Self-esteem in Early Adolescence as Predictor of Depressive Symptoms in Late Adolescence and Early Adulthood: The Mediating Role of Motivational and Social Factors
Self-esteem in Early Adolescence as Predictor of Depressive Symptoms in Late Adolescence and Early Adulthood: The Mediating Role of Motivational and Social Factors
M. Masselink 0
● E. Van Roekel 0
● A. J. Oldehinkel 0
0 Department of Developmental Psychology, Tilburg University , Tilburg , The Netherlands
1 M. Masselink
Ample research has shown that low self-esteem increases the risk to develop depressive symptoms during adolescence. However, the mechanism underlying this association remains largely unknown, as well as how long adolescents with low self-esteem remain vulnerable to developing depressive symptoms. Insight into this mechanism may not only result in a better theoretical understanding but also provide directions for possible interventions. To address these gaps in knowledge, we investigated whether self-esteem in early adolescence predicted depressive symptoms in late adolescence and early adulthood. Moreover, we investigated a cascading mediational model, in which we focused on factors that are inherently related to self-esteem and the adolescent developmental period: approach and avoidance motivation and the social factors social contact, social problems, and social support. We used data from four waves of the TRAILS study (N = 2228, 51% girls): early adolescence (mean age 11 years), middle adolescence (mean age 14 years), late adolescence (mean age 16 years), and early adulthood (mean age 22 years). Path-analyses showed that low selfesteem is an enduring vulnerability for developing depressive symptoms. Self-esteem in early adolescence predicted depressive symptoms in late adolescence as well as early adulthood. This association was independently mediated by avoidance motivation and social problems, but not by
Self-esteem ● Depression ● Motivation ● Social problems ● Avoidance ● Social support
1 Interdisciplinary Center Psychopathology and Emotion regulation,
University of Groningen, University Medical Center Groningen,
Groningen, The Netherlands
approach motivation. The effect sizes were relatively small,
indicating that having low self-esteem is a vulnerability
factor, but does not necessarily predispose adolescents to
developing depressive symptoms on their way to adulthood.
Our study contributes to the understanding of the
mechanisms underlying the association between self-esteem
and depressive symptoms, and has identified avoidance
motivation and social problems as possible targets for
The prevalence of depression increases sharply from around
2% in early adolescence to around 18% in early adulthood
(Hankin et al. 1998; Oldehinkel and Ormel 2015)
factors contribute to this surge in the experience of
depressive symptoms during adolescence
Low self-esteem has been suggested to be an important
factor that increases vulnerability to depression
Orth et al. 2016)
. An impressive amount of research has
shown that low self-esteem and depressive symptoms often
co-occur among adolescents
(e.g., Carbonell et al. 1998;
Lee and Hankin 2009; Overholser et al. 1995; Sowislo and
. Longitudinal studies suggest that the direction
of the association between self-esteem and depressive
symptoms is predominantly from self-esteem to depressive
symptoms rather than the other way around (Sowislo and
Orth 2013). The association holds even after controlling for
previous levels of depressive symptoms and Big Five
(Sowislo et al. 2014)
. Low self-esteem
thus seems to be a unique factor that makes adolescents
vulnerable to develop depressive symptoms. The
association between self-esteem and depressive symptoms is
particularly interesting to examine during adolescence, as
self-esteem affects many of the developmental challenges
adolescents have to deal with, such as identity formation
and reshaping social relations
and Morris 2001)
. Exploring the developmental pathway
from self-esteem to depressive symptoms can shed light on
Although previous studies have provided insight into the
likely direction of the association between self-esteem and
depressive symptoms, the underlying mechanism is far from
clear. Insight into this mechanism cannot only increase our
understanding of the developmental pathway of how low
self-esteem may result in depression, it may also foster the
development of interventions. Interventions purely aimed at
bolstering (short term) self-esteem have been shown to be
(Baumeister et al. 2003; Swann et al.
. However, targeting not only low self-esteem, but
also the broader context of factors influenced by self-esteem
as well, may provide leads for more effective interventions.
To elucidate how self-esteem relates to depressive
symptoms, we tested whether early adolescents experiencing low
self-esteem remain vulnerable to develop depressive
symptoms over prolonged periods of time, and if so,
through which mediators.
Self-esteem levels tend to decrease in early adolescence
and increase in later adolescence
(Baldwin and Hoffmann
, but those who have lower levels of self-esteem than
others at one time point are likely to have lower self-esteem
than others at the following time point as well
. This suggests that self-esteem is a
stable and enduring vulnerability. Longitudinal studies have
been highly valuable in identifying the likely direction of
the association between self-esteem and depressive
symptoms (i.e., from self-esteem to depressive symptoms), but to
a much lesser extent in identifying the time frame in which
adolescents with low self-esteem remain vulnerable to
developing depressive symptoms. This is partly due to the
relatively short duration of most studies that cover multiple
time points, with the duration usually ranging between
2 weeks and 2 years
(Sowislo and Orth 2013)
covering longer time periods often only investigated
crosslagged effects with the previous time point
(e.g., Orth et al.
. Exceptions are studies conducted by Trzesniewski
and colleagues (2006), who found that low self-esteem
between ages 11 and 15 years increased the probability of a
Major Depressive Disorder at age 26, and a study by Steiger
and colleagues (2014), showing that adolescents with low
or declining self-esteem between 12 and 16 years were
more likely to show depressive symptoms at age 35. These
two studies suggest that low self-esteem is a stable
vulnerability factor over many years. However, another
longitudinal study over 10 years found that, after controlling for
potential confounders, self-esteem at age 15 did not
meaningfully predict depressive symptoms at age 25
et al. 2008)
. Given the limited and contradicting studies, we
replicated these studies by investigating whether self-esteem
in early adolescence predicted depressive symptoms in late
adolescence and early adulthood.
