Special Needs Characteristics of Children With Emotional and Behavioral Disorders That Affect Inclusion in Regular Education

Abstract

The aim of this study is to determine the discriminating special needs characteristics of children with emotional and behavioral disorders (EBD) that predict restrictiveness of placement in special education. The focus is on dynamic factors instead of static factors. To this end, 235 children with EBD in special schools and 111 children with EBD in regular education were compared in terms of behavioral, emotional, academic, and environmental variables. Measurements used were the Child Behavior Checklist and Teacher’s Report Form, information in the children’s assessment reports, and the Dutch Family Home Environment Scale. In a logistic regression analysis, eight variables were found to be relevant predictors for placement in special schools instead of regular education. Relational problems between child and caregiver, academic performance, and the age at which the child received youth care for the first time were identified as the three predictors that could most affect the inclusion of children with EBD in regular education. Implications of these findings for future research and practice are discussed.

Keywords

emotional and behavioral disorders special needs educational placement special education inclusion

Children with emotional and behavioral disorders (EBD) such as autism spectrum disorders, attention deficit hyperactivity disorders, and conduct disorders experience difficulties in numerous developmental areas, such as social adaptation and academic achievement (Landrum & Singh, 1995; Panacek & Dunlap, 2003; Reid, Gonzalez, Nordness, Trout, & Epstein, 2004; Wagner, Kutash, Duchnowski, Epstein, & Sumi, 2005; Williams-White, Scahill, Klin, Koenig, & Volkmar, 2007).

Because of these many difficulties, in Western societies, children with EBD are generally placed in facilities for special education tailored to their needs. Although the structure of special education differs from country to country, these facilities usually cover a continuum ranging from standard education in a regular classroom to education in combination with residential treatment. In general, the educational policies of most countries are aimed at placing children with disabilities in the least restrictive environment (Lindsay, 2007). The aim to place as many children with disabilities as possible into mainstream education is registered in the Salamanca Statement (United Nations Educational, Scientific and Cultural Organization [UNESCO], 1994), which declares that all children, including children with disabilities, must have the opportunity to be educated in regular schools. In other words, regular educational facilities must be “schools for all.” The statement is based on children’s rights and the concern that these rights are contravened by segregating children with disabilities from the mainstream educational curriculum and practices (Lindsay, 2007). Several countries support the ideology of the Salamanca Statement and therefore made or continued to make considerable efforts to adapt their educational policies, to contribute to the aim of inclusion. In Great Britain, for example, the Special Educational Needs and Disability Act (2001) was introduced, in the Netherlands, the Expertise Centers Act (2003), and in the United States, the Individuals With Disabilities Education Act (1997).

Research on the distribution of children with disabilities over the continuum of special education demonstrates that children with EBD are usually placed in educational settings of a more restrictive type (Cullinan, Epstein, & Sabornie, 1992; De Greef & Van Rijswijk, 2006; Denny, Gunter, Shores, & Campbell, 1995; Stoutjesdijk & Scholte, 2009) because EBD is considered the most challenging group of disabilities to be handled in regular education (regardless of whether additional support is available; Hallenbeck, Kauffman, & Lloyd, 1993; Kauffman & Landrum, 2009). A similar picture emerges when a comparison is made between children with EBD and children with other forms of disabilities, such as physical handicaps or learning disabilities (LD); in special education, children with EBD are more often placed in segregated classrooms or separated facilities (De Greef & Van Rijswijk, 2006; Epstein, Nelson, Polsgrove, Coutinho, & Quinn, 1993; Stephens & Lakin, 1995). Given the considerable efforts on the part of governments to offer children with disabilities the opportunity to be educated in regular schools, the question arises why the inclusion of children with EBD in these school settings is relatively limited. This is an important matter to address not only in light of children’s abilities and educational rights but also considering the findings that some children with EBD are being placed in more restrictive settings than strictly necessary (Epstein & Cullinan, 1994; Hallenbeck et al., 1993). Furthermore, once a placement decision has been made, few of these children change their educational setting (Buysse & Bailey, 1994). When more is known about the special educational needs of children with EBD that affect inclusion in regular education, interventions can be aimed at these components, so that more children with EBD can attend regular schools.

