Family Functioning and Adolescent Internalizing and Externalizing Problems: Disentangling between-, and Within-Family Associations

Abstract

Adolescence is often a period of onset for internalizing and externalizing problems. At the same time, adolescent maturation and increasing autonomy from parents push for changes in family functioning. Even though theoretically expected links among the changes in family functioning and adolescent internalizing and externalizing problems exist, studies examining this link on the within-family level are lacking. This longitudinal, pre-registered, and open-science study, examined the within-family dynamic longitudinal associations among family functioning, and internalizing and externalizing problems. Greek adolescents (N = 480, Mage = 15.73, 47.9% girls, at Wave 1) completed self-report questionnaires, three times in 12 months. Random-Intercept Cross-Lagged Panel Models (RI-CLPM) were applied; such models explicitly disentangle between-family differences from within-family processes, thereby offering a more stringent examination of within-family hypotheses. Results showed that family functioning was not significantly associated with internalizing or externalizing problems, on the within-family level. Also, alternative standard Cross-Lagged Panel Models (CLPM) were applied; such models have been recently criticized for failing to explicitly disentangle between-family variance from within-family variance, but they have been the standard approach to investigating questions of temporal ordering. Results from these analyses offered evidence that adolescents with higher internalizing and externalizing problems compared to their peers, tended to be those who later experienced worse family functioning, but not vice versa. Implications for theory and practice are discussed.

Full text

Journal of Youth and Adolescence (2020) 49:804–817
https://doi.org/10.1007/s10964-019-01094-z
EMPIRICAL RESEARCH
Family Functioning and Adolescent Internalizing and Externalizing
Problems: Disentangling between-, and Within-Family Associations
Stefanos Mastrotheodoros 1,2 ●Catarina Canário3●Maria Cristina Gugliandolo4●Marina Merkas5●Loes Keijsers6
Received: 9 July 2019 / Accepted: 24 July 2019 / Published online: 5 August 2019
© The Author(s) 2019
Abstract
Adolescence is often a period of onset for internalizing and externalizing problems. At the same time, adolescent maturation
and increasing autonomy from parents push for changes in family functioning. Even though theoretically expected links
among the changes in family functioning and adolescent internalizing and externalizing problems exist, studies examining
this link on the within-family level are lacking. This longitudinal, pre-registered, and open-science study, examined the
within-family dynamic longitudinal associations among family functioning, and internalizing and externalizing problems.
Greek adolescents (N=480, Mage =15.73, 47.9% girls, at Wave 1) completed self-report questionnaires, three times in
12 months. Random-Intercept Cross-Lagged Panel Models (RI-CLPM) were applied; such models explicitly disentangle
between-family differences from within-family processes, thereby offering a more stringent examination of within-family
hypotheses. Results showed that family functioning was not significantly associated with internalizing or externalizing
problems, on the within-family level. Also, alternative standard Cross-Lagged Panel Models (CLPM) were applied; such
models have been recently criticized for failing to explicitly disentangle between-family variance from within-family
variance, but they have been the standard approach to investigating questions of temporal ordering. Results from these
analyses offered evidence that adolescents with higher internalizing and externalizing problems compared to their peers,
tended to be those who later experienced worse family functioning, but not vice versa. Implications for theory and practice
are discussed.
Keywords Adolescence ●Family functioning ●Internalizing ●Externalizing ●Random-intercept cross-lagged panel models ●
Within-family
Introduction
Adolescence is a period of vast changes on multiple levels
(cognitive, emotional, social). Adjusting to these changes
can be challenging for adolescents, who often experience an
increase in internalizing (Graber 2013) and externalizing
problems (Georgiou and Symeou 2018). At the same time,
adolescents’families need to adapt to the adolescent’s
increasing needs for autonomy and independence, some-
thing that may lead to a temporary decrease in positive
family functioning (De Goede et al. 2009). Theoretical
accounts of adolescent development posit that youth
develop in multiple contexts (Bronfenbrenner and Morris
2006), of which families are the most proximal and influ-
ential. Thus, developmental perspectives postulate that
changes in family functioning will trigger changes in ado-
lescent internalizing and externalizing problems. At the
same time, multiple theoretical accounts highlight that this
influence might be bidirectional (Crouter and Booth 2003).
*Stefanos Mastrotheodoros
s.mastrotheodoros@uu.nl
1Research Center Adolescent Development, Utrecht University,
Utrecht, The Netherlands
2Department of Psychology, University of Athens, Athens, Greece
3Faculty of Psychology and Education Science of the University of
Porto, Porto, Portugal
4Department of Human, Social and Health Sciences, University of
Cassino and South Latium, Cassino, Italy
5Department of Psychology, Catholic University of Croatia,
Zagreb, Croatia
6Department Developmental Psychology, TSB, Tilburg University,
Tilburg, The Netherlands
Supplementary information The online version of this article (https://
doi.org/10.1007/s10964-019-01094-z) contains supplementary
material, which is available to authorized users.
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Family systems theories (Cox et al. 2001), such as the
Circumplex Model of Marital and Family Systems (Olson
2000), posit that the family system consists of sub-systems,
which dynamically affect each other. Therefore, based on
family systems perspectives, adolescent adaptation (as seen
in the presence or absence of internalizing and externalizing
problems) may also affect other subsystems that define
family functioning, such as the parent-child relationship, as
well as the family as a whole.
Although there is an increasing number of studies
addressing how adolescent adaptation is reciprocally linked
to parenting (Keijsers et al. 2011), and how parenting
changes during adolescence (Mastrotheodoros et al. 2018),
only a few studies have examined the bidirectional links
between family functioning (at the system level) and ado-
lescent adaptation. Furthermore, even though the dynamic
processes are theoretically postulated on the within-family
level, almost no studies on family functioning have
employed techniques that adequately disentangle the
within-family effects (Keijsers 2016), from the between-
family differences and associations (Hamaker et al. 2015).
The current pre-registered longitudinal study investigated
the direction of the longitudinal effects between family
functioning and adolescent internalizing and externalizing
problems, while taking into account the disaggregation of
the between-person differences from the within-person
effects, using Random Intercept Cross-Lagged Panel
Models.
Family Functioning and Adolescent Internalizing
and Externalizing Problems
Although extant research has found evidence for the link
between adolescent adaptation and parenting, the family
systems approach states that there are qualities of the system
as a whole that predict adolescent adaptation above and
beyond the dyadic relationship qualities. The Circumplex
Model of Marital and Family Systems (Olson 2000)isa
prominent theoretical framework, which emphasizes three
important family system qualities: family flexibility, cohe-
sion, and communication. Flexibility describes the quality
and expression of leadership and organization, roles, and
rules in the family. Cohesion describes the emotional
bonding among family members. Communication describes
the degree to which members openly discuss and express
their views, and needs (Olson 2011). These dimensions
have been extensively used to investigate family function-
ing (e.g., Olson 2011), as seen in different measurement
instruments, and family therapy approaches (Walsh 2003).