The pathway from low self-esteem to depressive
symptoms in adolescents is likely to pass through several
(Kuster et al. 2012; Orth et al. 2016)
Identifying those factors facilitates more refined theory
building and may ultimately foster the development of
focused interventions. In the present research, we looked at
two sets of potentially cascading mediators. The first set
concerned the question how self-esteem may influence
approach and avoidance motivation; the second set was
used to explore how self-esteem and approach and
avoidance motivation may influence social contact with peers,
perceived social support from peers, and social problems
(see Fig. 1 for a graphical representation of our proposed
model). In the following, we will describe this process in
more detail, starting with approach and avoidance
Self-esteem has received considerable attention in
developmental research because self-esteem has a
(Harter and Whitesell 2003)
, which may
affect developmental trajectories. Self-esteem thus not only
entails cognitive evaluative aspects of the self, but also
(Baumeister et al. 1989; Heimpel et al.
. Individuals with low self-esteem are characterized by
negative views about the self and an avoidance focus to
protect the self from possible harm, whereas individuals
with high self-esteem are characterized as having an
approach motivation to maintain and further enhance
(Baumeister et al. 1989; Heimpel et al. 2006)
different motivational characterizations for low vs. high
self-esteem are similar to what can be expected from
activation of the Behavioral inhibition System (BIS) and
Behavioral Activation System (BAS) respectively
and White 1994; Gray 1994)
. The BIS is sensitive to signals
of punishment, non-rewards and novelty; and activation of
this system is related to avoidance and inhibition of goal
pursuit. The BAS, on the other hand, is sensitive to reward,
non-punishment and escape from punishment; and
activation of this system is related to goal setting, pursuit and
maintenance. Research findings have indicated that
selfesteem is indeed negatively related to activation of the BIS,
and positively related to activation of the BAS
Rushton 2010; Kuppens and Van Mechelen 2007; Park
. High activation of the BIS and low activation of
BAS have also been proposed to relate to depression
et al. 2002; Shankman and Klein 2003; Gray 1994)
research results are generally consistent with this reasoning
(Trew 2011). High levels of BIS are often conceptualized as
indicators of avoidance motivation and high levels of BAS
as indicators of approach motivation
(Elliot and Thrash
. In the remainder of this article, we will therefore
refer to approach and avoidance motivation. Although
approach and avoidance motivation may be directly related
to depressive symptoms, they may do so indirectly via
social contact, social problems, and perceived social
Many of the developmental challenges that adolescents
face revolve around their position in their social
(Steinberg and Morris 2001)
. These challenges
include changing schools, building new social networks,
changing relations with family members, adopting an
increasingly more adult role over time, and identity
(Forbes and Dahl 2010; Steinberg and Morris 2001)
Peers play a complex role in the lives of adolescents. On the
one hand, peers can be sources of interpersonal stress,
which has been proposed to be one of the leading causes of
depressive symptoms during adolescence (Hankin et al.
2007). On the other hand, adolescents also increasingly rely
on their peers, and peers become the most important source
of social contact and social support
(Levitt et al. 1993;
Steinberg and Morris 2001)
. Not being able to face the
social challenges and to fit in with peers may have adverse
consequences, through various pathways. First, adolescents
who are not able to adopt, maintain and build new social
networks may fail to fulfill their basic human need to belong
(Baumeister and Leary 1995). A lack of social contact has
been related to the experience of depressive symptoms and
(Hopko and Mullane 2008; Lennarz et al.
. Second, adolescents may receive insufficient social
support to deal with the challenges they are faced with. The
importance of social support has been highlighted by
several studies, and a lack of perceived social support has been
shown to relate to depressive symptoms
(Galambos et al.
2004; Lee et al. 2014)
. Third, for successful integration into
new social networks, adolescents have to be socially
adjusted. Various forms of social adjustment problems have
been associated with depressive symptoms among
(Allen et al. 2006)
. Social factors thus seem important
predictors of depressive symptoms, and are likely to remain
so throughout adolescence due to the continuously
changing and developing social demands (e.g., developing
romantic interests, transition from secondary school to
college or university). Compared with adolescents with high
self-esteem, adolescents with low self-esteem report a
smaller social network
(Marshall et al. 2014; but see Stinson
et al. 2008)
, more social problems (Egan and Perry 1998),
and lower levels of social support
(DuBois et al. 2002;
Marshall et al. 2014)
. Below we will describe how these
social factors may be affected by self-esteem and approach
and avoidance motivation.
Because approach and avoidance motivations regulate
goal setting, the motivational system influences how
individuals interact with the world and what activities they
engage in. An individual with avoidance motivation may
have the goal to avoid rejection by peers. One strategy
would be to put extra effort in being liked, but the negative
expectations about the own ability to do so that go along
with low self-esteem may also lead to another strategy:
avoidance of social interaction
individual with approach motivation, on the other hand, may
actively seek out social interactions because it can enhance
the feeling of self-worth. We thus expect approach
motivation to be positively associated with social contact and
avoidance motivation to be negatively associated with
Over time, approach and avoidance responses may take
the form of a reinforcing cycle, and by doing so exert
enduring effects on adolescent development. Reactions to
certain situations may evolve into social schemas that are
used in future situations
(Crick and Dodge 1994)
. When an
individual with low self-esteem is successful in avoiding
harm to the self by restricting involvement in social
interactions, this success is stored in memory and may be
retrieved in a later instance, therefore making it more likely
that the same strategy will be used. Over time, this can lead
to a lack of social skills, as these skills are acquired by trying
and learning from previous occasions
(Crick and Dodge
1994; Rubin et al. 1998)
. Avoidance motivation may thus
lead to less opportunities to develop the social skills required
for successful social interactions. On the opposite,
individuals with high approach motivation may have and take
more opportunities to work on their social skill development
and will therefore experience less social problems.
