Behavioral and Academic Progress of Children Displaying Substantive ADHD Behaviors in Special Education

Abstract

Objective: Exploring differences in behavioral and academic progress between children displaying substantive ADHD behaviors (M age of 9.4 years) in special schools (n = 38) and in inclusive education (n = 26). The contribution of pedagogical strategies to positive outcomes was also examined. Method: Measurements used were the Teachers’ Report Form, the Social Emotional Questionnaire, assessments of academic achievement, and the Pedagogical Methods Questionnaire. Mixed-model ANOVAs and Pearson’s correlations were used to analyze the data. Results: Significant progress was found regarding disorder-specific problem behavior and in all academic areas, but no interaction effect was found between time and setting. Correlations indicated that positive behavior reinforcement and emotional support are the pedagogical strategies that contributed most to behavioral adaptation. Conclusion: Children displaying substantive ADHD behaviors in both groups develop equally well in the areas of behavioral and academic functioning where significant progress was found.

Keywords

ADHD special education inclusion behavioral progress academic achievement

Inattentive, impulsive, and hyperactive behavior that varies in intensity is rather common among children in the general population (Levy, Hay, McStephen, Wood, & Waldman, 1997; Polderman et al., 2007). However, if such behavior becomes developmentally inappropriate, an ADHD could be present. According to the criteria of the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev. [DSM-IV-TR]; American Psychiatric Association [APA], 2000), ADHD can be diagnosed when problems such as excessive motor activity, inability to sustain attention, difficulty in taking turns, and interrupting others persist over 6 months and cause significant impairments of daily functioning in multiple settings such as home and school. Approximately, 8% of school-age children in the United States are diagnosed with ADHD (Centers for Disease Control and Prevention [CDC], 2012), and similar prevalence estimates are found worldwide (Skounti, Philalithis, & Galanakis, 2007). Due to their characteristic symptoms and impairments, a classroom can be a challenging environment for children with ADHD.

Findings of studies on academic and behavioral functioning of children with ADHD in an educational setting indicate that there are several areas of concern. First of all, academic underachievement is very common within this population, regardless of cognitive abilities (Barry, Lyman, & Klinger, 2002). It is especially reading and mathematics that cause considerable difficulties (Frazier, Youngstrom, Glutting, & Watkins, 2007; Massetti et al., 2008). What is more, this underachievement is found to persist into adolescence and results in negative academic prospects across the life span (Daley & Birchwood, 2010; Ek, Westerlund, Holmberg, & Fernell, 2010). Second, difficulties in social interaction with classmates and teachers are significantly more often observed in children with this disorder than in typically developing peers, especially when aggressive behavior is present (Batzle, Weyandt, Janusis, & Deviett, 2010; Hinshaw, 2002; McConaughy, Volpe, Antshel, Gordon, & Eiraldi, 2011). It is worrisome in this respect that symptoms of opposition, defiance, and aggression are often associated with ADHD (LeFever, Villers, Morrow, & Vaughan, 2002; Owens et al., 2005), and that oppositional defiant disorder (ODD) is one of the disorders most frequently codiagnosed (Jensen, Martin, & Cantwell, 1997).

A consequence of these impairments is that children with ADHD are more likely to require special educational support in either a regular classroom or a more restrictive environment such as a resource classroom or a school for special education (Biederman et al., 1996; Kendall, Leo, Perrin, & Hatton, 2005; Marks et al., 2009). Findings even indicate that these children are significantly less likely to spend the majority of instructional time in a regular classroom than children with disabilities other than ADHD (Schnoes, Reid, Wagner, & Marder, 2006). Considering the urgent need for support and the risk of falling behind in academic performance, it is important to monitor academic and behavioral outcomes to determine whether children make sufficient progress and timely identify areas where additional support or intervention is needed.

Another valuable reason for collecting data about progress outcomes is that such information is relevant to decisions about educational placement (Charman, Howlin, Berry, & Prince, 2004). Parents generally have a major voice in these decisions. However, studies have shown that choices between special educational settings are often based on parental preferences and beliefs about the extent to which educational settings can provide proper support, and the perceived social impact on their child (e.g., Connor, 1997; De Boer, Pijl, & Minnaert, 2010; Leyser & Kirk, 2004; Runswick-Cole, 2008), rather than on information about developmental prospects. This also seems to be the case in the Netherlands. Parents’ comparative assessment regarding placement of their child in special or in inclusive education is often driven by opinion and emotion. Therefore, placement decisions are partly guided by prejudices against special schools and in favor of inclusive education, and vice versa (De Greef & Van Rijswijk, 2006). Demographic preferences also play a role, such as whether or not the school is in the vicinity (De Greef & Van Rijswijk, 2006). To enable both parents and professionals to make better informed placement decisions, it is important that they have information at their disposal about developmental progress of children in various special educational settings.

