University of Southern California Dissertations and Theses

Negative peer relationships and academic failures as predictors of depressive symptoms in early adolescence

(USC Thesis Other)

Negative peer relationships and academic failures as predictors of depressive symptoms in early adolescence

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content Running head: PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS

Negative Peer Relationships and Academic Failures as Predictors of Depressive
Symptoms in Early Adolescence

Alexandra L. Cram
Masters Thesis
University of Southern California

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 2
Abstract
This short-term longitudinal investigation examines associations between academic achievement,
social functioning, and depressive symptoms among a diverse group of early adolescents.
Participants were 400 middle school students (186 Vietnamese American; 107 Mexican
American; 107 = other; mean age = 12.2 years) followed across two consecutive school years. At
both points in time, participants completed a peer nomination inventory assessing multiple
indices of social functioning (e.g. rejection, unpopularity, relational victimization, and overt
victimization) and a self-report measure of depressive symptoms. Grade point averages (GPAs)
were obtained from a review of school records. Results indicated significant positive associations
between social maladjustment and depressive symptoms at both time one and time two.
Findings, however, did not provide evidence for relations between academic functioning and
emotional adjustment at either measurement point. Taken together, results emphasize the relative
importance of peer functioning during the vulnerable period of early adolescent development.
Distinct patterns within gender and ethnic/racial subgroups are additionally discussed.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 3
TABLE OF CONTENTS
Page
ABSTRACT………..…………...………………………………………………………...... x
INTRODUCTION..........................................................................................................…… 1
METHODS………………………......................................................................................... 7
Overview .................................................................................................................. 12
Bivariate correlations and descriptive statistics........................................................ 13
Factorial invariance and cross sectional associations…………………………...… 14
Predicting T2 depressive symptoms......................................................................... 14
Gender comparison ................................................................................................. 16
Ethnic comparison .................................................................................................. 16
DISCUSSION..................................................................................................................... 18
Limitations and future directions ........................................................................... 23
REFERENCES................................................................................................................... 26
TABLES ............................................................................................................................ 37
FIGURES........................................................................................................................... 44

