In This Issue

Executive functioning profiles of children who display inattentive and overactive behavior in general education classrooms

The goal of this study was to gather information about the impact of such behaviors in the classroom setting

By Ara J. Schmitt, PhD, Jeffrey Miller, and Krista Long

Executive functions include cognitive processes that coordinate, integrate and control cognition, particularly in novel situations, and are necessary for higher-order problem solving and goal-directed behavior (Bernstein & Waber, 2007; Hughes & Graham, 2002; Marlow, 2000; Shallice & Burgess, 1991). One group of children that are theorized to have executive function deficits is those with attention disorders (Barkley, 1997).

Consistent with this notion, many studies have documented poorer executive functioning for children with Attention deficit/Hyperactivity Disorder (ADHD) compared to normal controls (see Barkely, 2006 for a review). Although a universal profile of executive dysfunction for children with attention problems as measured by laboratory-based tests of executive functions has proven elusive (Brown, 2006; Geurts, Verte, Oosterlaan, Roeyers, & Sergeant, 2005; Goldberg, et al., 2005; Sergeant, Geurts, & Oosterlaan, 2002; Tsal, Shalev, & Mevorach, 2005; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005), empirical studies investigating the executive function profile of children with attention problems consistently find that poor response inhibition and reaction time variability distinguish children with ADHD from normal controls (Epstein et al., 2011; Geurts, Verte, Oosterlaan, Roeyers, & Sergeant, 2004; Geurts, Verte, Oosterlaan, Roeyers, & Sergeant, 2005; Happe, Booth, Charlton, & Hughes, 2006; Sergeant et al., 2002). Gordon, Barkley,and Lovett (2006), among others who have reviewed the extant literature, concluded that continuous performance tests most reliably differentiate children with ADHD from those that do not (Barkley, 2006; de Zeeuw et al., 2008). Still, imperative to note is that the absence of disinhibition does not rule out the presence of an attention problem (Riccio, Reynolds, Low, & Moore, 2002).

Beyond the hallmark characteristic of disinhibition, no consistent executive function profile has been established for children with attention problems. Further, when comparing the executive function profiles of children with ADHD-Predominantly Inattentive Type (ADHD-I) and ADHD-Combined Type (ADHD-C), the patterns are neither consistent across studies, nor do the patterns appreciably differ across subtypes of attention problems (Epstein et al. 2011; Geurts, Verte, Oosterlaan, Roeyers, & Sergeant, 2005; Houghton,et al., 1999; Riccio, Homack, Pizzitola-Jarratt, & Wolfe, 2006; Sergeant, Geurts, & Oosterlaan, 2002; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). On the surface these findings appear to dispute conclusions that ADHD-C and ADHD-I are “distinct and unrelated disorders” (Milich, Balentine, & Lynam, 2001, p. 463; Adams, Milich, & Fillmore, 2010). Thus, it is unlikely that failure to establish a clear pattern of executive dysfunction using lab-based instruments is an artifact of multiple attention problem subtypes being present within the clinical samples.

One hypothesis for the lack of consistent results is that the executive function profiles have not converged into a stable pattern across studies due to the presence of inconsistent and irrelevant variance from comorbid disorders. ADHD has been shown to be comorbid with at least one other disorder in up to 44 percent of children in community samples and 87 percent in clinic samples (Barkley, 2003). As just one example, there is substantial evidence for the co-occurrence of ADHD and major depression throughout the developmental period (Ostrander, Crystal, & August, 2006). Further, from a neurobiological perspective, major depression involves abnormal functioning of the hypothalamic-pituitary-adrenal (HPA) axis that is associated with structural changes in the frontal cortex, among other structures (Weinstock, 2008). Thus, frontal cortex mediated executive function deficits could differentially impact the executive function profiles of children with ADHD and major depression compared to those with ADHD and not major depression resulting in different profiles for what appear to be children with ADHD. This was evidenced by Jonsdottir, Bouma, Sergeant and Scherder (2006) who found that performance on tests of executive function was not related to ADHD symptom severity, but rather to symptoms of depression. Therefore, it may be fruitful to study the executive function profiles of children in a natural setting, as opposed to clinic referred children who are also at high risk for comorbid problems. One might look to general education classrooms for examples of such children.