There have been many studies on outcomes of children with ADHD regarding academic achievement and aspects of behavioral functioning such as aggression, social interaction, and classroom behavior (e.g., Barnard, Stevens, To, Lan, & Mulsow, 2010; Jitendra et al., 2007; Kern et al., 2007; Merrel & Tymms, 2001). However, to our knowledge, in none of these studies developmental outcomes have been compared across different special educational settings, even though children with ADHD can receive special educational support in settings of varying restrictiveness. Our study will be the first to compare progress between children displaying substantive ADHD behaviors in special schools and in inclusive education. Also, it is one of few recent studies to monitor progress for the duration of a year. Most previous research has been experimental by nature and often measures progress by evaluating a specific intervention implemented in a classroom context (e.g., Barnard et al., 2010; DuPaul, Weyandt, & Janusis, 2011; Fabiano et al., 2010; Miranda, Presentación, & Soriano, 2002; MTA Cooperative Group, 2004; Owens et al., 2005). In contrast with this type of research, the assignment of children to groups was not manipulated in our study, and no program intervention or consultation was provided to teachers in either educational setting. Because natural conditions were maintained, outcomes will be more representative of the typical practice in community-based special educational settings (Owens & Murphy, 2004; Raggi & Chronis, 2006). With this idea in mind, differences between the two settings regarding the use of common pedagogical strategies in the daily classroom support of children displaying substantive ADHD behaviors were also explored, as were the contributions of these strategies to positive outcomes. Results will extend current knowledge, because so far it has been unclear what kind of pedagogical strategies are used to support children with ADHD in special educational settings, to what extent they are used, and the effectiveness of these strategies (Danforth & Kim, 2008; Loe & Feldman, 2007).

For the study reported here, two research questions were formulated:

Research Question 1: Do children displaying substantive ADHD behaviors and who receive special educational support benefit in terms of development in academic and behavioral aspects, and are there differences between special educational settings with regard to this development?

Research Question 2: Are there differences between educational settings regarding pedagogical strategies used to support children displaying substantive ADHD behaviors, and which of these strategies are linked to positive development?

Although our study was explorative in nature, the following hypotheses were formulated with respect to the outcomes:

Hypothesis 1: Children displaying substantive ADHD behaviors show progress in both settings in behavioral functioning and academic achievement. Differences between settings may be that children in special schools make greater progress in both areas than children in regular classrooms, because the school and classroom environment of special schools is more geared toward special (educational) needs of children displaying ADHD-associated behaviors.

Hypothesis 2: Concerning pedagogical strategies, we hypothesized that in special schools these are emphasized more strongly than in regular schools, because of the lower teacher–student ratio. Providing a special pedagogical climate is generally also a more intrinsic aspect of the daily practice in special schools. Strategies aimed at structuring the learning environment are expected to be most closely related to positive development, along with those offering emotional support (Scholte, van Berckelaer-Onnes, & van der Ploeg, 2007).

Method

Procedure

Data were collected at schools for special education and at regular schools that provide support for children with special educational needs, in an urban part of the Netherlands. Parents of 4- to 12-year-old children receiving special educational support were requested to participate in the study, and to give written informed consent to information about their children being provided by schools and teachers. To select the parents, a random sample was taken of 7 out of 16 special schools and of 2 out of 4 educational services providing special educational support in regular schools. Special schools connected to residential facilities were excluded from the sample. Subsequently, we then asked the teachers of the children for whom consent had been obtained and school psychologists based at the schools monitoring the development of these children to fill in relevant questionnaires that could be returned to Leiden University. Depending on the questionnaire, the forms were filled in either by teachers or by school psychologists. Pre- and postassessment questionnaires were completed for 180 children with emotional and behavioral disorders. The surveys took place approximately halfway through the school year (M interval of 11 months), which resulted in two different teachers rating children’s behavioral functioning and academic achievement, thus reducing teacher bias. The responding school psychologist remained the same throughout the assessments.

Participants

All children in the sample were eligible for special educational support, because they met the admission criteria designed by the Dutch government. The criteria used by the service sector for children with ADHD (children with emotional and behavioral disorders) consist of three parts: (a) a developmental, behavioral and/or emotional disorder according to the DSM-IV-TR (APA, 2000), accompanied by (b) serious impairments to attending regular education that (c) the continuum of regular educational care cannot provide without additional services (Ministerie van OCW [Ministry of Education], 2006). Examples of such serious impairments are relational problems with classmates and/or teachers, being a danger to others and/or oneself, and severe motivational and attention problems. An independent committee assesses whether a child is eligible for special education. Subsequently, the child’s teacher determines, in consultation with the parents, whether special educational support should be provided in a special or a regular school.

