Friendship Groups of Depressed Adolescents

Adolescent Internalizing Symptoms and the “Tightknittedness”
of
Friendship Groups
Sonja E. Siennick and Mayra Picon
Florida State University
Adolescents with depression have lower peer status overall, but
tend to befriend each other. We examined the
“tightknittedness” of their friendship groups by testing whether
adolescent friendship groups’ average levels of or vari-
ability in internalizing symptoms predict group cohesiveness.
We used four waves (9th–12th grades) of survey and
social network data on 3,013 friendship groups from the
PROmoting School-Community-University Partnerships to
Enhance Resilience study. Friendship groups with higher
average depressive symptoms were less cohesive; groups
with higher average anxiety symptoms had greater reciprocity.
Groups with greater variability in depressive symptoms
had greater density; variability in anxiety symptoms was not
consistently associated with cohesion. The friendship
groups of depressed adolescents appear less cohesive than the
“typical” adolescent friendship group.
When compared with their peers, adolescents with
more depressive symptoms have fewer friends,
have less stable friendships, and are more often
victimized and rejected by their peers (Chan &
Poulin, 2009; Kochel, Ladd, & Rudolph, 2012; Rose
et al., 2011; Stice, Ragan, & Randall, 2004). Yet
depressive symptoms also are a basis for friend-

ship formation, such that adolescents experiencing
these symptoms tend to be friends with each other
(Cheadle & Goosby, 2012; Hogue & Steinberg,
1995; Schaefer, Kornienko, & Fox, 2011). This
means that even if they have lower status in their
larger peer networks, many adolescents with
depressive symptoms do have friends, and those
friends often have depressive symptoms them-
selves. Thus many youth with depressive symp-
toms are likely embedded in friendship groups of
adolescents with similar symptoms. Yet we do not
know whether these friendship groups are as cohe-
sive as the groups formed by youth without
depressive symptoms, or whether they are
structurally weaker and thus not comparable sub-
stitutes, at least in terms of cohesion, for typical
friendship groups. Most studies of depressive
symptoms and peer networks have focused on
dyadic interactions or on individual adolescents’
status within entire social networks, rather than on
friendship groups.
This study examined whether friendship groups
comprised of adolescents with more depressive
symptoms are smaller and “looser,” or less tight-
knit, than groups characterized by fewer depres-
sive symptoms. It also examined whether groups
whose members vary more in their levels of
depressive symptoms are smaller and less tight-
knit. Finally, it distinguished between symptoms of
depression and symptoms of anxiety, which stud-
ies suggest may have opposite effects on friendship
cohesion (Rose et al., 2011). To our knowledge, this
is the first paper to describe the internal cohesive-
ness of friendship groups with members who have

varying constellations of depressive and anxiety
symptoms, as well as one of the only papers to
examine characteristics of depressed youths’
friendships at the group or “clique” level, versus
at the dyad level or at the ego level (examining
individual youths’ status in the larger friendship
network).
How Do Depressed Friendship Groups Form?
Research has uncovered four microlevel processes
that appear to underlie the similarity between
We thank Derek Kreager, Jim Moody, and David Schaefer for
their helpful comments. Grants from the W. T. Grant
Foundation
(8316), National Institute on Drug Abuse (R01-DA018225), and
National Institute of Child Health and Development (R24-
HD041025) supported this research. The analyses used data
from PROSPER, a project directed by R. L. Spoth, funded by
the
National Institute on Drug Abuse (RO1-DA013709) and the
National Institute on Alcohol Abuse and Alcoholism
(AA14702).
The content of this article is solely the responsibility of the
authors and does not necessarily represent the official views of
the National Institutes of Health.
Requests for reprints should be sent to Sonja E. Siennick, Col-
lege of Criminology and Criminal Justice, Florida State Univer-
sity, 112 S. Copeland Street, Tallahassee, FL 32306. E-mail:
[email protected]
© 2019 Society for Research on Adolescence
DOI: 10.1111/jora.12484
JOURNAL OF RESEARCH ON ADOLESCENCE, 30(S2), 391–

402
https://orcid.org/0000-0002-6681-9225
https://orcid.org/0000-0002-6681-9225
mailto:
friends on various emotional and behavioral
dimensions: selection, de-selection, influence, and
social withdrawal. The first, selection or homo-
phily, is based on the notion that people are
attracted to similar others (Berger & Calabrese,
1975) and implies that friends’ similarity in depres-
sive symptoms occurs because adolescents choose
to befriend youth who have levels of symptoms
similar to theirs. Indeed, an early longitudinal net-
work study of high school students found that
selection partly explained adolescent friends’ simi-
larity in internalized distress (Hogue & Steinberg,
1995). These findings have been replicated by more
recent studies on depressive symptoms (Kiuru,
Burk, Laursen, Nurmi, & Salmela-Aro, 2012; Van
Zalk, Kerr, Branje, Stattin, & Meeus, 2010) and on
social anxiety symptoms as well (Van Zalk, Van
Zalk, Kerr, & Stattin, 2011). Moreover, one of these
studies found evidence of a second process—de-
selection. Specifically, this study found that youth
were more likely to terminate friendships with
adolescents who became more dissimilar in terms
of depressive symptoms over a 1-year period
(Kiuru et al., 2012). Thus, one reason why adoles-
cent friends have similar levels of depressive
symptoms is that adolescents are more likely to
become and stay friends with other adolescents
who resemble them on this dimension.

Another reason involves a third process. Influ-
ence, or socialization, suggests that friends have
similar levels of depressive symptoms because they
influence each other’s symptoms and become
increasingly similar over time. This occurs through
mechanisms such as co-rumination, or excessively
discussing one’s problems within a friendship
(Rose, 2002). Hogue and Steinberg’s (1995) early
network study examined influence processes as
well, and found that males’, but not females’, inter-
nalized distress grew more similar to their friend-
ship groups’ levels over time. A later study using a
sample of third graders similarly found that chil-
dren’s levels of depressive and social anxiety
symptoms became more similar to the average
level of their friends’ symptoms over a 1-year per-
iod (Mercer & Derosier, 2010). Further evidence of
depression socialization comes from two longitudi-
nal studies of dyads that found that adolescents’
depressive symptoms were predicted by their best
friends’ symptoms, controlling for their initial
levels of depressive symptoms (Prinstein, 2007; Ste-
vens & Prinstein, 2005). A more recent study found
similar evidence of socialization of depressive
symptoms, but only among female best friend
dyads (Giletta et al., 2011). Other internalizing
symptoms may be transmitted in the same way.
One study, for example, found that friends, espe-
cially girls, tended to influence each other’s levels
of social anxiety over time (Van Zalk, Van Zalk,
Kerr, et al., 2011). This influence may be especially
strong in certain friendship groups: These same
authors also found that youth who affiliated with
“Radical” crowds, those comprised of Goths and
Punks, were most influenced by their peers’ social

