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Heterogeneity among adolescents with elevated depressive symptoms: distinct patterns of social and academic attributes

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Heterogeneity among adolescents with elevated depressive symptoms: distinct patterns of social and academic attributes

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HETEROGENEITY AMONG ADOLESCENTS WITH ELEVATED
DEPRESSIVE SYMPTOMS: DISTINCT PATTERNS OF SOCIAL AND
ACADEMIC ATTRIBUTES

by

Shelley R. Tom

_______________________________________________________________

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)

August 2010

Copyright 2010 Shelley R. Tom
ii
TABLE OF CONTENTS
List of Tables iii
List of Figures iv
Abstract vi
Chapter One: Introduction 1
Chapter Two: Method 14
Chapter Three: Results 21
Chapter Four: Discussion 45
References 58
Appendix: Survey Packet of Study Measures 68
iii
LIST OF TABLES
Table 1: Descriptive Statistics for the Measures (N = 336) 22
Table 2: Bivariate Correlations among All Variables (N = 336) 24
Table 3: Cluster Analysis of Adolescents with Elevated Levels of 31
Depressive Symptoms
iv
LIST OF FIGURES
Figure 1: Scatter plot depicting the association between peer 25
nomination scores for popularity and self-reported
depressive symptoms

Figure 2: Scatter plot depicting the association between peer 26
nomination scores for social preference and self-reported
depressive symptoms

Figure 3: Scatter plot depicting the association between peer 27
nomination scores for friendship and self-reported
depressive symptoms

Figure 4: Scatter plot depicting the association between scores for 28
grade point average and self-reported depressive symptoms

Figure 5: Bar graph depicting mean scores for popularity for each 34
subgroup of adolescents with elevated levels of depressive
symptoms and normative contrast group

Figure 6: Bar graph depicting mean scores for social preference for 35
each subgroup of adolescents with elevated levels of
depressive symptoms and normative contrast group

Figure 7: Bar graph depicting mean scores for friendship for each 36
subgroup of adolescents with elevated levels of depressive
symptoms and normative contrast group

Figure 8: Bar graph depicting mean scores for relational aggression 37
for each subgroup of adolescents with elevated levels of
depressive symptoms and normative contrast group

Figure 9: Bar graph depicting mean scores for overt aggression for 38
each subgroup of adolescents with elevated levels of
depressive symptoms and normative contrast group

Figure 10: Bar graph depicting mean scores for relational victimization 39
for each subgroup of adolescents with elevated levels of
depressive symptoms and normative contrast group.
v
Figure 11: Bar graph depicting mean scores for overt victimization for 40
each subgroup of adolescents with elevated levels of
depressive symptoms and normative contrast group

Figure 12: Bar graph depicting mean scores for dependency for each 41
subgroup of adolescents with elevated levels of depressive
symptoms and normative contrast group

Figure 13: Bar graph depicting mean scores for social anxiety for each 42
subgroup of adolescents with elevated levels of depressive
symptoms and normative contrast group

Figure 14: Bar graph depicting mean scores for grade point average for 43
each subgroup of adolescents with elevated levels of depressive
symptoms and normative contrast group

Figure 15: Bar graph depicting mean scores for academic engagement for 44
each subgroup of adolescents with elevated levels of depressive
symptoms and normative contrast group.
vi
ABSTRACT
This study utilized a cross-sectional, multi-informant approach to examine a
typology of adolescents who are experiencing elevated depressive symptoms.
Participants were 336 predominantly Asian-American adolescents (167 males, 169
females; mean age = 14.99 years) from a high school in Hawaii. Adolescents
completed a peer nomination inventory assessing popularity, social preference,
friendship, aggression, and peer victimization. Self-report measures assessed
dependency, social anxiety, academic engagement, and depressive symptoms, and
data on academic achievement were obtained from school records. Among
adolescents who were high in depressive symptoms, one subgroup was popular and
had a mixed pattern of behavioral and academic adjustment, one subgroup was high
in academics but low in social impact, and one subgroup was both aggressive and
rejected in the peer group. The overall pattern of findings with an ethnically
underrepresented population highlights the need to consider heterogeneity among
youth who report high levels of depressive symptoms in adolescence.

