Research on Child and Adolescent Psychopathology
https://doi.org/10.1007/s10802-022-00906-4
Prospectively Predicting Adult Depressive Symptoms from Adolescent
Peer Dysfunction: a Sibling Comparison Study
Carter J. Funkhouser1,2 · Sameer A. Ashaie3 · Marc J. Gameroff4,5 · Ardesheer Talati4,5 · Jonathan Posner4,5 ·
Myrna M. Weissman4,5 · Stewart A. Shankman1
Accepted: 10 February 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022
Abstract
Previous studies have shown that peer dysfunction in adolescence predicts depression in adulthood, even when controlling
for certain individual- and/or family-level characteristics. However, these studies have not controlled for numerous potential familial confounders, precluding causal inferences. The present study therefore used a sibling comparison design (i.e.,
comparing siblings within families) to test whether peer dysfunction (e.g., lack of friendships, victimization) in adolescence
continues to predict depression in adulthood after accounting for unmeasured familial confounds and individual characteristics in adolescence. Participants’ (N = 85) dysfunction with peers was assessed in adolescence (Mage = 13.21, SD = 3.47)
by self- and parent-report, and adult depressive symptoms were assessed up to five times, up to 38 years later. Multilevel
modeling was used to examine the effect of adolescent peer dysfunction on adult depressive symptoms after adjusting for
familial confounds and/or individual characteristics in adolescence (e.g., baseline depressive symptoms, dysfunctional relations with siblings/parents). Both self-reported (b = 1.28, p < 0.001) and parent-reported (b = 0.56, p = 0.032) adolescent peer
dysfunction were associated with greater depressive symptom severity in adulthood in unadjusted models. Self-reported
(but not parent-reported) adolescent peer dysfunction continued to predict adult depressive symptoms after controlling for
familial confounding and measured covariates such as adolescent depressive symptoms and relations with siblings and
parents (b = 1.06, p = 0.035). Although confidence intervals were wide and the potentially confounding effects of numerous
individual-level factors were not ruled out, these findings provide preliminary evidence that perceived peer dysfunction in
adolescence may be an unconfounded risk factor for depressive symptoms in adulthood.
Keywords Peer relationships · Social factors · Relationships · Risk factors · Depression
* Carter J. Funkhouser
carterfunkhouser@gmail.com
1
Department of Psychiatry and Behavioral Sciences,
Northwestern University, 680 N. Lake Shore Drive, Chicago,
IL 60611, USA
2
Department of Psychology, University of Illinois at Chicago,
1007 W. Harrison Street, Chicago, IL 60607, USA
3
Center for Aphasia Research and Treatment, Shirley Ryan
AbilityLab, 355 E. Erie Street, Chicago, IL 60611, USA
4
College of Physicians and Surgeons, Department
of Psychiatry, Columbia University, 1051 Riverside Drive,
New York, NY 10032, USA
5
Division of Translational Epidemiology, New York State
Psychiatric Institute, 1051 Riverside Drive, New York,
NY 10032, USA
Depression is a leading cause of disability (Friedrich, 2017)
and has a peak onset beginning in adolescence (Avenevoli
et al., 2015), a developmental period characterized by change
and increased autonomy. Identifying depression risk factors
in adolescence and mechanisms underlying their association
with depression later in life is therefore critical for reducing depression's public health burden through prevention.
Peer functioning and relationships are particularly important sources of support in adolescence (Larson et al., 1996).
Numerous etiological theories of depression emphasize the
role of peer stressors and lack of peer support in the development or exacerbation of adolescent depression (Cohen &
Wills, 1985; Hammen, 2005; Panzarella et al., 2006), and
peer dysfunction (e.g., peer victimization, lack of friendships, affiliation with deviant peers) is strongly associated
with depression and other psychopathologies in adolescence
(e.g., Roach, 2018). Importantly, several longitudinal studies
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Research on Child and Adolescent Psychopathology
have found that peer dysfunction in adolescence predicted
depression later in adolescence (Michelini et al., 2021;
Reijntjes et al., 2010) and in early and middle adulthood
(Bagwell et al., 2001; Bean et al., 2019; Copeland et al.,
2013; Landstedt et al., 2015; Modin et al., 2011), suggesting
that adolescent peer dysfunction may be a valid prospective indicator of depression risk. Importantly, some other
studies have found support for a symptoms-driven model
(i.e., depressive symptoms-> peer dysfunction; Kochel et al.,
2012; Shapero et al., 2013) and it is plausible that peer dysfunction and depressive symptoms reciprocally reinforce
each other (Rudolph, 2009). If so, this transactional process
may contribute to the maintenance or recurrence of depressive symptoms.
