Environmental and Genetic Variance in Children's Observed and Reported Maladaptive Behavior

Child Development, October 1998, Volume 69, Number 5, Pages 1286-1298

Environmental and Genetic Variance in Children's Observed and Reported Maladaptive Behavior

Leslie D. Leve, Allen A. Winebarger, Beverly I. Fagot, John B. Reid, and H. Hill Goldsmith

The genetic and environmental contributions to children's maladaptive behavior are assessed in a sample of 154 twin pairs (77 MZ twin pairs and 77 DZ twin pairs), who range in age from 6 to 11 years. To bridge the strengths of behavioral genetic methods and environmental assessment techniques, we use a multimethod, multimeasure approach to data collection, and analyze the data using behavioral genetic modeling techniques. Results indicate that genetic variation accounts for a majority of the variance in parent-reported child maladaptive behavior (average = 62%). One parent-report measure also suggests a smaller, significant contribution of shared environmental variance. In contrast to the parental ratings, the observational coding and global impressions of parent-twin interactive behavior suggest that shared environment is the primary source of variance accounting for parent and child maladaptive behavior. This is due, in part, to the direct influence one's interactive partner has on the expression of maladaptive behavior in an interactive setting. When controlling for the co-participant's behavior, genetic variation increases and shared environmental variation decreases.

INTRODUCTION

Attempts to disentangle the effects of "nurture" from their context in "nature" have been made throughout the course of the study of psychology and behavioral

genetics (Plomin, DeFries, & McClearn, 1990). Due to inconsistent findings generated from the two disci-

plines, they have traditionally been at odds with one another. However, advances in environmental (e.g., Conger, Ge, Elder, & Lorenz, 1994; Patterson, Reid, & Dishion, 1992) and behavioral genetic (e.g., Neale & Cardon, 1992) approaches make the potential for col- laborative studies quite promising (Reiss, 1993). Spe- cifically, environmentally oriented researchers (e.g., Patterson, 1982) have successfully addressed issues such as diagnostic heterogeneity and method error by taking advantage of behavioral sampling techniques. Approaches using both parent report (checklist and interview) and direct observation help avoid

problems such as reporter bias, knowledge of developmental appropriateness, interviewer bias, and other forms of method variance (Bank, Dishion, Skin- ner, & Patterson, 1990; Schaughency & Rothlind, 1991). Behavioral genetic approaches have also ex-

panded to include statistical techniques for simulta- neous testing of genetic and environmental influences (DeFries & Fulker, 1985), for measuring rater bias, and for measuring gene by environment interactions (Neale & Cardon, 1992). Environmental multimethod approaches combined with the sophis- ticated analysis and modeling techniques provided by behavioral geneticists allow for a more complete

understanding of the environmental and genetic underpinnings of child behavior.

The goal of this study was to integrate the research approaches used by behavioral geneticists and environmental researchers to more completely understand the nature of child maladaptive behavior. This was achieved by collecting both parent-report and observational data on school-age children's negative behavior. Additionally, we sought to examine how parents interact with their children by collecting observational data on parenting interactions. We begin by presenting a selective review of studies that have examined child and parenting behavior using a variety of methods. Our results help clarify some of the discrepancies found in the literature and suggest an explanation for the differences between observational and questionnaire-based assessment.

Genetic and Environmental Influences on Children's Maladaptive Behavior

Parent Report

The primary method for studying genetic and environmental underpinnings of child aversive behavior has been parent report of child behavior. Most typically, the Child Behavior Checklist (CBCL; Achenbach & Edelbrock, 1983) has been the measure of choice. However, even when researchers use the

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Leve et al. 1287

Table 1 Selective Review of Recent Behavioral Genetic Studies Using the Exter-

nalizing or Aggression Subscale of the Child Behavior Checklist

Author N (Pairs) Age (Years) h2 C2

Ghodesian-Carpey & Baker, 1987 38 4-7 .78 .00 Hewitt et al., 1992 249 8-11 boys .40 .59

250 8-11 girls .26 .66 248 12-16 boys .31 .67 234 12-16 girls .33 .61

Schmitz et al., 1994 160 2-4 boys .03 .49 160 2-4 girls .18 .39

van den Oord et al., 1994 426 12 .65 .18

Note: h2 = additive genetic variance; c2 = shared environmental variance.

same self-report measure, differences in the relative contributions of genes and the environment are found. Table 1 presents the sample size, age of child, and genetic and shared environmental variance in several recent studies using externalizing or aggression scores from the CBCL (see Goldsmith, Gottes- man, & Lemery, 1997, for an additional review). As can be seen in Table 1, estimates range from .03 to .78 for genetic variance, and from .00 to .67 for shared environmental variance. This clearly reflects a re- markable difference across studies.

