Gender differences in consequences of ADHD symptoms in a community-based organization for youth

Abstract

Attention-Deficit/Hyperactivity Disorder (ADHD) has been linked to disruptive behavior and disciplinary consequences; however, the variables involved in this process are largely unknown. The current study examined rule-breaking behavior as a mediator of the relation between ADHD symptoms and disciplinary actions 1 year later during after-school care at a community-based organization in a sample of 147 school-age children (M = 8.22 years; 54.4% male). Additionally, gender was examined as a moderator of these relations. Total ADHD symptoms positively predicted rule-breaking behavior at 1-year follow-up, which in turn was positively associated with disciplinary actions also at 1-year follow-up. Gender moderated these relations, such that the mediated effect of rule-breaking behavior on the association between total ADHD symptoms and disciplinary actions was significant for boys but not for girls. Further, when ADHD symptom dimensions were simultaneously included in the model, only hyperactive/impulsive symptoms were a positive predictor of rule-breaking behavior, and rule-breaking behavior mediated this link between hyperactive/impulsive symptoms and disciplinary actions. However, when examining ADHD symptom dimensions, no gender differences emerged. Implications for findings and future directions are discussed.

Keywords

ADHD symptoms community discipline rule-breaking behavior

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common childhood disorder, with prevalence rates occurring in 3-7% of children (American Psychiatric Association, 2000). Symptoms of ADHD have been associated with numerous negative consequences, such as disciplinary referrals in school (Molina, Smith, & Pelham, 2001). However, little to no research has examined ADHD symptoms as a risk factor for disciplinary actions in other contexts, such as after-school programs or other extra-curricular activities. Examining ADHD symptoms in after-school settings is an important extension of the literature, as after-school settings are less structured environments than school and offer more opportunity for engagement in rule-breaking behavior (Eccles, Barber, Stone, & Hunt, 2003). More specifically, a school setting offers more consistency, less physical contact, and less talking time than after-school settings, which can limit the occurrence of behavioral problems associated with ADHD symptoms, and ultimately decrease the likelihood of identifying the mechanisms that are involved in this developmental progression. Further, mechanisms such as rule-breaking behavior, which may account for the relation between ADHD symptoms and disciplinary actions, have not been evaluated. Disciplinary action is an important outcome to evaluate for prevention work, as frequent discipline referrals lead to chronic behavioral problems and program suspension (e.g., Tobin & Sugai, 1999). Accordingly, the current study examined relations between ADHD symptoms at baseline and disciplinary actions in after-school care at 1-year follow-up. The potential mediating influence of rule-breaking behavior was examined, such that ADHD symptoms would predict rule-breaking behavior at 1-year follow-up, which in turn would be concurrently associated with disciplinary actions also at 1-year follow-up. Furthermore, because gender differences in both ADHD symptoms and rule-breaking behavior have been found (e.g., Abikoff et al., 2002; Gershon, 2002), the current study explored whether gender moderated these relations. Examining gender differences is particularly important in ADHD, as prior studies have suggested that girls may experience less impairment, particularly in impulsivity (Newcorn et al., 2001). However, gender effects are not consistent in nonreferred groups and thus may be affected by referral bias (Biederman et al., 2005). Therefore, continuing to examine gender differences in outcomes of ADHD symptoms is needed, especially in nonreferred samples.

Early behavioral problems, such as aggression, noncompliance, and high activity levels, are evident among the majority of children during the preschool years. Yet most children outgrow these behaviors by school entry (Campbell, Shaw, & Gilliom, 2000). However, children who continue to exhibit these behavior problems as they enter school are at risk for developing persistent externalizing problems (Campbell, Pierce, Moore, Marakovitz, & Newby, 1996). Thus, problem behavior becomes particularly concerning when children reach school age. Therefore, the current study examines behavior problems and after-school care disciplinary consequences in school-aged children.

Disciplinary actions

Disciplinary actions (e.g., formal reports of child problem behavior) have implications for more severe behavioral and legal consequences. For instance, frequent discipline referrals lead to chronic behavioral problems and school suspension (e.g., Tobin & Sugai, 1999). The number of times a child displays disciplinary problems in school has been found to be associated with increased risk for later arrest rates in both primary and secondary school (Walker & Sprague, 1999). Although disciplinary actions in after-school care have important implications for youth outcomes, previous literature has only examined disciplinary action as it occurs within a school setting. Indeed, positive outcomes are associated with affiliation in after-school care. For example, participation in boys’ and girls’ clubs are correlated with lower levels of truancy, less favorable attitudes toward cheating, less cigarette use, increased enjoyment and effort in school, and is protective against risk for alcohol use associated with increasing age (Anderson-Butcher, Newsome, & Ferrari, 2003). Thus, understanding factors that are associated with increased risk for potential suspension and expulsion (as a result of repeated disciplinary write-ups) from after-school organizations is necessary for the prevention of future substance use and academic and behavioral problems. One such factor to examine is the pathway from symptoms of ADHD to disciplinary action, as symptoms of ADHD are associated with a host of negative long-term outcomes, including rule-breaking behavior and disciplinary problems (e.g., Molina et al., 2001).

ADHD symptoms

ADHD is characterized by the primary symptoms of poor sustained attention, deficient impulse control, and excessive activity level (Barkley, 1990). The symptoms of ADHD have been clustered together into valid symptom dimensions, one symptom dimension consisting of inattention symptoms and the other symptom dimension consisting of hyperactivity/impulsivity symptoms (Carlson, Shin, & Booth, 1999; Willcutt, Chhabildas, & Pennington, 2001). ADHD symptoms are associated with a number of negative adjustment outcomes, such as poor social functioning, peer rejection, educational difficulties, internalizing symptoms, and substance use (Bauermeister et al., 2007b; Connor et al., 2003; Hoza, 2007; Ohlmeier et al., 2008). Children suffering from ADHD symptoms have also been shown to exhibit greater rates of behavior problems than other children, such as noncompliance, rule-breaking, physical and verbal aggression, and overall poor classroom behavior (Abikoff et al., 2002; Anderson, Hinshaw, & Simmel, 1994). Furthermore, ADHD symptoms in children can lead more significant behavior problems, including more frequent rule violations at school and repeated disciplinary referrals (Molina et al., 2001). Thus, children who exhibit ADHD symptoms are highly disruptive in their environment and appear to receive more discipline from authority.

