Journal of Pediatric Psychology, Vol. 25, No. 7, 2000, pp. 493-502
© 2000 Society of Pediatric Psychology
Aggression, Antisocial Behavior, and Substance Abuse in Survivors of Pediatric Cancer: Possible Protective Effects of Cancer and Its Treatment
University of Cincinnati
All correspondence should be sent to Robert B. Noll, Children's Hospital Medical Center, Division of Hematology/Oncology, 3333 Burnet Avenue, Cincinnati, Ohio 45229. E-mail: nollr0{at}chmcc.org .
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Abstract |
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Objective: To examine aggression, antisocial behavior, and substance abuse in young adult survivors of pediatric cancer (PCS) relative to case control peers (CC).
Methods: We obtained self-reports of current aggression, antisocial behavior, and lifetime substance use from 26 PCS (time off-treatment, M = 56 months) and 26 CC using the Antisocial Behavior Checklist and the Drinking and Drug History. A report of current aggression and antisocial behavior also was obtained from primary caregivers using the Child Behavior Checklist.
Results: PCS self-reported significantly less illegal drug use and experimentation than CC. No significant differences emerged between groups for use of alcohol and tobacco nor for aggression and antisocial behavior.
Conclusions: PCS are functioning as well as, or better than, CC in terms of aggression, antisocial behavior, and substance abuse. However, given the compromised health status of survivors, efforts should focus on further reduction of drug-related risk behaviors that may amplify organ damage or increase risk for further malignancies in this population.
Key words: pediatric cancer; survivors; adolescents; young adults; substance use; aggression; antisocial behavior.
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Introduction |
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Advances in pediatric cancer treatment over the past two decades have resulted in a dramatic increase in long-term survival rates of children diagnosed with cancer. It is estimated that 1 in every 900 young adults will be a survivor of childhood cancer by the year 200 (Bleyer, 1990
). Increasingly
intense courses of treatment, including chemotherapy, radiation, and surgery,
are responsible for the improved prognosis. However, the combination of
decreased mortality and increased treatment intensity has raised concerns
about psychosocial quality of life for survivors. Psychosocial quality of life
can be defined as the individual's functioning within the broad domain of
mental health, including emotional well-being, behavioral adaptation, presence
or absence of psychiatric symptoms, intellectual functioning, and social
competence.
No studies report significant psychiatric problems in survivors of
pediatric cancer (see review by Kazak,
1994). However, conclusions regarding more subtle or circumscribed
psychosocial difficulties are less clear. Social or emotional difficulties
have been identified by some studies (e.g.,
Mulhern, Wasserman, Friedman, &
Fairclough, 1989), whereas others have identified few of these
problems for children surviving cancer (e.g.,
Kazak, Christakis, Alderfer, & Coiro,
1994). Of note, studies that report difficulties have consistently
described internalizing problems such as anxiety, depression, somatic
complaints, or social withdrawal (e.g.,
Zeltzer et al., 1997).
Children treated with cranial irradiation also may demonstrate more
difficulties related to inattention, concentration, or short-term memory
(e.g., Lockwood, Bell, & Colegrove,
1999). However, studies suggesting problems with physically
aggressive behavior are conspicuously absent from the literature. This void is
logical because children with cancer experience side effects that may
interfere with the development of these externalizing behaviors.
Persistent fatigue (Granowetter,
1994) and growth problems
(Kirk et al., 1987) are two
side effects of treatment that may limit a child's ability to engage in
physically aggressive behaviors. Specifically, general malaise and diminished
stature may leave a child feeling more physically vulnerable and result in
avoidance of aggressive peer groups and situations. Additionally, lengthy
hospital stays and frequent outpatient appointments take considerable time and
may limit a child's opportunities for unsupervised time with peers. Increased
parental involvement is another result of the pediatric cancer experience
(Rait et al., 1992) that may
decrease a child's opportunities to engage with peers in aggressive or
delinquent activities (Dishion, Capaldi,
Spracklen, & Li, 1995). This limitation in unsupervised time
with peers may be particularly important for children diagnosed during early
adolescence, as this is the peak time for initiation into early forms of
substance use (Tyc, Hudson, Hinds,
Elliott, & Kibby, 1997).
The association of school-age aggression and involvement in deviant peer
groups with later aggression, antisocial behavior, and substance abuse in
adolescence and young adulthood has been well documented. There is substantial
agreement that aggression is a highly stable behavioral characteristic
(Rubin, Chen, McDougall, Bowker, &
McKinnon, 1995). Childhood aggression predicts subsequent
externalizing behaviors, antisocial activities, and drug use/abuse through
adolescence and adulthood (Dobkin,
Tremblay, Masse, & Vitaro, 1995). Both early aggressive
behavior and difficulties with peer acceptance predict early onset of alcohol
and drug use (Boyle et al.,
1992). Early onset of substance use has been associated with
greater severity of abuse in adolescents and young adults
(Mezzich et al., 1993;
Newcomb & Bentler,
1990).
