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This study aimed to describe problem behaviors and psychosocial strengths, examine the problem-strength interrelations, and evaluate profiles of problems and strengths in youth with Down syndrome (DS). The community-based sample consisted of 67 parents of children with DS aged between 4 and 19 years. Parents reported about the developmental age (Vineland screener), behavioral problems (Child Behavior Checklist), and psychosocial strengths (Behavioral and Emotional Rating Scale) of their child. Results indicate that attention, social, and thought problems were most prevalent, whereas family involvement and receiving/expressing affection were identified as strengths. A confirmatory factor analysis identified problems and strengths as distinct, yet related, variables. Moreover, a cluster analysis of problems and strengths identified four different profiles. Implications for interventions are discussed.
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
Behavioral Problems and Psychosocial Strengths: Unique
Factors Contributing to the Behavioral Profile of Youth
With Down Syndrome
Lisa M. Dieleman, Sarah S.W. De Pauw, Bart Soenens, Geert Van Hove, and Peter Prinzie
This study aimed to describe problem behaviors and psychosocial strengths, examine the
problem-strength interrelations, and evaluate profiles of problems and strengths in youth
with Down syndrome (DS). The community-based sample consisted of 67 parents of
children with DS aged between 4 and 19 years. Parents reported about the developmental
age (Vineland screener), behavioral problems (Child Behavior Checklist), and psychosocial
strengths (Behavioral and Emotional Rating Scale) of their child. Results indicate that
attention, social, and thought problems were most prevalent, whereas family involvement
and receiving/expressing affection were identified as strengths. A confirmatory factor
analysis identified problems and strengths as distinct, yet related, variables. Moreover, a
cluster analysis of problems and strengths identified four different profiles. Implications for
interventions are discussed.
Key Words: Down syndrome; emotional and behavioral problems; psychosocial strengths; behavioral
Down syndrome (DS) has aroused a longstanding
interest in scholars and practitioners (e.g., Dykens
& Kasari, 1997), leading to a nuanced perspective
on its behavioral phenotype. Research has shown
that children with DS vary largely in their
behavioral presentation and possess both weak-
nesses and strengths (Chapman & Hesketh, 2000;
Grieco, Pulsifer, Seligsohn, Skotko, & Schwartz,
2015). Nevertheless, these studies have tended to
focus either on strengths or on behavioral
problems. As such, important questions about
their interrelation and co-occurrence have not
been addressed. Do problem behaviors and
strengths represent two ends of a continuum or
are they separate constructs? Does an absence of
behavioral problems by definition indicate the
presence of strengths (and vice versa) or can
different profiles of problems and strengths be
distinguished? This study aims to obtain a more
comprehensive view on the behavioral phenotype
of children with DS by (1) describing both
strengths and problems, (2) examining their
interrelations, and (3) evaluating profiles of
strengths and problems.
Emotional-Behavioral Problems and
Psychosocial Strengths in Youth With DS
Children with DS are, although exhibiting fewer
emotional and behavioral problems than children
with specific syndromes or with nonspecific
intellectual disability (Chapman & Hesketh,
2000; Grieco et al., 2015; Rice et al., 2015), ‘‘far
from problem-free’’ (Dykens, 2007, p. 273).
Multiple studies have documented substantially
more problems in children with DS than in their
typically developing peers (Dekker, Koot, van der
Ende, & Verhulst, 2002; Dykens, 2007; Dykens &
Kasari, 1997). Children with DS are especially at
risk to display hyperactivity, impulsivity, atten-
tional problems, noncompliance, and compulsive-
like behavior (Dykens, 2007; Evans & Gray, 2000;
Siegel & Smith, 2011). van Gameren-Oosterom
212 Problems and Strengths in DS
and colleagues (2011) found that social, thought,
and attention problems were the most prevalent
problems in a cohort of Dutch 8-year-olds with
DS. A follow-up study indicated that these three
problem domains remained most problematic
during late adolescence (van Gameren-Oosterom
et al., 2013).
Although research has documented systemat-
ically the problem behaviors in children with DS,
only a few studies examined their psychosocial
strengths. This is unfortunate because research
increasingly demonstrates the importance of fo-
cusing not only on problems but also on the
strengths of children with a disability (Buntinx &
Schalock, 2010). The current research used a
‘‘strength-based approach’’ originating from posi-
tive psychology (Seligman & Csikszentmihalyi,
2000), which states that each individual manifests
strengths. Psychosocial strengths are defined as
behaviors that create a sense of satisfaction, foster
relationships, strengthen the ability to cope with
adversity, or generally promote development
(Epstein & Sharma, 1998). An example is the
degree to which children are able to express
affection in close relationships. These psychosocial
strengths reflect qualities of a person as a whole
and can be differentiated from adaptive skills,
which refer to conceptual (e.g., number concepts),
social (e.g., social problem solving), and practical
(e.g., use of money) skills that allow coping with
the requirements of daily life (American Associa-
tion on Intellectual and Developmental Disabili-
ties, 2010). Until today, most research in DS has
focused on adaptive skills (Dressler, Perelli, Feucht,
& Bargagna, 2010; Dykens, Hodapp, & Evans,
2006), at the neglect of psychosocial strengths.
However, some studies concerning the behavioral
phenotype of children with DS can give an
indication of their psychosocial assets. These
studies identified social understanding, empathy,
and social behavior as strengths of children with
DS (Di Nuovo & Buono, 2011; Marchal et al.,
2016). Children with DS are, for example, reported
to respond adaptively to distress in others by
expressing concern and offering comfort (Kasari,
Freeman, & Bass, 2003).
Emotional-Behavioral Problems and
Psychosocial Strengths: Two Ends of a
Continuum or Separate Constructs?
According to the strength-based approach, the
presence of problem behavior cannot be simply
equated with the absence of psychosocial strengths
(Rashid & Ostermann, 2009). Several studies in
samples of children with developmental disorders,
showed that emotional and behavioral problems
and psychosocial strengths are related yet distinct
constructs, suggesting that both indicators of
adjustment need to be assessed to provide a
comprehensive understanding of a population’s
behavioral phenotype (Lambert et al., 2015).
Although problem behavior and psychosocial
strengths, as defined by Epstein and Sharma
(1998), have not been simultaneously addressed
yet in DS, a few studies examining the behavioral
phenotype in DS can give an indication of their
co-occurrence (Di Nuovo & Buono, 2011;
Rosner, Hodapp, Fidler, Sagun, & Dykens,
2004). Jacola, Hickey, Howe, Esbensen, and Shear
(2014) showed, for example, that problem behav-
ior and adaptive skills are low to moderately
correlated in youngsters with DS. The variance
shared between both indicators of adjustment was
modest (i.e., 620%), suggesting that both
variables cannot be simply equated to each other.
These results raise the question whether, in
addition to behavioral profiles characterized by
the presence of strengths and the absence of
problems (or vice versa), some children with DS
display a combination of problems and strengths
or, conversely, whether some children display
neither strengths nor problems.
The Present Study
The overall goal of this study was hence to obtain
a more balanced and comprehensive view on the
behavioral phenotype of youth with DS.
As a first aim, we described the degree and
nature of problem behaviors and psychosocial
strengths, as defined by Epstein and Sharma
(1998), in youth with DS. In addition, this study
also aimed to relate the problems and strengths of
children with DS to children’s gender, as well as
both chronological age (CA) and developmental
age (DA). Research on the role of gender has
yielded inconclusive findings. Some studies sug-
gested that boys with DS exhibit more external-
izing problems, such as aggressive behavior, than
girls (van Gameren-Oosterom et al., 2013), where-
as other studies did not report this gender
difference (Dykens & Kasari, 1997; Rice et al.,
2015). Studies on strengths in youth with DS
generally do not report systematic gender differ-
ences (Dykens et al., 2006; Jacola et al., 2014). The
impact of CA on the behavioral phenotype in DS
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
L. M. Dieleman et al. 213
has been repeatedly documented in the literature,
as several studies suggest that externalizing prob-
lems in children with DS increase during child-
hood and decline throughout adolescence,
whereas internalizing problems increase from
middle childhood to adolescence (Dykens, Shah,
Sagun, Beck, & King, 2002; Rice et al., 2015).
Strengths are reported to increase during early
childhood (Dykens et al., 2006; Hauser-Cram et
al., 1999). However, from middle childhood
onwards, these strengths appear to be no longer
correlated with age, suggesting that there might be
a plateau in development or, alternatively, that
various developmental pathways may emerge
(Dressler et al., 2010; Dykens et al., 2006). Several
studies have also indicated DA as an important
determinant of the behavioral phenotype in DS,
suggesting that problem behavior decreases as DA
increases (Di Nuovo & Buono, 2011; Evans &
Gray, 2000), and some studies suggested that
strengths might grow with increasing DA (Marchal
et al., 2016).
As a second aim, we examined the interrela-
tions between problem behaviors and psychosocial
strengths in a DS population. In order to explore
whether the problem and strength scales represent
distinct constructs, we used a confirmatory factor
analysis (CFA). If the problem and strength scales
represent opposite constructs, the variables will be
represented by a single factor or by two highly
(negatively) correlated factors. However, based on
the reviewed literature, we expected that the CFA
would result in a model that identifies strengths
and problems as distinct constructs.
Although the descriptive analysis and the
CFA give an indication of how the constructs
are generally related, they do not inform us about
the specific profiles of children with DS. Although
problems and strengths might be moderately
negatively correlated, this does not indicate that
all children exhibit high levels of problems and
low levels of strengths or vice versa. Therefore, our
third aim was to evaluate naturally occurring
profiles, i.e. combinations of behavioral problems
and psychosocial strengths, in DS by using a
cluster analysis. If problems and strengths are
almost opposite constructs, we expected to find
only two profiles: (1) children with high levels of
problems and low levels of strengths, and (2)
children with a lot of strengths and few problems.
