LCA) performed using the
statistical program Mplus 4.21
(Muthén & Muthén, 1998 – 2006).
The FCP LCA model was created using a second-order latent
factor structure. A set of 16 first-
order latent factors, each with three indicators, served as
indicators of the second order FCP
latent factor. The 16 first-order latent factors assessed each
family members’ interaction with
the three other family members for the three conversation
orientation measures and the one
control orientation measure (4 family members × 4 measures).
For example, the mother’s
Communication factor assessed her communication to the other
family members and was
indicated by the observer ratings of her communication to the
father, to the adolescent, and to
the sibling. The adolescent’s and the sibling’s gender were
entered as covariates of the FCP
latent factor.
The adolescent’s Externalizing Behavior latent factor had five
observed variables as indicators:
(1) self-reported delinquency, (2) externalizing disorder
symptoms, (3) observed hostility to
the mother, (4) observed hostility to the father, and (5) teacher
ratings. The adolescent’s age
and gender were entered as covariates of the Externalizing
Behavior latent factor.
We had hypothesized the presence of four FCP and two
Externalizing Behavior classes. To be
confident that these were the most likely number of classes, we

tested LCA models that had
fewer and more classes than the hypothesized number. Because
no single criterion is yet
accepted for deciding the most likely number of classes within a
population, we used a
combination of theoretical and statistical criteria. First, we
relied upon theory to provide the
starting point for our model tests. Thus, to create the FCP
variable, we tested models specifying
one, two, three, four, and five classes. For the Externalizing
Behavior variable, we tested one,
two, and three classes. Statistical criteria included the Bayesian
information criterion (BIC;
Hagenaars & McCutcheon, 2002) and the Lo-Mendell-Rubin
adjusted LRT (LMR; Lo,
Mendell, & Rubin, 2001). The BIC is a measure of model fit
based on the −2 log likelihood
statistic with a penalty for small samples and increasing
parameters. A large decrease in the
BIC value when the number of classes is increased indicates an
improved fit for the model
specifying the additional class. The LMR tests the null
hypothesis that reverting to a model
with one less class than specified would improve model fit. A
statistically significant LMR
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suggests that this hypothesis can be rejected and that the model
being tested produced a
significant improvement in model fit relative to a model with
one less class. We also considered
class sizes and model convergence. Models that produced
classes with few or no members or
that did not converge were rejected.

For each of our study hypotheses, we estimated the probability
that an adolescent would be
placed in the high externalizing subgroup on the basis of family
communication patterns or
adoption status or both. All probabilities were calculated as
posterior probabilities, and all
analytical models were run as mixture models using Mplus 4.21
(Muthén & Muthén, 1998 –
2006). The following provides a description of how we tested
each of the study hypotheses.
Testing H1 required that we regress the two-class Externalizing
Behavior latent variable on
adoption status and two covariates, adolescent’s age and sex
using logistic regression. H1
would be supported if adopted adolescents had significantly
greater odds of being placed in
the high externalizing subgroup relative to nonadopted
adolescents.
To test H2, we estimated the proportion of adoptive and
nonadoptive families for each FCP
class and statistically compared the adoptive and nonadoptive
pairs of proportions using
Fisher’s exact tests. H2 would be supported if the tests showed
that adoptive and nonadoptive
families were distributed similarly across family communication
patterns. Additionally, we
regressed the FCP latent variable on adoption status and two
covariates, adolescent and sibling
gender, using multinomial logistic regression with the Laissez
Faire family communication
pattern as the reference group. H2 would be supported by this
test if adoptive and nonadoptive
families had even odds of placement within each family

communication pattern.
Testing H3 required that we estimate the proportion of
adolescents in the high versus the low
externalizing subgroups for each family communication pattern.
Proportions were compared
statistically using Chi Square and Fisher’s exact test. H3 would
be supported if Consensual
families had the smallest proportion of adolescents placed
within the high externalizing
subgroup, the Protective and Pluralistic families had similar,
midlevel proportions, and the
Laissez Faire families had the largest proportion of adolescents
placed in the high externalizing
subgroup.
To test H4, we estimated the models used to test H3 two more
times, once using the sample of
adoptive families and a second time using the sample of
nonadoptive families. Thus, we
obtained the proportion of adopted and nonadopted adolescents
estimated to be in the high
externalizing subgroup for each family communication pattern.
Proportions were statistically
compared using Fisher’s exact test. H4 would be supported if
adoptive Laissez Faire and
Protective families had significantly higher proportions than
nonadoptive Laissez Faire and
Protective families and adoptive and nonadoptive Consensual
and Pluralistic families had
similar proportions.
Missing Values Analyses
Data from 592 families were available for these analyses, 318 of
which had complete data on
all study variables. Almost all missing data were due to missing

teacher reports or fathers who
did not participate in the observation tasks. As noted above,
31% of the teacher externalizing
behavior ratings were missing. Also, in 23% of the families,
fathers did not participate in the
observational tasks. All other study variables had no more than
3% missing data.
Current research indicates that when missing data are unrelated
to the study outcome (i.e.,
missing at random), recovering missing data using a reliable
estimation procedure is preferable
to case deletion (Schafer & Graham, 2002). For each
externalizing behavior measure, we
compared mean values for adolescents whose father did and did
not participate in the
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observational tasks or who did and did not have teacher report
data. T test results showed no
statistically significant differences on the basis of father
participation. Adolescents without
teacher report data, however, did report significantly higher
externalizing behavior (t = 3.14,
p = .002) and externalizing symptoms (t = 4.15, p < .00). To
examine the possibility that our
results could be biased by missing data, we tested each study
hypothesis with and without
listwise deletion of missing data. For every hypothesis, the
pattern of findings was similar,
although the smaller sample produced fewer statistically
significant results.
Mplus handles missing data by adjusting model parameter

