Epilepsia, 33(6):1115-1122, 1992 Raven Press, Ltd., New York 0 International League Against Epilepsy
Correlates of Behavior Problems in Children with Epilepsy Joan K. Austin, "Michael W. Risinger, and ?Laurel A. Beckett Department of PsychiatriclMental Health Nursing, Indiana University School of Nursing, Indianapolis, Indiana; *Minnesota Comprehensive Epilepsy Program, P . A., Minneapolis, Minnesota; and f Channing Laboratory, Harvard Medical School, and Department of Biostatistics, Hurvard School of Public Health, Boston, Massachusetts, U.S.A.
Summary: We report results from the first part of an ongoing longitudinal study aimed at identifying the relative contributions of demographic, seizure, and family variables in the prediction of behavior problems in children with epilepsy. We studied 127 children with epilepsy aged 8-12 years and their mothers. Self-report questionnaires, interviews, and medical records were data sources. Backward and forward stepwise elimination procedures using multiple regression indicated five variables that contrib-
uted significantly to prediction of behavior problems: female gender, family stress, family mastery, extended family social support, and seizure frequency. These factors accounted for 29% (p < 0.001) of the variation in behavioral problems. Findings suggest that family variables are important correlates of behavior problems and should be considered in clinical management of children with epilepsy. Key Words: Behavior-Child-EpilepsyFamily-Seizure-Behavior therapy.
Substantial evidence shows that children with epilepsy have a higher incidence of mental health problems than do children with other chronic physical disorders. Children with epilepsy have been shown to have poorer self-concepts (Matthews et al., 1982; Margalit and Heiman, 1983; Austin, 1989) and more behavioral problems and psychiatric disturbances (Rutter et al., 1970; Scott, 1978; Hoare, 1984~;Austin, 1989) than do children with other chronic physical conditions. Factors leading to behavior problems in children with epilepsy have not been well delineated in research studies, making it difficult for clinicians to identify children in need of preventive interventions. Research suggests that several different factors, including demographic, seizure, and family variables, influence adaptation to childhood epilepsy. Demographic variables that have been identified as being potential risk factors for behavior problems in children with epilepsy include low socioeconomic status (SES) (Hermann and Whitman, 1986; Hermann et al., 1989; Hoare and Kerley, 1991) and young age (Hoare and Kerley, 1991). Research on gender and psychopathology has been inconsistent, with no differences reported by some investigators
(Holdsworth and Whitmore, 1974; Hoare and Kerley, 1991), but at least one study showing boys to be more at risk for behavioral problems at school than girls (Stores, 1978). Most research has focused on the relationship between seizure variables and adaptation (Hermann, 1986), and several seizure variables have been linked with mental health problems. Hermann et al. (1989) reported that age at onset of seizures, seizure control, seizure type, etiology, duration of epilepsy, and treatment with more than one antiepileptic drug (AED) were associated with some types of behavior problems in children with epilepsy. Other researchers (Hoare, 1984~;Austin, 1988) have reported that seizure frequency is positively associated with behavioral problems. Results have not always been consistent: e.g., Hoare (1984~)reported that focal EEG abnormalities and complex partial seizures (CPS) were associated with increased psychiatric disturbance. In contrast, Whitman et al. (1982) noted no relationship between temporal lobe epilepsy and psychopathology in children with epilepsy. Evidence shows that children with epilepsy who also have deficits in neuropsychological functioning may be at increased risk for psychopathology (Hermann, 1981, 1982; Rutter, 1981). Lending support for the hypothesis that brain insult is linked with psychopathology is the consistent finding of a higher incidence of psychiatric disorder in children
Received November 1991; revision accepted March 1992. Address correspondence and reprint requests to Dr. J. K. Austin at Indiana University School of Nursing, 1111 Middle Dr., Indianapolis, IN, U.S. A.
1115
J . K . AUSTIN ET A L .
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with chronic conditions involving the brain than in children with chronic conditions not involving the brain (Rutter et al., 1970; Breslau, 1985; Austin, 1989). Furthermore, the findings by Hoare (1984~) that children with newly diagnosed epilepsy had a higher rate of psychiatric disturbance than children with newly diagnosed diabetes supports the hypothesis that a neurologic dysfunction predisposed the children to both the epilepsy and the psychiatric disorder. Family factors have also been shown to be associated with behavior problems in children with epilepsy. Hermann et al. (1989) reported divorced or separated parents to be a predictor of behavior problems, especially depression, in both boys and girls. In a small descriptive study, Mulder and Suurmeijer (1977) noted a relationship between parental control and dependency in the child with epilepsy. Hoare and Kerley (1991) reported an association between family stress and child behavioral disturbance. Austin (1988) reported differences in family characteristics between children who had behavioral problems and those who did not. Families of children with problems were shown to have significantly poorer functioning, less intrafamily esteem and communication, less extended family social support, and less financial efficacy than families of children without problems. Unfortunately these studies have been limited by small samples, limited measurement of family attributes, or failure to consider seizure and demographic variables in the same analysis with family variables. This literature review shows that demographic, seizure, and family variables have all been shown to be associated with behavior problems in children with epilepsy, but because past studies have not used multivariate designs or statistical techniques, the relative importance of these three types of variables is not known. Consequently, Hermann (Hermann and Whitman, 1986; Hermann et al., 1989) recommended that a multietiologic approach be used in future investigations of childhood psychopathology in epilepsy. We report results from the first part of an ongoing longitudinal study with a multietiologic approach designed to identify the relative contributions of demographic , seizure, and family variables in prediction of child behavior problems.