Thus, to assess associations between family functioning and
adolescents’internalizing and externalizing problems, it is
important to measure and investigate how the family
functions as a system (e.g., Delsing et al. 2005).
Family relationships transform during adolescence
(Mastrotheodoros et al. 2019a), and this transformation
might be stressful for adolescents and the family system as
a whole. During adolescence, a good fit between the ado-
lescent’s developmental needs (e.g., for autonomy), and the
opportunities offered by the environment (e.g., the family)
are expected to facilitate adolescent adaptation (Gutman
and Eccles 2007). Therefore, it is expected that cohesive,
flexible, and openly communicating families will accom-
modate adolescents’needs without major disruptions.
Conversely, families that are distant, inflexible, and do not
facilitate open communication, may constitute a misfitfor
adolescent development, which is expected to cause an
increase in the stress levels of adolescents (see stage-
environment fit hypothesis, Gutman and Eccles 2007), who
already struggle to transition from childhood to young
adulthood.
Unlike the vast majority of studies on the link of ado-
lescent adaptation with parenting (e.g., Keijsers et al. 2011),
empirical evidence on the association between dimensions
of family functioning and internalizing and externalizing
problems in adolescence is relatively scarce. Family func-
tioning, as well as a positive family climate, have been
negatively linked to adolescents’depressive symptoms over
time (Klasen et al. 2015). Also, family flexibility was found
to be negatively related to adolescents’depressive symp-
toms, internalizing and externalizing problems (Joh et al.
2013), and has been identified as a better predictor than
family cohesion for identifying at-risk behaviors (Tafà and
Baiocco 2009). Family cohesion was found to be negatively
related to adolescents’depressive symptoms, but not related
to anxiety symptoms (White et al. 2014). Furthermore,
family communication was negatively related to inter-
nalizing and externalizing behaviors (Elgar et al. 2013) and
was shown to be effective in reducing conduct problems
(Molleda et al. 2017).
Most likely, such influences are reciprocal in nature,
running not only from the family to the adolescent, but also
vice versa (Crocetti et al. 2016). Thus, adolescents’inter-
nalizing and externalizing problems can also have an effect
on how the family functions as a whole. In fact, empirical
work suggests that family flexibility, cohesion, and com-
munication may decrease in families with a seriously
mentally ill person (Koutra et al. 2014), but how sub-
clinical internalizing and externalizing problems during
adolescence affect family functioning is not yet clarified.
More specifically, studies on the relation between family
functioning and adolescents’psychological outcomes are
mostly cross-sectional in nature (Queen et al. 2013). Even
though few recent studies used longitudinal designs, they
did not investigate the direction of effects (e.g., White et al.
2014). Given the dearth of relevant empirical evidence,
research should address the directionality of the relation
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between family functioning and adolescents’psychological
outcomes using longitudinal, cross-lagged designs.
The theoretical ideas regarding how adolescent adaptation
and family functioning are reciprocally related pertain to
processes within families. Thus, changes in the adolescent and
the family system of the same family are related. However,
hardly any study has been conducted on the within-family
level (Hamaker et al. 2015; Keijsers and van Roekel 2018), in
what regards empirical research of family effects and the
reciprocity therein. Almost all studies on the topic of family
functioning and adolescent internalizing and externalizing
problems have focused on between-family differences or
associations, by comparing families with each other, for
instance with correlational designs (for an exception, see
Kapetanovic et al. 2019). Some recent empirical studies
highlight how both ecological levels, the between-family and
the within-family level, might yield different insights, for
instance regarding negotiations of privacy boundaries with
parents (Dietvorst et al. 2018), or the spillover of interparental
conflict on parenting (Mastrotheodoros et al. 2019b). In fact,
in some situations, the within-, and between-family effects
may be opposite in sign (Dietvorst et al. 2018), a situation
called a Simpson’s paradox (Kievit et al. 2013).
Current Study
Family systems perspectives propose that family function-
ing is influential for adolescent adaptation (e.g., Cox et al.
2001). They suggest that if family functioning deteriorates,
this will negatively impact adolescent internalizing and
externalizing symptoms. An important aspect of this
hypothesis is that it focuses within one family, hence, on the
within-family level. Even though extant research has
improved our understanding of how family functioning and
parenting dynamically associate with adolescent adaptation
(Crocetti et al. 2016), a focus on within-family processes
while controlling for between-family stable differences is a
more appropriate test of the theory (e.g., Hamaker et al.
2015; Keijsers 2016), and holds the potential to further
expand our understanding of adolescent development
(Keijsers and van Roekel 2018).
To test the theoretical premises on the correct ecological
level of inference, the present study investigated to what
extent dynamic associations between family functioning
and internalizing and externalizing problems were present at
the within-family level, by applying Random Intercept
Cross-Lagged Panel Models (Hamaker et al. 2015; Keijsers
2016). These novel structural equation models are suitable
for differentiating reciprocal associations at the within-
family level, from stable associations at the between-family
level. Based on the existing empirical evidence about the
relationship between family functioning and adolescent
internalizing and externalizing problems at the between-
family level (e.g., Crocetti et al. 2016), and guided by the
family systems (Cox et al. 2001) and family developmental
theoretical perspectives (e.g., Georgiou and Symeou 2018),
it was hypothesized that family cohesion, flexibility, and
communication will have a significant longitudinal negative
within-family effect on internalizing and externalizing
problems (Hypothesis 1). Thus, it was expected that periods
with decreased cohesion, flexibility and communication
would precede periods with heightened internalizing and
externalizing problems. Additionally, it was hypothesized
that internalizing and externalizing problems will have
longitudinal negative within-person effects on family
cohesion, flexibility and communication (Hypothesis 2).
Method
Sample
The sample for this study consisted of 480 Greek adolescent
students (47.9% girls, 15.7 years old at T1) attending 8 high
schools in Athens, Greece. The schools were selected from
the pool of all the high schools in Attiki (the prefecture
Athens lies in, with more than a third of the country’s
population). Access to this pool was given by the Greek
Ministry of Education. In order to broaden the population of
interest, from this pool 8 high-schools from different parts
of Athens metropolitan area were selected. These parts
corresponded to different socio-economic strata: 3 schools
from the center of Athens (low/lower-middle class),
3 schools from the western, southern, and eastern parts of
the city (middle class areas), one school from the northern
suburbs (upper-middle class), and one school from a less-
urbanized town on the east of Athens (middle class).