estimates using full-information
maximum-likelihood estimation (FIML; Muthén & Shedden,
1999; Schafer & Graham,
2002). To obtain reliable estimates, Mplus requires that the
proportion of available data for
each study variable and between each pair of variables be at
least .10. These proportions were
all above .53 and the majority were above .97. Therefore, we
used the FIML option to deal
with missing data.
Results
Estimating FCP Classes and Externalizing Behavior Classes
LCA results produced the strongest support for the four-class
FCP model. The pattern of decline
in the BIC statistic supported the four-class model over either
the three- or five-class model.
The class sizes estimated by the four-class model (Consensual =
6.7%, Pluralistic = 31.8%,
Protective = 21.9%, Laissez Faire = 39.6%) were the most
evenly distributed of all models
tested, and most importantly, the patterns of family behavior
estimated by the four-class model
varied in theoretically expected ways. We rejected the five-class
LCA model because it
estimated a class containing just 1% of the families and
produced a relatively small drop in the
BIC (four- to five-class BIC change = 68.02) and a statistically
insignificant LMR (LMR =
182.85, p = .14). The two-class model was also rejected because
the relative decrease in the
BIC statistic from the one- to the two-class model (BIC change
= 1441.21) and the LMR statistic
(LMR = 952.55, p = .008) supported the presence of more than
two classes. The three-class

model produced a good fit (two-to three-class BIC change =
258.94, LMR = 376.76, p = .002).
But three problems with this model led us to reject it. First, the
mean family behaviors produced
by this model showed few interpretable patterns. Second, the
model produced an uneven class
distribution of two quite large classes and one small class.
Finally, the BIC declines
substantially from the three- to the four-class model (three- to
four-class BIC change = 122.69),
suggesting the possibility of a fourth class.
Evidence of the extent to which the four-class model estimated
the expected family
communication patterns is presented in Figure 1. Each bar in
Figure 1 represents one family
member’s mean factor score. The first bar in every set depicts
the mother’s mean factor score.
Thus, the left-most white bar represents the Control factor score
mean of .38 estimated for
mothers placed within the Protective family communication
pattern. The second bar in every
set depicts the father’s mean. The third bar is the adolescent’s
mean, and final bar in every set
is the sibling’s mean factor score. (Standard errors and t values
for the scores presented in
Figure 1 are available upon request from the first author.)
As shown in Figure 1, Consensual families had two parents who
were relatively high on control
behavior and all family members tended to engage in high levels
of communication, listening,
and warmth. No one in the typical Pluralistic family showed
high control, and members
engaged in moderate levels of communication and listening and
relatively little warmth.

Protective families had one controlling parent and engaged in
relatively little communication
and moderate levels of listening and warmth. Finally, Laissez-
Faire families consistently
engaged in the lowest levels of all measured behaviors.
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LCA estimation of adolescent externalizing behavior subgroups
showed that a two-class model
fit the data best (one-class BIC = 15709.66, two-class BIC =
12610.97, three-class BIC =
12454.54; two-class LMR = 529.37, p < .00, three-class LMR =
240.15, p = .17). The two-class
model placed 79.9% of the adolescents in the low externalizing
behavior subgroup and 20.1%
in the high externalizing subgroup.
Hypothesis Testing
Logistic regression results showed that adopted adolescents
were more likely to be placed in
the high externalizing subgroup relative to nonadopted
adolescents (odds ratio (OR) = 3.21,
95% Confidence Interval (CI) = 1.75 – 5.90), supporting H1.
Adolescents’ gender and age also
predicted externalizing subgroup placement. Boys (OR = 5.68,
CI = 3.07 – 10.51) and older
adolescents (β = 0.320, CI = 0.15 – 0.49) were most likely to be
placed in the high externalizing
subgroup.
Proportions of adoptive and nonadoptive families within each
FCP were quite similar
(Consensual: adoptive = 6.7%, nonadoptive = 3.8%; Pluralistic:
adoptive = 31.3%, nonadoptive

= 30.0%; Protective: adoptive = 20.5%, nonadoptive = 26.0%;
Laissez Faire: adoptive = 41.1%,
nonadoptive = 40.4%), supporting H2. Statistical comparisons
using Fisher’s Exact tests found
no statistically significant differences between the proportions
of adoptive and nonadoptive
families within each FCP. Also, multinomial logistic regression
results using Laissez-Faire as
the comparison showed that adoptive and nonadoptive families
had even odds of placement in
each family communication pattern (Consensual OR = 1.64,
95% CI = 0.70 – 3.84; Pluralistic
OR = 1.07, 95% CI = 0.66 – 1.72: Protective OR = 0.76, 95% CI
= 0.46 – 1.25).
Across family communication patterns, proportions of
adolescents in the high externalizing
subgroup supported H3 (Consensual = 1.1, Pluralistic = 16.0,
Protective = 13.4, Laissez Faire
= 21.3; χ2 = 150.76, p < .01). Fisher Exact tests showed that the
proportion of high externalizing
adolescents estimated for Laissez-Faire families was
significantly larger than the proportion
for Pluralistic families (p = .04). The was no difference in
proportions for Pluralistic and
Protective families (p = .11). Small cell size (only one
Consensual family adolescent was placed
in the high externalizing subgroup) precluded comparing
Protective and Consensual families.
Proportions of adopted and nonadopted adolescents within each
FCP in the high externalizing
subgroup followed the expected pattern (Consensual: adoptive =
2.6%, nonadoptive = 0.0%;
Pluralistic: adoptive = 16.7%, nonadoptive = 12.3%; Protective:
adoptive = 18.5%,