anxiety (Van Zalk, Van Zalk, & Kerr, 2011).
Finally, a fourth process of social withdrawal
may contribute to the resemblance among friends
in depressive symptoms. Under this mechanism,
adolescents with depressive symptoms may with-
draw from peer interaction to avoid experiencing
stigma and negative interactions with others, or
because they perceive themselves as socially
incompetent (Altmann & Gotlib, 1988; Rudolph,
Hammen, & Burge, 1994). This social withdrawal
may exclude adolescents with depressive symp-
toms from normative peer networks, leaving them
to befriend other marginalized youth, including
those who are also experiencing symptoms. Consis-
tent with this, one study found that youth with
few friends, who often also had symptoms of
depression, tended to befriend each other, and this
indirectly created depression similarity among
friends (Schaefer et al., 2011).
In this paper, we do not test these microlevel
processes. Instead, we take as our starting point
the friendship groups that are formed by these pro-
cesses, and we examine the characteristics of those
groups. As we next describe, the processes that
make friends similar on depressive symptoms
might also create cohesive, tight-knit friendship
groups. However, a separate literature on group
functioning suggests that these symptoms instead
might undermine group cohesiveness.
Potential Associations Between Depressive
Symptoms and Group Structure
Membership in cohesive friendship groups could

offer many potential benefits to adolescents who
are experiencing depressive symptoms. These
groups are important contexts for development
and for flows of influence, information, and sup-
port among peers (Brechwald & Prinstein, 2011;
De�girmencio�glu, Urberg, Tolson, & Richard, 1998;
Ellis & Zarbatany, 2007; Simons-Morton & Farhat,
2010). Tight-knit groups of friends with depressive
symptoms could offer group members more oppor-
tunities for supportiveness, intimacy, and sharing,
which could enhance their well-being (Buhrmester,
392 SIENNICK AND PICON
1990). They could also provide unified buffers
against the bullying and peer victimization that
adolescents with depressive symptoms are at risk
for experiencing (Kaltiala-Heino, Fr€ojd, & Mart-
tunen, 2010; Kochel et al., 2012).
Although research suggests that adolescents
with depressive symptoms have lower quality peer
relations in general, it is possible that these adoles-
cents still manage to form strong, cohesive friend-
ship groups. Theoretically, they have friendship
problems because their peers find some of their
behaviors aversive, such as their excessive reassur-
ance-seeking, their redirecting conversations to
focus on their problems, and their acting socially
helpless (Agoston & Rudolph, 2013; Coyne, 1976;
Prinstein, Borelli, Cheah, Simon, & Aikins, 2005;
Schwartz-Mette & Rose, 2016). However, if pro-
cesses of selection are at play—that is, if adoles-
cents with depressive symptoms choose to form

friendship groups with each other despite these
behaviors—then the behaviors may not undermine
the internal cohesiveness of those groups. Indeed,
there is evidence that some level of emotional dis-
tress may actually enhance these friendships by
prompting social support and self-disclosure (Hill
& Swenson, 2014). In addition, if processes of
socialization are at play, then the increased similar-
ity among members of depressed groups may
enhance group cohesiveness. In fact, research sug-
gests that processes such as co-rumination serve as
protective factors for friendship problems, even
when they worsen depressive and anxiety symp-
toms (Rose, 2002; Rose, Carlson, & Waller, 2007).
It thus is possible that groups comprised of adoles-
cents with depressive symptoms have strong inter-
nal connections despite their members’
symptomatology and lower status within the larger
peer network.
Yet that possibility is in contrast with predic-
tions from research on the impact of emotions on
small group functioning, which provides some of
the only existing group-level evidence on this topic.
That work, which tends to use adult samples, has
shown that group members’ affect and moods do
influence group performance and cohesion (Kelly
& Jones, 2012). Much of this research has focused
on group members’ positive emotions, which have
been found to facilitate within-group communica-
tion, reduce within-group conflict, and promote
within-group cooperation and bonding (Spoor &
Kelly, 2004). If negative emotions have the opposite
effect, depressive symptoms could worsen these
features of adolescent friendship groups. This may
be especially likely if adolescents with depressive

symptoms befriend each other less because they
like each other than because they have few alterna-
tive friendship opportunities, as under the social
withdrawal mechanism (Schaefer et al., 2011).
Without the positive mood and strong mutual lik-
ing that promote group cohesiveness, friendship
groups composed of adolescents with depressive
symptoms may be less tight-knit than the friend-
ship groups formed by their less depressed peers.
Research has yet to determine whether these symp-
toms enhance or undermine the internal cohesive-
ness of adolescent friendship groups.
Variation by Type of Internalizing Symptom and
Extent of Similarity
Two considerations complicate studies of this topic.
First, many past studies of depressive symptoms
and peer relations have not distinguished between
depressive and anxiety symptoms. Depression and
anxiety have distinct developmental courses (Cum-
mings, Caporino, & Kendall, 2014) and could have
different associations with peer problems. Yet in
this literature, depressive symptoms are often
examined as part of a broader “internalizing” or
“distress” construct that includes general anxiety.
Notably, this combined construct does not consis-
tently predict peer problems (Hill & Swenson,
2014; Hogue & Steinberg, 1995; Mcleod & Uemura,
2012). Indeed, studies that have separated the two
suggest that depressive symptoms drive the harm-
ful effects of internalizing symptoms on peer prob-
lems (de Matos, Barrett, Dadds, & Shortt, 2003;
Kennedy, Spence, & Hensley, 1989; Strauss, Lahey,
Frick, Frame, & Hynd, 1988). In fact, youth with

some forms of anxiety may have few peer prob-
lems at all (Chen, Cohen, Johnson, & Kasen, 2009;
de Matos et al., 2003). For example, general anxiety
symptoms have been found to be associated with
having more and higher quality friendships (Rose
et al., 2011) and less hostile peer interactions
(Rudolph et al., 1994). The differential effects of
depressive and anxiety symptoms could stem from
the fact that although both are characterized by
negative affect, only depression is characterized by
low positive affect (Rose et al., 2011), potentially
making adolescents’ anxiety less aversive to, or
even eliciting sympathy from, their peers.
A second consideration is whether heterogeneity
in, versus simply the average level of, depressive
symptoms within a friendship group is associated
with lower group cohesiveness. A group with a
moderate average level of depressive symptoms
could be composed of several adolescents who
DEPRESSION AND FRIENDSHIP GROUPS 393
each are experiencing moderate depression, or a
mixture of adolescents who are not depressed and
adolescents who are highly depressed. In the latter
case, the weaker homophily among group mem-
bers in depressive symptoms could undermine
group cohesiveness. Past research shows that peers
who are dissimilar in mood or behavior are more
likely to argue with, reject, and defriend each
other, perhaps because they experience relation-
ships with dissimilar others as less validating
(Bl€ote, Bokhorst, Miers, & Westenberg, 2012; Chow,

Tan, & Ruhl, 2015; Hafen, Laursen, Burk, Kerr, &
Stattin, 2011; Van Zalk et al., 2010; Wright, Giam-
marino, & Parad, 1986). In experimental studies as
well, people who are experiencing depression, anx-
iety, or bad moods prefer others who have the
same feelings over others who do not (Baker, Hud-
son, & Taylor, 2014; Rook, Pietromonaco, & Lewis,
1994; Rosenblatt & Greenberg, 1991). If dissimilar-
ity has the same impact on the multiple relation-
ships within friendship groups, then groups with
more internal variation on depressive or anxiety
symptoms could be less cohesive.
This Study
This study used survey and social network data
from a large community sample of adolescents to
examine the friendship groups of distressed adoles-
cents. First, we examined whether groups with
greater average within-group distress are smaller
and more loosely connected. In doing so, we distin-
guished between depressive and anxiety symp-
toms, which are often comorbid but which may
have opposite effects on adolescent friendships.
Second, we also examined whether groups whose
members have more dissimilar levels of distress
are smaller and more loosely connected. Based on
past work, we expected that group depressive
symptoms would be negatively associated with
measures of group cohesion; group anxiety symp-
toms would be unassociated or positively associ-
ated with group cohesion; and within-group
variability in these symptoms would be negatively
associated with measures of group cohesion.
METHOD