The students were assessed three times in 12 months
(two 6-month intervals), between March 2012 and March
2013. The procedures were identical in all three waves.
Trained assistant researchers along with the first author
visited the classrooms during school hours. Questionnaire
completion took part in 2-hour slots, after the school prin-
cipal’s permission.
Measures
Family functioning
To assess the dimensions of family functioning, the Family
Adaptability and Cohesion Evaluation Scales—IV
(FACES-IV, Olson 2011) was used. The FACES-IV has
been translated and adapted in Greek, and it has shown
good psychometric properties in Greek samples (Koutra
et al. 2013).
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Flexibility
The Balanced Flexibility subscale from the FACES—IV
(Olson 2011) was used to assess family flexibility. This
scale consists of 7 items that are addressed in a likert scale
that ranges from 1 (Strongly Disagree)to5(Strongly
Agree). Example items are: “Our family tries new ways of
dealing with problems”and “My family is able to adjust to
change when necessary”. In the current study, this scale
showed satisfactory internal consistency ranging from α=
0.66 to α=0.69 from Wave 1 to Wave 3. The Intraclass
Correlation Coefficient (ICC) was 0.58, indicating that 58%
of the variance was due to stable differences between-
families and the remainder 42% was due to fluctuations
over time, or variance within-families.
Cohesion
The Balanced Cohesion subscale from the FACES-IV (Olson
2011) was used to assess family cohesion. This scale consists
of 7 items that are addressed in a likert scale that ranges from
1(Strongly Disagree)to5(Strongly Agree). Example items
are: “Family members feel very close to each other”,and
“Family members are supportive of each other during difficult
times”. In the current study, this scale showed satisfactory
internal consistency ranging from α=0.71 to α=0.75 from
Wave 1 to Wave 3. The ICC was 0.61, indicating that 39% of
the variance was within-family variance.
Communication
The Family Communication scale from the FACES-IV (Olson
2011) was used to assess family communication. This scale is
based on the Parent-Adolescent Communication scale (Barnes
and Olson 1985) which was revised and included in the 4th
edition of the FACES. This scale consists of 10 items that are
addressed in a likert scale that ranges from 1 (Strongly Dis-
agree)to5(Strongly Agree). Example items are: “Family
members are satisfied with how they communicate with each
other”,and“Family members can calmly discuss problems
with each other”. In the current study, this scale showed good
internal consistency ranging from α=0.89 to α=0.90 from
Wave 1 to Wave 3. With an ICC of 0.62, 38% of the variance
was allocated at the within-family level.
Internalizing and Externalizing Problems
Depressive Symptoms
The Greek version of the Symptoms Checklist 90—Revised
(SCL-90R, Donias et al. 1991) was used to measure
symptoms of depression. The Depression subscale consists
of 13 items which are addressed on a 5-point likert scale,
from 0 (Not at all)to4(Very much). An example item is
“How much were you bothered by feeling low on energy or
slowed down?”. In the current study, the scale showed good
internal consistency, with Cronbach’sαranging from 0.83
to 0.88, from Wave 1 to Wave 3. The ICC was 0.66,
indicating that 34% of the variance was due to within-
person fluctuations over time.
Anxiety
The Greek version of the SCL-90R (Donias et al. 1991)was
used to measure symptoms of anxiety. The Anxiety subscale
consists of 10 items that are addressed on a 5-point likert
scale, from 0 (Notatall)to4(Very much). An example item
is “How much were you bothered by nervousness or shaki-
ness inside?”. The internal consistency in the current study
was good, with Cronbach’sαranging from 0.79 to 0.84, from
Wave 1 to Wave 3. The ICC was 0.64. Thus, 36% of the
variance was within-person variance.
Anger
The Anger subscale from the Greek SCL-90R (Donias et al.
1991) was used to measure anger. This subscale consists of
6 items that are addressed on a 5-point likert scale, from 0
(Not at all)to4(Very much). An example item is “How
much were you bothered by outbursts of anger that you
could not control?”. In this study, Cronbach’sαwere good,
ranging from 0.81 to 0.85, from Wave 1 to Wave 3. The
ICC was 0.58, indicating that 42% of the variance was due
to within-person fluctuations in anger.
Preregistered Analytic Procedure
Random-Intercept Cross-Lagged Panel Models (RICLPM,
Hamaker et al. 2015) were applied to disaggregate within-,
from between-family processes and answer the research
questions. The analytic plan for this study has been pre-
registered on the Open Science Framework on November
23rd, 2018 (anonymized link: https://osf.io/8f95w/?view_
only=ef1f8f29824942889039bde2fa983994). The proce-
dure described in detail in the pre-registered document, and
briefly summarized here, was followed. First, as planned,
data were screened for missing data. Little’s MCAR test
was significant, but the normed chi-square (χ2/df) was low
(386/279 =1.38), implying a small violation of the MCAR
assumption. Therefore, Full Information Maximum Like-
lihood, with Robust standard errors (MLR, Satorra and
Bentler 2001) was applied. With respect to the ICC, there
was more than 10% of variance on the within-person level
for each measure. Thus, applying an analytic technique that
explicitly disaggregates the two levels of variance was
warranted. Nine bivariate RICLPMs were specified, per
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combination of family and outcome dimensions (Table 1).
The basic model was a fully constrained model, with carry-
over stability and cross-lagged effects constrained over
time, as shown in Fig. 1. Finally, as planned, alternative
models were applied, which consisted of different specifi-
cations of the RICLPM (i.e., an unconstrained RICLPM), as
well as standard Cross-Lagged Panel Models.
Results
Descriptive Statistics
Table 2presents the descriptive statistics (means, standard
deviations, and Cronbach’sα) of the study variables.
Within-Person Dynamic Associations Among Family
Functioning and Internalizing and Externalizing
Problems
Table 3presents the fit indices for the bivariate RICLPMs.
All models had an acceptable fit (Table 3), according to the
predetermined criteria of RMSEA < 0.08, CFI > 0.90 and
TLI > 0.90. Tables 4–6present the parameter estimates of
the RICLPMs for each family functioning dimension with
each of the outcome measures. In these models, four types
of effects are provided: between-family correlations, within-
time associations (correlated change), within-family stabi-
lity effects, and within-family cross-lagged effects. The
syntaxes can be found following this OSF link: https://osf.
io/r9kpy/?view_only=0d55d50910274dd8acba47fa
28738d98.