nonadoptive = 4.1%; Laissez Faire: adoptive = 26.9%,
nonadoptive = 7.8%), supporting H4.
The nearly 5:1 difference in proportions for adoptive and
nonadoptive adolescents in Protective
families was statistically significant (p = .047), as was the 3:1
ratio for Laissez Faire (p = .005).
Proportions of adoptive and nonadoptive adolescents in
Pluralistic families were similar (p = .
36). Small cell size precluded comparing proportions in
Consensual families.
Discussion
On the basis of what is known about associations between
family communication and
adolescent adjustment from existing studies (Steinberg, 2001),
much of what we report here
is not unexpected. Our goal, however, was to apply the FCP
Theory, which suggests that
creating shared social reality among family members plays a
central role in adolescent
adjustment, to furthering our understanding of adopted
adolescent adjustment. Our results
support the FCP Theory and indicate that existing theories
based largely on families with
genetically related parents and children may not completely
apply to complex families, like
adoptive families.
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As others have reported, we found that adoption status is
associated with adolescent adjustment
(Bimmel et al., 2003; Juffer & van IJzendoorn, 2005; Keyes,
Sharma, Elkins, Iacono, McGue,
2007; Lee, 2003; O’Brien & Zamostny, 2003; van IJzendoorn et

al., 2005). We also replicated
early research showing that family communication patterns
directly relate to adolescent
adjustment such that children in families that emphasized a
combination of conversation and
conformity were least likely to have adjustment problems
(Steinberg, 2001). Our findings go
beyond previous work to show that adoption status and family
communication patterns interact
in important ways and better explain adopted adolescent
adjustment. Specifically, adoptive
families that emphasized conformity over conversation
orientation (i.e., protective families)
or that used neither conformity nor conversation orientation
(i.e., laissez-faire families) either
failed to mitigate the risks of adoption associated with
adolescent adjustment or even amplified
them. Adoptive families high in conversation orientation (i.e.,
consensual and pluralistic
families) appeared to mitigate those risks to the extent that their
risk for child adjustment
problems was statistically undifferentiated from nonadoptive
families.
This does not mean that conversation orientation is universally
positive for adolescent
outcomes. Our results demonstrate that communication without
control from parents leads to
poor child adjustment, regardless of adoption status. We
estimated that 16.7% of adopted
adolescent and 12.3% of nonadopted adolescents stemming from
Pluralistic families were in
the externalizing group, which for nonadopted adolescents was
the highest proportion. Only
when conversation orientation was paired with parental control
in the form of conformity

orientation was conversation orientation associated with
superior outcomes.
Family communication patterns that placed adoptive families at
particular risk for adolescent
adjustment problems were the Protective and Laissez-Faire
types. It is no surprise that these
communication patterns are associated with adolescent
adjustment problems. What we report
that is new is that adoption status and family communication
patterns interact such that adopted
children in these families were at substantially greater risk for
adjustment problems relative to
nonadopted children. In fact, more than a quarter of adopted
adolescents in Laissez-Faire
families fell into the high externalizing subgroup compared to
only 8% of the nonadopted
adolescents. This suggests that adopted children may be much
more sensitive to the parental
indifference and neglect typical of Laissez-Faire families than
nonadopted children. We also
found that controlling parenting without communication is much
more detrimental to adopted
children than to nonadopted children. Adopted children in
Protective families were at almost
five times the risk of being placed in the high externalizing
group compared to nonadopted
children in Protective families.
Theory-Based Explanation of Results
We proposed that the interaction between adoption status and
family communication pattern
occurs because adoptive families face more challenges to
creating a shared reality than
nonadoptive families. According to FCP Theory, the existence
of a shared reality means more

accurate communication and fewer misunderstandings and
conflict, reducing the risk of child
adjustment problems (Koerner & Fitzpatrick, 2004, 2006).
Genetically related family members
likely share a sense of belonging based on physical appearance,
blood ties, and shared social
attitudes or cognitions based in genetic inheritance
(Abrahamson et al., 2002; Alford et al.,
2005; Olson et al., 2001; Tesser, 1993). All these shared
characteristics facilitate their ability
to create a shared reality, even in the absence of conversation.
Adoptive families typically do
not share these advantages.
In Protective families, where the parent(s) dictate the social
reality, we speculate that
nonadopted adolescents likely share at least some of their
parents’ cognitions. Therefore, they
might accept their parents’ regulatory messages, even if they
are offered without much
opportunity for discussion. Adopted adolescents probably have
cognitive processes that differ
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from their parents. Therefore, adopted adolescents in Protective
families may find their parents’
regulatory messages more difficult to accept. As a result, they
are either less compliant or more
likely to experience negative psychological consequences from
their interactions with their
parents, which are expressed in externalizing behaviors.
In Laissez-Faire families, where social reality is neither
dictated nor discussed, rebellion

against parental authority might play a lesser role in putting
adopted adolescents at increased
risk. The salient factor in Laissez-Faire families is the absence
of shared reality. We propose
that challenges to developing a sense of identity faced by
adopted adolescents (Bimmel et al.,
2003; Grotevant et al., 2001) are exacerbated in the absence of a
shared reality. For adopted
adolescents, questions about “who am I” can be complicated by
limited information about birth
parents and differences between themselves and adoptive family
members. In nonadoptive
Laissez-Faire families, genetically based similarities afford at
least a minimal sense of shared
reality, providing a foundation from which to answer questions
about one’s identity.
Limitations and Future Directions
Although they are based on theory, these arguments are yet to
be fully tested. For example, we
theorize that similarities among family members based on
genetic relatedness is the most likely
explanation for the interaction between adoption status and
family communication pattern. We
did not, however, measure cognitive processes. Conducting
research that directly assesses how
family members perceive their environments, and in particular,
how children perceive their
parents’ regulatory messages will be an important next step in
our research program. Also, this
study used cross-sectional data. Therefore, it is possible that the
observed family
communication patterns developed in response to or in
coincidence with child adjustment
problems. Future, longitudinal tests of this theory are needed to
understand better the complex