One explanation for these differences across studies is the range in age of the children. The age of child ranges from 2- to 4-year-olds in Schmitz, Cherny, Fulker, and Mrazek (1994), to 12- to 16-year-olds in Hewitt, Silberg, Neale, Eaves, and Erikson (1992). Other longitudinal studies have suggested that the relative contributions of genetic and environmental variance may change over the lifespan (McGue, Bacon, & Lykken, 1993; Pogue-Geile & Rose, 1985). Second, although each study in Table 1 used the CBCL as the measure of child aversive behavior, the studies differ in which parent (mother or father) completed the questionnaire, in which subscale or composite score was analyzed, and in whether boys' and girls' data were analyzed together or separately by sex. For example, Ghodesian-Carpey and Baker (1987) used the aggression subscale of the CBCL, whereas the other studies each used the externalizing composite score. A third explanation for differences in heritability estimates is that the scoring procedures for the CBCL were modified in 1991 (Achenbach, 1991). Van den Oord, Boomsma, and Verhulst (1994) appear to use the newer scoring procedures, whereas the remaining studies in Table 1 use the older scoring procedures. In the older scoring procedure, the items that compose the subscales differ by sex, whereas the newer procedures keep the items constant across sex. Together, these differences in sample age, scale ana-

lyzed, and scoring procedures may account for some of the variation seen in the table. The present study includes mother report of child externalizing and in-

ternalizing behavior on the CBCL to help build on the parental report literature and to assess how similar mother report on the CBCL is to other measures of child maladaptive behavior.

Self-Report

Another common method for assessing maladaptive behavior is self-report. Typically, self-report is not used with young children, as they may not have the cognitive and perspective-taking skills to accu- rately assess their own maladaptive behavior. How- ever, self-report is used in studies of adolescents or adults. Rowe (1983) collected a self-report questionnaire measure of adolescent delinquency in a sample of boys and girls. He found that MZ twins were more alike than DZ twins for both sexes, resulting in heritability estimates of 39% and 61% for boys and girls, respectively, and shared environmental variance estimates of 35% and 37%, respectively. Self-report studies of aggression and antisocial behavior in adults typically find quite strong contributions of genetic effects and little or no effect of shared environment (e.g., McCartney, Harris, & Bernieri, 1990; McGue et al., 1993). A review of the literature on antisocial behavior also suggests moderate to strong heritability estimates in adolescent and adult self-report data (Gottesman & Goldsmith, 1994).

Teacher Report

A third method for examining child maladaptive behavior is to ask the child's teacher. In general, studies using teacher report are less common than studies

using parent or self-report, as twin pairs may be

spread across classrooms or schools, making data col-



1288 Child Development

lection efforts more extensive. Graham and Steven- son (1985) collected teacher-report data on 385 early adolescent twin pairs by asking the teacher who was most familiar with each child to complete the Rutter Teacher Scale of Behavioral Deviance (Rutter, 1967). They found that genetic variance accounted for 23% of the variance in boys' behavior and 66% of the variance in girls' behavior, whereas shared environmental variance accounted for 49% of the variance in boys' behavior and 0% of the variance in girls' behavior. Other studies examining teacher report of child maladaptive behavior are currently underway (e.g., Leve, Reid, & Fagot, 1998; McGue & Iacono, 1995).

Observation

Although use of observational methods has been fairly common in studies of infant behavior, studies of children's maladaptive behavior in middle childhood have most heavily relied on questionnaire assessment. Several recent studies have attempted to change this and integrate multiple methods of assessment. Most notably, the Nonshared Environment in Adolescent Development (NEAD) project includes an observational component (Reiss et al., 1994). Using data from the NEAD project, O'Connor, Hethering- ton, Reiss, and Plomin (1995) reported on adolescents' observed antisocial behavior to their mothers and fathers during 10 min dyadic problem-solving interactions. The adolescents came from a variety of family structures, including identical and fraternal twin families and step-parent families, which allowed for a full range of genetic relatedness among siblings (from identical twins sharing 100% of their genes to unrelated step-siblings sharing 0% of their genes). Adolescent antisocial behavior was coded from the problem-solving interactions using a global coding system of 5 point Likert scales. For antisocial behavior toward the mother, O'Connor and col- leagues found that a significant portion of the variance was accounted for by genetic variability (36%), but that shared environmental variance did not play a significant role. For adolescents' behavior toward their fathers, results indicated significant contributions from genetic (31%) and from shared environmental (17%) variance. Other observational studies using global coding mechanisms have also found stronger contributions from genetic than from shared environmental variance (e.g., Ghodesian-Carpey & Baker, 1987), although the genetic variance component in observational data is generally not as strong as in parent-, self-, or teacher-report studies.

This study measured children's maladaptive behavior with two types of observational coding strate-

gies. First, a time-based sampling technique for assessing behavior in 10 s intervals was used. This allowed for a frequency count of the number of maladaptive behaviors the child exhibited. Second, a global coding system was used to assess an overall rating of child maladaptive behavior. The two coding systems each had their own benefits. The time-based sampling technique was effective at counting fre- quencies and giving a more microsocial recording of child behavior, whereas the global coding impressions were useful for discerning general aspects of the behavior that may be present but not represented by a time-sampling coding system (Weinrott, Reid, Bauske, & Brummett, 1981). The global coding allowed for the inclusion and evaluation of behaviors that may otherwise be missed on standardized time- based sampling systems using prespecified discrete behaviors.

Genetic and Environmental Influences on Parenting Behavior

Because children spend considerable time in the family environment, we also sought to measure parenting interactions. Parenting behavior is one way to examine environmental and genetic influences via the child's extended phenotype. That is, parents may respond to their children differently depending on the child's phenotype. Parenting behavior can be viewed in two ways: (1) Do parents behave consistently with their two children? and (2) Does this con- sistency vary as a function of whether the children are MZ or DZ twins? In the sense that parents modify their behavior depending on the child's phenotype, parenting becomes appropriate for behavioral genetic analysis.

