Generalization of the antisocial trait from home to school settings

JOURNAL OF APPLIED DEVELOPMENTAL PSYCHOLOGY | | • 209-223 (1990)

Generalization of the Antisocial Trait from Home to School Settings

ELIZABETH RAMSEY

GERALD R. PATTERSON

Oregon Social Learning Center

HILL M. WALKER

University of Oregon

A model is presented that explains the link between antisocial behavior at home and antisocial behavior at school. It is hypothesized that antisocial behavior evidenced at home at an early age increases the likelihood that antisocial behavior will be displayed at school 1 year later. The model was tested on a sample of 80 fourth-grade males by using the structural equation modeling approach in the EQS analysis program (Bentter, 1986). A chi-square goodness-of-fit test for the model showed a strong agreement between the hypothesized model and the observed covariance structure of the data. Results suggested support for the presence of an antisocial trait that is consistent across time and settings.

Initial training for antisocial child behaviors (e .g. , fighting, lying, noncompliance, stealing, tantrums, firesetting, etc.) usually takes place in the home setting (Kazdin, 1985; Patterson, 1982; Wahler & Dumas, 1986). The child 's home environment and family interaction patterns set the stage for the development of most forms of antisocial behavior. Parents who are socially disadvan- taged, substance abusive, or under a great deal of stress are at risk for major disruptions in parenting skills (Patterson, Reid, & Dishion, in press). As these parents' effectiveness in managing discipline confrontations breaks down, coercive exchanges between them and their children are likely to increase. In fact, Loeber and Dishion (1983) found negative reports of parental family management practices to be the most effective predictor of adolescent delinquency. This

Support for the research presented in this chapter is provided by Grant Nos. MH 37940 and MH 17126, Center for Studies of Antisocial and Violent Behavior, NIMH, U.S. PHS; Grant No. MH 37911, Mood, Anxiety, and Personality Disorders Research Branch, Division of Clinical Research, NIMH, US. PHS; Grant No. HD 22679, Center for Research for Mothers and Children, NICHD, U.S. PHS; Grant No. DA 05304, National Institute of Drug Abuse, U.S. PHS.; and Grant No. (30084300 57, Special Education Programs Office, U.S. DHEW.

Correspondence and requests for reprints should be sent to Elizabeth Ramsey, Oregon Social Learning Center, 207 East 5th Avenue, Suite 202, Eugene, OR 97401.

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210 RAMSEY, PATTERSON, AND WALKER

paper tests the assumption that the antisocial behavior in children learned at home will show evidence of generalization to the school setting.

In past theoretical formulations, many clinicians and researchers believed that child behavior was not highly stable over time or across settings, and that children would eventually outgrow any behavioral problems they might display at a young age. However, it is now generally agreed that children who evidence extreme forms of antisocial behavior at an early age in the home are very likely to maintain such high levels throughout adolescence and into adulthood (Lefko- witz, Eron, Walder, & Huesmann, 1977; Loeber, 1982). As Olweus (1980) has noted, stability coefficients for childhood aggression rival those derived from the stability of IQ scores. Furthermore, such stability in antisocial behavior is established at a surprisingly early age. For example, in an observational study of mother-child interactions, a stability correlation of .49 was found for child coerciveness measured at age 22 months and again at age 42 months (Martin, 1981). Longitudinal studies have also shown a continuity between childhood forms of antisocial behavior with later delinquency and adult crimes (Lefkowitz et al., i977; Patterson et al., in press; West, 1969). Robins' (1974) classic review of 23 follow-up studies of antisocial children led to the conclusion that n o

adult delinquents began their careers after the age of 18 (Robins, 1974). More recent studies strongly suggest that the antisocial pattern begins before Grade 1 (Campbell, Ewing, Breaux, & Szumowski, 1986; Loeber & Dishion, 1983). Not only is there a remarkable continuity in the individual development of antisocial behavior, but there is strong evidence for its transmission across generations (Farrington, 1987; Wahler & Dumas, 1986).

According to Patterson (1982), the above stability data provide support for the hypothesis that extremely aggressive children program their own social environments. The highly predictable reaction of others (e.g., rejection) to antisocial children tends to keep these children locked into the coercion process.