Strachman and Gable (2006)
showed that, compared to
people with few social avoidance goals, people with more
social avoidance goals tend to have better memory for
negative information, are more likely to interpret ambiguous
social cues as negative, and are more pessimistic in their
evaluations of social actors. On the one hand, individuals
with an avoidance motivation may perceive to receive little
social support due to their negative expectations and
interpretations, on the other hand they may also participate in
less social interactions and therefore receive less social
There may be gender differences in the associations
between self-esteem, the mediators, and depressive
symptoms. Starting from early adolescence, girls report more
(Bennik et al. 2014; Hankin et al.
, lower self-esteem levels (Fichman et al. 1996),
higher levels of avoidance motivation
(Jorm et al. 1998)
higher levels of perceived social support from friends, and
more friends than boys
(Cheng and Chan 2004; Rueger
et al. 2009)
. However, associations between self-esteem and
(Orth et al. 2009; Rieger et al. 2016)
between self-esteem and social support or social contact
(Marshall et al. 2014; Stinson et al. 2008)
do not seem to
differ between boys and girls. Some evidence from research
in adolescent and adult samples suggests gender differences
in the association between perceived social support and
(Kendler et al. 2005; Rueger et al.
. Overall, however, the picture is one of gender
differences on the mean level rather than on the level of
associations. In our model we thus expected to find similar
associations for boys and girls.
Based on the above-described considerations, we tested a
theoretical model (Fig. 1) in which the association between
self-esteem and depressive symptoms is partly mediated by
approach and avoidance motivation and social factors. More
specifically, we tested whether (1) self-esteem in early
adolescence predicted depressive symptoms in late
adolescence and early adulthood; (2) self-esteem predicted
approach and avoidance motivation; (3) approach and
avoidance motivation predicted social contact with peers,
social problems, and social support from peers; and (4) the
social factors served as mediators of the relation between
approach and avoidance motivation and depressive
symptoms. We also investigated whether the associations in our
model were equal across genders.
The adolescent data came from the first (T1, 10–12 years),
second (T2, 12–15 years) and third (T3, 14–18 years) wave
and the adult data from the fifth (T5, 21–24 years) wave of
the Tracking Adolescents’ Individual Lives Survey
(TRAILS). TRAILS is a large prospective cohort study
following young adolescents up into adulthood, conducted
in the northern part of the Netherlands, with assessment
waves 2–3 years apart. The data collection for T1 started in
2001; the data collection for T5 was finished at the end of
2013. Recruitment of participants followed a two stage
process. First, demographic information of all adolescents
born between October 1, 1989 and September 20, 1991 was
obtained from five northern municipalities. Adolescents
could only be included if their school was also willing to
participate. In total, 135 primary schools were approached
to participate in the study, of which 122 agreed to
participate. Second, parents and children of those schools were
approached to participate in the study, of who both had to
give informed consent.
After exclusion of participants who could not participate
because of serious health or language problems, 2935
children and their parents were invited for the first
measurement wave. Eventually 2230 (76.0%; mean age 11.1
years, SD = 0.56; 50.8% girls) adolescents participated in
the T1 wave. The response rates for the follow-up waves
were 96.4% at T2 (N = 2149, 51.0% girls, mean age =
13.65, SD = 0.53), 81.4% at T3 (N = 1816, 52.3% girls,
mean age = 16.27, SD = 0.73), and 79.7% at T5 (N = 1778,
52.7% girls, mean age = 22.29, SD = 0.65). More detailed
sample descriptions can be found elsewhere
et al. 2015)
. A total of 102 cases had too much missing data
across measurement waves to be included in analyses,
resulting in a total sample of 2128. Using T-tests we
examined whether participants who had missing data on
either depressive symptoms at T3 or T5 differed on the
other model variables. We only found differences in mean
levels between the groups for social contact (mean missing =
15.92, SD = 9.25, mean valid = 12.46, SD = 8.00, t
(472.37) = 6.27, p < .001) and BIS (mean missing = 2.45,
SD = 0.53, mean valid = 2.56, SD = 0.52, t (2088) = 4.50,
p < .001).
At T1 and T2, questionnaires were administered to the
participants in their school class under supervision of one or
more TRAILS assistants. T3 questionnaires were filled in at
school or at home. T5 questionnaires were filled in at home,
online or on paper. Descriptive statistics and reliabilities of
the measures are reported in Table 1, and zero order
correlations in Table 2.
Self-esteem was assessed at T1 with an adjusted version of
the 36-items Self-Perception Profile for Children (SPPC)
. This measure has been validated for use in a
sample of Dutch school children
(Muris et al. 2003)
used the 6-item scale to assess global self-esteem. Instead of
the original format
in which respondents had
to decide to which of two descriptions they were most alike,
we used a format akin to the one developed by
. In this format, single statements about “some kids”
(e.g., “Some kids are satisfied with themselves”) were listed,
to which adolescents answered on a 4-point scale ranging
from “I do not resemble those children at all” to “I precisely
resemble those children”.
Approach and avoidance motivation
Approach and avoidance motivation were measured with
the 20-item Behavioral Inhibition Scale (BIS) and
Behavioral Activation Scale
(BAS; Carver and White 1994)
This measure was originally developed for adults, but has
been shown to be suitable for use in an adolescent
population as well
(Cooper et al. 2007)
. Answers were given on a
4-point scale ranging from “very not true” to “very true”. An
example BIS item is “I worry about making mistakes”. The
BAS measure consists of three subscales (reward
responsiveness, drive and fun seeking), which can be combined
into one BAS-scale
(Jorm et al. 1998)
. An example of a
BAS item is “I go out of my way to get things I want”.