For children who survive cancer treatment, this constellation of risk
behaviors may carry additional, serious consequences. Long-term pediatric
cancer survivors have been found to have an increased incidence of second
malignancies (Meadows & Fenton,
1994), as well as increased risk for adverse health outcomes due
to organ damage and other late physical effects of treatment
(DeLaat & Lampkin, 1992).
Involvement with deviant peer groups and substance abuse could amplify organ
damage or increase risk for further malignancies. This has been an increasing
concern for health care professionals working with this population
(Hollen, Hobbie, & Finley,
1997). It is especially important to evaluate the involvement of
survivors in these risk behaviors.
The physical and social side effects of pediatric cancer treatment
ultimately may serve a protective role with regard to the development of early
risk behaviors by limiting behavioral options. A recent study found that
school-age children with cancer were viewed as less aggressive and disruptive
than classmates by both teachers and peers
(Noll, Gartstein, Vannatta, Bukowski,
& Davies, 1999). Additionally, sociometric ratings of
acceptance indicate that school-age children with cancer actually may enjoy a
higher level of popularity than class-room comparison peers, despite the
imposed behavioral limitations (Noll et
al., 1999). Given the continuity of externalizing behavior, if
pediatric cancer treatment limits involvement in early externalizing behavior,
as suggested by Noll and colleagues
(1999), children diagnosed
with cancer during early adolescence may be at decreased risk for serious
problems with aggression, antisocial behavior, and substance use in young
adulthood.
The aim of this study was to explore a constellation of risk behaviors in a population of young adult survivors of pediatric cancer diagnosed during early adolescence. Regional and generational variability of drug use necessitated use of an appropriate comparison group. Pediatric cancer survivors who had reached age 18 were compared to same-age peers. Both groups had been identified during the cancer survivor's initial treatment and were followed prospectively since diagnosis. We hypothesized that (1) young adults who were cancer survivors would be rated as engaging in fewer aggressive and antisocial behaviors than peers; and, (2) young adults who were cancer survivors would report less substance abuse than peers.
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Method |
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This research was reviewed and approved by the Institutional Review Board of Children's Hospital Medical Center.
Participants
Pediatric Cancer Survivors (PCS). Participants in this research
were part of a longitudinal study of children with chronic illness conducted
at a children's medical center. Children were eligible for participation in
the first phase of data collection if they were: (1) 12-15 years of age at
time of diagnosis; (2) receiving treatment for a malignancy that did not
primarily involve the central nervous system (CNS); (3) attending school at
the time of recruitment; and, (4) not enrolled in full-time special education.
Because this medical center is the only pediatric in-patient facility in the
region and has the only board-certified pediatric oncologists, it serves
nearly every child diagnosed with cancer in the area. This fact, in
combination with recruitment above 97%, suggests that the original sample
consisted of nearly every child aged 12 to 15 in this area who was diagnosed
with pediatric cancer during the study period
(Noll et al., 1999).
Participants from the initial cohort
(Noll et al., 1999), were
eligible for participation in this follow-up study if they were (1)
approximately 18 years of age, and, (2) off-treatment and in remission at the
time of data collection. Of the 29 participants from the initial cohort who
met the age requirement, two were excluded because of relapse and ongoing
treatment. In addition, one individual declined to participate, thus yielding
a final sample of 26 survivors (16 males, 10 females) and their primary
caregivers. This sample included survivors of leukemias (n = 9),
lymphomas (n = 12), and various solid tumors (n = 5). All
survivors received chemotherapy during treatment and seven participants also
received 1800 cGy whole brain radiation therapy (WBRT) during the induction
phase of treatment. All survivors had been off-treatment for at least one year
(M = 4 years 8 months, SD = 1 year 8 months) at the time of
data collection and were in first continuous remission.
Case Controls. Case controls (CC) were obtained using a case-by-case matching procedure. During the initial treatment phase for each child with cancer, case controls were identified who were classmates of the same age and race and who had the closest date of birth to the target child. If the child with the closest date of birth declined to participate, the child with the next closest date of birth was asked. The recruitment rate for first-choice case controls was 87%. At follow-up, two of these individuals declined to participate and one participant could not be located, yielding a final sample of 26 case controls (16 males, 10 females) and their primary caregivers. All participants in this study had been originally classified as White by simple observation at the time of initial recruitment.
Procedure
As each participant's eighteenth birthday approached, that individual's
family was contacted to participate in data collection. Following written
consent, questionnaires were administered individually to all participants by
a trained member of the research team. Each family received monetary
compensation for participating.
Measures
Demographic Questionnaire. This instrument
(Noll et al., 1999) assessed
background information from the primary caregiver, including occupational
information needed to determine the socioeconomic status (SES) of each family
using the Revised Duncan (Nakao &
Treas, 1992). We chose the Revised Duncan because occupation-based
measures represent a more contemporary indicator of SES than traditional
income-based measures (Hauser,
1994).