ADHD symptoms may also put children at risk for developing further behavior problems, such as rule-breaking and other types of conduct problems. Disruptive behavior is believed to follow a general developmental pathway, in which ADHD symptoms emerge initially, followed by less severe conduct problems (e.g., rule-breaking) and more severe conduct problems emerging later on (Waschbusch, 2002). ADHD symptoms have also been shown to be associated with an increased likelihood, more severe form, and earlier onset of conduct disorder (Thompson, Riggs, Mikulich, & Crowley, 1996). By midadolescence, about 22% of children with childhood ADHD had a diagnosis of conduct disorder (Biederman et al., 1996). In boys with ADHD, even very low rates of conduct problems and rule-breaking behaviors were a significant risk factor for the development of conduct disorder in adolescence and anti-social personality disorder in early adulthood (Manuzza, Klein, Abikoff, & Moulton, 2004). Further, research on children with symptoms of ADHD and co-occurring conduct problems such as fighting, stealing, and truancy suggest that they are at high risk for lifelong patterns of antisocial and delinquent behaviors and have even been referred to as “fledging psychopaths” (Gresham, Lane, & Lambros, 2000).

Theorists posit that cognitive deficits are a substantial predisposing factor for the developmental link between ADHD and rule-breaking behavior (e.g., Hummer et al., 2011; Pihl & Peterson, 1991). The early overlap between behavior problems and academic underachievement suggests that there may be underlying causal cognitive factors, such as language deficits, poor verbal skills, or neurodevelopmental delays (Hinshaw, 1992). Moffitt (1990) suggests that children with attention and neuropsychological deficits in preschool are at substantial risk for delinquency in adolescence, positing that they may fail to recognize warnings of punishment and have deficits in self-control functioning. Further, as cognitive functioning is influenced in part by genetics, genetic research suggests that the overlap of ADHD and conduct problems can be explained by common genetic factors in addition to environmental factors, such as social and family adversity (Thapar, Harrington, & Mcguffin, 2001).

It may be that rule-breaking behavior mediates the link between ADHD symptoms and its disciplinary consequences. Symptoms of ADHD (impulsivity, excessive activity, and poor attentional focus) appear to put children at risk for engaging in rule-breaking behavior (e.g., Barkley, 1997), and rule-breaking is likely to result in disciplinary action. Thus, rule-breaking behavior may actually account for the relations between symptoms of ADHD and disciplinary action, providing an explanation for why children with a high number of ADHD symptoms are more likely to face consequences from authority figures.

There appear to be, however, gender differences in ADHD symptoms as well as in the association between ADHD symptoms and other problem behaviors that need to be considered. Boys are nine times more likely to meet criteria for ADHD than girls in clinical samples and about three times more likely in community samples (Gershon, 2002). The gender difference in rates of ADHD show that boys are much more likely to be referred for, identified with, and treated for ADHD than girls (Gomez, Harvey, Quick, Scharer, & Harris, 1999). This may be due to the more disruptive, impulsive, and overt aggressive behaviors that boys with ADHD tend to show compared to girls with ADHD, who demonstrate more covert forms of aggression (Zalecki & Hinshaw, 2004). In observed classroom behavior, boys with ADHD demonstrated higher rates of rule-breaking and externalizing behaviors than did girls with ADHD (Abikoff et al., 2002). School suspension was also much more common in ADHD boys than girls (Bauermeister et al., 2007a). Girls with ADHD, on the other hand, are more likely to be diagnosed with the predominantly inattentive type and less likely to have comorbid conduct disorder and oppositional defiant disorder than boys with ADHD (Biederman et al., 2002). However, no gender differences in comorbid externalizing disorders for each ADHD symptom dimension are evident (Levy, Hay, Bennett, & McStephen, 2005). Thus, the link between ADHD symptoms and rule-breaking behavior and disciplinary actions may be more evident in boys than girls; however, it is unclear if gender differences exist when symptom dimensions are taken into account.

The current study

In sum, the current study examined relations between ADHD symptoms, rule-breaking behavior, and disciplinary actions at 1-year follow-up in an after-school program housed in a community-based organization for youth. An after-school setting is ideal for understanding these data because some researchers question the reliability of school records due to numerous unrecorded incidents, inconsistent criteria between teachers, and the consequences of such incidents (Evans, Langberg, Raggi, Allen, & Buvinger, 2005). Therefore, a well-monitored setting with consistent criteria for disciplinary action, such as the after-school program in the current study, is ideal for collecting this type of data. In addition, the current study examines ADHD symptom counts in a high-risk community sample. The current sample is defined as at-risk based on the socioeconomics of participants. In the literature, socioeconomic disadvantaged youth are often described as at-risk for early developmental difficulties and psychosocial problems due to more economic and social stressors (Gibbs, 1998). In using an at-risk sample individuals are more likely to present with ADHD symptoms, allowing developmental risks to be better examined. Further, examining ADHD symptoms on a continuum (rather than all-or-nothing diagnosis), does not exclude children exhibiting symptoms at a sub-clinical level, providing more statistical power and allowing us to understand these associations for those with varying levels of attentional problems.

ADHD symptoms were examined as a predictor of disciplinary actions 1 year later, using all symptoms of the disorder as well as the two symptom dimensions (inattention and hyperactivity/impulsivity). Rule-breaking behavior (assessed at 1-year follow-up) was examined as a potential mediator of this association. Associations were examined while also controlling for prior levels of disciplinary actions and rule-breaking behavior. In addition, gender was examined as a moderator of the proposed mediational pathway. ADHD symptoms were expected to positively predict rule-breaking at follow-up, which in turn would be associated with disciplinary actions. Based on the previous literature highlighting the disruptive nature of behavior in boys with ADHD (Abikoff et al., 2002), it was also expected that gender would moderate these associations, such that the rule-breaking behavior would be a significant mediator of ADHD symptoms and disciplinary actions for boys but not for girls.

Finally, due to the high statistical overlap between ADHD symptoms and Oppositional Defiant Disorder (ODD) symptoms (e.g., Biederman et al., 2007; Goldman, Genel, Bezman, & Slanetz, 1998), models that also included ODD symptoms as a covariate were estimated in order to evaluate whether ADHD symptoms were associated with rule-breaking behavior over and above their statistical overlap with ODD symptoms.

