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ORIGINAL ARTICLES |
From the Division of Behavioral Medicine, St. Jude Children’s Research Hospital (S.P.), and Department of Pediatrics, University of Tennessee College of Medicine (R.S.), Memphis, TN.
Address reprint requests to: Sean Phipps, PhD, Division of Behavioral Medicine, St. Jude Children’s Research Hospital, 332 N. Lauderdale, Memphis, TN 38105-2794. Email: sean.phipps{at}stjude.org
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONNOTESACKNOWLEDGMENTSREFERENCES |
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METHODS: Measures of defensiveness, trait anxiety, and anger expression were obtained from three groups of children: those with cancer (N = 130), those with chronic illnesses (diabetes, cystic fibrosis, and juvenile rheumatoid disorders; N = 121), and healthy control participants (N = 368). Based on their self-reports, participants were categorized according to the adaptive style paradigm as either high anxious, low anxious, defensive high anxious, or repressor. The prevalence of these categories was compared across groups.
RESULTS: Children in the cancer and chronic illness groups both reported significantly higher levels of defensiveness and lower levels of anxiety than did the healthy control participants. Application of the adaptive style paradigm produced a significantly higher percentage of children identified as repressors in the both cancer and chronic illness groups relative to healthy children. Children classified as repressors also reported significantly less expression of anger than did nonrepressors.
CONCLUSIONS: An increased prevalence of repressive adaptation is not unique to children with cancer, but may be generally characteristic of children with serious chronic illness. Use of anger in place of anxiety as the repressed affect produced a similar distribution of adaptive styles in the study populations.
Key Words: adaptive style, • childhood cancer, • chronic illness, • repression, • children.
Abbreviations: AESC = Anger Expression Scale for Children;; CDI = Children’s Depression Inventory;; CF = cystic fibrosis;; CSD = Children’s Social Desirability Scale;; DM = diabetes mellitus;; JRD = juvenile rheumatoid disorders;; STAIC = State-Trait Anxiety Inventory for Children.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONNOTESACKNOWLEDGMENTSREFERENCES |
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Although most of the research on this issue has involved adults, there is evidence to suggest that the same phenomenon occurs in children and that this issue may be particularly problematic in the assessment of seriously ill children (8–11). For example, studies utilizing children’s self-reports have consistently reported surprisingly low levels of distress in children with cancer. Most studies of depressive symptoms have found significantly lower levels of depression in children with cancer than in their healthy peers (8, 10, 12). This phenomenon has not been limited to self-reports of depression but has also been found with measures of anxiety, self-esteem, behavioral problems, general psychopathology, and even somatic distress (8, 10, 13–15). It is possible, of course, that the positive self-reports of children with cancer may be a valid reflection of their exceptionally high level of functioning. An alternative explanation, which we favor, is that these findings are a reflection of the low-end specificity problem and that the self-reports of children with cancer are biased in some way toward minimization of distress.
The adaptive style paradigm, developed initially by Weinberger et al. (16), provides a heuristic model for evaluation of individuals who report low levels of psychological distress. Assessment of adaptive style involves the simultaneous use of two measures: a measure of subjective distress (eg, trait anxiety) and a measure of defensiveness, typically assessed using social desirability scales. Cutoffs are made on these measures and used in a 2 x 2 table to assign respondents into four categories labeled high anxious, low anxious, defensive high anxious, and repressor. For those who score low on the anxiety measure, one must differentiate between the "true low anxious," who are presumed to be accurately reporting low levels of distress, and "repressors" (low in anxiety, high in defensiveness), who tend to present themselves in a favorable light. Research has shown that those who fall in the repressor cell represent a distinct personality style (17–19). When repressors respond positively to self-report inventories, they are not just engaging in denial or impression management but genuinely think of themselves as well-adjusted, self-controlled, and content, and they organize their behavior to protect that self-image (19). Such individuals are likely to seem very healthy on all self-report measures of mental health.
Canning et al. (8) were the first to assess adaptive style in children with cancer as a possible explanation for bias in self-report. In a population of adolescent cancer patients they found 1) significantly lower levels of self-reported depressive symptoms in the cancer group relative to the control group, 2) a significantly higher percentage of repressors in the cancer group, and 3) that repressor status accounted in large part for the group differences in depression scores. Those findings were subsequently replicated in a larger population of children with cancer across the age range 7 to 16 (10). Using Weinberger’s (19) method of categorizing repressors as those above the 75th percentile on defensiveness and below the median on anxiety, Phipps and Srivastava (10) reported a doubling of the prevalence of repressive adaptive style in the cancer group compared with the healthy control group (36% vs. 18%). Perhaps more striking was the complete absence of depressive symptomatology in those identified as repressors. Not only did repressors obtain the lowest mean scores on the Children’s Depression Inventory (CDI) (20), but of 119 participants identified as repressors from both the cancer and control groups, not one had a CDI score indicative of even mild depressive symptoms (ie, a CDI score >12) (10). It is apparent that children identified as having a repressive adaptive style are unlikely to look distressed on any self-report instruments.
The current study was designed to assess whether a high prevalence of repressive adaptation is unique to children with cancer or may be found in other populations of children with serious chronic illnesses. Children with newly diagnosed cancer were identified and assessed as soon as possible after diagnosis. These children provide a cohort that will be followed longitudinally to examine changes in adaptive style over time. In this article, we compare the baseline (diagnosis) responses of the cancer group to those of children with other serious health conditions who have been ill for some time, along with a healthy comparison group. This design allows for examination of whether differences in adaptive style are more reflective of acute reactivity or chronic adaptation.
A second objective of the study was to explore the inclusion of a measure of anger expression into the adaptive style assessment paradigm. The adaptive style literature suggests that angry, hostile impulses are particularly likely to be repressed in those with a repressive style (19), and in an earlier pediatric study, combining measures of either anxiety or anger with defensiveness to obtain adaptive styles produced similar results (21). Thus, we attempted to expand the adaptive style measurement paradigm to include a new measure of anger expression, created for this study. We hypothesized that, due to their repressive adaptive style, children with cancer would score lower on measures of anger expression than other groups of chronically ill children or healthy control subjects. Furthermore, we predicted that anger expression could be substituted for trait anxiety in the adaptive style measurement paradigm, producing equivalent results. Children with cancer were compared with three other groups of chronically ill children: those with diabetes mellitus (DM), cystic fibrosis (CF), and juvenile rheumatoid disorders (JRD), as well as with a group of healthy control children. The children with cancer were assessed shortly after diagnosis and then followed longitudinally, whereas the chronically ill and control children were assessed once in a cross-sectional design. This article presents a comparison of chronically ill and control children with the cancer group assessed at the time of diagnosis.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONNOTESACKNOWLEDGMENTSREFERENCES |
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Chronically ill group.
Children with a diagnosis of DM, CF, or JRD were recruited from specialty outpatient clinics at a major children’s teaching hospital. Children in the age range 7 to 18 years who were at least 1 month from diagnosis of their condition were eligible to participate. Again, children who did not speak English or who had any known history of cognitive impairment were excluded. Of 127 patients approached, 121 (95%) agreed to participate.
Control group.
A group of healthy school children in grades 2 to 12 were recruited from four schools (two public, two private) in the same geographic area as the cancer center and children’s hospital. A letter explaining the purpose of the study was distributed by teachers in designated classes and sent home with students for parental consent. Students returning the letter with parental signature were eligible for study. In addition to providing permission for their child to participate, parents were also asked to confirm that their child was in good health and not in treatment for any significant ongoing illness. Data were obtained from 368 control children, representing just under half (49.4%) of the 745 letters of request that were distributed. This represents an approximate rate of participation, because due to student absences, an exact percentage of refusals was not calculated.
The demographic and medical background of the participants is presented in Table 1. The groups did not differ significantly in mean age. However, significant differences between groups were observed on race and gender. The cancer group included a higher percentage of males in comparison to both the chronically ill and control groups, where there was a higher percentage of female participants (
2 (2,613) = 19.6, p < .001). Regarding race, there was a lower percentage of black participants and a higher percentage of white participants in the control group relative to both the cancer and chronically ill groups (2(4,607) = 19.5, p < .001). As intended, the cancer group was heterogeneous in terms of cancer diagnoses, and the breakdown is representative of the population of cancer patients served by the institution in this age range (Table 1). The current sample focused on newly diagnosed patients to obtain a baseline measure for subsequent longitudinal assessments. The mean length of time elapsed since diagnosis in the cancer group was 19.8 days (SD = 8.6). The diagnostic breakdown of the chronically ill children is also presented in Table 1. The DM group consisted entirely of children with Type 1 insulin-dependent DM. The JRD group consisted primarily of children with juvenile rheumatoid arthritis but also included some children with juvenile forms of lupus, dermatomyositis, and other chronic conditions treated in the hospital’s rheumatology clinic. In contrast to the cancer group, the chronically ill group was made up of children with longstanding disorders. The mean length of time since diagnosis for this group as a whole was 5.72 years (SD = 3.3), with means of 4.6, 10.8, and 3.5 years for the DM, CF, and JRD groups, respectively.
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) for this version is 0.88 (10). This unidimensional scale provides a single score, with higher scores indicating greater defensiveness.
State-Trait Anxiety Inventory for Children.
Anxiety was measured with the trait scale of the State-Trait Anxiety Inventory for Children (STAIC) (24). This is a widely used self-report measure of child anxiety, and abundant reliability and validity data have been reported (24). Internal reliabilities (Cronbach’s ) have been reported as 0.78 for females and 0.81 for males, with 6-week test-retest reliability of 0.71 (24). A single score is produced, with high scores indicative of higher anxiety.
Anger Expression Scale for Children.
The Anger Expression Scale for Children (AESC) was created for this study. A 30-item questionnaire was developed using items from existing anger expression scales, items adapted from existing scales to be more appropriate for children, and new items that were created to tap additional aspects of anger expression relevant to children. The original measure consisted of four a priori subscales, labeled "trait anger," "anger-out," "anger-in," and "anger-control," as modeled after the adult State-Trait Anger Expression Inventory (25). However, factor analytic procedures revealed a clear two-factor structure. The first factor, which we labeled "anger expression," consisted of 12 items from both the a priori trait anger and anger-out scales. Higher scores on this subscale indicate more frequent experience of anger and greater outward expression of anger. Internal reliability (Cronbach’s ) on the anger expression subscale was 0.83. The second factor, labeled "anger control," contained nine items coming from both the a priori anger-in and anger-control scales. Higher scores indicate greater efforts at controlling or reducing the outward expression of anger. Internal reliability for this scale was 0.83. A total of nine items from the original scale did not load significantly on either factor and were dropped. Further information on the psychometric properties of this instrument are presented elsewhere (26).
Procedure
For the cancer group, lists of patients newly admitted to the institution were reviewed weekly, and eligible patients were recruited from both outpatient and inpatient settings. Participants were seen individually by research assistants, who obtained informed consent according to institutional guidelines and administered a battery of self-report measures. A small percentage of patients had the items read aloud to them, either at the patient’s request or because of concern by the research assistant that the child’s reading skills were inadequate for the task. The remainder of the participants completed the measures on their own with the research assistant standing by to address any questions. The chronically ill group was recruited only from outpatient settings. For children consenting to participate, questionnaire data were obtained in a manner identical to that of the cancer patients. Control participants completed an identical battery of self-report measures in group format in their classrooms. In elementary school classes, the items were read out loud by research staff. In middle school and high school classes, the measures were distributed and students completed them on their own during designated class time set aside for this task.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONNOTESACKNOWLEDGMENTSREFERENCES |
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Group differences on the adaptive style measures using the combined chronically ill group were assessed using analysis of covariance, with age, gender, and race included as covariates. These covariates were included to correct for the demographic differences between groups and not because of any hypothesized relationships of these variables with the outcome measures. Group means are presented in Table 2. The groups differed significantly in defensiveness (F(2,597) = 19.5, p < .0001). Contrary to prediction, post hoc tests revealed that both cancer (p < .0001) and chronically ill (p < .0001) groups obtained significantly higher defensiveness scores than the healthy control group and did not differ from each other, although there was a trend for the chronically ill group to obtain even higher scores than the cancer group (p = .07). Age and race were significant covariates in the analysis, but gender was not. Likewise, on trait anxiety, significant group differences were found (F(2,597) = 8.0, p < .0001), and post hoc comparisons indicated that both the cancer (p < .0001) and chronically ill (p = .005) groups reported significantly lower anxiety than the healthy control group and did not differ from each other. Gender was a significant covariate, but age and race were not. Finally, there was a significant group difference on anger expression(F(2,595) = 4.5, p = .011). The only significant post hoc comparison indicated that the cancer group reported less anger expression than the control group (p = .005). Age and race were significant covariates.