As seen in Tables 4–6, in most models including family
flexibility and family communication the between-person
associations with internalizing and externalizing problems
were negative and significant. Adolescents who reported
better family functioning (indicated by higher flexibility,
and family communication) compared to other adolescents,
Table 1 List of predictors and outcome measures
Family functioning dimensions Adolescent outcomes
Family flexibility Depressive symptoms
Family cohesion Anxiety symptoms
Family communication Aggression
Fig. 1 Random intercept cross-lagged panel model as applied in this study
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tended to also report lower internalizing and externalizing
problems compared to their peers. An exception to this was
the between-person associations among family cohesion
and adolescent internalizing and externalizing problems;
these associations were not significant.
With regard to estimates for within-family correlated
change, as well as the estimates for within-family cross-
lagged effects, Tables 4–6show that there were no sig-
nificant estimates. That is, whether an adolescent experi-
enced changes in the family functioning, compared to this
adolescent’s own typical family functioning, was unrelated
to this adolescent’s change (either increase or decrease) in
her/his internalizing and/or externalizing problems. In short,
these results indicate that despite the meaningful variances
on the within-family level in each variable, and in contrast
to the hypotheses offered by family systems theory, the
associations among family functioning and internalizing
and externalizing problems are more a matter of between-
family differences, than of correlated within-family
fluctuations.
Alternative Models
As planned (see link to OSF), further analyses were con-
ducted to investigate whether models specified differently
than the initial RICLPMs could provide a better fit to the
data. These models were: 1) standard Cross-Lagged Panel
Models (standard CLPMs), and 2) RICLPMs where the
lagged coefficients were left free to vary across time inter-
vals (instead of being fixed equal across time intervals). Fit
was judged based on the same criteria used for the initial
models (RMSEA, CFI, TLI). In Table 3, the alternative
models that had a better fit compared to the initial models
are noted with an asterisk.
The parameter estimates for those alternative models
with better fit compared to the initial models are given in
Tables S1-S4 in the Supplementary Material. In all models
that included Depressive symptoms, as well as those
including Family Cohesion (5 models in total) the more
parsimonious standard CLPM provided better fit than the
initial RICLPMs. As shown in the Supplementary Material,
in all five standard CLPMs, significant negative cross-
lagged effects emerged from Depressive symptoms at Wave
1 and at Wave 2, to family functioning at Wave 2 and at
Wave 3, respectively, as well as from Anxiety and Anger to
Family Cohesion. Although CLPM confounds within-, and
between-family variances (Berry and Willoughby 2017;
Keijsers 2016), the findings from the alternative models, in
combination with the findings from the initial RI-CLPMs
that only showed between-family associations, indicate that
those adolescents who reported higher Depressive symp-
toms at Wave 1 and at Wave 2, compared to their peers,
tended to also have lower family functioning at Wave 2, and
at Wave 3, respectively.
Finally, regarding the unconstrained RICLPMs, five
models had significantly better fit compared to the initial
RICLPMs. As seen in Tables S1–S4 in the Supplementary
Material, no significant within-family effects were found in
any of those alternative models.
Sensitivity Analyses
Sensitivity analyses were conducted to explore whether
results are robust when controlling for adolescent sex and
socioeconomic status. Please note that these analyses were
not part of the initial plan, and they are not preregistered. In
this study, socioeconomic status was a composite score
comprising of mother education, father education, mother
employment, father employment, family status, own house
(vs. rent), and home density. Those variables were mea-
sured in all three waves, resulting in three measures of ses,
which were then combined in one general ses variable.
Table S5 in the Supplementary Material presents the fit
indices for the initial models (RICLPM) and the best fitting
alternative models (either RICLPM-unconstrained, or
standard CLPM), after controlling for adolescent sex and
socioeconomic status, by regressing the observed scores of
family functioning and internalizing/externalizing pro-
blems on sex and ses. Tables S6–S8 present the results of
the RICLPM models controlling for adolescent sex and
Table 2 Descriptive statistics (means, standard deviations, and internal
consistency coefficients α) for all study variables
MSDα
Age 15.73 0.82
Depressive symptoms Τ1 0.95 0.67 0.85
Depressive symptoms Τ2 0.92 0.64 0.83
Depressive symptoms Τ3 0.88 0.71 0.88
Anxiety Τ1 0.83 0.62 0.79
Anxiety Τ2 0.76 0.58 0.80
Anxiety Τ3 0.71 0.63 0.84
Anger Τ1 1.11 0.88 0.82
Anger Τ2 1.00 0.88 0.85
Anger Τ3 0.97 0.86 0.85
Flexibility Τ1 23.31 4.38 0.66
Flexibility Τ2 23.36 4.50 0.69
Flexibility Τ3 23.21 4.50 0.68
Cohesion Τ1 24.39 4.73 0.71
Cohesion Τ2 24.65 4.65 0.73
Cohesion Τ3 24.56 4.65 0.75
Communication Τ1 29.63 6.07 0.89
Communication Τ2 29.39 5.97 0.88
Communication Τ3 28.92 6.40 0.90
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family socioeconomic status. Tables S9–S12 present the
parameter estimates for the best-fitting alternative models,
controlling for adolescent sex and family socioeconomic
status.
As can be seen by comparing those estimates with the
models without covariates, only few minor changes
emerged, and they mostly referred to the autoregressive
stability of anger, which turned significant in the models
with covariates (Tables S6–S8). One additional change was
that the between-family correlation among Depressive
symptoms and Family Flexibility in the alternative uncon-
strained RICLPM (Table S9) turned non-significant. All
other parameter estimates remained largely unchanged,
which indicates that the substantive results of this study
hold also when controlling for adolescent sex and family
socioeconomic status.
Discussion
Adolescence is a formative period with many changes
happening on the cognitive, emotional, and social spheres.
Family relationships also change during adolescence.
Additionally, for some adolescents adolescence is when
internalizing and externalizing problems develop. Theore-
tically, links between family functioning, and internalizing
and externalizing problems are expected to take place on the
within-family level. Yet, most developmental research thus
far has failed to adequately focus on within-family pro-
cesses. This study examined some of the key premises of
family systems theory, that within-family changes in the
family system would be bidirectionally linked to within-
child changes in internalizing and externalizing problems.
