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Oppositional defiant disorder

Oppositonal Defiant Disorder (ODD) an ongoing pattern of disobedient, hostile, and defiant behavior toward authority figures that goes beyond the bounds of normal childhood behavior. more...

When a child cannot seem to control his anger or frustration, even over what seems to be trivial or simple to others. The child will often react in violent or negative ways to his own feelings. more...

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A physician will commonly refer the child to a psychiatrist who will determine if the child frequently shows four or more of the following behaviors or signs of the disorder for more than six months:

  • Arguing with adults
  • Losing temper
  • Angry or resentful of others
  • Actively defies adults requests or rules
  • Negative attitude
  • Blames others for their own mistakes or behaviors
  • Seems touchy or easily annoyed by others
  • Deliberately annoys others
  • Acts spiteful or vindictive

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Factor Structure and Criterion Validity of Secondary School Teacher Ratings of ADHD and ODD [1] - Attention-Deficit Hyperactivity Disorder, Oppositional
From Journal of Abnormal Child Psychology, 2/1/01 by Brooke S. G. Molina

Brooke S. G. Molina [2,5]

Bradley H. Smith [3]

William E. Pelham [4]

Attention-Deficit Hyperactivity Disorder (ADHD) is currently viewed as a heterogeneous disorder with two factors: inattention and impulsivity-hyperactivity. This conceptualization of ADHD is based primarily on research with children or samples that mix children and adolescents. To examine if the 2-factor ADHD model is appropriate for adolescents and if the ADHD factors are distinct from Oppositional Defiant Disorder (ODD) in adolescents, teacher rating data were collected for 2 samples of adolescents. The results of a confirmatory factor analysis supported the convergent and divergent validity of a model with separate but correlated factors for inattention, impulsivity-hyperactivity, and defiant behavior. Further evidence of construct validity was found when factor scores were examined relative to the criterion variables of academic performance and rule-breaking behavior. The results support the utility of teacher ratings of ADHD and ODD in the assessment of adolescents, and the applicability of the DSM-IV co nceptualization of these disorders to adolescents.

KEY WORDS: Adolescent; ADHD; behavior ratings; disruptive behavior.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a well-researched behavioral syndrome, with hundreds of studies describing the clinical picture, comorbid disorders, putative etiologies, and responses to various forms of treatment (for review, see Barkley, 1998). Most of these studies, however, are of elementary school-aged children. Only recently has an interest in the manifestation of ADHD in adolescence and adulthood taken a foothold in the scientific literature. We now know from prospective longitudinal studies of children with ADHD that most children retain their diagnosis of ADHD into their teenage years (Barkley, Fischer, Edelbrock, & Smallish, 1990; Mannuzza et al., 1991). However, little research has been conducted with adolescent-specific samples to test the assumptions underlying the measurement of this disorder in adolescence. For example, the appropriateness of adopting the 2-factor conceptualization of ADHD symptoms reflected by the DSM-IV ADHD typology has not been established for adolescent s (American Psychiatric Association, 1994). Perhaps more importantly, the distinction between ADHD symptoms and the symptoms of Oppositional Defiant Disorder (ODD) has not been thoroughly examined in adolescent-specific samples.

Factor analytic studies of parent or teacher ratings of children's behavior have identified two dimensions underlying ADHD symptoms, one of inattention symptoms and another of impulsivity and hyperactivity symptoms (e.g., Burns, Walsh, Owen, & Snell, 1997; DuPaul et al., 1997; Pillow, Pelham, Hoza, Molina, & Stultz, 1998). The DSM-IV adoption of the ADHD subtypes, namely inattentive type, hyperactive-impulsive type, and combined type, reflects the results of these studies. For example, factor analyses (both exploratory and confirmatory) of parent and teacher ratings for a large, representative sample of North American school children aged 3-17 found factors for inattention/cognitive problems, impulsivity-hyperactivity, and oppositionality (parent-rating scale only) problems (Conners, Sitarenios, Parker, & Epstein, 1998a, 1998b). With the exception of a few items indexing academic difficulties that loaded onto the inattention factor, the 2-factor structure of ADHD symptoms was replicated, including the distin ctiveness of the two ADHD factors from other symptoms. Furthermore, in this and other studies the two dimensions of ADHD were empirically distinct from ODD and CD, providing support for the construct validity of the ADHD disorder (Hinshaw, 1987; Lahey & Willcutt, 1998).

An important finding in the factor analytic study by Conners et al. (1998a, 1998b) was the equality of the correlation matrices for the teacher-rating scale items across three age groups (3- to 7-year-olds, 8- to 12-year-olds, 13- to 17-year-olds), which suggested that the factor structure would apply throughout the childhood and adolescent age range. Thus, there is preliminary evidence that, within an adolescent school-based population, the 2-factor model of ADHD and distinctiveness of ADHD from ODD applies to behavior ratings of adolescents. However, the items on the Revised Conner's Parent and Teacher Rating Scales overlap only partially with the list of symptoms in the DSM-IV. As a result, the studies by Conners et al. do not provide a specific test of the factor structure of the DSM-IV symptoms for ADHD in adolescents.