To answer the question stated above, it is important to determine variables that contribute to the differences in levels of restrictiveness of children’s placements. This means that research investigating variables that actually predict these differences is needed. Previous studies on predictors of placement of children with EBD in facilities for special educational care have suggested that demographic variables such as low socioeconomic status (SES; La Paro, Olsen, & Pianta, 2002; Westendorp, Brink, Roberson, & Ortiz, 1986), ethnicity (Cohen, Parmelee, Irwin, Weisz, Howard, Purcell, & Best, 1990; Westendorp et al., 1986), young age (Robertson et al., 1998), male gender (Westendorp et al., 1986), and low IQ (Kauffman, Cullinan, & Epstein, 1987) contribute to the prediction of educational placement at a more restrictive level, together with variables that indicate stress in family functioning, such as maternal depression (Robertson et al., 1998; Westendorp et al., 1986), parental marital history (Westendorp et al., 1986), child maltreatment (Johnson-Reid, Drake, Kim, Porterfield, & Han, 2004), and quality of home environment (La Paro et al., 2002). An interesting and rather surprising factor is that in most of these earlier studies, static variables such as gender, age, and ethnicity were the most prominent predictors of educational placement setting, whereas dynamic variables such as behavioral, psychological, and academic measures had no or little effect, although these are the main factors indicating students’ (educational) needs (Kauffman et al., 1987; Robertson et al., 1998). This means that, despite previous research, there is still a lack of understanding about which dynamic variables determine differences in educational placement. Such variables are important to identify because, unlike static variables, they can be used for intervention purposes. With this in mind, the goal of the present study is to determine the dynamic variables that can predict educational placement, so that interventions in regular schools can be aimed more directly at these special educational needs to increase possibilities to provide “need-tailored” education for children with EBD. In contrast with existing research, the most obvious static variables age, gender, and ethnicity, which tend to suppress the importance of dynamic variables in the prediction of placement setting, have therefore been controlled for in this study.

The present study also includes academic performance (a variable that is a major indicator of students’ educational needs), and family functioning has been examined more thoroughly. This is in response to research findings by Westendorp et al. (1986) and Buysse and Bailey (1994), who still found gaps in the knowledge base concerning factors that contribute to the prediction of placement and indicated that future research should examine the pieces missing from the puzzle by including family characteristics and academic functioning. To date, only a few studies have been conducted, which used this as a starting point, and included children with EBD who received inclusive education in regular classrooms besides children who go to more restrictive facilities.

Furthermore, in previous research, the decisions about eligibility and assignment to a specific form of special education were made by the same authorities. In this study, the placement process was conducted in the Netherlands and consists of two parts according to the current statutory regulations. In the first step, an independent committee decides whether a child is eligible for special education. If so, in the second step, the child’s teacher determines in consultation with the parents whether the child will be placed in an inclusive setting or in a special school. This way, the procedure not only guarantees that people who are most aware of the child’s behavioral and educational needs are involved in the process of placement decision but also ensures that what is measured are not factors that relate to formal decisions on special education eligibility but only factors related to placement.

With regard to the aim of this study, two research questions were formulated:

Research Question 1: What are the differences and similarities between the characteristics of children with EBD in inclusive settings and children in special schools in the Netherlands?

Research Question 2: Which of these differences contribute most to the prediction of the level of restrictiveness of educational placement in the Netherlands?

Method

Procedure

The educational system in the Netherlands includes regular and special education. Since 1998, special education consists of four different clusters with their own area of expertise regarding teaching and caring for children with disabilities. Cluster 1 offers special education for the visually impaired (1% of all children within special education), Cluster 2 for the hearing impaired and/or children with serious speech and language problems (14%), Cluster 3 for children with cognitive and/or physical disabilities (41%), and Cluster 4 for children with EBD (44%; CBS, Central Bureau of Statistics 2009). To be found eligible for special education, children have to meet the cluster-specific criteria designed by the Dutch government to get access to this type of education. When this is the case, children are entitled to receive a form of special education within the cluster that supports their disability. Whether this special educational care is provided within a separate facility or within a regular school with additional support (inclusive setting) is decided in concordance by parents and teachers. Thus, although parents in the Netherlands have a choice to place their child with a disability in a regular school setting, the number of children with disabilities in special schools still exceeds the number in regular schools (Stoutjesdijk, Lemstra, & Jongbloed, 2007). Therefore, it can be concluded that the movement toward inclusive education for all children with disabilities in the Netherlands is still in a rather premature state compared with some other countries.

This study was performed in cooperation with a Dutch institute that provides special education and youth care for children with EBD (Horizon Foundation) in special and regular schools. Between December 2007 and May 2008, 380 parents of children with EBD who received special educational care from this institute were asked through a letter whether they were willing to participate in this study by filling out questionnaires, which they could return to Leiden University with an enclosed prepaid envelope. For the selection of parents, a random sample of 7 out of 16 special schools and 2 out of 4 educational services providing special educational care in regular schools was taken. Special schools connected to residential facilities were left out. Parental consent was obtained with regard to providing information about their children by the school and by teachers who were also asked to fill in some questionnaires. Eventually, questionnaires were filled in by parents and teachers for 346 children.

Apart from questionnaires, data were also obtained by examining information in assessment reports of the children with the help of an inventory list. This list was used not only to collect demographic features of the children in the sample, such as age, sex, and living conditions, but also to record the presence of relevant child and family risk factors. Students of Leiden University gathered this information as part of their master’s thesis in education and child studies. Before they set to work on the data collection, they received detailed instructions on how to list, define, and interpret the concepts in the inventory list and the information in the reports.