Following an ongoing methodological discussion on the
Table 3 Model fit indices for
all models Model Type χ2df CFI TLI RMSEA
Flexibility—depressive symptoms RICLPM-fixed 14.433 5 0.988 0.964 0.063
Flexibility—depressive symptoms* CLPM 16.214 7 0.988 0.975 0.052
Flexibility—depressive symptoms* RICLPM-free 2.716 1 0.998 0.968 0.060
Flexibility—anxiety RICLPM-fixed 17.601 5 0.984 0.951 0.073
Flexibility—anxiety CLPM 20.939 7 0.982 0.962 0.064
Flexibility—anxiety* RICLPM-free 2.304 1 0.998 0.975 0.052
Flexibility—anger RICLPM-fixed 12.153 5 0.990 0.971 0.055
Flexibility—anger CLPM 21.280 7 0.981 0.959 0.065
Flexibility—anger RICLPM-free 4.786 1 0.995 0.924 0.089
Cohesion—depressive symptoms RICLPM-fixed 17.407 5 0.985 0.954 0.072
Cohesion—depressive symptoms* CLPM 13.878 7 0.991 0.982 0.045
Cohesion—depressive symptoms RICLPM-free 6.688 1 0.993 0.894 0.109
Cohesion—anxiety RICLPM-fixed 16.380 5 0.986 0.957 0.069
Cohesion—anxiety* CLPM 14.152 7 0.991 0.981 0.046
Cohesion—anxiety* RICLPM-free 5.366 1 0.994 0.917 0.095
Cohesion—anger RICLPM-fixed 18.861 5 0.982 0.945 0.076
Cohesion—anger* CLPM 12.016 7 0.993 0.986 0.039
Cohesion—anger RICLPM-free 14.313 1 0.982 0.736 0.167
Communication—depressive symptoms RICLPM-fixed 13.790 5 0.990 0.969 0.061
Communication—depressive symptoms* CLPM 4.073 7 1.000 1.007 0.000
Communication—depressive symptoms RICLPM-free 3.507 1 0.997 0.956 0.072
Communication—anxiety RICLPM-fixed 18.596 5 0.984 0.951 0.075
Communication—anxiety* CLPM 13.830 7 0.992 0.982 0.045
Communication—anxiety* RICLPM-free 0.633 1 1.000 1.007 0.000
Communication—anger RICLPM-fixed 13.720 5 0.989 0.967 0.060
Communication—anger* CLPM 13.911 7 0.991 0.982 0.045
Communication—anger* RICLPM-free 2.117 1 0.999 0.983 0.040
RICLPM-fixed random-intercept cross-lagged panel models with time invariance constrains on the
autoregressive stabilities and the cross-lagged effects, CLPM cross lagged panel model, RICLPM-free fully
unconstrained random intercept cross lagged panel model, CFI comparative fit index, TLI Tucker–Lewis
Index, RMSEA root mean square error of approximation
*This model has better fit than the initial/original model, and therefore alternative model results are presented
in the Supplementary Material
810 Journal of Youth and Adolescence (2020) 49:804–817
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interpretation of the CLPM (Berry and Willoughby 2017;
Hamaker et al. 2015; Keijsers 2016), these longitudinal
dynamic associations were tested at the within-family level,
while controlling for stable differences and associations at
the between-family level (e.g., Keijsers 2016). Even though
the expected significant negative associations among all
variables on the between-family level were found, no
significant associations emerged at the within-family level.
Thus, even though adolescents who grow up in families
with worse communication, lower cohesion, and lower
flexibility seem to be at higher risk for adaptation problems,
within-family changes in family functioning were unrelated
to child adaptation, which is in contrast to the pre-registered
hypotheses. Applying standard CLPMs as an alternative
Table 4 Parameter estimates for the bivariate fixed RICLPMs modelling family flexibility with depressive symptoms, anxiety, and anger
Family Flexibility Depressive symptoms Anxiety Anger
BSEpβBSEpβBSEpβ
Correlations
Between-Person −0.299 0.129 0.021 −0.149 −0.327 0.148 0.027 −0.186 −0.322 0.212 0.129 −0.149
T1 −0.112 0.081 0.168 −0.096 −0.151 0.090 0.091 −0.131 −0.285 0.164 0.083 −0.166
Cross-lagged effects
Problems 1 →Flex. 2 0.028 0.636 0.965 0.005 0.409 0.811 0.614 0.068 −0.259 0.611 0.671 −0.062
Problems 2 →Flex. 3 0.028 0.636 0.965 0.003 0.409 0.811 0.614 0.045 −0.259 0.611 0.671 −0.062
Flex. 1 →Problems 2 0.011 0.013 0.413 0.107 0.004 0.013 0.752 0.036 −0.004 0.023 0.862 −0.017
Flex. 2 →Problems 3 0.011 0.013 0.413 0.064 0.004 0.013 0.752 0.028 −0.004 0.023 0.862 −0.019
Stability paths
Flex. 1 →Flex. 2 −0.144 0.133 0.282 −0.148 −0.159 0.135 0.236 −0.164 −0.128 0.163 0.433 −0.127
Flex. 2 →Flex. 3 −0.144 0.133 0.282 −0.137 −0.159 0.135 0.236 −0.151 −0.128 0.163 0.433 −0.126
Problems 1 →Problems 2 −0.166 0.105 0.115 −0.269 0.028 0.158 0.860 0.040 0.300 0.192 0.118 0.295
Problems 2 →Problems 3 −0.166 0.105 0.115 −0.103 0.028 0.158 0.860 0.022 0.300 0.192 0.118 0.341
Correlated change
T2 0.154 0.173 0.374 0.235 0.079 0.180 0.660 0.104 −0.236 0.341 0.490 −0.141
T3 0.023 0.097 0.815 0.020 −0.019 0.087 0.828 −0.019 −0.054 0.142 0.703 −0.037
Problems: denotes the internalizing and externalizing problems, as specified in the columns; Flex.: family flexibility
Table 5 Parameter estimates for the bivariate fixed RICLPMs modelling family cohesion with depressive symptoms, anxiety, and anger
Family Cohesion Depressive symptoms Anxiety Anger
BSEpβBSEpβBSEpβ
Correlations
Between-Person −0.287 0.167 0.086 −0.143 −0.117 0.206 0.571 −0.076 −0.314 0.271 0.246 −0.149
T1 −0.112 0.110 0.307 −0.080 −0.224 0.134 0.095 −0.154 −0.117 0.262 0.656 −0.056
Cross-Lagged Effects
Problems 1 →Cohesion 2 −0.241 0.781 0.758 −0.035 −0.189 0.870 0.172 −0.170 −0.547 0.589 0.353 −0.119
Problems 2 →Cohesion 3 −0.241 0.781 0.758 −0.022 −0.189 0.870 0.172 −0.164 −0.547 0.589 0.353 −0.123
Cohesion 1 →Problems 2 −0.006 0.014 0.653 −0.077 −0.021 0.015 0.167 −0.159 −0.010 0.025 0.706 −0.045
Cohesion 2 →Problems 3 −0.006 0.014 0.653 −0.046 −0.021 0.015 0.167 −0.159 −0.010 0.025 0.706 −0.048
Stability Paths
Cohesion 1 →Cohesion 2 0.141 0.128 0.270 0.151 0.155 0.120 0.195 0.157 0.126 0.139 0.363 0.135
Cohesion 2 →Cohesion 3 0.141 0.128 0.270 0.141 0.155 0.120 0.195 0.158 0.126 0.139 0.363 0.126
Problems 1 →Problems 2 −0.166 0.114 0.144 −0.266 0.301 0.477 0.528 0.319 0.335 0.189 0.076 0.325
Problems 2 →Problems 3 −0.166 0.114 0.144 −0.105 0.301 0.477 0.528 0.305 0.335 0.189 0.076 0.379
Correlated change
T2 −0.148 0.205 0.470 −0.193 −0.393 0.191 0.039 −0.323 −0.221 0.296 0.457 −0.117
T3 0.076 0.102 0.455 0.061 −0.090 0.117 0.443 −0.077 −0.077 0.151 0.608 −0.048
Problems: denotes the internalizing and externalizing problems, as specified in the columns; Cohesion: family cohesion
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and more parsimonious approach revealed significant
negative cross-lagged effects of internalizing and externa-
lizing problems on family functioning, but not vice versa.
