Investigation of the Heterogeneity of Disruptive Behaviour in Elementary-Age Children

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1 Investigation of the Heterogeneity of Disruptive Behaviour in Elementary-Age Children DANIEL A. WASCHBUSCH, STEPHEN PORTER, NORMAND CARREY, S. OMAR KAZMI, KERRY A. ROACH, and DELIA A. D AMICO, Dalhousie University Northern Region Partners in Action for Children and Youth Abstract We evaluated parent and teacher ratings of a large sample (N = 1579) of elementary-school children in Canada to determine how different conceptualizations of disruptive behaviour are co-related and related to other measures of functioning. Parent and teacher ratings were consistent, and suggested three separate but correlated aspects of disruptive behaviour in children: (1) reactive/oppositional behaviour, (2) proactive/callous behaviour; and (3) inattention-impulsive-overactive behaviour. These were uniquely and significantly related to DSM-IV diagnostic scores and to other measure of impairment, indicating that they measure distinct aspects of disruptive behaviour in children. Résumé Nous avons évalué les évaluations des parents et enseignants d un grand échantillon (N = 1579) d enfants canadiens à l école élémentaire afin de déterminer comment différentes conceptualisations d un comportement perturbateur sont interreliées et reliées à d autres mesures du fonctionnement. L appréciation des parents et des enseignants était uniforme et suggérait trois aspects distincts mais coreliés de comportement perturbateur chez l enfant : 1) comportement réactif/oppositionnel, 2) comportement proactif/sans pitié et 3) comportement d inattention-impulsif-hyperactif. Ces comportements se rapportaient de façon unique et significative aux scores de diagnostic DSM-IV et à d autres mesures de déficience, indiquant qu ils mesurent des aspects distincts du comportement perturbateur chez l enfant. Disruptive behaviour is a prevalent societal problem, affecting about 5% to 10% of elementary-school children (e.g., Offord, Boyle, Fleming, Blum, & Grant, 1989). Children with disruptive behaviour problems tend to have fewer friends, struggle academically, and have impaired family relationships (Connor, 2002). Disruptive children also negatively affect others in their environment as peer targets of disruptive children s actions experience higher rates of depression, anxiety, and school failure (Perry, Kusel, & Perry, 1988). The financial costs also are considerable since disruptive behaviour is one of the most common reasons for referrals to pediatric health clinics (R. T. Brown et al., 2001) and to special education services in schools (Jerome, Gordon, & Hustler, 1994). Unfortunately, disruptive behaviour in children is often not a temporary condition that children outgrow. Instead, disruptive behaviour shows considerable stability over the lifespan (Loeber, 1982; Loeber & Dishion, 1983) and has much forensic relevance. A number of studies have found that 50% to 70% of children who exhibit serious disruptive behaviour in childhood and adolescence are arrested in adulthood (Loeber, 1990), with about 40% of children with disruptive behaviour problems developing antisocial personality disorder as adults (Lahey & Loeber, 1997). In fact, there is growing evidence that persistent disruptive behaviour in childhood is a developmental precursor to child and adolescent delinquency, which is in turn a developmental precursor to serious, violent, and chronic antisocial behaviour in late adolescence and adulthood (Loeber & Farrington, 2001). These and other data argue that gaining a greater understanding of disruptive behaviour in childhood should be an important focus for forensic psychology. Researchers, clinicians, legal professionals, and others who work with disruptive children are likely to agree that the general category disruptive child behaviour is overly broad. To reduce this heterogeneity, disruptive behaviour is often distinguished into specific subtypes. One commonly used subtype is the distinction between inattentive-impulsive-overactive (IO) behaviours and oppositional-defiant (OD) behaviours. Although the validity of this distinction was at one time questioned, it is now well established that they constitute separate but related aspects of disruptive behaviour (Hinshaw, 1987), and that different combinations of these two types of disruptive behaviour are related to different areas of Canadian Journal of Behavioural Science, 2004, 36:2,

2 98 Waschbusch, Porter, Carrey, Kazmi, Roach, and D Amico impairment (Waschbusch, 2002). For example, recent longitudinal studies suggest that children who exhibit both IO and OD behaviours (as compared to children with either IO-only or OD-only) have a substantially elevated risk for serious, violent, and chronic antisocial behaviour when they become adolescents and adults (Lynam, 1996; Moffitt, 1993; Moffitt, Caspi, Harrington, & Milne, 2002). Distinguishing IO and OD is probably the most widely used method of subtyping disruptive child behaviour, as reflected by the fact that both the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 1994) and the International Classification of Disease (World Health Organization, 1993) recognize this distinction. At the same time, it has been suggested that the distinction between IO and OD is not sufficient for understanding disruptive child behaviour. As a result, other methods of conceptualizing disruptive behaviour have been suggested. These methods are thought to provide unique information about what is complementary to the more widely used distinction between IO and OD. One example of an alternative means of distinguishing disruptive behaviour is the concept of reactive and proactive aggression. Reactive aggression can be defined as angry, impulsive aggression whereas proactive aggression is nonangry, nonimpulsive aggression (Dodge & Coie, 1987). The validity of this distinction is now considerable (K. Brown, Atkins, Osborne, & Milnamow, 1996; Dodge, 1991; Woodworth & Porter, 2002). Relative to proactive aggression, reactive aggression is more associated with early physical abuse experiences (Dodge, Pettit, Bates, & Valente, 1995), peer rejection (Coie, Dodge, Terry, & Wright, 1991; Dodge & Coie, 1987; Volling, Mackinnon-Lewis, Rabiner, & Baradaran, 1993; Waschbusch, Willoughby, & Pelham, 1998), and disruptive school behaviour (K. Brown et al., 1996; Waschbusch et al., 1998). On the other hand, at least two studies have found that proactive aggression in childhood is a better predictor of later delinquency than is reactive aggression (Pulkkinen, 1996; Vitaro, Gendreau, Tremblay, & Oligny, 1998). These studies suggest that reactive