METHODS Sample We studied 136 children aged 8-12 years with epilepsy for at least 1 year, currently receiving prescribed AEDs, with no other chronic conditions, Epilepsiu, Vol. 33, No. 6, 1992
who had an IQ of at least 70. Children in classes for the mildly mentally handicapped were excluded. Approximately 85% were from four outpatient clinics in two large medical facilities plus the private patients of the pediatric neurologists from these clinics. Approximately 10% of the sample were children treated by private neurologists, and 5% were children who had been evaluated by one of the participating neurologists but were being treated by a pediatrician at the time of the interview. The families of all children meeting the criteria in these clinics were asked to participate. Only one family declined because of the time involved for the interview. Approximately 89% of the sample were white, 10% black, and 1% other. Parents or legal guardians were also interviewed and asked to complete questionnaires about the child and the family. The sample for the current analysis was 127 children and their mothers. Nine children from the total sample were excluded: 4 because their epilepsy syndrome could not be classified, 2 because their mothers did not participate, and 3 because they had not received AEDs in the month before the interview. Procedures Once we determined from the medical records that subjects met the criteria, parents were approached about the study and asked for permission to approach their children. Interviews and selfreport questionnaires were completed independently by parents and children. Approximately one half of the data collection took place before or after regularly scheduled appointments with physicians and one half took place in the home. Instrumentation
Child behavior problems The dependent variable, behavioral functioning of the child, was measured by the mothers’ ratings on the Child Behavior Checklist (CBCL) (Achenbach and Edelbrock, 1983). The CBCL consists of 118 behavior problem items on which parents rate their children using 3-point scales, with a higher score reflecting more problems. Past research has shown the scale to have strong reliability and validity (Achenbach and Edelbrock, 1983; Jones et al., 1988) and to be relevant for use with children with epilepsy (Dorenbaum et al., 1985). Internal consistency reliability for the total behavior problems score used in this analysis was 0.95. Raw scores for the total behavior problems score were converted to standardized T scores (mean 50, SD 10) and normed for age and gender as specified by Achenbach and Edelbrock (1983).
CHILD BEHAVIOR PROBLEMS Demographic variables Child age was measured to the nearest month. SES was measured by the method of Green (1970), in which income, education, and occupation are combined in one scale. This scale has been shown to be a reliable and valid indicator of SES in prediction of health behavior (Green, 1970). Seizure variables Four seizure variables were included as independent variables in the analysis: epilepsy syndrome, age of onset, seizure frequency, and polytherapy . To measure epilepsy syndrome, children were assigned by M.R. to either a generalized or partial syndrome category and a primary (idiopathic) or secondary (symptomatic) subcategory. The International League Against Epilepsy classification was used (Commission, 1989). Classification of epilepsy syndrome, which is dependent in part on identification of seizure type, provides additional information regarding the presumptive or proven etiology of the patient’s illness. The classification used in the current study was intended to distinguish between patients with known presumed or acquired cerebral insults (secondary partial and generalized epilepsies) and patients with no evidence for acquired cerebral insult (primary partial and generalized epilepsies). Epilepsy syndrome was classified based on the following three-step procedure. In the first step, the clinical seizure type or types were determined from descriptions of seizures provided by the mother and clinical descriptions provided in the medical records. In the second step, reports of EEGs in the medical records were examined for abnormalities. Specifically identified were normal and abnormal background, bisynchronous spikewave (23Hz vs. ~ 2 . 5 H z ) focal , slowing, and focal epileptiform abnormality. The extent of EEG investigation varied. Most subjects had only interictal EEG samples, and the number of these EEG samples also varied. A few subjects had video EEG documentation of ictal events. In all cases, only positive evidence of EEG abnormality was used in syndrome formulation. In the third step, information from parents and medical records was examined for evidence of an acquired cerebral insult or lesion. For 1 child, we could not classify the epilepsy syndrome except as primary. Age of onset of epilepsy, which was obtained from the mother in an interview, was measured to the nearest year. Seizure frequency was also obtained from the mother and placed into one of eight categories ranging from “seizure-free for 1 year or more” to “30 or more seizures in the past month.” Children were also placed in categories of polyther-
1117