Although the association between adolescent peer dysfunction and adult depression has been consistently observed across
studies, it is important to rule out the possibility that this relationship is due to confounders that cause both adolescent peer
dysfunction and adult depression. Determining whether this
association is confounded (i.e., spurious) is essential for developing preventative interventions based on causal mechanisms
underlying risk and determining which adolescents will benefit from preventative interventions (Cuijpers et al., 2012). For
example, if the association is entirely due to a confounder, a
preventative intervention that successfully targets adolescents’
peer functioning would have no impact on depression risk in
adulthood. Previous studies indicate that statistically controlling for certain individual-level (e.g., sex, baseline depression
severity) and/or family-level (e.g., socioeconomic status) confounders attenuated – but did not fully explain – this relationship (Bean et al., 2019; Bowes et al., 2015; Landstedt et al.,
2015). However, many potential family-level confounders (e.g.,
parental depression, maladaptive home environment, genetic
characteristics; Gjerde et al., 2017; Silberg et al., 2010) have not
been considered in prior studies, precluding stronger “causal”
inferences. For example, maladaptive parental interpersonal
behaviors, cognitions, and affective processes may be passed
from parent to offspring via social learning and subsequently
contribute to peer dysfunction (e.g., Goodman et al., 1993).
Maladaptive parental behaviors (e.g., negative parenting) may
also function as stressors that directly contribute to offspring
depression (Goodman & Gotlib, 1999; Hammen et al., 2004)
and later increases in depressive symptoms across adolescence
(Garber & Cole, 2010).
Although randomized experiments are ideal for eliminating potential confounding effects, quasi-experimental
designs such as the sibling comparison design can rule out
certain confounders in cases when randomization is infeasible. The sibling comparison design compares siblings
from the same family who are discordant on an ‘exposure’ (e.g., peer dysfunction), and can be thought of as a
matched case–control study (Frisell, 2020). Statistically
comparing siblings eliminates the effect of all unmeasured
13
environmental (e.g., race/ethnicity, socioeconomic status,
neighborhood factors, family characteristics) and genetic
confounders shared between siblings (Lahey & D’Onofrio,
2010). Importantly, the sibling comparison design’s strength
of controlling for all familial confounders without measuring them comes with the tradeoff that it is difficult to know
which specific genetic and environmental confounders are
shared between siblings (and thus controlled for) in a particular study. Thus, sibling comparison analyses represent a
useful first step to test – and potentially rule out – a large set
of potential confounders that would be exceedingly difficult
to measure and control for in a sample of unrelated individuals. If a sibling comparison analysis suggests familial confounding, further studies would then be necessary to identify
the specific confounding factors.
Although there is limited research on this topic comparing biologically related individuals, twin studies (which
similarly compare siblings [i.e., twins]) of 6- to 10-yearolds suggest that peer difficulties and bullying victimization
in childhood are primarily attributable to genetic characteristics (Ball et al., 2008; Boivin et al., 2013; Brendgen
et al., 2017; Morneau-Vaillancourt et al., 2019). Additionally, a retrospective study of female twins reported that the
association between peer victimization in adolescence and
depressive episodes in adulthood was 60% “causal” (i.e.,
unexplained by genetic or environmental confounds) and
40% attributable to genetic factors that influence both adolescent peer victimization and adult depression (Kretschmer
et al., 2018). This study did not consider other types of peer
dysfunction, however, and its retrospective assessment of
peer victimization 40 years earlier and focus on females may
have limited the validity and generalizability of these results.
In sum, very few studies have used sibling designs to control
for familial confounding, and those that have (a) focused on
peer victimization without considering other forms of peer
dysfunction, (b) measured peer dysfunction in childhood
rather than adolescence, and/or (c) had notable methodological limitations (e.g., retrospective assessment).
The present study used a prospective design to (1) replicate
the previously observed relationship between peer dysfunction
in adolescence and depressive symptoms in adulthood using a
follow-up of up to 38 years, and (2) test whether this relationship remained after accounting for unmeasured genetic or environmental confounds shared between siblings and/or measured
covariates that vary between siblings. Notably, dysfunctional
relations with parents and siblings during adolescence have
also predicted depression in adulthood (Reinherz et al., 2003;
Waldinger et al., 2007), and thus were included as covariates
to test whether the association between adolescent peer dysfunction and adult depressive symptoms was independent of
these other interpersonal domains. We also conducted supplementary analyses estimating the unique effects of self- versus
parent-reported adolescent peer dysfunction to test specificity.
Research on Child and Adolescent Psychopathology
Methods
Table 1 Sample characteristics
Characteristic
Frequency (%)
or Mean (SD)
Female sex
Age
Baseline (i.e., adolescence)
First follow-up
Second follow-up
Third follow-up
Fourth follow-up
Fifth follow-up
Lifetime history of MDD
MDD onset before baseline
MDD onset after baseline
Grandparental history of MDD
Characteristics Measured in Adolescence
Depressive symptoms
Self-report
Peer dysfunction
Relations with siblings
Relations with parents
Parent-report
Peer dysfunction
Dysfunction in sibling relations
Dysfunction in parent relations
46 (54.1%)
Participants
This study used data from a longitudinal, three-generation
cohort study. The initial sample (G1s) consisted of white,
non-Hispanic, predominantly middle class adults with either
Major Depressive Disorder (MDD) or no history of psychiatric illness or treatment recruited from outpatient psychiatric
clinics or the community in the early 1980s. G1s, their children (G2s), and their grandchildren (G3s) completed numerous waves of assessments over the following decades. The
present study focused on G2s because G1s were not assessed
in adolescence and G3s had not yet reached middle age. G2s
first participated at wave 1 or 2 (approximately 1982–1984),
and later completed assessments of depressive symptoms at
five follow-up waves in adulthood (ending in 2020). There
were 126 G2s with non-missing wave 1 self- or parent-report
peer dysfunction data, and 85 participants available for analysis after excluding those without any depression assessments in adulthood.1 The sample consisted of 15 singletons
and 70 participants with at least one participating biological
sibling (nested within 34 families).