Participants

The sample of this study consists of 346 children with EBD who grew up in an urban part of the Netherlands. They all met the criteria of Cluster 4 special education, which are as follows: (a) a developmental, behavioral, and/or emotional disorder according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., DSM-IV; American Psychiatric Association, 1994) accompanied by (b) serious impairments to attain regular education which (c) the continuum of regular educational care cannot supply for without additional help (Ministerie van OCW, 2006). Examples of serious impairments are relational problems with classmates and/or teachers, to be a danger to others and/or oneself, and severe motivational and attention problems. Two groups were studied: one group of 235 children (M_age of 9.8 years, SD = 1.98 years) placed in separated facilities for special education (special school) and one group of 111 children (M_age of 10.4 years, SD = 1.79 years) who received special education in regular classrooms for most of the school day (inclusive education). The mean age of both groups did not differ significantly (p > .05). The distribution of boys and girls in both groups is approximately similar (88% and 12%, respectively, for the special school group and 89% and 11%, respectively, for the inclusive education group). Around 85% of the children in both samples had a Caucasian ethnic background. Regarding the level of support services in both groups, there were no differences in program factors. The special schools and regular schools did not provide for an additional treatment such as family support or residential care and only focused on care related to educational disabilities. In special schools, this care was provided by specialized teachers and teacher aides (paraprofessionals). The teachers in regular schools were trained and coached by professionals from special educational services. Moreover, students with EBD in regular classrooms received support from learning support teachers (either visiting or based at the school).

Measures

To determine the factors that could contribute to the prediction of educational placement of children with EBD, studies on the relationship between risk factors and the development of problem behavior were examined. The results showed that temperament, family risk factors, academic performance, and SES were mostly associated with behavioral problems (Eckenrode, Rowe, Laird, & Brathwaite, 1995; Herrenkohl, Herrenkohl, Rupert, Egolf, & Lutz, 1995; Nelson, Stage, Duppong-Hurley, Synhorst, & Epstein, 2007; Papp, Cummings, & Schermerhorn, 2004; Rae-Grant, Thomas, Offord, & Boyle, 1989). Nowadays, the main consensus is that emotional and behavioral problems in children are not caused by single risk factors but are the result of interactions between characteristics of the child and risk and protective factors in the child’s environment, such as family factors, school, and leisure activities. To systematically investigate the variety of risk factors, so-called “multiple-risk models” were introduced (Bronfenbrenner & Morris, 2006; Greenberg, Lengua, Coie, & Pinderhughes, 1999; Scholte, 1998). In this study, this multiple-risk model approach was also used to structure the multitude of factors that could contribute to the prediction of educational placement of children with EBD. Together with the results of the before-mentioned studies on placement predictors, this gives good suggestions of variables that should be taken into account when examining placement issues of children with EBD, namely, child factors (problem behavior and cognitive functioning), child and family risk factors (including the number of years of education of the caretakers and out-of-home care), and family functioning.

Problem behavior

The Dutch versions of the Child Behavior Checklist (CBCL; Verhulst, Van der Ende, & Koot, 1998) and the Teacher’s Report Form (TRF; Verhulst, Van der Ende, & Koot, 1997) were used to obtain problem behaviors assessed by the child’s caregiver and the child’s teacher, respectively. Both instruments provide a total scale score (Total Problems), two broadband scale scores (Internalizing Problems and Externalizing Problems), and six narrowband subscale scores (Affective Problems, Somatic Problems, social problems, Attention Deficit/Hyperactivity Problems, Oppositional Defiant Problems, and Conduct Problems). Parents and teachers can rate behavioral and emotional problems by answering 118 questions with a response set (0 = not true, 1 = sometimes true, and 2 = very true). From both instruments, the summary scale T-scores of Internalizing Problems and Externalizing Problems were used in this study. With regard to the Dutch version of the CBCL and TRF, satisfactory psychometric characteristics for these two subscales were reported (Cronbach’s α > .87, test–retest reliability [r] > .81; Verhulst et al., 1997).

Cognitive functioning

In this study, the concept cognitive functioning contains academic performance and IQ. Academic performance over the previous 6 months in comparison with peers is represented by a 4-point scale (1 = weak [more than 10 months behind], 2 = below average [between 5 and 10 months behind], 3 = average [no arrears], and 4 = above average [more than 1 month ahead]). This classification is based on a method recommended by the Dutch government to annually assess educational progress. The assessment battery consists of tests for reading, spelling, and math and gives an indication of the performance level of students in terms of months of education compared with a norm group of peers. The tests all meet the psychometric requirements of tests for diagnostic purposes with a Cronbach’s alpha of .83 or higher for the subscales on reading, .86 or higher for the subscales on math, and .87 or higher for the subscales on spelling (CITO, [Central Institute for Test Development] 2009). The variable “academic performance” is derived from averaging the outcomes on the tests for reading, math, and spelling. IQ scores were obtained from the assessment reports in which the Wechsler Intelligence Scale–Revised was used to measure intelligence.

Child and family risk factors

The data concerning the risk factors were obtained through examining the assessment reports of the children. These assessment reports were composed by school psychologists and used by a commission to determine the need for special education for the children in this study. Therefore, they contain extensive information about the functioning of the children and their families. A total of eight risk factors were subtracted from the information found in the files of the children. Psychiatric problems of parents, psychiatric problems of siblings, childhood maltreatment, sense of parenting incompetence, relational problems between child and caregiver, and out-of-home care were coded in a binary fashion as absent or present. The first five of these risk factors were indicated as present if the assessment reports contained information of mental health services, child services, or social services that explicitly mentioned these factors. Out-of-home care was indicated as present if reports about the child mentioned placement in residential treatment, foster care, and/or under supervision of a guardian. Moreover, the continuous variable “age at which the child came in contact with youth care for the first time” was obtained from the reports. Contact with youth care is defined as any request for care or referral that is followed on. Finally, the continuous variable “years of education” was assessed by calculating the highest number of years of education of the caregivers in the household.