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 1
Negative Peer Relationships and Academic Failures as Predictors of Depressive Symptoms in
Early Adolescence
In the present research, we examine adolescent depressive symptoms through the lens of
a competency-based model of depression (i.e. Cole, 1991). This model posits that failures in
salient developmental tasks (tasks within domains of achievement relevant to an individual
during a certain developmental period) relate to depressive symptoms through individuals’
underlying views of low self-competence (Masten & Coatsworth, 1995). Specifically, this study
investigates the associations between youths’ social and academic competencies and reports of
depressive symptoms within a diverse, low-income and high achieving context. We emphasize
the distinction between success and competence, in that the latter is defined as “good adaption,
not necessarily superb achievement” (Masten & Coatsworth, 1998, pg. 206). With this in mind,
the current study’s central objective is to investigate the associations between failures in these
salient developmental tasks and youths’ emotional functioning.
Understanding risks for depression within an early adolescent population is of practical
importance given the substantial elevations in depressed mood that coincide with the onset of
this developmental period (e.g., Hankin et al., 1998; Rutter, 1991). Despite the increased
prevalence of depression during adolescence, competency-based frameworks have primarily
been tested in preadolescent samples. As peer group interactions and academic work in the
classroom constitute central challenges of middle childhood (Masten & Coatsworth, 1998;
Masten & Curtis, 2000), failures in both areas are presumed to be particularly detrimental within
these earlier years (Boivin, Poulin, & Vitaro, 1994; Hartup & Stevens, 1999; Hawker & Boulton,
2000; Schwartz et al., 2008). A normative shift in priorities over time, however, must be taken
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 2
into account when conceptualizing salient developmental tasks in an early adolescent population
(Masten & Coatsworth, 1998).
As youths transition from childhood to adolescence, peer relationships take on a more
central role in their daily lives. Early adolescents spend increased amounts of time with peers as
compared to younger children, look to peers in the formation of their own identity, and may even
restructure their own patterns of behavior and decisions to more closely resemble those of their
friends or peer group (Brown, 1990; Dishion, Spracklen, Andrews, & Patterson, 1996). Given
this developmental shift, it is hypothesized that difficulties with peers will serve as a particularly
strong risk factor for depressive symptoms in this early adolescent sample.
Although past researchers have demonstrated the negative emotional impact of a range of
aspects of peer maladjustment (e.g. rejection, victimization) in isolation (Desjardins &
Leadbeater, 2011; Hawker & Boulton, 2000; Lopez & DuBois, 2010; Prinstein & Aikins, 2004),
we are unaware of any existing studies taking a multidimensional approach in the examination of
associations between adolescents’ social and emotional functioning. Building on past research,
we measure peer relationships through four indices of social functioning indicated by past
research to be problematic within an adolescent population (Desjardins & Leadbeater, 2011;
Hawker & Boulton, 2000; Lev-Wiesel, Nuttman-Shwartz, & Sternberg, 2006; Lopez & DuBois,
2010; Martin, Cole, Clausen, Logan, & Strosher, 2003; Prinstein & Aikins, 2004; Sweeting,
Young, West, & Der, 2006). Specifically, these indices include rejection (i.e. being disliked),
unpopularity (i.e. having low dominance, social impact, and power), relational victimization (i.e.
efforts of peers to damage relationships through ignoring, exclusion, and spreading rumors), and
overt victimization (i.e. efforts of peers to harm through direct verbal or physical threats or
attacks). Our efforts to measure the experiences of youth within these four domains of social
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 3
functioning aim to capture those individuals who fail to meet the most basic requirements of
good adaption in peer relationships.
In addition to examining negative peer relationships, we explore the role of academic
performance in adolescent depressive experiences. Although investigations of middle childhood
samples tend to report moderate correlations between academic failure and depression (Cole,
1996; Schwartz et al., 2008), the transition to adolescence marks a normative decrease in
academic motivation (Anderman & Maehr, 1994; Simmons & Blyth, 1987). Several studies even
suggest that for some adolescents, social and achievement related goals stand in opposition to
one another. Perceiving their peers as low in academic motivation, certain youths may create a
need to minimize displays of their own academic efforts and achievements in order to fit in
(Fuligini, Eccles, Barber, & Clements, 2001; Juvonen & Murdock, 1993, 1995; Luthar, 1995).
Research is mixed, however, as other studies indicate small but significant positive associations
between adolescents’ functioning in social and academic domains (Cauce, 1987; Green,
Forehand, Beck, & Vosk, 1980; Berndt & Keefe, 1995; Wentzel & Caldwell, 1997; Chen,
Chang, & He, 2003). Likewise, the association between academic functioning and depressive
symptoms in this age range is somewhat unclear, extant literature reporting negative correlations
ranging from weak to moderate (Reinherz, Frost, & Pakiz, 1991; Resnick, et al., 1997; Roeser,
Eccles, & Sameroff, 1998; Shippee & Owens, 2011).
In the few studies that consider both academic and peer variables as predictors of
adolescent adjustment, associations between social relations and emotional functioning are
consistently significant and at least of a moderate strength. Correlations between academic and
emotional variables, on the other hand, range from essentially zero to significant and large.
(Cole, Martin, Powers, & Truglio, 1996; Gerard & Beuher, 2004; Luthar, 1995; Lopez &
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 4
DuBois, 2005). Although there does not appear to be a clear pattern of the role of descriptive
factors (i.e. geographic region, socioeconomic status) in relation to these associations, studies
rarely include schools’ overall academic performance in background descriptions. Given the role
of context in defining competency (Masten & Coatsworth, 1998), we aim to extend this existing
body of research through exploring our research questions within a diverse group of low-income
adolescents within the context of a relatively high achieving school. This population is of
particular interest as multiple mechanisms may effect youths’ functioning within such a context.
Changing priorities in adolescence imply that youths’ may place increasing value on social
relations and decreasing emphasis on academic achievement during this period. Yet, within the
context of a high-achieving student body, it is also possible that both social functioning and
academic achievement will continue to be central to students’ functioning in spite of these
changing developmental priorities. These two hypotheses are weighed against each other in the
present study.
Supplementary to our main hypotheses, we explore the roles of gender and ethnic/racial
group as two potentially important moderator variables of the hypothesized associations. Gender
is of particular interest as females, on average, both express significantly more depressive
symptoms than males and are more frequently diagnosed with a major depressive disorder (for
reviews, see Cyranowski, Frank, Young, & Shear, 2000; Nolen-Hoeksema, 1990). Although the
reported age of onset for this phenomenon varies slightly across studies, evidence suggests that a
gap begins to emerge within the early adolescent developmental period (Cole et al. 2002;
Hankin, et al., 1998; Twenge & Nolen-Hoeksema, 2002). Consequently, understanding gender
differences within this particular age range may capture important contributing factors in the
early phases of gender disparities in depressive symptoms.
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 5
Many theories have been developed to explain factors contributing to rising rates of
depression among adolescent girls (for a review see Nolen-Hoeksema & Girgus, 1994). The
research most relevant to the proposed hypotheses addresses dissimilarities in adolescent boys’
and girls’ value systems, expecting failures in specific areas to lead to depressive symptoms as
predicted by youth’s gender. Adolescent girls tend to value social goals (e.g., having friends,
helping others) above nonsocial goals (e.g., getting good grades, making money). Alternatively,
boys more frequently emphasize achievement, self-interest, and self-presentation (Chung &
Asher, 1996; Ford, 1982; Rose & Asher, 1999; Rose & Asher, 2004; Strough & Berg, 2000).
Consistent with these value systems, girls report more distress and hurt feelings than boys when
confronted with peer victimization (Pacquette & Underwood, 1999), higher levels of sadness in
the face of peer rejection (Goodman & Southam-Gerow, 2010), and a greater degree of
depressive symptoms in relation to not being liked (Oldenhinkle, Rosmalen, Veenstra, Dijkstra,
& Ormel, 2007; Prinstein & Aikins, 2004; Oldenberg & Kems, 1997). Boys’ depressive
symptoms, on the other hand, tend to correlate most strongly with achievement related variables,
such as poor performance in sports (Oldehinkle et al., 2007) and school dissatisfaction (Sund,
Larsson, & Wichstrom, 2003). Considering these gender differences, we hypothesized that
negative peer relationships would be more strongly related to depression for girls as compared to
boys, while poor academic functioning would be more strongly related to depression for boys as
compared to girls.
Finally, we consider the diversity of our sample and examine the role of ethnic/racial
group membership in defining salient developmental tasks. Past explorations of associations
between academic failure, social relations, and depression have taken place in samples composed
of primarily Caucasian, African-American and Hispanic youths (Cole et al., 1996; Lopez &
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 6
DuBois, 2005; Gerard & Beuher, 2004; Luthar, 2005). Beyond a theoretical interest, the
changing demographics of urban school environments necessitate increased awareness of
predictors of depression across adolescents from a broad range of backgrounds.
The ethnic/racial composition of the school in the present study is typical of a Southern
California school, with one-quarter Hispanic students (specifically Mexican-American) and
roughly half of students being a member of an Asian-American ethnic/racial group (specifically
Vietnamese-American). Conceptual considerations identify Vietnamese- and Mexican-American
adolescents as informative comparison groups. Although youths from each background tend to
be exposed to collectivist value systems (Hofstede, 2003; Oyserman, Coon, & Kemmelmeier,
2002) that emphasize the importance of social relationships (Triandis, 1995), Vietnamese-
Americans consistently outperform Mexican-Americans academically on nationwide
standardized tests of achievement (Aud, Fox, & KewelRamani, 2007). Given these patterns, we
expected that while social success would be important to youth of both cultural backgrounds,
academics might play a more prevalent role in the adjustment of Vietnamese-American as
compared to Mexican-American youth. Consistent with this hypothesis, one study finds that the
school relationship relates to Asian-American students’ expressed levels of depressive symptoms
while making no contribution to the adjustment of Hispanic students (Moon & Rao, 2010). To
date, we are unaware of any existing studies comparing the associations between social and
academic functioning and depressive symptoms among Asian-American and Hispanic youths, or
examining depression among Mexican- and Vietnamese-American youths specifically.
Current Study. In order for tests of competency-based models of depression to continue
to evolve, there is a necessity for fully elaborated designs that incorporate a simultaneous focus
on multiple salient predictors among emerging adolescents. Furthermore, given the diverse
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 7
composition of today’s urban environments, there is a clear need for research that translates
existing developmental models to students from different economic, geographical, and ethnic
backgrounds. Finally, this is the first known study to examine the extent to which social and
academic variables predict depression in a population of primarily Vietnamese- and Mexican-
American adolescents.
Given the body of existing research, we proposed two rivaling hypotheses regarding the
associations between negative peer relationships, academic success, and depressive symptoms
within our early adolescent sample. On the one hand, the importance of peers in this
developmental period suggests that difficulties in social relations will be positively related to
depressive symptoms while academic achievement will not be related to depressive symptoms.
In contrast, the high achieving context in which this study was conducted may indicate that both
indicators of competency will continue to be tied to adolescent depressive symptoms. We
additionally made several secondary hypotheses regarding the role of gender and ethnic/racial
groups in our analyses. Specifically, it was expected that peer relations would be more predictive
of depressive outcomes for girls as compared to boys and that academic success would be more
closely tied for boys as compared to girls. We also expected that academics would be more
strongly related to depressive symptoms for Vietnamese-American as compared to Mexican-
American youth.
Methods
Participants
The current project was completed within the context of the University of Southern
California Academic Success Project (ASP). This ongoing longitudinal study is comprised of a
unique and diverse sample of middle school students in the Southern California region (46.5%
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 8
Vietnamese American, 3.6% other Asian/ Pacific Islander, 26.8% Mexican American, 2.3%
other Hispanic/ Latino, 1.8% non-Hispanic White, 0.3% African American, 18.8% Mixed, and
2.2% not classified). The majority of participating students identified as first- or second-
generation immigrants (71.9% and 22.9% respectively), which is consistent with the
demographics of the Vietnamese-American ethnic enclave within which the school is located.
According to the 2010 U.S. Census Bureau, income levels of residents in this district rank within
the lower middle range of nationwide socioeconomic status (SES; U.S. Census Bureau, 2010)
and students’ reports of their parents’ education, income, and current job status also fell below
these national averages (Duong & Schwartz, 2012). Likewise, school records qualified 72.0% of
participants for a free or reduced-price lunch program during the 2008-2009 and 2009-2010
school years.
As required by California's Public Schools Accountability Act of 1999, the participating
school’s Academic Performance Index (API) is publicly listed by the California Department of
Education (California Department of Education, 2011). This measure provides a numerical
academic performance score for districts, schools, and ethnic subgroups based on the results of
statewide testing. Overall, the participating school’s API fell within the moderate to high range
as compared to other California Middle Schools. The school’s Asian-American population
scored slightly higher on this measure than the overall average of Asian-American students
across California, and in the top quartile when compared to the combined averages of students of
all ethnic/racial groups. Hispanic students attending the school were in the top quartile for all
Hispanic students statewide but performed below state averages across ethnic/racial groups.
When Asian American and Hispanic ethnic/racial groups were compared within the participating
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 9
school, Asian-American students outperformed Hispanic students on this measure of academic
achievement.
Recruitment
For Year 1 (Y1) recruitment, 6
th-
and 7
th
-graders attending the specified middle school
(562 students) were invited to participate in the project. Following the recommendations of
school officials, students enrolled in self-contained special education classes and limited English
proficiency classes were excluded from the recruitment process. English, Vietnamese, and
Spanish versions of parental consent forms were distributed to all eligible students to take home.
On the day of testing, youth were also asked to indicate if they agreed to participate in the study
through signing a student assent form. Students received small individual rewards for returning
the consent forms (i.e. candy or stickers) regardless of whether their guardians denied or
confirmed participation. In addition, all classes with an 80% consent form return rate or above
were given a larger communal reward (a class pizza party).
Attrition and Retention
Four hundred fifty-three 6
th
- and 7
th
-graders (80.6% of all eligible; M = 12.2) participated
in Y1 data collection. Students self-identifying as Mexican-American (N = 129; 72 girls, 57
boys) or Vietnamese-American (N = 207; 105 girls, 102 boys) comprised 74.2% of the original
sample. The retention rate (88.3%) was high across the two years of the study (N=400; 213 girls,
187 boys; Mexican-American N = 107; 58 girls, 49 boys; Vietnamese-American N = 186; 94
girls, 92 boys).
Procedure
Data was collected at the end of spring semester 2009 and 2010 via group-administration
by trained graduate and undergraduate researchers. During each 70-minute session, one
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 10
administrator read standardized instructions and questionnaire items out loud to the class while a
second administrator circulated the classroom answering participants’ questions. Students
completed a demographic survey, a self-report questionnaire recording depressive symptoms,
and a peer-nomination inventory assessing social relationships.
Measures
Demographic variables. As recommended by Phinney (1992), students were asked to
identify their own ethnicity on the first page of the questionnaire packet. Students’ genders and
grade levels were obtained from school records.
Social standing and peer victimization. Each participant was provided with a list of 50
random peers from their grade level and asked to identify up to nine students who fit into a series
of descriptors. All participating students’ names appeared on 50 separate lists and a participant’s
name never appeared on his or her own list. Students used the unique identification numbers
from the same 50-student list for social rejection, unpopularity, and victimization peer
nomination items. The total number of nominations a student received for this item was
standardized within each list in order to control for the random fluctuations occurring across
lists. Although peer nomination research looking at elementary students typically uses an entire
class list (e.g. Hymel, 1986), the procedure implemented in the proposed study is ideal for
middle school students as they interact with peers in various classes throughout the day (e.g.
Schwartz, Gorman, Nakamota, & McKay, 2006). In addition, researchers acquired participants’
course grades from school administration following the completion of the academic year.
Using the 50-student list identified in the peer nominations procedure, participants
nominations of up to nine students who they “didn’t like that much” was used as an indicator of
rejection (Nelson & Dishion, 2004; Schwartz et al. 2008). Peer nominations of up to nine
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 11
students who were “unpopular” were used as indicators of low social status (Cillessen &
Mayeux, 2004). Finally, participants were asked to identify up to nine peers for four items
describing students who were victimized at school. This measure included questions designed to
cover two subtypes of victimization. Relational victimization questions addressed students who
get “mean things said about them” and were “excluded or ignored” by other students (at Time 1
[T1], r = .38, p < .001; at Time 2 [T2], r = .63, p < .001. Physical victimization questions asked
about students who get “hit, pushed, or bullied” and “beat up” (at T1, r = .37, p <.001 at T2, r =
.62, p = .00). The relational victimization and physical victimization scores were kept as two
separate items in the proposed analyses as past research indicates distinctness between these two
constructs (Crick & Grotpeter, 1995).
Depressive symptoms. Participants’ reports of depressive symptoms were measured with
the Children’s Depression Inventory (CDI; Kovacs, 1985). This frequently used and well
validated self-report instrument measures depression in children and adolescents. Each of the 27
items on this scale is composed of three sentences describing varying degrees of severity in
symptoms or a consequence of symptoms of depression. We dropped one item from this measure
that inquires about suicidal ideation. Each item is scored 0, 1, or 2, with higher numbers
indicating increasing symptom severity. The CDI includes five subscales: negative mood (6
items; at T1, α = .71; at T2, α = .76), interpersonal problems (4 items; at T1, α = .53; at T2, α =
.59), ineffectiveness (4 items; at T1, α = .63; at T2, α = .65), anhedonia (8 items; at T1, α = .70;
at T2, α = .74), and negative self-esteem (4 items; at T1, α = .70; at T2, α = .66). Derivation and
validation of the subscales is described by Kovacs (1992). There were two items on the
interpersonal problems scale and one item on the anhedonia scale that assessed adolescents’ own
perceptions of academic and social proficiency. Because of conceptual tautology with our
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 12
predictor variables we dropped these items from analysis (ineffectiveness = 2 items; at T1, α =
.29; at T2, α = .43; anhedonia = 7 items; at T1, α = .67; at T2, α = .73).
Academic achievement. Students’ year-end grades in five academic courses (science,
mathematics, social science, reading, and language arts) were recorded to determine academic
functioning. For each student, letter grades were converted into numerical scores (“F” = 0 to “A”
= 4) for each of the five courses. Given a considerable overlap between students’ grades in
reading and language arts (at T1 r = .76, p = .000; at T2 r = .77, p = .000), these two scores were
combined and averaged into a single score prior to analyses.
Results
Overview
The main hypotheses of this study focused on examining predictive associations between
competencies in academic and social domains and depressive tendencies. We also consider
gender and ethnicity as potential moderator constructs. Given the makeup of our sample,
analyses of ethnicity as a moderator included only Mexican- and Vietnamese-American youths.
To address these objectives, we relied on a series of latent variable models. The hypothesized
models (see Figures 1 and 2) and gender/ethnic differences between these models were tested
with structural equation modeling (SEM) using the AMOS 5.0 statistical package (Arbuckle,
2003).
Before examining structural pathways, we conducted careful examinations of model
parameters through evaluating three indices of fit: the chi-square statistic, the comparative fit
index (CFI), and the root-mean-square residual error of approximation (RMSEA). Each of these
measures assesses a different aspect of goodness-of-fit. The most traditionally tested
measurement of fit, the chi-square statistic, provides a statistical test of whether the difference
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 13
between the actual and reconstructed model structures are significant, or the models’ “badness of
fit.” As this statistic tends to be biased toward significant effects in large sample sizes,
acceptable fit is instead indicated when the ratio of the chi-square to degrees of freedom does not
exceed 3.0 (Carmines & McIver, 1981). Secondly, we examined the comparative fit index (CFI;
Bentler, 1990), which ranges from zero to one and is derived from the comparison of the
hypothesized model with the independence (or null) model in which all variables are assumed to
be uncorrelated. CFI values greater than .90 are considered to be an adequate fit. Finally, the
RMSEA is an index that incorporates adjustments for model complexity (i.e. the number of
parameters in the model) in estimating error of approximation in the population. Browne and
Cudeck (1993) suggested that a RMSEA value of .08 or less indicate acceptable model fit. Byrne
(2010) describes each of these indices in greater detail.
Bivariate correlations and descriptive statistics
Means and standard deviations for each of the variables are presented in Table 1. In order
to minimize the influence of skewness of variable distributions in our analyses, log
transformations were applied to all variables prior to model specification. Bivariate correlations
among the variables are summarized in Table 2. As indicated in the table, the stability of the
constructs across the two waves of data collection generally fell in the moderate range. Although
the associations were relatively small, there was a pattern of positive correlations between the
indicators for negative peer relations and depressive symptoms as well as a pattern of negative
correlations between academic functioning and depressive symptoms.
In our analyses, gender (0 = male; 1 = female) and ethnicity (0 = Mexican-American; 1 =
Vietnamese-American) were coded as dichotomous variables. Compared to boys, girls were
more likely to be rejected and to receive lower grades in math and science. Additionally, there
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 14
was an association between ethnicity and academic functioning such that Vietnamese-American
youths received higher grades than Mexican-American youths in all four academic areas at both
time points (see Table 1). The effect sizes for all significant associations related to gender and
ethnicity were small (Cohen, 1988).
Factorial Invariance.
Prior to conducting inferential analyses, we conducted a series of models to demonstrate
factorial invariance (Byrne, Shavelson, & Muthén, 1989). Although for the most part, our models
met model assumptions, there were several notable exceptions. Within the T1 correlational
model and at T2 within the longitudinal model, we found partial factorial invariance with a
difference of the loading of social science onto academic functioning between genders (T1: Δχ
2