The average age at baseline was 13.21 (SD = 3.47), and
participants were followed up for an average of 30.86 years
(SD = 7.16; range = 17.1–37.8). The five follow-ups in adulthood were spaced approximately five years apart and participants completed an average of 2.62 (SD = 1.43) followups. The average ages at the first and last follow-ups were
30.86 (SD = 3.63) and 49.03 (SD = 4.11), respectively. More
detailed information about the age at each follow-up and
demographic and clinical characteristics are presented in
Table 1. Study procedures were approved by the institutional
review board. Written informed consent was obtained from
adults for themselves and minors, and verbal assent was
obtained from minors.
13.21 (3.47)
30.86 (3.63)
34.97 (4.05)
42.73 (3.87)
46.64 (4.09)
49.03 (4.11)
44 (51.8%)
16 (18.8%)
28 (32.9%)
50 (58.8%)
15.17 (9.28)
1.28 (0.22)
1.37 (0.40)
1.33 (0.33)
1.26 (0.31)
1.22 (0.26)
1.33 (0.38)
MDD Major Depressive Disorder as assessed at each wave using the
Schedule for Affective Disorders and Schizophrenia (Mannuzza et al.,
1986) or equivalent for minors. Depressive symptoms in adolescence
were measured using the Center for Epidemiological Studies Depression Scale for Children
The Social Adjustment Inventory for Children and Adolescents (SAICA; John et al., 1987) is a semi-structured interview delivered separately to parent and youth, and assesses
adolescents’ functioning in many domains. The present
study focused on three subscales measuring interpersonal
functioning with peers, siblings, and parents, respectively.
Each subscale contains items assessing either adaptive
functioning or problems in that interpersonal domain. Items
are rated on a 4-point Likert scale ranging from ‘very true’
to ‘not at all true’ (for items regarding adaptive functioning)
or ‘not a problem’ to ‘severe problem’ (for items regarding
problems). The 16-item peer functioning subscale contains
items assessing various components of adaptive peer functioning or problems with peers. Assessed components of
adaptive peer functioning include acceptance (e.g., “makes
new friends easily”, “has a steady group of friends”), popularity (e.g., “is popular with others”), close friendships
(“has one or two special friends”), and leadership (e.g., “is
a leader”). Assessed problems with peers include victimization (“is teased/bullied by other kids”), bullying perpetration
(“bullies other kids”), shyness (“is shy with other kids”),
difficulty maintaining friendships (e.g., “has trouble keeping
friends”), and deviant peer affiliation (e.g., “hangs out with
other kids who get into trouble”).2
1
2
Measures
Social Adjustment Inventory for Children and Adolescents
Three G2 participants who first participated at wave 2 were
included to maximize power, and their wave 2 data was used as baseline.
One item (“wants to be with girls/boys [opposite sex]”) was
excluded from the peer functioning subscale due to a negative correlation (rs = -.01 and -.08) with the subscale score.
13
Research on Child and Adolescent Psychopathology
Dysfunction in sibling and parent relations was measured
using the 9-item sibling relations and 10-item parent relations subscales, respectively.3 The sibling relations subscale
contains three items assessing positive interactions with siblings (“plays or does things with them”, “is friendly toward/
affectionate with them”, “talks with them”) and six items
assessing problems with siblings such as avoidance (“avoids
contact with siblings”, “is avoided by siblings”), bullying
(“scapegoats/bullies siblings”, “is scapegoated/bullied by
siblings”), and physical aggression (“injures siblings”, “is
injured by siblings”). The parent relations subscale separately assesses positive interactions with one’s mother and
father using three items each (six items total) similar to those
in the sibling relations subscale (“does things with mother/
father”, “is friendly/affectionate toward mother/father”,
“talks with mother/father”). The parent relations subscale
also contains several items assessing problems with parents
(e.g., “has strong negative reaction or refuses to do chores
or honor restrictions”, “damages home or family property”).
Adolescents’ functioning was assessed using both selfand parent-report for all but six participants. These six
participants (five of whom were singletons) were missing
self-reported peer dysfunction data, and thus were excluded
from analyses of self-reported (but not parent-reported)
adolescent peer dysfunction. The parent-report SAICA was
completed by the mother for 90.1% of participants. Internal
consistency was adequate for the peer dysfunction (selfreport α = 0.73; parent-report α = 0.83) and dysfunction in
sibling (self-report α = 0.80; parent-report α = 0.78) and parent (self-report α = 0.75; parent-report α = 0.80) relations
subscales.
