Journal of Pediatric Psychology, Vol. 27, No. 8, 2002, pp. 699-710
© 2002 Society of Pediatric Psychology
Siblings of Children With a Chronic Illness: A Meta-Analysis
University of Regina
All correspondence should be sent to Donald Sharpe, Department of Psychology, 3737 Wascana Pkwy, University of Regina, Regina, Saskatchewan, Canada S4S OA2. E-mail: sharped{at}uregina.ca.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodResultsDiscussion*Denotes studies included in... |
|---|
Objective: To review the literature pertaining to the siblings of children with a chronic illness.
Methods: Fifty-one published studies and 103 effect sizes were identified and examined through meta-analysis.
Results: We found (1) a modest, negative effect size statistic existed for siblings of children with a chronic illness relative to comparison participants or normative data; (2) heterogeneity existed for those effect sizes; (3) parent reports were more negative than child self-reports; (4) psychological functioning (i.e., depression, anxiety), peer activities, and cognitive development scores were lower for siblings of children with a chronic illness compared to controls; and (5) a cluster of chronic illnesses with daily treatment regimes was associated with negative effect statistics compared to chronic illnesses that did not affect daily functioning.
Conclusions: More methodologically sound studies investigating the psychological functioning of siblings of children with a chronic illness are needed. Clinicians need to know that siblings of children with a chronic illness are at risk for negative psychological effects. Intervention programs for the siblings and families of children with a chronic illness should be developed.
Key words: pediatric chronic illness; siblings; meta-analysis; psychological adjustment.
|
Introduction |
|---|
|
TopAbstractIntroductionMethodResultsDiscussion*Denotes studies included in... |
|---|
Between 5% and 40% of children suffer from a chronic illness (Newacheck & Halfon, 1998
;
Perrin & MacLean, 1988).
Williams (1997) defined a
chronic illness as a "medically diagnosed ailment with a duration of 6
months or longer, which shows little change or slow progression" (p.
312). In the United States, between 4 and 7 million children suffer from one
or more chronic illnesses, and about one-half to one million of those children
suffer from a severe chronic childhood disability
(Newacheck & Halfon, 1998;
Patterson, 1988). In all
likelihood, these figures underestimate the number of children with a chronic
illness (Lenton, Stallard, Lewis, &
Mastroyannopoulou, 2001). Childhood chronic illness has long been
thought to have a negative impact on the psychological functioning and
behavior of the ill child, that "compared with healthy peers, children
with ongoing health conditions are at greater risk of mental health
problems... emotional disorders, abnormal behavioral symptoms, and
school-related adjustment problems"
(Cohen, 1999, p. 149). All
family members could be affected by having a child with a chronic illness.
This review focuses on the literature pertaining to the siblings of children
with a chronic illness.
Siblings of Children With a Chronic Illness
In one of the first literature reviews of the impact of illness on the
siblings of children with a chronic disease, McKeever
(1983) concluded that these
siblings were a "population at risk" (p. 210). Hannah and
Midlarsky (1985) also found
siblings to be a "population at risk to experience psychological
difficulties" (p. 510), but there was the suggestion of some positive
benefits to growing up with an ill sibling, such as greater compassion. More
recent reviews (e.g., Faux,
1993; Packman,
1999; Williams,
1997) repeat these themes: negative outcomes but the suggestion of
some long-term, positive effects. The most striking impression from these
literature reviews, however, is the lack of consensus. "To anyone
reading the literature reporting research studies of the psychological
adjustment of the siblings of individuals with a disability, the overwhelming
impression is one of contradiction and confusion"
(Cuskelly, 1999, p. 111).
Quantitative Reviews of the Literature
A recent methodological advance to resolve discrepant findings across
studies is meta-analysis. This quantitative review strategy is employed to
assess factors both substantive and methodological that produce
inconsistencies across studies (Schmidt,
1992). Howe (1993)
employed a vote-count meta-analysis strategy to review 21 studies with control
groups or normative reference groups that examined siblings of children with
chronic illness. A vote-count meta-analysis is a simple tabulation of studies
by their outcomes. Howe concluded that siblings of children with a chronic
illness were at higher risk than other children for psychological problems,
that neurological conditions produced more negative effects than
nonneurological conditions, and that negative effects were most often
manifested as internalizing behaviors.
Summers, White, and Summers
(1994) conducted a vote-count
meta-analysis of 13 studies of siblings of children with a chronic illness or
an intellectual disability. These 13 studies were assessed for their
methodological quality and research methodology, and study results were
categorized as positive, negative, or nonsignificant. These researchers
concluded that being the sibling of a child with a disability had both
negative and positive consequences, that parent surveys and direct observation
generated more negative findings than child self-reports, and that higher
quality studies found fewer differences between siblings and comparison
samples. Like Howe's (1993)
review of the literature, the Summers et al. meta-analysis was constrained by
the limitations to the vote-count review strategy: no estimation of effect
size magnitude, no consideration of sample size, and no mechanism for
evaluating systematically the impact of moderator variables.
This Study
A recent meta-analysis of 25 studies and 79 effect sizes from the
literature on the siblings of individuals with intellectual disabilities
(Rossiter & Sharpe, 2001)
revealed a small negative effect for having a sibling with an intellectual
disability that could not be attributed to a publication bias or some other
artifact. This negative effect was most pronounced for measures of
psychological functioning, especially depression, and adult reports versus
child self-reports. This meta-analysis pertains to the siblings of children
with a chronic illness. Based on the findings from traditional literature
reviews and the vote-count meta-analyses, a negative effect was anticipated
for having a sibling with a chronic illness. A number of hypotheses based on
methodological and substantive issues were then derived.
Methodological Issues. The first methodological hypothesis was
that studies published more recently would show fewer negative and more
positive outcomes than earlier studies. Lamorey
(1999) observed more recent
studies to show fewer negative effects and more variation in outcomes. A
second methodological hypothesis was that more negative effects would be found
for parental reports than sibling self-reports
(Summers et al., 1994). The
third methodological hypothesis was that studies employing normative data for
comparison to the sibling samples would produce negative effects of greater
magnitude than found for studies that employed matched control groups
(Lavigne & Faier-Routman,
1992).
Substantive Issues. A number of hypotheses were also made that
related to substantive variables. First, a larger negative effect was expected
for internalizing over externalizing behaviors. Howe
(1993) found four of eleven
studies of siblings of children with chronic illness showed a negative effect
for internalizing behavior compared to only one of eight studies for
externalizing behaviors. Second, sibling outcomes were anticipated to vary by
the chronic disease and its features. One view is many chronic conditions of
childhood produce similar psychological and behavioral effects
(Vessey & Mebane, 2000).