One of the most important issues regarding the factor structure of the DSM-IV symptoms of inattention, impulsivity-hyperactivity, and defiance is the extent to which these factors provide unique, nonoverlapping information. Owing to the high correlations between ADHD factors and defiance, typically found in studies of children, suspicion arises as to whether simpler, more parsimonious models underlie the correlational structure of the items. In studies of children and adolescents combined, in spite of the high correlations found between the factors, measurement models including the 2-factors of ADHD (DuPaul et al., 1997) and ODD and CD as well (Burns et al., 1997) have fared better than simpler models. However, one of the hallmarks of adolescence is an increased striving for autonomy that may be viewed by some adults as defiance. To the extent that ADHD leads to misinterpretation or socially unacceptable expressions of these strivings, adult raters of behavior may have difficulty distinguishing between diffe rent types of adolescent behaviors experienced as disruptive. Furthermore, although the small amount of evidence available suggests that statistically significant differences between ADHD and nonADHD adolescents' activity levels continue in adolescence (Fisher, Barkley, Edelbrock, & Smallish, 1990; Mannuzza et al., 1991), clinical experience suggests greater variability in this symptom in adolescence than in childhood (Evans, Vallano, & Pelham, 1995; Robin, 1998). In light of these developmental considerations, it is prudent to determine whether the 2-factor structure underlying ADHD, and the distinction of ADHD from ODD, continues to hold in adolescence. The current study tested this possibility by comparing a 3-factor model of ADHD and ODD (inattention, impulsivity-hyperactivity, and ODD) to the more parsimonious 2-factor (ADHD and ODD) and 1-factor models of these disorders.

In addition to testing the factor structure underlying the ADHD and ODD symptoms, the criterion validity of the two ADHD factors has been suggested by differential associations with other variables (for review, see Lahey & Willcutt, 1998). For example, consistent with Conners' and colleagues' factor model suggesting that academic problems loaded best on a factor simultaneously indicated by inattention problem items (Conners et al., 1998a, 1998b), others have found that inattention is strongly associated with academic performance or impairment (Hudziak et al., 1998; Lahey et al., 1994), whereas impulsivity-hyperactivity is more strongly associated with teacher ratings of conduct problems (DuPaul, Power, McGoey, Ikeda, & Anastopoulos, 1998). In addition to finding a 2-factor model of ADHD, findings such as these have been used to support the idea that ADHD comprises two distinct subtypes, each of which may have distinct etiologic and prognostic features--a "pure" ADHD subtype associated with cognitive dysfunct ion versus an impulsive-aggressive subtype of ADHD (for review, see Halperin, Newcorn, & Sharma, 1996). However, whether this distinction continues into adolescence is not well researched. Thus, a goal of the current study was to test, for adolescents, the criterion validity of the ADHD dimensions in their association with academic and cognitive performance, rule breaking, and delinquent behavior.

Secondarily, we were interested in the associations between two demographic variables (age and gender) and teacher ratings of ADHD and ODD symptoms in adolescence. Although previous studies have shown age effects, mostly due to a decrease in impulsivity-hyperactivity (e.g., DuPaul et al., 1997; Gomez, Harvey, Quick, Scharer, & Harris, 1999; Hart, Lahey, Loeber, Applegate, & Frick, 1995), most age effects have been found by comparing mean ratings between children and adolescents, making it difficult to determine whether the reported decrease in symptomatology was truly due to age or a decreased familiarity with students in secondary versus elementary school. Furthermore, some inconsistencies in these findings suggest that further examination would be helpful. For example, Conners et al. (1998a, 1998b) found lower inattention and impulsivity-hyperactivity ratings for adolescents compared to children, whereas Pelham, Gnagy, Greenslade, and Milich (1992) found no age effect for ADHD symptoms in 5- to 14-year-old s. Regarding gender, the higher prevalence of all disruptive behavior disorders among male than among female children is well-documented (Barkley, 1998; Gaub & Carlson, 1997). However, relatively few studies have specifically examined gender differences in core symptom levels, and some inconsistencies in findings have emerged, with the possibility that referral status (whether or not the population being studied represents a clinic-referred or a community-based population) may moderate the gender effect (Gaub & Carlson, 1997). In the current study, we examined effects for both of these demographic variables: age effects in a sample of 13- to 18-year-old adolescents, and gender effects in a sample of middle school students.

Our research questions were addressed using teacher ratings of ADHD and ODD symptoms for two samples of adolescents. One sample was from a middle school (Study 1). Half of the students were referred multiple times to the principal for behavior problems in the school and represent a population of students at high risk for disruptive behavior. The other half of the students were randomly selected from the remaining student population. The second sample of adolescents was from a longitudinal study of children with ADHD (Study 2). About half of the adolescents had a childhood history of ADHD and were referred for treatment at a university clinic specializing in ADHD; the remaining half was a non-ADHD comparison group recruited as adolescents from the community. Thus, the samples represent a broad spectrum of adolescents that provide ample variability on measures of disruptive behavior and opportunities for cross-validation of findings across diverse and clinically meaningful populations.

STUDY 1: TEACHER RATINGS OF MIDDLE SCHOOL STUDENTS

Method

Participants

Participants were 247 sixth, seventh, and eighth graders at a public middle school in a small Midwestern city (11-16 years old, M = 13 years). Of the participants, 44% were female, and 69% were Caucasian (19% African Americans, 4% Latinos, and 8% others). Individual reports of parental income or education were not available. However, the population of students at the school was socioeconomically disadvantaged with the majority of parents either unemployed or having low-paying jobs. School district statistics indicated that over 60% of the students' families reported sufficiently low income to qualify for the free or reduced price meal programs.