apy or monotherapy based on the number of AEDs they were currently receiving. Family variables Marital status, family stress, and family adaptive resources were independent variables. For marital status, families were classified as either being oneparent or two-parent based on the home in which the child lived. Family stress was determined by the Family Inventory of Life Events and Changes (FILE) (McCubbin and Thompson, 1987), a 71-item self-report instrument that provides information on strains and life changes in nine areas: intrafamily strain, marital strains, pregnancy and childbearing strains, financing and business strains, work-family transitions, illness and family care strains, losses, transitions of family members, and legal violations. The reliability and validity of the total score was shown to be strong in previous research (McCubbin and Thompson, 1987). The internal consistency reliability (coefficient a)for the current sample on the FILE was 0.82. Family adaptive resources were measured by the Family Inventory of Resources for Management (FIRM) (McCubbin and Thompson, 1987). FIRM is a 69-item questionnaire that provides information on four areas of family resources: esteem and communication, mastery and health, extended family social support, and financial well-being. Mothers rated how well the statements described their family on 4-point scales from 0 = “not at all” to 3 = “very well.” Reliability and validity properties of FIRM were shown to be strong in previous research (McCubbin and Thompson, 1987). Internal consistency reliability (coefficient a) for the four subscales in the current study ranged from 0.74 to 0.90. All family variables were scored so that higher scores reflected greater amounts of the attribute being measured.
Data analyses The effect of each independent variable on child behavior problems was assessed first by univariate analysis and then adjusted for other independent variables by multiple regression. The univariate analyses examined the effects of binary independent variables by two-sample t tests, the effects of multicategorical independent variables by analysis of variance (ANOVA), and the effects of intervalscaled independent variables by pairwise correlations. Because some of the possible predictors were strongly correlated with each other, a combination of strategies proposed by Mosteller and Tukey (1977) was used to eliminate some variables and Epilepsia, Vol. 33, N o . 6,1992
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combine others before multiple regressions were run. Two family resource variables from the FIRM, family mastery and extended family social support, were retained because they were not highly correlated (Y = 0.40) and they had the greatest reduction in residual sum of squares in prediction of child behavior problems. Multiple linear regression was performed to identify the seizure, demographic, and family variables contributing significantly to prediction of behavior problems, with adjustment made for age and gender. The results of backward and forward stepwise regressions were compared and found similar. Residual analyses and tolerance analyses indicated no problems with multicollinearity, outliers, or influential points. RESULTS Sample characteristics The sample of 127 children was almost evenly divided between boys and girls (mean age of 10.5 years) (Table 1). Most of the children were in twoparent homes (72%). The mean SES score of 59.7 was representative of an upper middle-class family. Age of onset of epilepsy ranged from immediately after birth to 11 years (mean of 5.1 years). One third of the children had been seizure-free 3 1 year, had had 3 2 0 seizures in the precedwhereas 4% ing month. Most (84%) were receiving only one AED. Four epilepsy syndromes were distinguished: 28% of the children had primary generalized, 8% TABLE 1. Descriptive information of sample Variable Demographic
M Child age (yr) (range 8-12) Two-parent homes Socioeconomic status (range = 33.6-84.3) Seizure Age of onset (yr) (range i l - 1 I) Seizure frequency (range 1-8) Seizure-free 3 1 yr Seizure-free 6 mo to 1 yr Seizure-free 3-6 mo Seizure-free 1-3 mo 1-9 siezures in past month 10-19 seizures in past month 20-29 seizures in past month 230 seizures in past month Epilepsy syndrome Primary generalized Secondary generalized Primary partial Secondary partial Monotherapy Family Stress (range 0-31) Mastery (range 8-59) Extended family social support (range 1-12) Child Behavior problems (range 34-91)
Epilepsia, Vol. 33, No. 6, 1992
49.6% Mean = 10.5 71.7% Mean = 59.7 Mean = 5.1 Mean = 3.2, SD = 2.0 33.1% 11.8% 8.7% 17.3% 19.7% 3.9% 1.6% 3.9% 27.6% 7.9% 14.2% 49.6% 83.5% Mean 9.9, SD 5.7 Mean 38.9, SD 9.5 Mean 8.7, SD 2.6 Mean 63.4, SD 10.7
had secondary generalized, 14% had primary partial, and 50% had secondary partial. The mean score for behavior problems in the sample was 63.4, which is at the clinical cutoff for normal behavior established by Achenbach and Edelbrock (1983). Approximately 50% of the sample had a score >63, the ninetieth percentile for the general population. Furthermore, 27% of the sample had total scores >70, which indicates more reported behavior problems than all but 2% of the general population (Achenbach and Edelbrock, 1983). The family stress variable had a mean of 9.9, indicating that on the average the families had experienced -10 stressful events in the preceding year. The family resource variable of family mastery had a mean of 38.9, indicating that on the average the families perceived a “minimal” or low level of mastery over family events and outcomes. The other family resource variable, extended family social support, had a mean of 8.7, indicating that families were experiencing a “moderate” level of social support from relatives. Univariate analyses Results of the univariate analyses are shown in Table 2. No significant differences were noted between