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Classification of Adaptive Style Groups
As in prior studies, adaptive style groups were created after correcting for the effects of age, but not for race and gender (10). Age was a highly significant covariate of defensiveness (F(1,597) = 69.7, p < .0001), and correlational analysis indicated a significant inverse relationship that was found in all groups. For the control group the correlation was r(357) = -.336, p < .0001. Further examination of the significant covariates revealed that black participants obtained higher CSD scores than white participants (t(339) = -5.3, p < .001), and female subjects obtained higher STAIC scores than male subjects (t(359) = -3.9, p < .001. Correcting for age was considered necessary because adaptive style is conceptualized as a stable trait, but one whose appearance differs according to the developmental level of the child. Failure to correct for age would result in a disproportionately and misleadingly high percentage of younger children identified as repressors. Therefore, based on examination of mean scores by age in the control sample, separate norms were established on the CSD for three age groups (7–10, 11–13, and 14–18 years), and cutoffs were made at the 75th percentile of these distributions. In contrast, correcting for gender or race was not thought to be appropriate given that these are fixed characteristics, and differences in adaptive style by race or gender would reflect realistic and important sources of variance in the data.1
Adaptive style breakdowns were created using the procedure described by Weinberger (16), with an age-corrected upper-quartile split on defensiveness and a median split on trait anxiety. For children scoring below the 75th percentile on the CSD, those below the median on the STAIC were labeled low anxious, and those at or above the median, high anxious. For children at or above the 75th percentile on the CSD, those at or above the median on STAIC were labeled defensive high anxious, and those below the median, repressors. Significant group differences were observed in adaptive style (2(6, 610) = 29.4, p < .0001) (Table 3). The percentage of participants identified as low anxious and defensive high anxious were similar across groups, whereas the cancer and chronic illness groups showed a significantly lower percentage of high anxious subjects and a significant excess of repressors relative to the control group. Post hoc comparisons indicated that both the cancer and chronically ill groups differed significantly from the control group but not from each other. Testing group differences in repressor vs. nonrepressor status also produced significant results (2(2,610) = 14.9, p < .001). Again, both the cancer and chronic illness groups differed significantly from the control group but not from each other.
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Adaptive style classifications were then made substituting the AESC anger expression measure for the STAIC, using an identical, age-corrected 75th percentile split on the CSD and a median split on anger expression. Similar group differences were observed (2(6,608) = 25.2, p < .0001), with the cancer and chronically ill groups showing a lower percentage of high anger participants and a higher percentage of repressor participants relative to the control group (Table 4). Again, both the cancer and chronically ill groups differed significantly from the control group but not from each other.
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) was 0.54 (p < .0001). When categorization was dichotomized into repressor vs. nonrepressor, the absolute agreement was 90.5% ( = 0.73, p < .0001). Finally, the anger expression and anxiety measures were incorporated into the adaptive style paradigm simultaneously, defining repressors as those at or above the upper quartile in defensiveness and below the median on both AESC anger expression and STAIC. All others were categorized as nonrepressors. This method of categorization reduced the overall prevalence of repressors slightly but produced similar group differences (2(2,608) = 15.3, p < .001), with the cancer and chronic illness groups showing roughly double the prevalence of repressors (23.1% and 25.6%, respectively) in comparison to the control group (12.2%). |
DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONNOTESACKNOWLEDGMENTSREFERENCES |
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Adaptive style has, for the most part, been considered a stable personality trait, and there is some empirical evidence to support this (18, 19, 21). Thus, a rapid shift toward a more defensive/repressive style in the face of a serious life threat, as observed in the cancer group, would be unexpected and raises questions about the stability and the state vs. trait nature of this construct. However, the absence of any relationship between adaptive style and disease chronicity in this and prior studies (10) is also suggestive of some stability within disease populations. Perhaps a defensive change that occurs rapidly in some patients in response to the threat of serious illness is subsequently integrated and maintained as a more enduring personality style. Alternately, this defensive posture may be abandoned at a later date when it is no longer useful (eg, in the cancer population, after successful completion of therapy). Confirmation of this will require longitudinal studies, and our longitudinal follow-up of the cancer group was designed to address this question.
The expression of anger was found to relate significantly to the adaptive style construct, with repressors reporting less anger expression than other adaptive style groups. As predicted, substitution of anger for anxiety as the repressed affect in the adaptive style measurement paradigm produced very similar results. This replicates a finding previously reported in children with asthma (21). Simultaneous use of both anger expression and anxiety scores in the measurement paradigm led to a slight reduction in the overall percentage of participants identified as repressors, but it also produced a similar pattern of group differences. This approach provides a more stringent test for determination of repressor status, but it may also provide for greater Qreliability and stability in categorization.