In contrast, if the problems and strengths
constructs yield unique information, we expected
to find differentiated profiles containing different
combinations of problems and strengths. Further-
more, we examined whether the retained profiles
differ significantly concerning their gender distri-
bution, CA, and DA.
Participants and Procedure
Parents were invited to participate in a study on
the development of children with DS by
distributing invitations to the most important
parent associations for DS in Flanders (Belgium)
and the Netherlands, and through personal
contacts with training centers, schools, and
guidance services. Families had to meet the
following inclusion criteria: the child (1) had
received a formal diagnosis of Down syndrome
and (2) was at least 4 years old. Parents whose
children were older than 20 years were excluded
from this study (n¼2).Originally,84parentsof
children with DS participated, but 17 partici-
pants were excluded because of missing data. The
final community-based sample consisted of 67
parents of children (37 boys and 30 girls) with DS
aged between 4 and 19 years old (M¼9.5, SD ¼
3.92). There were no significant differences
between the group that was excluded based on
missing data (n¼17) and the included group (n¼
67) in terms of demographic characteristics such
as nationality of child (v
[3] ¼.95, p¼.81), type
of education of the child (v
[7] ¼5.63, p¼.58),
CA of the child, DA of the child, and parental
age (ANOVA, all p..05).
Mothers’ average age was 40.4 years (SD ¼
11.92) and fathers were on average 45.1 years old
(SD ¼5.7). Questionnaires were rated primarily by
the mother (79.1%) and in some instances by the
father (16.4%) or a foster parent (4.5%). Based on
personal preference, parents could fill out either
an online (86.6%) or paper version (13.4%) of the
questionnaire. There were no differences between
the two administration methods in terms of
demographic characteristics, behavioral problems,
psychosocial strengths, and frequency of missing
data. Some parents didn’t complete all question-
naires, resulting in varying sample sizes across
questionnaires (Table 1). More demographic
characteristics of the sample are summarized in
Table 1.
Developmental age. In order to examine the
impact of DA, parents rated the Vineland Screener
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
214 Problems and Strengths in DS
0–6 (Scholte, van Duijn, Dijkxhoorn, Noens, &
van Berckelaer-Onnes, 2008). The Vineland
screener 0–6 measures adaptive behaviors in the
domains of communication, daily living skills,
socialization, and motor skills and gives an
estimate of the DA (see Table 1).
Emotional and behavioral problems. Parents
child on the Child Behavior Checklist/4-18
(CBCL; Achenbach, 1991). The CBCL includes
eight syndrome scales: Withdrawn/Depressed
Behavior, Somatic Complaints, Anxious/De-
pressed Behavior, Social Problems, Thought
Problems, Attention Problems, Delinquent Be-
havior, and Aggressive Behavior. The first three
scales produce the Internalizing Problem factor
and the last two scales create the Externalizing
Problem factor. The sum of all syndrome scales
forms the Total Problems scale. Although the
CBCL was originally developed for typically
developing children, previous studies indicated
it as a suitable instrument to examine problem
behaviors in children with intellectual disability
(Koskentausta, Iivanainen, & Almqvist, 2004) and
children with DS (Dekker et al., 2002; Dykens &
Table 1
Demographics (n¼67)
Years (SD)or%
Mother 79.1
Father 16.4
Foster parent 4.5
Mother 40.4 (11.92)
Father 45.10 (5.70)
CA Child with DS 9.50 (3.92)
DA Child with DS 3.57 (1.06)
Marital status informant
Married 79
Co-habiting 12
Highest educational level parents (mother/father)
Unknown 12/16
Nationality child
Belgian 63
Dutch 34
Other 3
Type of education child
Special education
(Type 1
, Type 2
, Type 3
64 (7, 54, 2)
Regular education 33
Other/Unknown 3
Comorbidities child
Language disorder 22
Autism spectrum
disorder or
Motor disability 13
Other 7
(Table 1 continued)
Table 1
Years (SD)or%
Number of children in family
1 16.4
2 38.8
3 26.9
4 9.0
5 6.0
.5 3.0
Participants per questionnaire
Vineland Screener 97
Child Behavior Checklist 95
Behavioral and
Emotional Rating Scale
Note.CA¼chronological age, DA ¼developmental age,
DS ¼Down syndrome.
Type 1:education for children with a mild intellectual
Type 2: education for children with a moderate or severe
intellectual disability.
Type 3:education for children with severe emotional and/
or behavioral problems.
Parent-report, parents could indicate more than one
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
L. M. Dieleman et al. 215
Kasari, 1997; van Gameren-Oosterom et al.,
2011). In order to evaluate the level of emotional
and behavioral problems, raw scores were con-
verted into T-scores and classified as clinical
versus nonclinical on the basis of Dutch popu-
lation-based norms (Verhulst, Van der Ende, &
Koot, 1996).
Psychosocial strengths. Parents rated their
child’s psychosocial strengths on the Behavioral
and Emotional Rating Scale (BERS-2, Epstein,
2004). This questionnaire identifies positive emo-
tions, behaviors, and life aspects of an individual
by measuring five types of psychosocial strengths.
The Interpersonal Strength scale assesses the
ability of a child to adapt his or her emotions
and behavior to social situations (e.g., accepts
criticism). The Family Involvement scale assesses
the relationship of the child with his or her family
(e.g., participates in family activities). The Intra-
personal Strength scale measures the child’s
confidence and positive attitude (e.g., identifies
personal strengths). The School Functioning scale
measures the child’s academic performance and
skills (e.g., completes homework regularly). Final-
ly, the Affective Strength scale measures the extent
to which children can express and receive affection
(e.g., accepts the closeness and intimacy of others).
The questionnaire is well-validated in clinical and
nonclinical groups (Buckley, Ryser, Reid, &
Epstein, 2006; Epstein, 2004). The BERS-2 was
developed to be broadly applicable (in children
with and without disabilities) and, recently,
scholars have successfully used this questionnaire
in work with children with disabilities (Ren, 2010;
Sointu, Savolainen, Lappalainen, & Epstein,
2012). To evaluate the level of strengths, scores
were classified into groups based on the available
norms of a representative school population
(including mainly typically developing children
and a small percentage of children with disabili-
ties; Epstein 2004).
Plan of Analyses
First, we conducted descriptive analysis using
SPSS Statistics 21. Internal consistencies of the
scales were examined with Cronbach’s alpha (a).
with Multivariate Analysis of Covariance (MAN-
COVA). The internal reliability (a)oftheVine-
land screener in this study ranged from .77
(motor skills) to .95 (communication skills).
Second, we examine the interrelations between
problem behaviors and psychosocial strengths by
conducting a CFA including three latent factors for
problem behaviors (Externalizing factor indicated
by the subscales Aggressive and Delinquent Behav-
ior; Internalizing factor represented by the subscales
Anxious and Withdrawn Symptoms; and Cogni-
tive and Social factor indicated by the subscales
Thought, Attention, and Social Problems) and a
latent factor for strengths (indicated by the
Interpersonal, Intrapersonal, Affective, and Familial
strengths). The CFA was conducted with Mplus7.3
en & Muth´
en, 1998-2012). As missing data
were missing completely at random (MCAR) for
the included variables (Little’s MCAR test: v2(8)¼
12.39, p¼.14), full information maximum
likelihood was used. The model fit was evaluated
with the ratio of chi-square/degrees of freedom
(CMIN/DF), comparative fit index (CFI), root
mean square error of approximation (RMSEA), and
standardized root mean square residual (SRMR). A
good model fit is indicated by a CMIN/DF around
2 or lower, a CFI value of .95 or higher, a RMSEA
value of .08, and a SRMR value of .08 or lower (Hu
& Bentler, 1999; Kline, 2010).
Third, a cluster analysis was performed to
evaluate naturally occurring profiles (i.e., combi-
nations of behavioral problems and psychosocial
strengths). Cluster analysis was conducted with
SPSS Statistics 21. Prior to analysis, univariate and
multivariate outliers were identified. Seven indi-
viduals were excluded because they had a score
that (a) was more than 3 SD above or below the
mean and/or (b) had a Mahalanobis distance
higher than 10. For the cluster analysis we
followed a two-step procedure as recommended
by Gore (2000). First, Ward’s hierarchical cluster-
ing procedure was conducted. Only cluster
solutions explaining a minimum 50% of the
variance in the included variables were considered
for further analysis (Milligan & Cooper, 1985). In
a second step, nonhierarchical k-means clustering
was applied on the previously retained cluster
solution, resulting in an optimized cluster solu-
tion. The iterative procedure of the nonhierarchi-
cal k-means clustering allows, in contrast to the
hierarchical analysis, to reassign objects to better
fitting clusters through subsequent stages by
minimizing within-cluster variability and maxi-
mizing between-cluster variability. In order to test
the replicability of the obtained cluster solution
with nclusters, we conducted tests of omission in
which one cluster was left out and the remaining
participants were re-clustered into a cluster solu-
tion with n-1 clusters. Finally, ANOVA analyses
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
216 Problems and Strengths in DS
were conducted in order to examine whether
profiles differ significantly concerning their CA
and DA. Gender distribution across profiles was
examined using a Fisher’s exact test.