1
CHAPTER ONE
INTRODUCTION
In investigating depressive symptoms in children and adolescents, many
researchers have focused on the influence of academic and peer group experiences.
Academics and social relationships are important domains to consider in adolescence
because they represent salient developmental tasks during this stage of development
(Masten, 2005; Masten et al., 2005). During adolescence, major shifts occur in the
importance of the peer group, including increasing intimacy in dyadic friendships
(Berndt, 1982), the growth of peer networks and crowds (Brown, 1990; Cairns &
Cairns, 1994), and a heightened concern about peer approval in general (Eccles,
Midgley, Wigfield, & Buchanan, 1993). Academic performance also continues to be
important across adolescence and may impact future educational attainment and
employment (Smolensky et al., 2001). Indeed, academics and peer relations ranked
as the top two concerns reported by ninth graders in a study of the transition to high
school in the United States (Newman, Lohman, Newman, Myers, & Smith, 2000).
These critical tasks play a central role in overall adjustment, and failure could
indicate increased risk for problems such as internalizing (i.e., depression, anxiety,
and withdrawal) and externalizing behavior (i.e., aggression, delinquency, and
disruptive behaviors) (Masten et al., 2005; Patterson, Forgatch, Yoerger, &
Stoolmiller, 1998).
One theoretical perspective on depression posits that children and adolescents
regularly receive feedback regarding their competencies in different domains, and
2
that this feedback can have implications for their developing sense of self-worth
(Cole, 1991). According to this competency-based model, academics and social
relationships with peers represent central areas of functioning, and repeated negative
feedback in these domains may inhibit the development of positive self schemata.
Youth who internalize these negative messages about their competencies may
acquire maladaptive belief systems, potentially predisposing them for depressive
tendencies.
Other models on the development of depressive symptoms in childhood and
adolescence theorize that externalizing problems predict changes in internalizing
symptoms through failures in different areas of functioning (Capaldi, 1992; Kiesner,
2002). In Patterson and colleagues’ dual failure model, conduct-disordered
behaviors lead to academic and social failures that in turn contribute to depressive
symptoms and low self-esteem (Patterson, 1986; Patterson, Reid, & Dishion, 1992).
More pervasive than a lack of competence, the noxious behaviors of antisocial youth
are hypothesized to cause constant conflict with others, difficulties in the classroom,
and an increased vulnerability to depressed mood (Capaldi, 1992).
Another theoretical perspective on internalizing symptoms is Masten et al.’s
(2005) model of cascading effects. This model emphasizes the importance of
assessing multiple domains of behavior and the potential for cross-domain influence
over the course of development. Masten et al. propose that beginning in childhood,
externalizing behavior cascades to the academic domain and undermines academic
achievement across time. By adolescence, poor academic achievement is expected
3
to contribute to both externalizing and internalizing symptoms into young adulthood.
In this manner, externalizing problems can have both direct and indirect effects on
developmental outcomes. It is also possible that internalizing symptoms could
predict relative declines in externalizing behavior, as symptoms of social inhibition
or anxiety could counteract the growth of antisocial behavior in adolescence.
Empirical research in the past has generally found evidence for the role of
social and academic difficulties in adolescents’ risk for depression. Specifically,
depressive symptoms have been associated with several indicators of peer group
functioning including peer rejection (Prinstein & Aikins, 2004), low levels of
friendship (Rudolph, Ladd, & Dinella, 2007), low popularity (Sandstrom &
Cillessen, under review), peer aggression (Leadbeater, Boone, Sangster, &
Mathieson, 2006), and peer victimization (Hawker & Boulton, 2000). A growing
body of findings has also documented academic correlates of depressed affect
including low academic motivation (Gilman & Anderman, 2006), learning problems
(Dalley, Bolocofsky, Alcorn, & Baker, 1992), and poor grades (Gerard & Buehler,
2004; Shahar et al., 2006).
Although the existing findings regarding the correlates of depressive
symptoms during adolescence are convincing, there are some notable inconsistencies
in the literature. Mixed results have been found between adolescents’ functioning in
the peer group and indicators of dysphoric mood states (Luthar, 1995). Friendships
have also been shown to be associated with both positive (Berndt, 1996) and
negative adjustment (Fergusson, Wanner, Vitaro, Horwood, & Swain-Campbell,
4
2003). Likewise, a number of investigations with adolescent samples have shown
that academic problems are not necessarily linked to increases in depressive
symptomatology (Johnson, McGue, & Iacono, 2006; Luthar, 1995; Owens &
Newbegin, 2000).
One reason that may account for this heterogeneity in the literature is that
multiple profiles may exist among adolescents who self-report high levels of
depressive symptoms. Previous studies on the social and academic correlates of
depressive symptoms in adolescence did not consider subgroups and have generally
treated these youth as a uniform group (Gerard & Buehler, 2004; Luthar, 1995;
Prinstein & Aikins, 2004). However, it is possible that there are subgroups of youth
with depressive tendencies who have different experiences and distinct behavioral
and academic profiles. Past researchers have argued that an exclusive focus on
associations between adjustment variables at the aggregated sample-level may mask
a more complex set of findings (Lease, Kennedy, & Axelrod, 2002; Rodkin, Farmer,
Pearl, & Van Acker, 2000; Roeser, Eccles, & Freedman-Doan, 1999). For example,
correlational analyses alone could indicate average trends in the sample but miss the
presence of groups of individuals who show similar patterns of functioning across a
series of measures. These authors purport that cluster analysis is a necessary step in
detecting these subgroups of adolescents. A central objective in the current project
was to examine evidence for clusters of adolescents with elevated depressive
symptoms in terms of their peer relationships and academic functioning. It is
important to recognize the range of problems and needs of youth at risk for
5
depression if we are to further our understanding of this disorder and develop
appropriate interventions.
Past research has traditionally focused on a subgroup of youth with depressed
affect who are described as being both aggressive and rejected in the peer group
(Cillessen, van IJzendoorn, van Lieshout, & Hartup, 1992; Dodge, 1983; Panak &
Garber, 1992; Parkhurst & Asher, 1992). Members of the aggressive-rejected
subtype are often viewed as dysfunctional and display high levels of aggression
(Dodge, 1983). They have been characterized in the literature as highly disliked by
their classmates (Little & Garber, 1995), antisocial (Cole & Carpentieri, 1990), and
likely to experience peer victimization (Schwartz, 2000). Existing theoretical
perspectives suggest that problems with aggression predict impairments in the
development of social skills, which then lead to failures in social interactions and
subsequent depressive tendencies (Capaldi, 1992; Pedersen, Vitaro, Barker, &
Borge, 2007). Indeed, in a longitudinal study on the underlying processes
connecting these constructs, peer rejection was found to partially mediate the
association between aggressive behavior and later depressive symptoms (Panak &
Garber, 1992). Impairments in the social domain are paralleled by deficits in
academics as these youth also tend to do poorly in school (Toblin, Schwartz,
Gorman, & Abou-ezzeddine, 2005; Wentzel, 2003).
The link between an aggressive-rejected pattern and depressive symptoms
seems self-apparent. However, we also hypothesized that a subgroup of adolescents
who reported symptoms of depression would be characterized by high social
6
standing with peers. In their ethnographic work on the peer cultures of preadolescent
youth, Adler and Alder (1998) detailed the social worlds of popular children. These
authors described the potential cost associated with inclusion in the ‘in’ crowd, with
popular children engaging in persistent in-fighting to establish and maintain their
position in the social hierarchy. Given the social pressure inherent in their lifestyle,
popular youth might be at risk for depressive tendencies. In addition, high status
children in Adler and Adler’s studies often reported feeling isolated once they gained
admission into the popular clique since they had severed their relationships with low
status friends as a prerequisite to inclusion. Another potential risk of the social
pressures associated with popularity is disengagement from school. Particularly in
adolescence, popular youth have been found to have negative attitudes toward school
(Vitaro, Brendgen, & Wanner, 2005), and academic achievement may not be
compatible with values of the popular clique (Brown, 1990).
We also hypothesized that there would be a third subgroup of adolescents
with elevated depressive symptoms who would be characterized by their low social
impact in the peer group. Adler and Adler (1998) described a group of children who
were generally ignored by the rest of their peers. These youth were viewed as
“loners” who were unpopular and possessed few or no friends (Adler & Adler,
1998). Conceptually, this subgroup may correspond to the “neglected” social status
classification described by sociometric researchers (Asher & Wheeler, 1985; Coie,
Dodge, & Coppotelli, 1982; Dodge, 1983). Several researchers have observed that
while low impact youth are not necessarily disliked, their low social status affects
7
their ability to access relationships and be included in activities with their classmates
(Asher, Parker, & Walker, 1996; Dodge, 1983). Low impact adolescents may
therefore miss out on opportunities for friendship and dating, as well as the potential
for intimacy and social development that is possible in the context of these
relationships (Bukowski, Pizzamiglio, Newcomb, & Hoza, 1996; Parker & Asher,
1993). Adler and Adler further observed that low impact children longed to be
included in interactions with their peers. This subgroup may therefore be at risk for
depression because of their lack of companionship and their low self-perceived
competence with peers (Patterson, Kupersmidt, & Griesler, 1990). Academically,
low impact youth have been found to receive good grades and have been
characterized as “nerdy” (Adler & Adler, 1998; Wentzel & Asher, 1995).
Given the literature reviewed, a major goal of the current investigation was to
determine whether a three-cluster structure exists among adolescents who reported
high levels of depressive symptoms. Specifically, we hypothesized that we would
find one cluster of aggressive-rejected youth, a second cluster of high status youth,
and a third cluster of youth characterized by low social impact.
A second objective of this study was to build on past findings by examining
whether distinct patterns emerged across multiple assessments of social and
academic adjustment. A potential limitation of the existing literature is that previous
studies have generally measured only one dimension of peer group or academic
functioning at a time. However, this approach may underestimate the complexity of
how adolescents’ experiences relate to depressed mood states. To address this issue,
8
we assessed the social domain with measures of popularity and social preference
because they have been shown to offer unique contributions to adolescent
adjustment. While there is empirical overlap between popularity and social
preference as indicators of high social standing, research suggests that these two
constructs become increasingly more distinct in adolescence (Cillessen & Mayeux,
2004). As we have previously described, popularity is a reputational measure of
social influence and prestige, and is assessed by asking peers to identify the popular
students in their grade or class. Social preference, on the other hand, is defined as
being liked by many peers and disliked by few peers (Coie et al., 1982). Popular
youth are not necessarily well-liked (Rose, Swenson, & Waller, 2004), and
adolescents with high social preference scores as not necessarily deemed popular by
the peer group (Cillessen & Rose, 2005). High social preference tends to be linked
with positive behavioral attributes (Rubin, Bukowski, & Parker, 1998; Wentzel &
Erdley, 1993), whereas popularity is associated with a more mixed pattern of traits
and engagement in risky behaviors (Mayeux, Sandstrom, & Cillessen, 2008;
Prinstein, Meade, & Cohen, 2003). We were also interested in the role of friendship
since previous research has shown that friendship has a closer association with
depressive symptoms than social preference (Schwartz, Gorman, Duong, &
Nakamoto, 2008). Friendship contrasts with both popularity and social preference in
that it is conceptualized as a reciprocated, dyadic relationship rather than an indicator
of reputation in the larger peer group. Friendship involves an intimate relationship
9
between two individuals, and an adolescent who does not have high social status can
still have numerous friends.
Based on consistent links in the literature between popularity and peer
aggression and victimization, we incorporated measures of these forms of social
behavior (Cillessen & Mayeux, 2004; Prinstein & Cillessen, 2003). Items that
indexed aggression and victimization were also relevant to our investigation of
aggressive-rejected adolescents since past researchers have noted that these youth are
both the initiators and targets of aggressive behavior (Olson, 1992; Perry, Perry, &
Kennedy, 1993). Finally, we included assessments of dependency and social anxiety
to examine whether youth who are vulnerable to depressive symptoms varied in how
they viewed social relationships and interactions.
Similar to our multidimensional approach to adjustment in the peer group, we
examined school functioning with separate indicators of grade point averages
(GPAs) and academic engagement. Academic engagement measures are designed to
tap students’ behavior, cognitions, and feelings related to school compared to
measures of performance such as GPA. While the two constructs are positively
associated (Fredricks, Blumenfeld, & Paris, 2004), it is possible that problematic
peer experiences may affect an adolescent’s orientation toward school while not
immediately impacting his or her grades. Given the different meaning of academics
for each subgroup in previous investigations, we were particularly interested in the
role of academic functioning across clusters of adolescents with depressed affect.
10
In the current project, we hypothesized that we would find three subgroups
with distinct patterns of academic and peer group functioning among adolescents
with elevated depressive symptoms. We expected to find a cluster that corresponded
to the aggressive-rejected youth who were previously discussed. This subgroup
would primarily be characterized by elevated aggression, low social preference, low
levels of friendship, low scores on popularity, high levels of victimization, poor
grade point average, and low academic engagement. We also predicted that this
group would not report high levels of dependency or social anxiety as they tend to
engage in antisocial behavior and are generally not attuned to the social norms of the
peer group (Dodge, 1983).
We expected that a second cluster of youth with elevated depressive
symptoms would emerge that was similar to the popular group described by Adler
and Adler (1998). Adolescents in this cluster were hypothesized to score highly on
measures of popularity and aggression and poorly on measures of academic
achievement and engagement. Since social influence and relationships matter to this
subgroup of youth, we predicted that they would demonstrate elevated scores on
dependency and social anxiety. Furthermore, because past findings suggest that
popular youth frequently use manipulation and socially aggressive behaviors to
control other peers, we hypothesized that relational aggression would be more
relevant to this group than items measuring overt aggression (Cillessen & Mayeux,
2004; Rose et al., 2004).
11
A third cluster that we expected to find among youth with elevated
depressive symptoms was a subgroup that corresponded to the low social impact
group. We hypothesized that these adolescents would be characterized by low scores
on popularity, moderate scores on social preference, and high scores on grade point
average and academic engagement. Given that low impact adolescents desire
relationships but are typically unsuccessful in obtaining them, we also expected that
this group would show elevations on dependency and social anxiety.
We examined our hypotheses with a predominantly Asian-American sample
of adolescents in the context of Hawaii. Past research on depressive symptoms in
adolescence has primarily used European-American samples in the United States
(Accordino, Accordino, & Slaney, 2000; Johnson et al., 2006; Lefkowitz & Tesiny,
1980). However, the processes that lead to depressive tendencies may work
differently in other cultural settings. An exclusive focus on one culture could
overlook important differences in other settings in the patterns of associations and
the meaning of competence in areas such as academics and peer relationships
(Rubin, 1990; Weisz, McCarty, Eastman, Chaiyasit, & Suwanlert, 1997). The ability
to generalize past findings on depressive symptoms to other cultural settings is
important as it can inform the development of interventions for youth from diverse
backgrounds. Asian-American youth represent a historically understudied
population, despite belonging to one of the fastest growing minority groups in the
United States (U.S. Census Bureau, 2007). Although this group has received a great
deal of attention in the past because of their educational achievements (Lorenzo,
12
Frost, & Reinhertz, 2000), few studies have focused on adjustment problems that
they may experience such as symptoms of depression (Austin & Chorpita, 2004;
Hishinuma et al., 2004; Zhou, Peverly, Xin, Huang, & Wang, 2003). For this
investigation, we chose a sample that is representative of diverse West Coast cities in
the United States that have a high number of Asian-Americans.
Hawaii is a particularly interesting setting to study because of its diverse
population and history of immigration from various countries around the world.
Substantial portions of the population in Hawaii are comprised of Asian-Americans,
people of mixed ethnic backgrounds, and people of European-American descent.
While youth in this setting have frequent exposure to values from various cultures,
Asian cultures are particularly influential as Asian-Americans make up the largest
ethnic group in the state (U.S. Census Bureau, 2008). Investigating the social and
academic attributes of youth who report elevated depressive symptoms in this
context is theoretically relevant because Asian cultures place particular importance
on educational achievement and interpersonal relationships (Chen, Rubin, & Li,
1995; Shin, 2007; Triandis, 1995). Although the term ‘Asian’ represents a
heterogeneous group with marked within- and between-group variation, several
Asian cultures, especially those from East Asia, share these values of achievement
and connectedness with others (Kim & Park, 2006; King, Akiyama, & Elling, 1996;
Lin & Fu, 1990). Many researchers assert that in Asian and Asian-American
families, emphasis is placed on academic success as a means to achieve upward
mobility and bring honor to their family (Lee, Wong, Chow, & McBride-Chang,
13
2006; Zhou et al., 2003). Social connectedness is also believed to be critical to the
psychological well-being of individuals from cultures that emphasize
interdependence (Chen et al., 1995; Markus & Kitayama, 1991).
In summary, our objective in the present study was to examine evidence for
unique patterns of behavioral and academic attributes in subgroups of adolescents
with elevated depressive symptoms. We also sought to extend the current literature
by considering multiple aspects of adolescents’ social relationships with peers and
school functioning. To address these research goals, we used a cross-sectional
sample of predominantly Asian-American adolescents in a high school in Hawaii.
As adolescents’ cognitive abilities increase over the course of development, they
gain differentiated conceptualizations of themselves and their competencies in
specific domains (Marsh, 1990). We chose to focus on adolescence because this
complexity across social and academic variables is particularly relevant to our
investigation of the heterogeneity of youth who report high levels of depressive
symptoms. This is the first study to our knowledge that will examine depressive
symptoms in adolescence using a cluster analytic, multidimensional approach in the
context of Hawaii.
14
CHAPTER TWO
METHOD
Participants
Participants were 336 adolescents (167 males, 169 females) recruited from 20
classrooms in a private high school located in Honolulu, Hawaii. Participating
adolescents ranged in age from 13 to 18 years (M = 14.99; SD = 0.78) and were in
the ninth and tenth grades. Honolulu is an ethnically diverse city and the sample was
generally representative of the population of the area (U.S. Census Bureau, 2006-
2008). Students indicated their ethnic/racial background by self-report, and the
sample composition was 53% Asian-American of mainly East Asian descent, 23%
mixed background with Asian-American listed as one ethnic/racial background, 3%
mixed background without Asian-American as an ethnic/racial background, 17%
European-American, and 4% other background (e.g., Native Hawaiian/Other Pacific
Islander). In this study, references to ‘Asian-Americans’ refer to adolescents who
endorsed either an Asian-American background or a mixed background with Asian-
American included as one of the ethnic/racial groups. The breakdown of self-
reported generation status was 13% first-generation, 18% second-generation, 16%
third-generation, 34% fourth-generation, 9% fifth-generation, and 10% unclassified.
The school reported 8% of the participants as English as a second language (ESL)
students.
All students in the ninth and tenth grades were invited to participate in the
study. Consent forms were only provided in English, as students and school
15
administrators indicated that students’ parents could understand the consent forms to
the degree required to provide consent. Parents were informed of the study’s goals
and procedures and were reminded that their child’s participation was voluntary.
Students were also instructed that they could choose not to participate or not to
complete specific items without penalty. Regardless of study participation, all
classrooms that returned more than 80% of their parental consent forms received a
pizza party. Ninety-five percent of the students returned the consent forms, and 80%
of the total population returned positive parental permission and provided written
assent to participate. One student who received parental permission did not provide
assent during data collection and therefore did not participate in the study. All
participating students who were absent during data collection completed study
measures on specified make-up days.
Procedure
Data were collected in the spring semester of the school year using a peer
nomination inventory, self-report questionnaires, and a review of school academic
records. The self-report and peer nomination measures were group-administered in a
one hour classroom-based session by either the author or trained research assistants.
Administrators read a set of standardized instructions to the students and read each
questionnaire item aloud. The study administrators were from diverse ethnic/racial
backgrounds. To measure academic functioning, grades in math and English were
obtained from a review of school records.
16
Measures
Social preference. The participants completed a peer nomination inventory
that included descriptors focusing on adolescents’ behaviors and social standing.
Similar peer nomination items and methods have been used in past studies in both
North American (Schwartz, 2000; Schwartz, Gorman, Nakamoto, & Toblin, 2005)
and international settings (Schwartz, Chang, & Farver, 2001; Schwartz, Farver,
Chang, & Lee-Shin, 2002). Adolescents were given a list of all participating
students in their grade and were asked to nominate up to nine peers who fit each
behavioral or social status item description. One item in the peer nomination
inventory assessed liking (“students that you really like”), and one item assessed
disliking (“students that you don’t like that much”). The total number of
nominations received for each item was calculated and standardized within grade in
order to account for different grade sizes (Coie et al., 1982). We then generated a
social preference score from the difference between the liking and disliking
nominations and standardized this score within grade.
Popularity. We used one item in the peer nomination inventory to assess
popularity (“students that are popular”) and one item to assess unpopularity
(“students that are unpopular”). We then summed the number of nominations that
adolescents received for each item and standardized these scores within grade. An
overall popularity score was generated from the difference between the popularity
and unpopularity nominations and standardized within grade.
17
Friendship. As part of the peer nomination procedure, adolescents were
asked to nominate their best friend as well as the names of up to 10 additional peers
they considered to be close friends. The total number of friends was assessed using
the reciprocated nomination technique (i.e., adolescents were classified as friends
only if they reciprocally nominated each other for either ‘best friend’ or ‘close
friend’ item) (Hodges, Malone, & Perry, 1997; Ladd, Kochenderfer, & Coleman,
1997). In this sample, the number of friends ranged from 0 to 11, and the mean
number of friends each participant had was 4.66 (SD = 2.37).
Aggression. The peer nomination inventory included items that were
designed to tap into different subtypes of aggression. Because previous research
suggests that relational aggression has specific relevance for the construct of
popularity (Cillessen & Mayeux, 2004), we included separate scales measuring both
overt and relational forms of aggression. Two items assessed overt aggression
(“students that hit or push other students,” “students that start fights with other
students by punching or pushing them”; r = .93, p < .001), and two items assessed
relational aggression (“students who try to be mean to other students by ignoring
them or excluding them,” “students that gossip about other students”; r = .84, p <
.001). For later analysis, we calculated the total number of nominations received for
each item and standardized the totals within grade. Overt and relational aggression
variables were then generated from the mean of the respective items for each
subtype.
18
Peer Victimization. We also assessed subtypes of peer victimization and
used two peer nomination items for overt victimization (“students who get hit,
pushed, or bullied by other students,” “students who get beat up by other students”; r
= .78, p < .001) and two items for relational victimization (“students who get mean
things said about them,” “students who get left out of activities, excluded, or
ignored’; r = .78, p < .001). The total number of nominations was summed for each
item and then standardized within grade. We generated overt and relational
victimization variables from the mean of the respective items for each subtype.
Dependency. A modified version of Blatt, Schaffer, Bers, and Quinlan’s
(1992) Depressive Experiences Questionnaire for Adolescents (DEQ-A) was used to
assess level of dependency. The modified version of the scale includes the 29-item
Dependency subscale (e.g., “Without support from others who are close to me, I
would be helpless,” “I watch carefully for signs of rejection from others”; ! = .85),
which taps interpersonal concerns in general, and Neediness and Connectedness
specifically (Rude & Burnham, 1995). The participants responded to each item on a
1 (Not at All) to 7 (Very Well) Likert-type scale. The dependency variable consisted
of the mean of the 29 items (M = 4.49, SD = .71).
Social anxiety. To measure adolescents’ level of social anxiety, we used a
nine item modified version of LaGreca and Lopez’s (1998) Social Anxiety Scale for
Adolescents (SAS-A). The measure included items such as “I worry about what
others say about me” and “I’m afraid that others will not like me”. Adolescents were
asked to respond to each item on a 1 (Not at All) to 5 (All the time) Likert-type scale.
19
The mean of these 21 items was used (M = 2.57, SD = .76) and the internal
consistency was ! = .88.
Academic Engagement. Adolescents’ academic engagement was measured
using a scale developed by combining Fredricks, Blumenfeld, Friedel, and Paris’
(2005) school engagement scale and the ‘Youth School Disengagement’ scale from
the Michigan Study of Adolescent Life Transitions (Eccles et al., 1993). The scale
consisted of seven items (e.g., “I pay attention during class,” “I think working hard
for grades is a waste of time”; ! = .77), and students responded on a 5-point Likert-
type scale (1 = Not True, 5 = Really True). The mean of these items was calculated
to form the academic engagement variable (M = 3.77, SD = .55).
Depressive symptoms. A widely used short-form of the well-validated Child
Depression Inventory (CDI, Kovacs, 1992) was used to assess depressive symptoms.
This measure included 10 items and adolescents were asked to choose the sentence
that best describes how they had been feeling for the past few weeks (e.g., 0 = “I am
sad once in a while,” 1 = “I am sad many times,” 2 = “I am sad all the time”). The
CDI short form correlates with the full-scale version (r = .89), which has internal
consistency coefficients ranging from .71 to .89 and test-retest coefficients ranging
from .74 to .83 over two to three-week time intervals (Kovacs, 1992). In this study,
the internal consistency of the short-form items was ! = .83, and the mean of these
items was .33 (SD = .33).
Academic Achievement. We obtained grades in math and English from a
review of participating students’ first semester school records. Only a math grade
20
was reported for the ESL students. A numerical score was assigned to the letter
grades using a scale ranging from 0 for an “F” to 4.33 for an “A+”. Agreement
between the math and English scores was moderate, r = .39, p < .001. We calculated
the students’ grade point average (GPA) as the mean of their math and English
scores (M = 2.85, SD = .71).
21
CHAPTER THREE
RESULTS
Overview
We predicted that we would find evidence for the existence of three distinct
clusters of adolescents with elevated depressive symptoms. We posited that one
subgroup of these youth would be characterized by elevations on popularity and
relational aggression, and low levels of academic functioning. We expected another
subgroup to score highly on measures of aggression and victimization, and to have
low scores on social preference, popularity, friendship, and academics. We
hypothesized that the third group would be low in popularity and moderate in social
preference, and would have high scores on academic achievement and engagement.
Before we began our inferential analyses, we examined the distribution of
each of the variables and found that the peer relationship variables were positively
skewed. Therefore, prior to further analysis we applied log transformations to these
variables to control for skewness and the potential influence of outliers. Means,
standard deviations, ranges, and skewness and kurtosis values are shown in Table 1
for the entire sample. Our hypotheses were then tested using a combination of linear
and cluster analytic methods. First, we ran correlational analyses to evaluate
relations among all of the variables in this study. To further understand the
multivariate patterns of data, we then examined scatter plots of the distributions for
the associations between depressive symptoms and popularity, social preference,
friendship, and academic achievement. Next, we conducted a cluster analysis to
22
evaluate our hypotheses regarding clusters of youth with elevated depressive
symptoms. Finally, we ran a series of post-hoc analyses of variance (ANOVAs) that
compared the mean scores on all indicators of adjustment by cluster. Significant
results were decomposed using preplanned contrasts to compare each cluster to the
normative contrast subgroup.