boys and girls in level of behavior problems. When children in one-parent homes were compared with children in two-parent homes, no significant difference was noted in behavior problems. No differences in behavior problems were noted between those receiving one AED and those receiving two or more AEDS. ANOVA to determine whether there were differences in child behavior problems across the four epilepsy syndromes was not statistically significant. A contrast between children with primary syndromes and those with secondary syndromes was also nonsignificant. Variables that had significant bivariate correlations with behavior problems were child age, seizure frequency, family stress, family mastery, and extended family social support. Analyses of seizure frequency indicated that the mean behavior problems score increased from 59.5 in the third who had been seizure-free at least 1 year to 68.0 in the 9% with >10 seizures in the past month. Multiple regression analysis Multiple linear regression was performed with child behavior problems as the dependent variable. Child age, SES, age at seizure onset, seizure frequency, family stress, family mastery, and extended family social support were included as independent variables using numerical values. The additional effects of polytherapy , female gender,
CHILD BEHAVIOR PROBLEMS
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TABLE 2. Results for univariatc and correlational analysis Behavior problems Variable Demographic Gender M F Child age Number of parents in home Two One Socioeconomic status Seizure Age at seizure onset Seizure frequency Seizure-free a1 yr Seizure-free 6 mo to 1 yr Seizure-free 3-6 mo Seizure-free 1-3 mo 1-9 seizures in past month 10-19 seizures in past month 20-29 seizures in past month S30 seizures in past month Seizure syndrome Primary Generalized Partial Secondary Generalized Partial Number of medications Monotherapy Polytherapy Family Family stress Family mastery Extended family social support
Mean
SD
62.1 64.7
11.3 10.0
r-Value
p-Value
0.179
63.1 64.4
-0.16
0.036 0.541
-0.11
0.104
-0.03 0.24
0.353 0.003
10.5 11.4
59.8 61.5 66.6 65.6 65.2 70.4 68.0 65.0
10.0 10.8 10.8 14.0 7.4 13.2 7.0 5.8
62.3 63.9 58.3 64.3 65.6 64. I
11.1 11.0 10.4 10.4 11.2 10.3
63.3 64.0
10.9 10.1
0.179" 0.295'
0.766
0.39 - 0.42 - 0.36
0.001 0.001 0.001
" For four syndromes.
' For primary versus secondary. single-parent household, and secondary epilepsy syndrome (as compared with the combined primary epilepsy syndrome categories) were examined by indicator variables. Both backward and forward stepwise elimination procedures led to models using five variables (family stress, female gender, seizure frequency, family mastery, and extended family social support); all other variables were eliminated (Table 3). These five variables accounted for 29% of the variation in behavioral problems, a significant fraction (p < 0.001). Higher levels of family stress, TABLE 3 . Regression of seizure, demographic, and family variables on child behavior problems Variable
B weight
sr2
p-Value
Female gender Family stress Family mastery Extended family support Seizure frequency
4.19 0.42 -0.25 -0.83 0.97
0.037 0.036 0.036 0.032 0.031
0.01 1 0.012 0.013 0.019 0.020
Multiple R = 0.57, Adj. R2 = 0.29, B weight = unstandardized regression coefficient, F = 11.4, p < 0.001, Sr2 = squared semipartial correlation.
increased seizure frequency, and female gender were associated with more behavioral problems. Because family stress, a strong predictor of behavior problems, was multidimensional, additional analyses were performed to determine which of the nine areas of strain were most highly correlated with behavior problems. The strongest correlations were noted between child behavior problems and intrafamily strain (r = 0.43) and marital strain (Y = 0.28), respectively. DISCUSSION The prevalence of behavior problems in children with epilepsy in this study is consistent with results of previous studies and supports the need to identify factors that place these children at risk for problems. In our study, variables that accounted for -30% of the variation in child behavior problems included one demographic variable (female gender), one seizure variable (seizure frequency), and three family variables (family stress, extended family social support, and family mastery). Family stress and Epilepsia, Vol. 33, No. 6, 1992
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seizure frequency were positively related to behavior problems. Extended family social support and family mastery were negatively associated with child behavior problems. On a whole, these findings indicate that children who were experiencing behavioral problems tended to have poorer seizure control and to be in troubled families in which mothers were receiving less than needed support from relatives. The few findings in regard to demographic (e.g., child age) and seizure variables (e.g., age at onset and polytherapy) that are different from those reported in previous studies may be explainable by the differences in sample selection, especially the exclusion of children with IQs
Correlates of Behavior Problems in Children with Epilepsy Joan K. Austin, "Michael W. Risinger, and ?Laurel A. Beckett Department of PsychiatriclMental Health Nursing, Indiana University School of Nursing, Indianapolis, Indiana; *Minnesota Comprehensive Epilepsy Program, P . A., Minneapolis, Minnesota; and f Channing Laboratory, Harvard Medical School, and Department of Biostatistics, Hurvard School of Public Health, Boston, Massachusetts, U.S.A.
