Dutch Students in Special Education:
The Relationship Between Adverse Childhood Experiences (ACEs) and the Number of Provided Youth Services for Students with Emotional and Behavioral Disorders.
Master Thesis Forensic Child and Youth Care
Graduate School of Child Development and Education
University of Amsterdam
E. Sibbing, 10609016
Supervisors: Prof. Dr. G.J.J.M. Stams and E. Offerman, MSc.
Second Reviewer: I. Wissink, Ph.D.
Table of Contents Abstract 3 Introduction 4 Method 9 Participants 9 Procedure 10 Measures 11 Data-analysis Strategy 12 Results 13 Preliminary Analysis 13 Correlation Analysis 14 Discussion 14
Strengths and Limitations 17
Recommendations and Concluding Remarks 18
References 21
Abstract
Objective: The aim of this study was to investigate the relationship between Adverse
Childhood Experiences (ACEs) and the number of youth services among students with
Emotional and Behavioral Disorders (EBD). Method: This study included 102 students (M =
12.92, 83.3% male) from four primary (48%) and secondary (52%) schools for special
education in Amsterdam that belong to one organization for special education. The prevalence
of ACEs and youth services was established through analysis of school and youth service files.
Kendall’s tau was used to test the association between ACEs and the number of youth services.
Results: On average, students received 4.96 youth services and there was a weak, but
significant and positive association between ACEs and youth services. Implications: ACEs
among students with EBD are associated with more intensive treatment and repeated
breakdown of treatment, which is assumed to increase the number of youth services. General
practitioners and child youth care workers should recognize ACEs to enhance referral for
Introduction
More than half of the Dutch students who receive special education are provided with
additional youth services1 (jeugdhulp), a significantly higher number than among children in
regular education (Ministry of Public Health, Well-being, and Sports, 2017). This is not
surprising; a large part of students attending Dutch special education suffer from Emotional
and Behavioral Disorders (EBD) (CBS, 2020). Moreover, on average, students with EBD have
experienced more Adverse Childhood Experiences (ACEs) than students in regular education
(Verheggen, 2019; Vink, Van der Pal, Eekhout, Pannebakker, & Mulder, 2016). There has been
given little to no attention to this issue in research, even though it is known that experiencing
ACEs can have severe long-term negative effects, including physical, social, and behavioral
problems (Felliti et al., 1998).
A better understanding of the complexity and severity of problems faced by students with
EBD may offer a potential explanation for the number of provided youth services in special
needs students, given both the required intensity of treatments that target multiple problems at
the individual and contextual (e.g., family) level, and increased risk for failure and early or
repeated drop-out of treatment (e.g., Chasson, Vincent, & Harris, 2008). Therefore, this study
aims to answer the following question: “What is the relationship between Adverse Childhood
Experiences and the number of provided youth services of Dutch students with EBD?”.
Special education is intended for children and youth who face educational challenges. The
classrooms are smaller, which allows teachers to adapt and give attention to the special needs
of every individual student. Within the Dutch special education system, four clusters of schools
can be distinguished that all have a specific area of expertise (Stoutjesdijk & Scholte, 2009).
1 Youth services include the support and care of children with psychological, psychosocial and/or behavioral
problems and/or intellectual disabilities, as well as the guidance of their parents and guardians (Smeets & Van Veen, 2018).
Cluster 1 schools are for children with visual impairment; cluster 2 schools are for children
with hearing impairment and speech and/or language impairment; cluster 3 schools are for
children with chronic illness and intellectual and/or motor disabilities, and cluster 4 schools
are for children who suffer from developmental, emotional and/or behavioral disorders
(Scholte, 2008; Stoutjesdijk, 2013; Zweers, 2018). The severity of these problems has caused
students to fail in regular education and has created a need for extra support and special needs
services to help them achieve their educational goals (Stoutjesdijk, 2013). One of the criteria
for a child to be eligible for special education is that school services in regular education have
proven insufficient (Zweers, 2018). Before children are admitted to special education programs
they usually have received (several) youth services that have not reached their intended goal
(Scholte, 2008). In 2019, there were approximately 61,000 cluster 3 and 4 students in the
Netherlands; this number has been increasing over the past years (CBS, 2020). The present
study will focus on cluster 4 students. In other words: Dutch students with EBD who attend
special education.