Table 1
Descriptive Statistics for the Measures (N = 336)
Variables M SD Range Skewness Kurtosis
1. Depressive symptoms 0.33 0.33 0.00 - 1.90 1.52 2.85
2. Popularity 0.00 1.00 -2.42 - 2.23 -0.06 -0.77
3. Social preference 0.00 1.00 -3.13 - 2.15 -0.60 0.08
4. Friendship 4.66 2.37 0.00 - 11.00 -0.02 -0.49
5. Relational aggression 0.00 1.00 -1.05 - 3.56 1.05 0.79
6. Overt aggression 0.00 1.00 -0.65 - 6.69 2.34 8.03
7. Relational victimization 0.00 1.00 -1.12 - 4.19 1.02 0.92
8. Overt victimization 0.00 1.00 -0.66 - 5.15 2.16 5.40
9. Dependency 4.49 0.71 1.72 - 6.28 -0.47 0.62
10. Social anxiety 2.57 0.76 1.00 - 4.78 0.46 0.03
11. GPA 2.85 0.71 0.67 - 4.17 -0.55 -0.19
12. Academic engagement 3.77 0.55 1.57 - 5.00 -0.65 0.53
-
23
Bivariate Associations and Univariate Statistics
Bivariate correlations between the variables are summarized in Table 2.
Consistent with our hypotheses, depressive symptoms were negatively linked with
popularity, social preference, and friendship. However, it is important to note that
the magnitude of these effect sizes were relatively small (Cohen, 1988). Modest
effects could indicate heterogeneity between indices of social functioning and
depressive symptoms that correlational analyses alone may not detect. Likewise,
there was a negative association between grade point average and symptoms of
depression, with a small effect size.
Multivariate Distributions
We examined scatter plots for these relations to gain a more detailed
understanding of the patterns between depressive symptoms and the main social and
academic variables. Figures 1 to 4 illustrate relations between depressive symptoms
and the social (popularity, social preference, and friendship) and academic (GPA)
predictor variables. There appears to be substantial heterogeneity in the distribution.
It is particularly notable that there are adolescents with relatively high levels of
depressive symptoms in each quadrant. In other words, there are some youths with
elevated depressive symptoms who are doing well in school and some who are
characterized by positive peer relations. Thus, it is not surprising that the bivariate
effects reported in Table 2 are characterized by weak effect sizes.