Depressive Symptoms
Depressive symptoms in adolescence were included as a
covariate in certain analyses and was measured using the
Center for Epidemiological Studies Depression Scale for
Children (CES-DC; Weissman et al., 1980), a version of
the Center for Epidemiologic Studies Depression Scale
(CES-D; Radloff, 1977) modified for children and adolescents. The internal consistency of the CES-DC was acceptable (α = 0.73). Depressive symptoms in adulthood were
assessed at up to five follow-ups spaced approximately five
years apart, and were measured using the CES-D at the first
follow-up (α = 0.92), the Hamilton Rating Scale for Depression (HRSD; Hamilton, 1960) at the second (α = 0.83) and
3
One parent relations item (“damages home or family property”)
was excluded because 97% of adolescents and 99% of parents scored
this item as ‘not a problem.’.
13
third follow-ups (α = 0.92), and the Patient Health Questionnaire (PHQ-9; Kroenke et al., 2001) at the fourth (α = 0.92)
and fifth (α = 0.81) follow-ups. Participants completed only
one measure of depressive symptoms at each follow-up.
Although the variation in depressive symptom measures
is suboptimal and the inclusion of only one scale at each
follow-up precluded the calculation of contemporaneous
cross-measure correlations, previous studies indicate these
measures are moderately to highly intercorrelated and have
a great deal of content overlap (e.g., Chin et al., 2015; Sun
et al., 2020). The five adult depressive symptom assessments
were z-scored within wave prior to analyses.
Data Analysis
As adult depressive symptoms were assessed up to five times
per person, the data had a three-level structure with adult
depressive symptom assessments (level 1) clustered within
individuals (level 2), who in turn were clustered within
families (level 3). Multilevel modeling was used to estimate
associations between peer dysfunction and adult depressive
symptoms while accounting for the non-independence of
observations. Although several statistical approaches can
estimate within-family effects in sibling data (e.g., fixed
effect analysis), multilevel modeling was used because it
can more easily handle three-level data. This allowed us
to directly model level 1 adult depressive symptom scores,
which is preferable to modeling aggregates across level 1
(e.g., person-level averages of adult depressive symptom
scores) for several reasons. First, aggregating across level 1
would assume zero within-person variability in adult depressive symptoms, whereas modeling level 1 observations in a
multilevel model explicitly models within-person variability
(Clarke, 2008). Second, multilevel modeling accounts for
between-person variability in the amount of missing adult
depressive symptom data by weighting parameter estimates
such that participants with less missing data have stronger
influences on parameter estimates (Snijders & Bosker,
2012), thereby allowing all nonmissing depressive symptom assessments in adulthood to be included in the models.
All models used maximum likelihood estimation assuming
missingness at random and included nested random intercepts at the individual and family levels. The effects of peer
dysfunction and covariates (when included) were modeled
as person-level (level 2) fixed effect predictors of the random
person-level intercept. Random slopes were not included
there were too few siblings per family to reliably identify
estimate both random intercepts and slopes (Singmann &
Kellen, 2019). The effects of self- and parent-reported adolescent peer dysfunction were examined separately in the
primary analyses because the inter-rater correlation was only
moderate, r = 0.51, p <0.001.
Research on Child and Adolescent Psychopathology
The association between peer dysfunction in adolescence and depressive symptoms in adulthood was examined
in four models with increasingly strict statistical and/or
methodological controls. First, we estimated the unadjusted
association between adolescent peer dysfunction and adult
depressive symptoms. Second, potential individual-level
confounds were added as statistical covariates. Sex, age,
and dysfunctional relations with parents or siblings in adolescence were included as individual-level covariates due
to their associations with depression in previous studies
(Avenevoli et al., 2015; Landstedt et al., 2015; Waldinger
et al., 2007). Of note, covarying for adolescent social functioning in non-peer domains (i.e., parents, siblings) tested
whether the association between peer dysfunction and adult
depressive symptoms was independent of dysfunction in
non-peer relationships. We also covaried for depression
symptoms in adolescence to rule out the confounding effect
of depressive symptoms in adolescence. Potential familylevel confounds such as family history of MDD were not
included as statistical covariates because they were methodologically controlled for in subsequent models using sibling comparison. Indeed, the main strength of the sibling
comparison design is its ability to rule out the confounding
effects of all characteristics shared between siblings. Controlling for either select individual-level characteristics or
unmeasured familial characteristics in isolation and then
controlling for both sets of confounders simultaneously
allows the opportunity to quantify the extent to which the
association is confounded by select individual-level characteristics versus family-level characteristics.