Although most empirical research now indicates a continuity of antisocial behavior across time, a great deal of controversy still surrounds the issue of the consistency of behavior across settings (Epstein, 1979; Mischel, 1984). Much of the work in this area contains mixed findings (Forehand, Breiner, McMahon, & Davies, 1981; Harris & Reid, 1981; Walker & Buckley, 1972). In a 1968 review, Mischel concluded that the antisocial behavior trait was not stable across settings. Mischel's failure to identify strong evidence for consistency is regarded by the present authors and others to be the result of measurement problems resulting from: (a) reliance on single method or agent methodology, (b) use of self-report data, and (c) imprecise definitions (Epstein, 1983; Kenrick & Stringfield, 1980). The present authors assume that to measure a complex trait such as antisocial behavior adequately, it is necessary to conduct assessments that focus on collect- ing information from multiple agents (child, parent, teacher, peers) and using a variety of methods (self-report, direct observation, police records, etc.). In other words, the antisocial trait should be defined as a construct that is a composite of a

GENERALIZATION OF THE ANTISOCIAL TRAIT 211

number of indicators commonly associated with this trait. According to Patterson and Bank (1986), the best way to measure a theoretical entity is to form a nomological network consisting of numerous operational definitions of the same construct, but contributing different facets of understanding to the concept (measurement strategies, different agent conceptualization, etc.). If, for example, one construct indicator correlates highly with the construct as a whole, but has a low correlation with another single indicator, it would not make theoretical sense to drop it. It contributes to the broad composite or trait you wish to define. If only one assessment technique or social agent is used, it is possible to miss the severity and salience of a trait such as antisocial behavior because of possible instrument biases or distortions that occur within individual perception.

A study by Wright (1983) is a good example of an application of the use of aggregated measures in studying the antisocial trait. Wright observed 89 summer camp children characterized as generally aggressive or generally withdrawn. These children were observed on a daily basis across 21 different camp situations (e.g., music, athletics, group meetings, etc.). Each child was observed at least three times on different occasions in each setting. Seventy-two counselors rated the target children on nine different behaviors, including verbal aggression, physical aggression, and impulsivity. It was found that children characterized as aggressive showed consistent levels of aggression across settings, while withdrawn children, in contrast, evidenced relative levels of social withdrawal across settings (Wright, 1983).

Several studies from clinical samples also support the cross-setting consistency hypothesis. Patterson (1976), for example, found that of 27 boys shown to have conduct problems at home, 14 (52%) also had severe social or academic problems in the classroom. In a similar study, Johnson, Bolstad, and Lobitz (1976) observed children in their classrooms who were identified as deviant at home, and found that 50% were problems at school as well. In a study of 39 children referred to the Oregon Social Learning Center (OSI.X2) for severe behavior problems, 97.5% were reported by parents to display at least one problem behavior in both the school and home setting (Kirpatrick, 1978).

The purpose of the present study is to assess the consistency of antisocial behavior across time and settings. Structural equation modeling (SEM) techniques will be used to test the hypothesis that antisocial behavior in the home will persist over time and generalize to the school setting. This model specifies that antisocial behavior in the home will predict antisocial behavior at school 1 year later.

METHOD

Subjects Subjects for this study were drawn from a larger pool recruited by researchers at the Oregon Social Learning Center (OSI_C) for their study of family interaction


processes and antisocial behavior (Patterson & Bank, 1986). Subject families for the OSLC study were recruited from the three major school districts in a medium- sized metropolitan area (pop. about 250,000) and were selected using a multistep process that included (a) the identification of elementary schools considered “at risk” for high rates of delinquency based on police contacts and court records, (b) seeking participation at these schools of Grade 4 boys, their parents, and the

schools in which they were enrolled, and (c) eliminating non-English speaking families and those planning to move out of state in the near future. Two cohorts (n = 103, n = 104) of Grade 4 boys were recruited in 2 consecutive years (see Capaldi & Patterson, 1987; Walker, Shinn, O’Neill, & Ramsey, 1987 for details). Each family was paid up to $300 per year for participation.

For the present study, 80 subjects were selected from these two cohorts and divided into antisocial (n = 39) and at-risk/control (n = 41) subjects groups. Cohort I consisted of 16 subjects in the antisocial group and 19 in the control group; Cohort II consisted of 23 subjects in the antisocial group and 22 subjects in the control group.