24
Table 2
Bivariate Correlations among All Variables (N = 336)
Variables 1 2 3 4 5 6 7 8 9 10 11 12 13
1. Depressive symptoms — -.21
***
-.15
**
-.14
**
-.05 -.05 -.18
***
-.17
**
.27
***
.46
***
-.13
*
-.22
***
.07
2. Popularity — .36
***
.36
***
.42
***
.14
**
-.31
***
-.23
***
.05 -.16
**
-.07 -.10 .10
3. Social preference — .50
***
-.27
***
-.35
***
-.63
***
-.32
***
.11
*
-.05 .20
***
.11
*
.14
*

4. Friendship — .13
*
-.03 -.21
***
-.10 .14
**
-.07 .08 -.01 .18
***

5. Relational aggression — .37
***
.36
***
-.01 -.03 -.12
*
-.22
***
-.14
*
.24
***

6. Overt aggression — .25
***
.32
***
-.12
*
-.17
**
-.23
***
-.19
***
-.36
***

7. Relational victimization — .52
***
-.02 -.00 -.15
**
-.03 .00
8. Overt victimization — -.04 .00 -.07 -.15
**
-.37
***

9. Dependency — .60
***
-.03 .12
*
.16
**

10. Social anxiety — .01 .14
*
.10
11. GPA — .36
***
.11
*

12. Academic engagement — .08
13. Gender
1
—

Note.
1
Gender is coded 0 = male and 1 = female.
*
p ! .05,
**
p ! .01,
***
p ! .001.