Data
Sample. Our data were from PROmoting
School-Community-University Partnerships to
Enhance Resilience (PROSPER), a place-rando-
mized substance abuse prevention trial in 28 public
school districts in rural Pennsylvania and Iowa
(Spoth, Greenberg, Bierman, & Redmond, 2004;
Spoth et al., 2013). The districts enrolled between
1,300 and 5,200 students each, were at least 95%
English-speaking, were economically diverse (with
an average of 29% of families eligible for free or
reduced cost school lunches), and were predomi-
nantly white (61–96%). For the prevention trial, dis-
tricts were blocked on size and location and
randomly assigned to have universal substance
abuse prevention programming implemented by
community teams, or to be in the control condition.
In this study, we found that intervention condition
did not moderate any of our results, so we used
data from both conditions.
PROSPER’s sample began with two successive
cohorts of adolescents who were in sixth grade in
the Fall semesters of 2002 and 2003 (N = 10,849).
Half were female and nearly all (98%) were age 11
or 12. Adolescents completed machine-scored
paper-and-pencil surveys about their attitudes,
behaviors, and friendships during class sessions.
Follow-up surveys were administered each spring
from 6th–12th grades; at each wave, students who
had moved into study schools were recruited to
join the study. At each survey, adolescents pro-
vided assent, and parents and guardians were con-

tacted by mail and had the opportunity to return a
form excluding their child from the study. At any
given wave, approximately 3% of adolescents and
4% of parents declined to participate, and approxi-
mately 5% of adolescents were absent. We used
survey and social network data from 9th–12th
grades (four waves), when adolescents reported on
their depressive and anxiety symptoms. Because
cohort did not predict any of our outcomes, we
used combined data from both cohorts in our anal-
yses. Our analytical sample was 48% male and 84%
white; 76% lived in two parent households; 22%
were eligible for free or reduced-cost lunch; and at
ninth grade, 94% were age 14 or 15 (mean = 14.8).
Friendship identification and friendship group
creation. The surveys asked adolescents to write
the names of up to two best friends and five addi-
tional close friends in their school and grade. Most
adolescents (94%) nominated at least one friend;
adolescents who made no nominations were more
likely to be male, non-White, from single-parent
households, and to be eligible for free lunch, and
had higher depressive and anxiety symptom scores
than adolescents who nominated friends. The
PROSPER staff was able to match over 83% of
friendship nominations to students on the schools’
class rosters. Only 2% of nominations matched
multiple names on the rosters and thus could not
be matched with certainty, and <1% were inappro-
priate choices (e.g., pop stars). The remaining 15%

matched no name on the school grade rosters and
presumably were not adolescents’ grademates.
Since the entire grade-level was targeted for partic-
ipation in the study, these data allowed us to map
out adolescents’ own personal friendship ties and
the complete within-grade school friendship net-
works that existed at the time of the survey, and to
link adolescents with their friends’ survey
responses.
PROSPER staff identified distinct mutually exclu-
sive friendship groups within the larger friendship
networks using computer algorithms designed to
delineate groups by maximizing modularity scores,
which are weighted functions of within-group com-
pared to cross-group ties (Moody, 2001). The algo-
rithm began with starting values based on factor
analysis (Gest, Davidson, Rulison, Moody, & Welsh,
2007), and iteratively evaluated whether the modu-
larity score would be improved by reassigning each
student to another group, by merging any groups, or
by splitting any groups. When no more improve-
ments to the score were found, that set of friendship
group assignments was kept. This approach identi-
fied 3,090 friendship groups with at least three mem-
bers. We excluded 16 (1% of) groups with 40 or more
members because “group” likely means something
different for groups of this size (cf. Kreager, Rulison,
& Moody, 2011; Rubin, Bukowski, & Bowker, 2015).
Group sizes ranged from 3 to 38 members, with an
average of approximately 10. We also excluded 61
(2% of) groups that were missing information on
cohesiveness. The remaining 3,013 unique friendship
groups were our analytical sample.
Measures

Friendship group cohesiveness. Once discrete
friendship groups were identified and the friend-
ship ties between individual group members were
mapped out, measures of group structure were cal-
culated. Our measures of cohesiveness follow those
used in past work (Gest et al., 2007; Kreager et al.,
2011; Rubin et al., 2015). Group size was a count
measure of the number of adolescents in the group.
Density was the proportion of pairs of adolescents
within the group who were friends with each other
based on their nomination lists. Reciprocity was the
proportion of friendship nominations from one
group member to another that were reciprocated
(i.e., the proportion of dyads who both included
each other on their friendship lists). Transitivity
was the proportion of triads in the group in which
all three members were friends (i.e., where the
friend of an adolescent’s friend also was friends
with that adolescent). Together these measures cap-
ture the size and “tight-knittedness” of the groups.
Creation of group-level predictor variables. Our
group-level predictors and control variables were
aggregated versions of the survey responses given by
the individual group members. For example, to create a
group’s average depressive symptoms score for a given
wave, we computed symptoms scale scores for the indi-
vidual adolescents within the group and then averaged
them. Prior to doing this, we addressed item-level miss-
ing data at each wave from individual adolescents’ sur-
veys using multiple imputation (Rubin, 1987). Two
percent of adolescents were missing information on one
or more depression or anxiety items, and 6% were miss-
ing information on one or more control variables. There

were only modest differences between these adolescents
and those with complete data (e.g., those groups differed
by an average of 1/6 of a standard deviation on the focal
variables).
Depressive symptoms. The surveys included
items tapping symptoms of depression, such as
depressed mood (e.g., feeling sad or appearing tear-
ful), feelings of guilt and worthlessness, and suicidal-
ity (American Psychiatric Association, 2000).
Individual adolescents’ depressive symptoms scores
were the average of five items assessing whether in
the past 6 months they had experienced such depres-
sive symptoms (with each item scored 0–2; range of a
across waves = .83–.85). As described above, group
members’ scores were then averaged to create group-
level average depressive symptoms scores. The
within-group standard deviation of group members’
scores was our measure of the group’s variability in
depressive symptoms.
Anxiety symptoms. The surveys also included
items tapping symptoms of anxiety (e.g., excessive
anxiety and worry, muscle tension; American Psy-
chiatric Association, 2000). Individual adolescents’
anxiety symptoms scores were the average of three
items assessing such symptoms (each scored 0–2;
range of a across waves = .80–.83). Measures of
groups’ average anxiety symptoms and groups’
variability in anxiety symptoms were created using
the same strategies as for depression.
Control variables. Past research has identified
demographic correlates of group structure, such as

gender composition and group members’ family
structures and socioeconomic statuses, which may
confound the associations between group structure
and behavioral risk factors (Kreager et al., 2011).
We thus controlled for grade level (9–12), interven-
tion condition, group gender composition (all-male,
all-female, or mixed gender), and the proportion of
group members who were White, from two-parent
families, and eligible for free or reduced-cost
school lunch. Because reciprocity and transitivity
depend on the number of friendship ties within a
group, we also controlled for density in models of
those outcomes. Descriptive statistics for these and
other study variables are shown in Table 1.
Analytical Strategy
Our analyses were multilevel random effects
regression models predicting each measure of
group cohesiveness from the control variables and
either average levels of or variability in groups’
depressive and anxiety symptoms. The adolescents’
friendship groups were clustered within 29 schools,
violating the independence assumption of regres-
sion analysis. For instance, as shown in Table 1,
between 2% and 7% of the variance in each of our
outcomes fell between schools (vs. within schools).
Our use of multilevel regression models adjusted
our standard errors for this clustering through the
inclusion of variance components for school (Rau-
denbush & Bryk, 2002). Tests indicated that addi-
tional variance components were not needed for