Summary: We report results from the first part of an ongoing longitudinal study aimed at identifying the relative contributions of demographic, seizure, and family variables in the prediction of behavior problems in children with epilepsy. We studied 127 children with epilepsy aged 8-12 years and their mothers. Self-report questionnaires, interviews, and medical records were data sources. Backward and forward stepwise elimination procedures using multiple regression indicated five variables that contrib-
uted significantly to prediction of behavior problems: female gender, family stress, family mastery, extended family social support, and seizure frequency. These factors accounted for 29% (p < 0.001) of the variation in behavioral problems. Findings suggest that family variables are important correlates of behavior problems and should be considered in clinical management of children with epilepsy. Key Words: Behavior-Child-EpilepsyFamily-Seizure-Behavior therapy.
Substantial evidence shows that children with epilepsy have a higher incidence of mental health problems than do children with other chronic physical disorders. Children with epilepsy have been shown to have poorer self-concepts (Matthews et al., 1982; Margalit and Heiman, 1983; Austin, 1989) and more behavioral problems and psychiatric disturbances (Rutter et al., 1970; Scott, 1978; Hoare, 1984~;Austin, 1989) than do children with other chronic physical conditions. Factors leading to behavior problems in children with epilepsy have not been well delineated in research studies, making it difficult for clinicians to identify children in need of preventive interventions. Research suggests that several different factors, including demographic, seizure, and family variables, influence adaptation to childhood epilepsy. Demographic variables that have been identified as being potential risk factors for behavior problems in children with epilepsy include low socioeconomic status (SES) (Hermann and Whitman, 1986; Hermann et al., 1989; Hoare and Kerley, 1991) and young age (Hoare and Kerley, 1991). Research on gender and psychopathology has been inconsistent, with no differences reported by some investigators
(Holdsworth and Whitmore, 1974; Hoare and Kerley, 1991), but at least one study showing boys to be more at risk for behavioral problems at school than girls (Stores, 1978). Most research has focused on the relationship between seizure variables and adaptation (Hermann, 1986), and several seizure variables have been linked with mental health problems. Hermann et al. (1989) reported that age at onset of seizures, seizure control, seizure type, etiology, duration of epilepsy, and treatment with more than one antiepileptic drug (AED) were associated with some types of behavior problems in children with epilepsy. Other researchers (Hoare, 1984~;Austin, 1988) have reported that seizure frequency is positively associated with behavioral problems. Results have not always been consistent: e.g., Hoare (1984~)reported that focal EEG abnormalities and complex partial seizures (CPS) were associated with increased psychiatric disturbance. In contrast, Whitman et al. (1982) noted no relationship between temporal lobe epilepsy and psychopathology in children with epilepsy. Evidence shows that children with epilepsy who also have deficits in neuropsychological functioning may be at increased risk for psychopathology (Hermann, 1981, 1982; Rutter, 1981). Lending support for the hypothesis that brain insult is linked with psychopathology is the consistent finding of a higher incidence of psychiatric disorder in children
Received November 1991; revision accepted March 1992. Address correspondence and reprint requests to Dr. J. K. Austin at Indiana University School of Nursing, 1111 Middle Dr., Indianapolis, IN, U.S. A.
1115
J . K . AUSTIN ET A L .
1116
with chronic conditions involving the brain than in children with chronic conditions not involving the brain (Rutter et al., 1970; Breslau, 1985; Austin, 1989). Furthermore, the findings by Hoare (1984~) that children with newly diagnosed epilepsy had a higher rate of psychiatric disturbance than children with newly diagnosed diabetes supports the hypothesis that a neurologic dysfunction predisposed the children to both the epilepsy and the psychiatric disorder. Family factors have also been shown to be associated with behavior problems in children with epilepsy. Hermann et al. (1989) reported divorced or separated parents to be a predictor of behavior problems, especially depression, in both boys and girls. In a small descriptive study, Mulder and Suurmeijer (1977) noted a relationship between parental control and dependency in the child with epilepsy. Hoare and Kerley (1991) reported an association between family stress and child behavioral disturbance. Austin (1988) reported differences in family characteristics between children who had behavioral problems and those who did not. Families of children with problems were shown to have significantly poorer functioning, less intrafamily esteem and communication, less extended family social support, and less financial efficacy than families of children without problems. Unfortunately these studies have been limited by small samples, limited measurement of family attributes, or failure to consider seizure and demographic variables in the same analysis with family variables. This literature review shows that demographic, seizure, and family variables have all been shown to be associated with behavior problems in children with epilepsy, but because past studies have not used multivariate designs or statistical techniques, the relative importance of these three types of variables is not known. Consequently, Hermann (Hermann and Whitman, 1986; Hermann et al., 1989) recommended that a multietiologic approach be used in future investigations of childhood psychopathology in epilepsy. We report results from the first part of an ongoing longitudinal study with a multietiologic approach designed to identify the relative contributions of demographic , seizure, and family variables in prediction of child behavior problems.
METHODS Sample We studied 136 children aged 8-12 years with epilepsy for at least 1 year, currently receiving prescribed AEDs, with no other chronic conditions, Epilepsiu, Vol. 33, No. 6, 1992
who had an IQ of at least 70. Children in classes for the mildly mentally handicapped were excluded. Approximately 85% were from four outpatient clinics in two large medical facilities plus the private patients of the pediatric neurologists from these clinics. Approximately 10% of the sample were children treated by private neurologists, and 5% were children who had been evaluated by one of the participating neurologists but were being treated by a pediatrician at the time of the interview. The families of all children meeting the criteria in these clinics were asked to participate. Only one family declined because of the time involved for the interview. Approximately 89% of the sample were white, 10% black, and 1% other. Parents or legal guardians were also interviewed and asked to complete questionnaires about the child and the family. The sample for the current analysis was 127 children and their mothers. Nine children from the total sample were excluded: 4 because their epilepsy syndrome could not be classified, 2 because their mothers did not participate, and 3 because they had not received AEDs in the month before the interview. Procedures Once we determined from the medical records that subjects met the criteria, parents were approached about the study and asked for permission to approach their children. Interviews and selfreport questionnaires were completed independently by parents and children. Approximately one half of the data collection took place before or after regularly scheduled appointments with physicians and one half took place in the home. Instrumentation
Child behavior problems The dependent variable, behavioral functioning of the child, was measured by the mothers’ ratings on the Child Behavior Checklist (CBCL) (Achenbach and Edelbrock, 1983). The CBCL consists of 118 behavior problem items on which parents rate their children using 3-point scales, with a higher score reflecting more problems. Past research has shown the scale to have strong reliability and validity (Achenbach and Edelbrock, 1983; Jones et al., 1988) and to be relevant for use with children with epilepsy (Dorenbaum et al., 1985). Internal consistency reliability for the total behavior problems score used in this analysis was 0.95. Raw scores for the total behavior problems score were converted to standardized T scores (mean 50, SD 10) and normed for age and gender as specified by Achenbach and Edelbrock (1983).
CHILD BEHAVIOR PROBLEMS Demographic variables Child age was measured to the nearest month. SES was measured by the method of Green (1970), in which income, education, and occupation are combined in one scale. This scale has been shown to be a reliable and valid indicator of SES in prediction of health behavior (Green, 1970). Seizure variables Four seizure variables were included as independent variables in the analysis: epilepsy syndrome, age of onset, seizure frequency, and polytherapy . To measure epilepsy syndrome, children were assigned by M.R. to either a generalized or partial syndrome category and a primary (idiopathic) or secondary (symptomatic) subcategory. The International League Against Epilepsy classification was used (Commission, 1989). Classification of epilepsy syndrome, which is dependent in part on identification of seizure type, provides additional information regarding the presumptive or proven etiology of the patient’s illness. The classification used in the current study was intended to distinguish between patients with known presumed or acquired cerebral insults (secondary partial and generalized epilepsies) and patients with no evidence for acquired cerebral insult (primary partial and generalized epilepsies). Epilepsy syndrome was classified based on the following three-step procedure. In the first step, the clinical seizure type or types were determined from descriptions of seizures provided by the mother and clinical descriptions provided in the medical records. In the second step, reports of EEGs in the medical records were examined for abnormalities. Specifically identified were normal and abnormal background, bisynchronous spikewave (23Hz vs. ~ 2 . 5 H z ) focal , slowing, and focal epileptiform abnormality. The extent of EEG investigation varied. Most subjects had only interictal EEG samples, and the number of these EEG samples also varied. A few subjects had video EEG documentation of ictal events. In all cases, only positive evidence of EEG abnormality was used in syndrome formulation. In the third step, information from parents and medical records was examined for evidence of an acquired cerebral insult or lesion. For 1 child, we could not classify the epilepsy syndrome except as primary. Age of onset of epilepsy, which was obtained from the mother in an interview, was measured to the nearest year. Seizure frequency was also obtained from the mother and placed into one of eight categories ranging from “seizure-free for 1 year or more” to “30 or more seizures in the past month.” Children were also placed in categories of polyther-
1117
apy or monotherapy based on the number of AEDs they were currently receiving. Family variables Marital status, family stress, and family adaptive resources were independent variables. For marital status, families were classified as either being oneparent or two-parent based on the home in which the child lived. Family stress was determined by the Family Inventory of Life Events and Changes (FILE) (McCubbin and Thompson, 1987), a 71-item self-report instrument that provides information on strains and life changes in nine areas: intrafamily strain, marital strains, pregnancy and childbearing strains, financing and business strains, work-family transitions, illness and family care strains, losses, transitions of family members, and legal violations. The reliability and validity of the total score was shown to be strong in previous research (McCubbin and Thompson, 1987). The internal consistency reliability (coefficient a)for the current sample on the FILE was 0.82. Family adaptive resources were measured by the Family Inventory of Resources for Management (FIRM) (McCubbin and Thompson, 1987). FIRM is a 69-item questionnaire that provides information on four areas of family resources: esteem and communication, mastery and health, extended family social support, and financial well-being. Mothers rated how well the statements described their family on 4-point scales from 0 = “not at all” to 3 = “very well.” Reliability and validity properties of FIRM were shown to be strong in previous research (McCubbin and Thompson, 1987). Internal consistency reliability (coefficient a) for the four subscales in the current study ranged from 0.74 to 0.90. All family variables were scored so that higher scores reflected greater amounts of the attribute being measured.