(1) = 19.95, p < .05; T2: (Δχ
2
(1) = 9.35, p < .05), with a higher weight placed on this measure
for boys (T1: ß = .65, p < .001; T2: ß = .76, p < .001) as compared to girls (T1: ß = .47, p < .001;
T2: ß = .48, p < .001). Additionally, in the longitudinal model, we found partial factorial
invariance in our measure of negative social relationships with a difference of the loading of T2
unpopularity across genders (Δχ
2
(1) = 5.22, p < .05), with a greater weight placed on this
measure for boys (ß = .52, p < .001) as compared to girls (ß = .28, p < .001). The overall pattern
of factor loadings, however, remained the same between genders in both the T1 and longitudinal
models. As suggested by Byrne (2010), partial factorial invariance was sufficient to proceed with
higher-level analyses of structural pathways.
Cross sectional associations
Our first substantive analysis examined the hypotheses that T1 negative peer relations
and academic functioning were associated with T1 depressive symptoms. We specified a latent
variable model including T1 negative peer relations, T1 academic functioning, and T1 depressive
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 15
symptoms. The observed indicators for the T1 negative peer relationships variable included peer
reports of T1 rejection, unpopularity, relational victimization, and overt victimization. T1
academic functioning was indicated by school reports of T1 second semester grades in science,
math, and social science, and a language-reading score calculated from the average of students’
language arts and reading grades. Finally, the observed indicators for T1 depressive symptoms
were participant scores on the CDI of T1 ineffectiveness, negative self-esteem, anhedonia,
interpersonal problems, and negative mood.
The final model fit the data acceptably well (Model 1; see Table 3), and the overall
pattern of findings was supportive of the hypothesized associations. As illustrated in Figure 1,
each of the factor loadings was significant. There was a moderate positive association between
T1 negative peer relationships and T1 depressive symptoms, as well as a moderate negative
relation between T1 negative peer relationships and T1 academic functioning. The T1
association between academic functioning and depressive symptoms was negative, but marginal.
Next, we focused on replicating the T1 analyses with T2 variables. The final model again
fit the data acceptably well (Model 2; model fit statistics are summarized in Table 3), and
supported the overall pattern of findings of the hypothesized associations. The direction and
magnitude of correlations addressing substantive hypotheses partially replicated those in T1 with
a significant path between T2 negative peer relationships and T2 depressive symptoms (ß = .16,
p < .01) and a marginal association between T2 academic functioning and T2 depressive
symptoms (ß= -.11, p < .08). The relation between negative peer relationships and academic
functioning, however, was no longer significant at T2 (ß = -.03, ns). Overall, findings supported
our correlational hypotheses in both years of data collection.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 16
Predicting T2 Depressive Symptoms from T1 Negative Peer Relations and T1 Academic
Functioning
After examining the pattern of cross-sectional correlations among the latent variables in
T1 and T2 separately, we considered associations between negative peer relations, academic
achievement, and depressive symptoms across the two years of data collection. The full pattern
of longitudinal relations was assessed within the context of a model including measures of peer,
academic, and emotional functioning at both points in time (Cole & Maxwell, 2003). The
described model (Model 3; Figure 2) fit the data acceptably well (see Table 3). Analyses of the
association between T1 and T2 measures of each of the three latent constructs, revealed
moderate to high variable stability across years (see Figure 2). In particular, associations between
T1 academic functioning and T2 academic functioning approached 1.0. Given this high level of
stability, it is perhaps not surprising that we did not find a strong effect of longitudinal
associations. That is, social relationships and academic functioning at T1 were not significantly
associated with depressive symptoms at T2 in the context of the full cross-panel model.
Gender Comparisons
We next examined the hypothesis that the associations between negative peer relations,
academic functioning, and depressive symptoms would be moderated by youths’ gender. There
were no significant differences in latent variable correlations between the two genders at T1 (See
Table 4). When looking at girls and boys separately, however, distinct patterns emerged within
each gender. For girls the association between negative peer relations and depressive symptoms
was significant, as was the correlation between negative peer relations and academic functioning.
For boys, no associations were significant between any of the latent variables (See Table 5).
At T2, however, there was a significant difference in correlations between boys and girls
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 17
(See Table 4). When the pathways between each of the three latent variables were examined
independently, there was a significant difference in the association of negative peer relationships
and academic functioning, which was significant for girls but not boys (Δχ
2
(1) = 7.242, p < .01;
see Table 4 for gender specific correlations). T2 gender patterns in relation to substantive
hypotheses replicated those at T1. For girls, there was a significant relation between negative
peer relations and both depressive symptoms and academic functioning. For boys, no
correlations were significant (See Table 4).
Additionally, in the longitudinal model, there was a difference in the association between
T1 negative peer relations and T1 academic functioning (Δχ
2
(1) = 8.247, p < .001). For boys,
these variables were not significantly related (r = .03, ns) while for girls there was a negative
correlation (r = -.29, p < .01). There was also a difference in the stability academics between
genders (Δχ
2
(1) = 22.347, p < .001). Boys’ T1 academic functioning was a stronger predictor
of T2 academic functioning (B = .95, p < .001) than it was for girls (B = .87, p < .001).
Ethnic Comparisons
Finally, we examined each model comparing Mexican-American and Vietnamese-
American youths. Regarding ethnicity, constraining covariances did not produce a significant
Δχ
2
at either T1 or T2 (See Table 6). Distinct patterns did emerge when viewing the model
within the two ethnic/racial groups separately. For Mexican-American students, the only
significant correlation at either time point was the T1 association between negative peer
relationships and depressive symptoms. For Vietnamese-American students, however, at T1,
academic functioning was significantly negatively associated with depressive symptoms and
positively associated with peer functioning. Vietnamese-American T1 negative peer relationships
were not correlated with T1 depressive symptoms. The association between academic
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 18
functioning and depression held across T2 for Vietnamese-American participants but negative
peer relationships were no longer significantly related to either depressive symptoms or
academic functioning at T2.
Discussion
In this study, we examined a competency-based model of depression within a diverse,
relatively high achieving, early adolescent sample. Prior research conducted in middle childhood
samples has frequently tied both academic and social failures to depressive symptoms (Boivin et
al., 1994; Hartup & Stevens, 1999; Hawker & Boulton, 2000; Schwartz et al., 2008). In contrast
to these younger populations, findings from the present study suggest associations between early
adolescent social and emotional, but not academic and emotional functioning. This pattern of
results compliments existing literature that suggests adolescents place a greater priority on peer
relationships (Prinstein & Aikins, 2004) and a decreasing investment in academic success
(Anderman & Maehr, 1994; Simmons & Blyth, 1987) upon the entry to middle school. To our
knowledge, however, the current study is one of the first to directly focus on and
comprehensively examine associations between these variables across multiple years within the
period of early adolescence. Present research additionally builds upon prior literature through the
exploration of these variables in a unique and diverse population, the implementation of multiple
indices of social relationships, and independent informants for social, academic, and emotional
functioning within a competency-based model of early adolescent depression.
To investigate our research questions, we conducted SEM analyses assessing social
adjustment, academic functioning, and depressive symptoms at two waves of data collection. As
hypothesized, results suggested positive associations between negative peer relationships and
depressive symptoms within both the first and second year of measurement. In contrast,
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 19
associations between academic functioning and depressive symptoms were only marginal at both
points in time.
We consider several possible interpretations of these findings. Most relevant to our
central hypotheses, these results may indicate that social relationships play a central role within
an adolescent competency-based framework of depression. Masten and Curtis (2000) frame
maladaption within a developmental model of competence, conceptualizing it as a failure to meet
society’s expectations for important developmental areas. The theoretical underpinning of the
relation between performance in developmentally relevant domains and depressive symptoms is
that youth internalize feedback from others in response to their performance. As a result, they
learn to regard themselves in the ways they are seen by others (see Cooley, 1902; Mead, 1934).
The centrality of peer comparison in adolescent self-appraisal (Harter, Stocker, & Robinson,
1996) may exacerbate this process.
A more complete explanation, however, might consider a reciprocal model of causation.
Prior research has indicated that in addition to peer difficulties contributing to youths’ depressive
symptoms, social skills deficits displayed by depressed youths foster social isolation and disrupt
interpersonal interactions (Coyne, 1976; Hops et al., 1987). Early adolescents’ focus on social
interactions (Brown, 1990) may exacerbate such a cycle with unskilled social behavior displayed
by depressed individuals evoking more negative reactions from their peers during this stage of
life.
Regardless of the direction of causation, this pattern indicates that early adolescents with
social difficulties are at heightened risk for experiencing depressive symptoms. We do not find
evidence, on the other hand, that academics are significantly related to depressive symptoms
within this particular sample. Unfortunately, although numerous empirically validated programs
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 20
are well-established in improving youths’ academic functioning (Bangert-Drowns, Hurley, &
Wilkinson, 2004; Gettinger & Herd, 2011), the majority of schools do not use effective
implementations of evidence-based programs designed to enhance social-emotional development
(Gottfredson & Gottfredson, 2002; Ringwalt et al., 2009). Current findings are of interest in that
they suggest the integration of social-emotional programs into the school system may be
beneficial for early adolescents’ overall adjustment.
In addition to exploring correlations between constructs, our analyses noted high stability
within all three substantive variables across the two years of this study. Similar patterns have
emerged in prior studies including similar measures, with construct stability typically decreasing
with more time between measurement points (Cole et al., 1996; Luthar, 1995; Sandstrom &
Cillessen, 2006; Wierzbicki & McCabe, 1988; Lewinsohn et al., 1994). Measurement stability
provides important insights into the dynamics within this middle school system. Findings
indicate that by the first year of middle school, social, academic, and emotional patterns have
already been established, deficits in each area remaining stable across a two-year period. Such
stability is concerning as it suggests problems in each area may potentially interrupt normative
developmental processing over extended periods of time. Furthermore, as those early adolescents
struggling socially are likely to experience depressive symptoms, youths with deficits in one area
are at risk for maladjustment across multiple domains as well as multiple years.
Following the exploration of the associations between social, academic, and emotional
functioning in the sample as a whole, we investigated whether our findings were stable across
gender. Although there were no significant differences in the associations between social or
academic functioning and depressive symptoms, a significant group difference did emerge in the
second year of the study in the association between the two indicators of competency.
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 21
Specifically, for girls, social difficulties were related to poor academic functioning. For boys, on
the other hand, these variables were not significantly related. Granting this finding was not a
central hypothesis in the current study, a greater social cost for doing poorly in school for girls as
compared to boys may suggest that failure in either area might demand particular attention for
female adolescents.
As our sequential SEM model comparisons did not provide evidence that gender serves a