Third, we used sibling comparison to test whether the
association was due to familial confounding. The mean of
peer dysfunction scores was first calculated for each family,4 and serves as a proxy for family-level genetic and
environmental factors that are correlated with adolescent
peer dysfunction. We then created a family-centered peer
dysfunction variable representing each sibling’s deviation
(i.e., discordance) from their family’s mean. This familycentered variable reflects the amount of peer dysfunction
relative to the mean peer dysfunction of all adolescents
in the family. For example, if a family's mean was 5 and
a sibling within that family had a score of 9, that sibling's
family-centered score would be 9 minus 5, or 4. These calculations are demonstrated in Table S1 in Online Resource 1.
Finally, the peer dysfunction predictor in the first unadjusted
model was replaced in this model by the family-centered
4
Family-level means of adolescent peer dysfunction were calculated
using all individuals with adolescent peer dysfunction data (even if
they had no adult depression data) to maximize the reliability of these
estimates, and were based on 2.64 (SD = 0.59) and 2.60 (SD = 0.61)
adolescents per family for parent- and self-reported adolescent peer
dysfunction, respectively.
peer dysfunction score. The effect of family-centered peer
dysfunction is the within-family effect, which is a more
stringent test of causality because it controls for all genetic
and environmental confounders shared among siblings
(D’Onofrio et al., 2007). If the association between adolescent peer dysfunction and adult depressive symptoms is
entirely due to confounding factors shared between siblings
(e.g., MDD family history), one would expect all siblings
that share these factors to have similar adult depressive
symptom scores. In this scenario, the association would be
reduced to approximately zero when comparing siblings. In
contrast, if family-level factors have no confounding effect,
one would expect the association to be relatively unchanged
when comparing siblings. Singletons (n = 15) were excluded
from all models involving sibling comparison and when calculating family-centered peer dysfunction scores.
Fourth, we combined the use of sibling comparison and
measured covariates by simultaneously entering the familycentered peer dysfunction score as a predictor (as was done
in the third model) and including the same set of measured
covariates from the second model. This approach controls
for both measured individual-level confounders and unmeasured familial confounds.
Lastly, supplemental analyses tested whether prospective associations were specific to either self-reported or
parent-reported peer dysfunction by re-estimating the four
models described above with both self- and parent-reported
peer dysfunction included as simultaneous predictors. As
in the primary analyses described above, family-centered
peer dysfunction scores were used in the two models using
sibling comparison and raw (i.e., uncentered) peer dysfunction scores were used in the other two models. Analyses
were performed in R using the lme4 (Bates et al., 2015),
lmerTest (Kuznetsova et al., 2017), and simr (Green &
Macleod, 2016) packages.
Statistical Power
Statistical power in sibling comparison studies is related to
the amount of within-family variability (e.g., discordance)
in the exposure (Li et al., 2014). The average within-family
ranges for self-reported (M = 0.25) and parent-reported
(M = 0.31) peer dysfunction scores were equivalent to
0.97 SDs and 1.21 SDs, respectively, indicating sufficient
within-family variation in peer dysfunction (Kim, 2021).
The overall distributions of the family-centered peer dysfunction variables also indicated sufficient within-family
variability for both self-reported (M = -0.01, SD = 0.16,
range = -0.44–0.49) and parent-reported peer dysfunction
(M = 0.00, SD = 0.21, range = -0.67–0.67).
A post-hoc sensitivity analysis was also conducted using
Monte Carlo simulations. We substituted the effect of adolescent peer dysfunction with effect sizes ranging from 0.20
13
Research on Child and Adolescent Psychopathology
Fig. 1 Correlations between individual characteristics in adolescence. All values reflect Pearson correlations, except that correlations
involving sex are point-biserial correlations. Significant correlations
(p <0.05) are shaded. The color of the shading reflects the direction
of the correlation (red = negative, blue = positive) and the degree of
shading represents the strength of the correlation
to 1.20 in increments of 0.10. For each effect size, we simulated each model 500 times and then extracted the proportion
of iterations for which the effect of adolescent peer dysfunction on adult depressive symptoms was statistically significant (i.e., power) at alpha = 0.05. As in all other analyses,
singletons were excluded from sensitivity analyses involving
sibling comparison. The resulting power curves are plotted
in Fig. S1 in Online Resource 1.
non-singletons did not differ on any baseline characteristics
or depression symptom severity in adulthood (ps > 0.588),
supporting the generalizability of results from sibling comparison models to singletons (Lahey & D’Onofrio, 2010).
Lastly, assumptions of multilevel modeling were examined
using statistical tests and visualizations. Breusch-Pagan tests
(Breusch & Pagan, 1979) indicated that residual variances
were homogeneous (p > 0.05 for all models; also see Fig. S3 in
the supplementary materials). Diagnostic plots also indicated
that the assumptions of normality of residuals and linearity
were generally met (see Figs. S4 and S5 in the supplementary
materials).
Results
Preliminary Analyses
Correlations among individual characteristics in adolescence are presented in Fig. 1. Preliminary analyses examined
whether these characteristics differed between (a) individuals
who completed at least one assessment of depressive symptoms in adulthood and individuals who did not (and were
thus excluded from all analyses), or (b) singletons and nonsingletons. Individuals who completed at least one depressive
symptom assessment in adulthood did not differ from individuals who did not (ps > 0.148). Additionally, singletons and
13
Association Between Adolescent Peer Dysfunction
and Adult Depression
Unstandardized coefficients from models testing the association between adolescent peer dysfunction and adult depressive symptoms are presented in Fig. 2 and Tables 2 and 3.