From the main sample of 180 children with emotional and behavioral disorders with a pre- and post-assessment, we selected 64 children who displayed substantive ADHD behaviors. To be included in the subsample being studied, children had to score in the clinical range (defined as the 95th and higher percentiles in the standard Dutch youth population) on the “ADHD Total” subscale of the Social Emotional Questionnaire (SEQ; Scholte, van Berckelaer-Onnes, & van der Ploeg, 2008), a rating scale based on the diagnostic criteria of the DSM-IV-TR. Although this cut-off point implies that the children in the subsample display high levels of ADHD-associated behaviors, only about 36% of the children were formally diagnosed with the disorder (see Table 1). Therefore, we will here use the term displaying substantive ADHD behaviors to refer to the children in the subsample. Teachers served as informants because it is behavior in an educational setting that was examined, and studies have shown that teacher ratings are a reliable way of measuring ADHD problems (American Academy of Child and Adolescent Psychiatry [AACAP], 2007; American Academy of Pediatrics [AAP], 2001; Lauth, Heubeck, & Mackowiak, 2006). To be included in the sample, a full-scale IQ of 85 or higher was required to ensure that children included in the study were functioning at an intelligence level within or above the normal range.

Table 1.

Differences Between Children in Special Schools (n = 38) and Children in Inclusive Education (n = 26) on Background Variables at Time of Pre-Assessment.

	Special school	Inclusive education	Test
Age, M (SD)	9.3 (1.76)	9.5 (1.64)	t = 0.31, p = .761
IQ, M (SD)	100 (10.34)	104 (11.05)	t = 1.37, p = .177
Years spent in setting, M (SD)	1.9 (1.29)	2.0 (0.94)	t = 0.31, p = .754
Formal diagnosis ADHD (% yes)	32	44	χ² (1) = 1.33, p = .250
Psychotropic medication (% yes)	42	54	χ² (1) = 0.87, p = .352
Ethnicity (% Caucasian)	84	96	χ² (1) = 2.26, p = .225
Socioeconomic status
% lower education	24	12	χ² (2) = 4.21, p = .122
% secondary education	43	31
% higher education	33	57

Two groups were studied: one group of 38 children placed in separate facilities for special education (Special School) and one group of 26 children who were fully integrated in regular classrooms where they received special educational support (Inclusive Education). Grade levels ranged from third to fifth grade, with a majority of the children in fourth grade. In Table 1, statistics on relevant background variables of both settings are displayed. Analyses showed no significant differences between children on any of the variables at the time of pre-assessment. Also, the distribution of boys and girls in both settings is approximately similar (87% boys within Special School and 85% boys within Inclusive Education). Our sample did not include any children with comorbid ODD or conduct disorder (CD).

There were no perceptible differences in teaching materials or curriculum. Neither the special schools nor the regular schools provided additional treatments such as family support or residential care; they only focused on care related to educational disabilities. In special schools, this care was provided by specialized teachers, teacher aides (paraprofessionals), and school psychologists. The teachers in regular schools were coached by professionals from special educational services, also including school psychologists. In addition, children in regular classrooms received support from learning support teachers (either visiting or based at the school). Differences between settings mainly concerned the school environment. Compared with children in regular classrooms, children in special schools were placed in classrooms with fewer children, a more structured daily program, and fewer stimuli. Unlike children in regular classrooms, they had limited to no opportunity to interact with typically developing peers during school hours.

Measures

Progress in children’s functioning during 1 year was evaluated by pre- and post-assessments on multiple measures regarding behavioral functioning and academic achievement. Because children with ADHD can display general problem behavior alongside disorder-specific behavior (DuPaul & Stoner, 2003; Owens et al., 2005), progress for both types of behavior was measured separately.

The raw scores on the subscales Hyperactive/Impulsive Behavior and Inattentive Behavior of the SEQ were used to measure severity of symptoms specific for ADHD. With the SEQ, the presence of symptoms according to the DSM-IV-TR criteria of common developmental disorders in childhood can be assessed. Teachers rated the presence of symptoms by responding on a 5-point scale (1 = not at all, 2 = sometimes/incidentally, 3 = regularly/monthly, 4 = often/weekly, 5 = very often/daily). Psychometrics all met the requirements for tests for diagnostic purposes (Nunnaly & Bernstein, 1994). The internal consistency of the subscales from our sample was measured with Cronbach’s alpha (α) and found to be .84 for the subscale Inattentive Behavior and .86 for the subscale Hyperactive/Impulsive Behavior.

The Dutch version of the Teachers’ Report Form (TRF; Verhulst, Van der Ende, & Koot, 1997) was used to obtain non-disorder-specific problem behavior as perceived by the child’s teacher. The raw scores of the eight narrow band subscales (i.e., Withdrawn/Depressed, Somatic Complaints, Anxious/Depressed, Social Problems, Thought Problems, Attention Problems, Rule-Breaking Behavior, and Aggressive Behavior) were used in the present study to measure severity of general behavioral problems. Teachers rated behavioral and emotional problems by answering 118 questions with a response set (0 = not true, 1 = sometimes true, 2 = very true or often true). Satisfactory Cronbach’s alpha’s for internal consistency were found from our sample, ranging from .66 for the subscale Rule-Breaking Behavior to .94 for the subscale Aggressive Behavior.