Family functioning

To gain insight into family functioning, the Dutch Family Home Environment Scale was used (Van der Ploeg & Scholte, 2008), an instrument comparable with the Family Environment Scale of Moose and Moose (1981). Family functioning is measured by five subscales, namely, Organization (the strictness of rules that regulate the family interaction), Communication (the extent to which caregivers communicate in an open and harmonious way with their children), Partner Relationship (the quality of the relationship between caregivers), Responsiveness (the extent to which caregivers have an eye for the [developmental] needs of their children), and Social Support (the perceived amount of support from persons outside the family). Each of the subscales comprises 10 items. In addition, there is also one overall scale (Total Family Functioning). Respondents can mark each item on a 5-point scale (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = strongly agree). The internal consistency of the subscales is measured with Cronbach’s alpha and was found to be between .83 and .97. The test–retest reliability was measured by computing interclass correlations between the first and second measure and resulted in coefficients above .75 for all subscales. This indicates that the psychometric properties of the instrument meet the validity and reliability requirements set out for instruments serving diagnostic purposes (Evers, Van Vliet-Mulder, & Groot, 2000; Myers & Winters, 2002). The raw scores on the subscales were used in the analyses to represent the five continuous variables measuring family functioning.

Data Analysis

To conduct the statistical analyses, Statistical Package for Social Sciences (SPSS) 17 was used. The analysis of the data consists of two parts. First, independent sample t tests were performed between the groups inclusive education and special school on the before-mentioned variables on the domains of the multiple-risk model to examine the differences and similarities between children with EBD in both groups. Effect sizes were calculated for all significant findings. For this purpose, standardized mean differences (d) were used, where an effect size of .20 is considered small, .50 medium, and .80 large (J. Cohen, 1992).

Second, two logistic regression analysis procedures were performed to determine the most reliable and robust prediction of educational placement for children with EBD. Based on the theoretical background on which the variables in this study were selected and the aim of this study, initial logistic regression analyses were performed for all variables within a domain of the multiple-risk model to identify the most salient set of domains and represented variables to include in the final regression model (Hilbe, 2009; Hosmer & Lemeshow, 1989; Nelson et al., 2007). This way, the most parsimonious model to explain the data can be found considering the sample size and the relatively large number of variables, whereas model overfitting and production of numerically unstable estimates are avoided (Hosmer & Lemeshow, 1989).

To be considered for the final analysis, an omnibus χ² statistic needed to be significant (p < .05) for each domain. Subsequently, only individual factors within each domain that were statistically predictive (p < .05) for educational placement according to the Wald statistic were included in the final logistic regression model to identify the variables that most accurately predict educational placement setting.

Before the analyses, all relevant variables were inspected for outliers. Univariate outliers were investigated by box plots and were defined as scores that differed from the median by two SDs or more (A. Field, 2005). Multivariate outliers were examined using the Mahalanobis distance with p < .001 (Tabachnik & Fidell, 1996). Two cases were identified as univariate and multivariate outliers and were deleted. In addition, the variables were screened for singularity and multicollinearity. Singularity was examined by calculating Pearson correlations. The correlation matrix showed that none of the variables were highly correlated (r > .90; Tabachnik & Fidell, 1996). Next, the collinearity statistics were evaluated. For all variables, the variance inflation factor was lower than 10 and the tolerance was not greater than 0.1. Both statistics indicate no cause for concern (A. Field, 2005; Stevens, 2002).

Results

Differences and Similarities in Characteristics

The results of the independent sample t test between the two groups of children for the variables indicating problem behavior, cognitive functioning, child and family risk factors, and family functioning are presented together in Table 1.

Table 1.

Independent Sample t tests for Inclusive Education and Special School Groups on Problem Behavior, Cognitive Functioning, Child and Family Risk Factors, and Family Functioning