25

Figure 1
Scatter plot depicting the association between peer nomination scores for popularity
and self-reported depressive symptoms

26

Figure 2
Scatter plot depicting the association between peer nomination scores for social
preference and self-reported depressive symptoms

27

Figure 3
Scatter plot depicting the association between peer nomination scores for friendship
and self-reported depressive symptoms

28

Figure 4
Scatter plot depicting the association between scores for grade point average and
self-reported depressive symptoms

29
Cluster Analysis
Next, we conducted a cluster analysis to examine evidence for the presence
of three subgroups of youth with elevated depressive symptoms across the measures
of peer and academic functioning. For these analyses, we included only adolescents
with a depressive symptoms score of 0.5 or higher (n = 98). This score was
approximately one standard deviation above the mean and corresponds to a prorated
score of 13.5 on the full-scale version. We selected this cutoff by considering two
competing goals. While this score is relatively low for determining a cutoff for
symptoms of depression, we attempted to include a sufficient number of adolescents
for our analyses while still maintaining a subgroup that is experiencing depressive
tendencies relative to their peers.
In our cluster analysis we used a K-means clustering procedure, with a three-
group solution selected a priori. As shown in Table 3, the results of the cluster
solution provided support for our hypotheses. Three distinct behavioral and
academic profiles emerged that indicated the presence of subgroups among
adolescents with elevated depressive symptoms in our sample. The first cluster (n =
33) was characterized primarily by elevations on popularity, social preference, and
friendship, by high levels of relational aggression, and by low grade point averages
and academic engagement. Adolescents in this cluster also scored highly on
measures of dependency and social anxiety. This popular group was mainly
comprised of girls (73% female, 27% male), and the ethnic/racial breakdown was
52% Asian-American, 24% European-American, 21% mixed background that

30
included Asian-American, and 3% mixed background that did not include Asian-
American. The second cluster (n = 54) was low in popularity and friendship, had
moderate social preference scores, had high grade point averages and academic
engagement scores, and had elevated levels of dependency and social anxiety. This
group was generally equal across gender (44% female, 56% male) and had
ethnic/racial percentages of 72% Asian-American, 15% mixed background that
included Asian-American, 7% European-American, and 6% other background. The
third cluster (n = 11) had low levels of social preference, popularity, and friendship,
and elevations on both subtypes of aggression and victimization variables. Not
surprisingly, these adolescents also reported low levels of dependency and social
anxiety. This subgroup was further characterized by moderate grade point averages
and academic engagement. These aggressive-rejected adolescents were mostly boys
(36% female, 64% male) and the ethnic/racial composition of the group was 46%
Asian-American, 36% European-American, 9% mixed background that included
Asian-American, and 9% mixed background that did not include Asian-American.

31
Table 3
Cluster Analysis of Adolescents with Elevated Levels of Depressive Symptoms
Main
effect of
cluster
status
F(3, 332)
Popular
(n =33)
Low impact
(n = 54)
Aggressive-
rejected
(n =11)
Normative
contrast
(n =238)
Variable M SD M SD M SD M SD
1. Popularity 20.79
***
0.60
**
0.91 -0.53
***
0.82 -1.45
***
1.07 0.10 0.94
2. Friendship 28.07
***
6.85
***
1.39 3.20
***
1.46 1.64
***
1.69 4.82 2.34
3. Social
preference
22.29
***
0.49
*
0.79 -0.18 0.84 -2.02
***
0.78 0.07 0.95
4. Relational
aggression
6.84
***
0.46
*
1.03 -0.46
***
0.74 0.36 1.32 0.02 0.99
5. Overt
aggression
3.62
*
-0.10 0.91 -0.23 0.79 0.81
*
0.66 0.03 1.05
6. Relational
victimization
29.75
***
0.04 0.87 -0.07 0.83 2.48
***
0.92 -0.10 0.90
7. Overt
victimization
31.00
***
0.21 1.27 -0.20 0.63 2.47
***
1.57 -0.10 0.83
8. Dependency 12.22
***
4.91
***
0.48 4.82
***
0.68 4.09 1.22 4.37 0.66
9. Social
Anxiety
27.44
***
2.93
***
0.78 3.24
***
0.74 2.41 1.20 2.37 0.63
10. Grade Point
Average
2.69
*
2.55
*
0.63 2.93 0.82 2.64 0.64 2.88 0.69
11. Academic
Engagement
6.12
***
3.42
***
0.52 3.75 0.63 3.58 0.86 3.84 0.50

Note. Means with an asterisk are significantly different from means of the normative
contrast group.
*
p ! .05,
**
p ! .01,
***
p ! .001.

32
Post-hoc comparisons
To examine subgroup differences on each individual adjustment variable, we
ran a series of post-hoc univariate ANOVAs. As the bar graphs in Figures 5 through
15 illustrate, the pattern of findings for the three subgroups was supportive of our
hypotheses and there were significant differences for all of the variables. We then
conducted preplanned contrasts to determine which of the clusters were significantly
different from the normative group (n = 238).
Relative to their peers in the normative group, we found that adolescents who
were popular and also high in depressive symptoms had more friends and higher
social status (Figures 5 through 7). However, as depicted in Figure 8, these youth
had relational aggression scores that were significantly higher than the normative
contrast group. Figures 12 through 15 show that the popular subgroup was also more
interpersonally dependent and socially anxious than the normative group, was doing
worse in school, and was less academically engaged.
As illustrated in Figures 5 and 7, adolescents who had elevated depressive
symptoms and were in the low impact subgroup were less popular and had fewer
friends than adolescents in the normative group. They were also less relationally
aggressive (Figure 8), and more dependent and socially anxious (Figures 12 through
13). Grade point averages and academic engagement scores were not significantly
different between the low impact cluster and the normative contrast group.
Lastly, youth with depressive tendencies who were in the aggressive-rejected
subgroup were less popular (Figure 5), more socially rejected (Figure 6), and were

33
found to have fewer friends (Figure 7) than the normative contrast group. It was
notable that these adolescents were also more overtly aggressive than the normative
contrast adolescents, and more overtly and relationally victimized as shown in
Figures 9 through 11. However, aggressive-rejected adolescents did not significantly
differ from the normative group on GPA and engagement in school.

34

Figure 5
Bar graph depicting mean scores for popularity for each subgroup of adolescents
with elevated levels of depressive symptoms and normative contrast group. Means
with an asterisk are significantly different from mean of the normative contrast
group

*
p ! .05,
**
p ! .01,
***
p ! .001.

35

Figure 6
Bar graph depicting mean scores for social preference for each subgroup of
adolescents with elevated levels of depressive symptoms and normative contrast
group. Means with an asterisk are significantly different from mean of the normative
contrast group

*
p ! .05,
**
p ! .01,
***
p ! .001.

36

Figure 7
Bar graph depicting mean scores for friendship for each subgroup of adolescents
with elevated levels of depressive symptoms and normative contrast group. Means
with an asterisk are significantly different from mean of the normative contrast
group

*
p ! .05,
**
p ! .01,
***
p ! .001.

37

Figure 8
Bar graph depicting mean scores for relational aggression for each subgroup of
adolescents with elevated levels of depressive symptoms and normative contrast
group. Means with an asterisk are significantly different from mean of the normative
contrast group

*
p ! .05,
**
p ! .01,
***
p ! .001.

38

Figure 9
Bar graph depicting mean scores for overt aggression for each subgroup of
adolescents with elevated levels of depressive symptoms and normative contrast
group. Means with an asterisk are significantly different from mean of the normative
contrast group

*
p ! .05,
**
p ! .01,
***
p ! .001.

39

Figure 10
Bar graph depicting mean scores for relational victimization for each subgroup of
adolescents with elevated levels of depressive symptoms and normative contrast
group. Means with an asterisk are significantly different from mean of the normative
contrast group
*
p ! .05,
**
p ! .01,
***
p ! .001.

40

Figure 11
Bar graph depicting mean scores for overt victimization for each subgroup of
adolescents with elevated levels of depressive symptoms and normative contrast
group. Means with an asterisk are significantly different from mean of the normative
contrast group

*
p ! .05,
**
p ! .01,
***
p ! .001.

41

Figure 12
Bar graph depicting mean scores for dependency for each subgroup of adolescents
with elevated levels of depressive symptoms and normative contrast group. Means
with an asterisk are significantly different from mean of the normative contrast
group

*
p ! .05,
**
p ! .01,
***
p ! .001.

42

Figure 13
Bar graph depicting mean scores for social anxiety for each subgroup of adolescents
with elevated levels of depressive symptoms and normative contrast group. Means
with an asterisk are significantly different from mean of the normative contrast
group

*
p ! .05,
**
p ! .01,
***
p ! .001.

43

Figure 14
Bar graph depicting mean scores for grade point average for each subgroup of
adolescents with elevated levels of depressive symptoms and normative contrast
group. Means with an asterisk are significantly different from mean of the normative
contrast group
*
p ! .05,
**
p ! .01,
***
p ! .001.

44

Figure 15
Bar graph depicting mean scores for academic engagement for each subgroup of
adolescents with elevated levels of depressive symptoms and normative contrast
group. Means with an asterisk are significantly different from mean of the normative
contrast group
*
p ! .05,
**
p ! .01,
***
p ! .001.