For both cohorts, the students were assigned to antisocial or at risk/control groups as a function of their scores on two sets of measures collected by OSLC researchers. First, antisocial construct scores (Patterson & Bank, 1986), derived for the total Patterson sample of over 200 boys and composed of a weighted combination of measures from home observations, child and teacher interviews, and peer nominations, were used as one of the two primary subject selection criteria. Positive scores on this construct were indicative of higher levels of antisocial behavior. The antisocial subjects had a mean positive antisocial construct score of .50; for the control subjects, the average construct score was -.35. The second measure was the aggression subscale score derived from teacher and parent ratings of child behavior on the Achenbach Child Behavior Checklist (Achenbach & Edelbrock, 1983). For the antisocial group, subjects were selected who scored at or above one standard deviation from the Child Behavior Checklist norm sample and who had positive antisocial construct scores. All students in Cohorts I and II were then rank ordered on these dimen- sions; next, their families were contacted regarding study participation, begin- ning with those subjects with the most extreme scores. The control group was selected randomly from the pool of students who had aggression subscale scores in the normal range and whose antisocial construct scores were negative (see Walker et al. 1987) for details of statistically significant comparisons of the two groups on these measures). For purposes of this study, these two subject groups were recombined to create one sample of 80 subjects considered to be at varying levels of risk for the development of antisocial behavior.

No consistent differences were evident in the demographic data for ethnicity or parental income between subject cohorts or groups. Generally, the majority of parents of subjects for Cohorts I and II were in the lower income categories. Only


12% of all sample families earned more than $30,000 per year. Of the subjects in Cohort I, 72% were Caucasoid, compared to 100% in Cohort II.

Procedure

School Data. These data were obtained by (a) systematically observing the target children in their respective classrooms and on the playground, (b) having teachers complete Likert ratings of subjects' social skills (Walker & McConnell, 1988), and (c) inspecting the school records of each subject. Observations of playground behavior of the target subjects with their peers were collected using the Target/Peer Interaction Code (O'Neill, Ramsey, Shinn, Todis, Walker, & Spira, 1985) during two 15-min direct observations in which observers recorded the subjects and their peers' social behavior during continuous 10-s recording intervals. A direct duration measure of academic engaged time was also recorded during two 15-min observations within academic instruction periods in the subjects' classrooms. At the completion of the school year, data from each subject's permanent school file were collected on such measures as referral to or place- ment in special education, school attendance, formal discipline contacts with the school principal, and so forth.

Home Data. Parents and their children participated in a structured interview lasting 1V2 h and completed a number of questionnaires. Children were interviewed separately from their parents. The structured parent interview contained questions concerning the target child's behavior, health, background information, and parenting practices. The Achenbach Child Behavior Checklist was also completed by parents in interview sessions (Achenbach, 1978).

Telephone interviews were also administered to all target subjects (Cham- berlain & Reid, 1987). In each of the six brief telephone interviews, scheduled at least 2 days apart, both the parent and child responded to a series of questions concerning the target child's behavior in the preceding 24 h. The telephone interviews were scheduled at the convenience of the family and were usually administered between four o'clock in the afternoon and eight o'clock in the evening. In all cases, the child and parent (usually the mother) were interviewed separately.

The Family Process Code (Dishion et al., 1984) was used to collect home observation data on three different occasions. Three 50-min observations were conducted for each family. Observations usually occurred at least 1 week apart for 3 weeks. In two-parent families, both parents and at least one sibling had to be present during the observation period. The observation sessions were structured to facilitate the coding of all family members' behavior and to prevent interruptions in interaction sequences. During each observation, the family was asked to: (a) have no guests, (b) limit their family activities to one or two rooms,

214 RAMSpI PATTERSON, AND WALKER

(c) not watch television, and (d) limit phone conversations by not calling out and keeping incoming calls as brief as possible. Generally, the Family Process Code assesses family interaction such as verbal, vocal, nonverbal, and physical behavior, as well as whether the behavior had a negative, positive, or neutral impact. While other assessments-such as court records and laboratory measures-of family problem-solving were made, these data were not included in the model tested here.