Depressive symptoms were assessed at T1 and T3 with 13
items of the DSM-IV based Affective Problems scale of the
Youth Self-Report (YSR) questionnaire and at T5 with 14
items of the age-adjusted DSM-IV based Depressive
Problems scale of the Adult Self-Report (ASR) questionnaire
(Achenbach et al. 2003; Achenbach and Rescorla 2001)
Scores of the Affective Problems scale of the YSR have
been shown to be strongly related to actual depression
diagnosis in a Dutch sample of children, supporting its
validity (Ferdinand 2008). All questions of the YSR and
ASR were answered on a 3-point scale ranging from “not at
all” to “clearly/often”, and concerned the past 6 months. An
example item of the YSR/ASR is “I am unhappy, sad, or
To mitigate shared method variance and bias in reporting,
social problems were assessed at T3 by one of the parents.
We used the 11-item social problems scale of the Child
(CBCL; Achenbach et al. 2003;
Achenbach and Rescorla 2001)
. Response options were
similar to the depressive symptoms measure. An example
item is “Doesn’t get along with other kids”.
Social contact with peers was measured at T3 with items
designed by TRAILS about how many hours per week
adolescents spent with friends at their home, at the homes of
their friends, with their friends outdoors, and going out
during the week and weekend. Scores on these items were
summed to form the social contact variable.
Perceived social support from peers was measured at T3 as
part of the Event History Calendar (EHC), a method to
retrospectively obtain data about life events and activities,
for the TRAILS study developed into a semi-structured
interview of around 45 minutes. Responses on a EHC have
been found to correlate highly with questionnaire responses,
and proposed to be of superior quality
(Belli et al. 2001)
During this interview, participants were asked to indicate on
a 5-point scale from “never” to “always”, for each of a
maximum of seven friends, “Does [name friend] help you
when you are having a hard time”. The social support score
used in the analyses reflects the highest indicated social
support score received from one or more friends (e.g., when
someone received a score of 3 and a score of 5, we used the
latter). We used the highest received score because
adolescents may rely on social support from only some of their
friends, not necessarily all of them. As long as sufficient
support is received from some friends, support from other
friends may be irrelevant.
All associations between self-esteem and depressive
symptoms were investigated using the program Mplus 7.4
Muthén and Muthén 1998
–2015). Missing data were
handled using a Maximum Likelihood estimator with robust
standard errors to account for non-normality of the variables
We first examined the relation between self-esteem and
depressive symptoms at T3 and T5 without mediators.
Using path analysis, we subsequently expanded the models
by including the mediators, BIS and BAS at T2 and social
factors at T3. We included paths from self-esteem to all
variables in the model to test for both direct and indirect
effects. For similar reasons we included direct paths from
BIS and BAS to depressive symptoms. Path analysis
provides a way to test for direct effects between variables as
well as indirect effects. Depressive symptoms at T1 was
included as control variable by including paths to all other
variables in the model. All effects reported represent
standardized coefficients. Due to the fact that we wanted to test
for both direct and indirect effects, and control for the
influence of depressive symptoms at T1 on all other
variables, we had a saturated model. This means that goodness
of fit indicators could not be used as indicators of model fit.
However, we could test for model fit in multiple group
analyses where we constrained associations to be equal for
boys and girls. Goodness-of-fit indices included the
Chisquare, Comparative Fit Index (CFI), Root Mean Square
Error of Approximation (RMSEA), and the Standardized
Root Mean Square Residual (SRMR). As the significance
level of the Chi-square is highly dependent on the sample
size, model evaluations were based on the CFI, RMSEA
and SRMR. Models with CFI values > .90 were considered
to have acceptable fit and models with a CFI > .95 good fit,
RMSEA and SRMR values < .08 indicated acceptable fit
and <.05 good fit
(Hu and Bentler 1998)
The many paths that had to be estimated in our model
had the inherent risk of making Type 1 errors. To mitigate
this risk, we applied the False Discovery Rate method
(Benajmini and Hochberg 1995)
. This method takes into
account the proportion of significant results of the total
number of tests that are performed; a low proportion of
significant associations results in a stricter correction than a
high proportion of significant results. To calculate the FDR
derived significance threshold, an alpha level (.05) is
chosen, and the p-values of the performed tests are ranked from
low to high. For each ranked test, an FDR threshold is
Fig. 2 Model with standardized regression coefficients indicating
associations between self-esteem and depressive symptoms (T3) with
the mediators approach and avoidance motivation and social factors.
Non-significant direct paths from self-esteem tot the social factors and
associations from the control variable depressive symptoms at T1 are
not depicted. *p < .05, **p < .01, ***p < .001
FDR derived significance threshold ¼ number of tests=ranking
The lowest ranked significant p-value which has a
pvalue below its FDR threshold is used as a cut-off. All
ranked p-values above this cut-off are determined to remain
significant, all ranked p-values below are labeled
Self-esteem T1 and Depressive Symptoms T3
Self-esteem at T1 was significantly related to depressive
symptoms at T3 (β = −.13, p < .001), while controlling for
depressive symptoms at T1 (β = .30, p < .001). The results
of the subsequently tested model are presented in Fig. 2. For
clarity reasons we did not depict the insignificant direct
associations between self-esteem and the social factors, or
associations with the control variable. Self-esteem predicted
avoidance motivation, but not approach motivation.
Avoidance motivation directly predicted depressive
symptoms. As expected, avoidance motivation predicted more
social problems and less social contact. Surprisingly,
avoidance motivation was also related to more social
support. Approach motivation predicted more social contact.
Social problems were related to more depressive symptoms,
and surprisingly, we also found a positive association
between social contact and depressive symptoms. Social
support was not related to depressive symptoms. The only
direct association from self-esteem to the social factors was
with social problems. The direct associations with perceived
social support and social contact were not significant. In
total, 28 correlations and paths over time were tested in this
model. All reported associations remained significant after
applying the FDR correction which resulted in an adjusted
significance threshold of .030.