Aim 1: Describing Emotional-Behavioral
Problems and Psychosocial Strengths in
Table 2 shows the internal consistencies, mean
scores, and the percentage of clinical scores for
the CBCL scales and problem factors. The
internal consistencies of the subscales ranged
from .61 (social problems) to .88 (aggressive
behavior). Only the subscale somatic complaints
showed insufficient reliability (a¼.37), possibly
due to low variance. Therefore, the somatic
complaint scale was omitted in the CFA and
cluster analyses, while preserved in the descriptive
analyses (Table 2). Highest percentages of clinical
scores were found for social problems (25%),
followed by attention problems (20.3%) and
thought problems (18.8%). There were no
children who scored in the clinical range for
anxious/depressed behavior. In order to examine
the relative impact of gender and age (both CA
and DA), we conducted a MANCOVA with
gender as fixed factor, CA and DA as covariates,
and all CBCL-subscales as dependent variables.
Results showed that gender and DA did not affect
the problem behaviors (F[8,51] ¼.96 p¼.48 and
F[8,51] ¼2.02, p¼.06, respectively). CA,
however, did (F[8,51] ¼2.44 p,.05): older
children showed more anxious/depressed behav-
ior (F[1,58] ¼9.23, p.01) and withdrawn /
depressed behavior (F[1,58] ¼7.21, p.01) than
younger children.
Table 3 shows the internal consistencies,
means, and group classifications of the psychoso-
cial strengths. Internal consistency was good to
excellent for all scales, except for School Func-
tioning (a¼.65). Based on this lower reliability
and an item-level analysis, which indicated that
more than 50% of the data was missing for five
items of this scale, we decided to exclude the
School Functioning scale in further analyses. In
comparison with the norms provided by Epstein
(2004), the majority of children with DS tended to
exhibit an average amount of strengths. At the
same time, there was much interindividual varia-
tion in the strengths. The children showed most
strengths in the areas of family involvement and
affection; interpersonal strengths were rated mod-
erately, and intrapersonal strengths were consid-
ered as rather limited. A MANCOVA showed that
gender was unrelated to the strengths (F[4,56] ¼
.54, p¼.71), while both CA and DA significantly
related to the strengths (F[4,56] ¼2.80, p.05
and F[4,56] ¼11.02, p.001, respectively). Older
children scored lower on intrapersonal and
affective strengths (F[1,59] ¼7.65, p.01 and
F[1,59] ¼6.13, p.05) than younger children.
Parents reported more interpersonal (F[1,59] ¼
25.18, p.001), intrapersonal (F[1,59] ¼41.30, p
.001), affective (F[1,59] ¼24.24, p.001), and
familial (F[1,59] ¼25.56, p.001) strengths for
children with higher DAs.
Aim 2: How Are Emotional-Behavioral
Problems and Psychosocial Strengths
Interrelated in DS?
Correlations between problems and strengths
scales (Table 4) were negative but low to moderate
in terms of effect size (rs ranging from .12 to
.51). Social problems, thought problems, and
attention problems showed the strongest correla-
tions with all the strengths (rs ranging from .28 to
.51), whereas anxious/depressive behavior only
related significantly with affective strengths (.27).
In order to examine the distinction between
problems and strengths more formally, a CFA
with four latent factors for Externalizing Problems,
Internalizing Problems, Cognitive and Social
Problems, and Psychosocial Strengths was con-
ducted. This model (Figure 1) yielded a good fit
with CMIN/DF ¼1.51, CFI ¼.96, RMSEA ¼.09
and SRMR ¼.06. All indicators had strong,
significant loadings on the presupposed latent
factors. Psychosocial strengths were highly nega-
tively correlated with both the Externalizing
Problem factor (r¼.52) and the Cognitive and
Social Problem factor (r¼.63), whereas the
correlation with the Internalizing Problem factor
was moderately negative (r¼.30).
Aim 3: Evaluating Profiles of Emotional-
Behavioral Problems and Psychosocial
Strengths in DS
To conduct cluster analysis, we created four
composite variables by summing the identifying
scales (e.g., the variable Externalizing Problems
consisted of the Delinquent and Aggressive
Problem scale) after these scales had been
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
L. M. Dieleman et al. 217
standardized. By standardizing variables, differ-
ences in variability in the scales do not impact on
the cluster classification. Using Ward’s hierarchical
clustering procedure, cluster solutions with two to
six clusters were extracted and examined. The
solutions with two and three clusters explained less
than 50% of variance of one of the defining
variables and were not further considered. The
four-cluster solution was selected for nonhierar-
chical k-means clustering, as this solution account-
ed for 66%, 58%, 66%, and 68% of the variance in
Psychosocial Strengths, Internalizing Problems,
Externalizing Problems, and Cognitive and Social
Problems, respectively. The solutions with five or
six clusters explained similar amounts of variances
but the retained clusters solutions did not
Table 3
Strengths, Measured With BERS, in Children With DS (n¼63)
Scaled scores Comparison with the norms in %
average Average
average High
Interpersonal strength .92 8.06 2.57 17.5 15.9 60.3 6.3 0
Family involvement .85 10.08 2.80 9.5 9.5 57.1 20.6 3.2
Intrapersonal strength .86 7.79 2.82 19 30.2 42.9 7.9 0
Affective strength .81 9.89 2.7 4.8 20.6 55.6 15.9 3.2
School functioning .65 7.87 3.04 23.8 27.0 39.7 7.9 1.6
Note. BERS ¼Behavioral and Emotional Rating Scale; DS ¼Down syndrome; M: mean scaled scores (higher scores
represent more strengths), SD: standard deviations
Scaled scores are allocated into different groups based upon the available norms form a representative school-population
(Epstein, 2004). Scaled scores below 6 are categorized as ‘‘Low.’’ Scores from 6 to 7 are categorized as ‘‘ Below average.’’
Scaled scores from 8 to 12 are considered ‘‘Average.’’ Scaled scores from 13 to 14 refer to the category ‘‘ Above average.’’
Scaled scores from 15 to 16 are considered ‘‘High.’’
Table 2
Emotional and Behavioral Problems, Measured With the CBCL, in Children With DS (n¼64)
consistencies Raw scale scores Clinical scores
aMSD %
Anxious/Depressed .75 1.53 2.20 0.0
Withdrawn/Depressed .76 2.67 2.72 9.4
Somatic complaints .37 1.31 1.42 3.1
Social problems .61 4.28 2.35 25.0
Thought problems .84 1.67 2.60 18.8
Attention problems .76 6.78 3.61 20.3
Delinquent behavior .67 1.77 2.16 10.9
Aggressive behavior .88 8.17 6.27 6.3
Internalizing problem factor .83 5.39 5.07 10.9
Externalizing problem factor .89 9.94 7.71 21.9
Total problem factor .95 33.89 21.64 34.4
Note. CBCL ¼Child Behavior Checklist/4-18; DS ¼Down syndrome; M¼mean scores (higher scores indicate more
problems); SD ¼standard deviations.
Clinical scores are calculated by converting raw scale scores into T-scores on the basis of Dutch population-based norms
(Verhulst et al., 1996). Next, for the broad band factors, T-scores 63 were classified as clinical scores. For the small band
subscales, T-scores 70 were classified as clinical scores.
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
218 Problems and Strengths in DS
qualitatively differ from the four-cluster solution.
The optimized cluster solution is presented in
Figure 2. In this figure, z-scores, indicating the
relative differences between the cluster means and
the total sample mean, are presented. The first
cluster (n¼8) represented children with a very low
level of Psychosocial Strengths (z¼1.39) and
high levels of Internalizing Problems (z¼.59),
Externalizing Problems (z¼1.06) and Cognitive
and Social Problems (z¼.97). Because these
children exhibited the most maladaptive profile,
this cluster was labeled as ‘‘low strengths and high
overall problems.’’ The second cluster consisted of
children (n¼29) exhibiting a moderate level of
Psychosocial Strengths (z¼.29) and low levels of
Problem Behavior (z¼.55 for Internalizing
Problems, z¼.79 for Externalizing Problems,
and z¼.62 for Cognitive and Social Problems).
This cluster was labeled as ‘‘modest strengths and
low overall problems.’’ The third cluster consisted
of children (n¼13) with a relatively high amount
of strengths (z¼.55), relatively low levels of both
Internalizing Problems (z¼.45) and Cognitive
and Social Problems (z¼.20), and moderate
levels of Externalizing Problems (z¼.30). This
cluster was labeled as ‘‘moderate strengths and
externalizing problems.’’ The fourth cluster repre-
sented children (n¼3) with high levels of both
Strengths (z¼.85) and Internalizing Problems (z¼
.76), relatively high levels of Cognitive and Social
Problems (z¼.52), and moderate levels of
Externalizing Problems (z¼
.08). This cluster
was labeled as ‘‘high strengths and internalizing,
cognitive and social problems.’’ The optimized
solution accounted for 66%, 58%, 70%, and 65%
of the variance in Strengths, Internalizing Prob-
lems, Externalizing Problems, and Cognitive and
Social Problems.
To test the replicability of the obtained
solution, four tests of omission were conducted.
The overlap of the four new cluster solutions with
the original solution was high (i.e., only three
participants were clustered differently), indicating
that the obtained cluster solution was stable.
In Table 5, mean scores for the different
subscales per cluster are presented. ANOVA
analyses were conducted to examine differences
between the four clusters. Clusters differed most
strongly on the domain of aggressive behavior (g
¼.67), with children from Cluster 1 and Cluster 3
exhibiting the highest levels of aggression. Next,
clusters differed strongly on the amount of
attention problems (g
¼.60). Again, children
from Cluster 1 exhibited the most problems.