Academic achievement was measured by means of the method recommended by the Dutch Ministry of Education to assess educational achievement annually (Central Institute for Test Development [CITO], 2009). The assessment battery consists of tests for reading (Krom & Kamphuis, 2001), spelling (Moelands & Kamphuis, 2001), and mathematics (Jansen & Engelen, 2002), and gives the performance level of students in terms of months of education. Ten months equals 1 school year. The performance level can also be compared with a norm group of peers to determine whether a child is behind, on the same pace, or ahead of other children of the same age and school type. The tests for reading comprise tasks measuring, for example, context use, comprehension, and oral reading errors. The tests for mathematics include tasks measuring correct use of problem-solving strategies and basic number sense. The tests for spelling comprise tasks measuring, for example, oral spelling errors and capability of linking graphemes to corresponding phonemes. In the present study, the overall performance level of text reading accuracy, reading comprehension, mathematics, and spelling were used in the analyses. The tests all met 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 mathematics, and .87 or higher for the subscales on spelling (CITO, 2009). IQ scores were obtained from diagnostic reports in the school assessment files of the children. The Wechsler Intelligence Scale for Children–Revised (WISC-R; Van Haasen et al., 1986) was used to measure intelligence. Assessments were completed by a qualified clinician as part of the admission procedure for special education. On average, these assessments took place approximately 2 years before the present study was conducted (see Table 1; years spent in setting).

To explore pedagogical strategies used within the classroom to improve children’s functioning, school psychologists were asked to fill in the Pedagogical Methods Questionnaire (PMQ). With this inventory list, respondents can indicate to what extent teachers emphasize common pedagogical strategies used for children with ADHD in their daily classroom support. The use and emphasis on these strategies are instructed and monitored by the school psychologists and are registered in Individualized Education Programs (IEPs). Assessments take place on 4-point scales (1 = no emphasis, 2 = small emphasis, 3 = medium emphasis, 4 = large emphasis). Four strategies aimed at behavioral and emotional functioning were included, namely, (a) structuring of (learning) environment (e.g., using picture activity schedules and timers, contingency management, screening off workplace), (b) positive behavior reinforcement (e.g., praising desired behavior and ignoring negative behavior, using preferred items as a reward), (c) offering emotional support (e.g., emphasizing individual qualities, showing understanding and compassion, and building trust), and (d) reinforcement of social and communicative behavior (e.g., peer mediation, modeling, cognitive relabeling of situations and social interactions). These common strategies were based on literature about intervention and treatment of children with ADHD (e.g., DuPaul et al., 2011; Martinussen, Tannock, & Chaban, 2011; Rief, 2005; Wilkinson, & Lagendijk, 2007). To get an indication of the intensity of support given to children regarding academic achievement, three PMQ items were used, that is, (e) providing individual instruction, (f) using concrete instructions, and (g) repetition of assignments and instructions. The reliability of this instrument was determined in a separate study where the PMQ was filled in by the same raters within 3 weeks (test–retest reliability). Intraclass correlations of .80 and above were found between both PMQ measurements (Scholte, van Berckelaer-Onnes, & van Oudheusden, 2007), suggesting sufficient test–retest reliability (Nunnaly & Bernstein, 1994).

Results

Preliminary Analysis

To conduct the statistical analyses, IBM SPSS Statistics 19 was used. First, to determine whether children in both settings are comparable at the time of pre-assessment, differences between children displaying substantive ADHD behaviors in special schools and in inclusive education on the preassessment measures concerning behavioral functioning and academic achievement were examined with several independent sample t tests (two-tailed). Given the number of t tests conducted, a Bonferroni correction was applied to the analyses, resulting in an adjusted significance level of p < .005 for the measures of behavioral functioning and p < .013 for the measures of academic achievement. The results are presented in Table 2. (M scores and SDs are displayed in Tables 3 and 4, respectively.)

Table 2.

Results of Independent Sample t Tests (Two-Tailed) Between Children With ADHD in Special Schools (n = 38) and Inclusive Education (n = 26) on Problem Behavior, ADHD Symptoms, and Academic Achievement.

	t	p
TRF
Withdrawn/depressed	−1.086	.282
Somatic complaints	0.018	.985
Anxious/depressed	−1.700	.094
Social problems	0.023	.981
Thought problems	−0.509	.631
Attention problems	0.985	.374
Rule-breaking behavior	−1.827	.072
Aggressive behavior	−1.474	.145
SEQ
Inattentive behavior	1.954	.055
Hyperactive/impulsive behavior	−0.122	.903
Academic achievement
Reading accuracy	0.264	.793
Reading comprehension	−1.042	.305
Spelling	−1.044	.303
Mathematics	0.955	.345

Note. TRF = Teachers’ Report Form; SEQ = Social Emotional Questionnaire.

Table 3.

Progress in Problem Behavior and ADHD Symptoms of Children in Special Schools (n = 38) and Inclusive Education (n = 26) During a 1-Year Follow-Up.