Childhood chronic illnesses, however, vary on dimensions such as etiology, age
of onset, impact on functioning, and prognosis (see
Lobato, Faust, & Spirito,
1988). More severe chronic illnesses place greater restrictions on
the child's activities (Newacheck &
Taylor, 1992), and perhaps greater demands on parents, siblings,
the family system, and the community
(Patterson, 1988). Third, the
interaction of sibling gender and birth order was considered
(Howe, 1993;
Williams, 1997).
|
Method |
|---|
|
TopAbstractIntroductionMethodResultsDiscussion*Denotes studies included in... |
|---|
Fifty published studies from 1976 to 2000, representing over twenty-five hundred siblings of children with chronic illness, were identified from computer searches of databases such as PsycLit and MEDLINE, using key words such as "siblings" and "illness," from previous reviews of the literature and from the reference sections of located studies. Excluded from the meta-analysis were case studies, nonempirical or qualitative studies, or studies without an appropriate comparison group or normative data. Studies were also excluded that evaluated the reactions of healthy siblings to the illness or death of a brother or sister or pertained to the adult siblings of individuals with a chronic illness. Studies that employed no comparison group but that provided normative data were included in this meta-analysis.
Unpublished studies were not sought for inclusion in this meta-analysis.
First, it is almost impossible to collect all published studies in all
languages, much less all unpublished studies. Second, the peer-review process
for published studies serves as an albeit imperfect form of quality control.
Third, there is evidence that publication bias is less serious than once
feared (Sharpe, 1997).
Publication bias, the so-called "file-drawer" problem, is the
belief that the failure to include unpublished studies in the meta-analysis
might inflate the magnitude of effect sizes, given that published studies may
overrepresent statistically significant findings. To ascertain the likelihood
of such a publication bias, statistical and graphical analyses of effect sizes
were conducted.
Studies by the same author(s) that appeared to examine the same
participants (e.g., Breslau & Prabucki,
1987; Breslau, Weitzman, &
Messenger, 1981) were treated as a single study for the purposes
of this meta-analysis. Three of the primary studies
(Faux, 1991; Stawski,
Averbach, Barasch, Lerner, & Zimin, 1997;
Wood et al., 1988) provided
separate data for the siblings of children with distinctly different chronic
illnesses. These subsamples were treated as separate studies. In total, 51
study-level effect size statistics were evaluated. Each study was coded for
method of data collection (child self-report, parent report, or direct
observation), chronic illness, age of siblings, gender of siblings, number of
sibling and comparison participants, and dependent measure category:
psychological functioning (e.g., Internalizing subscales of the Child Behavior
Checklist), self-concept (e.g., Piers-Harris Self-Concept scale), care-taking,
sibling relationship, peer activities (e.g., Social Competence subscale of the
Child Behavior Checklist), cognitive functioning (e.g., intelligence test
scores), and cognitive development (e.g., school performance). Parent and
teacher reports were combined because only five studies asked teachers to
complete a dependent measure. Four of the five comparisons based on teacher
reports were not statistically significant. All codings were completed by the
first author and checked independently by the second author. Disagreements
were resolved by discussion.
Effect Size Calculations. An effect size statistic d
(Hedges & Olkin, 1985) was
calculated for each relevant outcome by subtracting the mean score for
comparison participants from the mean score for siblings with a chronic
illness and by dividing that sum by a pooled standard deviation. Normative
data provided by the primary authors in the published studies were substituted
for data from comparison participants when the latter were not provided. If
means and standard deviations were not reported, effect sizes were calculated
from summary statistics (e.g., t statistics, p values) by
employing the meta-analysis software package D-Stat
(Johnson, 1989). Effect sizes
were weighted by the reciprocal of their variance as recommended by Hedges and
Olkin (1985). When no data
were reported in a primary study but the difference between the sibling and
comparison groups was said to be nonsignificant, an effect size of zero was
recorded. For all analyses, negative effect sizes reflect less positive
functioning for siblings of children with a chronic illness relative to
comparison children or normative data.
Effect sizes from the same study, chronic illness, dependent measure
category, and method of data collection were combined and averaged. The
resulting set of 103 outcome-level effect sizes was evaluated for their
statistical significance (95% confidence interval around zero) and their
homogeneity (Hedges & Olkin,
1985). The effect sizes from the 51 studies were also examined
where appropriate to do so. The overall test for homogeneity
(QT) assesses whether a set of effect sizes is internally
consistent. For most meta-analyses, homogeneity of the set of effect sizes is
not achieved without some combination of outlier analysis and partitioning of
effect sizes into smaller clusters on the basis of moderator variables. The
identification and removal of outliers are appropriate if homogeneity can be
achieved by deleting no more than 20% of the effect sizes
(Hedges & Olkin, 1985).
Regardless of the outcome of the overall test of homogeneity, however, tests
of moderator variables are justified when based on theoretical considerations
(see Hall & Rosenthal,
1991).
After the overall test for homogeneity, effect size clusters were created on the basis of moderator variables (e.g., method of data collection). The homogeneity of effect sizes within clusters (QW) and differences between mean effect sizes across clusters (QB) were calculated. A significant QB value implies differences in the mean effect sizes associated with the effect size clusters. Interpretation of such an outcome is less clear if there are significant differences in effect sizes within one or more clusters (the QW statistic for each cluster). When moderator variables were continuous (e.g., sample size), correlations between effect sizes and the moderator variables were calculated.
|
Results |
|---|
|
TopAbstractIntroductionMethodResultsDiscussion*Denotes studies included in... |
|---|
The results are divided into three sections. The first section reports on tests of effect sizes: tests of the magnitude of mean effect sizes, tests for publication bias, and tests of homogeneity of effect sizes. The second section examines the role of methodological moderator variables, specifically, year of publication, method of data collection, and comparison group versus normative data. The third section considers substantive moderator variables, specifically, categories of dependent measures, differences by chronic illness, and effects of gender, birth order, and age of sibling.
Tests of Effect Sizes
Overall Effect Size. The weighted mean effect size for the 103
outcome-level effect sizes was Md = -.20 (the equivalent
of r = -.10), a negative value significantly different from zero (95%
confidence interval = -23 to -.16). This effect size may be an underestimation
of the true effect size magnitude. Thirty-two of the 103 effect sizes were
conservatively coded as zero because the authors of those primary studies did
not report statistics but stated differences were not significant. The
weighted mean effect size after deleting those 30 observations was
Md = -.26 (95% confidence interval = -.30 to -.22). The
weighted mean effect size for the 51 studies was Md = -.21
(95% confidence interval = -.26 to -.16).