Individually administered assessment tools aside, a large literature base supports the use of behavior rating scales as part of the assessment procedures for the diagnosis of ADHD. For example, the Behavior Assessment System for Children (BASC; Reynolds & Kamphaus, 1992) has not only been shown to discriminate those with an attention disorder from controls (Jarratt, Riccio, & Siekierski, 2005), but also to detect subtypes of ADHD (Vaughn, Riccio, Hynd, & Hall, 1997). More recently it has been established that rating scales measuring executive function also distinguish children with ADHD from controls. For example, Jarratt et al. (2005) found that when rated on the parent form of the Behavior Rating Inventory of Executive Function (BRIEF; Gioia, Isquith, Guy, & Kenworthy, 2000), children with ADHD were found to have significantly more problems across executive function domains than a normal comparison group, even after controlling for IQ. This finding is consistent with other studies that established that children with ADHD are rated poorer by parents across BRIEF executive function domains than normal controls (Mahone et al., 2002; Sullivan & Riccio, 2008; Toplak, Bucciarelli, Jain & Tannock, 2009). At least two studies exist to suggest that the parent BRIEF may be used to distinguish ADHD-C from ADHD-I. First, McCandless & O’Laughlin (2007) found that children with ADHD-C were rated as having more problems on the Behavioral Regulation and Inhibit scales compared to children with ADHD-I. Second, Gioia, Isquith, Kenworthy, and Barton (2002a) also found these two groups to differ on the parent BRIEF Inhibit scale. There are also preliminary data that suggest teachers rate children with ADHD-C as havingmore problems on the Metacognitive and Working Memory scales on the teacher BRIEF compared to normal controls (McCandless & O’Laughlin, 2007). However, in this same study, no teacher BRIEF scales were found to distinguish ADHD-C from ADHD-I. Similarly, Sullivan, and Riccio (2008) provided evidence that teachers rate children with ADHD unspecified by subtype as having more problems across teacher BRIEF domains than normal controls.

Unlike previous studies, the purpose of this investigation was not to study the executive function profiles of clinic referred children, or children with a formal ADHD designation. This study sought to capture children exhibiting sub-threshold inattentive and/or overactive behaviors in order to glean information about the impact of such behaviors in the classroom setting. General education classrooms were also selected to avoid the potential impact of comorbid disorders often present in the clinical samples of some studies (e.g., McCandless & Laughlin, 2007; Toplak, Bucciarelli, Jain, & Tannock, 2009). The results of this study may shed light on the presence these problem behaviors and concurrent executive function patterns that found in general education classrooms, and also inform the universal screening of children in schools for educational support (Jimerson, Burns, & VanDerHeyden, 2007).

Method participants

Rating scale responses were gathered from the teachers of 112 children in grades 1 (n = 36, 32.1 percent), 3 (n = 28, 25 percent), 4 (n = 31, 27.7 percent), and 5 (n = 17, 15.2 percent) with an average age of 8.37 years (SD = 1.65, Range 5 – 11 years). The participant sample included 65 (58 percent) boys and 47 (42 percent) girls, and 23 (21 percent) African American, 69 (62 percent) White, 8 (7 percent) Bi-racial, 6 (5 percent) Asian, and 6 (5 percent) Other children. Socioeconomic status of the participants was indicated by reduced lunch status. Twenty-one (18.8 percent) received free lunch, 6 (5.4 percent) received reduced lunch, and 85 (75.9 percent) received regular lunch. The participants came from eight different classrooms in an urban school district in the Mid Atlantic United States