and proactive aggression are valid and distinct aspects of disruptive behaviour, but little research has examined how they relate to other forms of disruptive behaviour, such as IO and OD. Hypothetically, reactive and proactive aggression should be at least partially distinct from IO and OD because the former are based on the well established social cognitive differences that have been found in disruptive children whereas the latter are not (Dodge, Lochman, Harnish, Bates, & Pettit, 1997; Waschbusch, Willoughby, & Pelham, 1997). However, very little research has examined this issue empirically. Another distinction that has been proposed as a useful complement to IO and OD is relationship (or relational) aggression (Crick & Grotpeter, 1995). Relationship aggression, sometimes referred to as indirect aggression (Lagerspetz & Bjorkqvist, 1992), can be defined as behaviour intended to harm another s friendships, reputation, or standing with peers. In support of the validity of relationship aggression is research showing that girls with elevated rates of relationship aggression have social cognitive styles and peer relationships that are more deviant than girls with lower rates of relationship aggression (Crick & Grotpeter; Crick & Ladd, 1990). Further, girls report being the recipients of relationship aggression to a greater degree than boys, whereas boys report being the recipients of physical aggression to a greater degree than girls (Crick & Nelson, 2002). Thus, relationship aggression appears to be a valid means of conceptualizing disruptive behaviour in children. Theoretically, relationship aggression should be partially independent of IO and OD since the former focuses on interpersonal processes whereas the latter do not, but no research has examined whether relationship aggression is associated with IO and OD after taking other types of disruptive behaviour into account. A third aspect of disruptive behaviour that may complement IO and OD is callous, unemotional (CU) behaviour (Frick & Ellis, 1999). Callous and unemotional behaviour can be defined as antisocial behaviour that is characterized by a lack of concern or caring about others. In support of this approach to conceptualizing disruptive behaviour is that children with elevated CU exhibit a greater severity and variety of conduct problems, have lower levels of anxiety, experience more normal (less impaired) parenting, and have a reward-dominant response style (Frick & Ellis). Theoretically, CU behaviours should be partially independent of IO and OD as the former are based on the adult psychopathy literature, whereas the latter are not. In fact, preliminary research suggests that CU behaviours do provide important and unique information about disruptive child behaviour, relative to IO and OD (Frick, Bodin, & Barry, 2000; Frick, O Brien, Wootton, & McBurnett, 1994), but no research has examined this issue while also evaluating other aspects of disruptive behaviour. Finally, it has been speculated that recovery from anger may be an important component of understanding disruptive child behaviour. That is, children who take a long time to get over anger or to get over a transgression from a peer (i.e., hold a grudge for a

3 Subtypes of Disruptive Behaviour 99 long time) may differ from disruptive children who do not have this characteristic. In fact, research on naturalistic play behaviour shows that boys with peer problems tend to display extended episodes of aggression (Coie et al., 1991). Similarly, a recent study using a lab-based aggressive task found that children who expressed reactive aggressive behaviour in response to peer provocation also tended to continue behaving aggressively for a longer period of time than did other children (Waschbusch et al., 2002). Thus, there is reason to believe that holding a grudge is a valid and important aspect of disruptive behaviour. However, it is unclear how this aspect of disruptive behaviour relates to other aspects of disruptive child behaviour. In summary, a variety of methods have been proposed for further specifying the general category of disruptive child behaviour. Theoretically, these methods of distinguishing disruptive behaviour are unique, providing complementary information about disruptive child behaviour, but no prior research has evaluated this possibility by examining these aspects of disruptive behaviour in a single sample of children. Doing so may help to determine the best method for conceptualizing disruptive behaviour, which may translate into more specific, and therefore more powerful, assessment methods, diagnostic formulations, and intervention strategies. Past research strongly suggests that there are important differences in the types of disruptive behaviour exhibited by boys and girls and by younger and older children. As noted earlier, a number of studies now show that boys are more likely to express physical aggression whereas girls are more likely to express relational aggression (Crick, 1995). Similarly, some types of disruptive behaviour increase over the course of development, whereas other types peak early in life and decrease thereafter (Loeber et al., 1993). Thus, in evaluating whether and how different types of disruptive behaviour are related, it will be important to take the child s age and sex into account. The purpose of the present study was to evaluate how theoretically distinct methods of conceptualizing disruptive behaviour are associated with each other and with other indicators of functioning. To do so, we gathered information on different aspects of disruptive behaviour from parents and teachers in large sample of elementary-age children. We hypothesized that several separate but correlated dimensions of disruptive behaviour would emerge, but no specific hypotheses are offered regarding the number of content of specific dimensions. Method Participants Participants were children in seven elementary schools (grades primary through six) in Eastern Canada. Children ranged in age from 5 to 12 years (M = 8.13; SD = 1.93) and consisted of 826 males (52.3%) and 753 females (47.7%). The majority of children lived with two parents (72.5%) and had one or two siblings (M = 1.45, SD = 1.06). Measures Nova Scotia IOWA Connors. The Nova Scotia IOWA Connors (NSIC) is a measure of disruptive behaviour consisting of 25-items, each of which has a 4-point Likert rating (see Appendix). The NSIC was designed by the authors to measure the following seven constructs: (1) inattentive-impulsive-overactive behaviour Items 1 to 5; (2) oppositional-defiant behaviour Items 6 to 10; (3) holding a grudge Items 11 to 13; (4) relationship aggression Items 14 to 16; (5) proactive aggression