Publication Bias. Given that only published studies were included
in the meta-analysis, there is a risk of publication bias as studies that do
not find statistically significant results may not be published and,
therefore, may not be included in the meta-analysis. To investigate
publication bias, four approaches were adopted. The first was funnel plots
created by plotting sample sizes for the siblings against effect sizes at the
study and outcome level. The plots were funnel-shaped. Data points were
distributed across the lower left and right quadrants and were less frequent
as sample size increased. This pattern is not consistent with a publication
bias (Begg, 1994). Second, Wang
and Bushman (1998) recommend a
normal quantile plot over a funnel plot to assess publication bias. A normal
quantile plot involves plotting the effect sizes against the quantiles or
percentile ranks of the normal distribution. There was no gap in the effect
sizes for the 51 effect sizes at the study level and a small gap around zero
for the 103 effect sizes at the outcome level. Third, calculation of the
fail-safe N statistic (Cooper,
1998) found that there would have to be an additional 566
nonsignificant studies to reverse the significant negative result from the 51
studies. This number is much larger than the cutoff value of 265 studies (five
times the number of retrieved studies plus 10;
Cooper, 1998). Fourth, one
would expect a relationship between sample size and effect size magnitude if a
publication bias were operating as larger effects, both positive and negative,
would be found for studies with smaller sample sizes that do not have the
statistical power to detect small effects. There was no significant
correlation, however, between the number of sibling participants and the
absolute value of the effect sizes at the outcome level (r [101] =
.06) or study level (r [49] = .07).
Tests of Homogeneity. Heterogeneity of effect sizes was found for both the 103 outcome-level effect sizes (QT [102] = 354.7, p < .0001) and the 51 study-level effect sizes (QT [50] = 139.8, p < .0001). At the outcome-level, deletion of 11 outcomes (10.7% of the 103 outcomes) resulted in a homogeneous set (QT [91] = 112.6, p < .12). The mean effect size magnitude was reduced from Md = -.20 for the 103 outcomes to Md = -.09 for 92 outcomes (95% confidence interval = -.13 to -.05). At the level of the 51 studies, homogeneity could be achieved by the exclusion of five studies (9.8% of the database) (QT [45)]= 61.4, p < .10). The mean effect size magnitude was reduced from Md = -.26 for the 51 studies to Md = -.09 for 46 studies (95% confidence interval = -.14 to -.02).
Methodological Moderator Variables
Year of Publication. There were modest, albeit non-significant,
correlations between publication year and study-level effect sizes (r
[49] = .21, p < .14). The interpretation for a positive
correlation is that effect sizes were somewhat more positive for recent
studies. There was also a modest negative correlation between year of
publication and sample size at the study-level (r [49] = -.22,
p <.12). This would suggest the sample size has declined over the
past 20 years. More studies of siblings of children with a chronic illness
were published in the 1990s (n = 27) than the 1980s (n = 19)
and 1970s (n = 4). However, there were five large-scale studies
(i.e., more than 100 siblings of children with a chronic illness) published in
the 1980s compared to only two such studies published in the 1990s.
Method of Data Collection. Another methodological variable hypothesized to moderate effect size magnitude was method of data collection. Sixty-one outcomes were associated with parent report. Child self-report accounted for the remaining 41 outcomes. Only one outcome was the product of direct observation. After deleting the direct observation outcome for this analysis only, the difference between the mean effect sizes associated with child reports and parent reports was significant (QB [1] = 7.0, p < .0001, see Table I). Although both the child reports and parental reports mean effect sizes were significantly different from zero, the mean effect size for parental reports (Md = -.23) was almost twice as large as that for child reports (Md = -.13).
|
Comparison Group vs. Normative Data. Eighty-two outcomes were evaluated against a comparison group compared to 21 outcomes contrasted to normative data. At the outcome-level, siblings of children with chronic illnesses appeared much worse off when compared to normative data (Md = -.34), in lieu of comparison groups (Md = -.09; QB [1] = 47.9, p < .0001). Both mean effect sizes differed significantly from zero (see Table I). Caution should be taken in interpreting this outcome, given there were four-times as many comparison group studies as normative group studies.
Substantive Moderator Variables
Dependent Measures. Table
I also presents the effect sizes at the outcome-level partitioned
by category of dependent measure. The most frequently represented category of
dependent measure was psychological functioning. Differences between effect
size clusters were significant (QB [6] = 27.3, p
< .0001). Psychological functioning, peer activities, and cognitive
development effect size clusters produced negative mean effect sizes
significantly different from zero. The sibling relationship category produced
a positive effect size, although not significantly different from zero.
Internalizing vs. Externalizing Behavior. To test the hypothesis that more negative effects would be found for internalizing behaviors over externalizing behaviors, and in light of the heterogeneous effect sizes for the psychological functioning category, we further partitioned that dependent measure category. Studies that contributed to this category were examined first for dependent variables that reflected internalizing behaviors (e.g., anxiety, depression, the Internalizing subscale of the Child Behavior Checklist) or externalizing behaviors (e.g., behavior problems, aggression, the Externalizing subscale of the Child Behavior Checklist). The mean effect size for the 26 internalizing outcomes was Md = -.41 (95% confidence interval = -.48 to -.34), a value significantly larger than the mean effect size for the 24 externalizing outcomes (Md = -.15, 95% confidence interval = -.23 to -.07; QB [1] = 21.5, p < .0001).
Chronic Illnesses. Table II presents the results at the study level for different chronic illnesses. Sixteen studies were not represented. Ten of those studies combined data from diverse chronic conditions and six studies examined unique chronic illnesses not considered by any other study of siblings of children with a chronic illness. Ten chronic illnesses were represented in the remaining 35 studies. Cancer was the chronic illness in 10 studies and diabetes in 6 studies. All other chronic illnesses were represented in two or three studies. Differences between effect size clusters were significant (QB [9] = 18.8, p < .03). All mean effect sizes were negative except for two studies evaluating cardiac disease that produced a positive effect size value not statistically different from zero.
|
Severity. A number of classification schemes for chronic illnesses
have been employed in previous literature reviews. One variable we considered
was prevalence (see Newacheck &
Halfon, 1998), but all childhood chronic illnesses have low
prevalence rates with the exception of asthma. Life expectancy is one
imperfect measure of the severity of a chronic illness that has been shown to
be related to family coping, achievement of maturational milestones, and
expectations for the future (Patterson,
1988; Vessey & Melbane, 2000). This is in spite of the life
expectancy for life-threatening chronic illnesses having risen substantially
over the last two decades with advances in medical treatments
(Jackson, 2000). For our
purposes, there were data available on the mortality rates for all the chronic
illnesses represented in our studies (see
Newacheck & Halfon, 1998;
Newacheck & Taylor, 1992;
Patterson, 1988). Five studies
could not be classified into greater or lesser severity because the studies
combined chronic illnesses of different mortality rates or did not report the
specific chronic illnesses of their participants' brothers and sisters.