Measures

The Behavior Assessment System for Children-2 (BASC-2) (Reynolds & Kamphaus, 2004) is a widely used measure of children’s problem and adaptive behaviors. This broad-band measure includes a Teacher Rating Scales form that has been shown to be a reliable and valid tool to identify behavior problems (Jarratt et al., 2005; Reynolds & Kamphaus, 2004). The Attention subscale was used in the present study. Behavior Rating Inventory of Executive Function – Teacher Form (BRIEF). The BRIEF (Gioia, Isquith, Guy, & Kenworthy, 2000) is a behavior rating scale designed to measure teacher ratings of behaviors associated with executive function. The BRIEF is composed of 86 items rated by the teacher on a three-point Likert scale. Responses are scored onto eight scales which are then organized into two composite scores labeled the Behavioral Regulation Index (comprised of the Inhibit, Shift, and Emotional Control scales), and the Metacognition Index (comprised of the Initiate, Working Memory, Plan/Organize, Organization of Materials, and Monitor scales). Internal consistency ranges from .80 to .98 (Gioia et al., 2000). The BRIEF manual indicates good validity, but subsequent analyses have suggested a three-factor structure better explains the organization of the subtests (Gioia, Isquith, Retzlaff, & Espy, 2002b).

Procedures

Teachers were asked to rate the children in their class using subscales of the BASC-2 and BRIEF. The Attention subtest of the BASC-2 and BRIEF rating scales were administered as part of a larger study of student literacy. The teachers were asked to complete the rating scales after at least one month of school to ensure the teachers had observed the children long enough to provide reliable behavior ratings.

Practice Forum: Executive Functioning Profiles of Children Who Display Inattentive and Overactive Behavior in General Education Classrooms

In order to assign the participants to one of the four experimental groups, studies that used behavior rating scales to categorize children into actual subtypes of ADHD were reviewed. For example, Derefinko, Adams, Milich, Fillmore, Lorch, & Lynam (2011) used a minimum T-score of 60 on behavior rating scales to formally classify child participants as having a subtype of ADHD. Therefore, a T-score cut off of 55 was used in this study to capture children exhibiting sub-threshold inattentive and/or overactive behaviors in order to glean information about the impact of such behaviors in the classroom setting. As the items on this BRIEF Inhibit scale reflect hyperactive and impulsive behavior, children rated with BRIEF Inhibit T-Scores of 55 or greater and BASC-2 Attention scores of less than 55 were assigned to the Overactive group. Children rated with BASC-2 Attention T-Scores of 55 or greater and BRIEF Inhibit T-Scores of less than 55 were assigned to the Inattentive group. Children rated with BASC-2 Attention and BRIEF Inhibit T-Scores of 55 or greater were assigned to the Combined, inattentive and overactive group. Children rated with BASC-2 Attention T-Scores and BRIEF Inhibit T-Scores of less than 55 were classified as Normal. Sample sizes of the groups were 10 (8.9 percent) Combined Type, 12 (10.7 percent) Overactive Type, 10 (8.9 percent) Inattentive Type, and 80 (71.4 percent) Normal. These rates are consistent with estimates of ADHD in the general population (DuPaul, Power, Anastopoulos, & Reid, 1998). Therefore, it appears the current sample is typical of the composition of general education classrooms.

Results

The means and standard deviations for all variables are provided by total group and for each experimental subgroup in Table 1. A preliminary, one-way MANOVA was conducted to ensure that it was appropriate to consider the ratings of boys and girls together in the final analyses. The independent variable for this analysis was gender and the BRIEF Shift, Emotional Control, Initiate, Working Memory, Plan/ Organize, Organization of Materials, and Monitor scales were entered as dependent variables. No significant gender differences were revealed, therefore, the results of both genders were combined in the final analyses.

Figure 1: BRIEF Teacher Form ratings across scales and groups.

Figure 1: BRIEF Teacher Form ratings across scales and groups.

A one-way MANOVA was conducted with the four experimental groups used as levels of the independent variable (attention group) and the seven executive function measures entered together as dependent variables. The overall model resulted in a Wilk’s lambda of .11 (F(21, 293) = 16.46, p < .001, Partial ????= .53). Univariate F tests for each executive function scale indicated all scales showed significant differences across groups (Table 1). A Tukey HSD post hoc analysis was conducted to examine multiple comparisons among the experimental groups. Tukey HSD results are presented in Table 1. The profile of executive function scores across groups is provided in Figure 1. As expected, post hoc multiple comparisons indicated that children in the Combined Type were rated significantly higher on all BRIEF subscales compared to normal controls (Gioia et al., 2002a).