Items 17 to 19; (6) reactive aggression Items 20 to 22; (7) callous/unemotional behaviour Items 23 to 25. The NSIC was completed by parents and teachers. The majority of the items on the NSIC (19/25) were drawn directly from past research. Specifically, the five inattentive-impulsive-overactive items and the five oppositional-defiant (OD) items were drawn verbatim from the IOWA Connors (Loney & Milich, 1982; Milich & Fitzgerald, 1985; Milich & Landau, 1988; Milich, Loney, & Landau, 1982; Pelham, Milich, Murphy, & Murphy, 1989), and the three reactive and three proactive items were drawn verbatim from the aggression rating scale (Crick & Dodge, 1996; Day, Bream, & Pal, 1992; Dodge & Coie, 1987; Dodge et al., 1997). The three relationship aggression items also were drawn directly from past research (Crick, 1996), but the items were reworded slightly to make them more concise. The remaining six items, including three designed to evaluate holding a grudge and three to evaluate callous/unemotional traits, are new. These items were selected from a larger pool of items after being independently ranked by two experts as among the best indicators of the relevant constructs. The validity of the callous/unemotional items is suggested by the fact that they are significantly associated with the callous-unemotional scale of the Antisocial Processes Screening Device (Frick & Hare, 2001) in a community and in a clinical sample (Waschbusch & Porter, 2002). Assessment of Disruptive Symptoms DSM-IV Version (ADS-IV). The ADS-IV consists of the DSM-IV symptoms of ADHD and ODD (American Psychiatric

4 100 Waschbusch, Porter, Carrey, Kazmi, Roach, and D Amico Association, 1994) evaluated using 0 to 4 Likert scales, along with items assessing impairment from symptoms and (for parents only) age of onset of symptoms (Waschbusch, Sparkes, & Northern Region Partners In Action for Children and Youth Services, 2003). Data were combined across parents and teachers by taking a maximum score on a symptom-bysymptom basis, as recommended for theoretical and empirical reasons (Piacentini, Cohen, & Cohen, 1992), and used to compute the following scores: (1) ADHDinattention (IA), consisting of a mean rating for the nine inattentive symptoms listed in DSM-IV under ADHD (α =.97); (2) ADHD-hyperactive/impulsive (HI), consisting of a mean rating for the nine hyperactive-impulsive symptoms listed in DSM-IV under ADHD (α =.95); and (3) ODD, consisting of a mean rating for the eight symptoms listed in DSM-IV under ODD (α =.97). Combined data were also used to determine whether or not children met ADHD or ODD criteria, as indicated by symptom count and impairment ratings. Conduct Disorder Rating Scale DSM-IV (CDRS-IV). The CDRS-IV measures symptoms of conduct disorder (CD) as defined by the DSM-IV (Waschbusch & Northern Region Partners In Action for Children and Youth, under review). For each symptom, raters evaluate how often the target child exhibited each of the symptoms over the past 12 months, using the following anchors: (0) never (1) once (2) monthly (3) weekly, and (4) daily. All 15 symptoms of CD were included on mother and father ratings, but the following symptoms were excluded from teacher rating: 1) running away from home, 2) forced someone into sexual activity, and 3) staying out at night. These items were excluded because teachers frequently do not have knowledge about the setting in which these behaviours typically occur and are therefore often unable to answer them (Waschbusch et al., 1997). Raters also indicated impairment due to symptoms and (for parents only) estimated age of onset of symptoms. Data were combined across informants by taking the maximum score on a symptom by symptom basis and resulting data were used to compute a CD score, consisting of the mean rating of the 15 CD symptoms (α =.76). Combined data were also used to evaluate whether children met criteria for CD, as indicated by symptom count and impairment ratings. Impairment Rating Scale (IRS). The IRS is designed to evaluate the child s current level of impairment in developmentally important areas (Fabiano et al., under review). For parents, seven areas were rated: (1) peer relationships, (2) getting along with parents, (3) getting along with siblings, (4) school performance, (5) family relationships, (6) self-esteem, and (7) overall functioning. For teachers, six areas were rated: (1) peer relationships, (2) getting along with teacher, (3) academic work, (4) classroom behaviour, (5) self-esteem, and (6) overall functioning. These items were originally developed as a visual-analogue scale but they were evaluated using Likert ratings for the present study, with possible responses ranging from 0 ( no need for treatment ) to 4 ( very severe need for treatment ). 1 The items measuring peer relationships, adult-child relationships (parent-child and teacher-child), and overall functioning were combined across parents and teachers and used in the current study. Teacher ratings of academics and classroom behaviour were also used but were not combined across raters because teachers are likely to be the most valid informant for these constructs. Positive peer nominations. Positive peer nominations were gathered from children whose parents consented to the procedure (n = 1,343; 85% of total sample) by asking children to name three of their classmates whom they would like to invite to a birthday party. 2 These names were recorded in the context of a larger academic seatwork task and used as a measure of social functioning. Positive peer scores were determined by computing the number of times each child was picked by their classmates (positive peer nominations). These were converted to z-scores within each classroom to control for differences in number of children across classrooms. Procedure Data were collected as part of the evaluation of a school board initiated intervention program named Behaviour Support Education and Treatment (BEST) (Waschbusch & Northern Region Partners In Action for Children and Youth, 2001). The BEST project was designed to prevent and treat disruptive behaviour in elementary-school children in the context of a school setting using behavioural strategies delivered at universal, targeted, and clinical levels. Six of the seven participating elementary schools were matched in pairs based on geographical location (urban vs. 1 Likert ratings, rather than a visual-analogue scale, were used to facilitate scoring and data entry in the present study (necessary due to the large sample size) and to allow for administration of items over the telephone in an unrelated study. 2 It was not possible to gather negative peer nominations due to school board policy.