In a next step, we looked at whether the significant
associations from self-esteem and approach and avoidance
motivation to depressive symptoms also indicated
significant indirect effects. After correcting for the seven tested
indirect effects (adjusted significance threshold remained
.05), all the tested indirect paths were significant, except the
path from self-esteem through avoidance motivation and
social contact. The largest indirect path went from
selfesteem tot social problems to depressive symptoms
(β = −.03). The indirect cascading path from self-esteem
through avoidance motivation and social problems was
β = −.001. The total indirect effect was β = −.05, p < .01
and the total effect of self-esteem on depressive symptoms
was β = −.13, p < .01.
We next tested a model where we included gender in the
model as a grouping variable and constrained all paths to be
equal for boys and girls. This model had excellent fit
(χ2 = (28, N = 2227) = 37.72, p = 0.10, RMSEA = .018,
CFI = .986, SRMR = 0.029). This model showed very
similar coefficients to the model without gender included as
grouping variable, with one exception. For both boys and
girls, it was approach motivation that was associated with
perceived social support (boys β = .04, girls β = .08,
p < .05), not avoidance motivation (boys β = −.02, girls
β = −.03, p = .38). This is an indication that the effect from
avoidance motivation to perceived social support in the
model without gender is an artefact, caused by the so-called
Simpson effect, or reversal paradox
(Kievit et al. 2013)
That is, when two subgroups (i.e., boys and girls) have
different mean scores on a variable, combining the data may
represent distorted and even reversed overall associations
Self-esteem T1 and Depressive Symptoms T5
Self-esteem at T1 was significantly associated with
depressive symptoms at T5 (β = −.08, p < .01) when
controlling for depressive symptoms at T1 (β = .23, p < .001).
We subsequently tested the same mediational model as
before but replaced depressive symptoms at T3 for
depressive symptoms at T5. The results showed that
selfesteem had no direct effect on depressive symptoms at T5.
Social contact at T3 was also not significantly related to
depressive symptoms anymore. Avoidance motivation
(β = .16, p < .001) and social problems (β = .17, p < .001)
remained significantly associated with depressive
symptoms. Applying the FDR correction did not render any of
the reported paths in the model insignificant (28 tests,
adjusted significance threshold 0.025). We subsequently
looked whether the significant associations from self-esteem
and avoidance motivation to depressive symptoms also
indicated significant indirect effects. All these paths were
indeed significant (4 tests, adjusted significance threshold
remained 0.05). The cascading path from self-esteem
through avoidance motivation and social problems was
again β = −.001. The total indirect effect was β = −.04, p
< .01, and the total effect of self-esteem on depressive
symptoms at T5 was β = −.08, p = .01.
In our last model, we entered gender as grouping variable
and constrained associations to be equal for boys and girls,
which resulted in excellent model fit (χ2 = (28, N = 2228)
= 30.20, p = 0.35, RMSEA = .008, CFI = .996, SRMR =
0.027). This model again showed very similar coefficients
to the model without gender included as grouping variable.
Alternate Models Considered
The models presented in this article came about after
receiving valuable feedback from reviewers on previously
tested models. Changes included incorporating associations
between contemporaneous associations and adding direct
effects from self-esteem to the social factors. In addition, we
removed childhood stress, which was included as potential
confounder. There are likely many other possible
confounders, and we had no reason to believe that childhood
stress was particularly important. Therefore, we decided
against including an arbitrarily chosen confounder. We
acknowledge the ever present risk of confounders
underlying certain associations, without pretending that we
adequately dealt with this by including one possible
confounder. Importantly, these changes to the model did not
alter our conclusions.
The models included a perceived social support variable,
which constituted the maximum perceived social support
score from up to seven friends. To check whether this
operationalization affected the results, we reran the models
with the mean perceived social support included in the
model instead of the maximum score. The results were
identical to the model with the maximum social support
The prevalence of depression increases sharply during
(Hankin et al. 1998)
. Identification of possible
vulnerability factors that predict the development of
depressive symptoms is therefore much needed. Many
studies have already shown that self-esteem and depressive
symptoms are related among adolescents, and longitudinal
studies have indicated that the association between
selfesteem and depressive symptoms most likely runs
predominantly from self-esteem to depressive symptoms
(Sowislo and Orth 2013)
. Self-esteem is thus proposed to be
an important vulnerability factor and may be particularly
relevant to study in adolescents, because of the important
role it plays in social development during adolescence
(Steinberg and Morris 2001)
. However, due to the limited
time span of most longitudinal studies, little is known about
the duration in which adolescents with low self-esteem
remain vulnerable to develop depressive symptoms.
Moreover, there is a lack of insight in how low self-esteem may
lead to depressive symptoms, because only few studies
investigated mediators of the association between
selfesteem and depressive symptoms
(cf. Kuster et al. 2012)
Identification of mediators is not only important for
theoretical understanding, it also provides directions for
interventions. To address these limitations, we investigated
whether young adolescents with low self-esteem remained
vulnerable to develop depressive symptoms during late
adolescence and early adulthood. In addition, we
investigated a cascading mediational model in which the
association between self-esteem and depressive symptoms was
hypothesized to be mediated by approach and avoidance
motivation and social factors.
Our study revealed that self-esteem in early adolescence
(mean age 11 years) was directly and indirectly associated
with change in depressive symptoms in late adolescence
(mean age 16 years) and only indirectly to change in
depressive symptoms in early adulthood (mean age 22
years). Our findings concur with two other longitudinal
(Steiger et al. 2014; Trzesniewski et al. 2006)
which negative effects of low self-esteem on depressive
symptoms up to two decades later were found, although our
effects were weaker. This suggests that low self-esteem can
be a stable vulnerability factor that makes adolescents
vulnerable to develop depressive symptoms throughout their
way to adulthood. We controlled for earlier levels of
depressive symptoms, indicating that self-esteem is a
unique predictor of depressive symptoms over time. This
goes against some researchers who state that global
selfesteem is inseparable from depression (Watson et al. 2002).