Previous research on the genetic and environmental underpinnings of parent-child interaction is sparse, but two studies found that mothers treat biologically related siblings more similarly than they treat unrelated siblings (Dunn & Plomin, 1986; Rende, Slomkowski, Stocker, Fulker, & Plomin, 1992). In a series of videotaped interactions, mothers were rated as demonstrating more similar levels of control and attention toward nonadoptive sibling pairs than to adoptive sibling pairs, although the correlations for both types of sibling pairs were fairly high (range = .36-.86) (Rende et al., 1992). Shared environmental variance was also a significant con- tributor to mothers' behavior. In the present study, we examined parent-twin dyadic interactions to see if parents tended to treat their twins similarly, regardless of the genetic relatedness of the twin pairs. Furthermore, because children's own behavior can



Leve et al. 1289

affect parenting behavior (Bell & Harper, 1977; Scarr & McCartney, 1983), we examined the similarity of parental treatment toward their children when differences in child behavior toward the parent were statistically removed. In this way, we were able to test whether the genetic and environmental underpinnings of parent-child interaction were influenced by the co-participant's behavior.

In summary, in this study we sought to investigate whether the contributions of genetic and environmental variance vary by method of assessment. As indicated in the previous review of the literature, studies have differed within and between method as to the relative roles of genes and the environment. Furthermore, a majority of studies have relied on questionnaire or interview as the primary method of assessment. By assessing children's maladaptive behavior using two types of observational measures, as well as two more traditional parent-report measures, we attempted to better understand the determinants of child behavior and parent-child interaction.

METHOD

Participants

Participants included 159 twin pairs and their primary caregiver (157 mothers, 2 fathers). The twins were school-aged (median = 8 years, 8 months; SD = 1 year, 9 months), with 94% of the children ranging between 6 and 11 years of age. Zygosity was deter- mined using the Zygosity Questionnaire (Goldsmith, 1991), which taps a wide range of developmental and medical history data. Zygosity questionnaires have historically been found to determine zygosity with an approximate 94% accuracy when compared to blood typing (Goldsmith, 1991). Three pairs of twins were dropped from analyses because they were adopted, and two pairs were dropped because they could not reliably be classified as MZ or DZ. The resulting sample included 154 twin families with the following subgroups: MZ males (n = 42), MZ females (n = 35), DZ males (n = 21), DZ females (n = 21), and DZ male/female twin pairs (n = 35).

Twin families were identified during 1993-1994 through birth announcements, twin organizations, and the public school system in the Williamette Val- ley of Oregon. Research assistants attempted to con- tact all eligible twin families. Twin families who were successfully contacted were provided with a description of the study and were invited to participate in the project. Approximately 50% of the families were originally contacted by phone, and 50% by letter. All families with twins in the appropriate age range who

responded to the solicitation were included in the study. Families were paid for their participation.

The twins were primarily European American (92%), and parents ranged from 24 to 52 years of age, with a median age of 38 years. Parents had a mean of 15 years of education, and their occupational status ranged from 1 to 9 on the Hollingshead occupational code, with the median for fathers equal to 6 (semipro- fessionals and small business owners) and the median for mothers equal to 5 (clerical and sales work- ers). Eighty-six percent of the twins were living in two-parent families. Age of parent and child, eth- nicity, parent occupation, parent education, and family structure did not differ by zygosity of the child. With the exception of family structure-more twins were living in two-parent families than would be ex- pected-the demographic background of the twin families was comparable to other samples of single- tons recruited through our research institute.

Measures

Children and their primary caregiver completed a series of questionnaires, participated at the laboratory in a parent-child interactive session, and individually watched a series of videotaped vignettes. Anal- ysis of the parent questionnaire report of child behavior and the parent-child interactive session are the focus of this study.

Parent Report

Personality Inventory for Children. The Short Form of the Personality Inventory for Children (PIC), revised format (Lachar, 1982), was used as a measure of behavioral and emotional adjustment. The PIC is an objective personality instrument developed as a children's parallel to the Minnesota Multiphasic Per- sonality Inventory (MMPI) for use with children 3 to 16 years of age. Originally 660 items in length, the Short Form of the PIC consists of 131 true-false items that are completed by an adult who is thoroughly familiar with the target child. In this study, the parent who was the primary caregiver completed the instrument at home, prior to the laboratory visit. Parents were asked to complete the questionnaire for each twin on separate days. Scores on the following five raw-score factors were obtained: undisciplined / poor self-control, social incompetence, internalization / somatic symptoms, cognitive development, and a validity factor assessing the parent's tendency to lie. The undisciplined, social incompetence, and internalization raw-item factor scores were used in this

study. The undisciplined factor consists of 30 items,




such as, "My child seems to enjoy destroying things" and "My child doesn't seem to learn from mistakes"; the social incompetence factor consists of 30 items, such as, "My child has little self-confidence" and

"My child has very few friends"; the internalization factor consists of 31 items, such as, "Often my child is afraid of little things" and "Everything has to be perfect or my child isn't satisfied." Test-retest reli-

ability coefficients between .81 and .92 have been demonstrated for the undisciplined, social incompetence, and internalization factor scores (Lachar, Gdowski, & Snyder, 1982; Wirt, Lachar, Klinedinst, & Seat, 1984).