Wechsler Adult Intelligence Scale-Revised (WAIS-R). Scores from
the Vocabulary and Block Design subtests of the WAIS-R
(Wechsler, 1981) were used to
compute an estimated Full Scale Intelligence Quotient. Correlations with Full
Scale IQ have been reported at.90 and reliability has been reported at.94
across nine age groups for this brief composite
(Sattler, 1992).
Child Behavior Checklist (CBCL). The CBCL
(Achenbach, 1991) is a
parent-report instrument that measures a child's behavioral and emotional
problems on a 3-point Likert scale ranging from "never true" to
"always true." CBCL items that exhibited face validity in terms of
aggression and anti-social behavior were selected for possible inclusion in an
index scale of aggressive and antisocial behavior. All items from the
delinquent behavior scale were included, with the exception of one item,
"Uses alcohol or drugs for nonmedical purposes." This item was
excluded to decrease overlap between the two hypotheses of the study. Ten
items from the aggressive behavior scale also were included. Finally, one
additional item, "Cruel to animals," which was not included on
either the delinquent or aggressive behavior scales, was included in the pool
of aggressive and antisocial items. The final pool of items was used in the
construction of an index scale of aggressive and antisocial behavior designed
to combine information from both primary caregiver and young adult.
Antisocial Behavior Checklist (ASB). The ASB
(Zucker & Noll, 1980) is a
46-item self-report questionnaire designed to assess the frequency of a
respondent's involvement in aggressive and antisocial activities on a 4-point
Likert-type scale from "never" to "often." The ASB was
adapted from an earlier antisocial behavior inventory
(Zucker & Barron, 1973).
This instrument demonstrates adequate test-retest reliability (r
=.91) over 4 weeks and internal reliability of 
=.93
(Noll, Zucker, Fitzgerald, & Curtis,
1992). The ASB has been shown to discriminate between individuals
engaging in anti-social behavior and case controls
(Noll et al., 1992). All items
included on the ASB were used in the construction of an index scale of
aggressive and antisocial behavior designed to combine information from both
primary caregiver and young adult.
Drinking and Drug History (DDH). The DDH
(Zucker, Fitzgerald, & Noll,
1990) is a self-report questionnaire developed to obtain
information about past and current drug consumption and common problems
resulting from excessive substance use. Literature indicates that self-report
of substance use is most accurate when adolescents are given sufficient
assurance of confidentiality (e.g., Rouse,
Kozel, & Richards, 1985;
Williams, Eng, Botvin, Hill, & Wynder,
1979). Previous work with the DDH also supports the validity of
this measure (Noll et al.,
1992). The DDH alcohol consumption data allow for categorization
of drinking patterns into quantity-frequency-variability (Q-F-V) indices of
heavy, moderate, light, or infrequent drinker, and abstainer
(Cahalan, Cisin, & Crossley,
1969). These five categories were collapsed in this study into the
following three categories for analyses related to alcohol use due to the
small sample sizes in six of the cells: (1) heavy or moderate drinkers, (2)
light or infrequent drinkers, and, (3) abstainers. The reported number of
cigarettes smoked per day over the last 30 days was used to classify each
participant into one of seven categories reflecting daily cigarette use (i.e.,
from none to two or more packs per day). In this study, these seven categories
were collapsed for analyses related to tobacco use into two dichotomous
categories (e.g., use and nonuse) due to the small sample sizes in ten of the
cells. The frequency of illegal substance use during the past 12 months was
used as a current measure of nonalcohol, nontobacco drug use. Finally, the
total number of illegal substances ever tried by an individual was used as a
measure of lifetime drug experimentation.
Data Reduction
Combining multiple sources of information into a single index scale
permitted a best-estimate of whether young adult participants were engaging in
aggressive or antisocial behavior. This approach minimized the potential
negative impact of social desirability and selective reporting on findings.
Further, this method of data reduction is supported by literature suggesting
that combining young adult and caregiver reports yields a more accurate
representation of aggressive and antisocial behavior (e.g.,
Loeber, Green, Lahey, &
Stouthamer-Loeber, 1989).