These results suggest that how families become more dif-
ferent from each other over time can be predicted from
preceding differences in child adaptation. However, the
interpretation of such statistical effects is an ongoing dis-
cussion by itself [for example, Berry and Willoughby
(2017) label such effects an uninterpretable blend].
Dynamic Associations Among Family Functioning
and Internalizing and Externalizing Problems: Not a
Within-Person Story
Based on previous theorizing and extant research, the
hypotheses of this study were that family functioning would
have a significant, longitudinal, negative within-family
effect on internalizing (Queen et al. 2013) and externaliz-
ing problems (Elgar et al. 2013). Also, it was predicted that
internalizing and externalizing problems would have a
significant, longitudinal, negative within-family effect on
family functioning. However, no significant effects in sup-
port of any of these predictions were found, despite the
relatively large sample size (N=480).
The absence of significant within-family effects (both
cross-lagged, and correlated change) indicates that the
associations among family functioning and internalizing
and externalizing problems are not a within-family process
in which the child and family system affect each other. In
contrast, the presence of significant cross-lagged effects in
the CLPMs, might indicate that the dynamic associations
among family functioning and adolescent internalizing and
externalizing problems might be a matter of stable differ-
ences between families in the emotional climate, which can
be predicted by child adaptation the preceding months. It
appears that what matters is the relative standing of an
adolescent’s family functioning in relation to other peers
when it comes to understanding who will develop inter-
nalizing and externalizing problems, and vice versa. In this
sense, the current results are in accordance with the results
of previous studies, which used between-family designs
(Branje et al. 2010). Adolescents who experience more
internalizing and externalizing problems relative to their
peers are also expected to experience worse family func-
tioning the following months. This study shows that it is
possible to identify who, among adolescents, might be more
in need of a psychological and/or family therapy interven-
tion, given the longitudinal effects found among symptoms
of depression and family functioning.
From a theoretical point of view, the absence of sig-
nificant within-family effects may help clarify the theore-
tical expectations on how family functioning and
internalizing/externalizing problems develop in middle to
late adolescence, and how it affects the psychological well-
being of individual adolescents. Given that the current study
applied an explicit disaggregation of between-, and within-
family sources of variance in investigating order of effects,
it stands to point that most family processes during ado-
lescence become meaningful only when the rest of the
group is taken into account. Thus, families differ from each
Table 6 Parameter estimates for the bivariate fixed RICLPMs modelling family communication with depressive symptoms, anxiety, and anger
Family Communication Depressive symptoms Anxiety Anger
BSEpβBSEpβBSEpβ
Correlations
Between-Person −0.647 0.182 0.000 −0.231 −0.621 0.230 0.007 −0.256 −0.941 0.319 0.003 −0.313
T1 −0.161 0.136 0.239 −0.095 0.021 0.142 0.883 0.013 −0.253 0.232 0.276 −0.102
Cross-lagged effects
Problems 1 →Comm. 2 0.037 0.953 0.969 0.005 0.804 1.424 0.572 0.111 0.672 0.931 0.470 0.138
Problems 2 →Comm. 3 0.037 0.953 0.969 0.003 0.804 1.424 0.572 0.064 0.672 0.931 0.470 0.114
Comm. 1 →Problems 2 −0.002 0.012 0.828 −0.036 −0.003 0.014 0.852 −0.034 0.012 0.021 0.580 0.070
Comm. 2 →Problems 3 −0.002 0.012 0.828 −0.018 −0.003 0.014 0.852 −0.022 0.012 0.021 0.580 0.063
Stability paths
Comm. 1 →Comm. 2 −0.040 0.157 0.799 −0.050 −0.041 0.165 0.805 −0.050 −0.041 0.155 0.791 −0.051
Comm. 2 →Comm. 3 −0.040 0.157 0.799 −0.032 −0.041 0.165 0.805 −0.033 −0.041 0.155 0.791 −0.033
Problems 1 →Problems 2 −0.167 0.112 0.135 −0.271 0.040 0.202 0.841 0.057 0.309 0.170 0.069 0.303
Problems 2 →Problems 3 −0.167 0.112 0.135 −0.105 0.040 0.202 0.841 0.033 0.309 0.170 0.069 0.345
Correlated change
T2 0.065 0.256 0.798 0.082 −0.013 0.312 0.968 −0.013 0.076 0.426 0.859 0.039
T3 −0.118 0.153 0.442 −0.072 −0.089 0.122 0.465 −0.061 −0.034 0.208 0.868 −0.016
Problems: denotes the internalizing and externalizing problems, as specified in the columns; Comm.: Family communication
812 Journal of Youth and Adolescence (2020) 49:804–817
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other, which may provide insights into who is at risk. The
Circumplex Model (Olson 2011), on which the current
study was based, may work well as a static description of
differences between families, yet, no evidence for the
hypothesized processes within-families was found. Newer
models may be needed that make explicit developmental
hypotheses regarding how the family processes, and fluc-
tuations therein, affect the psychological well-being of
individual members in the family. What is urgently needed
in this respect is a better clarification also of the time scale
at which these dynamic processes take place. For instance,
in dynamic system approaches (e.g., Granic and Patterson
2006), the accumulation of short-term micro-dynamics
should yield longer term divergent change in families and
child adaptation. But the short- and longer-term patterns
may be non-linearly related. The mere fact that reciprocal
effects were not found in the present study may also mean
that the focal time frame is discordant with the time scale at
which these mechanisms take place (Keijsers and van
Roekel 2018). Given that there is now a much better access
to the statistical techniques to explore such hypotheses (e.g.,
Dynamic Structural Equation Modeling, Asparouhov et al.