However, although not unlike several other studies
Orth et al. 2014)
, the total effect of self-esteem on
depressive symptoms was relatively small. This suggests that,
although low self-esteem is a vulnerability to develop
depressive symptoms over time, having low self-esteem in
early adolescence does not necessarily predispose the
individual to develop depressive symptoms during
development into adulthood. Still, the development of depressive
symptoms is likely not predicted by one or two major
factors, but rather by a multitude of factors (Hankin 2006). The
fact that self-esteem is a stable predictor of depressive
symptoms makes it worthwhile to further investigate the
nature of this association.
Our main goal was to examine the mechanism that
makes people with low self-esteem vulnerable to develop
depressive symptoms. We did so by examining whether
approach and avoidance motivation and subsequently social
factors, mediated the association between self-esteem and
depressive symptoms. Consistent with commonly described
characteristics of individuals with low self-esteem
(Baumeister et al. 1989; Sowislo and Orth 2013)
research (Heimpel et al. 2006), early adolescents with low
self-esteem reported more avoidance motivation, suggesting
that they seek to avoid possible harmful experiences in
order to protect the self from further harm. Moreover, our
results support theories of behavioral approach and
(Kasch et al. 2002; Shankman and Klein
2003; Gray 1994)
in that avoidance motivation was directly
and indirectly related to depressive symptoms in late
adolescence and early adulthood. An explanatory process
is that high avoidance motivation associated with low
selfesteem may result not only in desired avoidance of harm,
but also in missing out on possible rewarding instances.
This may negatively skew the balance between experienced
negative and positive events, leading to more depressive
In contrast to the results found for avoidance motivation,
self-esteem was not related to approach motivation. This
was surprising given evidence indicating that high
selfesteem is characterized by sensitivity to rewards and
motivation to attain rewards
(Erdle and Rushton 2010; Kuppens
and Van Mechelen 2007; Park 2010)
. A potential
explanation for these contrasting results could be that approach
motivation was assessed regarding events that form a threat
to self-esteem (e.g., a negative evaluation) in two of the
above-mentioned studies, but not in ours. It is conceivable
that, whereas most people are motivated to attain rewards
under normal circumstances, only people with high
selfesteem are motivated to do so in situations with a
selfthreat. Further research is needed to investigate whether the
relation between self-esteem and approach motivation is
actually moderated by the presence of a self-threat.
Another unexpected result regarding approach
motivation was that it had no effect on depressive symptoms. This
suggests that, in contrast to high avoidance motivation, low
approach motivation does not contribute to the risk to
develop depressive symptoms. Possibly, approach
motivation is specifically related to anhedonia, one of the two core
symptoms of depression
(Bijttebier et al. 2009)
. Only one of
the thirteen items of the depressive symptoms scale used in
this study measured anhedonia, so the measure may not
have been sensitive enough to show a relation with
approach motivation. Although there is theoretical
and Watson 1991)
and empirical support
(Hundt et al. 2007;
Kimbrel et al. 2007)
for this explanation, further research is
needed to explicitly test whether approach and avoidance
motivation relate to different aspects of depression (e.g.,
feeling sad and anhedonia).
In addition to avoidance motivation, social problems
were an important mediator of the association between
selfesteem and depressive symptoms. Self-esteem in early
adolescence was directly, and indirectly via avoidance
motivation, associated with social problems in late
adolescence. It is important to highlight that social problems were
measured by parent report, thus indicating a more or less
objective measure of social problems rather than a possibly
biased perception by the adolescent. The fact that avoidance
motivation predicted social problems is in line with the idea
that social skills have to be learned over time
(Rubin et al.
, and that avoiding social interactions impair this
development. Social problems, in turn, were associated with
depressive symptoms in late adolescence and early
adulthood. Although we found significant indirect effects for the
mediating role of social problems through avoidance
motivation and directly from self-esteem, the effect size of
the effect through avoidance motivation was negligibly
small. Social problems thus seem to function as a direct
mediator between self-esteem and depressive symptoms,
not in a cascading manner through avoidance motivation.
As the social problems measure used involved a lack of
social skills (e.g., “Doesn’t get along with other kids”) as
well as a negative perception of the environment (e.g., “Not
liked by other kids”), there are at least two explanations for
the mediating role of social problems. First, because
individuals with low self-esteem tend to interpret social
interactions more negatively and in a self-depreciatory
(Strachman and Gable 2006)
, they may misjudge
social situations and therefore fail to respond appropriately,
leading to social problems. Feeling unable to cope with the
social environment can be very distressing, especially for
adolescents, thus leading to depressive symptoms. Second,
negative perceptions of the social environment may result in
a self-fulfilling prophecy leading to fewer reported positive
(Downey et al. 1998; Strachman and Gable
. This dearth of positive interactions may cause an
unfulfilled need to belong resulting in depressive feelings.
Regardless of the explanation, our results show the influence
of self-esteem on social problems and stress the importance
of positive and successful social interactions during
adolescence, a time where strong social bonds are formed, and
fitting in is particularly important (Steinberg and Morris
2001). The results thus suggest that interventions may not
only be aimed at increasing self-esteem, but also on reducing
social problems, for example with social skill training.
For the other social factors, expected associations were
not found or in contrast with our expectations. Avoidance
motivation was positively instead of negatively associated
with social support. However, the constrained models for
boys and girls suggested that this is the result of a so-called
(Kievit et al. 2013)
, that is, the effect found
in the whole sample reversed within the subgroups (i.e.,
boys and girls) that made up the sample. In the model with
gender included, the association of avoidance motivation
with perceived social support was in the expected negative
direction but not significant. In this model it was approach
motivation that was positively and significantly associated
with perceived social support. Social support was not
related to depressive symptoms, which contrasts research
showing clear beneficial effects of social support with
regard to experienced psychological distress and depression
(DuBois et al. 2002; Lee et al. 2014)
. That said, Orth et al.