Delinquent behavior and social problems, on the
other hand, show the lowest differences across
clusters (g
¼.30 and g
¼.37, respectively). When
looking at the psychosocial strengths, interperson-
al strengths differed most strongly across the
clusters (g
¼.56), with children from Cluster 1
Table 4
Correlations Between Emotional and Behavioral Problems and Psychosocial Strengths
Variable 1 2 3 4 5 6 7 8 9 10
Problem scales
1. Anxious/Depressed
2. Withdrawn/Depressed .69
3. Social problems .38
4. Thought problems .63
5. Attention problems .50
6. Delinquent behavior .62
7. Aggressive behavior .39
Strength scales
8. Interpersonal strength .12 .27
9. Family involvement .12 .27
10. Intrapersonal strength .12 .30
.25 .73
11. Affective strength .27
Note. Correlations in bold remain significant when corrected for multiple comparisons (Bonferroni correction), p,.00091.
*p ,.05; **p ,.01; ***p ,.001.
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
L. M. Dieleman et al. 219
scoring significantly lower than the children from
the other clusters.
Next, we evaluated the role of gender and CA
and DA. No significant differences were found
between the clusters in terms of gender distribu-
tion (Fisher’s exact test ¼3.38, p¼.34). ANOVA
analyses (Table 5) also indicated no significant
differences in CA between clusters. The clusters
Figure 1.Confirmatory factor analyses (CFA) of the included variables. Due to item overlap
correlations were allowed between thought problems and attention problems and between attention
problems and social problems.
Figure 2.Four-cluster solution based on z-scores for Psychosocial Strengths, Internalizing Problems,
Externalizing Problems, and Cognitive and Social Problems.
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
220 Problems and Strengths in DS
did differ significantly for DA, with children from
Cluster 1 having a significant lower DA than
children from the other clusters.
In recent years, calls have been made by
international organizations, such as the American
Association on Intellectual and Developmental
Disabilities, to devote more attention to the
strengths of children with disabilities, in order to
arrive at a more balanced view on their adjustment
and to support more tailor-made interventions.
Although the behavioral phenotype of children
with DS has been studied intensively, research on
strengths in children with DS primarily attended
to their adaptive skills (Dressler et al., 2010). The
focus on these conceptual, practical, and social
skills does give an indication of the ability of
children with DS to cope with requirements of
daily life, but does not offer a holistic view of the
children’s sources of well-being. Psychosocial
strengths, as defined by Epstein and Sharma
(1998), reflect broader emotional and behavioral
skills, competencies, and characteristics that pro-
mote well-being and development (Tedeschi &
Kilmer, 2005). These psychosocial strengths re-
main, until today, rather unexamined in children
with DS (with the exception of social competence
skills, Kasari et al., 2003). As a result, it also
remains unclear how strengths and behavioral
problems relate and co-occur in this population.
This study aimed to obtain a more balanced view
of children with DS by (1) describing both their
problems and strengths, (2) by examining their
interrelations, and (3) by evaluating profiles of
problems and strengths.
Emotional-Behavioral Problems and
Psychosocial Strengths in Youngsters
With DS
First, in line with previous research (van Gameren-
Oosterom et al., 2011; 2013), parents of children
with DS reported most clinically elevated prob-
lems in the social and attention domain. These
behavioral problems may be important to take
into account, for example, within the school
context. Teachers may try to avoid overstimulating
children with DS, for instance by having frequent
breaks to optimize their attention throughout the
day. Consistent with previous studies (e.g., Evans
& Gray, 2000), parents also reported high levels of
thought problems, indicating that children with
DS are at risk for developing obsessive or
Table 5
ANOVAs Indicating Differences Between Clusters
F(3,49) g
Chronological age (years) 8.76 3.26 9.65 3.92 7.84 3.14 13.51 4.34 2.15 .12
Developmental age (months) 32.38
10.28 44.66
11.61 49.46
8.55 54.33
6.66 5.33
Anxious/Depressed 2.13
1.35 .48
.87 .85
1.07 4.33
3.06 12.64
Withdrawn/Depressed 4.75
1.49 1.24
1.50 1.31
.95 3.33
1.16 15.63
Social problems 6.38
2.13 3.10
1.61 3.54
1.61 6.00
1.00 9.75
Thought problems 3.13
2.03 .41
.68 1.23
1.17 1.67
.58 13.22
Attention problems 10.63
2.67 4.52
1.33 6.46
2.33 9.00
2.65 24.10
Delinquent behavior 2.50
1.78 .52
.99 1.39
.96 2.00
1.73 7.14
Aggressive behavior 15.63
6.70 3.45
2.76 10.85
2.08 7.33
.58 33.06
Interpersonal strength 4.13
.99 8.86
1.66 9.08
1.66 10.00
2.65 20.54
Family involvement 6.25
1.39 10.73
2.12 11.62
1.81 12.00
2.65 14.22
Intrapersonal strength 5.25
1.39 8.03
2.21 9.69
2.14 10.00
3.00 7.96
Affective strength 6.88
1.46 10.38
2.24 11.54
2.11 11.33
2.31 8.67
Note. Due to unequal variances, the Games Howell post hoc test is reported for the subscales anxious, thought, attention
and aggressive behavior. All other tests report the LSD post hoc test. Different superscripts (a, b, c) refer to significant
differences between clusters.
**p,.01, ***p,.001.
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
L. M. Dieleman et al. 221
repetitive thoughts or behaviors. Also in line with
prior studies (Dykens & Kasari, 1997; van Game-
ren-Oosterom et al., 2011), parents reported low
levels of anxious/depressive behavior. Notably, we
found internalizing problems to be related with
CA, indicating that older children with DS exhibit
more anxious and withdrawn behavior than
younger children. In the literature, this phenom-
enon has been linked to the higher proneness for
depression, repeatedly reported in adults with DS
(Dykens, 2007). This phenomenon might also
reflect that the capacity to show internal distress
increases as children with DS grow older or,
alternatively, that parents become gradually more
skilled at detecting signals of internal distress.
In addition, this study supplements the
dominant focus on problems by also shedding
light on the psychosocial strengths of children
with DS. Interestingly, parents identified the most
strengths for family involvement and expressing/
receiving affect. This suggests that parents gener-
ally experience their interactions with the child as
positive, perceiving their child as having a real
sense of belonging to the family. Most parents also
indicate that their child effectively communicates
emotions and is very receptive for affection from
others. These findings are in line with previous
studies identifying social understanding/behavior
and empathy as the best developed skills of
children with DS (Di Nuovo & Buono, 2011;
Dykens et al., 2006; Kasari et al., 2003). One
intriguing question is how the moderate level of
interpersonal strengths (i.e., the ability to adapt to
social situations) can be aligned with the docu-
mented high prevalence of social problems. In this
regard, it is important to note that the CBCL-
social problems scale assesses personal preference
of the child and social acceptance by others,
whereas the BERS-interpersonal strengths subscale
focuses on actual behaviors during social interac-
tions. Thus, it appears that, despite experiencing
quite a number of social difficulties, children with
DS are well able to adjust their emotions and
behavior in more specific social situations (e.g.,
considering consequences of own behavior). Least
reported by parents were intrapersonal strengths,
indicating that children with DS experience less
behaviors such as being self-confident, expressing
a sense humor, and identifying own feelings.
Results further suggest that strengths of children
with DS improve as DA increases, indicating that
the acquisition of conceptual, practical, and social
skills fosters psychosocial strengths (or vice versa).
There was also a negative relation between CA and
intrapersonal and affective strengths. As the cross-
sectional design of this study precludes a thorough
examination of age effects, inquiring about the
developmental course of psychosocial strengths in
longitudinal research is highly warranted.
The Interrelation Between Emotional-
Behavioral Problems and Psychosocial
Strengths in Youngsters With DS
In line with previous studies in different (e.g.,
Lambert et al., 2015) and similar populations
(Jacola et al., 2014), the correlation analysis and
the CFA pointed towards the distinctiveness of
the concepts of behavioral problems and psycho-
social strengths in children with DS. The strong
negative relation between Cognitive and Social
Problems and Psychosocial Strengths suggests that
their co-occurrence is least likely. This is in line
with Jacola and colleagues (2014), who reported a
strong negative association between attention
problems and adaptive skills. The negative relation
between internalizing problems and strengths was,
on the other hand, rather moderate, suggesting
that they are more likely to co-occur.
Despite the moderate to strong correlations
between strengths and problems, the CFA did
support a four-factor model, identifying all four
indicators as separable constructs. This implies
that problems and strengths are not mutually
exclusive and that both encompass distinct and
valuable information about the behavioral pre-
sentation of a child with DS. Therefore, the next
step was to examine naturally occurring profiles
in this group.
Profiles of Emotional-Behavioral
Problems and Psychosocial Strengths in
Youngsters With DS
The cluster analysis identified four different
profiles of problems and strengths. Interestingly,
most children exhibited moderate to high levels
of strengths (in combination with different levels
and types of problems), whereas only a small
number of children (Cluster 1, n¼8) showed an
absence of strengths. This cluster (low strengths
and high overall problems) represents the most
maladaptive group of children with DS and is in
strong contrast with Cluster 2 (modest strengths
and low overall problems), the largest group of
children exhibiting strengths but no behavioral
problems. If psychosocial problems and strengths
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
222 Problems and Strengths in DS
would represent perfectly opposite constructs,
one would expect only these two profiles to
emerge. However, two other clusters (i.e., clusters
3 and 4) reveal children with more nuanced
combinations of problems and strengths. Cluster
4 is particularly interesting, because this cluster
represents children with DS who, in spite of
several problems (such as internalizing problems),
exhibit a high number of strengths.