Data analyses The effect of each independent variable on child behavior problems was assessed first by univariate analysis and then adjusted for other independent variables by multiple regression. The univariate analyses examined the effects of binary independent variables by two-sample t tests, the effects of multicategorical independent variables by analysis of variance (ANOVA), and the effects of intervalscaled independent variables by pairwise correlations. Because some of the possible predictors were strongly correlated with each other, a combination of strategies proposed by Mosteller and Tukey (1977) was used to eliminate some variables and Epilepsia, Vol. 33, N o . 6,1992
J . K . AUSTIN ET AL.
1118
combine others before multiple regressions were run. Two family resource variables from the FIRM, family mastery and extended family social support, were retained because they were not highly correlated (Y = 0.40) and they had the greatest reduction in residual sum of squares in prediction of child behavior problems. Multiple linear regression was performed to identify the seizure, demographic, and family variables contributing significantly to prediction of behavior problems, with adjustment made for age and gender. The results of backward and forward stepwise regressions were compared and found similar. Residual analyses and tolerance analyses indicated no problems with multicollinearity, outliers, or influential points. RESULTS Sample characteristics The sample of 127 children was almost evenly divided between boys and girls (mean age of 10.5 years) (Table 1). Most of the children were in twoparent homes (72%). The mean SES score of 59.7 was representative of an upper middle-class family. Age of onset of epilepsy ranged from immediately after birth to 11 years (mean of 5.1 years). One third of the children had been seizure-free 3 1 year, had had 3 2 0 seizures in the precedwhereas 4% ing month. Most (84%) were receiving only one AED. Four epilepsy syndromes were distinguished: 28% of the children had primary generalized, 8% TABLE 1. Descriptive information of sample Variable Demographic
M Child age (yr) (range 8-12) Two-parent homes Socioeconomic status (range = 33.6-84.3) Seizure Age of onset (yr) (range i l - 1 I) Seizure frequency (range 1-8) Seizure-free 3 1 yr Seizure-free 6 mo to 1 yr Seizure-free 3-6 mo Seizure-free 1-3 mo 1-9 siezures in past month 10-19 seizures in past month 20-29 seizures in past month 230 seizures in past month Epilepsy syndrome Primary generalized Secondary generalized Primary partial Secondary partial Monotherapy Family Stress (range 0-31) Mastery (range 8-59) Extended family social support (range 1-12) Child Behavior problems (range 34-91)
Epilepsia, Vol. 33, No. 6, 1992
49.6% Mean = 10.5 71.7% Mean = 59.7 Mean = 5.1 Mean = 3.2, SD = 2.0 33.1% 11.8% 8.7% 17.3% 19.7% 3.9% 1.6% 3.9% 27.6% 7.9% 14.2% 49.6% 83.5% Mean 9.9, SD 5.7 Mean 38.9, SD 9.5 Mean 8.7, SD 2.6 Mean 63.4, SD 10.7
had secondary generalized, 14% had primary partial, and 50% had secondary partial. The mean score for behavior problems in the sample was 63.4, which is at the clinical cutoff for normal behavior established by Achenbach and Edelbrock (1983). Approximately 50% of the sample had a score >63, the ninetieth percentile for the general population. Furthermore, 27% of the sample had total scores >70, which indicates more reported behavior problems than all but 2% of the general population (Achenbach and Edelbrock, 1983). The family stress variable had a mean of 9.9, indicating that on the average the families had experienced -10 stressful events in the preceding year. The family resource variable of family mastery had a mean of 38.9, indicating that on the average the families perceived a “minimal” or low level of mastery over family events and outcomes. The other family resource variable, extended family social support, had a mean of 8.7, indicating that families were experiencing a “moderate” level of social support from relatives. Univariate analyses Results of the univariate analyses are shown in Table 2. No significant differences were noted between boys and girls in level of behavior problems. When children in one-parent homes were compared with children in two-parent homes, no significant difference was noted in behavior problems. No differences in behavior problems were noted between those receiving one AED and those receiving two or more AEDS. ANOVA to determine whether there were differences in child behavior problems across the four epilepsy syndromes was not statistically significant. A contrast between children with primary syndromes and