Child Behavior Checklist. The parent who was the

primary caregiver also completed the CBCL at home, prior to the laboratory visit. Again, parents were in- structed to complete the questionnaire for each twin on separate days. The CBCL consists of 115 child behavior problems that parents rated on a 3 point scale as not true, somewhat/sometimes true, or often/ mostly true (Achenbach, 1991). Internalizing and ex-

ternalizing raw-item factor scores were used in this

study. The internalizing factor scale consisted of a

composite of the withdrawn, somatic complaints, and anxious-depressed subscales, and the externaliz-

ing factor scale consisted of a composite of the delin-

quent behavior and aggressive behavior subscales (Achenbach, 1991). The actual items that composed each factor were identical for boys and girls. Reliabil-

ity and concurrent validity have been shown to be

satisfactory (Achenbach, 1991; Achenbach, Howell, Quay, & Conners, 1991).

Observation

Observation behavioral counts. Parent-child dyads participated in three videotaped interactional episodes. The first was a free-play segment, the second was a structured task in which the parent-twin dyad worked together to make a series of difficult designs out of colored blocks, and the third was a clean-up session. Each play episode lasted 5 min, with the ex-

ception of the clean-up phase, which ended when the parent and child indicated they were finished or when the 5 min had passed, whichever came first. The primary caregiver interacted in the laboratory with each twin separately, approximately 30 min apart. The order of participation was counterbal- anced for the birth order of the twins. Videotapes were coded using a modification of the Response Class Matrix (Mash, 1987), in which parent and child behavior is recorded in 10 s intervals. More than one code could be counted in any given interval, although each code was counted no more than once in an interval. Discrete counts of parental directives and

child negative behavior were used in this study. Scores were aggregated across the three interactional

episodes. Parental directives were defined as any statement or question that requested the child to do

something different than what he or she was cur-

rently doing, such as, "Put the red piece in next," or

"Why don't you play with the truck?" Directives could include commands, suggestions, or commands

given in the form of a question. A few parents issued no directives at all in a given episode, and others pro- duced a directive in over two-thirds of the intervals within a given episode.

Child negative behavior was coded as any verbal statement or nonverbal action indicating the affective states of anger, refusal, or discouragement. It included nonverbal actions, such as having a tantrum, throwing an object, or pulling away from the parent's grasp. It also included verbal negatives, such as

name-calling, whining, and refusal. Interrater reli-

ability was .84 for the parental directives and .74 for child negative behavior.

Observer impressions: global ratings. After watching the parent-child interaction episodes, research assistants provided global ratings of the adaptive and

nonadaptive behavior of the parent and child. The

parent global rating scale consisted of 13 items on a 5 point Likert-type scale that assessed the degree to which the parent was supportive of the child, effective at parenting, and able to handle the child's diffi- culties. The child global rating scale consisted of 10 items on a 5 point Likert-type scale that assessed the

degree to which each twin was difficult to parent, involved in the task, and noncompliant to the parent's suggestions. Items were reversed where appropriate, so that higher scores indicated more negative behavior. (See Table 2 for a listing of the actual items.) All the dyadic interactions were videotaped; 84% of the tasks were globally rated from these videotapes, and 16% were globally rated immediately after watching the live interaction. For the mother behavior composite, the average interrater reliability was .85 and the interitem alpha reliability was .84. For the child behavior composite, interrater reliability was .90 and interitem alpha reliability was .83. There were no differences in interitem reliability for the live versus videotaped ratings. Additionally, interrater reliability was similar when the two coders completed their global ratings from the videotapes, or when one of the coders completed the global rating after watching the live interaction.

Statistical Approach

Data were entered using a double-entry data file and analyzed using the augmented DeFries-Fulker



Leve et al. 1291

Table 2 Global Impressions of Parent-Child Interaction Task Rated on 5 Point Scale

Would you judge the parent to be: 1. Sensitive to the child's needs (R) 2. Directive/gave commands to the child 3. Supportive of child's efforts (R) 4. Intrusive in child's activities 5. Encouraging of independent behavior (R) 6. Able to keep child involved in activities (R) 7. Instructive or informative to child (R) 8. Able to share in task completion with child (R) 9. Rushing or hurrying the child

10. Effective (R) 11. Harsh 12. Permissive 13. Having fun (R)

Would you judge the twin to be: 1. Involved in the task (R) 2. Able to perform the task easily (R) 3. Directive/gave commands to the parent 4. Dependent on the parent for guidance 5. Frustrated with the task 6. Compliant to parent's suggestions or commands (R) 7. On task (R) 8. Aggressive 9. Difficult to parent

10. Having fun (R)

Note: (R) indicates that this item was reversed in the creation of the scale.

(DF) regression approach for behavioral genetic model fitting (Cyphers, Phillips, Fulker, & Mrazek, 1990; DeFries & Fulker, 1985), which allows for si- multaneous testing and estimation of both genetic and shared environmental influences. In DF regression, one twin's score is predicted from the co-twin's score, the coefficient of relationship (in twin analyses, MZ = 1 and DZ = .5 for additive genetic effects), and the interaction of the co-twin's score and the coefficient of relationship (Rodgers, Rowe, & Li, 1994). This model is expressed by the following equation:

T, = biT2 + b2R + b3(T2 * R) ? e,

where T1 represents the score on each measure for one twin member of each twin pair, T2 represents the score of the other twin member of each pair, R is the coefficient of genetic relatedness (R = 1.0 for MZ twin

pairs and .5 for DZ twin pairs), the bs are the least-

squares regression coefficients, and e is the error or residual (nonshared environmental variance plus measurement error). In this equation, the bl coefficient estimates the shared environmental variance

(c2) in the population because it represents twin resemblance independent of genetic relatedness. The b2 coefficient reflects, in part, any differences between MZ and DZ twin pairs on each particular measure (see Rodgers et al., 1994, for a discussion of the use

of the b2 coefficient in trait-selected samples as testing the equal shared environmental assumption). The b3 coefficient estimates the population heritability (h2). When statistically significant, the b3 coefficient suggests that twin resemblance is conditioned on the de-

gree of genetic relatedness (R). For each measure, we used a multiple-step proce-

dure to determine the final, best-fitting model, as suggested by Cherny, DeFries, and Fulker (1992). This involved testing the full DF regression model described above first. Then, if the additive genetic effect was negative (h2), it was dropped from the model.

Alternatively, if the estimate of shared environmental variance (C2) was negative, it was dropped from the model and testing was done for nonadditive genetic (dominance) effects. This was achieved by including a term for the coefficient of relationship (d) times the score for the second twin member. The (d) term was coded as 1.00 for MZ twin pairs and .25 for DZ twin

pairs, as specified by genetic theory (Falconer, 1989). Standard errors and significance levels were adjusted for the correct degrees of freedom by multiplying the standard error by the square root (df double-

entered/df single-entered).

RESULTS

The results are presented in two sections. First, de-

scriptive statistics, including the mean, variance, interscale correlations, and intraclass correlations, are

presented for the parent-report and observation variables. Next, model fitting was conducted using a series of DF regression analyses.

Descriptive Information

The means and standard deviations for the parent- report and observation data are presented in Table 3. There was a significant difference by zygosity in the mean level of the undisciplined and social incompetence scales of the Personality Inventory for Children. The mean levels also appeared to suggest that MZ and DZ boys were rated as showing higher levels of

undisciplined and externalizing behavior than MZ and DZ girls. No such sex differences were apparent in the observational data. However, examination of the means for each variable using a Scheff• test indicated that there were no specific significant differences by zygosity group for any scale at the p < .05 level. Furthermore, when zygosity groups were collapsed across child sex to compare the means of all MZ versus all DZ twin pairs, no significant differences were found. Nonetheless, to control for potential sex and age differences between the twin pairs, we regressed out age and sex in the remaining analy-




Table 3 Means and Standard Deviations for Parent-Report and Observation Data

DZ MZ

Male/ Male Female Male Female Female

Measure M (SD) M (SD) M (SD) M (SD) M (SD)

CBCL:

Internalizing 4.6 (4.3) 5.1 (5.1) 3.9 (3.9) 4.6 (5.3) 5.9 (6.0) Externalizing 9.2 (7.5) 6.6 (6.3) 8.1 (7.1) 6.8 (5.4) 8.1 (6.8)

PIC:

Undisciplineda 6.7 (5.0) 4.9 (4.2) 5.6 (4.2) 4.4 (3.0) 6.3 (4.7) Social incompetencea 4.8 (4.3) 5.0 (3.9) 4.9 (3.9) 4.0 (3.7) 5.1 (3.9) Internalizing 3.7 (2.6) 3.4 (3.4) 2.7 (2.7) 3.5 (3.1) 3.8 (3.8)

Observation: Parent directives 6.3 (2.7) 6.2 (2.7) 7.2 (2.9) 7.1 (3.0) 6.7 (3.2) Child negative .3 (.7) .3 (.6) .4 (.7) .4 (.8) .4 (.7)

Observer impressions: Parent negative 1.7 (.4) 1.7 (.5) 1.8 (.4) 1.7 (.5) 1.8 (.6) Child negative 1.6 (.5) 1.6 (.4) 1.7 (.6) 1.6 (.4) 1.7 (.5)

Note: MZ = monozygotic, DZ = dizygotic, CBCL = Child Behavior Checklist, PIC = Personality Inventory for Children. "a The comparison of means for the undisciplined and social incompetence subscales of the PIC indicated a significant difference between zygosity groups at the p < .05 level. When zygosity groups were collapsed across sex to compare the means of all MZ versus all DZ twin pairs, no significant differences were found.

ses. Additionally, because sample sizes were somewhat small within each zygosity type, the sample was collapsed across sex into MZ (n = 77) and DZ (n = 77) groups for the remainder of the analyses.

To assess the relation among the variables by method, the interscale correlations were examined. As shown in Table 4, the interscale correlations indicated high agreement by method. For example, the two CBCL scales and the three PIC scales all correlated significantly with one another. These five mea-

sures compose the parent-report scales. By far the strongest correlations within the parent-report scales were those between scales representing the same content domain. That is, the externalizing scale of the CBCL and the undisciplined scale of the PIC correlated .72; the internalizing scale of the CBCL and the internalizing scale of the PIC correlated .67. There were also strong and significant correlations among the observations and global observer impression measures of parent and child (range = .17-.63). The

Table 4 Interscale Correlations between Parent-Report and Observation Dataa

Measure 2 3 4 5 6 7 8 9

CBCL: 1. Internalizing .62*** .39*** .39*** .67*** -.03 -.07 .15* .10 2. Externalizing .72*** .18** .48*** .04 .02 .18** .14*

PIC: 3. Undisciplined .13* .37*** -.05 .03 .12* .10 4. Social incompetence .36*** -.04 -.08 -.04 .03 5. Internalizing -.01 .07 .17** .19**

Observation: 6. Parent directive .44*** .17** .27** 7. Child negative .40*** .55**

Observer impressions: 8. Parent negative .63** 9. Child negative

"a Corrected for sex and age differences. "*p < .05; **p < .01; ***p < .001.



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Table 5 Raw and Adjusted Intraclass Correlations as Measures of Twin Similarity

MZ DZ

Adjusted Adjusted Raw R Ra Raw R Ra

Measure (SE)b (SE)b (SE)b (SE)b

I. Parent report and observation data CBCL:

Internalizing .80 (.07) .79 (.07) .51 (.10) .51 (.10) Externalizing .86 (.06) .86 (.06) .63 (.09) .64 (.09)

PIC:

Undisciplined .83 (.06) .83 (.06) .40 (.11) .41 (.10) Social incompetence .80 (.07) .80 (.07) .24 (.11) .24 (.11) Internalizing .81 (.07) .80 (.07) .55 (.10) .55 (.10)

Observation: Parent directives .66 (.10) .60 (.10) .53 (.11) .51 (.11) Child negative .54(.11) .52 (.11) .39(.11) .40(.11)

Observer impressions: Parent negative .76 (.08) .77 (.07) .80 (.07) .80 (.07) Child negative .61 (.09) .56 (.10) .44 (.10) .42 (.10)

II. Observation data with co-participants' behavior partialed out Observation:

Parent directives .62 (.11) .57 (.12) .38 (.13) .35 (.13) Child negative .47 (.12) .44 (.13) .30 (.13) .29 (.13)

Observer impressions: Parent negative .78 (.07) .78 (.07) .67 (.09) .60 (.09) Child negative .63 (.09) .58 (.10) .30 (.11) .19 (.11)

"a Corrected for sex and age differences.

b Corrected for the appropriate degrees of freedom.

correlation between parent and child measures suggests that the child's extended phenotype may be playing a role in the parent-child similarity. When the cross-method correlations were examined, as in comparing the PIC social incompetence score to the global impressions of child negative behavior, the correlations were small and in most cases nonsignificant (range = -.08-.19). The variation in correlations by method provides further support for examining each measure individually, rather than forming composite measures.

The intraclass correlations for the individual measures are presented in Part I of Table 5. Correlations listed under Part II of Table 5 will be described in a later section. Part I of Table 5 displays both the raw correlations and the correlations corrected for sex and age differences. In most cases, these adjustments have little effect on relative magnitude of the correlations. As shown in the table, there were some differences between MZ and DZ twin correlations. For most variables, the MZ twin correlations were higher than the DZ twin correlations, suggesting genetic effects. Using the adjusted correlations, genetic effects were suggested for the CBCL internalizing (h2 = .56), the CBCL externalizing (h2 = .44), and the PIC inter-

nalizing (h2 = .50) scales, as estimated by doubling the difference between the MZ and DZ correlations (Falconer, 1989). The MZ correlations for the PIC social incompetence and undisciplined scale were more than twice that of their respective DZ correlations, so that doubling the MZ-DZ difference would overesti- mate heritability. In contrast, the observation and observer impressions data showed less of a difference between MZ and DZ twin pairs, suggesting shared environmental effects. However, stronger conclu- sions can be drawn from the data using model-fitting techniques than from inspection of the correlational patterns.

Model Fitting The best-fitting DF regression models for each of

the variables are presented in Table 6. These models were developed following the procedure described by Cherny, DeFries, and Fulker (1992), as described in the Method section of this article. For each variable, a model showing additive genetic effects (A), common or shared environmental effects (C), and unshared environmental effects (E) is presented if both A and C were positive. When either the A or




Table 6 DF Regression Results for Parent Report and Observation Data: Best Models

Measure Model A D C (E) R2

CBCL: Internalizing ACE .56** (.25) ... .23 .21 .42***

Externalizing ACE .44** (.21) ... .41*** (.17) .15 .58*** PIC:

Undisciplined ADE .78*** (.36) .04 ... .18 .45*** Social incompetence ADE .14 .65* (.42) ... .21 .32***

Internalizing ACE .52** (.24) ... .29 .19 .46*** Observation:

Parent directives ACE .19 ... .42* (.24) .39 .32*** Child negative ACE .24 ... .28 .48 .21***

Observer impressions: Parent negative CE ... ... .79*** (.05) .21 .63*** Child negative ACE .29 ... .27 .44 .24***

Note: Numbers in parentheses following the significant estimates are the standard errors, corrected for the appropriate degrees of freedom. A = additive genetic; D = dominant (nonadditive) genetic; C = common (shared) environmental; E = nonshared environmental variance. "* p < .05; ** p < .01; ***

p < .001.

C parameter was negative, it was dropped from the model. When C was dropped from the model, the effects of genetic nonadditivity were examined, using an ADE model as suggested by Waller (1994). Be- cause the total variance accounted for must sum to 1, E was indirectly estimated by subtracting A and C (or D) from 1. Adjusted significance levels and corrected standard errors are provided for A, D, and C.

As shown in Table 6, the regression analyses provided evidence for additive genetic effects for the CBCL internalizing scale, the PIC undisciplined scale, and the PIC internalizing scale. In addition, the

regression indicated significant dominant genetic effects for the PIC social incompetence scale. Signifi- cant additive genetic and shared environmental effects were both suggested for the CBCL externalizing scale, whereas shared environmental effects alone were important for the observation of parent directives and the observer impressions of parent negatives. Neither genetic nor shared environmental influences were significant for the observation of child

negatives or the observer impressions of child negatives. Although the correlations and regression beta

weights suggest that the children's behavior is similar, we cannot distinguish from these data whether the similarity is due to genetic or shared environmental sources. Additionally, nonshared environmental influences (or error) may be an important source of variance in observed child behavior.

Because the observation and observer impressions data were collected while the parent and child were

engaged in a dyadic interaction, it is possible that some of the variation in each individual's behavior is the direct result of the co-participant's behavior.

That is, the parent could have directly affected the child's behavior, and the child could have directly affected the parent's behavior. To assess the environmental and genetic underpinnings of each participant's behavior that is free from contamination of the co-participant's behavior, a second series of regres- sions was computed for the observation and observer

impression data. Part II of Table 5 provides the ad-

justed and raw correlations of the observational data with the co-participant's behavior partialed out. In

general, these correlations are somewhat lower than the corresponding correlations in Part I of Table 5, especially for the DZ twin pairs.

The regression models analyzed the residual score after the co-participant's behavior had been partialed out, such that parent's behavior was partialed out of the child's behavior when predicting to child variables, and the child's behavior was partialed out from the parent's behavior when predicting to parent variables. The best-fitting models for the residualized scores are presented in Table 7. For one model-the observer impressions of child negative behavior- the best-fitting model included a dominant genetic component. The best-fitting models for the other three observation variables included genetic, shared, and nonshared environmental components. All four models accounted for a significant proportion of the variance, but only the model examining the observer

impressions of parent negatives had a significant estimate of shared environmental variance. None of the residualized variables had a significant estimate of

genetic variance. Compared to the nonresidualized

regression analyses, the heritability estimates for the observational variables are larger and the shared en-



Leve et al. 1295

Table 7 DF Regression Results for Observational Data with Co-Participants' Be- havior Partialed Out

Measure Model A D C (E) R2

Observation: Parent directives ACE .44 ... .13 .43 .22*** Child negative ACE .30 ... .14 .56 .13***

Observer impressions: Parent negative ACE .36 . . . .42** (.18) .22 .46*** Child negative ADE .20 .38 ... .42 .17***

Note: The number in parentheses following the significant estimate is the standard error, corrected for the appropriate degrees of freedom. A = additive genetic; D = dominant (nonadditive) genetic; C = common (shared) environmental; E = nonshared environmental variance. * p < .05; ** p < .01; *** p < .001.

vironmental estimates smaller in Table 7 than in Table 6.

DISCUSSION

Overall, our correlational data show that the twins tend to resemble each other. This is especially true when parental reports of child behavior are examined, as the average MZ twin correlation is .81, and the average DZ twin correlation is .47. When the MZ and DZ twin correlations are compared, the MZ correlations are consistently higher than the DZ correlations for the parent-report data. With the exception of the externalizing scale of the CBCL, the DF regression analyses suggest that at least half the variance of scores from parent-report data results from additive and dominant genetic variation among individuals. Additive genetic and shared environmental variance are both contributing to parental ratings on the CBCL externalizing scale. When comparing these results to previously published studies, the CBCL externalizing data are most similar to those of Hewitt et al. (1992), who also found relatively equal estimates for genetic and shared environmental variation in their analyses of the CBCL, as shown in Table 1. This suggests that the age of the child may play a significant role in determining the relative roles of genes and the environment, as both this and the Hewitt study assess children in the middle childhood age range.

But the age of child cannot be the only important factor influencing the parent-report data because the other parent-report variables in the present study tend to suggest a much greater role for genetic variability than for shared environmental variability. Even though each measure assesses the general quality of child maladaptive behavior, these results suggest that the particular measure or specific quality of child behavior may affect the heritability estimates.

For example, perhaps internalizing behavior (as measured by either the PIC or the CBCL) is a more herita- ble trait than externalizing behavior. Others (Hewitt et al., 1992; Schmitz et al., 1994) have found this to be the case for boys' behavior. Additionally, in two of the three PIC variables, the MZ twin correlation was more than twice that of the DZ correlations, hint- ing that this questionnaire may be particularly sus- ceptible to parental rater bias problems pointed out by other researchers in this area (e.g., Bank et al., 1990; Hewitt et al., 1992).

To collect data using a method that is less suscepti- ble to rater bias, the present study also collected observational data from a parent-child interaction session. Dyads were observed in a structured setting in which the environment was constrained to be similar across families. In contrast to the parent-report data, when the results from the observation data are examined, a different picture emerges. The full models (without the co-participant's behavior partialed out) indicate that shared environmental variation plays a significant role in the observation and observer impressions of parents' directive and negative behavior. Genetic effects on parent behavior are nonsignificant. This suggests that parents treat their children similarly, regardless of the genetic relatedness between the children. This finding is similar to earlier reports of parent-child interaction (e.g., Rende et al., 1992), which have also found that parents tend to treat even unrelated children quite similarly to one another (although genetically related children were treated even more similarly than genetically unrelated children).

The results from the observation of child behavior indicate small, nonsignificant-with our sample size-contributions for both shared environment and genetic variation (the genetic and shared environmental regression coefficients range between .24 and .29). The magnitude of correlations in other studies




investigating children's observed prosocial and antisocial behavior toward their caregiver tend to be similar to those found in the present study. For example, O'Connor et al. (1995) found correlations of approximately .45 for MZ twins and .25 for DZ twins. The adjusted correlations for observed child behavior in this study range from .52 to .56 for MZ twin pairs and .40 to .42 for DZ twin pairs. In comparison to the observations of parent behavior, the observations of child behavior suggest that it is less influenced by shared environmental variance. The idea that child behavior toward the parent is less likely to show shared environmental variance than parental behavior toward their children is not new. In a study of adolescents, O'Connor et al. found that genetic variance accounted for an average of 55% of the reliable variance in children's observed behavior toward their parents, but only 20% of the reliable variance in parents' observed behavior toward their children. This difference in heritability may be the result of two processes. First, genetic variance may be less promi- nent when studying the parents of twins, because we are measuring the child's genes being reflected through the parent's behavior, and the genes are sim- ply more clearly reflected in their own versus others' behavior. Second, differences in heritability may also result from the interactive nature of the observation task. The present study examines what parent and child behavior look like in the observational task, with differences in the co-participant's behavior con- trolled for to see if the context of the interaction has an effect on the heritability of maladaptive behavior.