The positive unadjusted association for self-reported adolescent peer dysfunction (b = 1.28, p <0.001) was consistent with findings from unrelated individuals (e.g., Bagwell
et al., 2001; Bean et al., 2019; Landstedt et al., 2015; Modin
Research on Child and Adolescent Psychopathology
Fig. 2 Unstandardized associations between self-reported (left) and parent-reported (right) adolescent peer dysfunction and adult depression.
Error bars represent 95% confidence intervals. * p <0.05 ** p <0.01 *** p <0.001
et al., 2011), and was not attenuated when controlling for sex
and other individual characteristics (i.e., depressive symptoms, age, and dysfunction in relations with siblings and
parents) in adolescence (b = 1.34, p = 0.003). The association remained significant in the sibling comparison model
that controlled for familial confounding (b = 1.15, p = 0.005).
The sibling comparison model that additionally controlled
for measured covariates also indicated a significant (albeit
slightly reduced) association (b = 1.06, p = 0.035).
Analyses of parent-reported adolescent peer dysfunction similarly found a significant unadjusted association
with adult depressive symptoms (b = 0.56, p = 0.032),
although this effect was substantially weaker than the
unadjusted association for self-reported peer dysfunction.
This association was further weakened and no longer significant (bs ≤ 0.41, ps ≥ 0.182) after introducing statistical
(i.e., measured covariates) and/or methodological (i.e.,
sibling comparison) controls.
Results of supplemental analyses examining the unique
effects of self- versus parent-reported adolescent peer
dysfunction are plotted in Fig. S2 in Online Resource
2. Self-reported peer dysfunction significantly predicted
adult depressive symptoms in all four models (bs ≥ 1.28,
ps ≤ 0.013) and its unique association was not attenuated
by the inclusion of statistical covariates and/or use of sibling comparison. In contrast, parent-reported peer dysfunction did not uniquely predict adult depressive symptoms in any of the models (bs ≤ 0.00, ps ≥ 0.199).
Discussion
Preventing depression is a pressing public health issue,
and peer dysfunction in adolescence predicts depression
in adulthood. Determining whether this effect is due to
confounders is a critical requisite to effectively reduce
13
Research on Child and Adolescent Psychopathology
Table 2 Unstandardized
coefficients (SEs) of models
using self-rated adolescent peer
dysfunction to predict adult
depressive symptoms
Model
Predictors
Unadjusted
Covariates a
Sibling
Sibling
Comparison Comparison +
Covariates a
(Intercept)
Adolescent peer dysfunction
(self-reported)
Covariates Measured in Adolescence
Sex [Female]
-1.67***
(0.43)
1.28***
(0.32)
-2.22*
(0.85)
1.34**
(0.43)
-0.07
(0.10)
1.15**
(0.38)
-0.51
(0.55)
1.06*
(0.48)
–
–
Age
–
Baseline depressive symptoms
–
Dysfunction in sibling relations
(self-reported)
Dysfunction in parent relations
(self-reported)
–
0.22
(0.17)
0.00
(0.03)
0.02
(0.01)
0.06
(0.24)
0.02
(0.27)
0.08
(0.17)
-0.01
(0.03)
0.01
(0.01)
0.21
(0.24)
0.03
(0.29)
*
a
–
–
–
p < 0.05;** p < 0.01;*** p < 0.001
Covariates were individual-level characteristics measured in adolescence
depression risk through targeted prevention. This is particularly urgent considering the prevalence of adolescent
peer dysfunction (e.g., one-third of adolescents report
being bullied by peers; Modecki et al., 2014) and dramatic reductions in youth's face-to-face peer contact and
support during the COVID-19 pandemic (Orben et al.,
2020; Rogers et al., 2021), potentially increasing risk
for depression. The present study examined the prospective association between peer dysfunction in adolescence
and depressive symptoms in adulthood, and compared
siblings within families to test whether this association
remained after adjusting for family-level confounders. We
found that both self- and parent-reported adolescent peer
dysfunction predicted adult depressive symptoms up to
38 years later, replicating prior longitudinal studies of
unrelated individuals (Bagwell et al., 2001; Bean et al.,
2019; Copeland et al., 2013; Landstedt et al., 2015; Modin
et al., 2011). Results further indicated that the prospective association between self-reported adolescent peer
dysfunction and adult depressive symptoms was only
slightly attributable to unmeasured genetic and environmental confounders or measured covariates (e.g., baseline depressive symptoms and dysfunction in sibling and
parent relations in adolescence). Sibling comparison is a
strong quasi-experimental design, and these results suggest that self-reported peer dysfunction may be an unconfounded risk factor for depressive symptoms in adulthood.