moderating effect on our substantive hypotheses, we discuss patterns independently within each
gender subgroup in order to inform directions for future gender comparisons within larger
samples. Among female adolescents, peer relationships were associated with depressive
symptoms as well as academic functioning at both points of measurement. These findings may
be consistent with the hypothesis that girls’ tendency to place self worth in social functioning
during a life stage characterized by increasing peer conflict may be one underlying factor of the
increasing prevalence of depression among adolescent girls (Collins & Laursen, 1992).
Furthermore, given the relative importance of social communication and verbal sharing within
female relationships (Frey & Röthlisberger, 1996; Maccoby, 1990), interpersonal deficits
displayed by depressive girls could evoke particularly negative reactions from their peers. For
boys, on the other hand, there were no significant associations between variables at either point
in time. This may suggest that different processes exist among male adolescents.
Following the investigation of gender differences, we also examined our variables within
the two primary ethnic subgroups in the sample, Vietnamese- and Mexican-American youth.
Again, as no significant group differences emerged in these comparisons, we investigated within
group patterns of Mexican- and Vietnamese-American ethnic/racial subgroups in order to
generate hypotheses for future testing. For Mexican-American students, although there was a
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 22
significant correlation between negative peer relationships and depression in the first year of data
collection, these variables did not correlate across the two years. The relation between academics
and depression, on the other hand, was not significant at either time point. The findings within
this subgroup may replicate those of the overall sample, only reaching significance within one
year, perhaps due to a smaller sample size and lower power. This weak evidence of increased
value placed in peer relationships for emotional adjustment within a Mexican-American
population calls for further investigation in a larger sample of Mexican-American youth.
Among Vietnamese-American youths, on the other hand, a distinct pattern emerged. To
our knowledge, such a pattern has not been observed in extant research of adolescent
populations. For this subgroup, the negative association between academic functioning and
depressive symptoms was significant across both years of the study. The association between
negative peer relationships and depressive symptoms, however, was not significant at either time
point examined. Prior research has indicated that many Asian-American peer cultures encourage
high educational aspirations (Fletcher, Darling, Steinberg, & Dornbusch, 1995; Steinberg,
Dornbusch, & Brown, 1992). The current study, however, additionally finds that even within the
emerging social priorities of adolescence, academics may still continue to play a central role in
emotional functioning for this ethnic/racial group. These findings could also be explained by a
reaction to the “model minority” stereotype. That is, perhaps Vietnamese-American youth feel
extra pressure from teachers and peers to achieve academically due to racial stereotypes of
Asian-Americans as a high achieving group (Tran & Birman, 2010). An inability to meet these
high standards may heighten the risk for developing symptoms of depression. Regardless of
underlying causal factors, findings within this ethnic/racial subgroup emphasize the possibility
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 23
that academic failure may be a salient sign of maladjustment among Vietnamese-American early
adolescents and call for future exploration among larger samples of this particular subgroup.
Overall, our hypotheses were partially supported in the current study. Findings emphasize
the role of developmental period in a competency-based model of depression. Within this early
adolescent sample, we found significant associations between social failures and depressive
symptoms. We did not, however, find any evidence in support of the association between
academic and emotional functioning. One important implication from these findings is that
school based mental health professionals acknowledge the value of social relations during
adolescence, even within a relatively high achieving school. On a policy level, although it is
important to continue to emphasize academic success given the long-term impact of school
success or failure on career and social outcomes (Rumberger, 1987), it may be of value to
additionally begin to support adaptive social adjustment.
Limitations and Future Directions.
Several limitations and unexpected findings within the current study suggest directions
for future research. First, given interindividual stability across the two time points of data
collection, we are unable to make causal statements or reject-third variable explanations for our
findings. Future research should include additional points of measurement in order to capture the
more meaningful intraindividual fluctuations across time. Second, the dimensional measurement
of depressive symptoms is consistent with research indicating depression as a continuous
distribution of severity (Hankin, Fraley, Lahey, & Waldman, 2005). Dimensional findings may
suggest the importance of broad scale school-based interventions for youth at various levels of
emotional maladjustment. Nevertheless, there are critics of dimensional investigations of
depressive symptoms (Solomon, Ruscio, Seeley, & Lewinsohn, 2006), and we suggest that
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 24
future investigations build on this competency-based model by observing these variables in a
clinical population with depression measured by clinician assessment. Third, although not central
to our research questions, we found that the relations between competency indicators were not as
clear as correlates of depression. That is, at the first measurement point, there was a moderate
negative association between negative peer relationships and academic functioning. Somewhat
surprisingly, this association was no longer significant at the second measurement point.
Potential factors underlying this curious pattern calling for further exploration.
Results additionally suggest that research continue to explore the role context, culture,
and gender in competency based models of depression. The overall pattern was replicated within
female and Mexican-American adolescents while boys did not seem to be described by this
model. Future research may reveal that Vietnamese-American youths are a unique sample, with
academics playing a greater role than peer relationships in depressive symptoms within this
subgroup. Additionally, given power concerns in the current study, we were not able to look at
effects within each gender-ethnicity pairing (e.g. Vietnamese-American girls, Mexican-
American boys, etc.). Prior research suggesting conflicting roles of social and academic values
for certain male minority subgroups (Ogbu, 2004; Taylor & Graham, 2007) point future research
to examine these research questions among specific gender-ethnic pairings. Finally, given the
specificity of our sample (Mexican- and Vietnamese- American youths within a high achieving
ethnic enclave in Southern California), we caution against the generalization of the results of our
study outside of this scope. On the other hand, the increasing diversity of any school system
defines no school context as truly “typical”. Thus, we believe a central message to be taken from
our results is that caution should be taken in generalizing any findings beyond a particular
context without fully exploring and recording the intricacies of that sample. Future research in
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 25
this area should also be mindful to report the characteristics of each sample (including the
neighborhood and school context, gender, and ethnic/racial groups). When power is sufficient,
such studies may additionally break down the sample as a whole into more specific subgroups in
order to more specifically define the population of interest.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 26
References
Anderman, E., & Maehr, M. L. (1994). Motivation and schooling in the middle grades. Review of
Educational Research, 64, 287–309.
Aud, S., Fox, M. A., KewalRamani, A. (2010). Status and trends in the education of racial and
ethnic minorities (NCES 2010-015). Washington, DC: U.S. Department of Education.
Bangert-Drowns, R., Hurley, M. M., & Wilkinson, B. (2004). The effects of school-based
writing-to-learn interventions on academic achievement: A meta-analysis. Review of
Educational Research, 74(1), 29-58.
Bentler, P. M. (1990). Comparative fix indexes in structural models. Psychological Bulletin, 107,
238–246.
Berndt, T. J., & Keefe, K. (1995). Friends’ influence on adolescents’ adjustment to school. Child
Development, 66, 1312–1329.
Boivin, M., Poulin, F., & Vitaro, F. (1994). Depressed mood and peer rejection in childhood.
Development and Psychopathology, 6, 483– 498.
Brown, B. B. (1990). Peer groups and peer cultures. In S. S. Feldman & G. R. Elliott (Eds.), At
the threshold: The developing adolescent (pp. 171-196). Cambridge, MA: Harvard
University Press.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen
& J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park,
CA: Sage.
Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications,
and programming (2
nd
ed.). New York, NY, US: Routledge/Taylor & Francis Group,
New York, NY.
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 27
Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the equivalence of factor
covariance and mean structures: The issue of partial measurement invariance.
Psychological Bulletin, 105(3), 456-466.
California Department of Education. (2011). 2011 Adequate Yearly Progress Report. Carmines,
E., & McIver, J. (1981). Analyzing models with unobserved variables: Analysis of
covariance structures. In G. Bohrnstedt & E. Borgatta (Eds.), Social measurement:
Current issue (pp. 65–115). Beverly Hills, CA: Sage.
Carmines, E. G., & McIver, J. P. (1981). Analyzing models with unobserved variables: Analysis
of covariance structures. In G. W. Bohrnstedt & E. F. Borgatta (Eds.), Social
measurement: Current issues. Beverly Hills, CA: Sage.
Cauce, A. M. (1987). School and peer competence in early adolescence. A test of domain
specific self-perceived competence. Developmental Psychology, 23, 287–291.
Chen, X., Chang, L., & He, Y. (2003). The peer group as a context: Mediating and moderating
effects on the relations between academic achievement and social functioning in Chinese
children. Child Development, 74, 710–727.
Chung, T., & Asher, S. (1996). Children’s goals and strategies in peer conflict situations.
Merrill-Palmer Quarterly, 42, 125–147.
Cillessen, A. H. N., & Mayeux, L. (2004). From censure to reinforcement: Developmental
changes in the association between aggression and social status. Child Development, 75,
147–163.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. (2nd ed.). Hillsdale, NJ:
Erlbaum.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 28
Cole, D. A. (1991). Preliminary support for a competency-based model of depression in children.
Journal of Abnormal Psychology, 100, 181-190.
Cole, D. A., Martin, J. M., Powers, B., & Truglio, R. (1996). Modeling causal relations between
academic and social competence and depression: A multitrait-multimethod longitudinal
study of children. Journal of Abnormal Psychology, 105(2), 258-270.
Cole, D. A., & Maxwell, S. E. (2003). Testing mediational models with longitudinal data: Myths
and tips in the use of structural equation modeling. Journal of Abnormal Psychology,
112, 558–578.
Cole, D. A., Tram, J., Martin, J., Hoffman, K., Ruiz, M., Jacquez, F., & Maschman, T. (2002).
Individual differences in the emergence of depressive symptoms in children and
adolescents: A longitudinal investigation of parent and child reports. Journal of
Abnormal Psychology, 111, 156–165.
Collins, W. A., & Laursen, B. (1992). In Shantz C. U., Hartup W. W. (Eds.), Conflict and
relationships during adolescence. New York, NY, US: Cambridge University Press, New
York, NY.
Cooley, C. H. (1902). Human nature and the social order New York: Scribner.
Coyne, J. C. (1976). Depression and the response of others. Journal of Abnormal Psychology,
85, 186-193.
Crick, N. R., & Grotpeter, J. K. (1995). Relational aggression, gender, and social-psychological
adjustment. Child Development, 66, 710–722.
Cyranowski, J. M., Frank, E., Young, E., & Shear, K. (2000). Adolescent onset of the gender
difference in lifetime rates of major depression: A theoretical model. Archives of General
Psychiatry, 57, 21-27.
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 29
Desjardins, T. L., & Leadbeater, B. J. (2011). Relational victimization and depressive symptoms
in adolescence: Moderating effects of mother, father, and peer emotional support. Journal
of Youth and Adolescence, 40(5), 531-544.
Deaux, K. (1996). Social identification. In E. T. Higgins & A. W. Kruglanski (Eds.), Social
psychology: Handbook of basic principles (pp. 777– 798). New York: Guilford Press.
Dishion, T. J., Spracklen, K. M., Andrews, D. M. & Patterson, G. R. (1996). Deviancy training
in male adolescent friendships. Behavior Therapy, 27, 373-390.
Duong, M. & Schwartz, D. (2009). Associations between social adjustment and academic
achievement among Mexican American and Vietnamese American early adolescents
(Spring, 2010). Unpublished manuscript. University of Southern California.
Fletcher, A. C., Darling, N. E., Steinberg, L., & Dornbusch, S. M. (1995). The company they
keep: Relation of adolescents’ adjustment and behavior to their friend’s perceptions of