A more in-depth examination of the problem
subscales indicated that the differences between
clusters concerning externalizing problems were
mostly driven by differences in aggressive behav-
iors. Clusters differed, in contrast, only little on
delinquent behavior. This might be related to the
lower levels of variance in delinquent behaviors.
This in-depth examination also indicated that,
even though children from different clusters
hardly differed on social problems (such as not
being liked by other children), children with DS
did differ strongly in their ability to adapt to
social situations (i.e., interpersonal strengths).The
finding that children with DS vary strongly in
their interpersonal strengths is in contrast with
the stereotypical idea that a child with DS is
charming and sociable (Gilmore, 2006; Gilmore,
Campbell, & Cuskelly, 2003). Although this
stereotypical idea has been shown to be inaccu-
rate, it still might impact the perception and
expectations of laymen and parents (Gilmore,
2006; Gilmore et al., 2003). Therefore, these
results stress the importance of an in-depth
assessment of both problems and strengths.
Cluster 1 is characterized by a lower DA,
compared to the other clusters, suggesting that the
DA of children with DS substantially determines
the behavioral phenotype. Stimulating conceptu-
al, practical, and social skills might thus promote
the development of psychosocial strengths or
decrease behavioral problems in children with
DS. However, it is also possible that the high
amount of problem behaviors and the absence of
strengths hinder this group from developing
adaptive skills, leading to a lower DA. To further
elucidate reciprocal relations between DA and the
behavioral profile of children with DS, future
research should use longitudinal designs.
In sum, the differentiated combinations of
problems and strengths in this study indicate that
the presence of emotional or behavioral problems
does not necessarily exclude the presence of
psychosocial strengths in children with DS (and
vice versa), appealing clinicians, researchers, and
caregivers to attend to both behavioral domains in
their practices.
Clinical Relevance
By focusing on the deficits of children with DS,
research and practice risk overlooking crucial keys
to support these children and their families. This
study stresses the importance of a more holistic
approach by including both problems and psy-
chosocial strengths in assessments of children with
DS. By assessing a child’s strengths, as well as his
or her problems, we do not only attain a more
comprehensive view on the child. The child and
his or her parents might also feel more empow-
ered, and a positive relationship between the child,
the parents, and the practitioner can be facilitated
(Tedeschi & Kilmer, 2005).
The current findings can also be integrated
into interventions for children with DS because
they might help (a) examining which children are
most at risk for a maladaptive development, (b)
uncovering sources of strengths upon which can
be built in interventions, and (c) identifying which
specific interventions are needed. In this regard,
the children with low levels of strengths in
addition to high levels of problems (Cluster 1)
appear to be most at-risk and, hence, might need
more intensive or longer support than other
children with DS. Interventions for these children
should target the diverse problem behaviors, while
simultaneously addressing the strengths. Practi-
tioners can, for example, try to foster family
involvement by searching for activities that are fun
and feasible for both the child with DS and the
other family members. These activities might, at
the same time, offer opportunities to deal with
problem behaviors, such as aggression. Tailor-
made interventions for children from Cluster 4
could, on the other hand, focus more on applying
strengths in order to overcome the internalizing
problems. Because these children exhibit higher
levels of interpersonal and affective strengths, it
might be interesting to work on communicating
and interpreting signals of internal distress.
Similarly, interventions for children from clusters
2 and 3 can be tailored towards their specific
profiles by focusing on fostering specific domains
of strengths. Yet, as these profiles are based on
group patterns, it remains crucial to also address
one individual’s specific profile in order to tailor a
person-based support and intervention plan.
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
L. M. Dieleman et al. 223
Limitations and Future Directions
To the best of our knowledge, this study is among
the first to derive profiles of problems and
strengths in children with DS. Therefore, future
research is needed to replicate these profiles and to
gain insight in their developmental antecedents.
For instance, research could examine whether and
how profiles are related to different parenting
behavior and to temperamental characteristics of
the child. Research is also needed to examine the
developmental pathways of these profiles.
Some limitations must be acknowledged. First,
the generalizability of the present findings is limited
by the small sample size, the convenience sampling
method, and the use of parents as single infor-
mants. Another important issue relates to the
selected instruments. Both the CBCL (Achenbach,
1991) and BERS-2 (Epstein, 2004) were originally
developed for the general population and might
not be specific or sensitive enough to capture all the
problems and strengths of children with DS. Some
scholars noted that the CBCL (Achenbach, 1991)
may underestimate behavioral problems in children
with intellectual disability (ID) because (1) prob-
lems that are typical for these children might not be
assessed, and (2) children with ID might express
these problems differently (Koskentausta et al.,
2004). Yet, multiple studies have now shown that
the CBCL is a suitable instrument to use in
children with DS (e.g., Dekker et al., 2002) and
more heterogeneous ID (e.g., Borthwick-Duffy,
Lane, & Widaman, 1997). Previous research also
found the BERS-2 (Epstein, 2004) adequate to
assess psychosocial strengths in children with
heterogeneous disabilities (e.g., Ren, 2010). Choos-
ing these instruments in this study enabled the
comparison to comparable studies with the CBCL
(e.g., van Gameren-Oosterom et al., 2011; 2013)
and BERS-2 (e.g., Jacola et al., 2014). Moreover,
our study suggests that the BERS-2 (Epstein, 2004)
is a promising instrument to identify strengths in
youth with DS. Only the School Functioning scale
proved less useful in this sample, as five items were
less than 50% endorsed by parents, presumably
because the items entailed school-specific goals not
validated by children with DS. Thus, more research
addressing the validity of all the BERS-2 scales in a
DS population is needed. A final limitation is the
cross-sectional design of the current study, which
impedes the inference of causal relations. Future
research using longitudinal designs is highly
recommended to reveal the developmental path-
ways of behavioral problems and strengths in DS
and understand their long-term interrelations.
This study contributes to research about the
behavioral phenotype of children with DS by (1)
describing their most prevalent problems and
strengths, (2) examining the interrelations between
behavioral problems and psychosocial strengths, and
(3) by describing four different profiles of problems
and strengths. These findings emphasize the impor-
tance of assessing psychosocial strengths in addition
to behavioral problems and provide suggestions to
integrate both concepts in interventions.
Achenbach, T. M. (1991). Manual for the Child
Behavior Checklist/4-18 and 1991 profile. Bur-
lington, VT: University of Vermont, Depart-
ment of Psychiatry.
American Association on Intellectual and Develop-
mental Disabilities. (2010). Intellectual disability:
Definition, classification, and systems of support.
Washington, DC: American Association on
Intellectual and Developmental Disabilities.
Borthwick-Duffy, S. A., Lane, K. L., & Widaman,
K. F. (1997). Measuring problem behaviors in
children with mental retardation: Dimensions
and predictors. Research in Developmental
Disabilities, 18(6),415–433. http://dx.doi.
Buckley, J. A., Ryser, G., Reid, R., & Epstein, M. H.
(2006). Confirmatory factor analysis of the
Behavioral and Emotional Rating Scale-2
(BERS-2) Parent and Youth Rating Scales.
Journal of Child and Family Studies,15(1),27–37.
Buntinx, W. H. E., & Schalock, R. L. (2010).
Models of disability, quality of life, and
individualized supports: Implications for pro-
fessional practice in intellectual disability.
Journal of Policy and Practice in Intellectual
Disabilities, 7(4),283–294. http://dx.doi.
Chapman, R. S., & Hesketh, L. J. (2000).
Behavioral phenotype of individuals with
Down syndrome. Mental Retardation and
Developmental Disabilities, 6(2),84–95. http://
Dekker, M. C., Koot, H. M., van der Ende, J., &
Verhulst, F. C. (2002). Emotional and behav-
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
224 Problems and Strengths in DS
ioral problems in children and adolescents
with and without intellectual disability. Jour-
nal of Child Psychology and Psychiatry, 43(8),
Di Nuovo, S., & Buono, S. (2011). Behavioral
phenotypes of genetic syndromes with intel-
lectual disability: Comparison of adaptive
profiles. Psychiatry Research, 189(3),440–445.
Dressler, A., Perelli, V., Feucht, M., & Bargagna, S.
(2010). Adaptive behaviour in Down syn-
drome: a cross-sectional study from child-
hood to adulthood. Wiener Klinische
Wochenschrift, 122(2324),673–680. http://
Dykens, E. M. (2007). Psychiatric and behavioral
disorders in persons with Down Syndrome.
Mental Retardation and Developmental Disabili-
ties Research Reviews, 13(3),272–278. http://
Dykens, E. M., Hodapp R. M., & Evans D. W.
(2006). Profiles and development of adaptive
behavior in children with Down-Syndrome.
Down Syndrome Research and Practice, 9(3),45–
Dykens, E. M., & Kasari, C. (1997). Maladaptive
behavior in children with Prader-Willi Syn-
drome, Down Syndrome, and nonspecific
mental retardation. American Journal of Mental
Retardation, 102(3),228–237. http://dx.doi.
Dykens, E. M., Shah, B., Sagun, J., Beck, T., &
King, B. H. (2002). Maladaptive behaviour in
children and adolescents with Down’s syn-
drome. Journal of Intellectual Disability Research,
46, 484–492.
Epstein, M. H. (2004). Behavioral and Emotional
Rating Scale-2nd Edition: A strengths-based
approach to assessment. Austin, TX: PRO-ED.
Epstein, M. H., & Sharma, J. (1998). Behavioral
and Emotional Rating Scale: A strength-based
approach to assessment. Austin, TX: PRO-ED.