processes proposed here.
Methodological strengths include using innovative methods for
studying adoptive families and
their communication. For example, this is the first study we
know of that used observational
data and latent cluster analysis to determining family
communication patterns, as identified by
the FCP Theory. All previous studies have used self-reports
only (Koerner & Fitzpatrick,
2004, 2006). Also, rather than using mean adjustment scores to
assess adolescent adjustment,
we took serious the often repeated claim that only a small group
of adopted children experiences
adjustment problems and focused on predicting membership in
that subgroup.
There are limits to the generalizability of this study’s findings.
For example, we focused on
families with adolescent children. Family communication
patterns may operate differently
among families with younger or older children. As noted above,
longitudinal investigations
are needed. Also, as is characteristic of adoptive families, the
families in our sample were more
educated and had higher incomes than the general population.
They also were from the
Midwestern United States and the parents were predominantly
Caucasian with European
ancestry. Future studies that include, for example, stepfamilies
will need to test the
generalizability of our findings to families with more varied
socioeconomic, regional, ethnic,
and racial backgrounds.
To our knowledge, this is the first study to demonstrate an

interaction between adoption status
and family communication patterns. According to our theory,
this interaction occurs as a
function of parent-child genetic relatedness. This study is just a
first step in fully testing this
theory. If replicated through future studies, however, our
theoretical model could also apply
to other complex families in which parents and children are
genetically unrelated such as step-
or blended families and families formed through assisted
reproduction. Thus, this study
represents an initial step in what could potentially be a much
wider field of study.
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Acknowledgments
This research was supported by grants from the National
Institute on Alcohol Abuse and Alcoholism (AA11886) and
the National Institute on Mental Health (MH066140).
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Figure 1.
Graphical Presentation of Mean Factor Scores for the First-
Order Factor Indicators of the
Family Communication Patterns Latent Variable.
Note: First bar in every set: mother’s mean factor score. Second
bar: father’s mean factor score.
Third bar: adolescent’s mean factor score. Fourth bar: sibling’s
mean factor score. Bars rising
above 0 represent behavior levels above the overall mean. Bars
falling below 0 represent
behavior levels below the overall mean.
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COMS 203 – Communication and Everyday Life
Rubric for Literature Review
Criteria and Qualities
Low
Middle
High
Introducing the idea:

Problem statement
Neither implicit nor explicit reference is made to the topic or
purpose of the paper. No rationale discussed, missing thesis,
missing preview.
Readers are aware of the overall problem, challenge, or topic of
the paper. Vague rationale, thesis and preview.
The topic is introduced, and groundwork is laid as to the
direction of the paper. Rationale discussed, clear thesis and
preview.
Body:
Flow of the review
The body appears to have no direction, with subtopics appearing
disjointed.
There is a basic flow from one section to the next, but not all
sections or paragraphs follow in a natural or logical order.
The body is well organized with ideas building from general to
specific conclusions or is arranged topically. Transitions tie
sections and adjacent paragraphs together. Section headers are
used throughout.
Coverage of content
Major sections of pertinent content have been omitted or greatly
run-on. The topic is of little significance to everyday
communication.
All major sections of the pertinent content are included, but not
covered in as much depth, or as explicit, as expected.
Significance to everyday communication is questionable.
The appropriate content in consideration is covered in depth
without being redundant. Sources are cited when specific
statements are made. Significance to everyday communication is
evident.
Proposal of future study
A research question or hypothesis is provided but there is no
reference to why this study is needed.
The limitations of the existing research are addressed and
inform the research question or hypothesis proposed.
The limitations of the existing research are addressed and

inform the research question or hypothesis proposed. In
addition, it is suggested how answering this question or testing
this hypothesis will add to the entire body of literature on this
topic.
Clarity of writing and writing technique
It is hard to know what the writer is trying to express. Writing
is convoluted. Misspelled words, incorrect grammar, and
improper punctuation are evident.
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Varying Definitions of Online Communication and
Their Effects on Relationship Research
Elizabeth L. Angeli

State University
Author Note
Elizabeth L. Angeli, Department of Psychology, State
University.
Elizabeth Angeli is now at Department of English, Purdue
University.
This research was supported in part by a grant from the Sample
Grant
Program.
Correspondence concerning this article should be addressed to
Elizabeth
Angeli, Department of English, Purdue University, West
Lafayette, IN 55555.
Contact: [email protected]
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Running head: VARYING DEFINITIONS OF ONLINE
COMMUNICATION 1
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provides contact
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mail)

VARYING DEFINITIONS OF ONLINE COMMUNICATION
2
Abstract
This paper explores four published articles that report on results
from research conducted
on online (Internet) and offline (non-Internet) relationships and
their relationship to
computer-mediated communication (CMC). The articles,
however, vary in their
definitions and uses of CMC. Butler and Kraut (2002) suggest
that face-to-face (FtF)
interactions are more effective than CMC, defined and used as
“email,” in creating
feelings of closeness or intimacy. Other articles define CMC
differently and, therefore,
offer different results. This paper examines Cummings, Butler,
and Kraut’s (2002)
research in relation to three other research articles to suggest
that all forms of CMC
should be studied in order to fully understand how CMC
influences online and offline

relationships.
Keywords: computer-mediated communication, face-to-face
communication
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3
Varying Definitions of Online Communication and
Their Effects on Relationship Research
Numerous studies have been conducted on various facets of