45
CHAPTER FOUR
DISCUSSION
Our findings contribute to the existing literature by testing a proposed
typology of adolescents who are experiencing relatively high levels of depressive
symptoms. Results from this study shed light on the distinctions between subgroups
of these adolescents with regard to their peer group and school experiences. This
investigation is also noteworthy for its inclusion of ethnic groups that have arguably
been underrepresented in past studies.
Consistent with research conducted primarily with European-American
samples in the United States, we found that depressive symptoms were negatively
associated with measures of friendship, social preference, popularity, and academic
achievement (Accordino et al., 2000; Johnson et al., 2006). In other words,
adolescents who endorsed depressive tendencies tended to have fewer friends than
their classmates, were less accepted by the peer group, were viewed as less popular,
and were less likely to be doing well in school. However, the effect sizes for these
correlations were relatively small, and an inspection of scatter plots for each of these
relations revealed that adolescents who self-reported depressive symptoms were a
heterogeneous group.
We hypothesized that there would be three distinct groups of adolescents who
were high in depressive tendencies. Specifically, we expected to find one subgroup
that was comprised of popular adolescents who are reacting to social pressures,
another subgroup that is characterized by adolescents with low social impact who are

46
generally ignored by the peer group, and a third subgroup of highly aggressive
adolescents who are rejected by their peers. Our findings were consistent with this
proposed typology and suggest the need to consider heterogeneity in social and
academic profiles.
Among these subgroups, youth who had elevated depressive symptoms and
were popular clearly occupied positions of high social standing. These adolescents
had a large number of friends, were well-liked, and were considered by the larger
peer group to be socially dominant. While it may seem surprising that a subgroup of
popular youth are concurrently vulnerable to depressive tendencies given the status
that these adolescents enjoy, there is a growing body of literature that documents the
potential risks associated with popularity. A number of researchers have found links
between popularity and problematic outcomes, such as sexual experimentation
(Prinstein et al., 2003) and alcohol use (Mayeux et al., 2008). Ethnographic
descriptions of the popular ‘in crowd’ have also depicted a lifestyle characterized by
constant conflict and in-fighting to maintain the social hierarchy (Adler & Adler,
1998). Indeed, adolescents in our study who were popular and also high in
depressive symptoms were found to display elevated levels of social aggression.
These adolescents may therefore be experiencing internalized distress as a reaction to
the social pressures associated with high status.
Our findings on relational forms of aggression in this subgroup support past
research that describe popular adolescents as strategists who wield their social
influence by excluding and ignoring other classmates (Cillessen & Mayeux, 2004;

47
Hawley, 2003; Rose et al., 2004). In this model of popularity, relationships are the
currency through which power is exercised. Accordingly, we found that members of
the popular cluster endorsed high levels of dependency and social anxiety. It may be
the case that a reliance on others paired with sensitivity to negative interactions
leaves this subgroup particularly vulnerable to the stresses that accompany a popular
lifestyle. Considering that relational aggression has been found to be particularly
relevant for popular girls (Cillessen & Mayeux, 2004; Rose et al., 2004), it is also
interesting that popular adolescents with depressed affect in our sample were
predominantly female. These results seem particularly relevant in light of recent
evidence suggesting adjustment problems in adulthood for popular girls who use
relational aggression in high school, but not for popular boys (Sandstrom &
Cillessen, under review).
Poor functioning in the academic domain was another distinctive
characteristic of this group of adolescents. Adolescents who endorsed high
depressive symptoms and were popular received grades that were significantly lower
than their normative counterparts and reported significantly lower academic
engagement. Research conducted on popularity has indicated that popular youth
who are also aggressive tend to be characterized by poor academic achievement
(Schwartz, Gorman, Nakamoto, & McKay, 2006) and negative attitudes toward
school (Vitaro et al., 2005). Furthermore, youth who aspire to gain high social status
may be required to give up academic pursuits in order to ‘fit in’ with the norms of
the popular crowd (Brown, 1990). Researchers have suggested that social pressures

48
to disengage from academics may become increasingly pronounced in adolescence
(Adler & Adler, 1998; Juvonen & Murdock, 1995). Thus, this subgroup of youth
with elevated depressive symptoms is notable in that its profile included negative
attributes in both behavioral and academic areas of functioning.
In contrast to the popular subgroup, the second subgroup of adolescents who
reported elevated depressive symptoms was characterized by low social impact and
high academic performance. While they were not particularly disliked, this group
was viewed by their peers as low in popularity and social influence. Conceptually,
these youths may correspond to subgroups that have been described by past
researchers as “neglected,” “loners,” or “nerds” (Adler & Adler, 1998; Coie et al.,
1982). Low impact adolescents in our study had a smaller number of friends
compared to their normative schoolmates. Several researchers have observed that an
additional consequence of low status for these youth is fewer social opportunities,
such as friendship and romantic relationships, through which the development of
social competencies might occur (Bukowski et al., 1996, Parker & Asher, 1993).
Low impact students also reported experiencing high levels of social anxiety and
particular sensitivity regarding relationships, which may reflect their lack of social
connectedness in the peer group. Depressive symptoms among adolescents in this
subgroup may be associated with their limited access to social resources and their
tendency to be overlooked.
Youth who were experiencing depressive tendencies and had low social
impact were also less relationally aggressive than adolescents who did not report

49
many depressive symptoms. This portrayal is consistent with past findings that peers
do not view neglected youth as aggressive (Dodge, 1983). As children transition into
adolescence, having a reputation of being socially aggressive becomes increasingly
linked to high social standing (Cillessen & Mayeux, 2004). In a cluster analytic
study of preadolescents, Lease et al. (2002) speculated that neglected youth may be
unmotivated or unable to dominate others and are thus ignored because they are not
considered serious social competition.
Members of the low impact cluster were also distinct due to their scholastic
achievement and engagement in school. Youth classified as neglected in the extant
literature have generally demonstrated positive academic profiles (Parkhurst &
Asher, 1992; Wentzel, 1991; Wentzel & Asher, 1995). In line with these
conceptualizations, our results suggest that students in the low impact subgroup of
adolescents with high depressive symptoms tended to earn good grades and be
academically engaged. Despite their relative success in school, it is important for
researchers to recognize this group of youth who are at risk for internalized distress.
The nature of their status often results in them being left unnoticed. Moreover, low
impact youth may not draw the attention of teachers and parents since they are not
aggressive toward their peers.
The aggressive-rejected subgroup of adolescents who reported elevated
depressive symptoms was notable for their markedly low functioning across multiple
indicators of social adjustment. Compared with the normative group, aggressive-
rejected adolescents had few friends, were unpopular, and were not held in high

50
regard by their peers. These youth also had reputations of being both highly
aggressive and victimized. Given their overall disengagement from the peer group,
it is not surprising that the aggressive-rejected subgroup reported low levels of
dependency and social anxiety. Youth who display behavior that is not in tune with
societal norms would not be expected to endorse feelings of interdependency or
concerns about social interactions. The pattern of behavioral attributes that emerged
for this cluster generally matches existing descriptions of aggressive-rejected youth.
A considerable number of researchers have concluded that aggressive-rejected status
is associated with emotional and behavioral dysregulation (Schwartz, 2000), low
prosocial tendencies (Parkhurst & Asher, 1992), and frequent victimization
(Schwartz, 2000). Peers are often irritated by the disruptive behavior of these youth
and retaliate with aggression. It is theorized that these deficits in social skills may
lead to negative interactions with peers and later depressed mood (Capaldi, 1992;
Pedersen et al., 2007). Indeed, empirical evidence has consistently found links
between aggressive-rejected status and internalized emotional distress (Boivin,
Poulin, & Vitaro, 1994; Haynie et al., 2001; Schwartz, 2000).
While the overall pattern of findings was consistent with our hypotheses, the
data did not support our prediction that the aggressive-rejected subgroup of
adolescents with elevated depressive symptoms would have poor grades and low
school engagement. Several studies have found that aggressive-rejected youth tend
to have poor academic records (Wentzel, 2003), low teacher-rated academic
functioning (Schwartz, 2000), and low interest in school (Lease et al., 2002).

51
Instead, we found that these youth did not significantly differ from normative
adolescents with respect to their grades or engagement in school.
It is also significant that we found a portion of aggressive-rejected girls
among adolescents who were vulnerable to depressive tendencies. Most of the
existing research on aggressive-rejected youth has been conducted primarily with
boys (Cillessen et al., 1992; Dodge, 1983; Olson, 1992). While the small sample
size of the aggressive-rejected cluster in our study precluded further gender analyses,
future research should explore this issue. Existing evidence on girls who are
aggressive, rejected, and victimized suggests similar behavioral and academic
profiles across gender (Schwartz, 2000; Toblin et al., 2005). Most of the past
research on aggressive-rejected youths has also focused on younger age groups and
has not included assessments of relational aggression (Cole & Carpentieri, 1990;
Olson, 1992; Panak & Garber, 1992). More studies are needed that incorporate
multifaceted measures of aggression and explore potential gender and age effects in
this group of at-risk youth.
While the current investigation did not incorporate a longitudinal design, our
overall results provide some support for theoretical models posited by Cole (1991),
Patterson et al. (1992), and Masten et al. (2005) on depressive symptoms. Our
findings were broadly consistent with Cole’s perspective that difficulties in central
areas of competence such as academics and peer relationships are associated with
depressive symptoms in adolescence. For example, while adolescents in the low
impact subgroup in our study appeared to be functioning well in the academic

52
domain, their social anxiety and relatively low functioning with peers may put them
at risk for increased depressive symptoms. Patterson et al.’s dual failure model and
Masten et al.’s model of cascading effects primarily focused on the progression from
externalizing problems to internalizing symptoms. Adolescents in our study who
were aggressive, rejected by their peers, and had elevated depressive symptoms
appeared to fit Patterson et al.’s model of antisocial youth who display noxious
behavior and experience failures in social interactions. Similarly, the aggressive-
rejected adolescents in our sample were unpopular, had few friends, and tended to be
victimized in the peer group. However, they did not have significant deficits in
academic functioning as would be hypothesized by this model. In comparison,
adolescents in the popular subgroup were relationally aggressive and yet socially
successful in terms of high social standing and having numerous friends. This
subgroup also demonstrated poor academic achievement and low engagement in
school, which is consistent with the academic difficulties described in both Patterson
et al.’s and Masten et al.’s models. Relevant to our findings, all three perspectives
also emphasized the importance of assessing multiple domains of adjustment as one
domain could influence functioning in other domains. Furthermore, these models
highlight the need for longitudinal research to test the processes underlying
depressive symptoms in adolescence. We did not directly assess the causal
mechanisms specified by these models, and our findings can therefore provide only
limited insight regarding relations between the observed effects.