	Pre-assessment		Post-assessment		Effects
	Special school	Inclusive education	Special school	Inclusive education	Setting	Time	Setting × Time
	M (SD)	M (SD)	M (SD)	M (SD)	F	F	F
TRF
Withdrawn/depressed	5.13 (3.31)	4.15 (3.84)	5.08 (3.40)	4.23 (3.60)	1.42	<1	<1
Somatic complaints	0.76 (1.34)	0.77 (1.24)	0.29 (0.61)	0.38 (0.83)	<1	6.68	<1
Anxious/depressed	8.82 (6.69)	6.42 (4.57)	8.39 (5.77)	5.77 (4.14)	3.97	<1	<1
Social problems	4.71 (3.31)	4.73 (3.56)	4.32 (3.21)	3.27 (2.00)	<1	4.93	1.63
Thought problems	2.87 (2.92)	2.54 (1.86)	2.11 (2.37)	1.85 (1.67)	<1	5.17	<1
Attention problems	15.50 (7.71)	17.23 (7.43)	14.45 (7.17)	14.46 (8.35)	<1	4.10	<1
Rule-breaking behavior	1.87 (2.23)	0.92 (1.69)	1.79 (2.17)	1.35 (1.79)	2.14	<1	1.66
Aggressive behavior	14.39 (12.05)	10.31 (8.92)	13.26 (10.99)	8.92 (10.49)	2.71	1.70	<1
SEQ
Inattentive	7.82 (5.52)	10.73 (6.34)	6.45 (4.75)	8.19 (5.50)	3.70	8.31****	<1
Hyperactive/impulsive	8.80 (5.09)	8.65 (4.28)	7.37 (5.02)	7.08 (5.26)	<1	8.06****	<1

Note. TRF = Teachers’ Report Form; SEQ = Social Emotional Questionnaire.

****

p < .005 (adjusted significance level after Bonferroni correction).

Table 4.

Progress in Academic Achievement of Children With ADHD in Special schools (n = 38) and Inclusive Education (n = 26) During a 1-Year Follow-Up.

	Pre-assessment		Post-assessment		Effects
	Special school	Inclusive education	Special school	Inclusive education	Setting	Time	Setting × Time
	M (SD)	M (SD)	M (SD)	M (SD)	F	F	F
Text reading accuracy	22.38 (14.61)	19.75 (10.50)	29.41 (15.21)	22.88 (14.91)	<1	8.21**	1.22
Reading comprehension	32.65 (11.46)	27.00 (11.41)	43.47 (16.10)	33.09 (10.23)	3.29	13.77**	1.08
Mathematics	22.60 (16.32)	25.00 (11.76)	30.43 (16.30)	30.58 (12.37)	<1	59.86**	1.68
Spelling	23.32 (16.30)	19.83 (8.28)	31.44 (16.27)	27.42 (16.25)	<1	23.92**	<1

p < .013 (adjusted significance level after Bonferroni correction).

No significant effect (p > .05) of setting was found on any of the variables. This implies that at the start of the study, children in both settings had comparable behavioral and academic needs, and therefore internally valid comparisons can be made between both settings with regard to behavioral and academic development.

Progress in Behavioral Functioning and Academic Achievement

Progress in behavioral functioning and academic achievement was analyzed with 2 (setting: special school vs. inclusive education) × 2 (time: pre- and post-assessment) mixed-model ANOVAs. Developmental progress is indicated by a significant main effect of time (within-participant factor) for a specific outcome variable. A main effect for setting (between-participant factor) indicates that a difference in mean scores exists between specials schools and inclusive education regardless of time. An interaction between time and setting indicates a difference in the degree of progress between special schools and inclusive education. To define the magnitude of the effect, partial eta squared ( $η_{p}^{2}$ ) is reported (small effect: $η_{p}^{2}$ ~ .03; moderate: $η_{p}^{2}$ ~ .06; large: $η_{p}^{2}$ ≥ .14; Stevens, 1986). The adopted significance level after Bonferroni correction was p < .005 for the measures of behavioral functioning and p < .013 for the measures of academic achievement.

Mean scores and standard deviations at the time of pre- and post-assessment for children in special schools and inclusive education separately are shown in Tables 3 and 4. Results of the mixed-model ANOVA on each variable measuring behavioral functioning and academic achievement are presented in the last three columns, which represent the main effects for group and time, and the interaction effect between group and time.

Regarding behavioral functioning, a main effect for time was found for inattentive behavior, F(1,62) = 8.31, p = .003, $η_{p}^{2}$ = .12, and hyperactive/impulsive behavior, F(1,62) = 8.06, p = .004, $η_{p}^{2}$ = .12. This indicates that the problem scores on these two subscales decreased significantly within participants during approximately 1 year of special educational support. A trend toward significant decrease was found for problem scores on the TRF subscales Somatic Complaints, F(1,62) = 6.68, p = .010, $η_{p}^{2}$ = .10, Social Problems, F(1,62) = 4.93, p = .030, $η_{p}^{2}$ = .07, Thought Problems, F(1,62) = 5.17, p = .026, $η_{p}^{2}$ = .07, and Attention Problems, F(1,62) = 4.10, p = .047, $η_{p}^{2}$ = .06. No significant interaction effect between time and group was found. This suggests that children displaying substantive ADHD behaviors in special schools and in inclusive education developed equally positive regarding inattentive and hyperactive/impulsive behavior.