Methods

Participants

Participants were recruited from a mid-sized, southeastern community-based organization that provides low-cost after-school and summer care for between 200 and 300 school-age children daily. Written permission was granted from the organization’s administrative office as well as the University Institutional Review Board prior to participant recruitment. For one week prior to the study, a table was set up at the entrance with a sign that said, “Earn $5.00.” Children and caregivers who approached the table were provided with more information and were able to ask questions about the nature of the study. Caregiver consent was obtained for 147 children.

Participants ranged from 5 to 13 years of age (M = 8.22, SD = 1.99). Distributions of participant demographic data are reported in Table 1 . The proposed analyses are important to understand within this at-risk sample, because it offers generalizability to socioeconomically disadvantaged and diverse populations.

Table 1.

Demographic variables

Demographics	% (N)
Gender (male)	54 (80)
Race
African-American	67 (99)
Caucasian	20 (30)
Hispanic/Latino	4 (7)
Other or biracial	7 (11)
Fee reduction	96 (141)
Gov’t assistance with fees	87 (128)
Program attendance
Daily	86 (127)
4 days/week	7 (10)
3 days/week or less	7 (10)

Staff members responded to questions on all 147 children at baseline; however, staff only reported on the 74 (50.3%) children who remained organization members at 1-year follow-up. Of the children who no longer attended the organization, 9 had moved, 17 had financial reasons, 7 were suspended/expelled, 24 had been transferred to another organization, 4 were removed by their caregivers, 2 were injured, 9 had family legal issues, and one no longer attended for unknown reasons.

Procedure

After informed consent was obtained from primary caregivers, two designated staff members, the director of the organization, and the educational supervisor responded to questions regarding the child participants. Staff members consented prior to their participation at both baseline and 1-year follow-up. Staff reports of child measures were obtained electronically, using Medialab interview software. The educational supervisor was chosen specifically for his high frequency of interaction with the children in structured, academic settings (e.g., computer lab, life skills training, tutoring sessions). Director reports of child demographic information and disciplinary records were collected. The educational supervisor interviews were completed in less than 10 minutes per child and he was compensated $3.00 per child at baseline and he received a $250 gift card at follow-up (approximately $3.40 per child). The director interviews were completed in less than 5 minutes per child and the director was compensated $2.00 per child at baseline and received a $250 gift card at follow-up (approximately $3.40 per child). The same two staff members provided reports on child participants at baseline and at follow-up.

Measures

ADHD and ODD symptoms

The educational supervisor reported on the ADHD and ODD items of the Disruptive Behavior Disorder checklist (DBD; Pelham, Gnagy, Greenslade, & Milich, 1992). Responses on the items were recorded using a scale from 1 = not at all to 4 = very much. The nine inattention and nine hyperactivity/impulsivity ADHD items and eight ODD items were dichotomously re-coded to indicate whether or not the child demonstrated the symptom. Based on previous literature (Milich, Hartung, Martin, & Haigler, 1993), DBD items rated as occurring pretty much or very much (three or four) were considered to be valid, positive endorsements of a symptom. Sum scores of this count variable were computed and used for analyses. The internal consistencies of the total ADHD symptoms, inattention symptoms, and hyperactivity/impulsivity symptoms were very good (all αs = .99). The internal consistency of the ODD symptoms was also very good (α = .97). ADHD symptom scores ranged from 0 to 18 and ODD symptom scores ranged from 0 to 8.

Rule-breaking

Reports from the educational supervisor were obtained on the rule-breaking behavior scale of the Teacher Report Form (TRF; Achenbach & Rescorla, 2001). The measure consists of 12 items including “swearing or obscene language,” “steals,” and “doesn’t seem to feel guilty after misbehaving.” Responses were obtained using the following scale: 1 = not true, 2 = somewhat or sometimes true, 3 = very or often true. Note that program staff reports of teacher measures have been found to be valid and reliable indicators of child behavior (e.g., Cicchetti & Rogosch, 1997). Sum scores were computed and used for analyses. The internal consistency of the rule-breaking behavior scale was good (α = .89). Scores range from 1.0–2.0 at baseline and 1.0–2.1 at follow-up.

Disciplinary actions

The director utilized formal chart review to report the number of times documented disciplinary action (i.e., write-ups) took place for each child at baseline and 1 year later. Note that the program is a licensed daycare facility, receiving the highest star rating possible from the state. The program meets all state-mandated staff to child ratios and the entire facility is under 24-hour video surveillance, providing sufficient monitoring of child behavior and the ability to substantiate any behavior that may be questioned. Disciplinary write-ups result from more serious behavior, or minor misbehavior that has not ceased despite several attempts to correct the behavior. Reasons for write-ups include: fighting, sexually inappropriate behavior, cursing or inappropriate language, repeatedly refusing to follow directions, destruction of property, and stealing. Within the organization only two staff members can impose a formal write-up, the Organization Director and the Program Director, providing consistency over what behaviors result in formal disciplinary action. At baseline data collection, the number of disciplinary write-ups over the past academic year (approximately 6 months) was reported and at follow-up, the number of disciplinary write-ups within the past calendar year was reported. A 5-point Likert scale (1 = zero, 2 = once, 3 = twice, 4 = 3 times, and 5 = 4 or more) was used.

Data analyses

Study hypotheses were examined using structural equation models that were estimated in AMOS 18.0. One study variable, T2 rule-breaking behavior, exceeded a skewness value of 3 (skewness = 3.2); however, maximum likelihood estimation is relatively robust against such levels of nonnormality (Kline, 2010), accordingly maximum likelihood estimation was used. More specifically, full information maximum likelihood estimation (FIMLE) was used with the proposed data-analytic strategy to accommodate missing data. Up to 50% missing data is not a concern when using FIMLE (Arbuckle, 1996). FIMLE uses all available data to calculate parameter estimates and does not exclude missing data (Kline, 2010). FIMLE has been found to be less biased and more efficient than other strategies, such as pairwise and listwise deletion, to accommodate missing data (Arbuckle, 1996).

Based on guidelines from Hu and Bentler (1999), and what is commonly used in the structural equation modeling literature, model fit was determined using the following cutoff criteria. A good fit to the data was determined by χ² /df < 2, Comparative Fit Index (CFI) > .95 and Root Means Square Error of Approximation (RMSEA) < .08.

Meeker’s Test was used to examine meditational paths. This method has been found to provide a more accurate balance between Type I and Type II errors than other methods used to test indirect effects such as Sobel’s method (MacKinnon, Lockwood, & Williams, 2004). Using Meeker’s table of upper and lower values, 95% confidence intervals (CIs) were used to test the significance of the indicated indirect effects.