Internet relationships,
focusing on the levels of intimacy, closeness, different
communication modalities, and
the frequency of use of computer-mediated communication
(CMC). However,
contradictory results are suggested within this research because
only certain aspects of
CMC are investigated, for example, email only. Cummings,
Butler, and Kraut (2002)
suggest that face-to-face (FtF) interactions are more effective
than CMC (read: email) in
creating feelings of closeness or intimacy, while other studies
suggest the opposite. To
understand how both online (Internet) and offline (non-Internet)
relationships are affected
by CMC, all forms of CMC should be studied. This paper
examines Cummings et al.’s
research against other CMC research to propose that additional
research be conducted to
better understand how online communication affects
relationships.
Literature Review
In Cummings et al.’s (2002) summary article reviewing three
empirical studies on

online social relationships, it was found that CMC, especially
email, was less effective
than FtF contact in creating and maintaining close social
relationships. Two of the three
reviewed studies focusing on communication in non-Internet
and Internet relationships
mediated by FtF, phone, or email modalities found that the
frequency of each modality’s
use was significantly linked to the strength of the particular
relationship (Cummings et
al., 2002). The strength of the relationship was predicted best
by FtF and phone
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4
communication, as participants rated email as an inferior means
of maintaining personal
relationships as compared to FtF and phone contacts (Cummings
et al., 2002).
Cummings et al. (2002) reviewed an additional study conducted
in 1999 by the
HomeNet project (see Appendix A for more information on the
HomeNet project). In
this project, Kraut, Mukhopadhyay, Szczypula, Kiesler, and
Scherlis (1999) compared
the value of using CMC and non-CMC to maintain relationships
with partners. They
found that participants corresponded less frequently with their

Internet partner (5.2 times
per month) than with their non-Internet partner (7.2 times per
month) (as cited in
Cummings et al., 2002). This difference does not seem
significant, as it is only two times
less per month. However, in additional self-report surveys,
participants responded
feeling more distant, or less intimate, towards their Internet
partner than their non-
Internet partner. This finding may be attributed to participants’
beliefs that email is an
inferior mode of personal relationship communication.
Intimacy is necessary in the creation and maintenance of
relationships, as it is
defined as the sharing of a person’s innermost being with
another person, i.e., self-
disclosure (Hu, Wood, Smith, & Westbrook, 2004).
Relationships are facilitated by the
reciprocal self-disclosing between partners, regardless of non-
CMC or CMC. Cummings
et al.’s (2002) reviewed results contradict other studies that
research the connection
between intimacy and relationships through CMC.

Hu et al. (2004) studied the relationship between the frequency
of Instant
Messenger (IM) use and the degree of perceived intimacy
among friends. The use of IM
instead of email as a CMC modality was studied because IM
supports a non-professional
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5
environment favoring intimate exchanges (Hu et al., 2004).
Their results suggest that a
positive relationship exists between the frequency of IM use and
intimacy, demonstrating
that participants feel closer to their Internet partner as time
progresses through this CMC
modality.
Similarly, Underwood and Findlay (2004) studied the effect of
Internet
relationships on primary, specifically non-Internet relationships
and the perceived
intimacy of both. In this study, self-disclosure, or intimacy,
was measured in terms of
shared secrets through the discussion of personal problems.
Participants reported a
significantly higher level of self-disclosure in their Internet
relationship as compared to
their primary relationship. In contrast, the participants’ primary
relationships were
reported as highly self-disclosed in the past, but the current
level of disclosure was
perceived to be lower (Underwood & Findlay, 2004). This

result suggests participants
turned to the Internet in order to fulfill the need for intimacy in
their lives.
In further support of this finding, Tidwell and Walther (2002)
hypothesized CMC
participants employ deeper self-disclosures than FtF
participants in order to overcome the
limitations of CMC, e.g., the reliance on nonverbal cues. It was
found that CMC partners
engaged in more frequent intimate questions and disclosures
than FtF partners in order to
overcome the barriers of CMC. In their 2002 study, Tidwell
and Walther measured the
perception of a relationship’s intimacy by the partner of each
participant in both the CMC
and FtF conditions. The researchers found that the participants’
partners stated their
CMC partner was more effective in employing more intimate
exchanges than their FtF
6

partner, and both participants and their partners rated their
CMC relationship as more
intimate than their FtF relationship.
Discussion
In 2002, Cummings et al. stated that the evidence from their
research conflicted
with other data examining the effectiveness of online social
relationships. This statement
is supported by the aforementioned discussion of other research.
There may be a few
possible theoretical explanations for these discrepancies.
Limitations of These Studies
The discrepancies identified may result from a number of
limitations found in the
materials reviewed by Cummings et al. These limitations can
result from technological
constraints, demographic factors, or issues of modality. Each of
these limitations will be
examined in further detail below.
Technological limitations. First, one reviewed study by
Cummings et al. (2002)
examined only email correspondence for their CMC modality.
Therefore, the study is

limited to only one mode of communication among other
alternatives, e.g., IM as studied
by Hu et al. (2004). Because of its many personalized features,
IM provides more
personal CMC. For example, it is in real time without delay,
voice-chat and video
features are available for many IM programs, and text boxes can
be personalized with the
user’s picture, favorite colors and text, and a wide variety of
emoticons, e.g., :). These
options allow for both an increase in self-expression and the
ability to overcompensate
for the barriers of CMC through customizable features, as stated
in Tidwell and Walther
Because all
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limitations,
it is
important
to discuss
the
limitations
of articles
under
examination
.