2018; Continuous Time Structural Equation Modeling,
Voelkle et al. 2012), and novel methods to collect data into
short-term dynamics, such as Experience Sampling (Keij-
sers and van Roekel 2018), future studies and conceptual
developments may help move the field of family systems
forward.
Alternative Dynamic Associations Among Family
Functioning and Internalizing/Externalizing
Problems
Applying standard CLPMs as an alternative approach to
investigate the order of effects among family functioning
and internalizing/externalizing problems in adolescence,
consistent, significant, and negative cross-lagged effects
were found, from internalizing/externalizing problems to
family functioning over intervals of six months. Yet,
although statistically it is meaningful to see that adolescent
adaptation problems may predict interfamily differences
over time in family functioning, the theoretical interpreta-
tion of CLPM cross-lagged effects (e.g., are they between-
family?) is a question of methodological debate (Berry and
Willoughby 2017).
Statistically, adolescents that experienced more symp-
toms of depression compared to their peers, were more
likely to experience a deterioration in their family flex-
ibility, family cohesion, and family communication six
months later, while controlling for different types of stabi-
lity. Even though the exact meaning of CLPM is now an
issue of debate (Berry and Willoughby 2017; Keijsers
2016), the current findings do help to clarify extant cross-
sectional research on the associations among family func-
tioning and adolescent symptoms of depression (Elgar et al.
2013), by elucidating the direction of statistical prediction.
Importantly, the opposite direction of effects, that is, effects
of family functioning on symptoms of depression, was not
found. This is in accordance with recent longitudinal
research that has showed that during adolescence “child
effects”become stronger compared to “parent effects”(e.g.,
Georgiou and Fanti 2014; for a review, see Meeus 2016),
but it is in disagreement with other studies showing bidir-
ectional effects among adolescent symptoms of depression
and parent-adolescent relationship quality (Branje et al.
2010). Stated otherwise, in line with the view that parents
and family lose part of their significance compared to other
aspects of the adolescent’s psychosocial spheres (e.g., the
role of peers, other social networks), the current pre-
registered study offered no evidence for effects from family
functioning to adolescent symptoms of depression. There-
fore, the present results show that family as a system might
not play a significant causal role in developing depressive
symptoms during adolescence.
Furthermore, the results showed that adolescents who
experienced more anxiety and more anger, compared to
their peers, were the most probable to experience a decrease
in their family cohesion. Similar findings have been
obtained in extant research (e.g., Jozefiak and Wallander
2016). Similar to the findings regarding symptoms of
depression, these findings are in agreement with the “child
effects”view that adolescents play an ever stronger role in
the development of their environment, as they grow older
(e.g., Meeus 2016). In contrast, changes in the relative
standing of families in family cohesion do not appear to
have an effect of adolescent anger and symptoms of anxiety.
Limitations, Strengths, and Future Directions
Several limitations must be taken into account when con-
sidering the results of this study. First, even though self-
report can be an adequate method in obtaining insights
regarding internalizing problems, family functioning as well
as externalizing problems could also be measured with
other-reported data and/or observations, to obtain a more
objective view. Second, the causal processes between
family functioning and adolescent adaptation may take
place at longer or shorter time intervals, making it impos-
sible to detect them with the fixed time lags used in this
study. An alternative approach could be to have time lags
with multiple lengths in one study design (Keijsers and van
Roekel 2018) and apply continuous time models (Voelkle
et al. 2012) to assess how the effect depends on the length
of the time interval, and when the effect is the strongest.
Moreover, it could be that the duration of the study was
relatively small, making it impossible to detect the longer
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term (developmental changes in) within-family processes.
Following the same participants throughout adolescence,
preferably with measurement burst with shorter intervals,
might provide better insights in the dynamic interplay
among family functioning and internalizing and externa-
lizing problems at the macro-time scale. For instance, to tap
into influences between family functioning and adolescent
adaptation measurements at a meso-, or a micro-time scale,
daily diaries or Experience Sampling, may be useful addi-
tional methodologies.
Notwithstanding these limitations, this study has several
strengths and it offers important insights in the dynamic
interplay among family functioning and internalizing and
externalizing problems during adolescence. First, the
application of newly developed statistical techniques on
longitudinal data, which allows to differentiate within-
family from between-family effects, has specific strengths
in family research, as such research is often plagued by
challenges of differentiating gene-environment effects,
environmental effects, or other stable confounders, from the
actual influences family functioning has on the child. By
controlling for all stable differences in family functioning
and in the adolescent outcomes, by default, all stable con-
founders are controlled for, whether they are included in the
study design or not. This allows to examine relevant the-
ories on the ecological level these theories are postulated,
that is, the within-family level, and provides a much more
stringent test for the influences of families on children.
Earlier research has illustrated that this may also lead to
paradoxical findings, for instance, positive associations at
the between-family level, but negative associations at the
within-family level (e.g., Dietvorst et al. 2018). Thus, a new
wave of research, with novel analytical methods, may help
to critically evaluate and refine existing ideas. Second, the
theoretical background, the rationale, and the plan of ana-
lyses of this study were all pre-registered, based on state-of-
the-art methodological writings, and followed in detail in
this study. This is important because in this way all analyses
are well-thought in advance, and they are tailored to test
pre-specified hypotheses, instead of exploring associations
in a big dataset. Applying open science practices (Nosek
et al. 2015) is a promising route to improving psychological
science, and this study sets an example of how the analy-
tical plan for RICLPM can also be preregistered. Third, a
relatively large sample of a broadly understudied population
was used. Even though null results are difficult to test
(Ferguson and Heene 2012), the large sample indicates that
the null results found in this study are legitimate.
Overall, this study has been designed to provide a more
stringent test of existing theoretical hypotheses regarding
the link of family functioning with child internalizing and
externalizing problems. It is one example of a larger
movement in which it is advocated that future research
should be designed to match the theoretical time scales to
the analytical designs (Keijsers and van Roekel 2018).
Theory ultimately should determine what the adequate time
scale of observation is, and in this respect, building a solid
theoretical basis, which is explicit about the ecological level
and time scale of developmental processes, is a major
challenge for future research.