grade (to address potential temporal autocorrela-
tion in the data) or for the main independent vari-
ables (to address potential variability in effects
across schools). We used linear models for all
group-level outcomes except the skewed count
variable group size, for which we used negative
binomial models.
RESULTS
We first examined the associations between
groups’ average internalizing symptoms and their
size and structure. Table 2 shows the results of
multilevel negative binomial and linear regressions
predicting each group cohesiveness outcome from
group-level depressive and anxiety symptoms.
Groups with higher average depressive symptom
scores were significantly smaller in size, less dense,
and had lower reciprocity of friendships, but did
not have significantly lower transitivity.
TABLE 1
Descriptive Statistics for Study Variables (N = 3,013 Groups)
Variable
Mean/%, by Grade
Range ICC9th 10th 11th 12th
Dependent variables
Group size 10.54 10.11 9.48 9.07 3–38 .02
Group density 0.29 0.30 0.30 0.29 0.04–1 .07
Group transitivity 0.42 0.43 0.41 0.42 0–1 .05
Group reciprocity 0.39 0.40 0.37 0.37 0–1 .03

Independent variables
Group’s average depressive symptoms 0.30 0.28 0.27 0.23 0–
1.16 .02
Within-group variation in depressive symptoms 0.34 0.34 0.33
0.30 0–0.94 .02
Group’s average anxiety symptoms 0.48 0.49 0.49 0.45 0–1.75
.01
Within-group variation in anxiety symptoms 0.49 0.49 0.48 0.47
0–0.98 .01
Control variables
Grade 9 10 11 12 9–12 –
Intervention condition 46% 47% 49% 50% 0–1 –
All male group 25% 26% 20% 21% 0–1 .02
All female group 25% 23% 25% 21% 0–1 .01
Mixed gender group 50% 51% 56% 58% 0–1 .04
Percent of group that is White 83% 86% 86% 87% 0–1 .62
Percent of group that lives with two parents 77% 77% 76% 76%
0–1 0
Percent of group eligible for free or reduced-price lunch 26%
22% 21% 18% 0–1 .03
N 885 751 738 639
Notes. Intraclass correlation coefficients (ICC) represent the
proportion of variance in the variable that is between (vs.
within)
schools. ICCs are based on linear models for continuous
outcomes and logistic models for dichotomous outcomes.
Source: PROSPER Peers Study.
Examination of predicted values revealed that com-
pared with groups whose members had no depres-

sive symptoms, groups with elevated average
symptoms (1 standard deviation above the mean)
had on average 0.36 fewer members (9.38 vs. 9.74),
2% lower density (0.29 vs. 0.31), and 5% less
reciprocity (0.37 vs. 0.42). Supplemental analyses
revealed that depressive symptoms and transitivity
were negatively associated when density was
removed from the model, indicating that in groups
with higher average depressive symptoms there
were fewer ties to friends-of-friends because there
were fewer pairs of friends to begin with.
To further gauge the magnitude of the observed
associations, we compared the X-standardized coef-
ficients, which give the change in Y for a one-stan-
dard deviation increase in X, for group-level
depressive and anxiety symptoms with those for
two known correlates of group cohesiveness: the
proportion of members from two-parent families
and the proportion eligible for free or reduced-
price school lunch (Kreager et al., 2011). In the
group size model, the X-standardized coefficient
for depressive symptoms (bstdX = �.030) was 48%
larger than the absolute value of the analogous
coefficient for family structure (bstdX = .020, p < .05)
and 40% smaller than the analogous coefficient for
free lunch status (bstdX = �.048, p < .001). In the
density model, the three coefficients were compara-
ble in size (bstdX = �.010 for depressive symptoms,
.008 (p < .01) for family structure, and �.009
(p < .01) for free lunch status). In the reciprocity
model, the X-standardized coefficient for depres-
sive symptoms (bstdX = �.015) was more than dou-
ble the analogous coefficient for free lunch status
(bstdX = �.007, p < .05); family structure was not a
significant predictor of reciprocity.

In contrast with the findings on depressive
symptoms, groups with higher average anxiety
symptoms had greater reciprocity of friendships.
The X-standardized version of this coefficient
(bstdX = .014) was nearly double the absolute value
of that for free lunch status (bstdX = �.007).
Although the coefficients predicting group size and
density from group anxiety symptoms also were
positive, neither was statistically significant.
We next examined the associations of within-
group variation in internalizing symptoms with
groups’ size and structure. Table 3 shows that groups
with more variability among members in depressive
symptoms were less cohesive in terms of density,
but depressive symptom variability did not signifi-
cantly predict group size, reciprocity, or transitivity.
The findings for anxiety symptom variability were
very mixed. Specifically, anxiety symptom variabil-
ity positively predicted group size, negatively pre-
dicted density, did not predict reciprocity, and
positively predicted transitivity.
Sensitivity Analyses
We ran a series of ancillary analyses to determine
whether our main findings varied across grade
level or gender composition of the friendship
group. For example, to determine whether the
group-level effects of average distress on group
size differed by grade, we added two interaction
terms to the first model in Table 2, namely average
depressive symptoms 9 grade and average anxiety
symptoms 9 grade. Of the 48 resultant interaction
terms, only one was statistically significant: Vari-

ability in anxiety symptoms was negatively associ-
ated with group density only for all-female groups.
Because of the large number of tests run we urge
TABLE 2
Negative Binomial and Linear Random Effects Regression
Coefficients Predicting Adolescent Friendship Groups’
Cohesiveness From
Group Members’ Average Levels of Depressive and Anxiety
Symptoms (N = 3,013 Groups)
Predictor
Outcome
Group sizea Group density Group reciprocity Group transitivity
b (SE) b (SE) b (SE) b (SE)
Average depressive symptoms �.15 (.07)* �.05 (.02)* �.08
(.02)** �.04 (.03)
Average anxiety symptoms .03 (.06) .03 (.02) .06 (.02)** �.01
(.02)
Notes. All models included a variance component for school and
controlled for grade, intervention condition, group gender
compo-
sition, and group members’ race/ethnicity, family structure, and
free lunch eligibility. The reciprocity and transitivity models
also con-
trolled for density.
aNegative binomial coefficients shown; linear coefficients
shown for all other models.
*p < .05, **p < .01, ***p < .001.
Source: PROSPER Peers Study

caution in interpreting this single significant inter-
action.
DISCUSSION
Although adolescents with depressive symptoms
have more than their share of peer problems (Chan
& Poulin, 2009; Kochel et al., 2012; Rose et al., 2011),
they also tend to cluster together in friendship
groups, and we know little about the qualities of
those groups. This study went beyond past work on
depressed adolescents’ dyadic friendships, and their
individual statuses in larger social networks, to
reveal that friendship groups comprised of adoles-
cents with more depressive symptoms are smaller
and “looser,” or less tight-knit, than groups charac-
terized by lower depressive symptoms. That is, their
groups are composed of fewer adolescents, and the
members are less likely to all be friends with each
other. These associations were modest, but the effect
sizes were comparable to those of known demo-
graphic correlates of friendship quality, namely
family structure and socioeconomic status.
Our findings perhaps contradict what might be
expected based on theories of friendship formation
between adolescents with depressive symptoms.
For example, these friendships may form because
adolescents with these symptoms have a preference
for each other as friends (selection or homophily;
Kiuru et al., 2012; Van Zalk et al., 2010). Friends
also might change over time to become more like