Procedure

Data for the current study were collected as part of an evaluation of a school-wide intervention to decrease disruptive behavior in a middle school of approximately 400 students (Molina, Smith, McIlwain, Shem, & Wagner, 1997). In January 1996, parents were mailed letters describing the program and related research. Parents were instructed to contact the main office at the school if they did not want their child to participate in the research. Five (1%) of the parents refused.

Working with the school administration, the researchers identified two groups of students. A high-risk group comprising students who were referred three or more times to the Assistant Principal's office between August and May of the 1995/1996 school year for disciplinary action (n = 118). A comparison sample was randomly selected from the remaining students on the school roster (n = 129). Teachers completed paper-and-pencil ratings of the behavior of these 247 students, and they were blind to the risk group status of the students. Teacher forms were distributed to sixth-, seventh-, and eighth-grade team leaders who divided forms amongst the teachers on their team; teachers participated in choosing students to rate based on their familiarity with the student. [6] A total of 26 teachers provided ratings, and an average of 14.51 students were rated by each teacher (range = 1-26 students rated). Each student was rated only once. A total of 223 forms (90%) were returned with a valid answer for every item.

Measures

Teacher Reports of ADHD and ODD Symptoms. These were measured with 25 items directly adapted from the ADHD and ODD symptom lists in the DSM-IV. Each symptom was rated on a 4-point scale: 0 (not at all), 1 (mild problem), 2 (moderate problem), or 3 (severe problem). Items were ordered randomly. The wording of some DSM-IV items was revised to have less technical vocabulary and to provide some concrete examples (e.g., "often has difficulty paying attention for more than a few minutes to things like homework, board games, or chores"). One DSM-IV symptom of ADHD was omitted due to a clerical error ("is often on the go, or acts as if driven by a motor"). Similar rating scales based on DSM symptoms for ADHD have demonstrated excellent psychometric properties (e.g., DuPaul et al., 1997; Pelham et al., 1992; Wolraich, Feurer, Hannah, Baumgaertel, & Pinnock, 1998).

Objective Measures of Achievement and Rule-Breaking Behavior. In addition to the classification of students based on referral to the office, two other objective measures of achievement/behavior were available. Teachers recorded all instances of school-rule violations on 3 x 5 cards carried by all students at the school (part of the school-wide intervention). These violations were tallied on a daily and weekly basis for each student. For the current analyses, a variable representing the mean number of rule violations per week for the whole school year was used (M = 7.31, SD = 4.00 for the high-risk group; M = 2.62, SD = 1.99 for the low-risk group). Second, the final report card grade point average (GPA) was available (M = 1.67, SD = .88 for the high-risk group; M = 2.82, SD = .81 for the low-risk group).

Student Report of Delinquent Behavior. During the same month that the teachers completed the rating scales, all students were given the opportunity to complete a paper and pencil questionnaire about their own deviant behavior in and out of school. Prior to completing the questionnaires, the researchers or specially trained teacher or guidance counselor informed the students that participation in the survey was voluntary and confidential. Teachers administering questionnaires were provided standardized instructions to read and procedures to follow, including directing students to drop their questionnaires into sealed boxes that were collected and kept confidential by the research staff. All questionnaire instructions, including assurance of confidentiality of student answers, were read aloud to students prior to survey administration.

Students reported how often they had engaged in each of the 24 deviant behaviors in the past 3 months. A sample item is "In the past 3 months, how often have you lied to get what you want or to get out of doing something?" Response options ranged from 0 (never) to 4 (five or more times). Items were adapted from existing measures of delinquency (e.g., Self-Report of Delinquency Questionnaire, Loeber, Farrington, Stonthamer-Loeber, & Van Kammen, 1998; Elliott, Huizinga, & Ageton, 1985) to represent both DSM-IV symptoms of conduct disorder and a range of deviant behaviors in a self-report questionnaire format. A dimensional scale score which we call "delinquency" was calculated as the mean of the 24 items (M = .84, SD = .87 for the high-risk group; M = .33, SD = .42 for the low-risk group). The measure was internally consistent ([alpha] = .95), and students were moderately consistent in their self-reports of recent delinquent behavior, as indicated by a statistically significant correlation (r = .56, n = 233, p [less than].001) between this delinquency variable and mean delinquency calculated from an administration of the same questionnaire to the students 4 months earlier.

Results

Confirmatory Factor Analysis

EQS Version 5.5 for Windows (Bentler & Wu, 1995) was used to test the 3-factor models of the disruptive behavior items. A 3-factor model was tested where the nine inattention items were used as indicators of a first latent factor, the eight impulsivity and hyperactivity items were used as indicators of a second latent factor, and the eight ODD items were used as indicators of a third latent factor. The 2-factor model specified a latent ADHD factor indicated by the 17 ADHD items and a latent ODD factor indicated by the eight ODD items. For the 2- and 3-factor models, correlations among the latent factors were freely estimated, and items were not free to indicate more than one factor. A 1-factor model was tested wherein all items indicated a single latent factor of disruptive behavior. For all models, error terms were assumed to be independent. Because of significant positive skewness for many of the ADHD and ODD items, the Satorra-Bentler chi-squared statistic and associated robust confirmatory fit index (RCFI ) provided by EQS were examined to evaluate model fit. The Satorra-Bentler statistics have been shown to perform quite well under conditions of nonnormality in sample sizes as small as 200 (Curran, West, & Finch, 1996).