Problem behavior does not arise abruptly; usually, it is influenced by various factors over
an extended period of time (Rigter, 2013). The bio-ecological model (Bronfenbrenner, 1979)
describes that the development and behavior of children are strongly influenced by the
interaction between them and their environment in multiple contexts, including family, school,
and friends. Hence, the relationship between students and their parent or teacher, in which
desirable behavior is transferred, is extremely important (Stoutjesdijk, 2013). To illustrate, an
appropriate response to problem behavior can favor the development of (vulnerable) children,
but an inadequate response can reinforce unwanted behavior (Aunola & Nurmi, 2005; Scholte,
2008). One can imagine that students who suffer from behavioral disorders have a higher need
and protect them. Recent research showed that on average 74% of students with EBD in the
Netherlands have experienced four or more ACEs, which is alarming (Verheggen, 2019).
The significance of ACEs has been embraced since the groundbreaking study conducted
by Felitti et al. (1998), which gave insight in the high prevalence of child maltreatment and
neglect and the impact this has on the individual during the rest of his life in terms of (mental)
health (Bonnet, 2016). Approximately 9500 Americans were asked about ten types of traumatic
events experienced during their youth. The questionnaire included five personal ACEs
(physical, emotional and sexual abuse; physical and emotional neglect) and five ACEs
concerning other family members (addiction; domestic violence; [history of] imprisonment;
[mental] illness; or the absence of [a] parent[s] due to divorce, death or abandonment) (Felitti,
et al., 1998). The more ACEs, the higher the risk to develop, for instance, alcohol
abuse/addiction, depression, domestic violence, and cardiovascular disease in adulthood
(Felitti et al., 1998). ACEs can be very traumatic and when these experiences endure, they can
eventually lead to post-traumatic stress disorder (Whitfield, 1998). Besides these long-term
effects, ACEs also show a more immediate negative effect on adolescents, including a low
state of well-being (Moore & Ramirez, 2016). One of the reasons for the occurrence of these
problems is prolonged and constant stress experienced during childhood, which has a negative
effect on the development of the brain (Gunnar & Quevedo, 2007); emotional and cognitive
development is strongly influenced by the amount of stress children suffer from (Young &
Widom, 2014). Moreover, ACEs have been associated with disturbed child-parent attachment
relationships (Van IJzendoorn, Schuengel, & Bakermans-Kranenburg, 1999, Vasileva &
Petermann, 2018), which are strongly related to child psychopathology (Colonnesi, Draijer,
Stams, Van der Bruggen, Bögels, & Noom, 2011; Hoeve, Stams, Van der Put, Dubas, Van der
Laan, & Gerris, 2012; Madigan, Brumariu, Villani, Atkinson, & Lyons-Ruth, 2016; Spruit et
Up till now, it remains unclear what the high prevalence of ACEs means for the students
with EBD attending special education in terms of youth services they receive. It is known,
however, that students with EBD receive a substantial amount of youth services: in 2019, 61%
received care focused on their behavioral problems, and 38% received care for their psychiatric
disorders (Berenschot, 2019). A better understanding of the relationship between ACEs and
youth services can help improve the approach to and treatment of these children in the future
so they can reach their highest potential, as children have the right to receive appropriate care
(IVRK, 1989). This study hypothesizes that the more ACEs students have experienced, the
higher the number of youth services they have received. Several arguments support this
assumption.