Chronic illnesses of higher mortality rates, and thus greater severity, were HIV/AIDS, cancer, cystic fibrosis, renal failure, sickle cell anemia, and liver disease. Diabetes, cerebral palsy, rheumatic disease, bowel disease, craniofacial anomalies, cardiac disease, epilepsy, infantile hydrocephalus, spina bifida, hearing impairments, and asthma were disorders of lower mortality rates and thus considered less severe. The difference in the mean study level effect sizes between the two clusters was not significant (QB [1] = 2.2). The siblings of children with more severe chronic illnesses were no more at risk (Md = -.17), compared to the siblings of children with less severe chronic illnesses (Md = -.26).
Empirical Classification Approach. Lavigne and Faier-Routman
(1992) adopted an empirical
approach to evaluating differences across disorders by classifying chronic
illnesses post hoc on the basis of their outcomes. Three categories of
disorder were identified on that basis. We employed an analogous strategy by
partitioning effect sizes at the study level by disease into three categories:
(1) negative and statistically different from zero, (2) negative but not
statistically different from zero, and (3) positive albeit not significantly
different from zero. We then focused on those disorders in categories 1 and 3.
In the former category were cancer, diabetes, anemia, and bowel disease. These
four diseases can affect day-to-day functioning by requiring intrusive
treatment regimes and by restricting school and play activities. In the latter
category were cardiac, craniofacial anomalies, and infantile hydrocephalus.
These chronic childhood diseases are often treated by surgical intervention
and do not necessarily affect daily functioning to the same extent as those
illnesses in category 1.
Gender, Birth Order, and Age of Sibling Effects. We attempted to
determine whether gender and birth order influenced sibling psychological and
social functioning. Approximately half of the studies provided some
information relevant to gender effects. Unfortunately, with a few exceptions
(e.g., Sahler et al., 1994),
those studies did not provide separate data for male and female participants,
reported data selectively, or provided only summary statistics not amenable to
meta-analysis. Primary authors often provided a statement of no significant
effects for gender. Even less frequently presented was information pertaining
to birth order or the combination of gender and birth order.
In the meta-analysis of siblings of children with mental retardation,
Rossiter and Sharpe (2001)
coded studies for the proportion of male siblings and assessed the
relationship between those proportions and effect sizes. We adopted the same
strategy in this meta-analysis. The authors of six primary studies did not
provide sufficient information to determine the number of male and female
siblings. The percentage of male participants in the remaining studies ranged
between 30 and 61% (average 47%) with two exceptions; all siblings in
Israelite (1986) and Silver
and Frohlinger-Graham (2000)
were female. The resulting correlation between the proportion of male
participants and effect sizes at the study level was not significant
(r [42] = .04).
When available, the mean age and the age range of siblings were recorded. When the authors of a primary study failed to provide a mean age for siblings, the midpoint of the age range was used. Across all studies, the youngest siblings were 2 and the oldest were 20 with an average age range of 9.9 years (SD = 3.4). The mean age of participants was 10.8 years (SD = 2.1). There were no significant correlations between the mean age and study-level effect size values (r [47] = -.11), and between the age range and study-level effect size values (r [39] = -.16).
|
Discussion |
|---|
|
TopAbstractIntroductionMethodResultsDiscussion*Denotes studies included in... |
|---|
This meta-analysis found a statistically significant and negative overall effect for having a sibling with a chronic illness. This finding is consistent with quantitative reviews of the relevant literature that employed vote counts of significant and nonsignificant effects (e.g., Howe, 1993
;
Summers et al., 1994) and
traditional literature reviews (e.g.,
Faux, 1993;
Hannah & Midlarsky, 1985;
McKeever, 1983;
Packman, 1999;
Williams, 1997). The magnitude
of this negative overall effect was an effect size of -.20. Cohen's
(1988) widely adopted criteria
for effect size magnitude places the magnitude of the effect for siblings of
children with a chronic illness at the upper limits of a "small"
effect size. This effect size was substantially larger than the mean effect
sizes reported by Rossiter and Sharpe
(2001) for the siblings of
children with intellectual disabilities, but much smaller than the mean effect
sizes calculated by Lavigne and Faier-Routman
(1992) for the psychological
adjustment of children with a chronic illness.
Efforts were made to show that the negative outcome for the siblings of
children with a chronic illness could not be accounted for by restricting our
meta-analysis to published studies. An examination of the pattern of effect
sizes from funnel and normal quantile plots, and results from calculation of
failsafe Ns and correlations between sample size and effect size, all
serve as evidence against the results being an artifact of publication status.
Furthermore, a computer search was conducted of the Dissertations Abstracts
computer database using keywords from our computer searches. From the reading
of the abstracts, 9 dissertations generated negative outcomes, 15 showed no
differences or mixed results, and only 1 dissertation
(Gold, 1999) produced a
positive outcome for siblings of children with a chronic illness.
To investigate some possible determinants for the negative effect of having
a sibling with a chronic illness, we examined a number of potential moderator
variables. Methodological moderator variables were examined first. With the
correcting of methodological flaws in early studies
(Faux, 1993), reduction in
mortality rates and improvements in the quality of life for children with
chronic illnesses (Jackson,
2000), and the development of effective psychological
interventions for children with chronic illnesses (see
Kibby, Tyc, & Mulhern,
1998), we anticipated fewer negative findings for siblings in more
recent studies. A correlation between effect size and year of publication was
modest but in the anticipated direction. What has changed most over the last
30 years is our attitudes toward individuals with disabilities. In contrasting
early studies with more recent research, Lamorey
(1999) noted "the
educational, political, and medical context of disability in the 1960s and
1970s incorporated little of the advocacy, intervention and habilitation
efforts, normalization, and inclusion that characterize more current views of
disability" (p. 81). A second encouraging result relating to year of
publication was that more studies investigating the siblings of children with
a chronic illness were published in the last decade than in all previous
decades.