The 3-factor model provided the best fit to the data, with a robust CFI of .91. Although the Satorra-Bentler scaled chi-square was statistically significant, [[chi].sup.2](272) = 614.20, p [less than] .00001, indicating statistically significant departure of the model-reproduced covariance matrix from the sample covariance matrix, the standardized root mean square residual (SRMR; average difference between the reproduced and sample correlation matrices) was small (.06), and 92% of the standardized residuals were between -.10 and +.10, indicating adequate reproduction of the observed correlations among the 25 items. Standardized factor loadings ranged from .80 to .92 (M = .87), and all were statistically significant at better than p [less than].001 (see Table 1). The three latent factors were strongly and significantly correlated: inattention with impulsivity-hyperactivity, r = .85, inattention with ODD, r = .77, and impulsivity-hyperactivity with ODD, r = .87. In contrast, the 2-(ADHD and ODD) and 1-factor mo dels fit the data poorly, with the most telling differences being the robust CFI falling substantially below the conventionally accepted level of .90 for adequate model fit (Bentler & Bonett, 1980). For the 2-factor model, Satorra-Bentler [[chi].sup.2] (274) = 840.19, p [less than].00001, robust CFI = .84, SRMR = .07. For the 1-factor model, Satorra-Bentler [[chi].sup.2] (275) = 1107.70, p [less than].00001, robust CFI = .77, SRMR = .08. For the remaining analyses, 3-factor scores were created as means of the relevant items. Subcale internal consistencies were high ([alpha] = .97 for inattention, 9 items; [alpha] = .96 for impulsivity-hyperactivity, 8 items; [alpha] = .96 for ODD, 8 items).

Associations Between Teacher Ratings of Behavior and Criterion Variables

Academic Performance. Students with lower GPAs had higher teacher ratings of inattention (r = -.56, p [less than] .001), impulsivity-hyperactivity (r = -.37, p [less than] .001), and ODD (r = -.54, p [less than] .001). GPA was more strongly associated with inattention than with impulsivity- hyperactivity, t(217) = 5.20, p [less than] .001, and GPA was more strongly associated with ODD than with impulsivity- hyperactivity, t(217) = 4.19, p [less than] .001, as indicated by t-tests of the significance of difference between correlation coefficients when samples are not independent (Klugh, 1974).

Norm- Violating Behavior. Using a one-way MANOVA, a significant multivariate main effect of repeat referrals to the office for discipline was found for the teacher-rating factor scores, F(3, 219) = 33.08, p [less than] .001. Table II shows that students with repeat referrals to the office were rated as more inattentive, impulsive- hyperactive, and oppositional, and the magnitude of the effects were uniformly large. Mean scores for students without repeat referrals were clustered tightly near the bottom end of the scale, whereas mean scores for students with repeat referrals were centered around a value of one with more spread. No statistically significant differences were found among correlations between referral status and inattention (r = .49, p [less than] .001), impulsivity- hyperactivity (r = .48, p [less than] .001), and ODD (r = .54, p [less than] .001). Note that boys were not represented more often in the repeat referrals group (49% of boys were repeat referrals) than were girls (40% of girls were r epeat referrals, [x.sup.2](1) = 1.71, ns), indicating that gender was not responsible for the association between repeat referrals and teacher ratings.

Statistically significant correlations were found between mean weekly rule violations and inattention (r = .67, p < .001), impulsivity-hyperactivity (r = .67, p [less than] .001), and ODD (r = .67, p [less than] .001), and between self-reported delinquent behavior and inattention (r = .18, p [less than].05), impulsivity-hyperactivity (r = .19, p [less than] .05), and ODD (r = .24, p [less than] .01) [7] No statistically significant differences among these associations were found.

Demographic Variables. Teachers gave boys higher ratings than that for girls on all 3-factor scores, indicated by a statistically significant multivariate F(3, 209) = 3.92, p [less than] .01. Table II shows the significant effects of gender on each of the 3-factor scores, and the finding that the effects of gender were uniformly small in magnitude.

STUDY 2: TEACHER RATINGS OF ADOLESCENTS WITH AND WITHOUT CHILDHOOD HISTORIES OF ADHD

Method

Participants

Participants were 224 adolescents participating in an ongoing study of teenagers with and without childhood histories of ADHD. Of these adolescents (probands), 132 were recruited for the larger study because between 1987 and 1995 they had been assessed or had received treatment at an outpatient clinic specializing in the treatment of ADHD at the University of Pittsburgh Medical Center (UPMC). The remaining 92 adolescents, who were without any history of ADHD, were first recruited as adolescents from the community, using newspaper advertisements, flyers in schools, and advertisements in the university hospital voice-mail system. In the full sample, age ranged from 13 to 18 (M = 15.20, SD = 1.42), and most were boys (95.5%). Ethnicity was 88% Caucasians, 8% African Americans, and 4% others. Family income ranged from a low of $8,000 to a high of $300,000 (median = $46,583), and parent education ranged from partial high school to graduate professional. By study design, there were no statistically significant diff erences between the probands and community comparison groups on any of these demographic variables.