each other in terms of depressive symptoms (so-
cialization or influence; Mercer & Derosier, 2010;
Prinstein, 2007; Stevens & Prinstein, 2005). Indeed,
past research suggests that both processes are
likely at play (Hogue & Steinberg, 1995). With
friends specifically choosing each other on the basis
of their depression and then changing to further
mirror each other’s depression, we might predict
that their friendship groups would be no less cohe-
sive than the typical adolescent friendship. Yet our
findings suggest that this is not the case.
Our findings also contrast with a small body of
literature suggesting that interpersonal processes
associated with depression, such as co-rumination,
can enhance adolescent friendships (Rose, 2002;
Rose, Carlson, & Waller, 2007). They especially
contrast with a recent study that found that inter-
nalizing symptoms themselves, and not necessarily
any specific behavior associated with those symp-
toms, predicted higher dyadic friendship quality
(Hill & Swenson, 2014). We offer two possible
explanations for the divergent findings. First,
whereas other studies have examined perceived
dyadic friendship quality, we examined friendship
group size and structure. It is possible that even if
their groups’ structures are weaker, adolescents
with depressive symptoms can still experience sub-
jectively high friendship quality in specific friend-
ships within their friendship groups.
Second, many of the past studies that found
benefits of depressive symptoms for friendships
examined broad scales of internalizing symptoms
(Hill & Swenson, 2014; Rose, 2002). We separated

depressive from anxiety symptoms, and found
that the two had distinct associations with group
cohesiveness. First, anxiety symptoms were gener-
ally less predictive of group cohesiveness than
depressive symptoms. Second, whereas higher
average depressive symptoms were negatively
associated with cohesion, higher average anxiety
symptoms were associated with greater reciprocity
of group members’ friendships. This indicates that
anxiety symptoms may not be as damaging to
TABLE 3
Negative Binomial and Linear Random Effects Regression
Coefficients Predicting Adolescent Friendship Groups’
Cohesiveness From
Within-Group Variation in Depressive and Anxiety Symptoms
(N = 3,013 Groups)
Predictor
Outcome
Group sizea Group density Group reciprocity Group transitivity
b (SE) b (SE) b (SE) b (SE)
Variation in depressive symptoms .08 (.06) �.07 (.02)*** �.04
(.02) .01 (.02)
Variation in anxiety symptoms .28 (.07)*** �.07 (.02)** .04
(.02) .06 (.03)*
Notes. All models included a variance component for school and
controlled for grade, intervention condition, group gender
compo-
sition, and group members’ race/ethnicity, family structure, and
free lunch eligibility. The reciprocity and transitivity models

also
controlled for density.
aNegative binomial coefficients shown; linear coefficients
shown for all other models.
*p < .05, **p < .01, ***p < .001.
Source: PROSPER Peers Study.
friendship group structure as are depressive symp-
toms, and it is consistent with past work showing
that anxiety may not harm, and may under some
conditions actually enhance, adolescents’ friend-
ships (Chen et al., 2009; de Matos et al., 2003; Rose
et al., 2011).
Our findings are consistent with work showing
that group emotions, or the “content” of groups—
here, members’ internalizing symptoms—have
implications for the “structure” of those groups
(Rubin et al., 2015, p. 350). Theoretically, this is
because group affect can undermine group pro-
cesses such as communication and cooperation, thus
interfering with group bonding (Kelly & Jones,
2012; Spoor & Kelly, 2004). The logical next ques-
tions for research are (1) do these group processes
in fact mediate the association of depressive symp-
toms with group structure, and (2) what are the
implications of these processes and structure for
key functions of peer groups, such as peer support
and peer influence? For example, friendship groups
characterized by weaker internal ties may be less
effective at protecting and defending their members
against victimization by other peers, which

depressed youth are more likely to experience
(Kaltiala-Heino et al., 2010; Kochel et al., 2012).
Future studies should examine whether friendship
groups composed of more depressed adolescents
indeed appear worse on dimensions such as com-
munication, cooperation, conflict, and supportive-
ness. Future research also should test whether the
weaker group bonds among adolescents with
depressive symptoms paradoxically have protective
effects on other forms of problem behavior by
undermining the group processes that facilitate that
behavior. For instance, poor within-group commu-
nication could hamper the within-group spread of
attitudes favorable toward substance use. Although
depressive symptoms in adolescents are associated
with such attitudes (Siennick, Widdowson, Woess-
ner, Feinberg, & Spoth, 2017), perhaps the associa-
tion would be stronger if these adolescents were
embedded in tight-knit groups.
We found only partial support for the idea that
friendship groups with greater variability in inter-
nalizing symptoms would be less internally cohe-
sive. Variability in depressive symptoms was
negatively associated with group density, but not
with group size, reciprocity, or transitivity. Vari-
ability in anxiety symptoms did not consistently
predict group cohesiveness in one direction or the
other. The support for this hypothesis was weaker
than we would expect given the general finding
that adolescents tend to prefer friends with similar
levels of depression (Kiuru et al., 2012; Van Zalk
et al., 2010) and social anxiety (Van Zalk, Van Zalk,
Kerr, et al., 2011). It also is weaker than we would
expect given past work showing that people prefer

others with similar moods and affect (Bl€ote et al.,
2012; Chow et al., 2015; Hafen et al., 2011). Perhaps
at the friendship group level, dissimilarity in inter-
nalizing symptoms does not consistently make
group interactions less validating or interfere with
communication, cooperation, and other group
bonding processes, even if global depressive symp-
toms do.
Our study had limitations. First, there is the pos-
sibility of reverse causality, such that qualities of
friendship groups predict group internalizing
symptoms rather than the other way around. We
believe that this concern is mitigated by our mea-
surement of symptoms of depression and anxiety
during the 6 months prior to the survey and of
qualities of friendship groups at the time of the
survey. In addition, our proposed direction of
causality is consistent with recent longitudinal find-
ings that depression influences friendship forma-
tion (Schaefer et al., 2011). Still, future studies
should examine the impact of friendship group
tight-knittedness on internalizing symptoms, and
test for possible reciprocal associations. Second, our
sample was from rural and predominately White
school districts with large proportions of low-
income families. The advantage of this sample is
that the communities included in the study were
served by one public high school each, increasing
the chances that the social networks we mapped
captured adolescents’ entire friendship pools. Still,
future research should examine whether our results
generalize to different populations.
Another limitation of this study is that the items
we used to create our measures were only subsets

of the items that could possibly have been included
and thus our measures did not capture the full
spectrum of mood and anxiety symptoms. More-
over, we were unable to examine potentially rele-
vant problems such as social anxiety, which might
affect friendship group structure differently than
general anxiety. Indeed, one study found that
youth with social anxiety disorders had fewer close
friends, greater difficulty making friends, and
poorer quality peer interactions, compared to their
nonanxious counterparts (Alfano, Beidel, & Wong,
2011). In contrast, youth with general anxiety disor-
ders appeared more similar than not to the control
group, with the exception that anxious youth had
fewer friends overall than nonanxious youth
(Alfano et al., 2011). This suggests that social
anxiety might be more damaging than general anx-
iety, and thus groups comprised of socially anxious
youth might potentially be less cohesive than
groups formed by youth with general anxiety.
Our study is also limited by the use of self-report
measures of depressive and anxiety symptoms. Self-
report measures are prone to error due to over or
underreporting of behaviors, which could potentially
bias the results. Future studies should consider using
parent or teacher ratings to determine whether our
findings differ based on how adolescents’ depressive
or anxiety symptoms are measured. Also, because
our measures were not based on clinical diagnoses of
depression or anxiety, our results do not necessarily