53
Our results on the social and academic profiles of adolescents with elevated
depressive symptoms are also interesting to consider within the context of this
investigation. Hawaii is a region rich in ethnic diversity and exposure to various
cultures. Asian-Americans comprise the largest ethnic group in the state, and Asian
cultures have a particularly strong influence on society. Theoretical perspectives on
Asian-American values suggest that relationships and achievement are held in high
regard across many Asian cultures (Chen et al., 1995; Shin, 2007; Triandis, 1995).
We found that academics and peer relations were both important areas of functioning
for adolescents in this cultural setting. While the different subgroups of adolescents
with elevated depressive symptoms varied in terms of elevations among the social
and academic attributes, each subgroup demonstrated poor adjustment in either one
or both domains. This study also contributes to the limited research that exists on
depressive symptoms with Asian-American youth. Our findings on the diversity of
academic functioning across subgroups of adolescents with elevated depressive
symptoms specifically challenge the stereotypical notion of Asian-American youth
as high-functioning, model minority achievers (Gee, 2004). Moreover, several
researchers contend that social context may influence the meaning of achievement in
a given school setting through the imbedded values and norms (Becker & Luthar,
2002; Chen et al., 1995). For example, in a school where the dominant peer culture
supports studying and achieving good grades, it is possible that popularity could
coexist with engagement in school. However, we found that the popular youth in our
study who reported high depressive symptoms were performing poorly in school.

54
This result was consistent with past findings regarding the devaluation of school
among high status youth (Vitaro et al., 2005). Further research will clearly be
necessary before stronger conclusions can be drawn, as few studies have focused on
diverse settings with a large number of Asian-Americans.
Limitations and Future Directions
The results of this investigation make an important contribution to the
existing research on depressive symptoms among adolescent populations, but some
potential limitations should be acknowledged. First, we should caution against
making strong assumptions regarding causality in light of the correlational nature of
our data. It is not clear, for example, if low social impact in the peer group leads to
depressed affect for some neglected youth, or if adolescents with depressive
tendencies are unattractive targets for friendship and social interaction.
Alternatively, low social impact among one’s peers and symptoms of depression
may be markers of a third variable that may help to explain both attributes, such as
difficulties in the home environment (Franz & Gross, 2001). As previously
discussed, longitudinal designs would improve our ability to investigate these issues
of causality.
Second, it is difficult to make statements about culture because of the
considerable complexity that exists in the Hawaii context. Our goal was to examine
the behavioral and academic characteristics of youth with elevated depressive
symptoms in this setting rather than form conclusions about differences between
cultural groups both within and outside of Hawaii. Concerns regarding external

55
validity can also apply to investigations within a cultural context as there is likely to
be substantial variability in the customs, belief systems, and cultural practices that
characterize adolescents’ environments (Bukowski & Sippola, 1998). This
variability may be particularly relevant in a setting such as Hawaii, which has a long
history of immigration and exposure to diverse cultures.
It should also be noted that the ethnic/racial composition of our sample was
complex. The majority of adolescents in our study endorsed that they were only
Asian-American, and Asian-Americans represented the largest ethnic/racial group in
each cluster of youth who reported high depressive symptoms. In addition,
substantial portions of the overall sample reported having mixed ethnic/racial
backgrounds or backgrounds of only European-American descent. Bellmore,
Witkow, Graham, & Juvonen (2004) have hypothesized that other contextual
aspects, such as ethnic majority-minority status, may have implications for how peer
group adjustment relates to internalized distress. These authors found that for
adolescents who were members of the ethnic majority in their classroom, peer
victimization was more strongly associated with loneliness and social anxiety
compared to their ethnic minority peers. Further research is needed to tease apart the
potential influences of these various factors.
Likewise, future research on potential gender differences among subgroups
of youth with high depressive symptoms would be informative. In this study, we
found that members of the popular cluster were primarily girls. Investigators have
hypothesized that popular boys and girls who are relationally aggressive may have

56
different peer group experiences and divergent long-term outcomes (Sandstrom &
Cillessen, under review). We also found a number of aggressive-rejected girls
among adolescents who reported elevated levels of depressive symptoms. Research
on aggressive-rejected youth has traditionally focused on boys, and aggressive-
rejected girls have rarely been identified (Schwartz, 2000; Toblin et al., 2005).
Gender differences may also exist among adolescents who have low social impact
and are vulnerable to depressive tendencies. For example, Wentzel (2003) found
that girls who were classified as neglected in the peer group earned significantly
higher grades than their average status classmates, while neglected boys earned
significantly lower grades than youth in the average status group. Therefore,
research that investigates the role of gender would appear to be an important step in
understanding the diversity in youth at risk for depression.
Our findings in the present study illustrate the potential limitations of linear
approaches in dealing with heterogeneity and support the application of cluster
analytic techniques. Significant variability existed among youth with elevated
depressive symptoms in terms of peer group and academic functioning. For
example, the scores on indicators for academic adjustment were low for the subgroup
of adolescents who were popular, but adolescents who had low social impact scored
highly on the same measures. A sole reliance on correlational analyses would likely
have missed these differences in the meaning of academics for each group.
Furthermore, the specific combinations of variables are what make each cluster

57
unique and these patterns may have important implications for each group’s
adjustment.
In summary, the current project adds to the existing literature by providing
preliminary evidence for distinct subgroups among adolescents who report relatively
high levels of depressive symptoms. The popular subgroup was characterized by a
mixed pattern of adjustment including high social standing, numerous friends,
relational aggression, and poor academic adjustment. Adolescents in the low social
impact subgroup tended to be unpopular and neglected in the peer group, but were
doing well in school. Finally, the aggressive-rejected subgroup had significant
deficits in social functioning, but had moderate levels of academic functioning. In
addition, this is the first study that we are aware of that used cluster analysis and
multiple indicators of social and academic functioning to investigate depressive
symptoms among predominantly Asian-American adolescents in Hawaii. Taken
together, our results highlight the complexity of symptoms of depression in
adolescence, and further research conducted with longitudinal designs and
multidimensional approaches is needed.

58
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68
APPENDIX
SURVEY PACKET OF STUDY MEASURES

Cover Sheet

My name is: _________________________

My teacher is: _______________________

Please DO NOT write your name on any
other sheet of paper.

69

Office Use Only

ID # _____________

70
My Information
Gender: Male - 0 Female - 1

Grade: ________

My Age is: ________

My Birth date is:
____/____/____
mm / dd / yyyy

My family mainly speaks a language other than English at home:
Yes - 1 No - 0

If you answered ‘yes’, that Language is:
1 - Japanese 2 - Chinese 3 - Korean 4 - Tagalog
5 - Hawaiian 6 - Spanish 7 - Thai 8 -Vietnamese
9 - Other (please specify):_____________________

71
Please circle the ethnicity that best describes you.
1 - Japanese/ Japanese-
American
2 – Chinese/ Chinese-
American
3 - Caucasian/ European-
American
4 - Filipino/ Filipino-
American
5 - Korean/ Korean-
American
6 - Native Hawaiian or
Other Pacific Islander
7 - Latino or Hispanic/
Hispanic-American
8 - Black/ African-
American
9 - Vietnamese/
Vietnamese-American
10 - Thai/ Thai-American 11 - Portuguese/
Portuguese-American
12 - Asian Indian/ Asian
Indian-American
13 - Mixed (please
specify):
___________________
14 - Other (please
specify):
____________________

I was born in the US:
Yes-1 No-0

72
If your family immigrated to the United States, what generation status best describes
you?
____ 1st generation: I was born in another country.
In what country were you born? __________________

____ 2nd generation: My parents were born in another country.
In what country (or countries) were your parents born?
__________________________________________

____ 3rd generation: My grandparents were born in another country.
In what country (or countries) were your grandparents born?
__________________________________________

____ 4th generation: My great grandparents were born in another country.
In what country (or countries) were your great grandparents born?
__________________________________________

____ 5th generation: My great great grandparents were born in another country.
In what country (or countries) were your great great grandparents born?
__________________________________________

____ I don’t know.

73
Others at School
PLEASE TAKE OUT THE LIST ATTACHED TO THIS SURVEY AND USE IT
TO ANSWER THESE QUESTIONS.
Please DO NOT write your name, or the names of other students, anywhere on this
sheet!