ADHD Diagnosis. For the adolescents with childhood ADHD (probands), diagnosis of the disorder in childhood was accomplished with parent and teacher ratings of ADHD symptomatology, using the Disruptive Behavior Disorders Scale (DBD; Pelham et al., 1992). Endorsement of symptoms by parent or teacher sufficient to meet DSMIII-R or DSM-IV criteria for ADHD partially qualified an adolescent for entry into the study. Exclusionary criteria included an IQ of less than 80; seizures or other neurological problems; or a history of pervasive developmental, psychotic, sexual, or organic mental disorders. Community comparison adolescents were admitted to the study as adolescents if they did not meet criteria for ADHD at any time in their lives, based on parent and teacher report with the DBD and by the Diagnostic Interview Schedule for Children, Version 2.3 (Shaffer et al., 1996), as completed by mothers. Presence of other disorders, as long as the above exclusionary criteria were met, were acceptable.

Procedure

As adolescents, probands and the community comparison subjects participated with their parents in a onetime office-based interview. Adolescents, mothers, and fathers were interviewed privately. Confidentiality of information was assured unless suspicion of child abuse or neglect or impending danger to self or others was apparent. After permission was granted by parents and adolescents, a packet of questionnaires that included the DBD was sent to each adolescent's guidance counselor, who was instructed to distribute questionnaires to primary academic course teachers (e.g., English, Social Studies, Mathematics, etc.). Between one and five questionnaires were returned for all but 18 adolescents (92% return rate) whose parents either refused or whose teachers did not complete questionnaires. Because the factor analyses in the current study required complete data for all 26 DSM-IV ADHD and ODD items on the DBD, adolescents were retained for further analyses if at least one randomly selected teacher-rated DBD was c omplete. This resulted in a final data set of 118 adolescents, representing 52% of the probands (n = 68) and 54% of the community comparison adolescents (n = 50). [8] Overall, at least one completed DBD was collected for 53% of the sample, incomplete DBDs were collected for 39% of the sample, and no DBDs were collected for 8% of the sample. Further examination of the incomplete DBDs revealed that, on average, teachers provided in-range responses to 24 out of the 26 questions. Comparisons between the 118 adolescents with, and the 106 adolescents without, a complete set of teacher ratings (no ratings or incomplete ratings) revealed no systematic bias in terms of age, grade, gender, ethnicity, parental income, parental education, status as a proband or community comparison participant, IQ, achievement, or self-reported delinquency. Of the 118 teacher ratings provided, 45% were from English/Language arts teachers, 27% were from Mathematics or Science teachers, 17% were from teachers of Social Studies or a related field (e.g., government, world cultures), and the remaining were from a range of other types of teachers.

Measures

Teacher Reports of ADHD and ODD Symptoms. These were measured using the DBD (Pelham et al., 1992) adapted for DSM-IV. This measure, which reflects the symptoms for ADHD, ODD, and CD listed in the Diagnostic and Statistical Manual of Mental Disorders, DSM-III-R, and DSM-IV, consists of 45 items each, randomly ordered, with four close-ended response options ranging from 0 (not at all) to 3 (very much). Subscale scores from this measure correlate significantly with similar sub-scale scores from other well-known measures such as the Achenbach TRF (Achenbach & Edelbrock, 1986) and the IOWA/Abbreviated Conners Teacher Rating Scale (Goyette, Conners, & Ulrich, 1978; Loney & Milich, 1982; for correlations see Molina, Pelham, Blumenthal, & Galiszewski, 1998). Similar rating scales based on DSM symptoms for ADHD have demonstrated excellent psychometric properties (e.g., DuPaul et al., 1997; Pelham et al., 1992; Wolraich et al., 1998). For the current analyses, 26 items were used, which directly reflected the 18 sympto ms of ADHD and 8 symptoms of ODD in the DSM-IV (e.g., "often interrupts or intrudes on others," "often argues with adults"). The teacher rating measure in Study 1 differed from this measure by its exclusion of CD symptoms, simplified vocabulary, and response options.

Delinquent Behavior, Achievement, IQ. Delinquency was assessed as a count of the conduct disorder symptoms endorsed in the last year by either mother or adolescent, using the Diagnostic Interview Schedule for Children, Version 2.3 or 3.0 (Shaffer er al., 1996). For probands, M = 2.19, SD = 2.38; for community comparison adolescents, M = 1.16, SD = 1.45. A second delinquency score was also calculated as a mean of all DSM-IV conduct disorder symptoms reported on the DBD by teacher and mother (the maximum value across reporters was taken for each symptom). For probands, M = .34, SD = .36; for community comparison adolescents, M = .00, SD = .12. Full-scale IQ in adolescence was estimated using the Vocabulary and Block Design subtests of the WISCIII (Wechsler, 1991) or WAIS-R (Wechsler, 1981; Sattler, 1992). For probands, M = 93.59, SD = 17.90; for community comparison adolescents, M = 105.83, SD = 13.66. Achievement was indicated by the composite standard score of the screener subtests (Reading, Mathematics, Spe lling) from the Wechsler Individual Achievement Test (WIAT; 1992). For probands, M = 91.73, SD = 14.98; for community comparison adolescents, M = 103.20, SD = 12.16. Grade point average (GPA) was provided by each adolescent's guidance counselor. For probands, M = 2.38, SD = .93; for community comparison adolescents, M = 3.12, SD = .91.