apply to adolescents with clinical levels of depression
or anxiety. Lastly, the friendship groups we created
were mutually exclusive, and it is possible that some
adolescents may identify with multiple groups.
These “bridges” or “liaisons” are believed to play a
critical role in the diffusion of behaviors and informa-
tion between groups (Ennett & Bauman, 1996). Thus,
the groups they bridge could grow more similar to
each other in terms of depressive or anxiety symp-
toms. Moreover, it is possible that these adolescents
were less integrated into the groups to which they
were assigned. To the extent that they have different
levels of anxiety and depressive symptoms than do
core group members, this could have influenced our
results. Future research should examine whether
such friendship group liaisons do indeed differ in
levels of symptoms compared to core group mem-
bers, and whether their social position influences the
cohesiveness of the groups with which they identify.
Friendship groups are important because they
provide adolescents with sources of belongingness
and identity, and serve as channels for the spread of
information and peer influence (Brechwald & Prin-
stein, 2011; Ellis & Zarbatany, 2007; Simons-Morton
& Farhat, 2010). Our findings suggest that even
when adolescents with depressive symptoms, who
often are already socially marginalized, manage to
form friendship groups, those groups are not exact
substitutes for “typical” adolescent friendship
groups in terms of cohesiveness. This study extends
to the group level past work on the harmful effects
of depressive symptoms on peer relations, and in
doing so highlights the relevance of group structure
for our understanding of the social network statuses
of adolescents with depression.

REFERENCES
Agoston, A. M., & Rudolph, K. D. (2013). Pathways from
depressive symptoms to low social status. Journal of
Abnormal Child Psychology, 41(2), 295–308. https://doi.
org/10.1007/s10802-012-9675-y
Alfano, C., Beidel, D., & Wong, N. (2011). Children with
generalized anxiety disorder do not have peer prob-
lems, just fewer friends. Child Psychiatry and Human
Development, 42(6), 712–723. https://doi.org/doi:10.
1007/s10578-011-0245-2
Altmann, E. O., & Gotlib, I. H. (1988). The social behav-
ior of depressed children: An observational study.
Journal of Abnormal Child Psychology, 16(1), 29–44.
https://doi.org/10.1007/BF00910498
American Psychiatric Association. (2000). Diagnostic and
statistical manual of mental disorders (4th ed., text rev.).
Washington, DC: Author.
Baker, J. R., Hudson, J. L., & Taylor, A. (2014). An inves-
tigation into the lower peer liking of anxious than
nonanxious children. Journal of Anxiety Disorders, 28(6),
599–611. https://doi.org/10.1016/j.janxdis.2014.06.007
Berger, C. R., & Calabrese, R. J. (1975). Some explorations
in initial interactions and beyond: Toward a develop-
mental theory of interpersonal communication. Human
Communication Research, 1(2), 99–112. https://doi.org/
10.1111/j.1468-2958.1975.tb00258.x
Bl€ote, A. W., Bokhorst, C. L., Miers, A. C., & Westenberg, P.

M. (2012). Why are socially anxious adolescents rejected
by peers? The role of subject-group similarity character-
istics. Journal of Research on Adolescence, 22(1), 123–134.
https://doi.org/10.1111/j.1532-7795.2011.00768.x
Brechwald, W. A., & Prinstein, M. J. (2011). Beyond
homophily: A decade of advances in understanding
peer influence processes. Journal of Research on Adoles-
cence, 21(1), 166–179. https://doi.org/10.1111/j.1532-
7795.2010.00721.x
Buhrmester, D. (1990). Intimacy of friendship, interper-
sonal competence, and adjustment during preadoles-
cence and adolescence. Child Development, 61(4),
1101–1111. https://doi.org/10.1111/j.1467-8624.1990.tb
02844.x
Chan, A., & Poulin, F. (2009). Monthly instability in early
adolescent friendship networks and depressive symp-
toms. Social Development, 18(1), 1–23. https://doi.org/
10.1111/j.1467-9507.2008.00461.x
Cheadle, J. E., & Goosby, B. J. (2012). The small-school
friendship dynamics of adolescent depressive symp-
toms. Society and Mental Health, 2(2), 99–119. https://d
oi.org/10.1177/2156869312445211
Chen, H., Cohen, P., Johnson, J. G., & Kasen, S. (2009).
Psychiatric disorders during adolescence and relation-
ships with peers from age 17 to age 27. Social Psychia-
try and Psychiatric Epidemiology, 44(3), 223–230.
https://doi.org/10.1007/s00127-008-0421-2
Chow, C. M., Tan, C. C., & Ruhl, H. (2015). Misery loves
company: A dyadic approach to examining the effects
of depressive symptoms on friendship discord. Journal

of Social and Clinical Psychology, 34(9), 774–787.
https://doi.org/10.1521/jscp.2015.34.9.774
Coyne, J. C. (1976). Toward an interactional description
of depression. Psychiatry: Interpersonal and Biological
https://doi.org/10.1007/s10802-012-9675-y
https://doi.org/10.1007/s10802-012-9675-y
https://doi.org/doi:10.1007/s10578-011-0245-2
https://doi.org/doi:10.1007/s10578-011-0245-2
https://doi.org/10.1007/BF00910498
https://doi.org/10.1016/j.janxdis.2014.06.007
https://doi.org/10.1111/j.1468-2958.1975.tb00258.x
https://doi.org/10.1111/j.1532-7795.2011.00768.x
https://doi.org/10.1111/j.1532-7795.2010.00721.x
https://doi.org/10.1111/j.1532-7795.2010.00721.x
https://doi.org/10.1111/j.1467-9507.2008.00461.x
https://doi.org/10.1111/j.1467-9507.2008.00461.x
https://doi.org/10.1177/2156869312445211
https://doi.org/10.1177/2156869312445211
https://doi.org/10.1007/s00127-008-0421-2
Processes, 39(1), 28–40. https://doi.org/10.1080/
00332747.1976.11023874
Cummings, C. M., Caporino, N. E., & Kendall, P. C.
(2014). Comorbidity of anxiety and depression in chil-
dren and adolescents: 20 years after. Psychological Bul-
letin, 140(3), 816–845. https://doi.org/10.1037/

a0034733
de Matos, M. G., Barrett, P., Dadds, M., & Shortt, A.
(2003). Anxiety, depression, and peer relationships
during adolescence: Results from the Portuguese
national health behaviour in school-aged children sur-
vey. European Journal of Psychology of Education, 18(1),
3–14. https://doi.org/10.1007/BF03173600
De�girmencio�glu, S. M., Urberg, K. A., Tolson, J. M., &
Richard, P. (1998). Adolescent friendship networks:
Continuity and change over the school year. Merrill-
Palmer Quarterly, 44(3), 313–337. https://doi.org/10.
4319/lo.2013.58.2.0489
Ellis, W. E., & Zarbatany, L. (2007). Peer group status as
a moderator of group influence on children’s deviant,
aggressive, and prosocial behavior. Child Development,
78(4), 1240–1254. https://doi.org/10.1111/j.1467-8624.
2007.01063.x
Ennett, S. T., & Bauman, K. E. (1996). Adolescent social
networks: School, demographic, and longitudinal con-
siderations. Journal of Adolescent Research, 11(2), 194–
215. https://doi.org/10.1177/0743554896112003
Gest, S. D., Davidson, A. L., Rulison, K. L., Moody, J., &
Welsh, J. A. (2007). Features of groups and status hier-
archies in girls’ and boys’ early adolescent peer net-
works. New Directions for Child and Adolescent
Development, 118, 42–60. https://doi.org/10.1002/cd
Giletta, M., Scholte, R. H. J., Burk, W. J., Engels, R. C. M.
E., Larsen, J. K., Prinstein, M. J., & Ciairano, S. (2011).
Similarity in depressive symptoms in adolescents’
friendship dyads: Selection or socialization? Develop-