authoritative parenting the in the social network. Developmental Psychology, 31, 300–
310.
Ford, M. E. (1982). Social cognition and social competence in adolescence. Developmental
Psychology, 18, 323–340.
Frey, C. U., & Röthlisberger, C. (1996). Social support in healthy adolescents. Journal of Youth
and Adolescence, 25, 17–31.
Fuligni, A. J., Eccles, J. S., Barber, B. L. & Clements, P. (2001). Early adolescent peer
orientation and adjustment during high school. Developmental Psychology, 37, 1, 28-36.
Gerard, J. M., & Buehler, C. (2004). Cumulative environmental risk and youth maladjustment:
The role of youth attributes. Child Development, 75(6), 1832-1849.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 30
Gettinger, M., & Hurd, H. D. (2011). In Davis A. S. (Ed.), Developing and implementing
evidence-based academic interventions. New York, NY, US: Springer Publishing Co,
New York, NY.
Goodman, K. L. & Southam-Gerow, M. A. (2010). The regulating role of negative emotions in
coping with peer rejection. Child Psychiatry and Human Development, 41, 515-534.
Gottfredson, D. C., & Gottfredson, G. D. (2002). Quality of school-based prevention programs:
Results from a national survey. Journal of Research in Crime and Delinquency, 39, 3–35.
Green, K. D., Forehand, R., Beck, S. J., & Vosk, B. (1980). An assessment of the relationships
among measures of children's social compe-tence and children's academic achievement.
Child Development, 51, 1149-1156.
Hankin, B. L., Abramson, L. Y., Moffitt, T. E., McGee, R., Silva, P. A., & Angeli, K. E. (1998).
Development of depression from preadolescence to young adulthood: Emerging gender
differences in a 10-year longitudinal study. Journal of Abnormal Psychology, 107, 128-
140.
Hankin, B. L., Fraley, R. C., Lahey, B. B., & Waldman, I. D. (2005). Is depression best viewed
as a continuum or discrete category? A taxometric analysis of childhood and adolescent
depression in a populationbased sample. Journal of Abnormal Psychology, 114, 96–110.
Harter, S., Stocker, C., & Robinson, N. (1996). The perceived directionality of the link between
approval and self-worth: The liabilities of a looking glass self orientation among young
adolescents. Journal of Research on Adolescence, 6, 285–308.
Hartup, W. W., & Stevens, N. (1999). Friendships and adaptation across the life span. Current
Directions in Psychological Science, 8, 76 - 79.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 31
Hawker, D. S. J., & Boulton, M. J. (2000). Twenty years’ research on peer victimization and
psychosocial maladjustment: A meta-analytic review of cross-sectional studies. Journal
of Child Psychology and Psychiatry, 41, 441-455.
Hofstede, G. (2003). Culture’s consequences: Comparing values, behaviors, institutions and
organizations across nations (2nd ed.). Newbury Park, CA: Sage.
Hops, H., Biglan, A., Sherman, L., Arthur, J., Friedman, L., & Osteen, V. (1987). Home
observations of family interactions of depressed women. Journal of Consulting and
Clinical Psychology, 55. 341-346.
Hymel, S. (1986). Interpretations of peer behavior: Affective bias in childhood and adolescence.
Childhood Development, 57, 431–445.
Juvonen, J., & Murdock, T. B. (1993). How to promote social approval: Effects of audience and
outcome on publicly communicated attributions. Journal of Educational Psychology, 85,
365-376.
Juvonen, J., & Murdock, T. B. (1995). Grade-level differences in the social value of effort:
Implications for self-presentation tactics of early adolescents. Child Development, 66,
1694-1705.
Kovacs, M. (1985). The Children’s Depression Inventory. Psychopharmacology Bulletin, 21,
995–998.
Kovacs, M. (1992). Children's Depression Inventory (CDI) manual. North Tonawanda, NY:
Multi- Health Systems.
Lev-Wiesel, R., Nuttman-Shwartz, O., Sternberg, R. (2006). Peer rejection during adolescence:
Psychological long-term effects – a brief report. Journal of Loss & Trauma, 11, 131–142.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 32
Lewinsohn, P. M., Roberts, R. E., Seeley. J. R., Rohde, P., Gotlib, I. H., & Hops, H. (1994).
Adolescent psychopathology: II. Psychosocial risk factors for depression. Journal of
Abnormal Psvchologv, 103, 302-315.
Lopez, C., & DuBois, D. L. (2005). Peer victimization and rejection: Investigation of an
integrative model of effects on emotional, behavioral, and academic adjustment in early
adolescence. Journal of Clinical Child and Adolescent Psychology, 34, 25-36.
Luthar, S. S. (1995). Social competence in the school setting: Prospective cross-domain
associations among inner-city teens. Child Development, 66(2), 416-429.
Maccoby, E. E. (1990). Gender and relationships: A developmental account. The American
Psychologist, 45, 513–520.
Martin, J. M., Cole, D. A., Clausen, A., Logan, J., & Strosher, H. L. (2003). Moderators of the
relation between popularity and depressive symptoms in children: Processing strength
and friendship value. Journal of Abnormal Child Psychology, 31, 471.
Masten, A. S., & Coatsworth, J. D. (1995). Competence, resilience, & psychopathology. In D.
Cicchetti & D. Cohen (Eds.), Developmental psychopathology: Vol 2. Risk, disorder, and
adaptation (pp. 715- 752). New York: Wiley.
Masten, A. S., & Coatsworth, J. D. (1998). The development of competence in favorable and
unfavorable environments: Lessons from successful children. American Psychologist, 53,
205–220.
Masten, A. S., & Curtis, W. J. (2000). Integrating competence and psychopathology: Pathways
toward a comprehensive science of adaptation in development. Development and
Psychopathology, 12, 529–550.
Mead. G. H. (1934). Mind, self, and society. Chicago: University of Chicago Press.
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 33
Nelson, S. E. & Dishion, T. J. (2004). From boys to men: Predicting adult adaptation from
middle childhood sociometric status. Development and Psychopathology, 16, 441-459.
Nolen-Hoeksema, S. (1990). Sex differences in depression. Stanford, CA: Stanford University
Press.
Nolen-Hoeksema, S., & Girgus, J. S. (1994). The emergence of gender differences in depression
during adolescence. Psychological Bulletin, 115, 424–443.
Oldenburg, C. M., & Kerns, K. A. (1997). Associations between peer relationships and
depressive symptoms: Testing moderator effects of gender and age. Journal of Early
Adolescence, 17, 319–337.
Oldenhinkel, A. J., Rosmalen, J. G. M., Veenstra, R., Dijkstra, J. K., & Ormel, J. (2007).
Being admired or being liked: Classroom social status and depressive problems in early
adolescent girls and boys. Journal of Abnormal Chlid Psychology, 35, 417-427.
Ogbu, J. U. (2004). Collective identity and the burden of “acting White” in Black history,
community, and education. The Urban Review, 36, 1–35.
Oyserman, D., Coon, H. & Kemmelmeier, M. (2002). Rethinking individualism and
collectivism: Evaluation of theoretical assumptions and meta-analyses. Psychological
Bulletin, 128, 3–72.
Paquette, J. A. & Underwood, M. K. (1999). Gender differences in young adolescents'
experiences of peer victimization: Social and physical aggression. Merrill-Palmer
Quarterly, 45, 242-266.
Phinney, J. (1992). The Multigroup Ethnic Identity Measure: A new scale for use with diverse
groups. Journal of Adolescent Research, 7, 156-176.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 34
Prinstein M. J., & Aikins, J. W. (2004). Cognitive moderators of the longitudinal association
between peer rejection and adolescent depressive symptoms. Journal of Abnormal Child
Psychology, 32, 147–158.
Reinherz, H. Z., Frost, A. K., & Pakiz, B. (1991). Changing faces: Correlates of depressive
symptoms in late adolescence. Family & Community Health: The Journal of Health
Promotion & Maintenance, 14(3), 52-63.
Resnick, M. D., Bearman, P. S., Blum, R. W., Bauman, K. E., Harris, K. M., Jones, J., Tabor, J.
Beuhring, T., Sieving, R. E., Shew, M., Ireland, M., Bearinger, L. H., Udry, J. R., (1997).
Protecting Adolescents from Harm. Findings from the National Longitudinal Study on
Adolescent Health. Journal of the American Medical Association, 278 (10), 823–32.
Ringwalt, C., Vincus, A. A., Hanley, S., Ennett, S. T., Bowling, J. M., & Rohrbach, L. A. (2009).
The prevalence of evidence-based drug use prevention curricula in U.S. middle schools in
2005. Prevention Science, 10, 33–40.
Roeser, R. W., Eccles, J. S., & Sameroff, A. J. (1998). Academic and Emotional Functioning in
Early Adolescence: Longitudinal Relations, Patterns, and Prediction by Experience in
Middle School. Development and Psychopathology, 10(2), 321–52.
Rose, A. J., & Asher, S. R. (1999). Children’s goals and strategies in response to conflicts within
a friendship. Developmental Psychology, 35, 69–79.
Rose, A. J., & Asher, S. R. (2004). Children’s strategies and goals in response to help-giving and
help-seeking tasks within a friendship. Child Development, 75, 749–763.
Rumberger, R. W. (1987). High school dropouts: A review of issues and evidence. Review of
Educational Research, 57, 101-121.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 35
Rutter, M. (1991). Age changes in depressive disorders: Some developmental considerations. In
J. Garber & K. Dodge (Eds.), The development of emotional regulation and dysregulation
(pp. 273–300). Cambridge, England: Cambridge University Press.
Sandstrom, M. J., & Cillessen, A. H. N. (2006). Likeable versus popular: Distinct implications
for adolescent adjustment. International Journal of Behavioral Development, 30, 305–
314.
Schwartz, D., Gorman, A. H., Duong, M. T., & Nakamoto, J. (2008). Peer relationships and
academic achievement as interacting predictors of depressive symptoms during middle
childhood. Journal of Abnormal Psychology, 117, 289–299.
Schwartz, D., Gorman, A. H., Nakamoto, J., & McKay, T. (2006). Popularity, social acceptance,
and aggression in adolescent peer groups: Links with academic performance and school
attendance. Developmental Psychology, 42, 1116–1127.
Shippee, N. D., & Owens, T. J. (2011). GPA, depression, and drinking: A longitudinal
comparison of high school boys and girls. Sociological Perspectives, 54(3), 351-376.
Simmons, R. G., & Blythe, D. A. (1987). Moving into adolescence. Hawthorne, NY: De Gruyter.
Solomon, A., Ruscio, J., Seeley, J. R., & Lewinsohn, P. M. (2006). A taxometric investigation of
unipolar depression in a large community sample. Psychological Medicine, 36, 973–985.
Steinberg, L., Dornbusch, S. M., & Brown, B. B. (1992). Ethnic differences in adolescent
achievement: An ecological perspective. American Psychologist, 47, 723–729.
Strough, J., & Berg, C. A. (2000). Goals as mediator of gender differences in high-affiliation
dyadic conversations. Developmental Psychology, 36, 117–125.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 36
Sund, A. M., Larsson, B., & Wichstrom, L. (2003). Psychosocial correlates of depressive
symptoms among 12– 14-year-old Norwegian adolescents. Journal of Child Psychology
and Psychiatry, 44, 588–597.
Sweeting, H., Young, R., West, P., & Der, G. (2006). Peer victimization and depression in early-
mid adolescence: A longitudinal study. British Journal of Educational Psychology, 76(3),
577-594.
Taylor, A. Z., & Graham, S. (2007). An examination of the relationship between achievement
values and perceptions of barriers among low-SES African American and Latino
students. Journal of Educational Psychology, 99, 52–64.
Tran, N., & Birman, D. (2010). Questioning the model minority: Studies of Asian American
academic performance. Asian American Journal of Psychology, 1(2), 106-118.
Triandis, H. C. (1995). Individualism and collectivism. Boulder, CO: Westview Press.
Twenge, J. M., & Nolen-Hoeksema, S. (2002). Age, gender, race, socioeconomic status, and
birth cohort differences on the Children’s Depression Inventory: A meta-analysis.
Journal of Abnormal Psychology, 111, 578-588.
U.S. Census Bureau (2010). 2010 Census of population: General population characteristics of
the United States. Bureau of the Census: Washington, DC.
Wentzel, K. R., & Caldwell, K. (1997). Friendships, peer acceptance, and group membership:
Relations to academic achievement in middle school. Child Development, 68, 1198–
1209.
Wierzbicki, M., & McCabe, M. (1988). Social skills subsequent depressive symptomatology in
children. Journal of Clinical Child Psychology, 77, 203-208.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 37
Note.
a
Rejection, unpopularity, relational victimization, and overt victimization are standardized
values.
b
The possible values for science, math, social science, and reading/language arts grades
range from 0 to 4.
c
Reading/language arts grade = the average of students’ reading and language
arts grades.
d
The possible values for negative mood, interpersonal problems, ineffectiveness,
anhedonia, and self-esteem range from 0 to 2.
Table 1
Means and Standard Deviations for all variables
Time 1 Time 2
Variable M SD M SD
1. Rejection
a
-0.03 0.95 0.00 0.95
2. Unpopularity
a
0.03 0.99 0.03 0.99
3. Relational victimization
a
-0.02 0.96 -0.03 0.96
4. Overt victimization
a
0.00 0.99 -0.04 0.98
5. Science grade
b
3.02 1.13 3.07 0.97
6. Math grade
b
2.90 1.21 2.84 1.28
7. Social science grade
b
3.16 1.03 3.30 0.97
8. Reading/language arts grade
bc
3.02 0.98 3.31 0.98
9. Negative mood
d
0.36 0.33 0.37 0.38
10. Interpersonal problems
d
0.26 0.32 0.27 0.34
11. Ineffectiveness
d
0.34 0.36 0.31 0.36
12. Anhedonia
d
0.36 0.32 0.33 0.31
13. Self-esteem
d
0.35 0.40 0.33 0.37
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 38
Table 2
Correlation Between All Variables, Gender, and Ethnicity
Variable 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.
1 Reject .48*** .12* .45*** .29*** -.09 -.10 -.08 -.14** .07 .20*** .17** .03 .09 .15** .06
2 Unpop .24*** .42*** .34*** .15** .08 .12* .11* .10* .00 -.01 .01 .04 .05 .07 .02
3 RVic
a
.48*** .40*** .35*** .41*** .00 .04 .03 -.06 .10 .08 .14** .11* .13* .06 .11*
4 OVic