The influence of two other methodological moderator variables was
considered: parent reports versus child self-reports and comparison data
versus normative data. In the first case, parental reports were decidedly more
negative than child self-reports. Children may not perceive any negative
effects or may deny such effects until adulthood. Conversely, parents may be
overprotective of their children or may be overly sensitive to negative
outcomes. Collaborative data from fathers and mothers of the siblings and from
unbiased observers are needed to address this question. In the second case,
siblings of children with a chronic illness fared better relative to a control
group than when compared to normative data. Some authors went to considerable
effort to ensure equivalency between sibling and control participants. Silver
and Frohlinger-Graham (2000),
for example, recruited female sibling and control group participants from the
same university medical center and matched for sibling age, gender, birth
order, and age spacing.
Given heterogeneous effect sizes and negative effects after partitioning by
methodological moderator variables, a number of substantive moderator
variables were considered. Classification of dependent measures into discrete
categories revealed psychological functioning, peer activities, and cognitive
development were associated with negative mean effect sizes. Consistent with
Rossiter and Sharpe's (2001)
meta-analysis of siblings of individuals with intellectual disabilities, the
sibling relationship was the one category associated with a positive though
not significant effect size. The sibling relationship is paradoxical,
incorporating both conflict and companionship. Although having a sibling with
a chronic illness may be associated with difficulties across a number of
domains, the sibling relationship may be resilient and perhaps even enhanced
in the context of disability.
Consistent with previous reviews of this and related literatures
(Howe, 1993;
Rossiter & Sharpe, 2001),
internalizing behaviors such as anxiety and depression were associated with
larger negative effects than were externalizing behaviors. One can only
speculate as to why the brothers and sisters of children with a chronic
illness respond by internalizing their difficulties. A caretaker role involves
the sibling as a quasi-parent, participating in such activities as feeding and
dressing their sibling. There is evidence that the caretaking role is elevated
when one sibling has a disability (Boyce
& Barnett, 1993), and internalizing behaviors may be a
response to these inflated caretaking demands
(Gold, 1993). Frustrations
arising from parental inattention or caretaking responsibilities may not be
easily externalized by the healthy sibling into behaviors such as aggression,
given the precarious health status of their brother or sister.
A second substantive variable that was considered was the nature of the
chronic illness itself. Lavigne and Faier-Routman
(1992) suggest that it is not
the features of any specific disease that most affect psychological
functioning, but rather features that vary across childhood chronic diseases,
such as whether the disease is life-threatening. In this study, no difference
was found in the functioning of siblings when their brother or sister had a
more or less severe (i.e., mortality rates) childhood illness. However,
siblings of children that have a chronic illness that affects their day-to-day
functioning (e.g., bowel disease, cancer) are more negatively affected than
siblings of children less in need of intense, daily assistance (e.g.,
craniofacial anomalies). Again, this alludes to the central role of caregiving
demands and the amount of parental attention required by a child with a
chronic illness. There are data available for broad categories of chronic
illnesses on days of limited activity, proportion of children unable to engage
in activities, number of school absences, and physician contacts (see
Newacheck & Halfon, 1998).
As better methods of quantifying disease severity are developed, future
researchers should investigate further the impact of disease factors on
psychological functioning of siblings.
Lavigne and Faier-Routman's
(1992) meta-analysis of 87
studies of children with a chronic illness produced results strikingly
parallel to our findings from the sibling literature. Lavigne and
Faier-Routman found negative effects for overall adjustment and for measures
of internalizing behaviors, externalizing behaviors, and self-concept. Larger
effect sizes were found for internalizing behaviors over externalizing
behavior, and for studies that employed normative comparisons over control
groups. Lavigne and Faier-Routman also concluded the risk for psychological
problems varied by disease.
Any meta-analysis is limited by the nature and number of primary studies,
the data reported, the variables assessed, and the design of those primary
studies. All the studies in this meta-analysis were published, so our results
should not be generalized to unpublished research. We were unable to report on
the effect of variables such as gender and birth order or other moderator
variables such as family and parental functioning (see
Lavigne & Faier-Routman,
1993), as this information was not readily available in most
reviewed studies. One last limitation is that our examination of moderator
variables employed what is fundamentally a correlational technique to evaluate
the results from primary studies that assessed preexisting groups. On that
basis, we cannot conclude there is a causal relationship between adjustment
problems and having a sibling with a chronic illness.
One fear often expressed regarding meta-analysis is that a quantitative
review may inhibit future research by prematurely closing an area of inquiry
(Boden, 1992). To the contrary,
we believe this meta-analysis highlights the need for more, not less, research
into the psychological functioning of siblings of children with a chronic
illness. We hope that future research continues to employ comparison groups,
but also direct observation, longitudinal, and qualitative research designs,
nonreactive dependent measures, the reporting of gender and birth order data,
and the assessment of parental/familial risk factors. We would also hope that
more consideration will be given to features of specific chronic childhood
illnesses. There is also the need for studies of adult siblings of individuals
with a chronic illness and efforts to seek positive long-term consequences
such as greater empathy and a better understanding of individuals with
disabilities.
Family dynamics are an intriguing and often complex set of relationships
and even more so when a child in a family is born with or develops a chronic
physical illness. Families experiencing childhood chronic illness must adapt
to caregiving burdens, stress, and anxiety demands. Clinicians working with
the families of children with chronic illnesses need to be aware that siblings
are at some risk for negative psychological effects. Information sessions and
support groups have been shown to enhance children's psychological state,
their knowledge of disabilities, and their understanding of the family
situation (Wamboldt & Wamboldt,
2000). In a recent meta-analysis, Kibby et al.
(1998) found psychological
interventions for disease management and emotional/behavioral problems to be
effective for children and adolescents with a chronic illness. These programs
could be expanded to the siblings and families of children with a chronic
illness. The results from this meta-analysis suggest that one focus for
interventions should be internalizing behaviors such as anxiety and
depression. Future research should explore the effectiveness of these
interventions to assist the brothers and sisters of children with a chronic
illness.
|
Acknowledgments |
|---|
We thank Cathy L. Faye and three anonymous reviewers for their comments and suggestions. This research was supported by a Small Universities Grant from the Social Sciences and Humanities Research Council of Canada.
Received May 17, 2001; revision received December 21, 2001; accepted March 19, 2002
|
*Denotes studies included in the meta-analysis. |
|---|
|
TopAbstractIntroductionMethodResultsDiscussion*Denotes studies included in... |
|---|
Begg, C. B. (1994). Publication bias. In H. Cooper & L. V. Hedges (Eds.), The handbook of research synthesis (pp. 399-409). New York: Russell Sage Foundation.