Results

Participant retention

Data was collected on 147 participants at baseline and 74 participants at 1-year follow-up. There were no significant differences between included and dropped (no longer attending the organization) participants in age (t = 1.2, p = 23), gender (χ² = .57, p = 45), race (χ² = 2.8, p = .09), rule-breaking (t = 1.4, p = .18), or ADHD symptoms (t = 1.57, p = .12). This suggests that participant dropout was not related to any specific variable that was evaluated in the study. As expected, those removed from the program for behavioral issues (n = 7) exhibited higher levels of baseline ADHD symptoms (t = −2.4, p = .02), rule-breaking behavior (t = −3.2, p = .002), and disciplinary actions (t = −3.2, p = .002) than those who left the program for other reasons. However, this represents less than 5% of study participants, and did not result in overall analyses of follow-up participant differences, therefore it does not impact the assumption of data being missing at random (MAR). Thus, data was presumed to be MAR, further supporting FIMLE as the appropriate missing data analytic strategy (Arbuckle, 1996).

Descriptive statistics by gender

Correlations, means, standard deviations and gender differences of study variables are reported in Table 2 . Overall, children had on average 4.1 ADHD symptoms (Inattentive: M = 2.1, SD = 3.6; Hyperactive/Impulsive: M = 2.0, SD = 3.5). Boys had significantly higher rates of all types of ADHD symptoms. With regard to overall discipline, at baseline 55% of the children had received no write-ups, 7% received one write-up, 9.5% received two write-ups, 4% received three write-ups, and 24.5% received four or more write-ups. At the 1-year follow-up, approximately 66% received no write-ups, 12% received one write-up, 13.5% received two write-ups, 1.5% received three write-ups and 7% received four or more write-ups. Boys also had more disciplinary write-ups at baseline; however, there were no gender differences in discipline at follow-up.

Table 2.

Correlations, means, standard deviations and gender differences of study variables

	Girls (N = 67)							Boys (N = 80)
Variable	1	2	3	4	5	6	7	1	2	3	4	5	6	7	t
1. ADHD Total T1	—							—							−2.17^*
2. ADHD Inattentive T1	—	—						—	—						−2.26^*
3. ADHD Hyperactive/ Impulsive T1	—	.95^***	—					—	.94^***	—					−2.01^*
4. Rule-breaking T1	.74^***	.76^***	.72^***	—				.79^***	.77^***	.78^***	—				−1.20
5. Discipline T1	.49^***	.47^***	.50^***	.58^***	—			.52^***	.50^***	.52^***	.64^***	—			−3.33^**
6. Rule-breaking T2	.53^***	.48^**	.56^***	.68^***	.59^***	—		.77^***	.74^***	.80^***	.73^***	.53^***	—		−1.16
7. Discipline T2	−.09	−.12	−.06	.07	−.06	.13	—	.54^***	.51^**	.56^***	.52^**	.68^***	.66^***	—	−1.27
M	2.72	1.36	1.36	1.16	1.87	1.05	1.54	5.23	2.70	2.53	1.22	2.78	1.11	1.89
SD	6.10	3.09	3.09	0.27	1.53	0.18	0.94	7.64	3.95	3.81	0.31	1.74	0.26	1.39

Note.

^* p < .05;

^** p < .01;

^*** p < .001.

T1 = Time 1, T2 = Time 2, ADHD = ADHD symptoms, Discipline = disciplinary write-ups.

Path model

As seen in Figure 1, baseline ADHD symptoms were examined as predictors of rule-breaking behavior and disciplinary actions 1 year later, and rule-breaking was also examined as a predictor of disciplinary actions. Baseline levels of rule-breaking and disciplinary actions were controlled for in order to predict change over time in these variables. Note that age and race were originally included as covariates in the model; however, preliminary analyses suggested that age and race were not significant predictors of either rule-breaking behavior or discipline. Therefore, age and race were not included in the final model.

Figure 1.

Consequences of total ADHD symptoms path model. N = 147. Standardized and unstandardized (in parentheses) estimates are reported. Estimates for the disturbances (D1/D2) are proportions of unexplained variance. Covariances are not included for clarity purposes. *p < .05; **p < .01; ***p < .001.

The model provided a good fit to the data, χ²(2) = 1.99, χ²/df = 0.99, CFI = 1.00, RMSEA = 0.00. Results suggested that ADHD symptoms were positively associated with T2 rule-breaking behavior above and beyond T1 rule-breaking behavior, such that high levels of ADHD symptoms predicted increases in T2 rule-breaking behavior. T2 rule-breaking behavior was associated with T2 discipline, above and beyond T1 discipline, such that high levels of rule-breaking behavior were associated with increases in disciplinary “write-ups.” Furthermore, the test of indirect effects suggested that T2 rule-breaking behavior accounted for the relation between T1 ADHD symptoms and T2 discipline, B = 0.02, 95% CI (.002, .044). That is, high levels of ADHD symptoms predicted high levels of rule-breaking behavior, which in turn was associated with increases in discipline.

Gender effects

A multiple group model was then estimated in order to determine if this mediated pathway was invariant across gender groups. The unconstrained model yielded a good fit to the data, χ²(4) = 4.03, χ²/df = 1.01, CFI = 1.00, RMSEA = 0.01. Next, we constrained each causal path and covariance to be equal across the gender groups one at a time (eight separate models). The χ² diff test was then used to determine which model constraints resulted in a significant decrement in model chi-square. Constraints that result in a significant decrement in the model chi-square indicate gender differences. Results indicated that only two paths caused a significant decrement in the model fit, the path from ADHD to T2 rule-breaking, ▵χ²(1) = 5.0, p < .05, and the path from T1 to T2 disciplinary actions, ▵χ²(1) = 7.1, p < .05. Next we used a step-back approach, comparing a multiple group model with all paths constrained to be equal across groups, χ²(12) = 29.3, CFI = 0.93, RMSEA = 0.10, to a model with all parameters except the two paths constrained to be equal across the groups, χ²(10) = 10.2, CFI = 0.99, RMSEA = 0.01. The χ² diff test revealed that the model with all causal paths constrained to be equal except the two specified paths resulted in a significant improvement in model chi-square, ▵χ² (2) = 19.1, p < .05, indicating that the relation between ADHD and rule-breaking and the relation between T1 and T2 disciplinary actions vary by gender. Therefore, the model that constrained all paths to be equal with the exception of these two paths was retained, and as reported above, this model provided a good fit to the data. For boys, ADHD symptoms predicted increases in rule-breaking behavior; however, this association was not significant for girls. Also, high levels of T1 discipline predicted high levels of T2 discipline for boys, but not for girls. Testing the indirect effects for boys, ADHD symptoms were associated with T2 discipline through T2 rule-breaking behavior, B = 0.05, 95% CI (.045, .047).