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7
(2002). Self-disclosure and intimacy may result from IM’s
individualized features,
which are not as personalized in email correspondence.
Demographic limitations. In addition to the limitations of email,
Cummings et

al. (2002) reviewed studies that focused on international bank
employees and college
students (see Appendix B for demographic information). It is
possible the participants’
CMC through email was used primarily for business,
professional, and school matters
and not for relationship creation or maintenance. In this case,
personal self-disclosure
and intimacy levels are expected to be lower for non-
relationship interactions, as this
communication is primarily between boss and employee or
student and professor.
Intimacy is not required, or even desired, for these professional
relationships.
Modality limitations. Instead of professional correspondence,
however,
Cummings et al.’s (2002) review of the HomeNet project
focused on already established
relationships and CMC’s effect on relationship maintenance.
The HomeNet researchers’
sole dependence on email communication as CMC may have
contributed to the lower
levels of intimacy and closeness among Internet relationships as
compared to non-

Internet relationships (as cited in Cummings et al., 2002). The
barriers of non-personal
communication in email could be a factor in this project, and
this could lead to less
intimacy among these Internet partners. If alternate modalities
of CMC were studied in
both already established and professional relationships, perhaps
these results would have
resembled those of the previously mentioned research.
8
Conclusions and Future Study
In order to gain a complete understanding of CMC’s true effect
on both online
and offline relationships, it is necessary to conduct a study that
examines all aspects of
CMC. This includes, but is not limited to, email, IM, voice-
chat, video-chat, online

journals and diaries, online social groups with message boards,
and chat rooms. The
effects on relationships of each modality may be different, and
this is demonstrated by
the discrepancies in intimacy between email and IM
correspondence. As each mode of
communication becomes more prevalent in individuals’ lives, it
is important to examine
the impact of all modes of CMC on online and offline
relationship formation,
maintenance, and even termination.
The
conclusion
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the paper
addresses
and can
offer areas
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research.
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sions:
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english.pur

due.edu/ow
l/resource/
724/04/
9
References
Cummings, J. N., Butler, B., & Kraut, R. (2002). The quality of
online social
relationships. Communications of the ACM, 45(7), 103-108.
Hu, Y., Wood, J. F., Smith, V., & Westbrook, N. (2004).
Friendships through IM:
Examining the relationship between instant messaging and
intimacy. Journal of
Computer-Mediated Communication, 10, 38-48.
Tidwell, L. C., & Walther, J. B. (2002). Computer-mediated
communication effects on
disclosure, impressions, and interpersonal evaluations: Getting
to know one
another a bit at a time. Human Communication Research, 28,
317-348.

Underwood, H., & Findlay, B. (2004). Internet relationships and
their impact on primary
relationships. Behaviour Change, 21(2), 127-140.
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10
Appendix A
The HomeNet Project
Started at Carnegie Mellon University in 1995, the HomeNet
research project has
involved a number of studies intended to look at home Internet
usage. Researchers began
this project because the Internet was originally designed as a
tool for scientific and

corporate use. Home usage of the Internet was an unexpected
phenomenon worthy of
extended study.
Each of HomeNet’s studies has explored a different facet of
home Internet usage,
such as chatting, playing games, or reading the news. Within the
past few years, the
explosion of social networking has also proven to be an area
deserving of additional
research. Refer to Table A1 for a more detailed description of
HomeNet studies.
Table A1
Description of HomeNet Studies by Year
Year
of
Study
Contents
of
Study
1995-‐1996
93 families in Pittsburgh involved in school
or community organizations
1997-‐1999
25 families with home businesses

1998-‐1999
151 Pittsburgh households
2000-‐2002
National survey
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11
Appendix B
Demographic Information for Cummings et al. (2002)’s Review
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Journal of Family Communication

ISSN: 1526-7431 (Print) 1532-7698 (Online) Journal homepage:
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Discussions About Racial and Ethnic Differences
in Internationally Adoptive Families: Links With
Family Engagement, Warmth, & Control
Kayla N. Anderson, Martha A. Rueter & Richard M. Lee
To cite this article: Kayla N. Anderson, Martha A. Rueter &
Richard M. Lee (2015) Discussions
About Racial and Ethnic Differences in Internationally
Adoptive Families: Links With Family
Engagement, Warmth, & Control, Journal of Family
Communication, 15:4, 289-308, DOI:
10.1080/15267431.2015.1076420
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Journal of Family Communication, 15: 289–308, 2015
Copyright © Taylor & Francis Group, LLC
ISSN: 1526-7431 print / 1532-7698 online
DOI: 10.1080/15267431.2015.1076420
Discussions About Racial and Ethnic Differences in
Internationally Adoptive Families: Links With Family
Engagement, Warmth, & Control
Kayla N. Anderson and Martha A. Rueter
Department of Family Social Science, University of Minnesota
Richard M. Lee
Department of Psychology, University of Minnesota
Discussions about racial and ethnic differences may allow
international, transracial adoptive fami-
lies to construct multiracial and/or multi-ethnic family
identities. However, little is known about the
ways family communication influences how discussions about

racial and ethnic differences occur.
This study examined associations between observed family
communication constructs, including
engagement, warmth, and control, and how adoptive families
discuss racial and ethnic differences
using a sample of families with adolescent-aged children
adopted internationally from South Korea
(N = 111 families, 222 adolescents). Using data collected during
mid-adolescence and again during
late adolescence, higher levels of maternal control and positive
adolescent engagement were inde-
pendently associated with a greater likelihood that family
members acknowledged the importance
of racial and ethnic differences and constructed a multiracial
and/or multi-ethnic family identity.
Adolescent engagement was also related to a greater likelihood
that family members disagreed about
the importance of racial and ethnic differences, and did not
build a cohesive identity about differences.
Most international adoptions in the United States involve a
White parent and a child from another
country who is a U.S. racial and ethnic minority. Nine of ten
internationally adoptive parents are
White, whereas 8 of 10 children are from Asia, Latin America,
or Africa (U.S. Department of
Health & Human Services, 2013). It is not surprising then that
more than 80% of international
adoptions are considered transracial. The majority of
internationally adopted children are from
Asia (59%; U.S. Department of Health & Human Services,
2013). In 2009, for instance, more
than 105,000 children adopted from Asian countries were living
in U.S. adoptive homes with
White parents (Krieder & Raleigh, 2011).