5 Subtypes of Disruptive Behaviour 101 TABLE 1 Factor Structure of Disruptive Behaviour Items for Parent Ratings and Teacher Ratings Parent Ratings Teacher Ratings PC AR IO PC AR IO Peer-Directed Callousness (PC) gets others to gang up on peers gets others to reject a peer threatens bullies purposely excludes gossips phys force dominates enjoys being mean cold uncaring tries to get back lacks remorse Adult-Directed Reactive (AR) stays angry holds a grudge temper outburst defiant uncooperative quarrels overreacts to accidents Inattentive-Impulsive-Overactive (IO) fidgets inattentive fails to finish excite impulse hums Unclassified when teased, strikes back acts smart blames others Eigenvalues % Variance Note. Factor loadings of.40 or greater are in boldface. rural) and school size. One school from each matched pair was randomly selected to be an intervention school (three schools total) and the other school became a control school (three schools total). The seventh school was added to the project after these procedures were completed in order to ensure that all parts of the school district were represented. This school was randomly assigned to the control school condition. Teachers and parents of these students were asked to complete a packet of rating scales on the students in the schools as part of the evaluation of an intervention program (see below). All raters were told that completing the packets was voluntary and that their responses would be confidential. Teachers were given the option of taking an in-service day to complete ratings on students in their homeroom classrooms, and all teachers elected to do so. Therefore, teacher ratings were available for nearly all students in participating schools (n = 1,549; 98% of sample), except students who entered schools after teachers had completed their ratings. Of these 1,549, 1,493 had data on at least 50% of the disruptive behaviour ratings and were therefore included in analyses of teacher ratings. Mothers of 816 children (52% of total sample) returned rating packets. These were largely biological mothers (96.7%), with a median education described as technical school or community college (37.9%) and a median income described as ranging from $10,000 to $25,000 (38.9%). Fathers of 386 children (24% of total sample) returned ratings packets. These were largely biological fathers (88.9%), with a median education described as technical school or community college (31.9%) and a median income described as ranging from $25,000 to $40,000 (31.2%). Mother and father responses on the rating scales were combined by taking the highest score for each item. This proce-

6 102 Waschbusch, Porter, Carrey, Kazmi, Roach, and D Amico TABLE 2 Means, Standard Deviations, and Sample Sizes as a Function of Age and Sex Peer-Callous Adult-Reactive Inatt-Impul-Overact Sex/Age N M SD Cut M SD Cut M SD Cut Parent Ratings of PC, AR, IO Boys 5/ / / / Girls 5/ / / / Teacher Ratings of PC, AR, IO Boys 5/ / / / Girls 5/ / / / Note. Cut = cutoff score used to identify group 1.5 SD above the mean for their age and sex. dure has been recommended for both conceptual and empirical reasons (Piacentini et al., 1992) and is justified by the fact that mother and father ratings were highly correlated (e.g., r =.79 for a composite score of the disruptive behaviour ratings). The final sample of parent ratings after combining mother and father data was 834, which represents 463 mom-only ratings, 39 dad-only ratings, and 332 mom-and-dad ratings. Results Exploratory Factor Analysis Our first question was whether aspects of disruptive behaviour that are conceptually distinct emerge as distinct constructs in factor analysis. We examined this question using exploratory factor analysis, which proceeded in two steps. First, we determined the number of factors present in the data using parallel analysis (Glorfeld, 1995; O Connor, 2000). Results indicated three factors were justified for both parent and teacher data. Second, we determined the structure of the factors using principal-axis extraction with oblique (Promax) rotation. The rotated (pattern matrix) solution for the factor extraction is provided in Table 1. Items loading.40 and above were interpreted as a meaningful factor loading. The factors were interpreted as: (1) peer-callous (PC), which consisted of items indexing peer-directed antisocial behaviour and a lack of emotion or empathy; (2) adult-reactive (AR), which consisted of items indexing defiance and uncooperativeness toward adults and emotional reactivity; and (3) inattentive-impulsive-overactive (IO), consisting of items indexing inattentive, impulsive, and overactive behaviours. 3 Based on the exploratory factor analysis, scale scores were computed by averaging items that loaded.40 or greater on the same factor (see Table 1), with separate scores computed for parent and teacher ratings. Average scores, rather than summary scores, were used so that the metric of the items was preserved (e.g., average scores of 2 can be interpreted as pretty much, average scores of 3 can be interpreted as very much, etc.) and so that scale scores can be compared despite their different numbers of items. There were 10 items on the PC scale (Parents: M = 0.16, SD = 0.30, α =.87; Teachers: M = 0.11, SD = 0.34, α =.95), seven items on the AR scale (Parents: M = 0.41, SD = 0.53, α =.90; Teachers: M = 0.17, SD = 0.44, α =.93), and five items on the IO scale (Parents: M = 0.79, SD = 0.67, α =.86; Teachers: M = 0.68, SD = 0.73, α =.90). Item-total correlations and alpha if item 3 Nearly identical results emerged when parent and teacher ratings were combined by taking the maximum score across informants on a symptom-by-symptom basis and submitting these to the same analyses.