	Inclusive education (n = 111)		Special school (n = 235)
Variables	M	SD	M	SD	t test	d
Problem behavior
CBCL-internalizing	66.47	15.95	69.77	18.99	−1.59	0.18
CBCL-externalizing	57.44	12.44	64.39	14.80	−4.28**	0.49
TRF-internalizing	57.97	10.18	64.77	14.93	−4.96**	0.53
TRF-externalizing	57.16	12.21	64.47	14.82	−4.84**	0.53
Cognitive functioning
IQ	104	15.74	92	15.93	6.51**	0.78
Academic performance	2.91	0.81	2.11	0.79	8.71**	1.00
Child and family risk factors
Psychiatric problems–parents	0.38	0.49	0.41	0.49	−0.53	0.06
Psychiatric problems–siblings	0.15	0.36	0.20	0.40	−1.18	0.13
Parenting incompetence	0.33	0.47	0.45	0.50	−2.22*	0.22
Years of education	14.05	2.87	12.32	2.65	5.36**	0.63
Age first time youth care	6.16	1.88	5.07	2.05	4.74**	0.57
Childhood maltreatment	0.02	0.13	0.11	0.32	−3.97**	0.36
Out-of-home care	0.05	0.23	0.12	0.32	−2.15*	0.24
Relational problems child–caregiver	0.05	0.21	0.24	0.43	−5.76**	0.56
Family functioning
Responsiveness	12.01	2.86	12.97	3.42	−2.50*	0.31
Communication	19.99	5.99	21.95	5.74	−2.86**	0.33
Organization	13.87	3.49	14.95	3.83	−2.45*	0.30
Social network	17.37	6.43	19.93	7.59	−3.09**	0.36
Partner relationship	15.41	5.06	17.80	6.01	−3.65**	0.43

Note: CBCL = Child Behavior Checklist; TRF = Teacher’s Report Form.

p < .05. **p < .01.

The results show significant differences between groups on almost all variables within the four domains to the prejudice of children in special schools. It was found that children in special schools receive significantly higher scores on the Problem scales TRF-Internalizing, TRF-Externalizing, and CBCL-Internalizing than Children in Inclusive Education. Furthermore, children in special schools have significant lower IQs and perform less well on academic tasks in comparison to their peers, than children in inclusive education.

The results on the domains concerning child and family risk factors and family functioning show a similar picture. Children in special schools were significantly younger when they first received youth care than children in inclusive education. Moreover, they experienced childhood maltreatment, out-of-home care, and relational problems with their caregivers more often than children in inclusive education. A sense of parenting incompetence was more frequently reported within families of children in special schools than within families of children in inclusive education, and the number of years of education was significantly lower for families of children in special schools. Regarding the family functioning data, it was found that families of children in special schools had significantly higher scores on all subscales measuring family functioning. This indicates that parents of children in special schools report more difficulties with regard to responsiveness, communication, organization, social network, and partner relationship than parents of children in inclusive education. No differences between groups were found according to parents’ ratings on internalizing behavior and the occurrence of psychiatric problems of parents and siblings.

Determining Predictors

To determine statistically significant predictors of educational placement, initial logistic regression analyses were performed. In the following part, the results of these analyses will be examined for each domain separately.

Problem behavior

Initial logistic regression analysis of the behavioral factors showed a statistically significant omnibus χ² for the problem behavior domain as a whole, χ²(4) = 48.61, p < .01. Of the four variables entered into the equation, TRF-externalizing (B = 0.04, SE = .01, Wald = 10.87, p = .001), TRF-internalizing (B = 0.04, SE = .01, Wald = 13.88, p = .000), and CBCL-externalizing (B = 0.03, SE = .01, Wald = 8.25, p = .004) turned out to be significant predictors of educational placement within the problem behavior domain. CBCL-internalizing proved not to be a statistically significant predictor and is therefore not included in the final model for further analyses.

Cognitive functioning

For the cognitive functioning domain as a whole, a statistically significant omnibus χ² was found, χ²(2) = 77.51, p < .01. IQ (B = −0.03, SE = .01, Wald = 10.40, p = .001) and academic performance (B = −1.00, SE = .18, Wald = 32.64, p = .000) were significant predictors of educational placement setting.

Child and family risk factors

The results of the initial logistic regression analysis for this domain showed a statistically significant omnibus χ² for the risk factor domain as a whole, χ²(8) = 81.46, p < .01, with the following three factors being significantly predictive of educational placement: relational problems between child and caregiver (B = 1.76, SE = .53, Wald = 11.07, p = .001), age of first time youth care (B = −0.34, SE = .07, Wald = 23.15, p = .000), and years of education (B = −0.22, SE = .05, Wald = 20.18, p = .000). The other five risk factors were not statistically significant predictors and were therefore not included in the final model for further analyses.

Family functioning

The five variables of family functioning were included into an initial logistic regression analysis. A statistically significant omnibus χ² was found for the family functioning domain, χ²(5) = 18.88, p < .01. Of all subscales, the partner relationship factor turned out to be the only underlying predictor of educational placement (B = 0.05, SE = .03, Wald = 3.92, p = .048) and was therefore the one factor to be included into the final model.

Predicting Group Membership

Now that the variables that add to the prediction of group membership are known for each domain of the multiple-risk model, a logistic regression analysis is done to determine the final model. All nine variables that significantly predicted educational placement in the initial logistic regression analyses were entered simultaneously into the equation (method Enter).

The Hosmer and Lemeshow statistic was not significant with a chi-square of 9.828 (df = 8), p = .277. This indicates that the model fits the data well because the observed outcomes and predicted outcomes do not differ. Furthermore, the Omnibus test showed that the model as a whole proved to be significant. The model chi-square was 167.736 (df = 9), p < .01, indicating a statistically significant improvement in prediction using the model with all nine variables. This was also demonstrated by the improvement of correct predictions of placement. Using only the constant, 67.8% of placements of children with EBD in special education were correctly predicted, while using the full model, the percentage of correct predictions rose to 83.5%. In the full model, 70.3% of children with EBD were correctly predicted as belonging to the inclusive education group and 89.7% of children with EBD were correctly predicted as belonging to the special school group. Table 2 presents coefficients, the Wald statistic, associated degrees of freedom, and probability values for each of the predictor variables.