Discussion

Inferential analyses and visual analysis of figure 1 reveal that for children in general education classrooms there are differences in executive function abilities between children with and without inattentive behavior. Additionally, group differences also exist across children exhibiting inattention, overactivity, and combined inattention-overactivity. Specifically, the combined group showed significantly more problems compared to normal peers across all executive functions scales. The overactive group showed statistically significant elevations on the Shift, Emotional Control, Initiate, Working Memory, Plan/Organize, and Monitor scales compared to normal peers. Finally, the inattentive group had significantly greater problems measured by the Initiate, Working Memory, Plan/ Organize, and Monitor scales than normal peers. Therefore, it appears that the combination of inattention and overactivity has a cumulative, deleterious association with ratings of executive functions compared to either the presence of inattentive or overactive behavior alone. Furthermore, the primary differences between inattentive and overactive children in this sample were that the overactive children had greater problems with emotional control and the ability to shift attentional sets.

The current findings are consistent with the increasing number of studies that have identified executive function differences between children with ADHD-C and normal controls. This study also supports Milich and colleagues’ (2001) and Adams, Milich, and Fillmore’s (2010) claim that ADHD-I and ADHD-C are distinct disorders. Specifically, studies have begun to examine the notion of sluggish cognitive tempo (SCT) as a construct that may be used to explore the neurobehavioral manifestations of ADHD–I versus ADHD–C (Adams, Derefinko, Milich, & Fillmore, 2008; Carlson & Mann, 2000; 2002). Children with SCT are characterized with descriptors such as “daydreaming,” “drowsy,” “apathic,” “amotivation”, “underactive,” “slow moving,” “lacking in energy.” Based on SCT research findings, it is hypothesized that children exhibiting inattention will display executive function deficits consistent with the profile of SCT. The executive function profile of children who displayed inattentive behavior in this study seems to support the characterization of SCT.

Educators and specialists must be aware of the executive function problems associated with inattentive behavior and SCT, and consider providing children with such problems additional support in the areas of initiating work, working memory, planning for work completion, and selfmonitoring of learning behaviors. With respect to differentiating subtypes of ADHD using rating scales, Gioia et al. (2002a) compared the ratings of children with ADHD-C and ADHD-I using the BRIEF and found that both groups showed clinical-level elevationson the Inhibit, Initiate, Working Memory,Plan/Organize, Organization of Materials, and Monitor scales. McCandless & Laughlin (2007) also found that teacher BRIEF ratings did not adequately distinguish ADHD subtypes.

On the other hand, the present study was able to distinguish the executive function profiles of general education children who displayed inattentive and overactive behavior from children who only exhibited inattentive behavior using teacher ratings on the BRIEF. The difference in findings could be due to the fact that previousstudies involved clinic referred children with comorbid diagnoses who may have been given to more severe and global problems than the present sample.

This study contributes to the extant literature by demonstrating that children with subthreshold inattentive and/or overactive behavior in general education classrooms may differ by kind and severity of executive function abilities. Findings also underscore that great variability in executive functioning exist in classrooms and that rich information can be gleaned from teacher ratings of child behavior. The results of this study should be interpreted as preliminary because the modestly-sized sample of participants came from a single school in an urban school district. Future investigations might seek to use a larger sample of children from many schools and districts. Additional research is also needed to explore if the executive function profiles of children with inattentive and/ or overactive behavior changes across time. Given the nature of the larger study of which these data were gathered, another limitation of this investigation is that it was not possible to control for general cognitive ability or establish the number of participants, if any, who carried clinical diagnoses. Nevertheless, thefindings are encouraging as another step towards identifying the core executive function deficits that may be associated with different types of attention problems and that are present in general education classrooms.

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