mental Psychology, 47(6), 1804–1814. https://doi.org/10.
1037/a0023872
Hafen, C. A., Laursen, B., Burk, W. J., Kerr, M., & Stattin,
H. (2011). Homophily in stable and unstable adoles-
cent friendships: Similarity breeds constancy. Personal-
ity and Individual Differences, 51, 607–612. https://doi.
org/10.1016/j.paid.2011.05.027
Hill, E. N., & Swenson, L. P. (2014). Perceptions of
friendship among youth with distressed friends. Child
Psychiatry and Human Development, 45(1), 99–109.
https://doi.org/10.1007/s10578-013-0381-y
Hogue, A., & Steinberg, L. (1995). Homophily of internal-
ized distress in adolescent peer groups. Developmental
Psychology, 31, 897–906. https://doi.org/10.1037/0012-
1649.31.6.897
Kaltiala-Heino, R., Fr€ojd, S., & Marttunen, M. (2010).
Involvement in bullying and depression in a 2-year
follow-up in middle adolescence. European Child and
Adolescent Psychiatry, 19(1), 45–55. https://doi.org/10.
1007/s00787-009-0039-2
Kelly, J. R., & Jones, E. (2012). Investigating emotions
and affect in groups. In A. B. Hollingshead & M. S.
Poole (Eds.), Research methods for studying groups and
teams: A guide to approaches, tools, and technologies (pp.
154–172). New York: Taylor & Francis/Routledge.
Kennedy, E., Spence, S. H., & Hensley, R. (1989). An
examination of the relationship between childhood
depression and social competence amongst primary
school children. Journal of Child Psychology and Psychia-

try, and Allied Disciplines, 30(4), 561–573. https://doi.
org/10.1111/j.1469-7610.1989.tb00268.x
Kiuru, N., Burk, W. J., Laursen, B., Nurmi, J. E., & Sal-
mela-Aro, K. (2012). Is depression contagious? A test
of alternative peer socialization mechanisms of depres-
sive symptoms in adolescent peer networks. Journal of
Adolescent Health, 50(3), 250–255. https://doi.org/10.
1016/j.jadohealth.2011.06.013
Kochel, K. P., Ladd, G. W., & Rudolph, K. D. (2012). Lon-
gitudinal associations among youth depressive symp-
toms, peer victimization, and low peer acceptance: An
interpersonal process perspective. Child Development,
83(2), 637–650. https://doi.org/10.1111/j.1467-8624.
2011.01722.x
Kreager, D. A., Rulison, K., & Moody, J. (2011). Delin-
quency and the structure of adolescent peer groups.
Criminology, 49(1), 95–127. https://doi.org/10.1111/j.
1745-9125.2010.00219.x
Mcleod, J. D., & Uemura, R. (2012). Substance use, dis-
tress, and adolescent school networks. Journal of
Research on Adolescence, 22(3), 438–452. https://doi.
org/10.1111/j.1532-7795.2012.00787.x
Mercer, S. H., & Derosier, M. E. (2010). Selection and
socialization of internalizing problems in middle child-
hood. Journal of Social and Clinical Psychology, 29(9),
1031–1056. https://doi.org/10.1521/jscp.2010.29.9.1031
Moody, J. (2001). Peer influence groups: Identifying dense
clus-
ters in large networks. Social Networks, 23(4), 261–283.
https://doi.org/10.1016/S0378-8733(01)00042-9

Prinstein, M. J. (2007). Moderators of peer contagion: A
longitudinal examination of depression socialization
between adolescents and their best friends. Journal of
Clinical Child and Adolescent Psychology, 36(2), 159–170.
https://doi.org/10.1080/15374410701274934
Prinstein, M. J., Borelli, J. L., Cheah, C. S. L., Simon, V.
A., & Aikins, J. W. (2005). Adolescent girls’ interper-
sonal vulnerability to depressive symptoms: A longitu-
dinal examination of reassurance-seeking and peer
relationships. Journal of Abnormal Psychology, 114(4),
676–688. https://doi.org/10.1037/0021-843X.114.4.676
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear
models: Applications and data analysis methods. Thousand
Oaks, CA: Sage.
Rook, K. S., Pietromonaco, P. R., & Lewis, M. A. (1994). When
are dysphoric individuals distressing to others and vice
versa? Effects of friendship, similarity, and interaction task.
Journal of Personality and Social Psychology, 67(3), 548–559.
https://doi.org/10.1037/0022-3514.67.3.548
Rose, A. J. (2002). Co-rumination in the friendships of
girls and boys. Child Development, 73(6), 1830–1843.
https://doi.org/10.1111/1467-8624.00509
https://doi.org/10.1080/00332747.1976.11023874
https://doi.org/10.1080/00332747.1976.11023874
https://doi.org/10.1037/a0034733
https://doi.org/10.1037/a0034733
https://doi.org/10.1007/BF03173600
https://doi.org/10.4319/lo.2013.58.2.0489

https://doi.org/10.4319/lo.2013.58.2.0489
https://doi.org/10.1111/j.1467-8624.2007.01063.x
https://doi.org/10.1111/j.1467-8624.2007.01063.x
https://doi.org/10.1177/0743554896112003
https://doi.org/10.1002/cd
https://doi.org/10.1037/a0023872
https://doi.org/10.1037/a0023872
https://doi.org/10.1016/j.paid.2011.05.027
https://doi.org/10.1016/j.paid.2011.05.027
https://doi.org/10.1007/s10578-013-0381-y
https://doi.org/10.1037/0012-1649.31.6.897
https://doi.org/10.1037/0012-1649.31.6.897
https://doi.org/10.1007/s00787-009-0039-2
https://doi.org/10.1007/s00787-009-0039-2
https://doi.org/10.1016/j.jadohealth.2011.06.013
https://doi.org/10.1111/j.1467-8624.2011.01722.x
https://doi.org/10.1111/j.1467-8624.2011.01722.x
https://doi.org/10.1111/j.1745-9125.2010.00219.x
https://doi.org/10.1111/j.1745-9125.2010.00219.x
https://doi.org/10.1111/j.1532-7795.2012.00787.x
https://doi.org/10.1111/j.1532-7795.2012.00787.x
https://doi.org/10.1016/S0378-8733(01)00042-9
https://doi.org/10.1080/15374410701274934
https://doi.org/10.1037/0021-843X.114.4.676
https://doi.org/10.1037/0022-3514.67.3.548
https://doi.org/10.1111/1467-8624.00509
Rose, A. J., Carlson, W., & Waller, E. M. (2007). Prospec-
tive associations of co-rumination with friendship and
emotional adjustment: Considering the socioemotional
trade-offs of co-rumination. Developmental Psychology,