The lower report of anger expression in children identified as repressors is consistent with earlier findings of lower self-reports of depressive symptoms in this population as well (10, 12) and supports the conclusion that repressors are unlikely to look distressed on any self-report instruments (12, 19). The current findings of increased levels of repressive adaptive style across all chronic illness groups calls for awareness of this phenomenon among chronic illness researchers and clinicians and some prudence in the use and interpretation of self-report instruments in these populations. Unfortunately, the optimal methodological approach for handling this is not clear. The use of multiple informants and/or use of multiple assessment methods (eg, self-report, observational, physiological) are obvious and necessary approaches, but they also carry the problem of what to do when different approaches produce inconsistent results. In the absence of an accepted "gold standard" for measuring anxiety or other symptoms of mood disturbance, one cannot be certain about which of the conflicting results is more accurate. However, the current findings suggest that when self-report indicates the absence of distress, particularly in vulnerable populations such as chronically ill children, further assessment using additional informants or techniques is indicated.
A perplexing issue is the question of whether repression in the context of serious illness is adaptive. Do the lower reports of affective disturbance produced by such individuals represent a true indication of health or a sign of maladaptation? Certainly, in the face of highly threatening circumstances such as the onset of a catastrophic illness, the ability to block out or limit awareness of anxiety-provoking stimuli could be beneficial. Some evidence exists that adults identified as repressors do, in fact, have a lower prevalence of psychiatric problems than nonrepressors (27). Among adolescents, one study found that repressors demonstrated greater frustration tolerance, better social skills, and higher educational performance than their nonrepressor peers (28).
On the other hand, the disattention to threat characteristic of a repressive adaptive style may lead to reluctance to seek social support, inability to engage effectively in psychotherapy, and perhaps most importantly in the context of chronic illness, lack of attention to internal signals of distress, including physical symptoms, that could delay or interfere with effective medical treatment (17, 19, 29). Although one might anticipate that repressors would be less self-vigilant of their bodily response to illness and treatment, in a study of asthmatic children, repressors were actually found to be more accurate than nonrepressors in perception of their pulmonary function (30). The authors speculate that repression promotes more accurate symptom perception in that context by serving to maintain lower levels of negative affectivity. Nevertheless, considerable research points to the negative health consequences of a repressive coping style (29, 31), which could be magnified in the context of chronic illness. For example, repressors have shown a higher incidence of tension and migraine headaches, Crohn’s disease, ulcers, allergies, and hypertension (29, 31). In the laboratory, repressors have shown greater cardiovascular reactivity in response to stress than nonrepressors and have also shown higher resting blood pressure and blood pressure reactivity (32, 33). Other relevant physiological parameters that have been associated with a repressive adaptive style include elevated serum glucose (34), elevated low-density lipoprotein cholesterol levels (32), stress-induced changes in growth hormone (35), reduced immunocompetence (36), electroencephalograpic asymmetries (37), increased salivary cortisol (38), and increased allergies and food sensitivities (39). These studies have focused almost exclusively on adults, and further research is needed to explore this issue in pediatric populations.
A major limitation of the present study is the lack of a good demographic match between groups, particularly in light of the significant relationship between some demographic variables and the primary adaptive style measures. In our study design, we sampled from schools that should have provided a good demographic match to our cancer group (ie, where there was an approximate 50/50 gender ratio and 20–25% minority students). The rate of participation was better than 90% for both the cancer and chronically ill groups, but approximately 50% among control subjects. These rates are comparable to prior studies that used similar designs (10, 40). In this instance, the absence of a demographic match suggests a differential rate of participation in the control group as a function of race and gender. Specifically, it implies a lower participation of males relative to females and of black children relative to white children within the control pool. This may have biased the findings toward lower levels of repressive adaptation in the control population and could account, in part, for the observed group differences. However, selective attrition research has also shown that it is children who are more distressed and less restrained in their behavior who are less likely to participate in research (41, 42). If so, this would lead to bias in the opposite direction. We are convinced that our findings reflect real between-group differences and not an artifact of demographic mismatch,1 but this question cannot be fully resolved post hoc. The best approach to preventing this problem is through the use of case-control designs, which is our planned methodology for future studies in this area.
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONNOTESACKNOWLEDGMENTSREFERENCES |
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NOTES |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONNOTESACKNOWLEDGMENTSREFERENCES |
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Received for publication July 21, 2000.
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