(2014) did not find an effect of social support on depressive
symptoms either. An explanation for our null-finding may
be that the social support measure only concerned perceived
social support from friends, not from other important
sources of social support like family members
et al. 2002; Lee et al. 2014)
. It is possible that, although
peers become the main source of social support during
adolescence, support from family members remains pivotal
for emotional well-being. On the other hand, Orth and
colleagues (2014) did measure social support from multiple
sources and still found no effect on depressive symptoms,
so more research is needed to identify moderating factors
leading to these contrasting findings regarding the role of
Another unexpected finding was that social contact was
only associated with depressive symptoms in late
adolescence, and positively instead of negatively, albeit
weakly. This positive association might reflect a misbalance
between social bonding with peers, and bonding with
Deković and Meeus (1997)
involvement with peers during adolescence could be an indicator of
lack of attention and concern at home, rather than an
indicator of social competence” (p. 173). Adolescents scoring
particularly high on our social contact measures may have
been those who rely almost exclusively on social contact
with peers. Alternatively, a subgroup with high levels of
low quality social contact may have disproportionally
contributed to the overall effect with a positive association
with depressive symptoms, so masking the expected
negative association between social contact and depressive
symptoms in the other part of the sample. This remains
speculation as well because we do not know the quality of
the reported social contact, nor the type of friends.
Concurring with others
(Orth et al. 2009; Rieger et al.
, the excellent model fit of our models in which
associations were constrained to be equal for boys and girls
suggest that there are no meaningful gender differences in
the associations between self-esteem and depressive
symptoms. Thus self-esteem and depressive symptoms
seem to be comparably related in boys and girls.
Our study has some clear strengths in comparison with
prior research. The large sample provided us with enough
power to examine a relatively elaborate model. Our
longitudinal design from early adolescence into early adulthood
enabled us to investigate the prospective relation of
selfesteem on depressive symptoms across an important stage
of development. In addition, it enabled us to conduct
mediation analyses largely prospectively, providing less
biased results than cross-sectional mediation analyses
(Maxwell and Cole 2007; Selig and Preacher 2009)
tested several variables previously identified to be related to
self-esteem and depressive symptoms in one comprehensive
model, and could thus account for influences between those
variables. Finally, unlike the common practice in testing
path-models, we controlled for multiple testing by applying
the False Discovery Rate (FDR) method (Benajmini and
Hochberg 1995), which provides a balance between
decreasing the risks of Type I errors and losing too much
Some limitations have to be mentioned as well. Several
of these limitations relate to the fact that the data were not
collected specifically for this study, and we thus had to
capitalize on what was available. First, self-esteem was only
measured at the first measurement wave which precluded us
from assessing the stability and change of self-esteem over
time. Not only the level of self-esteem
(Sowislo et al. 2014)
but also patterns of change may be important vulnerability
(Kernis et al. 1998; Steiger et al. 2014)
. Due to
the one-time measurement of self-esteem, we were not able
to test effects of depressive symptoms on self-esteem and
how these may have affected the mediators included in our
models. Although less consistently and weaker than
vulnerability effects, the opposite so-called scar effects have
been found in previous research
(Shahar and Davidson
2003; Sowislo and Orth 2013; Steiger et al. 2015)
, so we
cannot rule out that such effects influenced the reported
results. Another consequence of this limitation is that we
were not able to test whether the social factors affected
selfesteem over time. Effects from social factors to self-esteem
are predicted by sociometer theory (Leary 2005).
Sociometer theory conceptualizes self-esteem as an indication of
social bonding. Being rejected by others indicates low
relational value and thus low self-esteem. Several studies
provide support for this view
(Gruenenfelder-Steiger et al.
2016; Srivastava and Beer 2005)
. Effects from self-esteem
to social factors are therefore very likely to be reciprocal.
The same applies to associations between approach and
avoidance motivation and social factors. In reality the
mechanism is thus likely much more complex than we were
able to test. Second, we only included approach and
avoidance motivation and social factors as mediators. Many
more variables are likely to play a role, for example
rumination (Kuster et al. 2012), dampening of positive effect
(Wood et al. 2003)
, and dysfunctional coping strategies
(Lee et al. 2014)
. Furthermore, many other mediators may
influence the relation of the social factors in our model and
depressive symptoms, for example peer acceptance
et al. 2010)
(van Roekel et al. 2016; Vanhalst
et al. 2012)
. Third, we were not able to control for the
mediators on earlier time points, and the social factors were
measured at the same time point as depressive symptoms at
T3, which possibly resulted in spuriously inflated estimates
(Cole and Maxwell 2003)
. This means, for example, that we
do not know whether the association between self-esteem
and avoidance motivation reflects a dynamic association or
a stable association, possibly driven by other factors. The
association between social contact and depressive
symptoms in late adolescence may be an artefact of measuring
both measures at the same time. Although the same applies
to social problems, this association was much more robust,
with an equal association with depressive symptoms at the
later time point. Fourth, the social support and social
contact measures were created for the purpose of the TRAILS
study and are not yet tested for validity. Fifth, the relatively
long time periods between measurement waves of 2–3 years
enabled us to examine effects over long time periods, but
precluded investigation of relations over shorter periods.