*Bettoli-Vaughan, E., Brown, R. T., Brown, J. V., & Baldwin, K. (1998). Psychological adjustment and adaptation of siblings and mothers of children with HIV/AIDS. Families, Systems and Health, 16, 249-266.
Boden, W. E. (1992). Meta-analysis in clinical trials reporting: Has a tool become a weapon? Editorial. American Journal of Cardiology, 69, 681.[Web of Science][Medline]
Boyce, G., & Barnett, W. (1993). Siblings of persons with mental retardation: A historical perspective and recent findings. In Z. Stoneman & P. Berman (Eds.), The effects of mental retardation, disability, and illness on sibling relationships: Research issues and challenges (pp. 145-184). Baltimore, MD: Paul H. Brookes.
*Breslau, N., & Prabucki, K. (1987).
Siblings of disabled children: Effects of chronic stress in the family.
Archives of General Psychiatry,
44,
1040-1046.
*Breslau, N., Weitzman, M., & Messenger, K.
(1981). Psychologic functioning of siblings of disabled children.
Pediatrics, 67,
344-353.
*Cadman, D., Boyle, M., & Offord, D. R. (1988). The Ontario Child Health Study: Social adjustment and mental health of siblings of children with chronic health problems. Developmental and Behavioral Pediatrics, 9, 117-121.
*Carandang, M. L. A., Folkins, C. H., Hines, P. A., & Steward, M. S. (1979). The role of cognitive level and sibling illness in children's conceptualizations of illness. American Journal of Orthopsychiatry, 49, 474-481.[Web of Science][Medline]
*Cohen, D. S., Friedrich, W. N., Jaworski, T. M., Copeland, D., & Pendergrass, T. (1994). Pediatric cancer: Predicting sibling adjustment. Journal of Clinical Psychology, 50, 303-319.[Web of Science][Medline]
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
Cohen, M. S. (1999). Families coping with childhood chronic illness: A research review. Families, Systems and Health, 17, 149-164.
Cooper, H. (1998). Synthesizing research: A guide for literature review (3rd ed.). Thousand Oaks, CA: Sage.
*Cowen, L., Mok, J., Corey, M., MacMillan, H., Simmons,
R., & Levison, H. (1986). Psychologic adjustment of the
family with a member who has cystic fibrosis. Pediatrics,
77, 745-753.
Cuskelly, M. (1999). Adjustment of siblings of children with a disability: Methodological issues. International Journal for the Advancement of Counselling, 21, 111-124.
*Dallas, E., Stevenson, J., & McGurk, H. (1993). Cerebralpalsied children's interactions with siblings: Influence of severity of disability, age and birth order. Journal of Child Psychology and Psychiatry, 34, 621-647.
*Daniels, D., Miller, J. J., Billings, A. G., & Moos, R. H. (1986). Psychosocial functioning of siblings of children with rheumatic disease. Journal of Pediatrics, 109, 379-383.[Web of Science][Medline]
*Daniels, D., Moos, R. H., Billings, A. G., & Miller, J. J. (1987). Psychosocial risk and resistance factors among children with chronic illness, healthy siblings, and healthy controls. Journal of Abnormal Child Psychology, 15, 295-308.[Web of Science][Medline]
*Dolgin, M. J., Blumensohn, R., Mulhern, R. K., Orbach, J., Sahler, O. J., Roghmann, K. J., Carpenter, P. J., Barbarin, O. A., Sargent, J. R., Zeltzer, L. K., & Copeland, D. R. (1997). Sibling Adaptation to Childhood Cancer Collaborative Study: Cross-cultural aspects. Journal of Psychosocial Oncology, 15, 1-14.
*Drotar, D., Doershuk, C. F., Stern, R. C., Boat, T. F.,
Boyer, W., & Matthews, L. (1981). Psychosocial functioning of
children with cystic fibrosis. Pediatrics,
67, 338-343.
*Engstrom, I. (1992). Psychological problems in siblings of children and adolescents with inflammatory bowel disease. European Child and Adolescent Psychiatry, 1, 24-33.
*Evans, C. A., Stevens, M., Cushway, D., & Houghton, J. (1992). Sibling response to childhood cancer: A new approach. Child: Care, Health and Development, 18, 229-244.[Web of Science][Medline]
*Faux, S. A. (1991). Sibling relationships in families with congenitally impaired children. Journal of Pediatric Nursing, 6, 175-184.[Medline]
Faux, S. A. (1993). Siblings of children with chronic physical and cognitive disabilities. Journal of Pediatric Nursing, 8, 305-317.[Medline]
*Feeman, D. J., & Hagen, J. W. (1990). Effects of childhood chronic illness on families. Social Work in Health Care, 14, 37-53.[Web of Science][Medline]
*Fernell, E., Gillberg, C., & von Wendt, L. (1992). Selfesteem in children with infantile hydrocephalus and in their siblings: Use of the Piers-Harris self-concept scale. European Child and Adolescent Psychiatry, 1, 227-232.
*Ferrari, M. (1984). Chronic illness; Psychosocial effects on siblings: Chronically ill boys. Journal of Child Psychology and Psychiatry, 25, 459-476.
*Ferrari, M. (1987). The diabetic child and well sibling: Risks to the well child's self-concept. Children's Health Care, 15, 141-148.
*Fielding, D., Moore, B., Dewey, M., Ashley, P., McKendrick, T., & Pinkerton, P. (1985). Children with end-stage renal failure: Psychological effects on patients, siblings and parents. Journal of Psychosomatic Research, 29, 457-465.[Web of Science][Medline]
*Gallo, A. M., Breitmayer, B. J., Knafl, K. A., & Zoeller, L. H. (1992). Well siblings of children with chronic illness: Parents' reports of their psychologic adjustment. Pediatric Nursing, 18, 23-27.[Medline]
*Gardner, N. (1998). Emotional and behavioural difficulties in children with diabetes: A controlled comparison with siblings and peers. Child: Care, Health and Development, 24, 115-128.[Web of Science][Medline]
Gold, J. I. (1999). Psychological adjustment in siblings of children with sickle cell disease: Relationships with family and sibling adaptational processes. Dissertation Abstracts International, 60(5), 2339B.