Table 2.

Logistic Regression Predicting Educational Placement in Restrictive Setting (N = 346)

Variables	β	SE	Wald statistic	df	Significance	Odds ratio
Problem behavior
CBCL-externalizing	0.030	0.013	5.444	1	0.020*	1.030
TRF-internalizing	0.052	0.015	12.861	1	0.000**	1.054
Child and family risk factors
Years of education	−0.124	0.057	4.756	1	0.029*	0.883
Age first time youth care	−0.394	0.083	22.448	1	0.000**	0.674
Relational problems child–caregiver	1.763	0.571	9.536	1	0.002**	5.828
Family functioning
Partner relationship	0.073	0.029	6.112	1	0.013*	1.075
Cognitive functioning
IQ	−0.031	0.011	8.531	1	0.003**	0.970
Academic performance	−0.956	0.208	21.153	1	0.000**	0.385

Note: CBCL = Child Behavior Checklist; TRF = Teacher’s Report Form.

p < .05. **p < .01.

The table shows that in the final model, CBCL-externalizing, TRF-internalizing, age of first time youth care, years of education, relational problems between child and caregiver, partner relationship, IQ, and academic performance are all significant predictors of educational placement of children with EBD in special education. Although a significant predictor in the initial logistic regression analysis, TRF-externalizing turned out to be an irrelevant predictor in the final model. The values of the coefficients of significant predictor variables reveal that the odds of children with EBD being placed in special schools rather than inclusive education increases with a unit decrease in IQ, academic performance, years of education, and age of first time youth care. Moreover, the odds of children with EBD being placed in special schools rather than inclusive education increases with a unit increase in scores on the Problem subscales CBCL-Externalizing, TRF-Internalizing, and partner relationship, and with a unit increase if there are relational problems between child and caregiver. The strongest predictors for educational placement setting are successively relational problems between child and caregiver, academic performance, and age of first time youth care. When relational problems between child and caregiver are present, the odds for placement in a special school are almost 6 times higher than for placement in an inclusive setting. Higher academic performance and older age of first time youth care increase the odds for placement in an inclusive setting over placement in a special school with 2.6 and 1.5 times, respectively. The unstandardized betas also indicate that the probability of placement in a special school is affected most by these three variables.

To rule out possible errors, some additional stepwise regression analyses were performed with the nine significant variables from the initial regression analyses. Forward likelihood ratio, forward conditional entry, backward likelihood ratio, and backward conditional entry showed similar results as previously reported. In all four entry conditions, the same eight variables proved to be significant predictors of educational placement, with the three before-mentioned variables (relational problems between child and caregiver, academic performance, and age of first time youth care) identified as most important in a similar order. Odds ratios for the four different analyses were practically identical to the ones from the Enter method for all nine variables, except for relational problems between child and caregiver, where the odds ratios ranged from 5.83-6.30 to 1.

Summarizing, the findings of before-mentioned analyses suggest that educational placement in more restrictive settings is predominantly determined by poor academic performance, a young age when first entering youth care, and relational problems between child and caregiver.

Discussion

Conclusions

The aim of this study was to gain greater insight into what characterizes the special educational needs of children with EBD who visit special schools or receive inclusive education at regular schools and to learn which of these characteristics affect inclusion of children with EBD in regular education. Knowledge of this kind can be used by parents, teachers, and policy makers to focus interventions more directly on these components, so that more children with EBD can attend regular schools.

Relevant indicators of children’s special educational needs were examined in a group of 235 children with EBD who attend schools for special education and a group of 111 children with EBD who receive inclusive education in regular schools. Overall, significant and substantial differences between the two groups were found. In general, children with EBD in special schools are more severely disabled, function on a lower cognitive level, experience more risk factors, and come from more poorly functioning families compared with children with EBD who receive regular education. No differences between children in special schools and children in regular education were found concerning the presence of psychiatric problems in parents and/or siblings. This contradicts the study of Robertson et al. (1998), who found differences between groups of children in various settings of educational care, namely, that children in more segregated parts of the educational continuum more often had parents with a history of mental illness. This conflicting result can reflect a real difference but can also be due to the study method used. In the present study, assessment reports of the children were used to extract information about psychiatric problems of family members. As the focus in these records lies primarily on children’s special educational needs, the presence of psychiatric problems was probably not reported consistently. Of course, this does not mean that these problems do not occur.

To examine whether the variables on which the two groups differed were actually predictive of the setting in which children with EBD receive education, a logistic regression analysis was performed with the placement setting as the dependent variable (restrictive or special school vs. nonrestrictive or regular school). In the final model, eight factors were determined that increase the chance of children with EBD being placed in a special school instead of an inclusive educational setting: high scores on CBCL-externalizing problems and TRF-internalizing problems, relational problems between child and caregiver, problems with partner relationship, low number of years of education, entering youth care at a young age, low IQ, and poor academic performance. Of these eight factors found, the presence of relational problems between child and caregiver, poor academic performance, and a young age when youth care was called in for the first time reflect the characteristics of children with EBD that are apparently the most difficult to handle in regular educational settings with additional support.