1. Write the ID codes of up to nine students that you really like.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

2. Write the ID codes of up to nine students that you don't like that much.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

3. Write the ID codes of up to nine students that hit or push other students.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

74

4. Write the ID codes of up to nine students who get hit, pushed, or bullied by other
students.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

5. Write the ID codes of up to nine students who get mean things said about them.
1 ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

6. Write the ID codes of up to nine students that start fights with other students by
punching or pushing them.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

75

7. Write the ID codes of up to nine students who try to be mean to other students by
ignoring them or excluding them.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

8. Write the ID codes of up to nine students who get left out of activities, excluded,
or ignored when other students are trying to hurt their feelings.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

9. Write the ID codes of up to nine students that gossip about other students.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

76

10. Write the ID codes of up to nine students who get beat up by other students.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

11. Write the ID codes of up to nine students that are popular.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

12. Write the ID codes of up to nine students that are UNpopular. These are
students who are NOT popular.
1. ________________ 2. ________________ 3. _________________
4. ________________ 5. ________________ 6. _________________
7. ________________ 8. ________________ 9. _________________

77

13. Write the ID code of your VERY BEST FRIEND from the list.
1. ________________

14. Write the ID codes of up to 10 students on the attached list who you consider
GOOD FRIENDS. These are students who are your REALLY CLOSE FRIENDS
(please do not include your best friend on the list).

1. ________________ 2. ________________
3. ________________ 4. ________________
5. ________________ 6. ________________
7. ________________ 8. ________________
9. ________________ 10. ________________

NOW PLEASE PUT ASIDE THE LIST OF NAMES AND ID CODES.
YOU WILL NO LONGER BE USING IT.

78
Feelings About School
1. I pay attention during class.
Not True Might be True Usually True Very True Really True
1 2 3 4 5

2. I complete my assignments on time.
Not True Might be True Usually True Very True Really True
1 2 3 4 5

3. I try to follow the rules in school.
Not True Might be True Usually True Very True Really True
1 2 3 4 5

4. When I am in class, I usually pretend that I am paying attention.
Not True Might be True Usually True Very True Really True
1 2 3 4 5

5. I think working hard for good grades is a waste of time.
Not True Might be True Usually True Very True Really True
1 2 3 4 5

6. I feel bored with most of my classes or subjects at school.
Not True Might be True Usually True Very True Really True
1 2 3 4 5

7. Grades are very important to me.
Not True Might be True Usually True Very True Really True
1 2 3 4 5

79
Things that Describe Me
These questions ask about how well different traits describe you.
Please read each of the following statements and decide how well they describe you.
Then circle the appropriate number for each item, based on the scale below.

1. Without support from others who are close to me, I would be helpless.
1 2 3 4 5 6 7
Not at all Somewhat Very well

2. I really need things that only other people can provide.
1 2 3 4 5 6 7
Not at all Somewhat Very well

3. It bothers me that relationships with people change.
1 2 3 4 5 6 7
Not at all Somewhat Very well

4. I seldom worry about being criticized for things I have said or done.
1 2 3 4 5 6 7
Not at all Somewhat Very well

5. I want to live up to what other people expect of me.
1 2 3 4 5 6 7
Not at all Somewhat Very well

6. I become frightened when I feel alone.
1 2 3 4 5 6 7
Not at all Somewhat Very well

80
7. If I lost a very close friend, it would feel like I lost an important part of myself.
1 2 3 4 5 6 7
Not at all Somewhat Very well

8. I have difficulty breaking off a friendship that is making me unhappy.
1 2 3 4 5 6 7
Not at all Somewhat Very well

9. I often think about the danger of losing someone who is close to me.
1 2 3 4 5 6 7
Not at all Somewhat Very well

10. When I am with others, I often put myself down.
1 2 3 4 5 6 7
Not at all Somewhat Very well

11. I am very concerned with how other people react to me.
1 2 3 4 5 6 7
Not at all Somewhat Very well

12. Even if two people are very close, there is still a lot of fighting.
1 2 3 4 5 6 7
Not at all Somewhat Very well

13. I watch carefully for signs of rejection from others.
1 2 3 4 5 6 7
Not at all Somewhat Very well

81
14. It’s important for my family that I succeed.
1 2 3 4 5 6 7
Not at all Somewhat Very well

15. I very often go out of my way to please or help people I am close to.
1 2 3 4 5 6 7
Not at all Somewhat Very well

16. I find it very difficult to say “No” to the requests of friends.
1 2 3 4 5 6 7
Not at all Somewhat Very well

17. Even if the person who is closest to me were to leave, I could still get along on
my own.
1 2 3 4 5 6 7
Not at all Somewhat Very well

18. I generally watch carefully to see how other people are affected by what I say or
do.
1 2 3 4 5 6 7
Not at all Somewhat Very well

19. I often blame myself for things I have done or said.
1 2 3 4 5 6 7
Not at all Somewhat Very well

82
20. I worry a lot about upsetting or hurting someone who is close to me.
1 2 3 4 5 6 7
Not at all Somewhat Very well

21. Anger frightens me.
1 2 3 4 5 6 7
Not at all Somewhat Very well

22. If someone I cared about became angry with me, I would feel frightened that he
or she might leave me.
1 2 3 4 5 6 7
Not at all Somewhat Very well

23. I feel uncomfortable when I am given important responsibilities.
1 2 3 4 5 6 7
Not at all Somewhat Very well

24. After a fight with a friend, I must make up for it as soon as possible.
1 2 3 4 5 6 7
Not at all Somewhat Very well

25. After an argument, I feel very lonely.
1 2 3 4 5 6 7
Not at all Somewhat Very well

26. Being alone doesn’t bother me at all.
1 2 3 4 5 6 7
Not at all Somewhat Very well

83
27. I rarely think about my family.
1 2 3 4 5 6 7
Not at all Somewhat Very well

28. If someone makes me angry, I let him (her) know how I feel.
1 2 3 4 5 6 7
Not at all Somewhat Very well

29. I am a very independent person.
1 2 3 4 5 6 7
Not at all Somewhat Very well

84
How I Feel
Please circle one sentence from each list that best describes how you have been
feeling for the past two weeks.
List 1
A. I am sad once in a while.
B. I am sad many times.
C. I am sad all the time.
List 6
A. Things bother me once in a while.
B. Things bother me many times.
C. Things bother me all the time.
List 2
A. Things will work out for me O.K.
B. I am not sure if things will work out
for me.
C. Nothing will ever work out for me.
List 7
A. I look O.K.
B. There are some bad things about my
looks.
C. I look ugly.
List 3
A. I do most things O.K.
B. I do many things wrong.
C. I do everything wrong.
List 8
A. I do not feel alone.
B. I feel alone many times.
C. I feel alone all the time.
List 4
A. I like myself.
B. I do not like myself.
C. I hate myself.
List 9
A. I have plenty of friends.
B. I have some friends, but I wish I had
more.
C. I do not have any friends.

85
List 5
A. I feel like crying once in a while.
B. I feel like crying many days.
C. I feel like crying every day.
List 10
A. I am sure that somebody loves me.
B. I am not sure if anybody loves me.
C. Nobody really loves me.

86
Interacting with Others
Please read each of the following statements and decide how much the item is true
for you. Then circle the appropriate number for each item, based on the scale below.

1. I worry about what others think of me.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

2. I feel shy even with kids I know very well.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

3. I’m afraid that others will not like me.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

4. I worry about what others say about me.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

5. I worry that others don’t like me.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

87
6. I am quiet when I’m with a group of people.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

7. If I get into an argument, I worry that the other person will not like me.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

8. It’s hard for me to ask others to do things with me.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

9. I’m afraid to invite others to do things with me because they might say no.
1 2 3 4 5
Not at all Hardly ever Sometimes Most of the time All the time

Abstract (if available)

Abstract This study utilized a cross-sectional, multi-informant approach to examine a typology of adolescents who are experiencing elevated depressive symptoms. Participants were 336 predominantly Asian-American adolescents (167 males, 169 females

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Asset Metadata

Creator Tom, Shelley R. (author)

Core Title Heterogeneity among adolescents with elevated depressive symptoms: distinct patterns of social and academic attributes

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Psychology

Publication Date 07/13/2010

Defense Date 06/15/2010

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag academic functioning,adolescence,depressive symptoms,OAI-PMH Harvest,peer relations

Place Name Hawaii (states), Honolulu (city or populated place)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Schwartz, David (committee chair), Farver, Jo Ann M. (committee member), Margolin, Gayla (committee member), Rueda, Robert S. (committee member), Shen, Biing-Jiun (committee member)

Creator Email srt76@hotmail.com,stom@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m3190

Unique identifier UC1231334

Identifier etd-Tom-3945 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-350243 (legacy record id),usctheses-m3190 (legacy record id)

Legacy Identifier etd-Tom-3945.pdf

Dmrecord 350243

Document Type Dissertation

Rights Tom, Shelley R.

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu