• Home
• Courses Listed by Topic
• Courses Listed by Hrs
• Courses Listed by Code
• CE Requirements
• Colleague Share
• Large Group Discount
• Instructors | About Us
• Free Training Videos
• Create an Account

Objectives. We explored the economic implications of conduct disorder (CD) among adolescents in 4 poor communities in the United States. We examined a range of expenditures related to this disorder across multiple public sectors, including mental health, general health, school, and juvenile justice.
Methods. We used self- and parental-report data to estimate expenditures during a 7-year period in late adolescence of a sample of youths. We contrasted expenditures for youths with CD and youths with oppositional defiant disorder, elevated symptoms (no CD diagnosis), and all others. Diagnosis was determined with a structured assessment.
Results. Additional public costs per child related to CD exceeded $70000 over a 7-year period.
Conclusions. Public expenditures on youths with CD are substantially larger than for youths with closely related conditions, reflecting the importance of prevention and early treatment for the disorder. (Am J Public Health. 2005;95: 1767-1772.)
The high social costs of mental disorder and disease among adults are well documented. For example, in 1990, the costs of depression alone exceeded $43 billion in direct and indirect costs.( n1) These costs are realized in the health and specialty mental health sector and extend into the workplace and beyond.
By contrast, relatively little is known about costs of emotional and behavioral problems among children and youths. Much of the available research focuses on attention-related disorders and is limited to related health expenditures or education costs.( n2-n6) The economic costs of other mental disorders, such as conduct disorder (CD) and oppositional defiant disorder, have received relatively little attention. This research gap is particularly striking in light of the link between these disorders and costly behaviors, such as delinquency. For example, CD, or "a repetitive and persistent pattern of behavior in which the basic rights of others or major age-appropriate societal norms or rules are violated,"( n7) has been linked with criminal activities, illegal substance use and abuse, and problems associated with early sexual debut, such as unwanted pregnancies and sexually transmitted diseases.( n8, n9) To be diagnosed with CD, a youth must display at least 3 criteria from a list of criteria (listed in The Diagnostic and Statistical Manual of Mental Disorders), which includes behaviors such as bullying, threatening, or intimidating others; being truant from school often; and frequently lying to get something or avoid obligations.
The resulting costs to society are potentially enormous and extend over many years. Particularly salient to policymakers are the costs taxpayers incur in the short term. Those costs stem from the youths' involvement in a variety of child-serving sectors, such as juvenile justice, child welfare, special education, and mental health services. For example, in a sample of children served in community mental health centers across the country, conduct-related diagnoses were the most common. Expenditures on services for these children can be quite large, totaling $13 000 or more per child during a 6-month period.( n10)
We used data from the Fast Track study--a longitudinal study of youths residing in poor neighborhoods in 4 communities--to examine the public costs of early conduct problems. The Fast Track study provided the data on which our analyses were based. Those data provided information on system involvement only, and we supplemented that information with data on the costs of those services. We examined the effect of CD on public costs. Finally, we considered the implications of these expenditures and the implications for prevention research.

Used the Eyberg Child Behavior Inventory (ECBI) to measure disruptive behavior problems in children and adolescents. A controversy exists, however, on the dimensional structure of the ECBI. To evaluate this issue, an exploratory factor analysis was first performed on a sample of 1,263 children and adolescents. This analysis identified 3 meaningful factors (i. e., Oppositional Defiant Behavior Toward Adults, Inattentive Behavior, and Conduct Problem Behavior) and a fourth, poorly defined factor. A confirmatory factor analysis (CFA) evaluated the fit of the 3 meaningful factors in a second sample of 1,264 children and adolescents. The 3-factor model with 2 correlated errors provided a excellent fit. This 3-factor model also provided a significantly better fit than 2- and 1-factor models. Multiple group CFA indicated that the factor pattern, item-factor loadings, factor correlations, and correlated errors were equivalent across the samples. The CFA on sex yielded similar results. Initial normative information is presented for boys (n = 1,322) and girls (n = 1,205) within 4 age ranges (i.e., 25, 6-9, 10-13, 14-17) for the 3 factors. The use of these 3 factors, especially Oppositional Defiant Behavior and Conduct Problem Behavior, should make the ECBI more useful as a screening and outcome measure.
The Eyberg Child Behavior Inventory (ECBI) is a parent rating scale widely used to measure disruptive behavior problems in children and adolescents (McMahon & Estes, 1997). Although the ECBI has positive psychometric properties, a controversy exists on the dimensional structure of the measure. Whereas Eyberg (1992) considers the ECBI a unidimensional measure of conduct problem behavior, others (McMahon & Estes, 1997) view the ECBI as a multidimensional measure of disruptive behavior. Although the ECBI contains items similar to the symptoms of oppositional defiant disorder (ODD), conduct disorder (CD), and attention deficit hyperactivity disorder (ADHD), the controversy continues about the dimensional structure of the measure (Eyberg & Colvin, 1994).
Our goal was to reexamine the structure of the ECBI in a more sophisticated manner than the previous studies (Burns & Patterson, 1990, 1991; Burns, Patterson, Nussbaum, & Parker, 1991; Eyberg & Colvin, 1994; Eyberg & Robinson, 1983; Robinson, Eyberg, & Ross, 1980). In an earlier study (Burns & Patterson, 1991), for example, we examined the ECBI's structure in a sample of 1,526 children from five pediatric clinics from four states and in a random sample of 1,003 children from the Seattle School District. We performed a principal components analysis with varimax rotation on each sample. We also limited the number of factors a priori to three because the ECBI contained ADHD, ODD, and CD type items. Although the three dimensions roughly approximated ODD, CD, and ADHD, we did not examine the degree of model fit or the equivalence of the results across the samples or sex. In addition, because we restricted the exploratory factor analysis to three factors, the analysis was not really exploratory. Finally, given the high levels of comorbidity among ADHD, ODD, and CD (Quay & Hogan, 1999), it is questionable whether orthogonal (varimax) rotation was an appropriate decision. These early studies have thus involved a series of questionable statistical decisions and, given the complexities of factor analyses, it is not surprising the studies yielded different conclusions on the factor structure of the ECBI (e.g., Burns & Patterson, 1990, 1991; Eyberg & Colvin, 1994).
To evaluate the structure of the ECBI in a better manner, we first combined the pediatric and random samples. Our next step was to create two random samples from the total data set, 1,263 children and adolescents in the first sample and 1,264 in the second. We then performed an exploratory factor analysis (EFA) with oblique rotation on the first sample. The goal of this exploratory analysis was to determine the number of clinically meaningful dimensions in the ECBI. The model selected from this EFA was then evaluated with confirmatory factor analysis (CFA) in the second sample to determine if the model provided a good fit as well as a significantly better fit than simpler models. In addition, we performed a multiple group CFA to determine if the factor pattern, item-factor loadings, and factor correlations of the model were equivalent across sex and across the samples. Finally, if meaningful dimensions are identified and replicated, we will present initial normative data on these dimensions to make the ECBI more specific as a screening and outcome measure.

ECBI. The ECBI contains 36 disruptive behavior problems. The parent indicates on a 7-point scale how often each behavior occurs; 1 (never), 2 and 3 (seldom), 4 (sometimes), 5 and 6 (often), and 7 (always). The parent also indicates if the occurrence of the specific behavior is currently a problem by circling "yes" or "no" for each behavior. This results in two summary scores--an intensity score (IS) and a problem score (PS). The IS score represents the total frequency of occurrence of the 36 behaviors (possible range from 36 to 252). The PS represents the total number of the 36 behaviors that are indicated to be problems (possible range from 0 to 36). Table 1 shows the 36 items on the ECBI.

For the pediatric sample, a total of 1,526 ECBIs were completed by parents or guardians in five outpatient pediatric clinics in four northwestern states (Pullman, WA; Seattle, WA; Lewiston, ID; Missoula, MT; and Portland, OR). For the random sample, 300 children were randomly selected on the basis of sex and ethnicity (Asian, African American, and Caucasian) within each grade level for Grades 1 to 12 from the Seattle School District (a total of 3,600 parents were mailed ECBIs). A total of 1,003 completed ECBIs were returned by the parents. This return rate of 28% was similar to a return rate of 29% obtained in a second study in the Seattle School District (Bums et al., 1997). Two of the adolescents were 18 years old and these two ratings were eliminated because they were outside the age range of the ECBI (2-17). This left a total of 1,001 children and adolescents.

The combination of the pediatric and random samples resulted in data on 2,527 children and adolescents. The sample was 52% boys and 48% girls, with an average age of 8.95 years (SD = 4.36, range 2-17). A total of 1,639 (65%) of the children were living with their biological mother and father; 464 (18%) with their mother only; 30 (1%) with their father only; 245 (10%) with their mother and stepfather; 42 (2%) with their father and stepmother; 18 (< 1%) with foster parents; and 89 (4%) with other relatives. In terms of ethnicity, 85% of the children were Caucasian, 5% African American, 4% Asian, 3% American Indian, less than 1% Hispanic, and 4% mixed ethnicity (e.g., 1/2 Caucasian and 1/2 African American). A total of 2,180 (86%) ECBIs were completed by the child's mother, 255 (10%) by the child's father, and 92 (4%) by other relatives or foster parents. The average education of the person who completed the ECBI on the child was 13.91 grades (SD = 2.65). A total of 179 (7%) of the raters had not completed high school; 860 (34%) had obtained a high school degree; 626 (25%) had attended some college; 538 (21%) had obtained a college degree; and 324 (13%) had completed some graduate study. In terms of family income, 335 families (14%) reported a yearly income of less than $10,000; 391 (16%) between $10,000 and $19,999; 557 (22%) between $20,000 and $29,999; and 1,194 (48%) over $30,000. Fifty of the raters did not provide information on family income. In terms of treatment status, 2,335 (92%) of the children were not currently in treatment for learning disabilities or behavioral problems; 86 (3%) were in treatment for learning disabilities; 72 (3%) for behavioral problems; and 34 (1%) for learning and behavioral problems.