7 Subtypes of Disruptive Behaviour 103 deleted did not identify any problematic items for any of the scales. Age and Sex Differences Our second question was whether the different types of disruptive behaviour that emerged in our factor analyses varied as a function of the child s age and sex. To evaluate this possibility, disruptive behaviour scores were examined using 4 (Age: 5/6 vs. 7/8 vs. 9/10 vs. 11/12) x 2 (Sex: boys vs. girls) ANOVAs. Significant interactions were followed up with simple effects tests and Bonferroni adjusted post-hoc tests. Means, standard deviations, and sample sizes for the scales are reported in Table 2. Parent ratings. On the PC scale, there was a significant main effect of Age, F(3, 828) = 4.03, p <.01, partial η 2 =.01, and a significant main effect of Sex, F(1, 828) = 7.48, p <.01, partial η 2 <.01. Follow-up tests showed that boys had higher PC scores than girls, and 11/12 year-olds had higher PC scores than 5/6 year-olds, with 7/8 and 9/10 year-olds in the middle of (but not different than) the other two ages. On the AR scale, there was a significant main effect of Sex, F(1, 839) = 6.91, p <.01, partial η 2 <.01. Examination of means showed boys had higher AR scores than girls. On the IO scale, there was also a significant main effect of Sex, F(1, 840) = 18.28, p <.001, partial η 2 =.02. Examination of means showed that boys had higher IO scores than girls. Teacher ratings. On the PC scale, there was a significant main effect of Age, F(3, 1,439) = 14.53, p <.001, partial η 2 =.03, and a significant main effect of Sex, F(1, 1,439) = 21.76, p <.001, partial η 2 =.01, but these were moderated by a significant Age x Sex interaction, F(3, 1,439) = 8.36, p <.001, partial η 2 =.02. Follow-up tests showed that: (a) 11/12 year-old boys had significantly higher PC scores than 11/12 yearold girls, p <.001; and (b) PC scores increased significantly with age for boys, ps <.05, but age was not significant for girls. On the AR scale, there was a significant main effect of Age, F(3, 1,459) = 6.61, p <.001, partial η 2 =.01, and a significant main effect of Sex, F(1, 1,459) = 40.62, p <.001, partial η 2 =.03, but these were moderated by a significant Age x Sex interaction, F(3, 1,459) = 4.71, p <.001, partial η 2 =.01. Follow-up tests showed that: (a) boys had significantly higher AR scores than girls at every age, ps <.05; and (b) PC scores increased significantly with age for boys, ps <.05, but age was not significant for girls. On the IO scale, there was a significant main effect of Age, F(3, 1,483) = 2.62, p <.05, partial η 2 <.01, and a significant main effect of Sex, F(1, 1,483) = 67.39, p <.001, partial η 2 =.04, but these were moderated by a significant Age x Sex interaction, F(3, 1,483) = 3.32, p <.05, partial η 2 =.01. Follow-up tests showed that: (a) boys had significantly higher IO scores than girls at every age, ps <.05; and (b) 11/12 year-old boys had significantly higher IO scores than other boys, ps <.05, but age was not significant for girls. In summary, these results show that boys have higher rates of disruptive behaviour than girls, and this is true for each type of disruptive behaviour and for both parent and teacher ratings. Results also showed that older boys tend to be rated as more disruptive than younger boys, but these results were less consistent. Scale Associations Our third question was how closely the different aspects of disruptive behaviour were associated. Because disruptive behaviour can be conceptualized both continuously and categorically, we examined the associations both continuously and categorically. Continuous analyses consisted of Pearson correlations computed with scale scores described above. Categorical analyses consisted of the following 2 x 2 chi-squares: (a) elevated PC score (yes vs. no) x elevated AR score (yes vs. no); (b) elevated PC score (yes vs. no) x elevated IO score (yes vs. no); and (c) elevated AR score (yes vs. no) x elevated IO score (yes vs. no). Elevated scores were those at least 1.5 SD above the mean as compared to others of their same age and same sex (see Table 2). Parent ratings. Pearson correlations showed that each of the disruptive behaviour scores was significantly correlated: (1) PC and AR r =.72, p <.001; (2) PC and IO r =.51, p <.001; and (3) AR and IO r =.65, p <.001. Categorical analyses showed that 57 children (6.8%) had elevated PC, 80 (9.4%) had elevated AR, and 72 (8.5%) had elevated IO scores. Chi-square analyses comparing these groups showed that the PC and AR groups were significantly associated, χ 2 (1) = , p <.001; 4.3% of the children were elevated on PC-only, 2.0% were elevated on AR-only, and 4.8% were elevated on both PC and AR. The PC and IO groups were also significantly associated, χ 2 (1) = , p <.001; 3.6% were elevated on PC-only, 5.2%were elevated on IO-only, and 3.2% were elevated on both PC and AR. The AR and IO groups were significantly associated, χ 2 (1) = , p <.001; 5.1% were elevated on AR-only, 4.3% were elevated on IOonly, and 4.3% were elevated on both IO and AR.