43(4), 1019. https://doi.org/10.1037/0012-1649.43.4.
1019
Rose, A. J., Carlson, W., Luebbe, A. M., Schwartz-Mette,
R. A., Smith, R. R., & Swenson, L. P. (2011). Predicting
difficulties in youth’s friendships: Are anxiety symp-
toms as damaging as depressive symptoms? Merrill-
Palmer Quarterly, 57(3), 244–262. https://doi.org/10.
1353/mpq.2011.0013
Rosenblatt, A., & Greenberg, J. (1991). Examining the
world of the depressed: Do depressed people prefer
others who are depressed? Journal of Personality and
Social Psychology, 60(4), 620–629. https://doi.org/10.
1037/0022-3514.60.4.620
Rubin, D. B. (1987). Multiple imputation for nonresponse in
surveys. New York, NY: John Wiley & Sons. https://d
oi.org/10.1002/SERIES1345
Rubin, K. H., Bukowski, W. M., & Bowker, J. C. (2015).
Children in peer groups. In M. H. Bornstein, T.
Leventhal & R. M. Lerner (Eds.), Handbook of child psy-
chology and developmental science, volume 4, ecological set-
tings and processes (Vol. 4(October), pp. 175–222).
Hoboken, NJ: John Wiley & Sons. https://doi.org/10.
1002/9781118963418.childpsy405
Rudolph, K. D., Hammen, C., & Burge, D. (1994). Inter-
personal functioning and depressive symptoms in
childhood: Addressing the issues of specificity and
comorbidity. Journal of Abnormal Child Psychology, 22
(3), 355–371. https://doi.org/10.1007/BF02168079
Schaefer, D. R., Kornienko, O., & Fox, A. M. (2011). Mis-
ery does not love company: Network selection mecha-

nisms and depression homophily. American Sociological
Review, 76(5), 764–785. https://doi.org/10.1177/
00031224
11420813
Schwartz-Mette, R. A., & Rose, A. J. (2016). Depressive
symptoms and conversational self-focus in adolescents’
friendships. Journal of Abnormal Child Psychology, 44(1),
87–100. https://doi.org/10.1007/s10802-015-9980-3
Siennick, S. E., Widdowson, A. O., Woessner, M. K.,
Feinberg, M. E., & Spoth, R. L. (2017). Risk factors for
substance misuse and adolescents’ symptoms of
depression. Journal of Adolescent Health, 60(1), 50–56.
Simons-Morton, B. G., & Farhat, T. (2010). Recent find-
ings on peer group influences on adolescent smoking.
Journal of Primary Prevention, 31(4), 191–208. https://d
oi.org/10.1007/s10935-010-0220-x
Spoor, J. R., & Kelly, J. R. (2004). The evolutionary signif-
icance of affect in groups: Communication and group
bonding. Group Processes & Intergroup Relations, 7(4),
398–412. https://doi.org/10.1177/1368430204046145
Spoth, R., Greenberg, M., Bierman, K., & Redmond, C.
(2004). PROSPER community-university partnerships
model for public education systems: Capacity-building
for evidence-based, competence-building prevention.
Prevention Science, 5(1), 31–39. https://doi.org/10.
1023/B:PREV.0000013979.52796.8b
Spoth, R., Redmond, C., Shin, C., Greenberg, M., Fein-
berg, M., & Schainker, L. (2013). PROSPER commu-
nity-university partnership delivery system effects on

substance misuse through 6 1/2 years past baseline
from a cluster randomized controlled intervention
trial. Preventive Medicine, 56(3–4), 190–196. https://doi.
org/10.1016/j.ypmed.2012.12.013
Stevens, E. A., & Prinstein, M. J. (2005). Peer contagion of
depressogenic attributional styles among adolescents:
A longitudinal study. Journal of Abnormal Child Psychol-
ogy, 33(1), 25–37. https://doi.org/10.1007/s10802-005-
0931-2
Stice, E., Ragan, J., & Randall, P. (2004). Prospective rela-
tions between social support and depression: Differen-
tial direction of effects for parent and peer support?
Journal of Abnormal Psychology, 113(1), 155–159.
https://doi.org/10.1037/0021-843X.113.1.155
Strauss, C. C., Lahey, B. B., Frick, P., Frame, C. L., &
Hynd, G. W. (1988). Peer social status of children with
anxiety disorders. Journal of Consulting and Clinical Psy-
chology, 56(1), 137–141. https://doi.org/10.1037/0022-
006X.56.1.137
Van Zalk, M. H. W., Kerr, M., Branje, S. J. T., Stattin, H.,
& Meeus, W. H. J. (2010). It takes three: Selection,
influence, and de-selection processes of depression in
adolescent friendship networks. Developmental Psychol-
ogy, 46(4), 927–938. https://doi.org/10.1037/a0019661
Van Zalk, N., Van Zalk, M. H. W., & Kerr, M. (2011).
Socialization of social anxiety in adolescent crowds.
Journal of Abnormal Child Psychology, 39(8), 1239–1249.
https://doi.org/10.1007/s10802-011-9533-3
Van Zalk, N., Van Zalk, M., Kerr, M., & Stattin, H.
(2011). Social anxiety as a basis for friendship selection

and socialization in adolescents’ social networks. Jour-
nal of Personality, 79(3), 499–526. https://doi.org/10.
1111/j.1467-6494.2011.00682.x
Wright, J. C., Giammarino, M., & Parad, H. W. (1986).
Social status in small groups: Individual group similar-
ity and the social “misfit”. Journal of Personality and
Social Psychology, 50(3), 523–536. https://doi.org/10.
1037/0022-3514.50.3.523
https://doi.org/10.1037/0012-1649.43.4.1019
https://doi.org/10.1037/0012-1649.43.4.1019
https://doi.org/10.1353/mpq.2011.0013
https://doi.org/10.1353/mpq.2011.0013
https://doi.org/10.1037/0022-3514.60.4.620
https://doi.org/10.1037/0022-3514.60.4.620
https://doi.org/10.1002/SERIES1345
https://doi.org/10.1002/SERIES1345
https://doi.org/10.1002/9781118963418.childpsy405
https://doi.org/10.1002/9781118963418.childpsy405
https://doi.org/10.1007/BF02168079
https://doi.org/10.1177/0003122411420813
https://doi.org/10.1177/0003122411420813
https://doi.org/10.1177/0003122411420813
https://doi.org/10.1007/s10802-015-9980-3
https://doi.org/10.1007/s10935-010-0220-x
https://doi.org/10.1007/s10935-010-0220-x
https://doi.org/10.1177/1368430204046145
https://doi.org/10.1023/B:PREV.0000013979.52796.8b
https://doi.org/10.1023/B:PREV.0000013979.52796.8b
https://doi.org/10.1016/j.ypmed.2012.12.013
https://doi.org/10.1016/j.ypmed.2012.12.013
https://doi.org/10.1007/s10802-005-0931-2

https://doi.org/10.1007/s10802-005-0931-2
https://doi.org/10.1037/0021-843X.113.1.155
https://doi.org/10.1037/0022-006X.56.1.137
https://doi.org/10.1037/0022-006X.56.1.137
https://doi.org/10.1037/a0019661
https://doi.org/10.1007/s10802-011-9533-3
https://doi.org/10.1111/j.1467-6494.2011.00682.x
https://doi.org/10.1111/j.1467-6494.2011.00682.x
https://doi.org/10.1037/0022-3514.50.3.523
https://doi.org/10.1037/0022-3514.50.3.523
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