The 2,257 children were randomly separately into two samples, 1,263 in the first and 1,264 in the second. The random assignment was performed so that each sample contained an equal percentage of children from the pediatric clinics and the Seattle School District. The factor analyses were performed on the IS item ratings because the PS item ratings involved a categorical variable (i.e., a "yes" or "no" answer for each item).
EFA on Sample 1. An EFA with maximum likelihood extraction and promax (oblique) rotation was performed on the Sample 1 IS ratings. Seven eigenvalues were greater than one (11.73, 2.47, 2.07, 1.56, 1.34, 1.32, and 1.10). We examined factor solutions of two to seven factors. In the two-factor model, Factor 1 consisted of ODD and CD type items and Factor 2 ADHD type items. In the three-factor model, the first factor consisted of ODD type items, the second factor CD type items, and the third factor ADHD type items. In the four-factor model, the items with weak loadings on the first factor, the ODD factor, separated to form the fourth factor. In this four-factor model, the ADHD and CD factors emerged as Factors 2 and 3. The five-, six-, and seven-factor models primarily resulted in the fourth factor from the four-factor model dividing into smaller factors. The results from the four-factor model were considered to provide the most clinically useful dimensions. The specific reasons for this decision will be discussed after the presentation of the results from the four-factor model.
Table 1 shows the results from the four-factor model. Items with loadings greater than .29 are shown in boldface in the table. The first factor involved oppositional defiant behavior toward adults (i.e., "argues with parents about rules," "acts defiant when told to do something," "refuses to obey until threatened with punishment," "sasses adults," "refuses to do chores when asked," "gets angry when does not get own way," "does not obey house rules on own," "refuses to go to bed on time," "has temper tantrums," and "yells or screams"). Because the items "slow in getting ready for bed" and "has poor table manners" had low loadings on this factor and did not involve an oppositional defiant aspect, these two items were not included in the CFA on the second sample. The elimination of these two items resulted in a clear and strong Oppositional Defiant Behavior factor.
The second factor contained behaviors similar to the symptoms of ADHD. The four items with the highest loadings represented ADHD inattentive symptoms (i.e., "has short attention span," "is easily distracted," "has difficulty concentrating on one thing," and "fails to finish tasks or projects"). These four items had loadings from .71 to .95. The other two items were somewhat similar to ADHD hyperactivity symptoms (i.e., "is overactive or restless" and "has difficulty entertaining himself alone"). These two items also had loadings substantially lower (.43 and .34, respectively) than the first four items. Given the distinction between inattention and hyperactive and impulsivity symptoms in the Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]; American Psychiatric Association, 1994) and the relative low loadings of these two items, they were not included on this factor for the CFA on Sample 2. The elimination of these two items resulted in a clear Inattentive Behavior factor.
The third factor involved overt and covert conduct problem behaviors. The overt aspect involved verbal and physical aggression toward other children (i.e., "teases or provokes other children," "verbally fights with friends his/her own age," "physically fights with friends his/her own age," "verbally fights with sisters and brothers," and "physically fights with sisters and brothers"). The covert aspect involved the behaviors of lying, stealing, and destruction of property. The item with the lowest loading on this factor was "is careless with toys and other objects" (.33). This item also had a relatively high loading (.26) on the ADHD factor. Because the item was also conceptually different from the other items on this factor, it was not included in the CFA on the second sample. The elimination of this item resulted in a clear Conduct Problem Behavior factor.
The fourth factor did not represent a meaningful dimension (see Table 1). In addition, there were only three items with substantial loadings on this factor (i.e., "whines" "cries easily," and "dawdles or lingers at mealtime"), with the other six items having loadings of approximately .30. This fourth factor may represent a response bias effect (Nunnally & Bernstein, 1994; C. Parks, personal communication, May 8, 2000). For example, when items with low loadings on the first factor separate from the first factor to form a separate factor consisting of items with low loadings, this suggests response bias and the possibility of a meaningless factor. The inclusion of this fourth factor, however, resulted in stronger and clearer first factor because the items on the fourth factor were removed from the first factor. This was the reason that the four-factor model was selected over the three-factor model. The four-factor model thus resulted in three clinically meaningful factors and one factor that did not represent a meaningful dimension and may also represent response bias (Nunnally & Bernstein, 1994; C. Parks, personal communication, May 8, 2000). Our goal in the CFA phase of the study was to evaluate the fit of the three clinically meaningful factors. The fourth factor was not included in the CFA because it did not represent a meaningful dimension, the items on this factor had low loadings, and the factor may represent response bias.
CFA on Sample 2. The first goal was to determine if the three-factor model resulted in a good fit. The three factors were (a) Oppositional Defiant Behavior Toward Adults, (b) Inattentive Behavior, and (c) Conduct Problem Behavior. The second goal was to determine if the fit of this three-factor model was significantly better than two- and one-factor models. In the two-factor model, the Oppositional Defiant and Conduct Problem Behavior factors were combined into a single factor with the Inattentive Behavior dimension being the second factor. In the one-factor model, the three factors were combined into a single factor.
EQS (version 5.7b, Multivariate Software, Encino, CA; Bentler, 1995) was used to perform the CFA on the second sample. Maximum likelihood estimation was used for these analyses along with robust estimation procedures. The EQS Comparative Fit Index (CFI), EQS Robust Comparative Fit Index (RCFI), LISREL Goodness-of-Fit (GFI), the standardized root mean square residual (SRMR), and the root mean square error of approximation (RMSEA) were used to evaluate model fit. The GFI provides a measure of the relative amount of variance and covariance accounted for by the model, whereas the CFI provides a measure of fit of a particular model relative to another model, usually a null model. Values greater than .90 for the GFI and CFI are usually required to indicate a good fit (Byrne, 1994). The SRMR represents the average of the absolute discrepancies between the observed and hypothesized matrices in correlational units (Bentler, 1995). Values of .05 or lower are suggested as necessary to consider a model a good fit. RMSEA provides a measure of model fit relative to the population covariance matrix when the complexity of the model is taken into account. Values less than .05 for the RMSEA indicate a close fit, with values as high as .08 representing a reasonable fit (Joreskog & Sorbom, 1993).
The three-factor model resulted in a reasonable fit. The CFI, RCFI, GFI, SRMR, and RMSEA values for the three-factor model were .860, .849, .860, .060, and .087 (.90 CI = .083-.090), respectively. The Multivariate Lagrange Multiplier Test, however, indicated that a significant improvement in model fit would occur with two correlated errors, DELTAchi2(2) = 540.46, p < .000001. The two-item pairs were "verbally fights with sisters and brothers" with "physically fights with sisters and brothers" and "steals" with "lies". The similar content of the first two items and the perhaps the high co-occurrence of the second two were possible reasons for the high correlations (i.e., .59 and .44, respectively; see Byrne, 1994). The CFI, RCFI, GFI, SRMR, and RMSEA values for the three-factor model with two correlated errors were .913, .907, .900, .049, and .069 (.90 CI = .065-.072), respectively. These values indicate a good fit. The three-factor model with two correlated errors also provided a significantly better fit than the two- and one-factor models, DELTAchi2(4) = 1030.00, p < .000001, and DELTAchi2(5) = 2390.48, p < .000001, respectively.
Multiple-group CFA across samples. A multiple-group CFA was used to determine if the factor pattern, factor loadings, factor correlations, and two correlated errors were equivalent from Sample 2 to Sample 1 (Byrne, 1994). Although it would have been better to have a third sample for this analysis, the results, nonetheless, allow for a specific test of the equivalence of these parameters from Sample 2 to Sample 1. Because there were 25 constraints imposed in this analysis, the per-comparison alpha was set at .002. None of the constraints were significant (all 25 ps > .02 and 23 ps > .05). The factor pattern, loadings, correlations, and correlated errors were thus equivalent across the two samples. Table 2 shows the factor loadings and Table 3 the factor correlations for Sample 1 and Sample 2. Each of the items had a significant loading on its assigned factor (ps < .0001). The factor correlations were significant as well (ps < .0001).
CFA on sex. For boys, the CFI, RCFI, GFI, SRMR, and RMSEA values for the three-factor model with two correlated errors were .911, .908, .891, .052, and .072 (.90 CI = .069-.075), respectively. For girls, these values were .903, .898, .895, .050, and .069 (.90 CI = .066-.073), respectively. This model also provided a significantly better fit than the two- and one-factor models for boys, DELTAchi2(4) = 1,122.28, p < .000001, and DELTAchi2(5) = 2,781.71, p < .000001, respectively, as well as for girls, DELTAchi2(4) = 803.45, p < .000001, and DELTAchi2(5) = 2,002.79, p < .000001, respectively.
Multiple-group CFA on sex. In the multiple-group CFA across sex, 3 of the 25 constraints were significant (ps < .0001). Three of the items had significantly higher loadings for boys than girls (i.e., "destroys toys and other objects," "verbally fights with friends his/her own age," and "physically fights with friends his/her own age"). With the exception of these three items, there was equivalence of factor pattern, factor loadings, factor correlations, and error correlations across sex. Table 2 show the factor loadings and Table 3 the factor correlations for boys and girls. Each of the items had a significant loadings on its assigned factor with the three factor correlations also being significant for boys and girls (ps < .0001).[1]