The importance of “academic performance” as a predictor of educational placement setting is further supported by the fact that academic difficulties and underachievement are often found to coincide with behavioral problems (Handwerk & Marshall, 1998; McConaughy & Mattison, 1994; Reid et al., 2004). For most regular schools, adequate support for this combination of special educational needs characteristics is not easy to provide (Landrum, Tankersley, & Kauffman, 2003), so it is understandable that children who display EBD along with academic difficulties have a higher chance of being placed in special schools or more restrictive settings.

Furthermore, the relatively large impact of “age of first time youth care” on distinguishing children with EBD in special schools from children with EBD who receive inclusive education can be explained by findings, which imply that an early onset of emotional and behavioral problems—in many cases accompanied by early involvement of youth care—is related to severity and chronicity of the problems (Hosp & Reschly, 2002; Silver et al., 1992). Considering the generally limited resources of regular schools to support children with serious problem behavior (Landrum et al., 2003), it could be very likely that children who have experienced youth care at an early age, and are therefore prone to more severe and chronic disabilities, will be placed in special schools or more restrictive settings sooner than children with milder disabilities.

Our finding that relational problems between children with EBD and their caregivers is the strongest predictor of educational placement in a restrictive setting seems difficult to understand at first sight because this factor is not intrinsically related to the conceptualization of special educational needs of children that is generally used. However, the role of this factor can be understood when the principles of a multiple-risk model, with protective and risk factors interacting and influencing normal and deviant development of children, are used as an explanatory framework. An important area where risk factors can linger is family functioning. Theory and research suggest that the interaction between child and caregiver is one of the most important predictors of problem behavior, with negative reinforcement and negative emotional bonding between child and caregiver increasing the probability of disruptive and antisocial behavior (e.g., T. Field, 2002; Stormshak, Speltz, DeKlyen, & Greenberg, 1997). In this respect, Bronfenbrenner (2005) suggested that a mutual emotional attachment between child and caregiver leads to an internalization of activities and feelings of affection that caregivers display, which in turn motivates the child to engage in the social environment. Children with less satisfying relationships with their caregivers have less positive views of themselves and more often engage in problem behavior. A possible way in which a troubled relationship between child and caregiver can affect functioning in an educational setting is reflected in a study by Kellam, Ling, Merisca, Brown, and Ialongo (1998). They state that children’s maladaptive aggressive behavioral response to classroom demands “may depend on family processes that precede and parallel the classroom social adaptational process, including the likelihood of coercive family interaction” (p. 183). This implies that when children interact with their caregivers in a negative manner, which reinforces maladaptive behavioral responses, it is possible that such coercive interactions are translated to a classroom setting with teachers and peers, and that the maladaptive behavior can escalate to more severe aggressive behavior within the classroom. In addition, research indicates that variables related to stress in family functioning and in relationships between family members (maternal depression, quality of home environment, child maltreatment) are associated with more segregated types of educational settings for children with EBD (Johnson-Reid et al., 2004; La Paro et al., 2002; Robertson et al., 1998; Westendorp et al., 1986). It could therefore be argued that children with EBD who experience relational problems with their caregivers often have more severe disabilities than children with EBD who do not have such problems or have it to a lesser extent. Given the before-mentioned lack of regular schools to be able to provide proper support for severe behavioral problems, the chances that these children will end up in special schools will increase.

The importance of academic performance, age of first time youth care, and relational problems between child and caregivers to predict the level of restrictiveness in educational placement for children with EBD are comparable with those reported by Hosp and Reschly (2002) for children with LD. They found an almost similar set of factors, namely, severity of academic difficulties, presence of behavioral problems, and family involvement, which largely influenced decisions regarding the placement of children with LD in more and less restrictive educational settings. This parallelism suggests that the three main predictors determining the restrictiveness of educational placement found in this study apply not only to children with EBD but also to children with LD, which stresses the importance of these factors for intervention purposes in special educational settings.

Limitations of the Present Study

Some considerations and cautions apply to the interpretation of our study results. First, because the sample was taken from several special schools in an urbanized part of the Netherlands, there are limitations to the generalizability of the findings to children in other settings and countries. Therefore, our study needs to be replicated with children from different ethnic and demographic backgrounds and older age groups, not only in the Netherlands but also in other countries to be able to conclude that the factors that most strongly influence decision making with respect to educational setting are robust, despite other possible influences. Second, our research was based on two types of education for children with EBD: special schools and inclusive education in a regular classroom. Because in the Netherlands only these two forms of special education are available, other types of special and inclusive education between these two extremes were not investigated. Previous research on educational placement of children with EBD focused primarily on the more segregated part of the special educational continuum. Consequently, the “in-between forms” of special education have not yet been evaluated. With this in mind, future research should not focus on children with EBD who receive education in the most segregated settings but should rather aim at including groups of children with EBD in a larger variety of settings on the special education continuum, especially those settings which are close to the fully integrated part. Third, despite careful initial consideration, probably not all variables that are potentially important predictors of educational placement were included in the analyses because a selection of instruments and variables had to be made. Although the results of this study are in line with previous research and theory, other discriminating factors may have come up as well if an even more extended set of (risk) variables had been used. However, the inclusion of relational problems between the child and caregiver in such a set of variables was a new aspect, not previously included in similar studies.