those with secondary syndromes was also nonsignificant. Variables that had significant bivariate correlations with behavior problems were child age, seizure frequency, family stress, family mastery, and extended family social support. Analyses of seizure frequency indicated that the mean behavior problems score increased from 59.5 in the third who had been seizure-free at least 1 year to 68.0 in the 9% with >10 seizures in the past month. Multiple regression analysis Multiple linear regression was performed with child behavior problems as the dependent variable. Child age, SES, age at seizure onset, seizure frequency, family stress, family mastery, and extended family social support were included as independent variables using numerical values. The additional effects of polytherapy , female gender,
CHILD BEHAVIOR PROBLEMS
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TABLE 2. Results for univariatc and correlational analysis Behavior problems Variable Demographic Gender M F Child age Number of parents in home Two One Socioeconomic status Seizure Age at seizure onset Seizure frequency Seizure-free a1 yr Seizure-free 6 mo to 1 yr Seizure-free 3-6 mo Seizure-free 1-3 mo 1-9 seizures in past month 10-19 seizures in past month 20-29 seizures in past month S30 seizures in past month Seizure syndrome Primary Generalized Partial Secondary Generalized Partial Number of medications Monotherapy Polytherapy Family Family stress Family mastery Extended family social support
Mean
SD
62.1 64.7
11.3 10.0
r-Value
p-Value
0.179
63.1 64.4
-0.16
0.036 0.541
-0.11
0.104
-0.03 0.24
0.353 0.003
10.5 11.4
59.8 61.5 66.6 65.6 65.2 70.4 68.0 65.0
10.0 10.8 10.8 14.0 7.4 13.2 7.0 5.8
62.3 63.9 58.3 64.3 65.6 64. I
11.1 11.0 10.4 10.4 11.2 10.3
63.3 64.0
10.9 10.1
0.179" 0.295'
0.766
0.39 - 0.42 - 0.36
0.001 0.001 0.001
" For four syndromes.
' For primary versus secondary. single-parent household, and secondary epilepsy syndrome (as compared with the combined primary epilepsy syndrome categories) were examined by indicator variables. Both backward and forward stepwise elimination procedures led to models using five variables (family stress, female gender, seizure frequency, family mastery, and extended family social support); all other variables were eliminated (Table 3). These five variables accounted for 29% of the variation in behavioral problems, a significant fraction (p < 0.001). Higher levels of family stress, TABLE 3 . Regression of seizure, demographic, and family variables on child behavior problems Variable
B weight
sr2
p-Value
Female gender Family stress Family mastery Extended family support Seizure frequency
4.19 0.42 -0.25 -0.83 0.97
0.037 0.036 0.036 0.032 0.031
0.01 1 0.012 0.013 0.019 0.020
Multiple R = 0.57, Adj. R2 = 0.29, B weight = unstandardized regression coefficient, F = 11.4, p < 0.001, Sr2 = squared semipartial correlation.
increased seizure frequency, and female gender were associated with more behavioral problems. Because family stress, a strong predictor of behavior problems, was multidimensional, additional analyses were performed to determine which of the nine areas of strain were most highly correlated with behavior problems. The strongest correlations were noted between child behavior problems and intrafamily strain (r = 0.43) and marital strain (Y = 0.28), respectively. DISCUSSION The prevalence of behavior problems in children with epilepsy in this study is consistent with results of previous studies and supports the need to identify factors that place these children at risk for problems. In our study, variables that accounted for -30% of the variation in child behavior problems included one demographic variable (female gender), one seizure variable (seizure frequency), and three family variables (family stress, extended family social support, and family mastery). Family stress and Epilepsia, Vol. 33, No. 6, 1992
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seizure frequency were positively related to behavior problems. Extended family social support and family mastery were negatively associated with child behavior problems. On a whole, these findings indicate that children who were experiencing behavioral problems tended to have poorer seizure control and to be in troubled families in which mothers were receiving less than needed support from relatives. The few findings in regard to demographic (e.g., child age) and seizure variables (e.g., age at onset and polytherapy) that are different from those reported in previous studies may be explainable by the differences in sample selection, especially the exclusion of children with IQs