Evans, D. W., & Gray, L. (2000). Compulsive-like
behavior in individuals with Down syndrome:
Its relation to mental age, adaptive and
maladaptive behavior. Child Development,
Gilmore, L. (2006). Perceptions of Down syn-
drome in the Australian community. Journal of
Developmental Disabilities 12, 1–13.
Gilmore, L. A., Campbell, J., & Cuskelly, M.
(2003). Developmental expectations, person-
ality stereotypes, and attitudes towards inclu-
sive education: Community and teacher views
of Down syndrome. International Journal of
Disability, Development and Education 50(1),
Grieco, J., Pulsifer, M., Seligsohn, K., Skotko, B.,
& Schwartz, A. (2015). Down syndrome:
Cognitive and behavioural functioning across
the lifespan. American Journal of Medical
Genetics, 169(2),135–149. http://dx.doi.
Gore, P. A., Jr. (2000). Cluster analysis. In H. E. A.
Tinsley & S. D. Brown (Eds), Handbook of
applied multivariate statistics and mathematical
modelling (pp. 297–321). San Diego, CA:
Academic Press.
Hauser-Cram, P., Warfield, M. E., Shonkoff, J. P.,
Krauss, M. W., Upshur, C. C., & Sayer, A.
(1999). Family influences on adaptive devel-
opment in young children with Down syn-
drome. Child Development, 70(4),979–989.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for
fit indexes in coviarance structure analysis:
Conventional criteria versus new alternatives.
Structural Equation Modeling: A Multidisciplin-
ary Journal, 6, 1–55.
Jacola, L. M., Hickey, F., Howe, S. R., Esbensen,
A., & Shear, P. K. (2014). Behavior and
adaptive functioning in adolescents with
down syndrome: Specifying targets for inter-
vention. Journal of Mental Health Research in
Intellectual Disabilities, 7(4), 287–305. http://
Kasari, C., Freeman, S. F. N., & Bass, W. (2003).
Empathy and response to distress in children
with Down syndrome. Journal of Child
Psychology and Psychiatry and Allied Disciplines,
Kline, R. B. (2010). Principles and practice of
structural equation modeling (3th ed.). New
York, NY: The Guilford Press.
Koskentausta, T., Iivanainen, M., & Almqvist, F.
(2004). CBCL in the assessment of psychopa-
thology in Finnish children with intellectual
disability. Research in Developmental Disabilities,
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
L. M. Dieleman et al. 225
Lambert, M. C., January, S. A., Epstein, M. H.,
Spooner, M., Gebreselassie, T., & Stephens, R.
L. (2015). Convergent validity of the Behav-
ioral and Emotional Rating Scale for youth in
community mental health settings. Journal of
Child and Family Studies, 24(12),3827–3832.
Marchal, J. P., Maurice-Stam, H., Houtzager, B.
A., Rutgers van Rozenburg-Marres, S. L.,
Oostrom, K. J., Grootenhuis, M. A., & van
Trotsenburg, A. S. P. (2016). Growing up with
Down syndrome: Development from 6
months to 10.7 years. Research in Developmental
Disabilities, 59, 437–450.
Milligan, G. W., & Cooper, M. C. (1985). An
examination of procedures for determining
the number of clusters in a data set. Psychome-
trika, 50(2), 159–179.
en, L. K., & Muth´
en, B. O. (19982012).
Mplus user’s guide. 7th ed. Los Angeles, CA:
en & Muth´
Rashid, T., & Ostermann, R. F. (2009). Strength-
based assessment in clinical practice. Journal of
Clinical Psychology, 65(5), 488–498. http://dx.
Ren, L. (2010). Educational performance of foster
children with disabilities in Taiwan. Procedia
Social and Behavioral Sciences, 2(2),825–829.
Rice, L. J., Gray, K. M., Howlin, P., Taffe, J.,
Tonge, B. J., & Einfeld, S. L. (2015). The
developmental trajectory of disruptive behav-
ior in Down syndrome, Fragile X syndrome,
Prader–Willi syndrome and Williams syn-
drome. American Journal of Medical Genetics,
Rosner, B. A., Hodapp, R. M., Fidler, D. J., Sagun,
J. N., & Dykens, E. M. (2004). Social
competence in persons with Prader-Willi,
Williams and Down’s syndromes. Journal of
Applied Research in Intellectual Disabilities, 17(3),
Scholte, E. M., van Duijn, G., Dijkxhoorn, Y. M.,
Noens, I. L. J., & van Berckelaer-Onnes, I. A.
(2008). De Vineland Screener 0-6 jaar. Leiden,
Netherlands: Pits.
(2000). Positive psychology – An introduc-
tion. American Psychologist, 55(1),5–14. http://
Siegel, M. S., & Smith, W. E. (2011). Psychiatric
features in children with genetic syndromes:
Toward functional phenotypes. Pediatric Clin-
ics of North America, 58(4),833–865. http://
Sointu, E. T., Savolainen, H., Lappalainen, K., &
Epstein, M. H. (2012). Parent, teacher and
student cross informant agreement of behav-
ioral and emotional strengths: Students with
and without special education support. Journal
of Child and Family Studies, 21(4),682–690.
Tedeschi, R. G., & Kilmer, R. P. (2005). Assessing
strengths, resilience, and growth to guide
clinical interventions. Professional Psychology:
Research and Practice, 36(3),230–237. http://
van Gameren-Oosterom, H. B. M., Fekkes, M.,
Buitendijk, S. E., Mohangoo, A. D., Bruil, J.,
& Van Wouwe, J. P. (2011). Development,
problem behavior, and quality of life in a
population based sample of eight-year-old
children with Down Syndrome. PLoS ONE,
6(7), e21879.
van Gameren-Oosterom, H. B. M., Fekkes, M., Van
Wouwe, J. P., Detmar, S.B., Oudesluys-Mur-
phy, A.M., & Verkerk, P.H. (2013). Problem
behavior of individuals with Down syndrome
in a nationwide cohort assessed in late
adolescence. Journal of Pediatrics, 163(5),
Verhulst, F. C., Van der Ende, J., & Koot, H. M.
(1996). Manual of the CBCL/4-18 [In Dutch:
Handleiding voor de CBCL/4-18]. Rotterdam,
Netherlands: Afdeling Kinder- en jeugdpsy-
chiatrie Sophie Kinderziekenhuis/Academisch
Ziekenhuis Erasmus Universiteit.
Received 10/15/2016, accepted 6/26/2017.
This research was funded by grants from the
Marguerite-Marie Delacroix Support Fund (GV/B-
202) and the Fund for Scientific Research Flanders
(FWO; 12B4614N and 11X6516N). The authors
wish to thank all the participating families and the
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
226 Problems and Strengths in DS
organizations that contributed to this research. Special
thanks to Joke De Smet and Eliene Wils for their help
with the data collection.
Lisa M. Dieleman, Sarah S.W. De Pauw, Bart
Soenens, and Geert Van Hove, Ghent University,
Belgium; and Peter Prinzie, Erasmus University
Rotterdam, The Netherlands.
Correspondence concerning this article should be
addressed to Lisa M. Dieleman, Ghent University,
Department of Developmental, Personality and
Social Psychology, H. Dunantlaan 2, 9000, Ghent,
Belgium (e-mail:
2018, Vol. 123, No. 3, 212–227 DOI: 10.1352/1944-7558-123.3.212
L. M. Dieleman et al. 227
... Down syndrome is a chronic, complex condition with multiple comorbidities (23)(24)(25), with ID as a common denominator. Depending on the background of the authors, individuals with Down syndrome are reported to have a range of CDBs (26,27), but few researchers have investigated their natures and etiologies (26,28). Mimicking the coining decision-making in the community, we focused on reported and observed CDBs at home (29)(30)(31) and at school (32). ...
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Background Terms currently used to describe the so-called challenging and disruptive behaviors (CBDs) of children with intellectual disabilities (ID) have different connotations depending on guiding contextual frameworks, such as academic and cultural settings in which they are used. A non-judgmental approach, which does not attempt to establish existing categorical diagnoses, but which describes in a neutral way, is missing in the literature. Therefore, we tried to describe CDBs in youth with ID in an explorative study. Methods Interviews with families investigated the CDBs of five youth with Down syndrome. At home, families tracked youth's sleep/wake behaviors and physical activity. Youth were observed in a summer school classroom. The collected information and suggested explanatory models for observed CDBs were reviewed with the families. Results We grouped CDBs as challenging , if they were considered to be reactive or triggered, or unspecified , if no such explanatory model was available. A third category was created for light-hearted CDBs: goofy , acknowledging the right to laugh together with peers. We found some relationships between sleep, physical activity, and CDBs and developed an explorative approach, supporting a child-centered perspective on CDBs. Conclusion The controversial discussions on terminology and management of CDBs in the literature demonstrate the need for a non-judgmental approach. Such an explorative approach, allowing non-professionals to not label, has been missing. The fact that, up to now, the light-hearted behaviors of an individual with ID have not been integrated in commonly-used behavioral checklists as their natural right , proves our concept and indicates that a paradigm change from judgment-based to exploratory-driven approaches is needed.
... Studies have attempted to identify specific patterns of cognitive delay in DS, which often include, for example, a lower IQ (Daunhauer et al., 2014), challenges in maintaining attention and controlling impulses (Dieleman et al., 2018), yet strengths when it comes to empathy and social skills (Buckley, 2012). In general, therefore, individuals with DS appear to demonstrate a low level of cognitive abilities (Startin et al., 2020) with significant EF challenges and delays Tomaszewski et al., 2018). ...