First of all, students with EBD are a difficult target group who experience a variety of
problems (Stoutjesdijk, 2013). Comorbidity of disorders occurs frequently; in fact, the
complexity of their problems has been increasing over the past years (Berenschot, 2019). This
asks for intensive treatment according to the Risk-Need-Responsivity model (Andrews, Bonta,
& Hoge, 1990). This model describes that for interventions to be effective, they need to take
into account three factors: the so-called What Works principles (Andrews & Bonta, 2010). The
first principle emphasizes the fact that interventions need to be adjusted to the risk level of the
recipient. For students with EBD this means intensive treatment, possibly resulting in multiple
youth services to meet their demands. In addition, children and youth with emotional disorders
are more likely to live in families “in which multiple risk factors exist for poor life outcomes”
(Wagner, Kutash, Duchnowski, Epstein, & Sumi, 2005), in other words: multi-problem
families (Ten Dam, Van ’t Hul, & Stad, 2009; Weisz, Ugueto, Cheron, & Herren, 2013). This,
and the fact that it is crucial that parents can respond to problem behavior adequately,
Given these points, it seems that the high prevalence of ACEs will contribute to more individual
as well as systemic problems, adding to a higher number of youth services.
Moreover, the complexity of problems contributes to a higher chance to drop out of
treatment (Chasson et al., 2008), resulting in more youth service use. Within forensic care,
families are often skeptic towards service providers, as there is an overall negative view
towards the youth service system (Ten Dam et al., 2009; Weisz et al., 2013). Service providers
are often seen as intruders, who interfere in family’s lives against their will and give them
unwarranted advice and directions. Parents do not always participate in therapy and their lack
of motivation can stand in the way of effective treatment (Bartelink & Van Dam, 2020). Their
view can be passed on to the children, as children’s expectations are shaped by interaction
patterns that they are accustomed to (Overbeek, Vermulst, Stattin, Ha, & Engels, 2007). To
illustrate, in trauma-focused therapy, the approval of parents has proven to be an important
predicting factor of how often a client shows up (Ormhaug & Jensen, 2018). Not only a lack
of attendance and motivation but also relocation can result in an early breakdown of treatment.
Students with EBD who live in multi-problem families can have an unstable living situation,
due to for example relational or financial difficulties within the household (Ten Dam et al.,
2009). Divorce, eviction, and out-of-home placements are common among these families and
can harm the endurance of treatment (Van Leiden & Ferwerda, 2004). That being the case,
students with EBD who have experienced several ACEs presumably receive more youth
services as well as child protection services.
As a final point, the interventions do not always reach their intended goal, resulting in
failure and more youth services that have to be executed. This can be caused by early dropout
or discontinued treatment, as well as low program integrity. Program-integrity cannot always
be guaranteed within forensic care, as it is difficult to examine the effectiveness of
problems (Hendriks & Stams, 2016). This conflicts with the second What Works principle, that
for an intervention to be effective, it has to be executed as intended (Andrews & Bonta, 2010).
This is a known problem within forensic care, as motivated clients who participate in research
are generally not representative of all children and youth who eventually receive the
intervention (Weisz et al. 2013). Also, externalizing behavior attracts so much attention that
the focus is usually solely on behavioral problems rather than their origin (Oterdoom, Lindauer,
& Schlatmann, 2020). By way of example, if someone is treated for aggression regulation the
therapy is not necessarily taking into account that clients might be traumatized.It also works
the other way around: for children and youth who are severely traumatized, some interventions
cannot start until their situation is stabilized (Struik, 2011). Thus, even though students with
EBD require intensive treatment, it is difficult to provide interventions that meet their needs
and that have proven to be effective among recipients facing such complex problems (Weisz
et al., 2013).
In summary, in the present study, it is assumed that ACEs play an important role in the way
services are deployed and executed among students with EBD, which are therefore expected
to contribute to a higher number of youth services. The present study has two primary aims to
answer. First, it will be examined through a case file study how many ACEs and youth services
students with EBD have experienced. Secondly, it will be examined if there is a relationship
between the number of ACEs and youth services students with EBD receive.
Method Participants
The present study is part of TARGET 4, a large-scale research containing four projects,
conducted by the University of Amsterdam in collaboration with Stichting Orion2 (Offerman,
2017). TARGET 4 aims to provide insight into what influences the dysregulation and
2 Stichting Orion is an organization and owns nine schools in Amsterdam that provide special education for students between 4 and 20 years old.
psychopathology of students with EBD and aims to develop and subsequently examine the
effectiveness of possible interventions for them (Offerman, 2017). TARGET 4 uses data
obtained from five special education schools located in Amsterdam: three primary schools (Mr.