Table 4 shows the internal consistency coefficients (Cronbach's alpha), means, standard deviations, and the scores corresponding to the 80th, 90th, and 98th percentiles for the Oppositional Defiant, Inattentive, and Conduct Problem Behavior subscales. These results are presented for boys and girls as well as boys and girls within four age ranges (2-5,6-9,10-13,and 14-17).

For boys (n = 1,322), the correlation between the IS and PS Oppositional Defiant Behavior subscales was .77, .70 for the Inattentive Behavior subscales, and .73 for the Conduct Problem Behavior subscales. For girls (n = 1,205), the correlation between the IS and PS Oppositional Defiant Behavior subscales was .77, .70 for the Inattentive Behavior subscales, and .73 for the Conduct Problem Behavior subscales.

Although our normative data on the three subscales do not represent national norms and individuals should carefully consider the characteristics of our sample in their use of these norms, this information on 1,322 boys and 1,205 girls from four states as well as urban and rural settings represents the best available normative information on the ECBI. The normative information also addresses a major limitation of the ECBI. When it is important to identify children who are presenting with "pure" CP [conduct problems], one potential solution [to the problem that the ECBI contains ODD, CD, and ADHD items] might be to score only those items related to either ODD (or ODD and CD), which would facilitate the selection of more homogeneous samples of children (but would preclude the use of existing normative data and cut-off scores). (McMahon & Estes, 1997, p. 153)
Our results provide solutions to these issues. Here we have established and replicated Opposition Defiant, Conduct Problem, and Inattentive Behavior subscales, provided initial normative data on the subscales as well as suggestions for cut-off scores for screening for a more complete assessment (e.g., the 90th percentile score on the subscales). The three subscales should make the ECBI more useful as a screening, outcome, and research measure.
In terms of a screening measure for treatment programs, probably the most common research use of the scale (e.g., Webster-Stratton, 1998), the Oppositional Defiant and Conduct Problem subscales should be particularly useful. As noted in the quote, if the goal is to identify children with only high levels of oppositional defiant behavior for parenting therapy interventions, then high scores on the Oppositional Defiant Behavior subscale would provide a better choice than high scores on the complete ECBI. In addition, the Conduct Problem Behavior subscale would be useful to determine the severity of the child's problems. For example, a child with a high score on the Oppositional Defiant and Conduct Problem Behavior subscales would probably represent a child with more severe problems than a child with only high scores on the Oppositional Defiant Behavior subscale (i.e., a child who has advanced further in the disruptive behavior disorder progression). If a child had high scores on the three subscales, then there would probably be an increased likelihood that a more formal assessment would indicate comorbidity for ODD, CD, and ADHD.
The three subscales may also result in the ECBI being more sensitive to interventions. For example, because many parenting therapy programs focus on increasing the child's compliance in parent-child interactions (McMahon & Wells, 1998), such treatment procedures may result in greater changes on the Oppositional Defiant Behavior subscale than the other two subscales. In addition, the behaviors coded in direct observational systems may have a stronger correlation with the Oppositional Defiant Behavior subscale than the other two subscales, especially given the focus on the child's oppositional defiant behavior toward the parent in these coding systems (McMahon & Estes, 1997). Direct observation of the child's behavior in interactions with other children, however, might show a stronger relation to the Conduct Problem Behavior subscale.
The three subscales should make the ECBI more useful for these reasons. Individuals should remember, however, that DSM-IV ODD is measured much better by the Oppositional Defiant Behavior subscale than the DSM-IV ADHD inattentive symptom dimension is measured by the Inattentive Behavior subscale. In a similar fashion, the CP subscale does not assess the full range of the DSM-IV CD symptoms, especially the more serious ones. In spite of these cautions, we believe that researchers and clinicians will find the subscales, especially the Oppositional Defiant and Conduct Problem Behavior subscales, more useful as screening, outcome, and research measures than the total ECBI score.
1 A CFA was not performed on the PS item ratings due to the categorical nature of the ratings (i.e., "yes" or"no"). It was possible, however, to perform a CFA on the PS ratings through the creation of item sets or parcels. For each factor, the items assigned to that factor were combined into two sets. Items were assigned to the sets based on their loadings from the CFA on the IS ratings (i.e., the item with highest loading was assigned to one set, the item with next highest loading to the next set, and so on until each item on the factor was assigned to one of the two sets). Here each factor is represented by two variables (i.e., two sets of items). The CFI, RCFI, GFI values for the three-factor model on Sample 1, Sample 2, boys and girls were .99 or higher. There was also equivalence across the samples and sex. Although these analyses do not allow for the evaluation of individual items, they can be considered to provide additional support for the three-factor model. These results are available from G. Leonard Burns.