.34*** .26*** .52*** .21*** -.07 .00 -.09 -.12* .09 .15** .12* .08 .06 .22*** .04
5 Sci -.19*** .08 -.11* -.11* .49*** .43*** .49*** .53*** .02 -.25*** -.21*** -.03 -.01 -.15** .05
6 Math -.26*** .02 -.13** -.19*** .52*** .41*** .42*** .32*** -.02 -.20*** -.17** .00 -.02 -.12* -.09
7 SocSci -.21*** .02 -.09 -.08 .55*** .56*** .37*** .50*** -.01 -.28*** -.20*** .02 -.01 -.15** .07
8 Eng -.18*** .06 .08 -.14** .58*** .58*** .65** .49*** .04 -.29*** -.22*** -.01 .03 -.14** .05
9 Mood .02 .13* .11* .08 -.01 -.02 .03 .02 .40*** .42*** .59*** .63*** .61*** -.14** -.04
10 InterPer .12* -.05 .05 .11* -.24*** -.19*** -.21*** -.22*** .37*** .44*** .57*** .42*** .39*** .11* -.01
11 Ineffec .08 .11* .14** .15** -.20*** -.24 -.25*** -.26*** .54*** .43*** .34*** .52*** .64*** .01 .02
12 Anhed .07 .23*** .12* .13** -.07 -.07 -.04 -.05 .65*** .39*** .57*** .48*** .56*** -.08 -.04
13 Neg SE .04 .14** .17** .08 .01 .01 -.02 -.00 .53*** .25*** .64*** .55*** .44*** -.02 .04
14 Gender .12* .02 .07 .34 -.14** -.03 -.09 -.16** -.07 .06 .02 .00 -.08 -- -.03
15 Ethnic .03 -.01 .06 .03 .10* .14** .15** .13* .06 .01 -.11* -.02 .01 -.03 --
Note. Correlations at Time 1 are shown below the diagonal and correlations at Time 2 are shown above the diagonal. Stability coefficients are shown on the diagonal. Overt victim
= overt victimization; relat victim = relational victimization; lang/reading = the average of students’ grades in language arts and reading; n. self-esteem = negative self-esteem.
Gender is coded as a dichotomous variable (Male = 0, Female = 1). Ethnicity is coded as a dichotomous variable (Mexican-American = 1, Vietnamese-American = 2). *p<.05.
**p<.01. ***p<.001
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 39