De Jonghschool, Van Detschool, and Gerhardschool) and two secondary schools (Orion
College Amstel and Orion College Drostenburg).
This study is part of the second project of TARGET 4: a case file study, including
in-depth analysis of school and youth service case files. Data from four schools were included;
Mr. De Jonghschool was excluded because data had not yet been collected when this
research was conducted. This resulted in a sample of 102 cluster 4 students (83.3% male;
16.7% female), between the ages of 8 and 17 years (M= 12.92, SD = 2.57). A slight
majority (52%) of students went to secondary school.
Procedure
The Faculty Ethics Review Board from the University of Amsterdam has given their
permission for the TARGET 4 research, file number 2017-CDE-7603, on the 26th of February
2017. Moreover, the board and each director of participating schools granted their permission.
Prior to the research, a letter was sent to parents/caregivers and teachers with information about
the aim and course of TARGET 4. Subsequently, parents/caregivers were approached by
teachers and researchers by phone or at school. When parents gave their permission, students
were approached and informed as well. For students who were 12- to 16-years old both parents’ and students’ permission was needed. For students who were 16-years or older only the students’ permission was needed to participate. They were told that participation was voluntary and that they could withdraw their permission at any moment.
Data for the present study were collected between February 2018 and the 18th of May 2020.
As parents and students from the Van Detschool and Gerhardschool gave their permission in
were excluded from this study. Parents and students from Orion College Amstel and Orion
College Drostenburg were asked for permission in the school year 2017-2018, which meant
that case files dated until August 2018 were coded. Eight research assistants filled out a
codebook after a thorough examination of all the available files per student. The research
assistants were obligated to follow a three-day course to practice and learn about how to
interpret the codebook. After this training, the interrater reliability was established by having
two research assistants code the same files. During the entire process of coding, there was
regular consultation between the coders to discuss their decisions. Also, there was a check-up
when the data was inserted into SPSS; the person who inserted the data only inserted files that
were coded by another research assistant.
Measures
The codebook that was used for this case study included five main topics: social
demographics, developmental history, educational trajectories, youth service trajectories, and
judicial trajectories. The present study focuses solely on the constructs Adverse Childhood
Experiences and executed youth services, which are incorporated in the topics concerning the
developmental history and youth service trajectories.
Adverse Childhood Experiences. The ACEs that are included in the codebook are based
on the ones mentioned in Felitti et al. (1998) and Oh et al. (2018) and include thirteen items:
0) absent/no ACE, 1) neglect3, 2) physical and/or emotional abuse, 3) sexual abuse, 4) witness
of domestic violence, 5) parents’ divorce 6) (sudden) death of a parent, 7) incarcerated parent, 8) parent(s) with a mental disorder, 9) parental substance abuse, 10) (multiple) hospitalizations,
11) other ACEs, and 12) unknown. There was a distinction between established and presumed
ACEs, which are both included in this study. Examples of other ACEs that were listed are
bullying, instability in the living situation, and illness of a parent, but these are not included in
this study. A variable containing the total number of ACEs per student was created by adding
ACE 1 to 11, which made it possible to do a frequency count.
Youth Services. For every student, the youth services that were mentioned in the available
files were listed. The codebook distinguished between youth services for which it was certain
that they had been (attempted to be) executed and youth services for which it was unknown
whether they had been executed. Only youth services for which it was certain that they had
been (attempted to be) executed were included in this study. Moreover, a distinction was made
between youth services that were deployed due to 1) problems of the child, 2) problems of the
parents and 3) systemic problems. Within the first category, youth services were divided into
several sub-categories: (diagnostic) examination, residential care (24 hours/part-time),
treatment in a clinical setting, extra courses or training within the school context, paramedical
care, and ‘other’. The present study merely included the categories hospitalization, treatment
in a clinical setting, and youth services that were deployed due to systemic problems. These
constructs were combined to create a variable concerning the total amount of executed youth
services per student.