It is very well possible that other and or stronger effects
faded away in our design. Sixth, we relied largely on
selfreport data, which has the risk of increased shared method
variance and bias in the responses. That said, highly
subjective concepts as self-esteem and experiencing depressive
symptoms are hard or even impossible to assess objectively,
making self-report the most suitable way of assessment
(Sowislo and Orth 2013)
. Social problems, our measure
with the greatest risk for shared method effects and bias by
mood-state was measured with parent-report. Seventh, our
main model was saturated, meaning that model fit could not
be tested. This means that the predictability of the model is
unknown. However, results from our constrained model
with gender included gave some confidence in our results.
In this constrained model we were able to test for model fit,
and the fit was excellent. The coefficients for boys and girls
were quite similar to what we found in our overall saturated
models, providing confidence in our model estimates.
Lastly, our analyses did not differentiate between-person
effects from within-person effects, which limits the
causal and clinical inferences that can be made from our
analyses. It is possible that associations that are found
between persons are not found within persons, in fact they
may even be opposite
(Hamaker et al. 2015; Keijsers 2016)
Analyses differentiating between-person effects from
(see for example Hamaker et al. 2015;
Ormel et al. 2002)
are required to further explore
association between self-esteem and depressive symptoms.
Nevertheless, our study identified possible important
mediators that could be included in future more sophisticated
In addition to clarifying several aspects of the
mechanism underlying the relation between self-esteem and
depressive symptoms, our results raise important questions
to be addressed in future research, such as whether
selfthreats moderate the relation between and self-esteem and
approach motivation; whether approach motivation is
related to anhedonia instead of negative mood; and arguably
most important whether the effects replicate within-persons.
Moreover, although we have no reason to believe that the
mechanisms we found are only at play among adolescents,
the path via social problems may be especially pronounced
among adolescents, considering that social challenges are
prevalent during adolescence. The path via avoidance
motivation may be less dependent on the developmental
period. It would therefore be interesting to see whether our
model replicates in adult samples.
Our study contributes to the process of understanding the
much researched but little understood association between
self-esteem and depressive symptoms in adolescence.
We extended existing research by showing that this
association is mediated by avoidance motivation and social
problems, but not in a cascading manner. This implies that
we have identified two relatively independent mediators of
the association between self-esteem and depressive
symptoms, a behavioral motivational one and a social one.
Importantly, as social processes are particularly relevant in
(Steinberg and Morris 2001)
findings related to the social path may be specific to this age
group and not apply to other developmental phases. Our
results were reassuring in that, although low self-esteem
may make early adolescents more vulnerable to developing
depressive symptoms in late adolescence and early
adulthood, young adolescents experiencing low self-esteem are
certainly not predisposed to experience depressive
symptoms during development into adulthood. For those with
problematic low self-esteem who do require an intervention,
existing therapies may fit very well with their needs.
Cognitive Behavioral Therapy (CBT) has been shown to be
effective in treating depressive symptoms among
(Asarnow et al. 2001; Crocker et al. 2013)
and it can
be used to target the negative expectations and habituated
avoidance behavior as well as the social problem behavior
(Asarnow et al. 2001). Overall, although reported
associations were small, we have shown that self-esteem may be an
enduring vulnerability to developing depressive symptoms
and we have identified possible mechanisms that make
young adolescents with low self-esteem vulnerable to
developing depressive symptoms later in life.
Funding Research reported in this publication was supported by a
Vici grant (016.001/002) from the Netherlands Organization for
Scientific Research to Albertine J. Oldehinkel. The data used were
collected as part of the TRacking Adolescents’ Individual Lives Survey
(TRAILS). Participating centers of TRAILS include various
departments of the University Medical Center and University of Groningen,
the Erasmus University Medical Center Rotterdam, the University of
Utrecht, the Radboud Medical Center Nijmegen, and the Parnassia
Bavo group, all in the Netherlands. TRAILS has been financially
supported by various grants from the Netherlands Organization for
Scientific Research NWO (Medical Research Council program grant
GB-MW 940-38-011; ZonMW Brainpower grant 100-001-004;
ZonMw Risk Behaviour and Dependence grants 60-60600-97-118;
ZonMw Culture and Health grant 261-98-710; Social Sciences
Council medium-sized investment grants GB-MaGW 480-01-006 and
GB-MaGW 480-07-001; Social Sciences Council project grants
GBMaGW 452-04-314 and GB-MaGW 452-06-004; NWO large-sized
investment grant 175.010.2003.005; NWO Longitudinal Survey and
Panel Funding 481-08-013), the Dutch Ministry of Justice (WODC),
the European Science Foundation (EuroSTRESS project FP-006),
Biobanking and Biomolecular Resources Research Infrastructure
BBMRI-NL (CP 32), the participating universities, and Accare Center
for Child and Adolescent Psychiatry.
Author Contributions M.M. conceived of the research questions,
performed the statistical analysis and drafted the manuscript, E.V.R.
helped to build the tested models and helped to draft the manuscript,
A.O. conceived of the study, participated in the design of the study and
helped to draft the manuscript. All authors read and approved the
Compliance with Ethical Standards
Conflict of Interest The authors declare that they have no
Ethical Approval All procedures performed in studies involving
human participants were in accordance with the ethical standards of
the institutional and/or national research committee and with the 1964
Helsinki declaration and its later amendments or comparable ethical
Informed Consent Informed consent was obtained from all
individual participants included in the study.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://crea
tivecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
Maurits Masselink is a PhD-student at the Interdisciplinary Center
Psychopathology and Emotion Regulation, University Medical Center
Groningen, Netherlands. His research interests include self-concept,
self-esteem, social processes, motivational processes, anhedonia,
depression and questionnaire construction.
Dr. Eeske Van Roekel is assistant professor at the department of
Developmental Psychology, Tilburg University, Netherlands. She
received her PhD on the topic of loneliness in adolescence at the
department of Developmental Psychopathology at Radboud University
Nijmegen, Netherlands. Her research interests include depression and
anhedonia in adolescence, positive affect in daily life, and personalized
interventions based on ecological momentary assessments.
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