8 104 Waschbusch, Porter, Carrey, Kazmi, Roach, and D Amico TABLE 3 Multiple Regression Analyses Using PC, AR, and IO to Predict Measures of Impairment PC AR IO r sr r sr r sr F-value R 2 Parent Ratings of PC, AR, IO Positive nominations (peer) -.11* * * -.19* 7.35*.05 Peer relationships (parent/tchr).44*.15*.44*.08*.43*.18* 57.43*.26 Adult-child relationship (prnt/tchr).52*.18*.53*.16*.44*.10* 82.17*.33 Impaired classroom work (teacher).16*.00.18*.00.28*.22* 17.46*.10 Impaired class behaviour (teacher).27*.07*.28* *.29* 39.57*.20 Overall treatment need (prnt/tchr).46*.08*.54*.16*.52*.22* 91.03*.36 Teacher Ratings of PC, AR, IO Positive nominations (peer) -.10* * -.06* -.24* -.17* 15.39*.06 Peer relationships (prnt/tchr).57*.12*.61*.18*.46*.13* *.41 Adult-child relationship (prnt/tchr).39*.03.45*.18*.32*.08* 77.31*.21 Impaired classroom work (teacher).29*.01.36*.01.59*.46* Impaired class behaviour (teacher).56*.07*.66*.16*.68*.36* *.57 Overall treatment need (prnt/tchr).44*.05*.52*.11*.57*.34* *.39 Note. Higher scores indicate greater impairment (worse behaviour) for all measures of impairment except positive peer nominations. Informants for measures of impairment are in parentheses: peer = other students in child s classroom, prnt/tchr = parent and teacher ratings combined, teacher = teacher ratings only. r = simple correlation; sr = semipartial correlation. F-value = F value for full regression model (df = 5, 812 for parent ratings and 5, 1413 for teacher ratings). *p <.05. Teacher ratings. Pearson correlations showed that each of the disruptive scores was significantly correlated: (1) PC and AR r =.81, p <.001; (2) PC and IO r =.45, p <.001; and (3) AR and IO r =.58, p <.001. Categorical analyses showed that 101 children (7.0%) had elevated PC, 101 (7.0%) had elevated AR, and 142 (9.5%) had elevated IO scores. Chi-square analyses comparing these groups showed that the PC and AR groups were significantly associated, χ 2 (1) = , p <.001; 2.9% of children were elevated on PC-only, 2.4% were elevated on AR-only, and 3.9% were elevated on both PC and AR. The PC and IO groups were also significantly associated, χ 2 (1) = 91.93, p <.001; 4.5% were elevated on PC-only, 6.6% were elevated on IO-only, and 2.5% were elevated on both PC and AR. The AR and IO groups were also significantly associated, χ 2 (1) = , p <.001; 5.4% were elevated on AR-only, 3.0% were elevated on IOonly, and 3.9% were elevated on both IO and AR. In summary, these results suggest that the different types of disruptive behaviour are separate but related constructs. This was true whether disruptive behaviour was defined by parent or teacher, and whether it was evaluated continuously or categorically. Association with Measures of Impairment Our fourth question was whether the different aspects of disruptive behaviour are uniquely associated with measures of daily functioning. We evaluated this issue using multiple regression analyses that examined the association between the PC, AR, and IO scales and other measures of impairment. Age and sex were entered on the first step of the regressions and PC, AR, and IO were entered on the second step. Simple correlations and semipartial correlations for the PC, AR, and IO scales, as well as the F statistic and the R-square for the overall model, are summarized in Table 3. Parent ratings. Simple correlations showed that PC, AR, and IO were significantly associated with the impairment measures, although the magnitude of the correlations varied widely (see Table 3). Semi-partial correlations showed that (1) the PC scale was significantly and uniquely (i.e., after taking age, sex, AR, and IO into account) associated with parent/teacher report of peer problems, adult-child problems, classroom behaviour problems, and overall need for treatment; (2) the AR scale was significantly and uniquely associated with peer relationships, adult-child relationships, and overall need for treatment; and (3) the IO scale was significantly and uniquely associated with each of the measures of impairment. Teacher ratings. Simple correlations showed that PC, AR, and IO were significantly associated with the impairment measures, although the magnitude of the correlations varied widely (see Table 3). Semipartial correlations showed that (1) the PC scale was significantly and uniquely (i.e., after taking age, sex, AR, and IO into account) associated with parent/teacher report of peer problems, adult-child problems, classroom behaviour problems, and overall need for treat-

9 Subtypes of Disruptive Behaviour 105 TABLE 4 Multiple Regression Analyses Using PC, AR, and IO to Predict DSM-IV Scores PC AR IO r sr r sr r sr F R 2 Parent Ratings of PC, AR, IO ADHD-inattention.36*.04.42*.03.58*.37* 90.58*.36 ADHD-hyperactive/impulsive.39*.06*.46*.04.62*.39* *.42 Oppositional Defiant Disorder.54*.10*.64*.26*.54*.14* *.45 Conduct Disorder.65*.29*.61*.13*.51*.11* *.48 Teacher Ratings of PC, AR, IO ADHD-inattention.27*.02.36* *.52* *.40 ADHD-hyperactive/impulsive.32*.05*.38*.04.50*.33* *.28 Oppositional Defiant Disorder.34*.04.41*.17*.27* *.18 Conduct Disorder.56*.23*.52*.08*.33* *.33 Note. ADHD = attention-deficit/hyperactivity disorder. r = simple correlation; sr = semipartial correlation. F = F-value for full regression model (df = 5, 812 for parent ratings and 5, 1413 for teacher ratings). *p <.05. ment; (2) the AR scale was significantly and uniquely associated with positive peer nominations and with parent/teacher ratings of peer relationships, adultchild relationships, classroom behaviour, and overall need for treatment; and (3) the IO scale was significantly and uniquely associated with each of the measures of impairment. In summary, the results of these analyses indicate that the various aspects of disruptive behaviour are uniquely associated with measures of daily functioning, even after taking other disruptive behaviour (as well the child s age and sex) into account. Association with DSM-IV Scores Our final question was how the aspects of disruptive behaviour used in the current study are related to the more well-established approach operationalized in the DSM-IV. This question is intended to determine whether gathering information on the aspects of disruptive behaviour evaluated in the present study provides complementary information to that contained in the DSM-IV, or if instead the information is largely redundant. To evaluate this issue, we computed multiple regressions to examine whether PC, AR, and IO scales predicted ADHD, ODD, and CD scores. Following earlier analyses, age and sex