Data-analysis Strategy
To answer the research question, a preliminary analysis of the number of ACEs that
occurred among the participants was conducted, as well as an analysis of the number of
provided youth services. Neither variable was tested for internal consistency, as data in the
present study concerned the prevalence of ACEs and youth services for which merely a
frequency count of events sufficed. Even though there is some evidence that one ACE increases
the chance of another ACE occurring (Coppens, Van Kregten en Schneijderberg, 2016), the
presence of a certain life event does not automatically make an individual susceptible to another
life event (Cleary, 1981). In other words, it is difficult to establish a high correlation within a
any other item (Cleary, 1981). In addition, there is no normal distribution in this data, so merely
non-parametric tests were used in the present study (Bijleveld & Commandeur, 2012; Bishara
& Hittner, 2012; Bishara & Hittner, 2015). Therefore, Kendall’s tau-b (τb) correlation
coefficient was calculated to examine the relationship between ACEs and the number of
provided youth services. Kendall’s tau-b is used to establish the strength and direction between two ranked variables. It is a simple statistical analysis, yet it is crucial in e.g. psychiatric data
where it is common to have outliers and skewed distributions (Arndt, Turvey, & Andreasen,
1999). Kendall’s tau-b has some advantages over the more common Spearman r; because it offers “more protection against type I errors, even under strict conditions” (Arndt, Turvey, & Andreasen, 1999).
Results Preliminary analysis
Adverse Childhood Experiences. Figure 1 offers an overview of the prevalence of ACEs
among students with EBD (M = 1.94, SD = 1.628). The majority of the students (79.4%; n =
81) experienced at least one ACE and approximately one in three (31.4%; n = 32) experienced
more than two ACEs. The highest number of experienced ACEs is 7, and occurred only once.
The ACE that was most common among students is having divorced parents (47%; n = 48),
followed by physical neglect (31.4%; n = 32) and having a parent with a mental disorder
(25.5%; n = 26).
Figure 1. The prevalence of ACEs among cluster 4 students in numbers (N = 102)
0 5 10 15 20 25 30 0 1 2 3 4 5 6 7 N S tuden ts Number of ACE's
Youth Services. Figure 2 offers an overview of the number of provided youth services
among students with EBD. Nearly every student received at least one kind of youth service
(97.1%; n = 99), ranging from one to fourteen youth services. On average, students received
4.96 youth services per person (SD = 3.14). Most students (91.2%; n = 93) have received
treatment(s) in a clinical setting or systemic therapy (83.3%; n = 85). Only a few students were
hospitalized for treatment (12.7%; n = 13).
Figure 2. The number of provided youth services among cluster 4 students (N = 102)
Correlation Analysis
The Kendall’s tau-b correlation coefficient (See Appendix A) showed that there is a weak,
but significant and positive association between ACEs and youth services (τb = .147, p < .05).
The effect is modest, but implies that the more ACEs among students with EBD, the higher the
number of youth services they received.
Discussion
Adverse Childhood Experiences have been an object of research since 1998, and recent
findings showed that the prevalence of ACEs among students with EBD in Dutch urban schools
for special education is high (Verheggen, 2019). The purpose of the current study was to
examine if ACEs contribute to more youth services among this specific group of students.
Although it is known that ACEs harm the development of children and adolescents (Moore &
0 2 4 6 8 10 12 14 16 18 0 1 2 3 4 5 6 7 8 9 10 11 12 14 N S tudent s
Ramirez, 2016; Toth & Manly, 2011), it has never been researched whether ACEs influence
the amount of youth services students with EBD receive. Current findings confirm the
hypothesis that there is a positive association between ACEs and the number of youth services,
although the effect is modest. On average, students with EBD experienced approximately two
ACEs and received nearly five youth services.