... Behavioral problems can be observed in this population in various areas of functioning: feeding, sleep, toilet training, and socialization [36,37]. An assessment with the Child Behavior Checklist [38] revealed that some children and adolescents with DS aged 4-19 years had social attention problems and thought problems [39]. Stereotypies are frequent in DS, see a review in [40]; however, they are less severe than in ASD [19]. ...
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Background: Autism spectrum disorder (ASD) may coexist with Down syndrome (DS). Most studies on this topic involve school-age children, adolescents, or adults with DS. This study looked at ASD symptoms, other mental health problems, and challenging behaviors in toddlers with DS at low risk of ASD. Methods: We used screening tools for autism in toddlers; BISCUIT-Parts 1-3 and Q-CHAT. We compared four groups of children aged 17-37 months: DS, ASD, Atypical Development (AD), and Typically Developing (TD). Results: Children with DS showed lower symptoms of ASD than children with ASD (without DS) and higher than TD children, except for repetitive behaviors/restricted interests. For comorbid mental health problems and difficult behaviors, children with DS scored lower than children with ASD. There were no differences between children with DS and TD children in this regard. Conclusions: The study results indicate that BISCUIT-Parts 1-3 are valid instruments to differentiate toddlers with DS from toddlers with ASD. However, they also show that toddlers with DS at low ASD risk are a very heterogeneous group when the ASD symptoms are considered. Autistic characteristics should be taken into account in supporting young children with this genetic condition.
... Previous study findings have shown that children and adolescents with DS have an appropriate performance according to their developmental age in EF domains related to affection, visual processing, receptive language and social behavior (Di Nuovo and Buono, 2011;Dieleman et al., 2018;Fidler, 2005;Marchal et al., 2016). On the other hand, parents and teachers of children and adolescents with DS report a perception of underperformance in working memory and in domains like inhibition, shifting and attention (Amad o et al., 2016;Borella et al., 2013;Daunhauer and Fidler, 2011;Daunhauer et al., 2014;Daunhauer, Gerlach-McDonald, Will and Fidler, 2017;Esbensen et al., 2019;Lee et al., 2011). ...
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The study aim was to characterize executive function in 114 children with Down syndrome from a reference institution in Bogotá, Colombia. Children were screened with the Battelle Developmental Inventory to establish their developmental age. Eighty children with an equivalent mental age of 2–5.11 years were allocated to groups of 20 according to their mental age. Parents and teachers then completed the Behavior Rating Inventory of Executive Function-Preschool Version. We found a high variability and a low correlation between parent and teacher ratings. In general, children showed a specific profile characterized by weakness in the domains of working memory, shifting, planning, and organization, and strengths in the emotional control domain. These findings indicate a characteristic pattern of executive function in children with Down syndrome. This profile could form the basis for the planning of clinical assessment programs.
... The clinical picture of individuals with DS is often complicated by the presence of functional deficits, behavioral symptoms and nutritional and social problems, all of which have increased prevalence with age (4,5). Sociality and social interactions are important for individuals with DS, who identify family involvement and affection as main supporting pillars in life (6). Interestingly, individuals with DS tend to have higher global scores for social adaptive skills compared to adults with other intellectual disabilities (ID) (7). ...
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People with Down Syndrome (DS) have a high prevalence of physical and psychiatric comorbidities and experience early-onset dementia. With the outbreak of CoVID-19 pandemic, strict social isolation measures have been necessary to prevent the spreading of the disease. Effects of this lockdown period on behavior, mood and cognition in people with DS have not been assessed so far. In the present clinical study, we investigated the impact of CoVID-19-related lockdown on psychosocial, cognitive and functional well-being in a sample population of 46 adults with DS. The interRAI Intellectual Disability standardized assessment instrument, which includes measures of social withdrawal, functional impairment, aggressive behavior and depressive symptoms, was used to perform a three time-point evaluation (two pre-lockdown and one post-lockdown) in 37 subjects of the study sample, and a two time point evaluation (one pre- and one post-lockdown) in 9 subjects. Two mixed linear regression models – one before and one after the lockdown – have been fitted for each scale in order to investigate the change in the time-dependent variation of the scores. In the pre-lockdown period, significant worsening over time (i.e., per year) was found for the Depression Rating Scale score (β = 0.55; 95% CI 0.34; 0.76). In the post-lockdown period, a significant worsening in social withdrawal (β = 3.05, 95% CI 0.39; 5.70), instrumental activities of daily living (β = 1.13, 95% CI 0.08; 2.18) and depression rating (β = 1.65, 95% CI 0.33; 2.97) scales scores was observed, as was a significant improvement in aggressive behavior (β = −1.40, 95% CI −2.69; −0.10). Despite the undoubtful importance of the lockdown in order to reduce the spreading of the CoVID-19 pandemic, the related social isolation measures suggest an exacerbation of depressive symptoms and a worsening in functional status in a sample of adults with DS. At the opposite, aggressive behavior was reduced after the lockdown period. This finding could be related to the increase of negative and depressive symptoms in the study population. Studies with longer follow-up period are needed to assess persistence of these effects. © Copyright © 2020 Villani, Vetrano, Damiano, Paola, Ulgiati, Martin, Hirdes, Fratiglioni, Bernabei, Onder and Carfì.
... Person-oriented techniques, such as cluster analysis, may be more amenable to the study of within-condition variability, than are the previously described group-based approaches. This approach seeks to identify homogeneous subgroups of children who exhibit similar behavior problem or psychopathology profiles, and has been used to classify typically developing children (Kamphaus et al. 1999), as well as children with autism spectrum disorder (ASD) (Baeza-Velasco et al. 2014;Lecavalier 2006), intellectual disability (ID) (Brown et al. 2004;Curry and Thompson 1982;Painter et al. 2018), Down syndrome (Dieleman et al. 2018), and learning disabilities (McKinney and Speece 1986;Speece et al. 1985). For example, Brown et al. (2004) identified an 8-cluster solution using the Aberrant Behavior Checklist (ABC; Aman et al. 1985) among a diverse sample of 601 children, adolescents, and young adults (M = 13.2 years) with ID (44% Problem Free, 19% Within Normal Limits, 12% Shy/Inactive, 6% Conduct Problem, 6% Hyperactive, 6% Social Withdrawal With Agitation, 4% Undifferentiated Behavior Disturbance, and 3% Autistic-Like Behavior). ...
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Background: Given the significant behavioral heterogeneity characterizing children with neurodevelopmental disorders and disabilities (NDD/D), the current study examined whether cluster analysis could classify a diverse sample into more homogeneous subgroups. Aims: We first utilized cluster analysis to identify subgroups of children demonstrating similar behavior profiles. Second, we investigated the distribution of children’s primary diagnoses represented within each cluster. Finally, we compared the clinical utility of clusters versus diagnoses for indices of child and family health. Methods: Caregivers provided data for 222 children with NDD/D (M = 8.22 years), completing measures of child behavior and child and family health. Results: A 4-cluster solution was revealed: Social Difficulties, Cross-domain Difficulties, Hyperactive-inattentive, and Low difficulties, and a range of conditions was found within each. For all indices of child and family health, clusters explained greater variance than did diagnoses. Conclusions: The current study provides new insight into the heterogeneous nature of behavior among children with NDD/D. Considering a child’s unique constellation of strengths and difficulties may serve as a clinically meaningful supplement to diagnosis that more fully elucidates functional profile.
Behavioral aspects of organized sports activity for pediatric athletes are considered in a world consumed with winning at all costs. In the first part of this treatise, we deal with a number of themes faced by our children in their sports play. These concepts include the lure of sports, sports attrition, the mental health of pediatric athletes (i.e., effects of stress, anxiety, depression, suicide in athletes, ADHD and stimulants, coping with injuries, drug use, and eating disorders), violence in sports (i.e., concepts of the abused athlete including sexual abuse), dealing with supervisors (i.e., coaches, parents), peers, the talented athlete, early sports specialization and sports clubs. In the second part of this discussion, we cover ergolytic agents consumed by young athletes in attempts to win at all costs. Sports doping agents covered include anabolic steroids (anabolic-androgenic steroids or AAS), androstenedione, dehydroepiandrostenedione (DHEA), human growth hormone (hGH; also its human recombinant homologue: rhGH), clenbuterol, creatine, gamma hydroxybutyrate (GHB), amphetamines, caffeine and ephedrine. Also considered are blood doping that includes erythropoietin (EPO) and concepts of gene doping. In the last section of this discussion, we look at disabled pediatric athletes that include such concepts as athletes with spinal cord injuries (SCIs), myelomeningocele, cerebral palsy, wheelchair athletes, and amputee athletes; also covered are pediatric athletes with visual impairment, deafness, and those with intellectual disability including Down syndrome. In addition, concepts of autonomic dysreflexia, boosting and atlantoaxial instability are emphasized. We conclude that clinicians and society should protect our precious pediatric athletes who face many challenges in their involvement with organized sports in a world obsessed with winning. There is much we can do to help our young athletes find benefit from sports play while avoiding or blunting negative consequences of organized sport activities.
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There is a need for more knowledge of valid and standardized measures of mental health problems among children and adolescents with intellectual disability (ID). In this study, we systematically reviewed and evaluated the psychometric properties of instruments used to assess general mental health problems in this population. Following PRISMA guidelines, we reviewed empirical research published from 1980 through February 2020 with an updated search in March 2021 in Medline, Embase, PsycINFO, Health and Psychological Instruments, CINAHL, ERIC, and Web of Science databases. Forty-nine empirical articles were included in this review. Overall, the review indicated consistently better documentation of the reliability and validity of instruments designed for the ID population compared to instruments developed for the general child population.