Regarding academic achievement, a significant main effect for time was found for all areas of academic development: text reading accuracy, F(1,62) = 8.21, p = .007, $η_{p}^{2}$ = .19, reading comprehension, F(1,62) = 13.77, p = .001, $η_{p}^{2}$ = .35, mathematics, F(1,62) = 59.86, p = .000, $η_{p}^{2}$ = .60, and spelling, F(1,62) = 23.92, p = .000, $η_{p}^{2}$ = .41. This indicates that the children in the sample made significant progress on these variables within approximately 1 year. The absence of a significant interaction effect suggests that children displaying substantive ADHD behaviors in special schools do not differ from their counterparts in inclusive education regarding the degree of progress that is made in academic achievement. However, at the time of pre-assessment, both children in special schools and children in inclusive education were already lagging behind on all subjects. On text reading accuracy, they were on average 6.7 months behind (SD = 8.68), on reading comprehension 3.9 months behind (SD = 5.55), on mathematics 4.1 months behind (SD = 5.69), and on spelling 7.7 months behind (SD = 8.88). No significant differences were found between groups on the mean number of months the children were behind (p > .05). Furthermore, the difference scores between pre- and post-assessment show that the children did not make the acquired progress of 10 months within a school year on almost all of the subjects, indicating an increase in the number of months they are behind. In other words, they made significant progress on all subjects, but this progress was not enough to make up any arrears.

Pedagogical Strategies Related to Progress

Independent sample t tests (two-tailed) were also conducted to examine differences between both settings regarding the extent in which pedagogical strategies were emphasized in the daily support of these children. Bonferroni correction was applied, resulting in an adjusted significance level of p < .007. No significant differences were found between settings with regard to the emphasis on pedagogical support strategies (p > .05).

In addition, exploratory correlational analyses were conducted with Pearson’s correlations to examine which strategies of the PMQ relate to behavioral and academic progress, measured as difference scores between pre- and post-assessment on the behavioral and academic measures. Correlations around .10 are considered small, around .30 medium, and around .50 large (Cohen, 1992). For this analysis, the samples of children in regular classrooms and children in special schools were pooled, since previous analyses showed no interaction effect between time and group, and no differences in methods used. Table 5 displays the correlations between strategies and progress in behavioral problem areas.

Table 5.

Correlations Between Difference Scores Behavioral Functioning and Pedagogical Strategies (N = 64).

	Structuring (learning) environment	Positive behavior reinforcement	Offering emotional support	Reinforcement of social and communicative behavior
TRF
Somatic complaints	.18	.22	.05	.13
Social problems	.30*	.35***	.45***	.01
Thought problems	.17	.21	.27*	.05
Attention problems	.23	.32***	.26*	.24
SEQ
Inattentive	.29*	.27*	.26*	.18
Impulsive/hyperactive	.13	.13	.02	.33***

Note. TRF = Teachers’ Report Form; SEQ = Social Emotional Questionnaire.

p < .05 (two-tailed). ***p < .01 (two-tailed).

Positive behavior reinforcement and offering emotional support were the pedagogical strategies that correlate most strongly with amelioration of behavioral problems within the six areas of problem behavior where progress was found. Significant correlations were all positive with effect sizes (r) ranging from medium (around .30) to strong (r = .45). Significant positive correlations with medium effect sizes were further found between structuring (learning) environment and a decrease of inattentive behavior (r = .29), and between reinforcement of social and communicative behavior and a decrease of impulsive/hyperactive behavior (r = .33).

Results reveal no significant correlations between emphasis of types of academic instruction and progress in text reading accuracy, reading comprehension, spelling, and mathematics. However, we did find that using concrete instructions (r = .28, p = .025) and repetition of assignments and instructions (r = .33, p = .008) had a positive influence on reducing inattentive behavior.

Discussion

Our study documents and compares academic and behavioral progress of children displaying substantive ADHD behaviors in special schools and in inclusive education after 1 year of receiving special educational support. As far as we know, such a comparison within this population has never been conducted so far. Also, relations between progress and the use of common pedagogical strategies were analyzed. As we expected, results indicate that children in both settings made significant progress in behavioral functioning showing a decrease of ADHD-disorder specific problem behavior. Regarding non-disorder-specific problem behavior, we found a trend toward a decrease of physical complaints, thought problems, and social problems. The decrease of internalizing problems such as physical complaints and thought problems does not seem directly related to ADHD, in view of the fact that the symptoms of the disorder are mainly externalizing. However, Jensen et al. (1997) found that comorbid internalizing symptoms were observed relatively frequently in children with ADHD, ranging from 13% to 50%. Regarding academic achievement, we found a significant increase on all measured curricular areas, but the increase rate was not in line with the academic achievement standards set for children with an IQ in the normal range. This implies that the children in the sample did make academic progress, but still underachieved in relation to their level of ability. These results correspond to previous research on academic outcomes of children with ADHD showing that underachievement is common in this population when IQ is controlled for (Diamantopoulou, Rydell, Thorell, & Bohlin, 2007) or when children with ADHD are compared with typically developing peers matched by intelligence (Barry et al., 2002).