Results

Confirmatory Factor Analysis

The 3-factor models tested in Study 1 were tested again in Study 2. Measurement modeling results were virtually identical to those found in Study 1. Although the 3-factor model did not perfectly reproduce the data, it clearly provided the best fit relative to plausible alternative models. The robust CFI was .88, the Satorra-Bentler scaled chi-square was statistically significant, [[chi].sup.2](296) = 437.65, p [less than] .00001, the SRMR was small (.07), and 92% of the standardized residuals were between -.10 and +.10. Standardized factor loadings ranged from a low of .72 to a high of .92 (average loading = .82), and all loadings were statistically significant at better than p [less than] .001 (see Table I). The three latent factors were strongly and significantly correlated: inattention with impulsivity-hyperactivity, r = .77, inattention with ODD, r = .75, impulsivity-hyperactivity with ODD, r = .87. In contrast, the 2-(ADHD and ODD) and 1-factor models fit the data poorly. For the 2-factor model, Satorra-Ben tler [[chi].sup.2](298) = 590.40, p [less than] .00001, robust CFI .75, SRMR = .09. For the 1-factor model, Satorra-Bentler [[chi].sup.2](299) 691.05, p [less than] .00001, robust CFI .67, SRMR = .09. For the remaining analyses, 3-factor scores were created as means of the relevant items. Subscale internal consistencies were high ([alpha] = .96 for inattention, nine items; [alpha] .93 for impulsivity-hyperactivity, nine items; [alpha] = .94 for ODD, eight items).

Associations Between Teacher Ratings of Behavior and Criterion Variables

Academic Performance and intellectual Functioning. Adolescents with higher teacher ratings of inattention, impulsivity-hyperactivity, and ODD had lower IQ scores (r = -.38, p [less than] .001; r = -.39, p [less than] .001; r = -.34, p [less than] .001; respectively), lower achievement scores (r = -.27, p [less than] .01; r -.27, p [less than] .01; r = -.18, p [less than] .10; respectively), and lower GPAs (r = -.63, p [less than] .001; r = -.45, p [less than] .001; r -.37, p [less than] .001; respectively). Although there were no statistically significant differences among the correlations for the standardized laboratory-based measures of functioning (IQ and WIAT achievement), GPA was more strongly correlated with inattention than with impulsivity-hyperactivity, t(99) = 3.24, p [less than] .01, and ODD, t(99) = 4.52, p [less than] .01. The difference between the GPA/impulsivity-hyperactivity and GPA/ODD correlations was not statistically significant, t(99) 1.47, ns.

Norm-Violating Behavior. Adolescents with higher DISC delinquent behavior scores were more inattentive (r = .23, p [less than] .05), impulsive-hyperactive (r .29, p [less than] .01), and oppositional (r = .36, p [less than] .001). DISC delinquency was more strongly associated with ODD than with inattention (t = 1.99, df= 115, p [less than] .05). Adolescents with higher DBD delinquent behavior scores were also more inattentive (r = .48, p [less than] .001), impulsive-hyperactive (r = .54, p [less than] .001), and oppositional (r = .67, p [less than] .001). DBD delinquency was more strongly associated with ODD than with inattention (t = 3.69, df = 114, p [less than] .01) or with impulsivity-hyperactivity (t = 3.01, df = 114, p [less than] .01). There was no difference in the size of the correlations between inattention/ODD and impulsivity-hyperactivity/ODD.

Demographic Variables. Correlations among age and the three teacher rating factor scores generally indicated less prominent symptomatology among older adolescents. They were less inattentive, r = - .22, p [less than] .05, and they were somewhat less impulsive-hyperactive, r = -.16, p [less than] .10, and oppositional, r = -.18, p [less than] .10. There were no significant differences among these associations.

DISCUSSION

The results of the two studies suggest that a 3-factor model of ADHD and ODD symptom ratings by secondary school teachers is superior to more parsimonious, but theoretically plausible, factor structure models. Specifically, the two-dimensional conceptualization of ADHD was supported, as was the empirical distinctiveness of the two ADHD dimensions (inattention and impulsivity-hyperactivity), from a single dimension underlying ODD symptoms. The 3-factor model was upheld in both studies despite several population and methodology differences between them, including age differences (younger sample in Study 1), population differences (school vs. clinic-based samples), and measure differences (rating scale differences between the studies). These findings suggest that the factor structure of symptoms suggested by the DSM-IV is particularly robust. Further, these findings bolster and extend to adolescents the results of other factor analytic studies of teacher ratings of disruptive behavior that support the construct validity of the DSM-IV model (e.g., Burns et al., 1997; Conners et al., 1998a, 1998b; DuPaul et al., 1997; Pillow et al., 1998).