The high prevalence of ACEs further supports the idea that students with EBD experience
more ACEs than students in both primary and secondary regular education, where roughly half
of the students reported no ACE (Karatekin, 2018; Vink et al., 2016). This finding highlights
the importance that youth service providers acknowledge that ACEs occur among this target
population, so they can adjust their approach. Treatment for children with EBD is focused too
much on one problem, rather than offering an integrated approach (De Kinderombudsman,
2019; Weisz et al., 2013). It is, however, important to look past the problems that attract the
most attention, such as externalizing behavior.
There are several explanations for the weak association that has been found. First, not all
students with EBD are recognized to be in need of psychological assistance, as there is a
“discrepancy between rates of child and adolescent psychopathology and rates of mental health service use” (Zwaanswijk, Verhaak, Bensing, Van der Ende, & Verhulst, 2003). There can be a threshold to arrive at appropriate youth services, as (parents of) children with EBD
occasionally do not seek help (Zwaanswijk, 2005) and even if they do, general practitioners do
not always refer them to mental health care because, for instance, psychosocial problems of
children are not detected (Verhaak, Van Dijk, Walstock, & Zwaanswijk, 2015).
In 2015 the Dutch Youth Act was introduced and aimed to reduce the burden on
specialized youth services by offering suitable care that was customized to the needs of children
and youth (Ministry of Public Health, Well-being and Sports & Ministry of Justice and Safety,
problems and offering preventive mental health care (ZonMw, 2019). An interim evaluation of
the law in 2018, however, shows this has not yet been accomplished. Many families that seek
help go to their general practitioners, as they are considered reliable and approachable.
However, obtaining referral is a tedious process, and is little put into practice. General
practitioners are not yet familiar with the supply of youth services in their municipality and
there is poor cooperation between them and local specialized health care givers (ZonMw,
2019), which results in children with EBD to be continuously undertreated, while problems
might not even be reported.
Second, several distressing cases about children and youth who were too complex to
receive youth care have been brought to the attention through media and reports (Martirosova,
2019; Smolenaars & Stokmans, 2019; Van den Heuvel & Waterberg, 2020; Van der Kaaden,
2019). Even though the Youth Act intended to simplify the youth care system, it has become
more difficult to facilitate care for complex cases now that 400 municipalities, including
policymakers, have become involved (Effting, 2016, ZonMw, 2019). Hence, one should bear
in mind that there could be students in the present study who never received the care they
needed.
To put it briefly, it is difficult to produce accurate numbers due to underreporting and
undertreatment of youth with complex problems, which provides an explanation for the weak
association that has been found in the present study. However, the results of our study
emphasize the necessity of research focused on the complex target population of children and
adolescents who attend special education. With this in mind, the present finding that ACEs
influence the number of youth services among students with EBD is valuable. Not only does it
imply that ACEs contribute to intensive treatment according to the Risk-Need-Responsivity
model (Andrews & Bonta, 2010) or increase the chance of early breakdown of treatment
what lies behind their externalizing behavior. This information is essential for the care for and
treatment of vulnerable children, such as students with EBD, as they are still sent from pillar
to post in an attempt to find suitable assistance (De Kinderombudsman, 2019).
Strengths and Limitations
Some limitations of this study should be mentioned. First, as previously stated, it is
difficult to conduct valid and reliable assessments in psychiatric research, including life events
(Breuk, Clauser, Stams, Slot, & Dorelijers, 2007; Cleary, 1981). This jeopardizes statistical
power to find significant effects, in particular, if only small effects can be expected due to
ceiling effects.Therefore, a post hoc analysis was conducted to compare the ACEs that were
reported in this study to the ACEs reported in the first TARGET 4 project: a screening research
that included the same participants as in this study (Verheggen, 2019). There was a positive
and significant association, which provides some support for the convergent validity of the
assessment of ACEs through case file information in the present study (Carlson & Herdman,
2012).
Second, it should be noted that the present study was dependent on the quality (low,
medium, or high) of available youth care and school files. About 85% of the case files were of
low quality and merely 15% were of medium quality; none were of high quality. Unfortunately,
this is a common problem within forensic care due to poor cooperation between youth service
providers and on account of privacy reasons (Asscher, Hendriks, & Stams, 2020).