Path model of ADHD symptom dimensions

A second path model that included both inattentive- and hyperactive/impulsive-type symptoms of ADHD as predictors of rule-breaking behavior and disciplinary actions at follow-up was then examined (see Figure 2 ). The model provided a very good fit to the data, χ²(2) = 1.01, χ²/df = 0.50, CFI = 1.00, RMSEA = 0.00. Results suggested that ADHD symptom dimensions were differentially associated with rule-breaking behavior above and beyond baseline levels of rule-breaking behavior. While taking into account the variance associated with the other dimension, high levels of hyperactivity/impulsivity symptoms were positively associated with rule-breaking behavior and inattention symptoms were negatively associated with rule-breaking behavior. Rule-breaking behavior was associated with discipline at follow-up, above and beyond baseline levels of discipline, such that high levels of rule-breaking behavior were associated with increases in disciplinary “write-ups.” The test of indirect effects suggested that rule-breaking behavior accounted for the relation between hyperactivity/impulsivity symptoms and discipline, B = 0.12, 95% CI (.02, .23). That is, high levels of hyperactivity/impulsivity predicted high levels of rule-breaking behavior, which in turn was associated with increases in discipline.¹

Figure 2.

Consequences of subtypes of ADHD symptoms path model. N = 147. Standardized and unstandardized (in parentheses) estimates are reported. Estimates for the disturbances (D1/D2) are proportions of unexplained variance. Covariances are not included for clarity purposes. ⁺ p < .06, *p < .05; **p < .01; ***p < .001.

Gender effects on ADHD symptom dimensions

The multiple group model was then estimated in order to determine if the mediated pathway of hyperactivity/impulsivity symptoms to discipline was invariant across gender groups. The unconstrained model yielded a good fit to the data, χ²(4) = 7.38, χ²/df = 1.85, CFI = 0.99, RMSEA = 0.076. Next, we constrained each causal path and covariance to be equal across the gender groups individually. The χ² diff test was then used to determine which model constraints resulted in gender differences. Results indicated that two paths caused a significant decrement in the model fit, the path from baseline to follow-up rule-breaking, ▵χ²(1) = 10.2, p < .05, and the path from baseline to follow-up disciplinary actions, ▵χ²(1) = 6.6, p < .05. Next we used a step-back approach, comparing a multiple group model with all paths constrained to be equal across groups, χ²(17) = 44.0, CFI = 0.96, RMSEA = 0.11, to a model with all parameters except the two paths constrained to be equal across the groups, χ²(15) = 27.4, CFI = 0.98, RMSEA = 0.076. The χ² diff test revealed that the model with all causal paths constrained to be equal except the two specified paths resulted in a significant improvement in model chi-square, ▵χ² (2) = 16.6, p < .05, indicating that the stability of rule-breaking behavior and the stability of disciplinary actions vary by gender. Thus, the model that constrained all paths to be equal with the exception of these two paths was retained, and as reported above, this model provided a good fit to the data. Findings indicated that mediated paths were equivalent for boys and girls. However, for girls the stability of rule-breaking behavior was stronger than it was for boys. In contrast, the stability of disciplinary actions is stronger for boys than for girls.

Accounting for ODD symptoms

Prior research suggests that ADHD and ODD symptoms overlap considerably, and both are related to subsequent problem behavior (e.g., Biederman et al., 2007; Goldman et al., 1998). Indeed, ADHD and ODD symptoms were highly correlated in the current sample, r = .80, p < .0001. Furthermore, both ADHD and ODD symptoms were positively correlated with rule-breaking behavior, rs = 69 and .68, ps < .0001, for ADHD and ODD, respectively, and with disciplinary actions, rs = .32 and .26, ps < .03. Therefore, we also evaluated models in which ODD symptoms were included as a covariate in order to determine whether ADHD symptoms were associated with rule-breaking behavior over and above their statistical overlap with ODD symptoms. The path model continued to provide a good fit to the data, χ²(2) = 1.99, χ²/df = 1.00, CFI = 1.00, RMSEA = 0.00; however, results suggested that ODD symptoms did not uniquely predict T2 rule-breaking behavior, β = .03, p = .87. In contrast, paths associated with ADHD symptoms remained significant and stable, with ADHD symptoms uniquely predicting T2 rule-breaking behavior, β = .27, p = .04. Further, the inclusion of ODD symptoms in the model did not affect the moderating effects of gender on the mediated pathways from ADHD symptoms to disciplinary actions. Additionally, significant effects for hyperactivity symptoms remained, β = .84, p < .001, when including ODD symptoms in the ADHD dimensions models. Findings suggest that once taking into account the overlapping variance of ADHD and ODD, only the unique effects of ADHD are associated with rule-breaking behavior. Thus, it appears that ADHD symptoms are uniquely and robustly associated with rule-breaking behavior, above and beyond their shared variance with ODD symptoms.

Discussion

The current study examined rule-breaking behavior as a mediator of the relation between ADHD symptoms and disciplinary actions in a community-based after-school program while also controlling for the stability of rule-breaking behavior and disciplinary actions and the variance associated with ODD symptoms. Findings suggested that overall ADHD symptoms positively predict disciplinary actions through rule-breaking behavior, such that high ADHD symptom counts predicted increases in rule-breaking behavior 1 year later, which in turn was associated with increases in disciplinary actions. However, these associations were only found for boys, not girls, when overall symptom counts were examined. In further examining ADHD symptom dimensions, results indicated that hyperactivity/impulsivity symptoms were responsible for the link between ADHD symptoms and rule-breaking behavior. When taking into account the shared variance with the other dimension, the unique variance associated with inattention symptoms negatively predicted rule-breaking behavior 1 year later. Further, note that no gender differences were found in the paths from ADHD symptom dimensions to disciplinary actions.