Gold, N. (1993). Depression and social adjustment in siblings of boys with autism. Journal of Autism and Developmental Disorders, 23, 147-163.[Web of Science][Medline]
Hall, J. A., & Rosenthal, R. (1991). Testing for moderator variables in meta-analysis: Issues and methods. Communication Monographs, 58, 437-448.[Web of Science]
Hannah, M. E., & Midlarsky, E. (1985). Siblings of the handicapped: A literature review for school psychologists. School Psychology Review, 14, 510-520.
*Harvey, D. H. P., & Greenway, A. P. (1984). The selfconcept of physically handicapped children and their non-handicapped siblings: An empirical investigation. Journal of Child Psychology and Psychiatry, 25, 273-284.
Hedges, L. V., & Olkin, L. (1985). Statistical methods for meta-analysis. New York: Academic Press.
*Horwitz, W. A., & Kazak, A. E. (1990). Family adaptation to childhood cancer: Siblings and family systems variables. Journal of Clinical Child Psychology, 19, 221-228.[Web of Science]
Howe, G. W. (1993). Siblings of children with physical disabilities and chronic illnesses: Studies of risk and social ecology. In Z. Stoneman & P. W. Berman (Eds.), The effects of mental retardation, disability, and illness on sibling relationships: Research issues and challenges (pp. 185-213). Baltimore, MD: Paul H. Brookes.
*Israelite, N. K. (1986). Hearing-impaired children and the psychological functioning of their normal-hearing siblings. Volta Review, 88, 47-54.[Web of Science]
Jackson, P. L. (2000). The primary care provider and children with chronic conditions. In P. L. Jackson and J. A. Vessey (Eds.), Primary care of the child with a chronic condition (3rd ed., pp. 3-19). St. Louis: Mosby.
Johnson, B. T. (1989). DSTAT: Software for the meta-analytic review of research literatures. Hillsdale, NJ: Erlbaum.
*Kazak, A., & Clark, M. W. (1986). Stress in families of children with myelomeningocele. Developmental Medicine and Child Neurology, 28, 220-228.[Web of Science][Medline]
Kibby, M. Y., Tyc, V. L., & Mulhern, R. K. (1998). Effectiveness of psychological intervention for children and adolescents with chronic medical illness: A meta-analysis. Clinical Psychology Review, 18, 103-117.[Web of Science][Medline]
*Labropoulou, S., & Beratis, S. (1995). Psychosocial adjustment of thalassaemic children's siblings. Journal of Psychosomatic Research, 39, 911-919.[Web of Science][Medline]
Lamorey, S. (1999). Parentification of siblings of children with disability or chronic disease. In N. D. Chase (Ed.), Burdened children: Theory, research, and treatment of parentification (pp. 75-91). Thousand Oaks, CA: Sage.
Lavigne, J. V., & Faier-Routman, J. (1992).
Psychological adjustment to pediatric physical disorders: A meta-analytic
review. Journal of Pediatric Psychology,
17, 133-157.
Lavigne, J. V., & Faier-Routman, J. (1993). Correlates of psychological adjustment to pediatric physical disorders: A meta-analytic review and comparison with existing models. Developmental and Behavioral Pediatrics, 14, 117-123.
*Lavigne, J. V., & Ryan, M. (1979).
Psychologic adjustment of siblings of children with chronic illness.
Pediatrics, 63,
616-627.
*Lavigne, J. V., Traisman, H. S., Marr, T. J., & Chasnoff, I. J. (1982). Parental perceptions of the psychological adjustment of children with diabetes and their siblings. Diabetes Care, 5, 420-426.[Abstract]
Lenton, S., Stallard, P., Lewis, M., & Mastroyannopoulou, K. (2001). Prevalence and morbidity associated with non-malignant, life-threatening conditions in childhood. Child: Care, Health and Development, 27, 389-398.[Web of Science][Medline]
Lobato, D., Faust, D., & Spirito, A. (1988).
Examining the effects of chronic disease and disability on children's sibling
relationships. Journal of Pediatric Psychology,
13, 389-407.
*Madan-Swain, A., Sexson, S. B., Brown, R. T., & Ragab, A. (1993). Family adaptation and coping among siblings of cancer patients, their brothers and sisters, and non-clinical controls. American Journal of Family Therapy, 21, 60-70.[Web of Science]
McKeever, P. (1983). Siblings of chronically ill children: A literature review with implications for research and practice. American Journal of Orthopsychiatry, 53, 209-218.[Web of Science]
*Mims, J. (1997). Self-esteem, behavior,
and concerns surrounding epilepsy in siblings of children with epilepsy.
Journal of Child Neurology, 12,
187-192.
Newacheck, P. W., & Halfon, N. (1998). Prevalence
and impact of disabling chronic conditions in childhood. American
Journal of Public Health, 88,
610-617.
Newacheck, P. W., & Taylor, W. R. (1992).
Childhood chronic illness: Prevalence, severity, and impact.
American Journal of Public Health,
82, 364-371.
*Noll, R. B., Yosua, L. A., Vannatta, K., Kalinyak, K.,
Bukowski, W. M., & Davies, W. H. (1995). Social competence of
siblings of children with sickle cell anemia. Journal of Pediatric
Psychology, 20,
165-172.
Packman, W. L. (1999). Review: Psychosocial impact of pediatric BMT on siblings. Bone Marrow Transplantation, 24, 701-706.[Web of Science][Medline]
Patterson, J. M. (1988). Chronic illness in children and the impact on families. In C. S. Chilman, E. W. Nunnally, & F. M. Cox (Eds.), Chronic illness and disability: Families in trouble series (vol 2; pp. 69-107). Newbury Park, CA: Sage.
Perrin, J. M., & MacLean, W. E. (1988). Children with chronic illness: The prevention of dysfunction. Pediatric Clinics of North America, 35, 1325-1337.[Web of Science][Medline]
Rossiter, L., & Sharpe, D. (2001). The siblings of individuals with mental retardation: A quantitative integration of the literature. Journal of Child and Family Studies, 10, 65-84.
*Rubovits, D. S., & Siegel, A. W. (1994). Developing conceptions of chronic disease: A comparison of disease experience. Children's Health Care, 23, 267-285.
*Sahler, O. J. Z., Roghmann, K. J., Carpenter, P. J., Mulhern, R. K., Dolgin, M. J., Sargent, J. R., Barbarin, O. A., Copeland, D. R., & Zeltzer, L. K. (1994). Sibling Adaptation to Childhood Cancer Collaborative Study: Prevalence of sibling distress and definition of adaptation levels. Developmental and Behavioral Pediatrics, 15, 353-366.