Neurobehavioral characteristics of adolescents with behavioral dysregulation disorder. (eng; includes abstract) By Pineda DA, Ardila A, Rosselli M, Puerta IC, Mejia S, Toro MC, The International Journal Of Neuroscience [Int J Neurosci], ISSN: 0020-7454, 2000; Vol. 101 (1-4), pp. 133-55; PMID: 10765995
Background There is growing recognition that violence and other forms of conduct problems increase during adolescence. The exact relationship between biological, psychological, and social variables has not been defined yet.
Objectives To analyze whether Intelligence Quotients (IQS), neurological history, child behavioral problems, executive functions, and soft neurological signs (SNS) can differentiate between undisciplined and unreliable adolescents (Behavioral Dysregulation Disorder subjects, BDD) and normal controls.
Method Twenty-five 13 to 16-year-olds, adolescents with BDD and 25 matched controls were used in this study. WISC-R, executive function assessment, neurological history, child behavioral problems, and SNS scores were analyzed using a Multivariate Analysis of Variance (MANOVA). A Multiple Regression Stepwise with Criteria Probability of F Analysis was used for predicting criteria variable variance.
Results WISC-R Verbal IQ (VIQ), Information, Similarities, and Vocabulary subtests presented statistically significant differences between BDD and controls (p < .001). No Performance IQ (PIQ) variables established significant differences between both groups. Executive function scores did not detect significant differences between groups either. Prenatal, neonatal, and neurological history scores were similar between both groups. Two child behavioral problem variables were significantly different, with higher scores in BDD group: use of weapons and drug-use (p < 05). A Multiple Regression Stepwise (Criteria Probability of F < .05) model, entering the predictive variables m each domain (intelligence, executive function, neurological antecedents, child behavioral problems, and SNS), and using the score on the criteria variable as dependent variable, found two predictive models: (1) WISC-R Information (Ad-R-SQ = 0.172 F-Ch. = 11.176, p < .01); and (2) WISC-R Information and drug-use (R-SQ: 0.26; F-Ch = 9.605 p < .001).
Conclusions A verbal factor and drug-use predicted fairly 30% of the variance of the criteria variable used for classifying adolescents with BDD. These results would mean that a language underlying factor and an environmental drug-use factor would be related to the BDD in adolescents.
Keywords: Behavioral Dysregulation Disorder; conduct problems; soft neurological signs; executive function
It has been observed that adolescents with aggression and other externalizing conduct disorders may present with some cognitive deficits similar to that found in adult executive dysfunction caused by frontal lobe brain lesions. Examples of such deficits include perseverative behavior, failure to use verbal feedback for correcting responses, and difficulties in sequential memory capability (Blake, Pincus and Buckner, 1995; Elliot, 1992; Giancola and Zeichner, 1994; Lapierre, Braun and Hodgins, 1995). These findings support the neurobehavioral theories that relate criminal behaviors with significant disturbances in inhibiting impulsive responses, presumably associated with frontal dysfunction (Lueger and Gill, 1990). Several studies have found a significant correlation between frontal lobe dysfunction and antisocial behavior in adolescents (Lueger and Gill, 1990: Malloy, Bihrle, Duffy and Cimino, 1992). The above findings support the assumption that conduct disorders may be related to cognitive dysfunctions in the representational systems controlling emotion, self-evaluation, self-control, and self-knowledge (Lewis, 1995).
Cognitive prefrontal dysfunction in adolescents with conduct disorders would suggest that the pattern of impulsive and uncontrolled responses may evolve into an antisocial behavioral pattern in adulthood. There is evidence of a close relationship between adolescence and the beginning of conduct problems either at home or in the street. At this age the highest prevalence of violent behaviors and other conduct problems frequently occur (Albert, Walsh, and Jonik, 1993; Blake et al., 1995).
Some classic studies (e.g., Becker, Isaac and Hynd, 1987; Golden, 1981; Luria, 1966; Passler, Isaac and Hynd, 1985; Yakovlev and Lecours, 1967) have presented developmental information about the different steps in the acquisition of social skill processes controlled by the frontal lobes. This maturation process involves not just as a passive acceptance of social rules without any kind of conflicts, but rather as an adequate development of self-assessment and self-conscious emotional management. The complex of mature social skills could be referred to as "Emotional Intelligence" (Lewis, 1995).
A number of risk factors for antisocial behavior have been established. Disruptive hyperactivity, oppositional defiant disorder, and childhood conduct problems have been strongly related to antisocial behavioral during adolescence (Biederman et al., 1995; Satterfield, Swanson, Schell and Lee, 1994). Several studies have reported that approximately 30% of the subjects who are diagnosed as presenting with Attention Deficit and Hyperactivity Disorder (ADHD) during childhood develop conduct disorders during adolescence (Gittelman, Mannuzza, Ronald and Bonagura, 1985; Mannuzza, Gittelman, Bonagura, Horowitz and Shenker, 1988; Mannuzza, Gittelman, Bonagura, Horowitz and Giampino, 1989). Hence, ADHD in childhood must be considered as an important risk factor for developing conduct disorder during adolescence. The research, however, usually does not specify ADHD type. Other authors have found that adolescent conduct disorders can have associated soft neurological signs (SNS) (Loney et al., 1980; Schonfeld, Shaffer and Barmack, 1989; Shaffer et al., 1985; Spreen, 1981). However, this evidence relating SNS with conduct disorder has been challenged (Lopera, 1997).
Some studies have suggested, that prenatal and neonatal problems could be considered as an additional risk factor for developing adolescent conduct disorders (Harris, 1995; Nichols and Tu-ChuanChen, 1981). Prenatal and neonatal problems may result in nonspecific brain function impairments, associated with some cognitive and behavioral symptoms. Nonetheless, as in any type of behavior, many different factors may be simultaneously acting in cases of conduct problems. Epilepsy represents another risk factor, which has been considered in several researches related to aggressive behavior (Ardila, 1988; Pincus, 1980; Pincus and Levis, 1991; Pined and Puerta, 1997). Socioeconomic status, domestic violence, stressful family and social events, and individual beliefs are also related to the occurrence of conduct disorders in adolescents. Early aggressive behavior increases the risk for developing a wide variety of behavior problems in early adulthood, including drug-abuse.