Table 3
Summary of Model Fit Indices
Model Figure χ
2
χ
2
/df df RMSEA CFI
1 1 167.23*** 2.69 62 .065 .927
2 164.45*** 2.65 62 .064 .930
3 2 487.26*** 1.79 272 .045 .941
Note. Model 1 = correlational model with all subjects at T1. Model 2 = correlational
model with all subjects at T2. Model 3 = longitudinal model with all subjects T1 and T2.
RMSEA = root-mean-square error of approximation; CFI = comparative fit index.
*p < .05. ** p < .01. *** p < .001.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 40
Note. RMSEA = root-mean-square error of approximation; CFI = comparative fit index.
a
T1-T2 Comparison = the longitudinal associations between T1 negative peer
relationships and academic functioning and T2 depressive symptoms controlling for T1
depressive symptoms and T2 negative peer relationships and academic functioning.
*p < .05. ** p < .01. *** p < .001.

Table 4
Comparing boys and girls at T1, T2, and across T1-T2
T1 Comparison χ
2
df χ
2
/df RMSEA CFI Δχ
2

Unrestricted model 213.19* 124 1.72 .043 .931
Equivalence of factor load 236.94* 134 1.77 .044 .921 23.75*
Equivalence of covariance 343.68* 137 1.78 .044 .918 6.74