No significant differences were found between the degrees of progress made by children in the two settings. This outcome was not expected, and suggests that for this particular group of children, school environment does not account for differences between settings regarding improvement of behavioral and academic functioning. Unfortunately, no studies comparing behavioral and academic progress of children displaying substantive ADHD behaviors in different special educational settings are available as yet, so our findings cannot be validated against previous studies on this specific topic. However, some studies have been conducted on progress of children with learning disabilities and behavioral disorders in general in special educational settings, which presumably included children with ADHD. Unlike our study, these studies did find differences in development between children across settings, although the results were not conclusive. For instance, a 4-year follow-up study by Peetsma, Vergeer, Roeleveld, and Karsten (2001) revealed no differences in psychosocial development between children with learning and behavioral disorders (LBD) in inclusive education and in special schools, but stronger cognitive gains were found for children with LBD in inclusive education. Schneider and Leroux (1994) found that children with behavioral disorders in special classes showed higher academic achievement, but less improvement in self-concept than children with behavioral disorders in inclusive classrooms.

We examined the influence of common pedagogical strategies used for children displaying substantive ADHD behaviors in the daily classroom practice of special educational settings by studying relations between progress and the extent to which these strategies were emphasized. Positive behavior reinforcement and offering emotional support were the strategies most closely correlated with a decrease in problem behavior. Concerning positive behavior reinforcement, this result is in line with extensive previous research into the effectiveness of interventions based on this strategy that aim at reducing problem behavior in children with ADHD (e.g., Fabiano et al., 2010; Owens et al., 2005). However, the relative importance of offering emotional support in the treatment of children with primarily externalizing behavior is somewhat less obvious, but similar results were also found in other studies. For example, Scholte, van Berckelaer-Onnes, and van der Ploeg (2007) examined emotional and behavioral development of children with ADHD in after-school day treatment centers and reported a reduction of ADHD symptoms at follow-up only when the emphasis on behavioral control was combined with expressing emotional support.

Contrary to our expectations, comparisons between educational settings indicated no differences in the extent to which pedagogical strategies were used. There has been only one other study on examining differences between educational settings regarding the use of pedagogical strategies in the support of children with ADHD. Reid, Maag, Vasa, and Wright (1994) compared children with ADHD who receive special educational support with children with ADHD who did not receive this support. They found that special education teachers used common pedagogical techniques such as individualized instructions and behavior modification more often than teachers in regular education. A possible reason for our results differing from those of Reid et al. is that there the regular schoolteachers, as opposed to the regular teachers in our study, were not coached by professionals from special educational services. As a consequence, these teachers may not have had the same level of knowledge of ADHD or of the techniques available to serve children with ADHD as the special education teachers in the study. Reasons given by Reid et al. for finding differences in the use of pedagogical strategies included the higher academic performance levels of the children with ADHD in regular education in their sample, and possible differences in behavior and severity levels between settings. We did not find such inequality in our study that could explain the absence of differences between settings in the use of pedagogical strategies.

Limitations of Our Study

There are some considerations and cautions to bear in mind in the interpretation of our study results. First, a factor that could have influenced the outcomes but was not controlled for in the study is medication use. Although the percentage of children who received psychotropic medication did not differ between settings, it remains a factor to take into account. However, the extent to which it could influence the outcomes is unclear, since some study findings indicate that the effect of medication use on a decrease in behavioral problems is larger than on an increase in academic achievement, which is often minimal (Barnard et al., 2010; DuPaul & Stoner, 2003; Miranda et al., 2002).

Second, although the children in the sample displayed substantive ADHD behaviors, only a part (~36%) were formally diagnosed with ADHD. As a result, there are limitations to the homogeneity of the sample and the generalizability of the findings to children who are diagnosed with the disorder. The generalizability of our findings regarding academic achievement might be less affected by this, because research on academic and educational outcomes has shown that children with behavior typical of ADHD, such as inattention, hyperactivity, and impulsivity, were no different regarding the degree of progress and poor academic achievement from children with a formal ADHD diagnosis (Loe & Feldman, 2007; Merrel & Tymms, 2001).

Third, the kind of specific pedagogical strategies and the extent to which these are emphasized in the support provided to children with ADHD cannot be obtained in great detail via the PMQ. Since the goal of this study was explorative by nature, that is, getting a first impression of the pedagogical strategies used in the support of children displaying substantive ADHD behaviors in special educational settings and the relation with progress, the use of an exploratory questionnaire seemed acceptable. In future research, however, it would be important to use an instrument that, for example, could measure the kind of emotional support offered in more detail, since providing emotional support was found to be an effective treatment strategy.