Both the Home Antisocial construct and the School Antisocial construct were developed by following the guidelines for this process as outlined by Patterson and Bank (1986) and Capaldi and Patterson (1989). In general, at least four steps were involved in their construction for each of the constructs. First, all the variables from each assessment domain that could possibly define the construct were listed. Second, the measures believed to define a construct were tested using Cronbach’s alpha to determine if they were internally consistent. If the item correlation to the total test score was .60 or better, then that item was retained. The third step in this process involved building a composite score for each measure and testing to see if that score significantly contributed to the construct as a whole. This task was accomplished by carrying out separate factor analyses for each of the two constructs. Those measures with significant factor loadings were retained. Finally, it had to be shown that the measures converged in defining only the construct they were supposed to: The Home Antisocial construct had to be discriminably different from the School Antisocial construct.

Operational Definitions of Constructs

Home AntisociuZ. This construct refers to the contingent use of aversive behaviors by the target subjects in their homes. The construct includes overt antisocial behaviors such as arguing, fighting, swearing, tantrums, and so on, and more covert behaviors such as substance abuse, stealing, lying, and so forth (Capaldi & Patterson, 1989). The child, the parent, and home observational data were used as sources for assessing the degree of home antisocial behavior.

Child Telephone Interview. The telephone interview consisted of 39 items and was administered six times, 3 days apart, to each subject. Each child responded yes or no when asked if, in the last 3 days, he had told a lie, gotten in trouble at school, taken anything, broken anything on purpose, smoked ciga- rettes, or taken any other illegal substance, In addition, subjects were asked about nine different aversive behaviors that might have occurred in the past 24 h. The total number of positive responses was calculated for each phone interview and averaged across all calls.

Home Observation. The Total Aversive Behavior score (TAB) was a summa- ry of all the different categories of coercive behaviors (e.g., destroy, negativism,


noncompliance, tease, yell, etc.) coded during the three observation sessions. The total duration of time the subject spent in coercive behaviors was divided by the total time spent interacting, to provide a measure of TAB.

Parent Report. Parents completed two questionnaires during interviews: the CBC (Achenbach, 1978) and the Overt/Covert Antisocial Behavior questionnaire (OCA). The OCA was developed in 1984 by researchers at OSLC and was designed to measure both overt and covert antisocial behaviors of each subject such as arguing with adults, throwing things, lying, and playing fairly. Thirty-six items from the OCA, 16 items from the CBC, and 17 items from the parent telephone interview were combined to form a parent report indicator for the Home Antisocial construct score. Mean responses for mothers and fathers were calculated separately on each measure and then averaged across the three to form one score for the parent report indicator.

School Antisocial. This construct measures both covert and overt antisocial behaviors displayed in playground and classroom situations at school. Data from the playground and classroom observations, the social skills scale, and the school tracking form were used to measure this construct.

Playground Observations. The Target/Peer Interaction Code (TPIC) (O'Neill et al., 1985) was used to record the free play and social behavior of target subjects and their peers in playground settings. The TPIC required coding of both the target subjects and their interacting peers' social behavior during continuous 10-s intervals. TPIC observations were recorded twice for each subject during daily 15-min recess periods. To simplify this observational data, discrete behaviors observed with the TPIC were aggregated into five composite variables, two of which contributed significantly to the School Antisocial construct score:

1. Total negative behaviors of the target subject: the sum of all negative behaviors emitted (verbal and physical, initiated and noninitiated) by the target subject.

2. Total negative behaviors by peers: the sum of all negative behaviors emitted (verbal and physical, initiated and noninitiated) by the peers of the target subject.

Social Skills Rating Scale. The Walker-McConnell Scale of Social Compe- tence and School Adjustment (Walker & McConnell, 1988) was used to assess teacher perceptions of each subject's social skills. The scale consisted of 43 positively worded items and produced a total social skills score that was used as an indicator for this construct. The total score was the sum of three subscale scores that measure:


1. Teacher-preferred social behavior: peer-related behavioral competencies that teachers value as appropriate to an academic setting (e.g., sharing, assisting other, taking turns, etc.).