The effect of parent-reported adolescent peer dysfunction on adult depressive symptoms was attenuated and no
13
–
–
longer significant when controlling for baseline individuallevel covariates or unmeasured familial confounding.
Peer dysfunction and depression in adolescence are interwoven with numerous potentially confounding characteristics within the individual and family (Deater-Deckard, 2001).
This study ruled out the confounding effects of familial characteristics and several important individual-level characteristics (e.g., adolescent depressive symptoms and dysfunction in sibling and parent relations), which extends previous
studies of unrelated individuals (Bagwell et al., 2001; Bean
et al., 2019; Copeland et al., 2013; Landstedt et al., 2015;
Modin et al., 2011) by controlling for a much more comprehensive set of potential confounders and more strongly
testing the potentially causal relationship between adolescent peer dysfunction and adult depressive symptoms. Supplemental analyses including self- and parent-reported peer
dysfunction as simultaneous predictors found that the effect
of self-reported peer dysfunction was largely independent of
parent-reported peer dysfunction, suggesting specificity. This
finding is consistent with evidence that it is the adolescent’s
perception of peer dysfunction – not peer dysfunction as
perceived by parents, teachers, or peers – that increases risk
for depressive symptoms (Epkins & Seegan, 2015; Kistner
et al., 1999). However, the sibling comparison design cannot
demonstrate causality because it does not rule out potential
confounders that differ between siblings (Frisell et al., 2012).
For example, interpersonal theories of depression suggest that
interpersonal skills deficits (e.g., excessive reassurance seeking) or impulse control difficulties contribute to peer rejection
Research on Child and Adolescent Psychopathology
Table 3 Unstandardized
coefficients (SEs) from models
using parent-rated adolescent
peer dysfunction to predict adult
depressive symptoms
Model
Predictors
Unadjusted
Covariates a
Sibling
Comparison
Sibling
Comparison +
Covariates a
(Intercept)
-0.73*
(0.33)
0.56*
(0.25)
-0.64
(0.62)
0.29
(0.36)
-0.08
(0.10)
0.41
(0.30)
-0.49
(0.59)
0.13
(0.39)
–
0.13
(0.19)
-0.04
(0.03)
0.02*
(0.01)
0.18
(0.48)
0.10
(0.28)
–
0.04
(0.18)
-0.03
(0.03)
0.01
(0.01)
0.41
(0.41)
0.07
(0.27)
Adolescent peer dysfunction
(parent-reported)
Covariates Measured in Adolescence
Sex [Female]
Age
–
Baseline depressive symptoms
–
Dysfunction in sibling relations
(parent-reported)
Dysfunction in parent relations
(parent-reported)
–
*
a
–
–
–
–
–
p < 0.05;** p < 0.01;*** p < 0.001
Covariates were individual-level characteristics measured in adolescence
and the onset, maintenance, or exacerbation of depressive
symptoms (Coyne, 1976; Gorka et al., 2013; Humphreys
et al., 2013). Residual genetic confounding is also possible,
as genetic factors that differed between siblings might influence both peer dysfunction and risk for depression. Comparing monozygotic twins can rule out all genetic confounders
and represents a future direction for extending this work.
Additionally, inferences from sibling comparison designs can
be biased if an individual’s adolescent peer dysfunction or
adult depression impacts those of their sibling(s) (Sjölander
et al., 2016). Finally, sibling comparison results can only be
generalized to singletons if siblings do not meaningfully differ from singletons in the population (Lahey & D’Onofrio,
2010). Siblings and singletons did not significantly differ on
a variety of characteristics in the present study, suggesting
this assumption may be satisfied. However, the relatively few
singletons (n = 15) may not be representative of singletons
in the population. In light of these limitations of the sibling
comparison design, triangulation with other designs with different limitations may help to support stronger causal inferences regarding the effect of dysfunction with peers on adult
depression (Lawlor et al., 2016).
Keeping these caveats in mind, these findings support
self-reported adolescent peer dysfunction as a potentially
causal risk factor for depressive symptoms in adulthood.
This inference is consistent with the results of a retrospective twin study of self-reported adolescent peer victimization and depressive episodes in adulthood (Kretschmer
et al., 2018), which found that this association could
only partially be explained by genetic and environmental
confounding. Although several non-causal explanations for
this association cannot be ruled out (as discussed above),
there are several possible mediating pathways underlying this relationship. Cognitive theories of depression
posit that the perception of prolonged peer dysfunction
may decrease self-esteem (e.g., Fenzel, 2000), leading
to the development of negative inferential styles and the
belief that desired interpersonal outcomes are unattainable (Panzarella et al., 2006; Rose & Abramson, 1992). In
turn, negative inferential styles may interact with negative
life events later in adolescence or adulthood to engender
hopelessness, which may cause depression either directly
(Abramson et al., 1989) or through decreased goal-directed
behavior (Davidson, 1998; McFarland et al., 2006).
If causal, these findings have several implications for
clinical practice and prevention. They suggest that preventative interventions could directly reduce depression risk
in adulthood by reducing peer dysfunction in adolescence.