Fourth, to reduce the number of factors influencing developmental gains, we ensured that children in both settings did not differ significantly on several relevant variables. However, since our study was conducted in a natural setting, children in the sample could not be randomly assigned to settings and no control group could be used. Other factors, such as unmeasured teacher, parent, or family factors, could also have influenced the outcomes. Therefore, the fact that we found no differences in progress outcomes between children in different special educational settings must be interpreted within this limitation and needs to be further confirmed in future studies. A related caution concerns the sample size. Although our overall results were quite conclusive, it is possible that some effects were not detected in our study due to the small number of children in both settings. For example, at pre-assessment, the differences between settings regarding anxious/depressed, rule-breaking behavior, and inattentive behavior were almost significant with p values < .10. Future studies with larger sample sizes are needed to explore this possibility.

Future Directions

With regard to teacher factors, future studies should consider incorporating measures of teachers’ knowledge of ADHD and experience with teaching children with ADHD. We expect these factors to influence progress outcomes because they have been found to correlate with positive attitudes toward including children with disabilities in regular classrooms (Huang & Diamond, 2009). Positives attitudes can in turn have a favorable effect on academic and behavioral outcomes of children with ADHD in a classroom setting (Sherman, Rasmussen, & Baydala, 2008).

Future research may also benefit from including additional important variables. Because we had to make a selection of instruments and variables for our study, not all relevant variables with respect to developmental gains in a school setting were included in the analyses. Therefore, apart from academic achievement, and general and disorder-specific problem behavior, researchers should consider including well-defined comorbidity such as learning disabilities or ODD, and measures of social adjustment.

Finally, a particularly interesting aspect in the study of progress outcomes of children with ADHD is the distinction between subtypes. Three subtypes of ADHD are distinguished: predominantly inattentive type, predominantly hyperactive-impulsive type, and combined type (APA, 2000). Apart from symptomatology, they also differ in the prevalence of comorbid problems. For instance, academic underachievement is related to all three subtypes but is more prevalent in the inattentive and combined subtypes than in the hyperactive-impulsive subtype (Diamantopoulou et al., 2007; Merrel & Tymms, 2001), and the inattentive subtype has a greater chance of underachieving in the long term than the other subtypes (Massetti et al., 2008). Furthermore, aggressive behavior, impairments in social interaction, and peer rejection are more often observed in children diagnosed with the hyperactive-impulsive and combined subtypes than in children with inattentive subtype (Barkley, DuPaul, & McMurray, 1990; Carlson & Mann, 2000; Milich, Balentine, & Lynam, 2001). As a consequence, Barkley et al. (1990) found differences in special educational placement between ADHD subtypes in the United States. Children with inattentive subtype received a learning disabled school placement more frequently than children with hyperactive-impulsive behavior, who in turn were placed in behavior disorders schools more often. In addition, Massetti et al. (2008) reported a higher use of special educational services by children with inattentive subtype compared with the other two subtypes. All in all, differences in subtypes and comorbid problems result in a rather heterogeneous population with a diversity of special educational needs. In view of this, we expect different outcomes to be found for children with different ADHD subtypes. Unfortunately, we were unable to examine this hypothesis in this study due to the small sample size. Distinguishing between ADHD subtypes will be a relevant approach for future research concentrating on progress in special educational settings.

Practical Implications

Our findings suggest that offering emotional support is an important pedagogical strategy to improve behavioral functioning of children with ADHD in an educational setting. Educators and program makers should therefore consider including emotional support when designing interventions for children with ADHD or put more emphasis on this strategy when it is used alongside other strategies.

The findings that children with ADHD in both special educational settings underachieve in relation to their cognitive abilities, and make less progress than typically developing peers so that they fall farther behind, are of considerable concern. Therefore, more attention for effective interventions and learning support strategies is necessary to enhance academic achievement. In addition, systematic monitoring of academic performance in core curricular areas and of behavioral functioning can offer crucial information that can be used to provide well-timed support tailored to the special educational needs of these children.

Conclusion

Children with ADHD show improvement in behavioral and academic functioning in special schools as well as in regular classrooms, indicating that they make parallel progress. However, academic achievement remains an aspect of concern. A combination of positive behavior reinforcement and emotional support seemed the most effective approach to improving behavioral functioning. More research is necessary to confirm our findings and should be aimed, among other aspects, at examining developmental progress across different special educational settings for different ADHD subtypes.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Regina Stoutjesdijk is a PhD candidate at the department of clinical child and adolescent studies of Leiden University. Her research addresses special education, developmental disorders, and effectiveness of behavioral interventions in an educational setting.

Evert M. Scholte, PhD, is a full professor of clinical child and adolescent studies at Leiden University. His current research interests include developmental psychopathology, and assessment of treatment and care in special education.

Hanna Swaab, PhD, is a full professor of clinical child and adolescent studies at Leiden University. Her research interests include neuropsychological assessment and treatment, and neurocognitive development.

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