were entered on the first step of the regressions and PC, AR, and IO were entered on the second step. Based on the results of the multiple regressions, ANOVAs and chi-square analyses were computed within the diagnostic categories (ADHD, ODD, CD) to compare children with higher versus lower PC, AR or IO scores on measures of impairment, age, and gender. These analyses further evaluated whether the PC, AR, and IO scores provide complementary information beyond DSM categories. Parent ratings. Results of multiple regressions (see Table 4) showed that the PC scale was significantly and uniquely associated with CD, the AR scale was significantly and uniquely associated with ODD, and the IO scale was significantly and uniquely associated with both inattention and hyperactive/impulsive scores from ADHD. These results were further explored in three additional sets of analyses. First, we compared children with conduct disorder who were also elevated on the PC scale (CD-PC, n = 26) to children with conduct disorder who were not elevated on the PC scale (CD-only, n = 24). Groups differed on teacher-rated academic work, F(1, 48) = 3.89, p <.05. Examination of means showed that the CD-only group were rated as having worse academic impairment than were the CD-PC group (CD-PC: M = 0.96, SD = 1.18; CD-only: M = 1.71; SD = 1.49). Second, we compared children with oppositional defiant disorder who were also elevated on the AR scale (ODD-AR, n = 64) to ODD children who were not elevated on the AR scale (ODD-only, n = 95). Groups differed on positive peer nominations, F(1, 130) = 3.27, p <.05, ratings of adult-child relationships, F(1, 157) = 4.99, p <.05, and ratings of overall need for treatment, F(1, 157) = 4.99, p <.05. Examination of means showed that the ODD-AR children were rated as having worse relationships with adults (ODD-AR: M = 1.81, SD = 1.17; ODD-only: M = 1.06, SD = 1.18) and having a greater overall need for treatment (ODD-AR: M = 2.13, SD = 1.05; ODD-only: M = 1.55, SD = 1.16), but received more positive nominations from peers (ODD-AR: M = -0.09, SD = 0.95; ODD-only: M = -0.41, SD = 0.70). Third, we compared whether children with ADHD (any subtype) who were also elevated on the IO scale (ADHD-IO, n = 145) differed from ADHD children who

10 106 Waschbusch, Porter, Carrey, Kazmi, Roach, and D Amico were not elevated on the IO scale (ADHD-only, n = 58). Results showed that the ADHD-IO group had a significantly higher ratio of females (41%) than the ADHD-only group (28%), χ 2 (1) = 3.66, p =.05. Groups also differed on ratings of peer relationships, F(1, 201) = 11.68, p <.05, ratings of adult-child relationships, F(1, 201) = 15.39, p <.05, ratings of classroom behaviour, F(1, 201) = 4.34, p <.05, and ratings of overall need for treatment, F(1, 157) = 8.01, p <.05. Examination of means showed that the ADHD-IO children were rated as having more peer problems (ADHD-IO: M = 1.69, SD = 1.20; ADHD-only: M = 1.06, SD = 1.17), worse relationships with adults (ADHD-IO: M = 1.66, SD = 1.37; ADHD-only: M = 0.95, SD = 1.06), worse classroom behaviour (ADHD-IO: M = 1.38, SD = 1.33; ADHD-only: M = 1.01, SD = 1.06), and having a greater overall need for treatment (ADHD-IO: M = 2.07, SD = 1.23; ADHD-only: M = 1.54, SD = 1.18). Teacher ratings. Results of the multiple regressions (see Table 4) showed that the PC scale was significantly and uniquely associated with CD, the AR scale was significantly and uniquely associated with ODD, and the IO scale was significantly and uniquely associated with both inattention and hyperactive/impulsive scores from ADHD. These results were further explored in three additional sets of analyses. First, children with conduct disorder who were also elevated on the PC scale (CD-PC, n = 14) were compared to conduct-disordered children who were not elevated on the PC scale (CD-only, n = 33). Groups were significantly different on positive peer nominations, F(1, 34) = 2.88, p =.05, ratings of peer relationships, F(1, 45) = 18.67, p <.05, academic work, F(1, 45) = 17.25, p <.05, classroom behaviour, F(1, 45) = 23.33, p <.05, and overall need for treatment, F(1, 45) = 13.68, p <.05. Examination of means showed that CD- PC children receive fewer positive nominations from peers (CD-PC: M = -0.93, SD = 0.58; CD-only: M = -0.32, SD = 0.96), were rated as having more problems with peers (CD-PC: M = 3.07, SD = 1.07; CD-only: M = 1.58, SD = 1.09), more academic problems (CD-PC: M = 2.64, SD = 1.34; CD-only: M = 1.00, SD = 1.20), worse classroom behaviour (CD-PC: M = 2.50, SD = 1.34; CDonly: M = 0.76, SD = 1.03), and as having a greater overall need for treatment (CD-PC: M = 3.21, SD = 1.05; CD-only: M = 1.91, SD = 1.13). Second, we compared whether children with oppositional defiant disorder who were also elevated on the AR scale (ODD-AR, n = 67) differed from ODD children who were not elevated on the AR scale (ODD-only, n = 111). Groups differed significantly on positive peer nominations, F(1, 144) = 11.89, p <.05, ratings of peer relationships, F(1, 175) = 41.23, p <.05, adult-child relationships, F(1, 175) = 5.16, p <.05, classroom behaviour, F(1, 175) = 90.20, p <.05, academic work, F(1, 175) = 17.54, p <.05, and ratings of overall need for treatment, F(1, 175) = 18.42, p <.05. Examination of means showed that the ODD-AR children received fewer positive peer nominations than ODD-only children (ODD-AR: M = -.62, SD =.65; ODDonly: M = -.14, SD =.88), were rated as having worse relationships with peers (ODD-AR: M = 2.18, SD = 1.19; ODD-only: M = 1.11, SD = 1.03) and with adults (ODD-AR: M = 1.67, SD = 1.27; ODD-only: M = 1.23, SD = 1.20), as having worse academic work (ODD-AR: M = 1.80, SD = 1.50; ODD-only: M = 0.94, SD = 1.21) and classroom behaviour (ODD-AR: M = 2.20, SD = 1.33; ODD-only: M = 0.61, SD = 0.89), and as having a greater overall need for treatment (ODD-AR: M = 2.32, SD = 1.35; ODD-only: M = 1.55, SD = 1.16). Finally, we compared whether children with ADHD (any subtype) who were also elevated on the IO scale (ADHD-IO, n = 115) differed from ADHD children who were not elevated on the IO scale (ADHDonly, n = 201). Groups did not differ on age, but the ADHD-IO group had a significantly higher ratio of females (36%) than the ADHD-only group (24%), χ 2 (1) = 4.56, p <.05. Groups differed on positive peer nominations, F(1, 298) = 5.19, p <.05; peer ratings, F(1, 298) = 97.10, p <.05; adult relationships, F(1, 298) = 41.01, p <.05; classroom behaviour, F(1, 298) = 74.42, p <.05; and overall treatment, F(1, 298) = 35.31, p <.05. Examination of means showed that