1. Male, 13 to 16 year-old students with WISC-R (Wechsler, 1993) Full Scale IQ (FSIQ) over 70.
2. A score of over 30 points in the selection questionnaire.
3. Consistent school attendance.
4. Voluntarily participation, as evidenced by documentation of informed consent. Permission was obtained from the parents and school.

1. Male, 13 to 16 year old students with WISC-R Full Scale IQ (FSIQ) over 70.
2. Score under 18 in the selection questionnaire.
3. Consistent school attendance.
4. Voluntarily participation, as evidenced by documentation of informed consent. Permission was obtained from the parents and school.

1. Wechsler Intelligence scales for children (WISC-R). The WISC-R Spanish version (Wechsler, 1993) was administered to the subjects. Verbal IQ (VIQ), Performance IQ (PIQ), and FSIQ were calculated using a prorated score, with four verbal subtests (Information, Similarities, Vocabulary, and Arithmetic) and four Performance subtests (Picture Completion, Block Design, Digit-Symbol, and Picture Arrangement) (Spreen and Strauss, 1991).
2. Wisconsin Card Sorting Test (WSCT). Standard procedures (Heaton, 1981) were used. The following scores were considered: Correct responses, Total errors, Categories, Perseverative responses, Perseverative errors, and Failure to maintain set. This test has normative scores obtained in Colombia (Rosselli and Ardila, 1993).
3. Verbal Fluency. Two conditions were used:

• 4. Trail Making Test (TMT). This is a visuomotor speed test. It is also considered to assess sustained and divided attention, and/or executive functioning (i.e., ability to make mental shifts). This test is included in the Reitan Neuropsychological Battery (Reitan and Wolfson, 1985), and has versions for adults and children (Spreen and Strauss, 1991). For this study the children's version of the test was used. Number of errors and times for Part A and Part B were scored.
• 5. Soft neurological signs (SNS) exam. This measure was composed of 15 items designed to assess the presence of mild difficulties, attributable to developmental anomalies of the central nervous system (CNS). These difficulties were grouped as: perseverations (abnormal serial and alternate geometric figure drawings), constructional dyspraxia (disturbances in the reproduction of five Bender figures), hypotonia (incapacity for sustaining a standing posture with the arms and the hands well extended forward during 30 seconds), ideational dyspraxia (difficulties to imitate ten sequential tool use gestures), ideomotor dyspraxia (difficulties in performing ten symbolic gestures), synkinesia (movements in the contralateral hand when the subject performs oppositional thumb/ finger movements with one hand), finger to nose dysmetria, left/ right orientation problems, dysdiadochokinesia (torpid alternate hand movements), tactile recognition difficulties, visual recognition disorders, and abnormal static posture (incapability to sustain the posture in one leg with the heel of the contralateral foot in tandem during 30 second). A zero to three scale was used. A higher score means a greater number of SNS.
• 6. Child Behavioral Disorders questionnaires. Four different questionnaires were developed. Three questionnaires were constructed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) (American Psychiatric Association, 1994) criteria for:
• 6.1. Attention Deficit/Hyperactivity Disorder (ADHD)
• 6.2. Oppositional Defiant Disorder (ODD), and
• 6.3. Child Conduct Disorder (CCD).

     These questionnaires were answered either by the

     participants' mothers, or by the maternal grandmothers when

     the mother was absent for any reason. Quantitative scores

     were obtained using a zero-to-three scale for each question.

     The higher the score, the greater number of symptoms in the

     participant (Appendix B).

     6.4. Use of weapons and drug-use. The mother and children

     were independently asked to answer some questions about the

     use of weapons and drugs (alcohol, cocaine, "bazuco" -base

     cocaine paste, inhalants, marijuana, heroine, and

     benzodiacepines). A quantitative score was obtained using

     a zero-to-three scale for each question. Similarly, a

     higher score indicates more frequent weapon contact or

     drug use.