Rule-breaking significantly accounted for the effects of ADHD symptoms (hyperactivity/impulsivity symptoms specifically) on disciplinary actions as expected. Findings are consistent with previous literature suggesting that children with ADHD engage in high levels of rule-breaking behavior and receive more disciplinary referrals at school (e.g., Molina et al., 2001), and our findings suggest that these effects are over and above the ODD symptoms. This suggests that children with ADHD would benefit from behavioral interventions that target rule-breaking behavior in order to avoid disciplinary consequences and possible program suspension or expulsion. Moreover, children who continue to engage in this behavior may be labeled as “troublemakers,” resulting in teachers and other authority figures treating these children with more stringent and often unfair tolerance policies (Cassidy & Jackson, 2005). Additionally, early intervention is particularly important for children who are at risk of future disciplinary problems, as a lack of participation in structured organized activities increases risk of substance use, truancy, and poor educational outcomes (e.g., Anderson-Butcher et al., 2003).

Importantly, however, the overall ADHD model was moderated by gender, such that rule-breaking behavior was a significant mediator of the link between total ADHD symptoms and disciplinary actions for boys, but not for girls. More specifically, the relation between total ADHD symptoms and rule-breaking behavior was significant for boys only. Although there was a positive correlation between ADHD symptoms and rule-breaking behavior for both genders, when taking into account the stability of rule-breaking, ADHD symptoms were not associated with increases in rule-breaking behavior for girls.

In contrast, however, when examining ADHD by symptom dimensions, boys and girls showed similar associations with rule-breaking behavior, and the mediated pathway was evident across genders. It seems that regardless of gender, hyperactivity/impulsivity symptoms are associated with rule-breaking behavior, which puts children at risk of disciplinary action. This finding is consistent with literature suggesting hyperactivity and impulsivity developing into future problem behavior, including legal consequences (e.g., Farrington, Loeber, & Van Kammen, 1990).

Gender inconsistencies across the models may be due to the difference in levels of severity in ADHD symptoms between boys and girls. Boys have almost three more symptoms of ADHD on average than girls and this may influence their development of rule-governed behavior (Barkley, 1997), particularly when examining hyperactivity/impulsivity and inattentive symptoms together. Since boys demonstrate a higher number of ADHD symptoms, they may be slower to develop rule-governed behavior (Barkley, 1997). Furthermore, the increased levels of ADHD symptoms in boys may have also increased the power to detect associations between ADHD and other study variables for boys. Yet when specifically examining hyperactivity/impulsivity symptoms, the link between these ADHD symptoms and rule-breaking behavior is evident for both genders. This suggests that the link between hyperactivity/impulsivity symptoms and rule-breaking behavior are strong, and evident even at lower symptom counts found in girls.

The findings also suggested that the stability of rule-breaking behavior was stronger for girls and the stability of disciplinary actions was stronger for boys. The implications of these findings seems to be that the same girls continue to exhibit rule-breaking behavior, while the same boys continue to be disciplined. Thus, it appears that write-ups (and their subsequent consequences) may be less effective for boys and different behavioral strategies should be considered (e.g., contingency management techniques). Further, correlational findings revealed that girls’ symptoms of ADHD and rule-breaking behavior at baseline were not associated with disciplinary problems at follow-up. Thus, it seems that other factors are involved. It may be that peer difficulties are causing disciplinary problems for girls. Girls are more likely to experience relational victimization in friendships than boys, who experience more physical victimization (Crick & Nelson, 2002). These relational peer problems are likely not captured under the traditional rule-breaking behaviors, but may still warrant disciplinary action for behaviors such as verbal aggression and rejection. Thus, there is evidence to suggest that gender differences in correlates of disciplinary actions for children exist.

The results of this study cannot be presented without referring to its limitations. First, only data for 50% of the original sample was collected at follow-up. This rate of organizational attendance is consistent with the retention rates of the organization. Although higher retention rates would be ideal, it is unrealistic within this setting. In addition, ADHD symptoms and rule-breaking behavior were assessed by staff report. ADHD symptoms and rule-breaking behavior may have been more highly correlated with the same reporter than if assessed with different reporters. Note that other studies have used staff report (e.g., Cicchetti & Rogosch, 1997) to assess child behavior; nonetheless it would be beneficial for future research to obtain parent and teacher reports to replicate study findings. In addition, it would have been useful to further examine pathways from ADHD symptoms to more serious outcomes, such as permanent removal from the program. However, we were unable to examine this association in the current sample, as the group of participants removed from the program was small (n = 7) and no specific follow-up data was available for these individuals. Future studies should examine pathways from ADHD to more serious outcomes (i.e., expulsion, delinquent behavior). Further, although we feel a strength of this study was the use of official records of disciplinary actions, some behaviors may have gone unnoticed or unreported. We, however, believe that the use of video monitoring aids in the validity of this datum. However, in the future it would be useful to also include video recordings and observational coding of children’s behavior. Finally, note that the current study included school-age children. Findings may not generalize to other development age groups.

Despite these limitations, the results show that rule-breaking accounts for the relation between ADHD symptoms (hyperactivity/impulsivity symptoms specifically) and disciplinary actions in at-risk children. Furthermore, when examining a total ADHD measure these associations were only significant for boys; however, when examining ADHD symptom dimensions these gender differences were not evident. While rule-breaking behavior often occurs in children with other disruptive behavior disorder symptoms, it may be expressed more frequently in an after-school setting, particularly in children with ADHD symptoms. After-school programs tend to have less structure and consistency than school classrooms and for children who lack self-control, this setting may offer more opportunities for rule-breaking behavior. Thus, this study provided a unique setting for the behavioral consequences of ADHD symptoms to be examined. Further, when controlling for ODD symptoms in the model, ADHD and not ODD symptoms uniquely predicted rule-breaking behavior at follow-up, suggesting these ADHD effects were above and beyond the effects of ODD symptoms. Therefore, the behavioral consequences of ADHD may be more profound than ODD in an after-school setting where the less structured environment is more conducive to rule-breaking. In addition, examining symptom counts in an at-risk sample allowed the study to examine a wide range of variability in ADHD symptoms and relations to behavioral consequences. Findings also have many implications for our understanding of these associations and treatment. First, findings appear to indicate that rule-breaking behavior is an important target of intervention in the prevention of disciplinary action for those who exhibit symptoms of ADHD, and that this effect is particularly relevant for those who exhibit high levels of hyperactivity/impulsivity symptoms. Second, findings indicate that gender differences may or may not be evident, depending on how ADHD symptoms are assessed.