When the regression analyses are conducted on the observational data with the co-participant's behavior partialed out, the genetic variation increases and the shared environmental variation decreases. This suggests that the co-participant is serving as a primary source of shared environmental variation. When behavior and actions of one individual are statistically removed from the co-participant's behavior, genetic effects appear to account for most of the remaining variation. This is especially true in ex- plaining child behavior. Although new, this finding is not particularly surprising because "shared environment" is defined as the ways in which the children (or twins) experience similar environments. In fact, many environmental researchers have found that parenting practices tend to be relatively consis- tent from child to child within a family (Shortt & Bank, 1996). One would then expect that partialing out parenting behavior from child behavior would result in a significant reduction in shared environmental variation.

Interestingly, shared environment still accounts for over one-third (42%) of the variation in the ob-

server impressions of parent negative behavior. This suggests that parents are perceived to treat their children equally negatively, regardless of the children's behavior. That is, in addition to genetic sources influencing parenting behavior (which account for 36% of parent negative behavior), shared environmental variance continues to account for a significant amount of the parenting behavior even after child behavior is partialed out.

One explanation for the higher estimates of shared environment in the observational data as compared to the parent-report data is that structured settings may result in more similar behavior, regardless of the genetic relatedness of the individuals involved. As suggested by Rende et al. (1992), a constrained context may be more conducive to complementaries in behavior. By contrast, when parents are asked to complete questionnaires or interviews about their children, they are most likely basing their ratings on a wide range of contexts, such that there is a greater likelihood for individual differences in behavior.

In this study we could not address whether it is the observational context, per se, that creates the in- crease in shared environmental variance, or if observational contexts tend to be more constrained than the context parents are using when they rate their children on questionnaires. Given the suggested variability by measure, the next step for researchers inter- ested in understanding children's maladaptive behavior across settings is to compare the similarity of children's behavior across a series of observational sessions that vary in their level of structure. If there are no differences by degree of genetic relatedness depending on the structure of the observational setting, it may be that the types of behaviors measured in observational settings (interactive, microsocial variables) tend to be more influenced by shared environmental variance. On the other hand, if differences are found by degree of genetic relatedness depending on the structure of the observational task, this suggests that behaviors having a shared environmental influence will appear in more structured contexts, whereas behaviors having genetic variance will man- ifest themselves in more unstructured contexts. This information will further our understanding of the genetic and environmental underpinnings of children's maladaptive behavior and clarify the context speci- ficity of behavior.

Although our sample is comparable in size to other developmental observational studies (e.g., Fagot, 1997; Ghodesian-Carpey & Baker, 1987; Shaw, Keenan, & Vondra, 1994), it is somewhat small in comparison to other questionnaire- and interview- based twin studies (e.g., Kendler, Neale, Kessler, Heath, & Eaves, 1992; Silberg, Rutter, Meyer, & Maes,



Leve et al. 1297

1996). Although the smaller sample size limits our

ability to evaluate alternative biometric models, it is

logistically difficult and prohibitively expensive to conduct a large-scale observational study com-

parable in size to the larger questionnaire- and interview-based twin studies. With this smaller

sample, however, we have been able to carefully measure parent-child interactive behavior, thereby addressing several unresolved issues concerning the role that the method of assessment can have on estimates of genetic and environmental influence. Future research with larger samples is needed to build upon these data and entertain more elaborate

hypotheses about the role of method variation in

genetic designs.

ACKNOWLEDGMENTS

This article is partially based on the dissertation of Allen A. Winebarger, University of Oregon, 1994. The research was supported in part by grants R01 MH54248 and P50 MH46690 from the Prevention Re- search Branch, NIMH, U.S. PHS to John B. Reid, grant R01 MH51560 from NIMH, U.S. PHS to H. Hill Gold- smith, the University of Oregon Department of Psy- chology research funds, and grant 5 T32 MH18935, an Emotions Research Training Fellowship from NIMH, U.S. PHS to Allen A. Winebarger. We wish to thank all the twin families who generously volunteered to

participate in this research. We also wish to thank

Beverly I. Fagot, colleague and mentor, for her in- valuable role in this project. Beverly passed away in March 1998. She is deeply missed.

ADDRESSES AND AFFILIATIONS

Corresponding author: Leslie D. Leve, Oregon Social

Learning Center, 160 East 4th Avenue, Eugene, OR 97401-2426; e-mail: [email protected]. Allen A.

Winebarger is at Grand Valley State University; Beverly I. Fagot was formerly at the Oregon Social

Learning Center and University of Oregon; John B. Reid is at the Oregon Social Learning Center; and H. Hill Goldsmith is at the University of Wisconsin- Madison.

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Environmental and Genetic Variance in Children's Observed and Reported Maladaptive Behavior

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