Nevertheless, a post hoc analysis proved that there was no association between the quality of
case files and ACEs, nor with youth services. Still, one can imagine that the number of ACEs
and youth services could be higher if all files would have been of high quality, possibly leading
to a larger effect.
Finally, during an analysis of case files, information is always subject to differences in
influence their decision-making (Zainal, 2007). It has, however, been attempted to establish
high interrater reliability in this study by obligating the research assistants to follow a course
prior to coding, and including frequent discussion moments during the research.
The present study also has a few strengths. An analysis of case files provides an opportunity
to gain knowledge of individuals without the risk of socially desirable answers (Breuk et al.,
2007). In other scientific methods, researchers are more dependent on respondents’ honesty,
since the risk of socially desirable responding (Krusenvik, 2016). When participants are
interviewed or fill in questionnaires, they might feel their anonymity cannot be secured,
causing them to hold back in their answers.
Moreover, it is often difficult to recruit participants in at risks populations. As mentioned
before, families within forensic care can be skeptic towards youth workers (Ten Dam et al.,
2009). This can negatively affect their opinion and attitude towards researchers, or at least
demotivate them to participate in research. Even though a case study is time-consuming for
researchers (Zainal, 2007), it does not take any effort for the students and their parents. In this
study, researchers were able to gather information on people who are usually hesitant to
participate in research, which makes the present study extremely valuable (Weisz et al., 2013),
especially because research findings from general population studies, even if they contain a
sufficient number of children and youth with complex problems, cannot always be generalized
to children who receive psychological treatment or attend schools for special education (Asscher, Wissink, Dekovć, Prinzie, & Stams, 2014).
Recommendations and Concluding Remarks
The present study attempted to shed light on the influence of ACEs on the number of youth
services for students with EBD, since this can provide an explanation for the high amount of
youth services among them. Despite the many aims of the Youth Act in 2015, there are still
valuable and necessary to help improve child and youth care, as only knowledge retrieved from
real-life cases can increase understanding of the most vulnerable children, such as students
with EBD (Asscher et al., 2014; Hendriks & Stams, 2016). Therefore, it is recommended that
general practitioners, who are the most important factor in referring children and youth to
mental health care (ZonMw, 2019), and child youth care workers, increase their awareness of
the high prevalence of ACEs among students with EBD. Without fully understanding the
underlying problems that these children and youth face, it is inevitable that youth services will
continue to fail for them. Needless to say, this is undesirable: a constant change of caregivers will endanger children’s trust and will lead to more resistance in their cooperation. Hence, a more trauma-focused approach is necessary (Oral et al., 2016).
The present study merely looked into the prevalence of both ACEs and youth services and
did not focus on the type of youth services that have been deployed for students with EBD.
Previous research showed that children and youth in residential care with EBD did not always
receive proper care before their hospitalization: the type of treatment did not match their
problems (Broeders, Van der Helm, & Stams, 2015). To illustrate, even though their risk
factors included deviant peers, aggression, and maltreatment, hardly any care was focused on
these domains that proved to be related to aggression and delinquency (Assink et al., 2015;
Van der Put et al., 2012), which were the reasons for residential placement. The researchers
plead that appropriate care for them might have prevented hospitalization.
As the present study proves that ACEs contribute to more youth services among students
with EBD, future research should endeavor to investigate whether treatment for students with
EBD is sufficiently tailored to their needs. This will increase the likelihood of a successful
outcome according to the Risk-Need-Responsivity model of effective interventions for youth
with complex problems (Andrews & Bonta, 2010), and from the perspective of personalized
signaling and recognizing ACEs among students with EBD, it is essential to explore whether
they receive treatment focused on possible trauma (Gutterman et al., 2016). Hopefully, a
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Appendix A: Tables
Table 1
Kendall’s tau-b correlation, one-tailed.
Number of Youth Services Adverse Childhood Experiences Correlation Coefficient .147*
Sig. .026