Implications for Practice

Despite the limitations mentioned above, our findings can be meaningful for clinical practice and policy making. The results indicate that children who are coping not only with EBD but also with academic problems and severe disturbances in the relationship with their caregivers are generally not assimilated in an inclusive educational setting. Taking into account the importance of the variable “age of first time youth care” in the analyses, this implies that to place more children with EBD in regular education, facilities must provide early and intensive interventions for children at risk for or diagnosed with EBD, which should also include academic and parental components. It is therefore important that education for children with EBD is more than only offering a place for difficult children to learn; it should also aim at promoting a healthy emotional and behavioral development. Although this is not the core responsibility of schools, it does fit their contributing role in the upbringing of children because children spend a large part of the day within the school walls.

To develop the strategies used in the educational and behavioral development of children with EBD, interventions in schools could therefore include principles of methods used to reduce dysfunctional behaviors in children, such as offering a supportive, responsive, and consistent environment in which positive behavior is encouraged and problem behavior limited (Fisher, Stoolmiller, Gunnar, & Burraston, 2007). In addition, it is important to pay more attention to the comorbidity of behavioral problems and academic problems at an early stage. The interfering nature of problem behavior tends to overshadow learning difficulties these children experience, which could result in even more problems in this area. The support given by regular schools must therefore focus on multiple problem areas at the same time and place extra emphasis on academic performance.

Inevitably, to improve teachers’ and other school personnel’s ability to make all this work, extra training and support is needed. This does not only apply to teachers already at work in the field but also to teachers-to-be. Teacher training colleges should focus their curriculum more on handling and supporting children with EBD in regular classrooms. As relational problems between children and caregivers turn out to be an important contributor to placement in a more restricted educational environment, special attention could for example be given to current knowledge of treatment concerning the sequela of bio-behavioral problems associated with inadequate caretaker relationships (T. Field, 2002; Fisher & Stoolmiller, 2008), to extend the theoretical background of teachers concerning this topic.

Besides teachers’ efforts to assist children with EBD in inclusive settings, it is also of great importance that caregivers take part in children’s education and treatment (Hosp & Reschly, 2002). In this context, Cartledge and Johnson (1996) pointed out that it is unlikely that teachers in regular education can support children with EBD in an effective manner without the assistance of the children’s parents. Teachers and schools must therefore invest in a productive parent–professional partnership in which there is room for open communication. In addition, problem behavior is more likely to diminish when treatment principles are applied consistently across environments. Schools must therefore stimulate a higher involvement of, and concern for, the caregivers of children with EBD. One way to achieve this is by offering occasional parent trainings in which parents become familiar with the treatment given to their children, so they can continue this at home. This, and the greater involvement in their child’s education, could also decrease feelings of isolation parents experience when managing a child with behavioral problems, which in turn can lead to a more positive relationship between child and caregiver (Fisher & Stoolmiller, 2008). Furthermore, if caregivers require specialized instructions on how their child with EBD can be handled positively, schools are generally seen as more easily approachable than professional youth care services. Under the pretext of support for their child, schools can encourage caregivers to get in touch with social and youth care services when needed.

However, taking into account the complexity of the problems of children with EBD who are placed in separated facilities and the fact that this and other studies have shown that children with EBD are the most difficult to include in regular educational settings (Cartledge & Johnson, 1996), it is questionable whether regular schools will ever be able to provide suitable education for children who have to cope with the most severe EBD. For these children, special schools, or wholly or partly separated facilities with more knowledge, time, and means to handle children with these types of behavioral problems will probably always be needed.

Presumably, inclusive education can therefore not be achieved for some children with EBD. With an ongoing special educational continuum in mind, it is thus important to develop procedures that take into account the individual needs of these children and can accurately assign children with EBD to the educational setting that best anticipates to these needs. As for now, there are still gaps in this process concerning identification and the need for intervention (Kauffman, 2001), which can lead to children with EBD being placed in unnecessarily restrictive environments (Epstein & Cullinan, 1994). We hope that the results of this study can contribute to refining the identification of children with EBD who need adequate educational support.

Finally, the findings of our study are of a descriptive nature; therefore, additional research on what works in the classroom for a range of emotional and behavioral problems is needed (Wagner et al., 2005) to provide a more solid basis for adequate support of these problems in various settings of educational care. To gain more insight into the aspects of special educational care that can stimulate positive development of children with EBD, a longitudinal follow-up study has started on the two samples used in this research, covering the emotional, behavioral, and academic development of the children. The results of this follow-up study will be presented in due course.

Footnotes

The authors declared no potential conflicts of interests with respect to the authorship and/or publication of this article.

The authors received no financial support for the research and/or authorship of this article.

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