The superiority of the 3-factor model across two samples of adolescents with very different ascertainment histories broadens the generalizability of the findings. Lahey and colleagues also found a similar 2-factor model of ADHD in both school- and clinic-based samples of elementary school-aged children (Lahey et al., 1988). Clinic-based samples, although having greater behavioral variability on the extreme ends of symptom indices such as teacher rating scales, are known for their higher rates of comorbidity and severity of disorder, thus limiting generalizability to children at large (Caron & Rutter, 1991). School-based samples, on the other hand, improve generalizability of results but at a cost; relatively few children fall into the clinical range. Our finding that the 3-factor model of ADHD and ODD symptoms was upheld in mixed samples of high-and low-risk students with wide-ranging disruptive behavior symptomatology suggests that the model is applicable to diverse populations. At the same time, our small mixed samples are not directly comparable to population- or to clinic-based samples, so caution is encouraged when generalizing to other populations. Multiple group analyses with larger samples and a common methodology, where the models can be statistically compared between subgroups (e.g., middle school compared to high school) or different populations (clinic vs. community samples; boys vs. girls), would directly test model equivalence (or lack of it).

We found that teacher ratings of inattention, impulsivity--hyperactivity, and oppositionality were all significantly related to a wide range of criterion variables that included GPA; standardized tests of achievement and IQ; objective measures of rule-breaking; delinquent behavior reported by adolescents, mothers, and teachers; and demographic variables. Previously concerns have been raised about the utility of secondary school teachers' ratings of behavior because of their relative lack of close contact with adolescents compared to elementary school children (Lahey et al., 1994). Our studies yielded an empirical refutation of this concern because the results provide positive evidence for the criterion-related validity of secondary school teacher ratings of behavior in general. However, this does not mean that ratings of student behavior by teachers will not vary from one classroom to the next, as we have shown (Molina et al., 1998). Rather, these results suggest that perceptions of a teacher may be helpful and valid toward capturing some of the difficulties (or lack thereof) experienced by a student in school.

Robust support was obtained for the discriminant validity of the inattention versus impulsivity--hyperactivity dimensions with regard to academic performance. Consistent with previous research findings (Conners et al., 1998b; DuPaul et al., 1998; Lahey et al., 1994), GPA was more strongly associated with teacher ratings of inattention than with teacher ratings of impulsivity--hyperactivity, and this result occurred in the middle school and clinic-based research samples. Interestingly, the association with GPA appears to have particular ecological utility. The correlations between the ADHD variables and GPA were much larger in magnitude (up to .63 for the correlation between inattention and GPA compared with correlations in the .30 to .40 range for IQ and standardized achievement), probably reflecting the greater long-term demands placed on attentional resources associated with earning a higher GPA compared with office-based testing that lasts an hour or two.

We were initially puzzled by the failure of multiple referrals for discipline and mean weekly rule violations to provide evidence of discriminant validity between the ADHD and ODD variables. In post hoc analyses, however, we examined the numbers of students whose teachers rated them as having moderate or severe symptoms of ADHD or ODD in sufficient number to meet symptom count criteria from the DSM-IV for these disorders (e.g., six or more symptoms of inattention). Most students who met the ADHD symptom count were in the referred group and also met symptom count criteria for ODD. Similarly, most students who met the ODD symptom count were in the referred group and also met symptom count criteria for ADHD. [9] Thus, referral status did not serve as a useful index of discriminant validity for ADHD because of the high degree of symptom comorbidity among students who were often sent to the main office for discipline. It is also possible that the middle school teachers failed to discriminate well between ADHD and ODD behaviors for students who were disruptive during class. Such a "negative halo effect" has also been found in previous studies (Schachar, Sandberg, & Rutter, 1986; Abikoff, Courtney, Pelham, & Koplewicz, 1993).

Some support for the discriminant validity of teacher ratings of ADHD versus ODD symptoms was found for the other delinquent behavior variables. In contrast to the official school records of rule-breaking behavior at the middle school, which were strongly correlated with all three of the ADHD/ODD factor scores, the student self-reports of delinquent behavior occurring both in and out of school were less strongly correlated with ratings of inattention than with ratings of ODD. This pattern was statistically significant only in Study 2, which may have been due to methodological differences between the two studies (e.g., increased opportunities for delinquent behavior among older teens in Study 2, a multiple reporter measurement approach for delinquent behavior in Study 2, an emphasis in Study 1 on rating high only those symptoms that caused problems). Thus, our findings suggest some discriminative validity between ADHD and ODD with regard to the more serious delinquent types of behavior that occur outside the school setting, such as stealing and fighting, rather than for behaviors that disrupt class but are not generally considered "delinquent" (e.g., talking out of turn, clowning around, being noisy) and which can result in the student being sent out of the classroom.

In Study 2, we found that teachers gave older teens lower ratings for all three of the DBD variables. The associations between age and behavior ratings were small (r ranges from -.16 to -.22) and of only trend-level significance for the impulsivity-hyperactivity and ODD variables, suggesting a mild decline in ADHD and oppositional behaviors through the adolescent period. This notion of a mild decline with age in the disruptive behavior disorder symptoms, in particular for ADHD, is also supported by the small effect sizes for age (d = .20-.25) obtained by Conners (Conners et al., 1998b) and DuPaul (DuPaul et al., 1997) when they compared teacher ADHD symptom ratings for boys in different age groups (e.g., late elementary school-aged vs. secondary school-aged boys). [10] Thus, even throughout adolescence, there appears to be a small decrease in noticeable levels of disruptive and inattentive behaviors as perceived by teachers. Reports of similar findings that were based on parent report (Conners et al., 1998a; Gomez et al., 1999) or on multiple reporters (Hart et al., 1995) suggest that the decrease may not be limited to perceptions by classroom teachers. Longitudinal studies of children with ADHD find that up to 80% have significant behavioral difficulties in adolescence (for review, see Barkley, 1998), which might explain why age effects for disruptive and inattentive behaviors are small. Whether a subgroup of children with mild attentional and behavioral deficits who learn compensatory strategies accounts for the age-related decline, versus whether a mild decline in symptoms occurs across the board, is a question for future research.