In particular, South Korea is the largest overall international
adoption sending country into
the United States, with more than 110,000 Korean children
adopted into American families
since the program’s inception (Selman, 2012). Compared to
domestic adoption, higher transracial
placement rates into White families (U.S. Department of Health
& Human Services, 2013) have
Correspondence should be addressed to Kayla N. Anderson,
Department of Family Social Science, University of
Minnesota, 290 McNeal Hall, 1985 Buford Avenue, St. Paul,
MN 55108. E-mail: [email protected]
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mailto:[email protected]

290 ANDERSON ET AL.
culminated in researchers calling for examination of race and
ethnicity issues in internationally
adoptive families (Galvin, 2003). This suggests attention is
warranted to understand families with
White parents and children adopted internationally from South
Korea, the most populous group
of internationally adoptive families.
How adoptive families discursively engage with racial and
ethnic differences may build a fam-
ily identity around this topic (Galvin, 2003, 2006a), and
promoting adopted children’s racial and
ethnic heritage is important for their adjustment (Johnston,
Swim, Saltsman, Deater-Deckard, &
Petrill, 2007; Lee, 2003; Mohanty, Keokse, & Sales, 2006). Yet,
there is little research about
which communication behaviors promote adoptive families’
race and ethnicity discussions. This
study examines how family communication (engagement,
warmth, control)—when children are
in mid-adolescence—contributes to how South Korean
internationally adoptive families with
White parents discuss race and ethnicity when children are in
later adolescence.
Addressing Race and Ethnicity Within International, Transracial
Adoptive Families
Galvin (2006a, 2006b) suggests nonbiological families are
“discourse dependent,” and construct
their family identity through internal communication and
management of boundaries with those
outside of the family. Attention has been given in recent years
to understanding how interna-

tionally adoptive families discuss adoptive family experiences
(Ballard & Ballard, 2011; Colaner
& Kranstuber, 2010; Harrigan, 2010) and manage boundaries in
response to outsiders’ com-
ments about their often visibly different family form (Docan-
Morgan, 2010; Suter, 2008; Suter &
Ballard, 2009; Suter, Reyes, & Ballard, 2011a, 2011b).
In addition to family discussions about adoption and external
boundary management, the
need to examine how international, transracial adoptive families
internally engage with racial
and ethnic differences has been stressed. Cultural socialization
frameworks indicate racial and
ethnic minority families, including adoptive families with racial
and ethnic minority children,
improve children’s heritage awareness and discrimination
defenses by promoting knowledge of
and pride in the child’s background through activities and
discussions related to cultural his-
tory (Hughes et al., 2006). Galvin’s (2003, 2006a) discourse-
dependency suggests discussions
about race and ethnicity in transracial adoptive families
strengthen the family’s racial and ethnic
identity. However, the practice of engaging with race and
ethnicity is complicated in transracial
adoptive families because predominantly White parents must
seek out ways to connect with and
discuss their child’s differing racial and ethnic heritage (Lee,
Grotevant, Hellerstedt, Gunnar, &
the MIAP Team, 2006). Compared to same-race ethnic minority
families, transracial adoptive
families have limited cultural resources to teach the child about
his/her heritage due to a lack of
shared racial, ethnic, or national origin heritage, a greater
likelihood of living in a racially White

community, and parents’ limited experiences with
discrimination (Shiao & Tuan, 2008).
Historically, research has focused on how international,
transracial adoptive families engage
in racial and ethnic activities (e.g., culture camps) instead of
discussions about race and ethnic-
ity (c.f., Carstens & Juliá, 2000; Vonk, Lee, & Crolley-Simic,
2010). However, activities and
discussions are distinct aspects of supporting racial and ethnic
differences (Kim, Reichwald,
& Lee, 2013). Recent communication research is filling gaps in
how adoptive families discur-
sively construct internal family identities about race and
ethnicity (e.g., Docan-Morgan, 2011;
Gao & Womack, 2013; Harrigan, 2009; Harrigan & Braithwaite,
2010; Suter, 2012). Adoptive
parents appear to walk the tenuous line between promoting
adoptive family similarities and
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FAMILY COMMUNICATION AND RACE & ETHNICITY 291
acknowledging the child’s birth heritage (e.g., Harrigan, 2009;
Suter, 2012). Adoptees, however,
tend to avoid race and ethnicity discussions with parents
because parents’ responses during such
discussions are often viewed as unhelpful (Docan-Morgan,
2011; Samuels, 2009).
Despite the increased focus on race and ethnicity discussions in
international, transracial adop-
tive families (e.g., Docan-Morgan, 2011; Harrigan, 2009), little
research has examined real-time
conversations about adoptive families’ racial and ethnic
differences. Most research has examined
parents’ (e.g., Harrigan & Braithwaite, 2010) or adolescents’
(e.g., Samuels, 2009) self-reports of
their families’ race and ethnicity discussions. However, parents
and adolescents tend to perceive
their conversations about race and ethnicity differently, and
adoptive parents may over-report
their engagement with racial and ethnic issues (Kim et al.,
2013). Capturing real-time discus-
sions about how international, transracial, adoptive families
discuss racial and ethnic differences
within their families as a whole provides additional insight into
how families engage with and
identify as multiracial and/or multi-ethnic families, if they do at
all.