7. A prenatal, neonatal and neurological history questionnaire was answered by the subjects' mothers (Appendix C). The following

     questions were included: vaginal bleeding during pregnancy,

     abdominal pain and contractions, infections, use of drugs

     and medications, maternal alcoholism or smoking, eclampsia,

     and seizures during pregnancy. Some questions about the

     children's early development were also included: seizures,

     developmental milestones, cerebral palsy, language and

     motor retardation, meningitis, and encephalitis before the

     age of six. Quantitative scores were obtained using a zero

     (never) to three (almost always; very frequent) scale.

Testing was performed by specially trained graduate neuropsychology students under the supervision of a professor. Examiners were blind to the purpose of the research.

CHILDREN AND ADOLESCENTS WITH EXTREME CONDUCT DISORDER (antisocial behavior) are easily bored, exhibit poorly sustained attention, and tend toward sensation-seeking behavior, according to Quay (1965). Others have supported this proposition (e.g., Borkovec, 1970; DeMyer-Gapin & Scott, 1977; Orris, 1969; Raine, Reynolds, Venables, Mednick, & Farrington, 1998; Siddle, Nicol, & Foggitt, 1973; Skrzypek, 1969; Walker et al., 1991; Whitehill, DeMyer-Gapin, & Scott, 1976). Quay (1977) argued that these characteristics are motivated by a pathological need for stimulation. For example, Skrzypek found that psychopathic delinquents had significantly lower pretest anxiety and significantly higher preference for novelty scores than did neurotic delinquents.
Some investigators (e.g., Skrzypek 1969) used anxious-fearful (i.e., neurotic) participants as a comparison group for participants with conduct disorders in their research designs. That research was designed on the basis of an assumption that fearful-anxious individuals and those with extreme conduct problems represent opposite extremes on an inhibition-extroversion continuum. Skrzypek included neurotic participants in his sample "because they constitute a group which theoretically should be on the opposite extreme of an anxiety and impulse-control continuum from psychopaths and because they could be theoretically characterized as 'pathological stimulus avoiders'" (p. 322). Borkovec (1970) considered the combination of heightened sensation-seeking and a lack of conditioned fear responses to be the "two-edged sword of antisocial behavior" (p. 222). Raine et al. (1998), Siddle et al. (1973), and Whitehill et al. (1976) mentioned the fearlessness of individuals with extreme conduct disorders and the inability to acquire anxiety as an anticipatory warning to punishment. Walker et al. (1991) found that boys with diagnoses of both conduct disorder and anxiety disorder were significantly less impaired than were boys with conduct disorder alone on four dependent measures: (a) peer nominations for fights most, (b) peer nominations for meanest, (c) parent reports of conflict with social systems (i.e., number of police contacts), and (d) school suspensions. In short, these researchers and others (Farrington, Gallagher, Morley, St. Ledger, & West, 1988; Kagan, 1994) viewed the presence of fear and anxiety as a protection against conduct disorders.
Much of the research to date is based on Gray's (1987) neuropsychological theory of fear and stress. Gray posited two neurological systems: (a) a behavioral inhibition system (BIS) that mediates both the expression of fear and the inhibition of behavior under threat of punishment and (b) a behavioral activation system (BAS) that mediates reward seeking and aggression. According to Gray, these two systems are neurologically separate and behaviorally orthogonal. On the basis of the results of their research, several authors have endorsed Gray's theory (e.g., Fowles, 1988; Gorenstein & Newman, 1980; Newman, Patterson, & Kosson, 1987; Quay, 1988, 1993; Shapiro, Quay, Hogan, & Schwartz, 1988; and Walker et al., 1991). The general conclusion has been that novel-stimulus seeking (BAS) is dominant over inhibition and fear (BIS) among antisocial adults and children with conduct disorders.
Such a perspective overlooks the fact that conduct problems and fear-anxiety do co-occur in children. For example, the classification suggested by Eysenck (1967) consisted of four basic personality types corresponding to the ancient Greek typology: neurotic extrovert (choleric), stable extrovert (sanguine), neurotic introvert (melancholic), and stable introvert (phlegmatic). The first type, the neurotic extrovert, may be characterized as irascible, angry, and hot-tempered, yet anxious and fearful. Zoccolillo's (1992) review of research on the co-occurrence of conduct disorders and anxiety disorders strongly supported the existence of this combination. Zoccolillo concluded, " ... anxiety disorders co-occur with conduct disorder[s] and its adult outcomes far more than expected by chance in the general population" (p. 554). Kashani, Deuser, and Reid (1991) confirmed that conclusion, and they found significantly higher anxiety in participants who exhibited both high physical aggression and high verbal aggression. Ialongo, Edelsohn, Werthamer-Larsson, Crockett, and Kellam (1994,1996) found a positive relationship between participants' level of anxiety in the fall during first grade and their level of aggression in the spring of first grade. Furthermore, Ialongo et al. (1996) reported that later aggression was strengthened in the presence of comorbid anxiety rather than attenuated.
Because the BAS and BIS are neurologically separate and orthogonal in their function, we hypothesized that individuals who exhibit high levels of functioning of both systems (i.e., individuals who experience high levels of inhibition as well as high levels of activation) may exhibit high levels of conduct disorders. Such individuals correspond to Eysenck's (1967) neurotic extrovert. The investigations of Kashani et al. (1991) and Ialongo et al. (1994,1996) clearly have supported that proposition. What accounts for the phenomenon? We suspected that the combination of two features--high fear-anxiety (a BIS function) and poorly sustained attention (a BAS function)--causes conduct problems to increase over time. Phenomenologically, we pictured the child who, because of a high threshold for arousal, would chronically seek novel stimulation, but who, because of poorly sustained attention to any single set of stimuli, would gain little information from his or her encounters with the environment. As a result, that child would seem not to learn from experience. Unlike the antisocial, amoral psychopath, that child would have an intact BIS, which would influence the child's level of fear and frustration. When such a child experiences punishing consequences, Gray's (1987) "fight/flight system" (p. 203) would be invoked, and he or she would respond with defensive aggression.