As expected, boys in the middle school received higher ratings than girls for all ADHD and ODD symptoms. Our results confirm and extend those of previous studies of mixed samples of children and adolescents (DuPaul et al., 1997; Conners et al., 1998b), showing a relatively stronger presence of disruptive behavior disorder symptoms for boys than for girls. Our findings are also consistent with meta-analytic conclusions by Gaub and Carlson (1997) that in nonreferred samples girls have fewer problems with inattention, and that in general, gender effect sizes are small but statistically significant for ADHD symptoms and other externalizing behaviors. It is likely that some, but probably not all, of these effects are due to teacher bias toward giving higher symptom ratings to boys, as indicated by Gaub and Carlson's report of the effects of rater source.

In sum, our factor analytic findings taken together with the results of previous factor analytic studies with youth, indicate robust support for the 3-factor model of ADHD and ODD symptoms throughout the childhood and adolescent age range. Our results also provide new data in support of the psychometric properties of teacher behavior ratings for adolescents. Future research examining the power of teacher ratings to discriminate between adolescents with childhood ADHD, as opposed to adolescents with other common childhood disorders such as depression or anxiety, would yield additional helpful data about teacher ratings in adolescence. In general, our findings lend credence to the idea that inattention, impulsivity--hyperactivity, and defiance may be viewed as separate but related constructs that have distinct clinical and theoretical implications. For example, compared to peers with problems with impulsivity--hyperactivity, young adolescents suffering problems related to inattention may have a unique neuropsyc hological profile, brain chemistry, and risk for academic problems. Likewise, compared with inattentive peers, young adolescents with problems primarily related to impulsivity--hyperactivity may have a unique behavioral profile, brain chemistry, and risk for behavioral problems including conduct problems and substance abuse. Exploration of the utility of discriminating among the disruptive behavior dimensions as they relate to the biological, psychological, and social functioning of adolescents could enhance our understanding of these disorders in adolescence.

ACKNOWLEDGMENTS

This research was supported by grants K21 AA00202, R01 AA11873, and P50 AA08746 from the National Institute of Alcohol Abuse and Alcoholism and by seed monies awarded by the University of Pittsburgh Department of Psychiatry. Research was also supported in part by grants from the National Institute on Drug Abuse (DA05605), the National Institute on Alcohol Abuse and Alcoholism (AA0626, AA 11873), and the National Institute of Mental Health (MH4815, MH47390, MH45576, MH50467, and MH53554). Appreciation is extended to Dr. Patrick Curran for his statistical guidance.

(1.) Portions of this article were presented at the 1999 biennial meeting of the International Society for Research on Child and Adolescent Psychopathology, Barcelona, Spain.

(2.) Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.

(3.) Department of Psychology, University of South Carolina, South Carolina.

(4.) Department of Psychology, SUNY at Buffalo, New York.

(5.) Address all correspondence to Brooke S. G. Molina, Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, 3811 O'Hara Street, Pittsburgh, Pennsylvania 15213: e-mail: molinab@msx.upmc.edu.

(6.) "Familiarity" with the student was not operationalized nor measured for teachers. We expect variability in this aspect of relationship between teacher and student, even though team leaders reported that familiarity with the student was considered when assigning raters.

(7.) Because these correlations raise concerns about typographical error, please note that when not rounded, the correlations between mean weekly rule violations and the rating scale variables were .669 for inattention, .673 for impulsivity-hyperactivity, and .665 for ODD.

(8.) For readers concerned about sample size requirements for our factor analyses, we refer to MacCallum, Widaman, Zhang, and Hong (1999). Their Monte Carlo study of sample size effects in factor analysis demonstrated that sample sizes of 100 are acceptable if the factor-to-variable ratio is good (i.e., at least several variables for each factor--more is usually better), not too many factors being estimated (such was the case in our studies), and high communalities (variance in the observed variables accounted for by the factors at .60 or better). Our analyses and results, which resulted in converging solutions with no Heywood cases, met these requirements.

(9.) We report here the numbers of students, in the nonreferred and referred groups, who met DSM-IV symptom count-only criteria for ADHD and ODD. Nonreferred group, neither ADHD nor ODD (n = 112); ODD only (n = 2); ADHD only (n = 3); ADHD and ODD (n = 3). Referred group, neither ADHD nor ODD (n = 55); ODD only (n = 15); ADHD only (n = 6); ADHD and ODD (n = 27). Total Ns = 120 (nonreferred) and 103 (referred). Note that these symptom counts should not be interpreted as "diagnoses" because only teacher ratings of current behavior were considered.

(10.) To calculate the effect sizes from the Canners and colleagues (Conners et al., 1998b) and DuPaul and colleagues (DuPaul et at., 1997) age effect analyses, we divided the relevant group mean differences by the pooled standard deviations, using the means, standard deviations, and Ns provided in the articles.

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