Primary caregiver (i.e., CBCL) and self-report (i.e., ASB) items of
aggressive and antisocial behavior were scored dichotomously (i.e., present or
not) to facilitate scale development. Subsequently, a 10-item index scale that
combined the information from both sources was created. This scale consisted
of items from the two measures that directly overlapped in terms of content
(Table I). Because items on the
CBCL are less specific and detailed than items on the ASB, several specific
items on the ASB corresponded with a single global item on the CBCL. Reports
from the two sources were combined such that an endorsement by either source
resulted in an endorsement for that item on the index scale. In the case where
several specific ASB items corresponded with a single global CBCL item, an
endorsement for any item in the ASB cluster resulted in an endorsement for
that single global item on the index scale. The 10 items on the index scale
were then summed to yield a summary score with a range of 0 to 10. This simple
information-combining method was chosen based on theoretical and empirical
literature suggesting that equal-weighting (i.e., "either/or")
techniques, such as those utilized in construction and scoring of the index
scale, are able to approximate best-estimate diagnoses made independently by
clinicians (Bird, Gould, & Staghezza,
1992; Piacentini, Cohen, &
Cohen, 1992). The summary score for the 10-item set was used in
hypothesis testing.
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Results |
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Demographics
A liberal criterion of
=.05 was used for all analyses. Two-tailed
univariate t tests that examined a variety of demographic variables
yielded nonsignificant results. PCS and CC were not different in the area of
family SES, with the mean for each group equating to technical, sales, and
administrative support occupations (PCS: M = 43.36, SD =
20.47; CC: M = 42.63, SD = 18.50; t [50] =.14, ns).
In addition, the two groups were not significantly different in estimated
intelligence (PCS: M = 105.08, SD = 14.93; CC: M =
104.46, SD = 13.51; t [50] =.16, ns) or age at time of
evaluation (PCS: M = 18 years 8 months, SD = 11 months,
range = 17 years 9 months-20 years 11 months; CC: M = 19 years 0
months, SD = 11 months, range = 18 years 0 months-20 years 11 months;
t [50] = -1.22, ns).
Aggression and Antisocial Behavior
A one-tailed t test was performed to test the hypothesis that PCS
would be rated as engaging in fewer aggressive and antisocial behaviors than
CC. No significant differences were found between PCS (M = 3.35,
SD = 1.81) and CC (M = 3.81, SD = 1.96) using our
10-item index scale, t (50) = -.88, ns.
Substance Use: General Issues
The hypothesis that PCS would report less substance use than CC examined
(1) alcohol use, (2) tobacco use, and (3) illegal substance use. Substance use
was conceptualized in this way to capture the greatest amount of information
regarding usage patterns and to ensure comparability of results to the few
previous studies that have examined the use of specific substances within this
population (e.g., Hollen & Hobbie,
1993; Tyc et al.,
1997). Because substance use may vary by region of the country, it
was necessary to compare PCS not only to a regional but also to a national
sample to aid in interpretation of any findings. Comparison of PCS to CC who
were drawn from the same communities allowed for a regional comparison based
on specific patterns of use for the tri-state area. Whenever possible, CC then
were compared to national epidemiological statistics of substance use by young
adults graduating from high school in the United States in 1998 (Monitoring
the Future Study; Johnston, Bachman,
O'Malley, Schulenberg, & Wallace, 1998). Whereas the former
comparison allowed for greater specificity of findings, this latter comparison
ensured generalizability of these findings to the larger population of young
adults in the country.
Alcohol Use. A two-way chi-square test was performed to compare
differences between PCS and CC on alcohol use for the 6 months preceding data
collection. Results from this analysis were not significant for alcohol use by
group membership, 
2 (2, N = 52) =.90, ns.
Specifically, 46% (n = 12) of PCS were classified as abstainers using
the Q-F-V index (Cahalan et al.,
1969), while 23% (n = 6) and 31% (n = 8) were
classified as infrequent/light and moderate/heavy drinkers, respectively. In
comparison, 35% (n = 9) of CC met criteria for abstainers, while 23%
(n = 6) and 42% (n = 11) were classified as infrequent/light
and moderate/heavy drinkers. Although epidemiological statistics were not
available regarding 6-month usage, in particular, the 35% abstinence rate of
CC in this study appeared to be in line with expectations based on statistics
for rates of annual (25%) and 30-day (48%) abstinence for young adults in the
general population (Johnston et al.,
1998).
Tobacco Use. A two-way chi-square test was performed to test
whether differences existed between PCS and CC on tobacco use for the month
preceding data collection. Results from this analysis yielded no significant
difference for tobacco use by group membership, 2 (1,
N = 52) =.32, ns. Descriptively, the majority of participants in both
groups reported no current use of tobacco (62%, n = 16 of PCS; 54%,
n = 14 of CC), with the remainder of participants in both groups
evenly distributed from light (<1 cigarette per day) to heavy (1
packs per day) smokers. Data from CC did not differ significantly from
epidemiological statistics (Johnston et
al., 1998) indicating that 65% of young adults in the general
population reported no use of tobacco in the preceding month.
Illegal Substance Use. Two one-tailed t tests were performed to test the hypothesis that PCS would report less illegal substance use than CC. These t tests focused on two distinct areas: (1) total frequency of substance use during the past 12 months and (2) lifetime number of different drugs tried.