Acknowledging Differences Framework: Discussions About
Racial and Ethnic
Differences
To understand how international, transracial adoptive families
discuss race and ethnicity, schol-
ars have emphasized the importance of whether or not families
acknowledge racial and ethnic
differences (Kim et al., 2013; Kirk, 1984; Lee, 2003; Shiao &
Tuan, 2008). In acknowledgment
of differences, all family members agree that the adopted
child’s racial and ethnic heritage is a
vital component of the family and discuss acting in ways that
support the adopted child’s racial
and ethnic background. These families transform from seeing
themselves as a same-race fam-
ily with similar ethnic or cultural experiences to a multiracial
and/or multi-ethnic family that
embraces diverse heritages. This framework suggests families
acknowledging differences cannot
ask adopted children to learn about their heritage without
familial engagement in learning about
the child’s birth culture; doing so isolates adopted children
from the family.
This framework also suggests two forms of discussion where
families do not universally agree
that racial and ethnic differences are important for the family
identity (Kim et al., 2013; Kirk,
1984; Shiao & Tuan, 2008). In rejection of differences, families
take a color-blind approach to
conversations about racial and ethnic differences by indicating
these differences are not relevant
to the family, and end any conversation about the importance of
their racial and ethnic diversity.
Families who reject differences may also have discussions that

diminish the importance of the
adopted child’s birth heritage. Finally, some families have
discrepant views of differences, or
disagreements, during their conversations about the importance
of racial and ethnic differences
and do not build a cohesive family identity about their
differences. In families with discrepant
views of differences, at least one family member may discuss
how the family actively supports
the child’s ethnic and racial heritage as an entire family.
However, another member may suggest
the family’s racial and ethnic differences are not salient life
experiences.
How Families Discuss Racial and Ethnic Differences: Family
Communication as a
Pathway
Family communication may be one avenue influencing how
international, transracial adoptive
families discuss racial and ethnic differences, and the identities
that are created. Theory on
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292 ANDERSON ET AL.
adoption-related communication (see the Family Adoption
Communication Model; Wrobel,
Kohler, Grotevant, & McRoy, 2003) suggests the general family
communication climate builds
an atmosphere that may influence how adoption is discussed.
This theory suggests parents’ warm,
empathetic behaviors may facilitate a climate where the family
and child are encouraged to
discuss adoption questions. Or, closed communication
environments may not encourage future
discussion of adoption-related issues because family members
perceive this conversation to be
off-limits for discussion (Wrobel et al., 2003). These ideas are
mirrored in family communica-
tion theories (e.g., Family Communication Patterns Theory
(FCPT); Koerner & Fitzpatrick, 2004,
2006), which suggest family communication behaviors create an
environment that regulates what
topics are discussed in families, who discusses topics, and
which family members wield decision-
making power. The goal of these communication behaviors is to
create shared family realities, or
cohesive family identities, about specific topics (Koerner &
Fitzpatrick, 2004, 2006).

Family communication and adoption theories (Burleson, Delia,
& Applegate, 1995; Grotevant,
Wrobel, van Dulmen, & McRoy, 2001; Koerner & Fitzpatrick,
2004, 2006) cite warm, conver-
sational engagement and control as vital in creating the
environment that alters how sensitive
conversations occur in families. Thus, three family
communication behaviors—engagement,
warmth, and control—may be related to how families discuss
the importance of their racial and
ethnic differences and the adopted child’s heritage. These three
communication behaviors may
also be related to whether families reach agreement about the
importance (e.g., acknowledge) or
unimportance (e.g., rejection) of racial and ethnic differences.
Studies exploring the relationship between family
communication and how adoptive families
discuss racial and ethnic differences are scarce and restricted by
conceptual limitations. For exam-
ple, parent-child engagement in cultural activities about the
adoptees’ heritage has been linked
to relationship quality (Yoon, 2000, 2004). Qualitative
assessments of content during racial and
ethnic differences discussions suggest communication may vary
based on how families discuss
racial and ethnic differences (Kim et al., 2013). Links between
family communication and how
families discuss racial and ethnic differences have not been
explicitly examined; however, these
studies provide initial support for the possibility that
communication behaviors are related to how
adoptive families discuss racial and ethnic differences.
Family Communication: Differences Across Family Members

Our study was informed by research indicating communication
behaviors vary across fam-
ily members. Individual family members’ communication
behaviors may each individually
contribute to the family environment, teaching family members
what topics are appropriate to
discuss and providing family members with the skills to broach
sensitive topics (Burleson et al.,
1995). Adolescents may discuss distinct topics with each parent
(Noller & Bagi, 1985) and com-
municate more with mothers than fathers (Noller & Callan,
1990; Steinberg & Silk, 2002). Family
members also relate differently to one another in systemic
settings when more than just a parent-
child dyad is present (Doherty & Beaton, 2004). Parents and
adolescents also have different
perceptions of their communication quality with one another
(Laursen & Collins, 2004; Rosnati,
Iafrate, & Scabini, 2007). This suggests each family member’s
communication behavior must be
examined using observational data in settings that include more
than just a parent-child dyad.
This study takes this approach to explore which family
members’ communication behaviors are
important for how families discuss racial and ethnic differences
and build multiracial and/or
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FAMILY COMMUNICATION AND RACE & ETHNICITY 293
multi-ethnic family identities. Based on theory and research
described previously, we propose
the following hypothesis:
H1: Engagement, warmth, and control will vary across
categories of how families discuss racial and
ethnic differences: acknowledgment, rejection, or discrepant
views of differences.
To test this hypothesis, observed family communication
behaviors for mothers, fathers, and
children in South Korean international, transracial adoptive
families were assessed in mid-
adolescence and compared with the three discussion categories
assessed in late-adolescence.
METHOD
Participants
Participants were a subset of families drawn from the Sibling

The Effect of Family Communication Patterns on Adopted Adolescent Adjustment

The Effect of Family Communication Patterns on Adopted Adolescent Adjustment

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