Given the moderating effect of gender found when examining total symptom counts of ADHD, interventions to prevent rule-breaking and program suspension may want to consider gender. Findings may suggest that boys who suffer from symptoms of ADHD may benefit from interventions that target less rule-breaking behavior, which may include supervision and other positive parenting strategies (Chronis, Chacko, Fabiano, Wymbs, & Pelham, 2004). For girls exhibiting symptoms of ADHD, it may be that strategies that focus on improving peer relationships may be beneficial. That is, some evidence suggests that peer group identification is more important for girls than boys, and this impacts peer influence on behavior (Kiesner, Cadinu, Poulin, & Bucci, 2002). Thus, future research should examine the role of peers in these associations, particularly for girls.

In contrast, findings appear to indicate that regardless of gender, those who exhibit symptoms of hyperactivity/impulsivity need to be targeted for the prevention of rule-breaking behavior. Interventions for both genders will likely need to address behavioral interventions, such as goal setting, behavioral contracts, and other strategies designed to increase self-control (DuPaul & Stoner, 2003).

Footnotes

Notes

References

Abikoff

H. B.

Jensen

P. S.

Arnold

L. L. E.

Hoza

Hechtman

Pollack

…Wigal

. (2002). Observed classroom behavior of children with ADHD: Relationship to gender and comorbidity. Journal of Abnormal Child Psychology, 30, 349–359.

Achenbach

T. M.

Rescorla

L. A.

(2001). Manual for ASEBA school-age forms and profiles. Burlington: University of Vermont, Research Center for Children, Youth, and Families.

American Psychiatric Association (APA). (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: American Psychiatric Association.

Anderson

Hinshaw

Simmel

(1994). Mother–child interactions in ADHD and comparison boys: Relationships with overt and covert externalizing behavior. Journal of Abnormal Child Psychology, 22, 247–265.

Anderson-Butcher

Newsome

W. S.

Ferrari

T. M.

(2003). Participation in boys and girls clubs and relationships to youth outcomes. Journal of Community Psychology, 31, 39–55.

Arbuckle

J. L.

(1996). Full information estimation in the presence of incomplete data. Mahwah, NJ: Lawrence Erlbaum Associates.

Barkley

R. A.

(1990). Attention deficit hyperactivity disorder: A handbook for diagnosis and treatment. New York, NY: Guilford Press.

Barkley

R. A.

(1997). ADHD and the nature of self-control. New York, NY: Guilford Press.

Bauermeister

J. J.

Shrout

P. E.

Chavez

Rubio-Stipec

Ramirez

Padilla

…Canino

. (2007a). ADHD and gender: are risks and sequela of ADHD the same for boys and girls? Journal of Child Psychology & Psychiatry, 48, 831–839.

10.

Bauermeister

J. J.

Shrout

P. E.

Ramirez

Bravo

Alegria

Martinez-Taboas

…Canino

. (2007b). ADHD correlates, comorbidity, and impairment in community and treated samples of children and adolescents. Journal of Abnormal Child Psychology, 35, 883–898.

11.

Biederman

Faraone

S. V.

Milberger

Jetton

J. G.

Chen

Mick

…Russell

R. L

. (1996). Is childhood oppositional defiant disorder a precursor to adolescent conduct disorder? Findings from a four-year follow-up study of children with ADHD. Journal of the American Academy of Child & Adolescent Psychiatry, 35, 1193–1204.

12.

Biederman

Kwon

Aleardi

Chouinard

V.-A.

Marino

Cole

…Faraone

S. V

. (2005). Absence of gender effects on attention deficit hyperactivity disorder: Findings in nonreferred subjects. The American Journal of Psychiatry, 162, 1083–1089.

13.

Biederman

Mick

Faraone

S. V.

Braaten

Doyle

Spencer

…Johnson

M. A

. (2002). Influence of gender on attention deficit hyperactivity disorder in children referred to a psychiatric clinic. The American Journal of Psychiatry, 159, 36–42.

14.

Biederman

Spencer

Newcorn

Gao

Milton

Feldman

Witte

(2007). Effect of comorbid symptoms of oppositional defiant disorder on responses to atomoxetine in children with ADHD: A meta-analysis of controlled clinical trial data. Psychopharmacology, 190, 31–41.

15.

Campbell

S. B.

Pierce

E. W.

Moore

Marakovitz

Newby

(1996). Boys’ externalizing problems at elementary school age: Pathways from early behavior problems, maternal control, and family stress. Development and Psychopathology, 8, 701–719.

16.

Campbell

S. B.

Shaw

D. S.

Gilliom

(2000). Early externalizing behavior problems: Toddlers and preschoolers at risk for later maladjustment. Development and Psychopathology, 12, 467–488.

17.

Carlson

C. L.

Shin

Booth

(1999). The case for DSM-IV subtypes in ADHD. Mental Retardation and Developmental Disabilities Research Reviews, 5, 199–206.

18.

Cassidy

Jackson

(2005). The need for equality in education: An intersectionality examination of labeling and zero tolerance practices. McGill Journal of Education, 40, 435–456.

19.

Chronis

A. M.

Chacko

Fabiano

G. A.

Wymbs

B. T.

Pelham

W. E.

(2004). Enhancements to the behavioral parent training paradigm for families of children with ADHD: Review and future directions. Clinical Child and Family Psychology Review, 7, 1–27.

20.

Cicchetti

Rogosch

F. A.

(1997). The role of self-organization in the promotion of resilience in maltreated children. Development and Psychopathology, 9, 797–815.

21.

Connor

D. F.

Edwards

Fletcher

K. E.

Baird

Barkley

R. A.

Steingard

R. J.

(2003). Correlates of comorbid psychopathology in children with ADHD. Journal of the American Academy of Child & Adolescent Psychiatry, 42, 193–200.

22.

Crick

N. R.

Nelson

D. A.

(2002). Relational and physical victimization within friendships: Nobody told me there’d be friends like these. Journal of Abnormal Child Psychology, 30, 599–607.

23.

DuPaul

G. J.

Stoner

G. D.

(2003). ADHD in the schools: Assessment and intervention strategies. New York, NY: Guilford Press.

24.

Eccles

J. S.

Barber

B. L.

Stone

Hunt

(2003). Extracurricular activities and adolescent development. Journal of Social Issues, 59, 865–889.

25.

Evans

S. W.

Langberg

Raggi

Allen

Buvinger

E. C.

(2005). Development of a school-based treatment program for middle school youth with ADHD. Journal of Attention Disorders, 9, 343–353.

26.