Drug use reported for the 12 months immediately preceding data collection
was significantly correlated with lifetime amount of drug use (r
=.97, p <.001). To control for individual variations in the age of
initiation to substance use, the former score was used to standardize the time
period being summed for frequency. As predicted, PCS (M =.96,
SD = 2.39) reported significantly less total illegal drug use in the
past year than CC (M = 2.69, SD = 4.44, t [38] =
-1.75, p <.05). PCS reported using some type of illegal drug
approximately one to two times during the preceding year, while CC reported
using six to nine times, on average. Six follow-up one-tailed t tests
were conducted on the individual substances for which a base rate above zero
existed for at least one group. A significant difference was found for use of
marijuana (t [48] = -1.73, p <.05). A trend also was
noted for use of amphetamines, but this effect did not reach statistical
significance (t [25] = -1.656, p =.055). Comparison with
epidemiological statistics (Johnston et
al., 1998) indicates that CC did not differ significantly from
young adults in the general population on use of marijuana or amphetamines.
Fifty percent of CC reported use of marijuana and 12% reported use of
amphetamines, in comparison to rates of 49% and 16%, respectively.
A one-tailed t test examining the lifetime number of illegal drugs ever tried also yielded a significant result. On average, PCS (M =.46, SD =.76) experimented with fewer drugs than CC (M = 1.12, SD = 1.51, t [37] = -1.98, p <.05). Specifically, 69% (n = 18) of PCS reported never having used any illegal substances, 15% (n = 4) reported use of one substance, and 15% (n = 4) reported use of two substances, with no participants reporting use of more than two substances. In contrast, the number and range of substances tried was much greater for CC. Forty-six percent (n = 12) of CC reported never having used an illegal substance, 27% (n = 7) reported use of one substance, 12% (n = 3) reported use of two substances, 8% (n = 2) reported use of three substances, 4% (n = 1) reported use of four substances, and 4% (n = 1) reported use of six different substances.
Six follow-up two-way chi-square tests were conducted on the individual
substances for which a base rate above zero existed for at least one group. A
significant difference was found for marijuana use only, with a smaller
proportion of PCS reporting ever having tried marijuana, 2 (1,
N = 52) = 8.50, p <.01. Specifically, 54% (n =
14) of CC reported having tried marijuana at least once during their lifetime,
while only 15% (n = 4) of PCS reported marijuana experimentation.
Data from CC again did not differ from epidemiological statistics
(Johnston et al., 1998) in
that 49% of young adults in the general population reported having tried
marijuana at least once.
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Discussion |
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The first hypothesis of this study was that PCS would be rated as engaging in fewer aggressive and antisocial behaviors than CC. Findings from this study did not support this hypothesis. No significant differences were found between PCS and CC based on combined report of young adults and their caregivers. The second hypothesis was that PCS would self-report less substance use than CC. This hypothesis was partially supported. No significant differences were found between PCS and CC on current use of alcohol and tobacco. However, PCS did report less use of illegal drugs during the past year than did CC. In addition, PCS reported significantly less lifetime drug experimentation. The effect for marijuana use was notably significant. Rates of marijuana use during the past year were significantly lower for PCS than for CC. Additionally, significantly fewer PCS reported having ever tried marijuana than did CC. This finding regarding marijuana use is consistent with the one previous study (Hollen & Hobbie, 1993
) that also compared marijuana use in PCS to a nonclinical
sample. Findings from Hollen and Hobbie
(1993) were nonsignificant but
were in the same direction as this investigation.
These results suggests that PCS are functioning as well as, or better than,
CC when compared on a variety of risk behaviors at long-term follow-up. Issues
of statistical significance aside, all of the findings in this study were in
the predicted direction. This consistent support across risk behaviors
suggests that the experience of pediatric cancer in early adolescence may
exert a subtle protective influence on the development of externalizing
behavior in PCS. This finding is consistent with literature that reports PCS
are generally well-adjusted and show few signs of psychopathology (e.g.,
Kazak et al., 1994). In fact,
these findings lend support to the few studies which have reported that
survivors of pediatric cancer appear to enjoy greater psychological health and
well-being than would be expected based on normative data (e.g.,
Elkin, Phipps, Mulhern, & Fairclough,
1997; Fritz & Williams,
1988). These studies suggest that the experience of pediatric
cancer and its treatment may actually result in improved psychosocial outcome
for survivors in a variety of distinct areas. This study both supports and
extends previous findings by demonstrating that PCS demonstrate decreased
vulnerability to illegal drug use.
This study is especially limited by the small sample size and the limited participation of minorities. The small number of participants resulted in poor power (d =.54 for a medium effect) to detect significant differences between PCS and CC. Approximately twice as many participants (51 per group) would have been needed to ensure adequate power (d =.80) to detect medium effect sizes. Compounding this problem were the low base rates reported for the use of most of the drugs sampled. Low base rates, combined with the small sample size, made statistical significance for the use of a particular drug difficult to achieve. This lack of statistical power may have contributed to the finding of a trend of decreased amphetamine use in PCS, rather than a statistically significant difference, as the base rates for both groups were relatively low and actually approached zero for PCS. Marijuana proved to be the exception, due to the medium effect size (d =.48) and the fact that base rates for use in both groups were well above zero.
Despite the limitations, this study has important clinical implications.
Although results suggest that young adults who are PCS demonstrate
significantly less use of illegal substances than CC, the use of drugs in any
quantity remains a risk factor that must be addressed. Substance use that
could amplify organ damage or increase risk for further malignancies is a
significant concern for health care professionals working with this population
(Hollen et al., 1997). As can
be seen in Table II, PCS are
reporting some current use of such substances. This is especially true for
alcohol and tobacco use, where many PCS are reporting levels of use similar to
that of CC. Tobacco use is of particular concern for this population, as it
may place PCS at increased risk for second malignancies.
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The difference in results obtained for alcohol and tobacco versus illegal
substances may be due to the developmental trajectory of drug use and the time
of diagnosis for this sample of PCS. Specifically, the use of alcohol and
tobacco generally precedes experimentation with other types of drugs
(McCutcheon & Thomas,
1995). For example, peak time for tobacco initiation is reported
to be 12 to 14 years of age (Tyc et al.,
1997). As PCS were 12 to 15 years of age at the time of diagnosis,
some may have already begun using alcohol and tobacco. As a result, the
experience of pediatric cancer and its treatment may have served to disrupt
the trajectory toward further, illegal drug use, rather than forestalling the
development of drug use entirely. Previous work in the area of tobacco use
lends support to this model. Although PCS may be less likely than peers to
start smoking following diagnosis and treatment, they appear likely to
continue smoking once addicted (Haupt et
al., 1992; Tao et al.,
1998). The results of this study, in conjunction with previous
work, underscore the need for the development of interventions and educational
strategies to further reduce these drug-related risk behaviors in PCS.
Follow-up programs for the express purpose of education, health promotion, and
health maintenance are of vital importance in working with this population to
decrease risk over the long term.
Despite the need for further reduction in the use of drugs by PCS, these survivors demonstrated decreased vulnerability in this area. A major contribution of this investigation is its ability to identify an area of relative strength for survivors. This may help to inform clinical decisions regarding where and how resources are directed in terms of educational interventions for this population. Further, studying the mechanisms proposed to underlie the development of this strength might allow for the implementation of effective interventions for other populations who are at risk for early substance use. Increased parental involvement and decreased unsupervised time with peers are two such mechanisms that may have particular relevance to decreasing risk behaviors in nonchronically ill populations.
Future work should focus on understanding the mechanisms that lead to
decreased vulnerability for PCS. A multisite study would be beneficial in a
variety of ways. First, this study represented nearly every child diagnosed
with cancer between ages 12 and 15 in this region during the study period.
However, with the addition of multiple sites, the pool of potential
participants would be much greater, allowing for greater power to detect
significant differences. Second, the medical center at which this study was
conducted currently follows the Children's Cancer Group guidelines for
standards of care (Noll & Kazak,
1997). It is conceivable that not all facilities that treat
children with cancer follow this framework for providing psychosocial services
and long-term medical/educational follow-up. A multisite study randomized on
psychosocial services provided to children during and after medical treatment
would help to ascertain the generalizability of this study's results. In
addition, this type of study would allow researchers to begin identifying the
variables (e.g., age at diagnosis, treatment effects, supportive care
services) that mediate the relationship between pediatric cancer treatment and
the decreased vulnerability observed in the area of illegal drug use.
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Acknowledgments |
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We thank the many individuals who assisted in data collection for this project, as well as the families who have participated in the work. This work fulfilled some of the requirements for the master's degree for J. R. Verrill and was supported in part by an American Cancer Society Institutional Grant #IRG189 and the American Cancer Society—Ohio Branch.
Received April 23, 1999; revision received June 4, 1999; accepted July 31, 1999
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References |
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|
TopAbstractIntroductionMethodResultsDiscussionReferences |
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Achenbach, T. M. (1991). Manual for the Child Behavior Checklist / 4-18 and 1991 profile. Burlington: Department of Psychiatry, University of Vermont.
Bird, H. R., Gould, M. S., & Staghezza, B. (1992). Aggregating data from multiple informants in child psychiatry epidemiological research. Journal of the American Academy of Child and Adolescent Psychiatry, 31, 78-85.[ISI][Medline]
Bleyer, W. A. (1990). The impact of childhood cancer on the United States and the world. CA-A Cancer Journal for Clinicians, 40, 355-367.
Boyle, M., Offord, D., Racine, Y., Szatmari, P., Fleming, J., &
Links, P. (1992). Predicting substance abuse in late adolescence:
Results from the Ontario Child Health Study follow-up. American
Journal of Psychiatry, 149,
761-767.