2. Peer-preferred social behavior: peer-related behavioral competencies that facilitate the development of friendships and social acceptance (e.g., com- plimenting others, having extended conversations, playing games skillfully, etc .).

3. School adjustment: behavioral competencies that determine a positive teacher-pupil adjustment within instructional contexts (e.g., making assistance needs known appropriately, following classroom rules, compliance, etc.).

Higher scores on this instrument indicated higher levels of perceived social competence and skill. The scale has a national standardization sample (K-6) of 1812 cases. The scale’s psychometric characteristics are excellent and the scale total score and subscale scores powerfully discriminate antisocial from nonan- tisocial students (Walker & McConnell, 1988).

School Record Tracking Form. As mentioned earlier, at the completion of Grade 5 for each subject, project staff required 15-30 min to collect data from each subject’s school file and to summarize (Walker & Todis, 1985). Written products, present in the target subject’s file, constituted the only information that could be entered onto the school tracking form. Among the measures recorded were the total number of school days attended by the subject. Percent absen- teeism was calculated by dividing the number of days absent by the total number of days in that school year. In addition, it was recorded if a child was retained for any grade up to and including Grade 5. Both retentions and attendance contributed significantly to the School Antisocial construct score.

Classroom Observations. Academic engaged time was assessed within each subject’s classroom using a definition and duration recording procedure developed by Walker, Severson, Haring, and Williams (1986). A student was defined as academically engaged if he was (a) attending to the assigned material and the academic tasks involved, (b) making appropriate motor responses (e.g., writing or computing), or (c) asking appropriately for assistance in an acceptable man- ner. Direct observations of pupils’ academic engagement were conducted during two 15-min sessions in which reading or math were being taught and the students were expected to do work. Duration was recorded using a stopwatch to track the amount of time each student was academically engaged during the allotted instructional time in the academic periods observed.

RESULTS

The intercorrelations among the nine indicators for the two constructs are sum- marized in Table 1. Inspection of the table reveals that the degree of convergence


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218 RAMSpI PATTERSON, AND WALKER

for both constructs was satisfactory. The median correlation for the Home Anti- social construct was .33 and the mean was equal to .39. For the School Anti- social construct, the median was - .19 and the mean was .34. The discriminant correlations were also in the same range; thus there was some danger that the model would not work as conceptualized. Ideally, discriminant correlations need to be low and convergent correlations high. Of particular interest were the high correlations between parental reports of antisocial behavior at home and teacher reports of social skills at school and observations of academic engaged time in the classroom. In addition, the correlation between home observations and retention was equal to .40.

Figure 1 outlines the tested model with the standardized coefficients representing the factor loadings of the indicator measures on each construct and the structural relationship between the two constructs. The structural model, using the EQS program, tests the difference between the hypothesized model and the actual observed model (Bentler, 1986). SEM has emerged as an effective method of testing simultaneously the hypotheses that the factor structure for two constructs are well articulated, and that the two constructs are related. In addition, by using SEM one can assess in a number of ways whether or not the hypothesized model works (e.g., significance of path coefficients, indicator loadings, etc.). The model produced an acceptable fit with the observed covariance structure, as indicated by

Grade4

.72

behavior

x2 t2q 34.65

p = .074

n = 80

FIG. 1. The relationship between antisocial behavior in the home and school settings.


a nonsignificant chi square, and is consistent with the hypothesis regarding generalization of antisocial behavior from the home to school setting: ×2 (24) = 34.65, p = .074.

The relationships between each construct and its proposed indicators were also tested. Standardized coefficients representing factor loadings are shown in Figure 1, connecting each indicator with its respective construct. All nine indicators have significant t values: t > 1.96. This means that each construct indicator loaded significantly and also adequately defined its respective construct for this sample. Finally, EQS assesses the standardized structural coefficient along paths that connect the constructs. The path coefficient linking home and school antisocial behavior was .72 (t = 3.79). The School Antisocial construct in Figure 1 indicates that 52% of the variance in subjects' school antisocial behavior was explained in that construct by the Home Antisocial construct.