Conclusion
Adolescence can be a challenging period for some adoles-
cents, because of the increased risk for the development of
internalizing and/or externalizing problems. Even though
parent-adolescent relationships change during adolescence
(Branje et al. 2012), as shown, for example, by the
increased parent-adolescent conflict intensity (Mas-
trotheodoros et al. 2019a), family remains an influential
context for adolescent development. Family systems theory
posits that family functioning is important for adolescent
adaptation, a proposition that is located on the within-family
level. Thus, if family functioning changes within one
family, for instance, the cohesion decreases, this should
affect the adolescent within that same family. To test this
proposition appropriately, it is necessary to explicitly dis-
aggregate variances due to between-family differences,
from the fluctuations and changes, as well as their asso-
ciations, at the within-family level (e.g., Hamaker et al.
2015; Keijsers 2016).
This study investigated the longitudinal dynamic asso-
ciations between family functioning and internalizing and
externalizing problems, on the within-family level, while
controlling for stable between-family differences and asso-
ciations. The null results on the within-family level indicate
that, during adolescence, fluctuations in family functioning
as well as in internalizing/externalizing problems are not
associated with each other at the 6-month time interval. At
the same time, significant effects in the CLPM models
suggest that statistical prediction is still possible—mainly
from adolescent adaptation to family functioning. For
example, based on the results of the current study, it is
suggested that adolescents who develop more symptoms of
depression are statistically in higher risk for experiencing
decreases in family functioning the following months
compared to their peers who do not experience increases in
depressive symptoms. However, this statistical link is most
likely not a causal one.
To conclude, the results of this study have important
theoretical and practical implications. The null results on the
within-person level call for further empirical research and
perhaps even theoretical refinement regarding the ecological
level and time scale at which developmental processes, such
as the ones studied here, take place (e.g., Keijsers and van
814 Journal of Youth and Adolescence (2020) 49:804–817
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Roekel 2018). It appears that, even though within-family
fluctuations in family functioning are largely incon-
sequential for adolescent internalizing and externalizing
problems, robust between-family associations exist in how
adolescent adaptation and family functioning relate to each
other. In families with more flexibility, cohesion, and
communication, adolescents are on average better adapted.
But, to date, we cannot conclude that this link is due to
within-family dynamic processes between changes in
family functioning and adolescent adaptation. Until a better
understanding of within-family processes is reached,
focusing on those adolescents with higher than average
symptoms of depression, anxiety, and anger may help to
identify those among youth that are most in need for family
interventions.
Acknowledgements The authors would like to thank the European
Association of Developmental Psychology—Early Researchers Union
(EADP ERU) for the organisation of the 2018 Writing Week in Erice,
Italy, to support collaboration on this article. Stefanos Mas-
trotheodoros would like to thank Prof. Dr Frosso Motti-Stefanidi, and
Dr Vasileios Stavropoulos for their vital contributions to this project.
The theoretical background, the hypotheses, and the analytic plan of
this study were preregistered on November 23rd, 2018, at the Open
Science Framework. The DOI to these documents is: https://doi.org/
10.17605/OSF.IO/CFP8Z Therefore, all analyses reported in the arti-
cle, except for the “Sensitivity Analyses”, are confirmatory.
Authors’Contributions S.M. conceived of the study, coordinated the
data collection, performed data collection, performed data entry, pre-
registered and performed the statistical analyses, interpreted the
results, and drafted the manuscript; C.C. drafted the manuscript criti-
cally, and was involved in the interpretation of the results; M.C.G.
drafted the manuscript, and was involved in the interpretation of the
results; M.M. drafted the manuscript critically, and was involved in the
interpretation of the results; LK. drafted the manuscript, helped with
the preregistration and performance of analyses, was involved in the
interpretation of results, and revised the manuscript critically. All
authors contributed significantly to the current manuscript. All authors
read and approved the final manuscript.
Funding This study has been supported by a scholarship to Stefanos
Mastrotheodoros from the Alexander S. Onassis Public Benefit
Foundation. Furthermore, work for this article has been supported with
a personal grant to Loes Keijsers awarded from The Netherlands
Organisation for Scientific Research (NWO-VIDI; ADAPT. Assessing
the Dynamics between Adaptation and Parenting in Teens
452.17.011.)
Data Sharing and Declaration The datasets generated and/or analyzed
during the current study are not publicly available but are available
from the corresponding author on reasonable request.
Compliance with Ethical Standards
Conflict of interest The authors declare that they have no conflict of
interest.
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
standards.
Informed Consent Informed consent was obtained from all individual
participants included in the study, for each wave separately after
explaining their role and their rights in the study and before starting
data collection.
Publisher’s note: Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
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 made.
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Stefanos Mastrotheodoros is a doctoral researcher at the
Department of Youth and Family, Utrecht University, the
Netherlands. He holds a PhD from the University of Athens,
Greece, where he studied the development of personal identity from
middle to late adolescence. He currently conducts a second PhD at
Utrecht University, investigating the determinants of parenting and the
development of parent-adolescent relationships during adolescence.
Catarina Canário is a doctoral researcher at the Center for
Psychology at the University of Porto, Portugal. She is currently
conducting research focusing on the effectiveness of positive parenting
interventions targeting different groups: (1) parents of overweight and
obese children, and (2) parents of children at-risk followed by the
protective services. Her research interests also focus on children’s and
parents’individual differences to the parenting interventions.
Maria Cristina Gugliandolo is a post-doctoral research fellow at the
Department of Human, Social and Health Sciences, University of
Cassino and South Latium. In 2014 she obtained the Phd in
Psychological Sciences at the University of Messina, and in 2016 a
Master in Applied Behavior Analysis at the University of Parma. Her
research interests focus on predictive factors of the adolescent
development, with a particular attention to adolescents’trait
Emotional Intelligence and parenting practices.
Marina Merkas is an Assistant Professor of Developmental
Psychology at the Department of Psychology, Catholic University of
Croatia. She has published articles on the determinants of well-being
of children and adolescents, and the effects of economic hardship and
pressure on the well-being of parents and children. She is interested in
family dynamics and how they are associated with different
developmental outcomes in children, the effects of digital
technology on child behavior, and new methodological approaches
to studying child development.
Loes Keijsers is an Associate Professor at the Department of
Developmental Psychology, Tilburg University, the Netherlands and
director of the Tilburg Experience Sampling Center (TESC). She
studies the normal and abnormal development of adolescent
adaptation, and the linkages with parenting (e.g., parental
monitoring, parent-child communication), applying state-of-the-art
methods, such as Random-Intercept Cross-lagged Panel Models and
Experience Sampling of the daily rhythms of family life.
Journal of Youth and Adolescence (2020) 49:804–817 817
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