Farrington

D. P.

Loeber

Van Kammen

W. B.

(1990). Long-term criminal outcomes of hyperactivity–impulsivity–attention deficit and conduct problems in childhood. In Robins

Rutter

(Eds.), Straight and devious pathways from childhood to adulthood (pp. 62–81). Cambridge, UK: Cambridge University Press.

27.

Frick

P. J.

Christian

R. E.

Wootton

J. M.

(1999). Age trends in the association between parenting practices and conduct problems. Behavior Modification, 23, 106–128.

28.

Gershon

(2002). A meta-analytic review of gender differences in ADHD. Journal of Attention Disorders, 5, 143–154.

29.

Gibbs

J. T.

(1998). High-risk behaviors in African-American youth: Conceptual and methodological issues in research. In McLoyd

V. C.

Steinberg

(Eds.), Studying minority adolescents: Conceptual, methodological, and theoretical issues (pp. 55–86). Mahwah, NJ: Lawrence Erlbaum Associates.

30.

Goldman

L. S.

Genel

Bezman

R.J.

Slanetz

P.J.

(1998) Diagnosis and treatment of attention-deficit/hyperactivity disorder in children and adolescents. Journal of the American Medical Association, 279, 1100–1107.

31.

Gomez

Harvey

Quick

Scharer

Harris

(1999). DSM-IV AD/HD: Confirmatory factor models, prevalence, and gender and age differences based on parent and teacher ratings of Australian primary school children. Journal of Child Psychology and Psychiatry, 40, 265–274.

32.

Gresham

F. M.

Lane

K. L.

Lambros

K. M.

(2000). Comorbidity of conduct problems and ADHD: Identification of “fledging psychopaths”. Journal of Emotional and Behavioral Disorders, 8, 83–93.

33.

Hinshaw

S. P.

(1992). Academic underachievement, attention deficits, and aggression: Comorbidity and implications for intervention. Journal of Consulting and Clinical Psychology, 60, 893–903.

34.

Hoza

(2007). Peer functioning in children with ADHD. Journal of Pediatric Psychology, 32, 655–663.

35.

Bentler

P. M.

(1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.

36.

Hummer

T. A.

Kronenberger

W. G.

Wang

Dunn

D. W.

Mosier

K. M.

Kalnin

A. J.

Mathews

V. P.

(2011). Executive functioning characteristics associated with ADHD comorbidity in adolescents with disruptive behavior disorders. Journal of Abnormal Child Psychology, 39, 11–19.

37.

Kiesner

Cadinu

Poulin

Bucci

(2002). Group identification in early adolescence: Its relation with peer adjustment and its moderator effect on peer influence. Child Development, 73, 196–208.

38.

Kline

R. B.

(2010). Principles and practice of structural equation modeling (3rd ed.). New York, NY: Guilford Press.

39.

Levy

Hay

D. A.

Bennett

K. S.

McStephen

(2005). Gender differences in ADHD subtype comorbidity. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 368–376.

40.

MacKinnon

D. P.

Lockwood

C. M.

Williams

(2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39, 99–128.

41.

Mannuzza

Klein

R. G.

Abikoff

Moulton

J. L.

(2004). Significance of childhood conduct problems to later development of conduct disorder among children with ADHD: A prospective follow-up study. Journal of Abnormal Child Psychology, 32, 565–573.

42.

Milich

Hartung

C. M

Martin

Haigler

E. D

. (1993). Behavioral disinhibition and underlying processes in adolescents with disruptive behavior disorders. In Routh

(Ed.), Disruptive behavior disorders in childhood (pp. 109–138). New York, NY: Plenum.

43.

Moffitt

T. E.

(1990). Juvenile delinquency and attention deficit disorder: Boys’ developmental trajectories from age 3 to age 15. Child Development, 61, 893–910.

44.

Molina

Smith

Pelham

(2001). Factor structure and criterion validity of secondary school teacher ratings of ADHD and ODD. Journal of Abnormal Child Psychology, 29, 71–82.

45.

Newcorn

J. H.

Halperin

J. M.

Jensen

P. S.

Abikoff

H. B.

Arnold

L. E.

Cantwell

D. P.

…Vitiello

. (2001). Symptom profiles in children with ADHD: Effects of comorbidity and gender. Journal of the American Academy of Child & Adolescent Psychiatry, 40, 137–146.

46.

Ohlmeier

M. D.

Peters

Te Wildt

B. T.

Zedler

Ziegenbein

Wiese

…Schneider

. (2008). Comorbidity of alcohol and substance dependence with attention-deficit/hyperactivity disorder (ADHD). Alcohol and Alcoholism, 43, 300–304.

47.

Pelham

W. E.

Jr. Gnagy

E. M.

Greenslade

K. E.

Milich

(1992). Teacher ratings of DSM-III-R symptoms for the disruptive behavior disorders. Journal of the American Academy of Child & Adolescent Psychiatry, 31, 210–218.

48.

Pihl

R. O.

Peterson

J. B.

(1991). Attention-deficit hyperactivity disorder, childhood conduct disorder, and alcoholism: Is there an association? Alcohol Health and Research World, 15, 25–31.

49.

Thapar

Harrington

McGuffin

. (2001). Examining the comorbidity of ADHD-related behaviours and conduct problems using a twin study design. British Journal of Psychiatry, 179, 224–229.

50.

Thompson

L. T.

Riggs

P. D.

Mikulich

S. K.

Crowley

T. J.

(1996). Contribution of ADHD symptoms to substance problems and delinquency in conduct-disordered adolescents. Journal of Abnormal Child Psychology, 24, 325–347.

51.

Tobin

T. J.

Sugai

G. M.

(1999). Using sixth-grade school records to predict school violence, chronic discipline problems, and high school outcomes. Journal of Emotional and Behavioral Disorders, 7, 40–53.

52.

Walker

H. M.

Sprague

J. R.

(1999). The path to school failure, delinquency, and violence: Causal factors and some potential solutions. Intervention in School and Clinic, 35, 67–73.

53.

Waschbusch

D. A.

(2002). A meta-analytic examination of comorbid hyperactive-impulsive-attention problems and conduct problems. Psychological Bulletin, 128, 118–150.

54.

Willcutt

E. G.

Chhabildas

Pennington

B. F.

(2001). Validity of the DSM-IV subtypes of ADHD. The ADHD Report, 9, 2–5.

55.

Zalecki

C. A.

Hinshaw

S. P.

(2004). Overt and relational aggression in girls with attention deficit hyperactivity disorder. Journal of Clinical Child & Adolescent Psychology, 33, 125–137.