*Sawyer, M., Crettenden, A., & Toogood, I. (1986). Psychological adjustment of families of children and adolescents treated for leukaemia. American Journal of Pediatric Hematology/Oncology, 8, 200-207.[Web of Science][Medline]
Schmidt, F. L. (1992). What do data really mean? Research findings, meta-analysis, and cumulative knowledge in psychology. American Psychologist, 47, 1173-1181.
*Schwirian, P. M. (1976). Effects of the presence of a hearing-impaired preschool child in the family on behavior patterns of older "normal" siblings. American Annals of the Deaf, 121, 373-380.[Web of Science][Medline]
Sharpe, D. (1997). Of apples and oranges, file drawers and garbage: Why validity issues in meta-analysis will not go away. Clinical Psychology Review, 17, 881-901.[Web of Science][Medline]
*Silver, E. J., & Frohlinger-Graham, M. J.
(2000). Brief report: Psychological symptoms in healthy female
siblings of adolescents with and without chronic conditions.
Journal of Pediatric Psychology,
25, 279-284.
*Stawski, M., Auerbach, J. G., Barasch, M., Lerner, Y., & Zimin, R. (1997). Behavioural problems of children with chronic physical illness and their siblings. European Child and Adolescent Psychiatry, 6, 20-25.[Web of Science][Medline]
*Stewart, D. A., Stein, A., Forrest, G. C., & Clark, D. M. (1992). Psychosocial adjustment in siblings of children with chronic life-threatening illness: A research note. Journal of Child Psychology and Psychiatry, 33, 779-784.
*Stewart, S. M., Kennard, B. D., DeBolt, A., Petrik, K., Waller, D. A., & Andrews, W. S. (1993). Adaptation of siblings of children awaiting liver transplantation. Children's Health Care, 22, 205-215.
Summers, C. R., White, K. R., & Summers, M. (1994). Siblings of children with a disability: A review and analysis of the empirical literature. Journal of Social Behavior and Personality, 9, 169-184.
*Tew, B., & Laurence, K. M. (1973). Mothers, brothers and sisters of patients with spina bifida. Developmental Medicine and Child Neurology, 15, 69-76.[Web of Science][Medline]
*Thompson, A. B., Cutner, M. E., & O'Rear, M. R. (1994). The psychosocial adjustment of well siblings of chronically ill children. Children's Health Care, 23, 211-226.
*Treiber, F., Mabe, P. A., & Wilson, G. (1987). Psychological adjustment of sickle cell children and their siblings. Children's Health Care, 16, 82-88.
*Tritt, S. G., & Esses, L. M. (1988). Psychosocial adaptation of siblings of children with chronic medical illnesses. American Journal of Orthopsychiatry, 58, 211-220.[Web of Science][Medline]
*Vance, J. C., Fazan, L. E., Satterwhite, B., &
Pless, I. B. (1980). Effects of nephrotic syndrome on the family:
A controlled study. Pediatrics,
65, 948-955.
*Van Dongen-Melman, J. E. W. M., De Groot, A., Hahlen, K., & Verhulst, F. C. (1995). Siblings of childhood cancer survivors: How does this "forgotten" group of child adjust after cessation of successful cancer treatment? European Journal of Cancer, 31A, 2277-2283.
Vessey, J. A., & Mebane, D. J. (2000). Chronic conditions and child development. In P. L. Jackson & J. A. Vessey (Eds.), Primary care of the child with a chronic condition (3rd ed., pp. 20-49). St. Louis: Mosby.
Wamboldt, M. Z., & Wamboldt, F. S. (2000). Role of the family in the onset and outcome of childhood disorders: Selected research findings. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 1212-1219.[Web of Science][Medline]
*Wallander, J. L., Varni, J. W., Babani, L., Banis, H.
T., & Wilcox, K. T. (1989). Family resources as resistance
factors for psychological maladjustment in chronically ill and handicapped
children. Journal of Pediatric Psychology,
14, 157-173.
Wang, M. C., & Bushman, B. J. (1998). Using the normal quantile plot to explore meta-analytic data sets. Psychological Methods, 3, 46-54.[Web of Science]
*Wang, R., & Martinson, I. M. (1996). Behavioral responses of healthy Chinese siblings to the stress of childhood cancer in the family: A longitudinal study. Journal of Pediatric Nursing, 11, 383-391.[Medline]
Williams, P. D. (1997). Siblings and pediatric chronic illness: A review of the literature. International Journal of Nursing Studies, 34, 312-323.[Web of Science][Medline]
*Wood, B., Boyle, J. T., Watkins, J. B., Nogueira, J., Zimand, E., & Carroll, L. (1988). Sibling psychological status and style as related to the disease of their chronically ill brothers and sisters: Implications for models of biopsychosocial interaction. Developmental and Behavioral Pediatrics, 9, 66-72.
*Zeltzer, L. K., Dolgin, M. J., Shaler, O. J. Z., Roghmann, K., Barbarin, O. A., Carpenter, P. J., Copeland, D. R., Mulhern, R. K., & Sargent, J. R. (1996). Sibling Adaptation to Childhood Cancer Collaborative Study: Health outcomes of siblings of children with cancer. Medical and Pediatric Oncology, 27, 98-107.[Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  D. J. Lobato and B. T. Kao Brief Report: Family-Based Group Intervention for Young Siblings of Children with Chronic Illness and Developmental Disability J. Pediatr. Psychol., December 1, 2005; 30(8): 678 - 682. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. Drotar Commentary: Involving Families in Psychological Interventions in Pediatric Psychology: Critical Needs and Dilemmas J. Pediatr. Psychol., December 1, 2005; 30(8): 689 - 693. [Full Text] [PDF]
|
|
|
|
|
|
R. Rodenburg, G. J. Stams, A. M. Meijer, A. P. Aldenkamp, and M. Dekovic Psychopathology in Children with Epilepsy: A Meta-Analysis J. Pediatr. Psychol., September 1, 2005; 30(6): 453 - 468. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. A. Houtzager, F. J. Oort, J. E. H. M. Hoekstra-Weebers, H. N. Caron, M. A. Grootenhuis, and B. F. Last Coping and Family Functioning Predict Longitudinal Psychological Adaptation of Siblings of Childhood Cancer Patients J. Pediatr. Psychol., December 1, 2004; 29(8): 591 - 605. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. A. Alderfer, L. E. Labay, and A. E. Kazak Brief Report: Does Posttraumatic Stress Apply to Siblings of Childhood Cancer Survivors? J. Pediatr. Psychol., June 1, 2003; 28(4): 281 - 286. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||