Cahalan, D., Cisin, I., & Crossley, H. (1969). American drinking practices: A national study of drinking behavior and attitudes. New Brunswick, NJ: Publications Division, Rutgers Center for Alcohol Studies.
DeLaat, C. A., & Lampkin, B. C. (1992). Long-term survivors of childhood cancer: Evaluation and identification of sequelae of treatment. CA-A Cancer Journal for Clinicians, 42, 263-282.
Dishion, T. J., Capaldi, D., Spracklen, K. M., & Li, F. (1995). Peer ecology of male adolescent drug use. Special Issue: Developmental processes in peer relations and psychopathology. Development & Psychopathology, 7, 803-824.
Dobkin, P. L., Tremblay, R. E., Masse, L. C., & Vitaro, F. (1995). Individual and peer characteristics in predicting boys' early onset of substance abuse: A seven-year longitudinal study. Child Development, 66, 1198-1214.[ISI][Medline]
Elkin, T. D., Phipps, S., Mulhern, R. K., & Fairclough, D. (1997). Psychological functioning of adolescent and young adult survivors of pediatric malignancy. Medical and Pediatric Oncology, 29, 582-588.[ISI][Medline]
Fritz, G. K., & Williams, J. R. (1988). Issues of adolescent development for survivors of childhood cancer. Journal of the American Academy of Child and Adolescent Psychiatry, 27, 712-715.[ISI][Medline]
Granowetter, L. (1994). Pediatric oncology: A medical overview. In D. J. Bearison & R. K. Mulhern (Eds.), Pediatric psychooncology (pp. 9-34). New York: Oxford University Press.
Haupt, R., Byrne, J., Connelly, R. R., Mostow, E. N., Austin, D. F., Holmes, G. R., Holmes, F. F., Latourette, H. B., Teta, M. J., Strong, L. C., Myers, M. H., & Mulvihill, J. J. (1992). Smoking habits in survivors of childhood and adolescent cancer. Medical and Pediatric Oncology, 20, 301-306.[ISI][Medline]
Hauser, R. (1994). Measuring socioeconomic status in studies of child development. Child Development, 65, 1541-1545.[ISI][Medline]
Hollen, P. J., & Hobbie, W. L. (1993). Risk taking and decision making of adolescent long-term survivors of cancer. Oncology Nursing Forum, 20, 769-776.[Medline]
Hollen, P. J., Hobbie, W. L., & Finley, S. M. (1997). Cognitive late effect factors related to decision making and risk behaviors of cancer-surviving adolescents. Cancer Nursing, 20, 305-314.[ISI][Medline]
Johnston, L. D., Bachman, J. G., O'Malley, P. M., Schulenberg, J. E., & Wallace, J. (Updated 1998, December 14). 1998 data tables and figures. In The Monitoring the Future Study: A continuing study of American youth. [Online]. Available: http://www.isr.umich.edu/src/mtf/. Posted by The Institute for Social Research, University of Michigan.
Kazak, A. E. (1994). Implications of survival: Pediatric oncology patients and their families. In D. J. Bearison & R. K. Mulhern (Eds.), Pediatric psychooncology (pp. 171-192). New York: Oxford University Press.
Kazak, A. E., Christakis, D., Alderfer, M., & Coiro, M. J. (1994). Young adolescent cancer survivors and their parents: Adjustment, learning problems, and gender. Journal of Family Psychology, 8, 74-84.
Kirk, J. A., Raghupathy, P., Stevens, M. M., Cowell, C. T., Menser, M. A., Bergin, M., Tink, A., Vines, R. H., & Silink, M. (1987). Growth failure and growth-hormone deficiency after treatment for acute lymphoblastic leukaemia. Lancet, 1, 190-193.[ISI][Medline]
Lockwood, K. A., Bell, T. S., & Colegrove, R. W., Jr.
(1999). Long-term effects of cranial radiation therapy on
attention functioning in survivors of childhood leukemia. Journal
of Pediatric Psychology, 24,
55-66.
Loeber, R., Green, S. M., Lahey, B. B., & Stouthamer-Loeber, M. (1989). Optimal informants on childhood disruptive behaviors. Development & Psychopathology, 1, 317-337.
McCutcheon, A. L., & Thomas, G. (1995). Patterns of drug use among White institutionalized delinquents in Georgia: Evidence from a latent class analysis. Journal of Drug Education, 25, 61-71.[ISI][Medline]
Meadows, A. T., & Fenton, J. G. (1994). Follow-up care of patients at risk for the development of second malignant neoplasms. In C. L. Schwartz, W. L. Hobbie, L. S. Constine, & K. S. Ruccione (Eds.), Survivors of childhood cancer: Assessment and management (pp. 319-328). St. Louis, MO: Mosby.