Strong tests of causation such as these are important precursors to the development of interventions based on
causal mechanisms underlying risk (Cuijpers et al., 2012).
Successful reduction of adolescent peer dysfunction may
also prevent the development of maladaptive processes
mediating the relationship between peer dysfunction and
depression (e.g., negative inferential style), obviating the
need to target these mediators for prevention. Results also
have implications for screening and resource allocation in
the context of prevention. Selective or indicated prevention programs offered to adolescents at elevated depression risk are more efficacious than universal programs, and
13
Research on Child and Adolescent Psychopathology
risk status has typically been determined using elevated
depression symptom severity, negative inferential style,
parental mood disorders, or familial conflict (Stice et al.,
2009). Pending replication and extension, these findings
suggest that using peer dysfunction as an important indicator of risk could help to identify high-risk adolescents
who would benefit most from preventative intervention.
It is important to note that peer dysfunction encapsulates
a wide range of dimensions and behaviors (e.g., trouble
making friends, victimization, unpopularity, lack of close
friendships) and the observed associations between adolescent peer dysfunction and adult depressive symptoms could
be specific to certain aspects of peer dysfunction. Different
dimensions of peer dysfunction are differentially associated with interpersonal skills, competencies, and outcomes
(Asher & Weeks, 2018). For example, one study found that
the strength of dyadic friendships (but not broader popularity) in mid-adolescence predicted depressive symptoms in
early adulthood (Narr et al., 2019). The heterogeneity of
the peer dysfunction measure thus prevents more specific
insights and hypotheses regarding both (a) potential mechanistic pathway(s) from adolescent peer dysfunction to adult
depressive symptoms, and (b) preventative interventions
that target specific domains of peer dysfunction. That is,
preventative interventions are unlikely to reduce all dimensions of peer dysfunction equally and identifying more specific intervention targets would inform intervention selection. For these reasons, testing whether these findings are
specific to particular dimensions of peer dysfunction is a
critical direction for future research.
Compared to self-reported adolescent peer dysfunction, parent-reported adolescent peer dysfunction was more weakly associated with adult depressive symptoms across all models. The
association between parent-reported peer dysfunction and adult
depressive symptoms also became nonsignificant when controlling for individual-level covariates, family-level confounders
(e.g., MDD family history), and/or self-reported peer dysfunction. This suggests that the association for parent-reported peer
dysfunction may be due to confounders. However, confidence
intervals were wide and sensitivity analyses indicated that the
nonsignificant effect of parent-reported peer dysfunction when
using methodological and/or statistical controls may have been
a type II error. Thus, the extent to which the effect of parentreported peer dysfunction is due to confounders is unclear.
This study had several noteworthy strengths, including
(a) the use of a quasi-experimental and longitudinal design
that tested prospective associations across a long followup while controlling for a variety of confounders, (b) the
examination of both self- and parent-reported adolescent
peer dysfunction as assessed by semi-structured interview,
and (c) consideration of dysfunction in relations with siblings and parents as potential confounds. There were also
several notable limitations. First, confidence intervals were
13
wide due to the relatively small sample size, particularly
when evaluating the magnitude of attenuation caused by
adding certain controls. Results should therefore be considered preliminary until they are replicated in larger samples.
Second, the sample was entirely white. Recruiting racially
homogeneous samples was unfortunately standard practice
when data collection began in the 1980s, and it is critical
that future studies examine generalizability in other racial/
ethnic groups. Studying generalizability in marginalized
groups is particularly important so that improvements in
knowledge regarding etiology and clinical practice do not
disproportionately apply to or benefit privileged groups.
Third, depressive symptoms in adulthood were assessed
using three different measures that, although moderately to
highly correlated (e.g., Chin et al., 2015; Sun et al., 2020),
are not identical in content (Fried, 2017). Fourth, the inclusion of a disproportionately high number of individuals with
a family history of MDD likely increased statistical power
by increasing variability in adult depression scores, but may
impact generalizability to more population-based samples.
Conclusion
These results suggest that the prospective association
between perceived peer dysfunction in adolescence and
depressive symptoms in adulthood cannot be explained by
a variety of potential confounds, suggesting that the association may be direct. If replicated and extended in larger
samples, these findings provide support for targeting adolescent’s perceptions of peer dysfunction to reduce depressive
symptoms in adulthood.
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s10802-022-00906-4.
Funding This work was supported by National Institute of Mental
Health grants R01MH36197, R01MH119771, and F31MH123042.
Compliance with Ethical Standards
Ethics Approval Study procedures were approved by the New York
State Psychiatric Institute institutional review board.
Informed Consent Written informed consent was obtained from adults
for themselves and minors, and verbal assent was obtained from minors.
Conflict of Interest Dr. Weissman has received royalties from Multihealth Systems related to the Social Adjustment Scale. Dr. Posner has
received grant support or consultancies from Takeda, Aevi Genomic
Medicine, and Innovation Science. There are no other potential conflicts of interest.
Research on Child and Adolescent Psychopathology
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