Within this framework, poorly sustained attention can occur in one of two ways. First, arousal levels are constitutionally and probably genetically variable (O'Gorman, 1983). Researchers studying infancy and childhood arousal have confirmed this fact (e.g., Eaves & Glen, 1996; Fagan & Detterman, 1992; Fagan & McGrath, 1981; Lewis & Brooks-Gunn, 1981; McCall, 1994; McCall & Carriger, 1993; D. H. Rose, Slater, & Perry, 1986; and Slater, Earle, Morison, & Rose, 1985). The thrust of this research makes it clear that humans vary, virtually from birth, in the degree to which they actively attend to and explore novel stimuli in the environment. Researchers also have shown links between low levels of attention to novelty and lower cognitive abilities in children and adolescents. We think that the influence of attention to novelty may not be limited to cognitive development, but may influence affective functioning as well. Thus, it seems possible that future adult psychopaths and neurotic extroverts may emerge from those infants who are born with a high need for stimulation and a low level of sustained attention for novel stimulus sets.
The second way in which poorly sustained attention can occur involves the learned responses of children who live in primitive environments. Eaves (Eaves, 1993; Eaves & Awadh, 1998) hypothesized that, at birth, humans are genetically capable of adapting to a wide array of environments. Each of us has the potential to become many different sorts of people. The precise set of environmental events we experience throughout our lives determines which particular traits ultimately characterize the individual. Humans, like all mammals, are able to learn affective routines to ensure survival in harsh environments. Affective routines require individuals to learn directly from their own experiences; to think concretely in terms of sensory representations of actual events; to respond quickly to short-term objectives such as finding food, water, and shelter; to use simple signs to communicate; and to know when to respond to threatening events by fleeing or by aggressing. Humans are equally capable of learning cognitive routines that allow them to thrive in complex, highly technical environments. Such routines place heavy demands on the ability to acquire, retain, and transfer abstract concepts; to think representationally rather than concretely; to develop long-term plans and implement them; to use language to communicate; and to cooperate with others by controlling visceral response to threat and aggression. Successful members of all civilized cultures represent those who have effectively adapted to these cognitive demands.
We have speculated that humans develop those neurologically based routines that most closely conform to the demands placed on them by their environments. Much like domestic pets that fare more poorly than do their feral counterparts when released in the wild, children who grow up in highly urban environments develop few survival routines for subsistence living. Conversely, children who are raised in primitive environments learn few of the socially appropriate behaviors required for success in a modern society. Although researchers have shown that children are immensely malleable during critical periods for learning particular adaptive functions, their malleability rapidly declines after the critical period has ended (e.g., Fromkin, Krashen, Curtiss, Rigler, & Rigler, 1974). At that point, unused neurons die (Hentgartner, 1998) and are absorbed by the body. The neurological pathways that are used become myelinated (i.e., coated with a fatty lipid substance called myelin). Myelination greatly increases processing speed but also grossly diminishes the growth of new synaptic pathways. The ease with which young children learn new languages and the difficulty experienced by most adults on the same task is an example of the phenomenon of critical periods. Thus, the human ability to learn new adaptive routines is generally more fluid during the developmental years and less so during adulthood.
Imagine a boy from a poor home with a depressed, alcoholic mother and a bitter, unemployed father, both of whom are abusive and highly inconsistent in their disciplinary practices. For this child, the supply of basic human needs (e.g., food, warmth, shelter) is unpredictable. Interactions with his mother are inexplicably cordial, even loving, one moment, and rejecting the next. His father often beats him, but the beatings are related more to the father's humiliation, frustration, and failure to succeed than to the boy's misbehavior. The human values and technical skills embraced by modern civilization and imparted in his school appear foreign and absurd to the child. Although he spends much of his life at home fending for himself, at school he must have permission for the simple act of going to the restroom. His teachers promote the virtues of learning long division and phonetic analysis, but the child can find no applications of long division or phonetic analysis in the daily routine of his own life. For such a child, life is not just harsh, but confusing as well. At birth, such a child may have a normal behavior activation system and a normal behavior inhibition system, but over time, he ceases to search for stable relationships among environmental stimuli. Gradually and without conscious awareness, his unspoken dictum becomes, "Life is chaotic; why spend time searching for structure?" For such a child, the only rule is that there are no rules, and because the environment is not only unstructured, but also highly punitive, he develops a wide array of fears and anxieties. We have proposed that a child who grows up in such environments develops defensive reactions as a way of life. That is, the combination of a chaotic (permanently novel) environment and the fears that are produced by such an environment creates a child who perceives threat and pain in ordinary, routine interactions with others. In the end, he "defends himself ... by striking preemptively" (Ialongo et al., 1996, p. 447). Thus, it seems possible that children with conduct problems may be environmentally induced as a function of low attention to novelty, high fear-anxiety, and time.
Our purpose in this study was to investigate the plausibility of the last assertion. Specifically, we tested the following null hypotheses:

1. The level of conduct problems does not change as the level of attention to novelty changes.
2. The level of conduct problems does not change as the level of fear-anxiety changes.
3. The level of conduct problems does not change as age changes.
4. The level of conduct problems does not change as a function of the interaction between levels of attention to novelty, fear-anxiety, and age.

Alternatively, we hypothesized that low attention to novelty would lead to more conduct problems, that high fear-anxiety would lead to more conduct problems, and that age would interact with level of attention to novelty and level of fear-anxiety to influence level of conduct problems. Specifically, we expected older children with lower levels of attention to novelty and higher levels of fear-anxiety to show higher levels of conduct problems. Conversely, we expected older children with higher levels of attention to novelty and lower levels of fear-anxiety to show lower levels of conduct problems.