Mezzich, A., Tarter, R., Kirisci, L., Clark, D., Buckstein, O., & Martin, C. (1993). Subtypes of early age onset alcoholism. Alcoholism: Clinical & Experimental Research, 17, 767-770.[ISI][Medline]
Mulhern, R. K., Wasserman, A. L., Friedman, A. G., &
Fairclough, D. (1989). Social competence and behavioral
adjustment of children who are long-term survivors of cancer.
Pediatrics, 83,
18-25.
Nakao, K., & Treas, J. (1992). The 1989 Socioeconomic Index of Occupations: Construction from the 1989 Occupational Prestige Scores (General Social Survey Methodological Report No. 74). Chicago: University of Chicago, National Opinion Research Center.
Newcomb, M. D., & Bentler, P. M. (1990). Antecedents and consequences of cocaine use: An eight-year study from early adolescence to young adulthood. In L. N. Robins & M. Rutter (Eds.), Straight and devious pathways from childhood to adulthood (pp. 158-181). New York: Cambridge University Press.
Noll, R. B., Gartstein, M. A., Vannatta, K., Bukowski, W. M., &
Davies, W. H. (1999). Social, emotional, and behavioral
functioning of children with cancer. Pediatrics,
103, 71-78.
Noll, R. B., & Kazak, A. (1997). Psychosocial care. In A. R. Ablin (Ed.), Supportive care of children with cancer (pp. 263-273). Baltimore, MD: Johns Hopkins Press.
Noll, R. B., Zucker, R. A., Fitzgerald, H. E., & Curtis, W. J. (1992). Cognitive and motoric functioning of sons of alcoholic fathers and controls: The early childhood years. Developmental Psychology, 28, 665-675.
Piacentini, J. C., Cohen, P., & Cohen, J. (1992). Combining discrepant diagnostic information from multiple sources: Are complex algorithms better than simple ones? Journal of Abnormal Child Psychology, 20, 51-63.[ISI][Medline]
Rait, D. S., Ostroff, J. S., Smith, K., Cella, D. F., Tan, C., & Lesko, L. M. (1992). Lives in a balance: Perceived family functioning and the psychosocial adjustment of adolescent cancer survivors. Family Process, 31, 383-397.[ISI][Medline]
Rouse, B. A., Kozel, N.J., & Richards, L. G. (Eds.). (1985). Self-report methods of estimating drug use: Meeting current challenges to validity (NIDA Research Monograph No. 57). Rockville, MD: Department of Health and Human Services, National Institute on Drug Abuse.
Rubin, K. H., Chen, X., McDougall, P., Bowker, A., & McKinnon, J. (1995). The Waterloo Longitudinal Project: Predicting internalizing and externalizing problems in adolescence. Development and Psychopathology, 7, 751-764.[ISI]
Sattler, J. M. (1992). Assessment of children (Revised and updated 3rd ed.). San Diego, CA: Jerome M. Sattler.
Tao, M. L., Guo, M. D., Weiss, R., Byrne, J., Mills, J. L.,
Robison, L. L., & Zeltzer, L. K. (1998). Smoking in adult
survivors of childhood Acute Lymphoblastic Leukemia. Journal of the
National Cancer Institute, 90,
219-225.
Tyc, V. L., Hudson, M. M., Hinds, P., Elliott, V., & Kibby, M.
Y. (1997). Tobacco use among pediatric cancer patients:
Recommendations for developing clinical smoking interventions.
Journal of Clinical Oncology,
15,
2194-2204.
Wechsler, D. (1981). Manual for the Wechsler Adult Intelligence Scale—Revised. San Antonio, TX: The Psychological Corporation.
Williams, C. L., Eng, A., Botvin, G. J., Hill, P., & Wynder, E.
L. (1979). Validation of students' self-reported cigarette
smoking status with plasma cotinine levels. American Journal of
Public Health, 69,
1272-1274.
Zeltzer, L. K., Chen, E., Weiss, R., Guo, M. D., Robison, L. L.,
Meadows, A. T., Mills, J. L., Nicholson, H. S., & Byrne, J.
(1997). Comparison of psychologic outcome in adult survivors of
childhood Acute Lymphoblastic Leukemia versus sibling controls: A Cooperative
Children's Cancer Group and National Institutes of Health study.
Journal of Clinical Oncology,
15, 547-556.
Zucker, R. A., & Barron, F. (1973). Parental behaviors associated with problem drinking and antisocial behavior among adolescent males. In M. Chafetz (Ed.), Research on alcoholism: I. Clinical problems and special populations (pp. 276-296). Washington, DC: U.S. Government Printing Office.
Zucker, R. A., Fitzgerald, H., & Noll, R. B. (1990). Drinking and drug history. Unpublished manuscript, Michigan State University.
Zucker, R. A., & Noll, R. B. (1980). Assessment of antisocial behavior: Development of an instrument. Unpublished manuscript, Michigan State University.
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