DISCUSSION

Generally, results of the structural modeling analysis reported herein suggest a reasonable fit between the hypothesized model and the actual empirical findings yielded by the analysis. Antisocial behavior displayed in the home setting ac- counted for a substantial amount of variance (52%) in the School Antisocial construct. It appears that when the antisocial trait is an aggregate measure of multiple behavioral indicators across agents, generalization is apparent across settings and time. Thus, the antisocial trait as defined here meets the definition of a trait as first outlined by Allport (1937). When Allport introduced the notion of a trait in the study of personality, he defined it as a disposition that is stable across time and settings. He also pointed out that traits are "dynamic and flexible dispositions, resulting at least in part, from the integration of specific habits, expressing characteristic modes of adaption to one's surroundings" (Allport, 1937, pp. 139-140). In our own words, multimethod and multiagent behavioral indicators for the antisocial trait are necessary to capture a wide array of habits elicited by varying stimuli in different contexts within an individual's social environment.

The results of this study compliment a relatively sparse literature describing the generalizability of antisocial behavior. Very little systematic research has been conducted to date that examines the cross-setting consistency and temporal stability of the antisocial trait (Mischel, 1984; Patterson, 1982). The assumption, however, is that both prosocial and antisocial behaviors emerge directly from the social exchanges between the child and his or her family members. The training provided in the home defines the first step in a process model. This model assumes that with continued time in the training process, there is a natural escalation in the amplitude of the coercive/negative behaviors performed by the child and other family members (Patterson, 1982). Each successive increase in the intensity of the coercive behavior is reinforced by the fact that it works. If this


is true, the more extreme and intense the maladaptive behaviors at an early age, the more likely the child will be to display the trait of antisocial behavior that will eventually generalize to new settings. Antisocial individuals are, almost by definition, less sensitive to subtle variations in setting demands (Patterson, 1982).

It has been shown that antisocial boys who are extremely deviant in more than one setting are more generally deviant than those who are deviant in only one setting (Loeber & Dishion, 1984). It has also been documented that two-thirds of boys described by their parents as having temper tantrums are also described by their teachers as fighters (Patterson, Reid, & Dishion, in press). Much more needs to be known, however, regarding antisocial children who may not display aversive behaviors across settings or who do not continue their progression along a path leading to the development of antisocial behavior. Furthermore, it needs to be determined which mechanisms explain the stability of an antisocial trait and which control changes in the trait over time. Also needed are longitudinal studies testing the hypothesis that children who are antisocial in both home and school settings are at greater risk for chronic delinquency. It should be noted that research on the situational specificity versus trait-like status of less severe forms of antisocial behavior has not yet been well established.

Our next test will be of the hypothesis that children displaying antisocial behaviors at home and school come from more chaotic families with home environments characterized by inconsistent discipline, overly harsh punishment, little positive reinforcement for prosocial behavior, and lax supervision. Initial support for this hypothesis was provided in the review by Loeber and Dishion (1984), and from the studies by Patterson (1982). Their results suggest that greater disruptions are associated with parental childrearing practices when children fight both at home and at school.

One clear implication seems to emerge from this study: Antisocial behavior treated in one setting cannot be expected to automatically generalize across nontreatment settings. To date, the major thrust of school programming by school psychologists for antisocial students has been based on a “late in the game” identification strategy. As a rule, steps are taken to intervene with a difficult student only after numerous repeat offenses occur. Such steps are often taken too late for a child who has displayed antisocial behavior for many years across a number of settings. In addition, interventions have focused on the individual child with minimal parent involvement in treatment regimens (Simon & Johnston, 1987). The responsibility for effecting behavior change in these intervention approaches rests primarily within the individual student. This study points to the need for parental involvement beyond just the problem identification and assessment phase. Child-centered interventions that exclude parents from intervention planning lose a potential resource for influencing the behavior change process, and most likely will show no generalized effects to the home setting. Research supports the notion that successful treatment in one setting does not spontaneously produce generalization of the behavior changes to other settings (Briener & Forehand, 1981; Wahler, 1969).


The present authors believe that to alter the eventual course of antisocial behavior, interventions must be strongly focused in three areas: (a) teaching family-management techniques to parents, (b) decreasing academic deficits, and (c) remediating the peer-related and adult-related interactional social problems of the child who is at risk for developing antisocial behavior and adopting a delinquent lifestyle in adolescence and adulthood.

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Generalization of the antisocial trait from home to school settings

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