the ADHD-IO children received fewer positive peer nominations (ADHD-IO: M = -0.54, SD = 0.79; ADHD-only: M = 0.26, SD = 0.85), were rated as having more peer problems (ADHD-IO: M = 2.16, SD = 1.19; ADHD-only: M = 0.81, SD = 0.97), worse relationships with adults (ADHD-IO: M = 1.66, SD = 1.26; ADHD-only: M = 0.74, SD = 1.02), worse classroom behaviour (ADHD-IO: M = 2.13, SD = 1.32; ADHD-only: M = 0.93, SD = 0.94), and having a greater overall need for treatment (ADHD-IO: M = 2.37, SD = 1.19; ADHD-only: M = 1.46, SD = 1.15). In summary, these results suggest that peer-callous, adult-reactive, and inattentive-impulsive-overactive dimensions of disruptive behaviour are related to ADHD, ODD, and CD, and that they may provide useful information for further discriminating within these groups. Discussion The purpose of this study was to investigate different conceptualizations of disruptive behaviour in a large community-based sample of children. Although numerous conceptualizations of disruptive behaviour have been proposed, few studies have evaluated

11 Subtypes of Disruptive Behaviour 107 how these different conceptualizations are inter-related. We evaluated both well-established, widely used measures of disruptive behaviour namely inattentive-impulsive-overactive behaviour, oppositionaldefiant behaviour, reactive aggression, proactive aggression, and relationship aggression and less well established but potentially important measures namely, callous-unemotional traits, and holding a grudge against others. Our results suggest that three dimensions can be extracted from data relating to these different conceptualizations of disruptive behaviour in children. The first dimension consisted primarily of characteristics associated with proactive aggression, relationship aggression, and callous/ unemotional traits. We interpreted this dimension as an index of peer-directed, callous behaviour (PC). The second dimension consisted primarily of items designed to measure oppositional-defiance, reactive aggression, and holding a grudge. We interpreted this as an index of adult-directed, emotionally reactive behaviour (AR). The third dimension consisted of items designed to measure inattentive-impulsiveoveractive (IO) behaviours and was interpreted as such. These factors were consistent across parent and teacher ratings. Further, the items that formed the IO factor have emerged as an independent factor in other research (Milich et al., 1982; Pelham et al., 1989). Collectively, these findings suggest that the factor structure is relatively robust and is likely to generalize to other samples. A number of analyses were used to evaluate these three dimensions. One set of analyses evaluated whether the dimensions differed as a function of children s age and sex. Boys were generally rated higher than girls on all three dimensions, which is consistent with a large number of studies that show disruptive behaviour tends to be more common among boys than girls (Loeber & Keenan, 1994; Silverthorn & Frick, 1999; Zoccolillo, 1993). Our analyses also showed that older boys were generally rated as more disruptive than younger boys, and that this was true for each of the scales. The increased severity on the PC and AR scales in the older children is consistent with numerous other studies that suggest disruptive behaviours in boys tend to increase with age (Lahey, Miller, Gordon, & Riley, 1999; Loeber & Keenan, 1994). On the other hand, past research has been inconsistent with respect to age-related changes in IO behaviour, with some studies finding decreases in IO with increasing age and other studies finding either increases or no change (see Lahey et al., 1999 for a review). Our results would seem to indicate an increase in IO behaviours with increasing age. It should be noted that these interpretations are based on cross-sectional data and should therefore be interpreted cautiously. The evaluation of age and sex effects also showed that the behaviours in question are generally rare. For example, less than 1% of the sample was rated in the pretty much or very much range on the PC scale, and this was true for both parent and teacher ratings. Similarly, less than 3% were rated in the pretty much or very much range on the AR scale, and less than 10% were rated pretty much or very much on the IO scale. The fact that these behaviours are rarely elevated suggests that they are likely to have a substantial negative impact on development when they are elevated. Analyses evaluating the overlap between the disruptive behaviour dimensions resulted in betweenscale correlations that ranged from.45 to.81. This range of correlations is typical for measures of disruptive behaviour (e.g., Frick et al., 2000; Hinshaw, 1987) and suggests that the best interpretation of the dimensions is that they are separate but moderately to highly related. This interpretation is bolstered by the fact that the population of children who are elevated on the scales is only partially overlapping, with some children elevated on more than one scale and other children elevated on a single scale. We also evaluated how the PC, AR, and IO scales were related to other measures of children s development, including measures of peer relationships, getting along with adults, academic work, classroom behaviour, and need for treatment. Among the most striking results to emerge from these analyses was that the IO scale was uniquely associated with nearly every outcome measure, even after taking the other disruptive scales into account, whereas the same was less true for the PC and AR scales. This finding adds to a considerable literature that argues for the importance that inattentive-impulsive-overactive behaviours play when evaluating disruptive behaviour (Waschbusch, 2002). The fact that the IO scale was strongly and uniquely (and inversely) associated with number of positive peer nominations children received, whereas the PC and AR scales were not, suggests that dysregulated, inattentive behaviours are linked to peer problems at least as strongly as behaviours such as aggression and defiance. This interpretation is consistent with a growing body of literature. For example, IO behaviours in childhood have been found to significantly predict peer problems in adolescence (Bagwell, Molina, Pelham, & Hoza, 2001), and IO behaviours have been shown to discriminate aggressive children who are rejected from aggressive children who are not rejected (Bierman & Wargo, 1995). These analyses also provide partial support for our interpretation of the PC