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According to the World Health Organization (WHO), SARS-CoV-2 has infected approximately 17 million people worldwide, and almost 670,000 have died from complications of the disease (1). Hence, countries around the world have implemented social distancing measures to reduce the spread of the virus. Coronavirus coping strategies have profoundly changed social dynamics, given the adverse effects on people’s mental health (2) and their psychosocial impact (3). Due to higher morbidity and mortality (4, 5) and potential previous mental illnesses (6), the elderly population should be given more considerable attention, considering they must adhere more appropriately and for more extended periods to preventive measures (7). However, despite these studies, the psychiatric impact of COVID-19 on the elderly population still lacks more significant theoretical support, since few reports are describing psychiatric symptoms associated with the pandemic (5). Given the above, this paper is intended to illustrate and correlate the mental, psychiatric, and psychological consequences for the elderly during the COVID-19 pandemic.
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This nine-year longitudinal study addresses the joint contribution of parent-rated negative controlling parenting and child personality on psychosocial outcomes in 141 families of children with autism spectrum disorder (83% boys, mean age Time 1 = 10.1). Latent change modeling revealed substantial variation in within-person change in parenting and psychosocial outcomes across a six- and three-year-interval. Over time, negative controlling parenting and child personality were consistently related to externalizing problems, whereas child personality was differentially related to internalizing problems and psychosocial strengths. Three personality-by-parenting interactions were significant, suggesting that children with less mature personality traits show more externalizing behaviors in the presence of controlling parenting. This study identified both parenting and child personality as important modifiers of developmental outcomes in youth with autism.
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Background: Research suggests that adolescents with Down syndrome experience increased behavior problems as compared to age matched peers; however, few studies have examined how these problems relate to adaptive functioning. The primary aim of this study was to characterize behavior in a sample of adolescents with Down syndrome using two widely-used caregiver reports: the Behavioral Assessment System for Children, 2(nd) Edition (BASC-2) and Child Behavioral Checklist (CBCL). The clinical utility of the BASC-2 as a measure of behavior and adaptive functioning in adolescents with Down syndrome was also examined. Methods: Fifty-two adolescents with Down syndrome between the ages of 12 and 18 (24 males) completed the Peabody Picture Vocabulary Test, 4(th) Edition (PPVT-IV) as an estimate of cognitive ability. Caregivers completed the BASC-2 and the CBCL for each participant. Results: A significant proportion of the sample was reported to demonstrate behavior problems, particularly related to attention and social participation. The profile of adaptive function was variable, with caregivers most frequently rating impairment in skills related to activities of daily living and functional communication. Caregiver ratings did not differ by gender and were not related to age or estimated cognitive ability. Caregiver ratings of attention problems on the BASC-2 accounted for a significant proportion of variance in Activities of Daily Living (Adj R(2) = 0.30)(,) Leadership (Adj R(2) = 0.30) Functional Communication (Adj R(2) = 0.28, Adaptability (Adj R(2) = 0.29), and Social Skills (Adj R(2) = 0.17). Higher frequencies of symptoms related to social withdrawal added incremental predictive validity for Functional Communication, Leadership, and Social Skills. Convergent validity between the CBCL and BASC-2 was poor when compared with expectations based on the normative sample. Conclusion: Our results confirm and extend previous findings by describing relationships between specific behavior problems and targeted areas of adaptive function. Findings are novel in that they provide information about the clinical utility of the BASC-2 as a measure of behavior and adaptive skills in adolescents with Down syndrome. The improved specification of behavior and adaptive functioning will facilitate the design of targeted intervention, thus improving functional outcomes and overall quality of life for individuals with Down syndrome and their families.
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Traditionally, assessment of youths’ emotional and behavioral functioning within community mental health is conducted from a deficit-based approach, often excluding the measurement of strengths. Assessing youths’ emotional and behavioral strengths can provide a comprehensive understanding of youths’ functioning and better inform treatment planning. The Behavioral and Emotional Rating Scale-Second Edition (BERS-2) is a standardized, norm-referenced assessment of the behavioral and emotional strengths of youth ages 5–18. The psychometric properties of the BERS-2 scores are well established; however, most previous studies have focused on youth within school settings. As such, the purpose of the present study was to evaluate the convergent validity of the scores from the caregiver version of the BERS-2 with a large, diverse sample of youth referred for community mental health services. The correlation coefficients between the BERS-2 scores and scores from the Child Behavior Checklist and the Columbia Impairment Scale were moderate to large, and in the expected directions. Thus, findings support the convergent validity and use of the BERS-2 scores for youth receiving community mental health services.
Background We analysed developmental outcomes from a clinical trial early in life and its follow-up at 10.7 years in 123 children with Down syndrome. Aims To determine 1) strengths and weaknesses in adaptive functioning and motor skills at 10.7 years, and 2) prognostic value of early-life characteristics (early developmental outcomes, parental and child characteristics, and comorbidity) for later intelligence, adaptive functioning and motor skills. Methods and procedures We used standardized assessments of mental and motor development at ages 6, 12 and 24 months, and of intelligence, adaptive functioning and motor skills at 10.7 years. We compared strengths and weaknesses in adaptive functioning and motor skills by repeated-measures ANOVAs in the total group and in children scoring above-average versus below-average. The prognostic value of demographics, comorbidity and developmental outcomes was analysed by two-step regression. Outcomes and results Socialisation was a stronger adaptive skill than Communication followed by Daily Living. Aiming and catching was a stronger motor skill than Manual dexterity, followed by Balance. Above-average and below-average scoring children showed different profiles of strengths and weaknesses. Gender, (the absence or presence of) infantile spasms and particularly 24-month mental functioning predicted later intelligence and adaptive functioning. Motor skills, however, appeared to be less well predicted by early life characteristics. Conclusions and implications These findings provide a reference for expected developmental levels and strengths and weaknesses in Down syndrome.
Individuals with Down syndrome (DS) commonly possess unique neurocognitive and neurobehavioral profiles that emerge within specific developmental periods. These profiles are distinct relative to others with similar intellectual disability (ID) and reflect underlying neuroanatomic findings, providing support for a distinctive phenotypic profile. This review updates what is known about the cognitive and behavioral phenotypes associated with DS across the lifespan. In early childhood, mild deviations from neurotypically developing trajectories emerge. By school-age, delays become pronounced. Nonverbal skills remain on trajectory for mental age, whereas verbal deficits emerge and persist. Nonverbal learning and memory are strengths relative to verbal skills. Expressive language is delayed relative to comprehension. Aspects of language skills continue to develop throughout adolescence, although language skills remain compromised in adulthood. Deficits in attention/executive functions are present in childhood and become more pronounced with age. Characteristic features associated with DS (cheerful, social nature) are personality assets. Children are at a lower risk for psychopathology compared to other children with ID; families report lower levels of stress and a more positive outlook. In youth, externalizing behaviors may be problematic, whereas a shift toward internalizing behaviors emerges with maturity. Changes in emotional/behavioral functioning in adulthood are typically associated with neurodegeneration and individuals with DS are higher risk for dementia of the Alzheimer's type. Individuals with DS possess many unique strengths and weaknesses that should be appreciated as they develop across the lifespan. Awareness of this profile by professionals and caregivers can promote early detection and support cognitive and behavioral development. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
The aim of this study was to investigate the developmental trajectories of verbal aggression, physical aggression, and temper tantrums in four genetic syndrome groups. Participants were part of the Australian Child to Adult Development Study (ACAD), which collected information from a cohort of individuals with an intellectual disability at five time points over 18 years. Data were examined from a total of 248 people with one of the four following syndromes: Down syndrome, Fragile X syndrome, Prader-Willi syndrome, or Williams syndrome. Changes in behaviors were measured using validated items from the Developmental Behavior Checklist (DBC). The results indicate that, while verbal aggression shows no evidence of diminishing with age, physical aggression, and temper tantrums decline with age before 19 years for people with Down syndrome, Fragile X syndrome, and William syndrome; and after 19 years for people with Prader-Willi syndrome. These findings offer a somewhat more optimistic outlook for people with an intellectual disability than has previously been suggested. Research is needed to investigate the mechanisms predisposing people with PWS to persistence of temper tantrums and physical aggression into adulthood. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
To assess problem behavior in adolescents with Down syndrome and examine the association with sex and severity of intellectual disability. Cross-sectional data of a Dutch nationwide cohort of Down syndrome children aged 16-19 years were collected using a written parental questionnaire. Problem behavior was measured using the Child Behavior Checklist and compared with normative data. The degree of intellectual disability was determined using the Dutch Social competence rating scale. The response rate was 62.8% (322/513), and the mean age 18.3 years (SD ± 0.8). The total score for problem behavior was higher in adolescents with Down syndrome than in adolescents without Down syndrome (26.8 vs 16.5; P < .001). Overall, 51% of adolescents with Down syndrome had problem scores in the clinical or borderline range on 1 or more Child Behavior Checklist subscales; this is more than twice as high as adolescents without Down syndrome. Adolescents with Down syndrome had more internalizing problems than their counterparts without Down syndrome (14% and 9%, respectively, in the clinical range); the percentages for externalizing problems were almost equal (7% and 9%, respectively, in the clinical range). The highest problem scores in adolescents with Down syndrome were observed on the social problems and thought problems subscales (large to very large standardized differences). Male sex and/or more severe mental disabilities were associated with more behavioral problems. Serious problem behavior is more prevalent in adolescents with Down syndrome. This demonstrates the need for a focus on general behavior improvement and on the detection and treatment of specific psychopathology in individuals with Down syndrome.