T2 Comparison χ
2
df χ
2
/df RMSEA CFI Δχ
2

Unrestricted model 206.26* 124 1.66 .041 .943
Equivalence of factor load 223.50* 134 1.67 .041 .938 17.24
Equivalence of covariance 233.50* 137 1.70 .042 .933 10.00*

T1-T2 Comparison
a
χ
2
df χ
2
/df RMSEA CFI Δχ
2

Unrestricted model 928.60* 584 1.59 .038 .905
Equivalence of factor load 965.18* 604 1.60 .039 .900 36.58*
Equivalence of covariance 977.32* 609 1.61 .039 .898 12.14*
Predictive equivalence 1006.29* 618 1.3 .040 .892 28.97***
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 41
Table 5
Correlations between negative peer relationships, academic functioning, and depressive
symptoms within genders at T1 and T2
Boys Girls
Peer Acad Dep Peer Acad Dep
Peer Peer
T1 Acad .07 Acad -.27**
Dep .12 -.02 Dep .28** -.10

Peer Acad Dep Peer Acad Dep
Peer Peer
T2 Acad .14 Acad -.23*
Dep .08 -.15 Dep .28** -.07
Note. peer = negative peer relationships; acad = academic functioning; dep = depressive
symptoms. *p < .05. ** p < .01. *** p < .001.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 42

Note. RMSEA = root-mean-square error of approximation; CFI = comparative fit index.
a
T1-T2 Comparison = the longitudinal associations between T1 negative peer
relationships and academic functioning and T2 depressive symptoms controlling for T1
depressive symptoms and T2 negative peer relationships and academic functioning.
*p < .05. ** p < .01. *** p < .001.
Table 6
Comparing Mexican- and Vietnamese-American participants at T1, T2, and across T1-T2
Model Y1 χ
2
df χ
2
/df RMSEA CFI Δχ
2

Unrestricted model 178.18 124 1.44 .048 .940
Equivalence of factor load 191.57 134 1.43 .047 .936 13.39
Equivalence of covariance 192.62 137 1.41 .046 .938 1.05

Model Y2 χ
2
df χ
2
/df RMSEA CFI Δχ
2

Unrestricted model 197.34 124 1.59 .048 .927
Equivalence of factor load 211.881 134 1.58 .047 .922 14.54
Equivalence of covariance 212.166 137 1.55 .046 .925 .29

Model Y1-Y2 χ
2
df χ
2
/df RMSEA CFI Δχ
2

Unrestricted model 1236.74 687 1.97 .044 .89
Equivalence of factor load 1362.75 709 1.94 .043 .89 126.01*
Equivalence of covariance 1369.47 714 1.93 .039 .89 6.72
Predictive equivalence 1379.39 721 1.96 .040 .88 9.92
PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 43

Table 7
Correlations between negative peer relationships, academic functioning, and depressive
symptoms within ethnicities at T1 and T2
Mexican-Americans Vietnamese-Americans
Peer Acad Dep Peer Acad Dep
Peer Peer
T1 Acad -.19 Acad -.25**
Dep .26* -.17 Dep .15 -.29**

Peer Acad Dep Peer Acad Dep
Peer Peer
T2 Acad -.08 Acad -.13
Dep .09 -.18 Dep .09 -.25**
Note. peer = negative peer relationships; acad = academic functioning; dep = depressive
symptoms. *p < .05. ** p < .01. *** p < .001.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 44

Figure 1. Measurement model (Model 1) examining the association between Time 1 (T1)
peer relations, academic performance, and depressive symptoms. Factor loadings and
path coefficients are standardized. See Table 1 for details on model fit. e = error.
*p < .05.

PREDICTING ADOLESCENT DEPRESSIVE SYMPTOMS 45

Figure 2. Measurement model (Model 3) examining the association between Time 1 (T1)
and Time 2 (T2) peer relations, academic performance, and depressive symptoms. Factor
loadings and path coefficients are standardized. See Table 1 for details on model fit. e =
error. *p < .05.

Abstract (if available)

Abstract This short-term longitudinal investigation examines associations between academic achievement, social functioning, and depressive symptoms among a diverse group of early adolescents. Participants were 400 middle school students (186 Vietnamese American

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

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

PDF

Using observed peer discussions to understand adolescent depressive symptoms and interpersonal interactions

PDF

Depressive outcomes following peer victimization during adolescence: the moderating role of friends’ attributes

PDF

Popularity as a predictor of friendship affiliation in adolescence

PDF

Differential associations between same- and cross-ethnicity negative peer attitudes and adjustment outcomes among Vietnamese and Mexican American adolescents

PDF

Community violence exposure and children's subsequent rejection within the school peer group: the mediating roles of emotion dysregulation and depressive symptoms

PDF

Actual and perceived social reinforcements of weight-related cognitions and behaviors in adolescent peer groups

PDF

Academic achievement, same- and cross-ethnic positive peer regard among Asian American and Latinx adolescents

PDF

The cultural expression of depression in Asian Americans and European Americans

PDF

Social status, perceived social reputations, and perceived dyadic relationships in early adolescence

PDF

Social network influences on depressive symptoms among Chinese adolescents

PDF

Offline social functioning and online communication: how social competence translates to an online context

PDF

Social attributes of adolescents’ problem-talk partners predict changes in depression

PDF

Examining the associations of respiratory problems with psychological functioning and the moderating role of engagement in pleasurable activities during late adolescence

PDF

Not just talk: observed communication in adolescent friendship and its implications for health risk behavior

PDF

Friendship as a protective factor in adolescence

PDF

Examining the longitudinal relationships between community violence exposure and aggressive behavior among a sample of maltreated and non-maltreated adolescents

PDF

Family aggression, prosocial friends, and the risk of dating and friend victimization in late adolescence

PDF

Investigating discrimination and depression within a couple context

PDF

The relationship between dating status and academic and social functioning among Latinx and Asian-American middle adolescents

Asset Metadata

Creator Cram, Alexandra L. (author)

Core Title Negative peer relationships and academic failures as predictors of depressive symptoms in early adolescence

School College of Letters, Arts and Sciences

Degree Master of Arts

Degree Program Psychology

Publication Date 12/03/2014

Defense Date 09/12/2012

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

Tag depressive symptoms,early adolescence,OAI-PMH Harvest,peer relationships,school achievement

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Schwartz, David (committee chair), Graham, Jesse C. (committee member), Margolin, Gayla (committee member)

Creator Email acram@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-123459

Unique identifier UC11291595

Identifier usctheses-c3-123459 (legacy record id)

Legacy Identifier etd-CramAlexan-1378.pdf

Dmrecord 123459

Document Type Dissertation

Rights Cram, Alexandra L.

Type texts

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

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA