(see also here)
Many lay persons and professionals believe that child sexual abuse (CSA) causes intense harm, regardless of gender, pervasively in the general population. The authors examined this belief by reviewing 59 studies based on college samples. Meta-analyses revealed that students with CSA were, on average, slightly less well adjusted than controls. However, this poorer adjustment could not be attributed to CSA because family environment (FE) was consistently confounded with CSA, FE explained considerably more adjustment variance than CSA, and CSA-adjustment relations generally became nonsignificant when studies controlled for FE. Self-reported reactions to and effects from CSA indicated that negative effects were neither pervasive nor typically intense, and than men reacted much less negatively than women. The college data were completely consistent with data from national samples. Basic beliefs about CSA in the general population were not supported.
[Introduction] 22
Previous Literature Reviews 23
Qualitative Literature Reviews 23
Causality 23
Intensity 23
Gender Equivalance 24
Limitataions of Qualitative Literature
Reviews 24
Sampling biases 24
Subjectivity and imprecision 24
Quantitative Literature Reviews 24
Synthesis of Quantitative Reviews 25
Causality 25
Pervasiveness 25
Intensity 26
Gender Equiquivalance 26
Current Review 26
Method 27
Sample of Studies 27
Coding the Studies 27
Psychological Correlates of CSA 28
Statistical Analysis 29
Results 29
Definitions of CSA, Prevalence Rates,
and Types of CSA 29
Definitions 29
Prevalence rates 29
Types of CSA 29
Magnitude of the Relationship Between
CSA and Psychological Adjustment 31
Sample-level analysis 31
Symptom-level analysys 31
Moderator Analysis 32
Semipartial correlational Analyses 32
Contrast analyses 33
Simple correlations 34
Moderators concerning aspects
of the CSA experience 34
Self-reported Reactions to and Effects
From CSA 35
Retrospectively recalled
immediate reactions 35
Current reflexions 36
Self-reported effects 36
Comparing male versus female
reactions and self-reported 37
effects via meta-analysis
Family Environment 38
Family environment-SCA relations 38
Family environment-symptom relations 39
Statistical control 39
Statistical validity 41
Discussion 42
The Four Assumed Properties of CSA Revisited 42
Gender Equivalance 42
Causality 43
Pervasiveness and Intensity of Negative
Effects or Correlates 44
Moderators 44
Child SexualAbuse as a Constrsuct Reconsidered 45
Summary and Conclusion 46
References 47
Appendix 51
[Introduction]
Child sexual abuse (CSA) has received considerable attention since the late
1970s from mental health care professionals, legislative, judicial, and law
enforcement personnel, the media, and the lay public (Rind & Tromovitch,
1997 ). Much of this attention has focused on possible effects of CSA on
psychological adjustment, as is shown in the professional literature and
popular press ( Pope & Hudson, 1995 ) and in the information and
entertainment media ( Esman, 1994 ; Kutchinsky, 1992 ; West & Woodhouse,
1993 ). The media have frequently presented lurid CSA cases combined with
high prevalence estimates, creating the image that CSA produces intensely
negative effects for all of its victims ( Esman, 1994 ; Kutchinsky, 1992 ;
West & Woodhouse, 1993 ). Many publications in the popular press and the
professional literature have similarly portrayed CSA as a "special destroyer
of adult mental health" ( Seligman, 1994 , p. 232), and some have attempted
to explain much or all of adult psychopathology as a consequence of CSA (
Esman, 1994 ; Nash, Hulsey, Sexton, Harralson, & Lambert, 1993 ). Examples
in the professional literature include McMillen, Zuravin, and Rideout (1995
, p. 1037), who commented that "child sexual abuse is a traumatic event for
which there may be few peers," and Rodriguez, Ryan, Rowen, and Foy (1996) ,
who combined estimates of national prevalence rates of CSA with selected
examples of empirical research to argue that posttraumatic stress disorder
is a common sequel of CSA in the general population. Opinions expressed in
the media and by many popular press and professional writers imply that CSA
has certain basic properties or qualities irrespective of the population of
interest. These implied properties are (a) CSA causes harm, (b) this harm is
pervasive in the population of persons with a history of CSA, (c) this harm
is likely to be intense, and (d) CSA is an equivalent experience for boys
and girls in terms of its widespread and intensely negative effects. The
purpose of the current review was to examine these implied basic properties.
Our goal was to address the question: In the population of persons with a
history of CSA, does this experience cause intense psychological harm on a
widespread basis for both genders?
An important first step is to discuss terminology. The term child sexual
abuse has been used in the psychological literature to describe virtually
all sexual interactions between children or adolescents and significantly
older persons, as well as between same-age children or adolescents when
coercion is involved. The indiscriminate use of this term and related terms
such as victim and perpetrator has been criticized because of concerns about
scientific validity (e.g., Kilpatrick, 1987 ; Nelson, 1989 ; Okami, 1990
; Rind & Bauserman, 1993 ). Kilpatrick argued that researchers have often
failed to distinguish between "abuse" as harm done to a child or adolescent
and "abuse" as a violation of social norms, which is problematic because it
cannot be assumed that violations of social norms lead to harm. Similarly,
Money (1979) observed that our society has tended to equate "wrongfulness"
with harmfulness in sexual matters, but harmfulness cannot be inferred from
wrongfulness. Nelson argued that the indiscriminate use of terms suggesting
force, coercion, and harm reflects and maintains the belief that these
interactions are always harmful, thereby threatening an objective appraisal
of them. Rind and Bauserman demonstrated experimentally that appraisals of
nonnegative sexual interactions between adults and
[Page 23]
adolescents described in scientific reports can be biased by the use of
negatively loaded terms such as CSA.
Problems of scientific validity of the term CSA are perhaps most apparent
when contrasting cases such as the repeated rape of a 5-year-old girl by her
father and the willing sexual involvement of a mature 15-year-old adolescent
boy with an unrelated adult. Although the former case represents a clear
violation of the person with implications for serious harm, the latter may
represent only a violation of social norms with no implication for personal
harm (Bauserman & Rind, 1997 ). By combining events likely to produce harm
with those that are not into a unitary category of CSA, valid understanding
of the pathogenicity of CSA is threatened ( Okami, 1994 ). The tendency by
researchers to label cases such as the latter as abuse reflects the slippage
of legal and moral constructs into scientific definitions ( Okami, 1990,
1994 ). Basing scientific classifications of sexual behavior on legal and
moral criteria was pervasive a half century ago ( Kinsey, Pomeroy, & Martin,
1948 ); more recently, this practice has been confined to a much smaller set
of sexual behaviors, particularly those labeled CSA.
With these caveats in mind regarding the scientific shortcomings of the term
CSA, we have nevertheless retained it for use in the current article because
of its pervasive use in the scientific literature and because many
researchers as well as lay persons view all types of sociolegally defined
CSA as harmful. On the basis of the terminology used in studies reviewed in
the current article, CSA is generally defined as a sexual interaction
involving either physical contact or no contact (e.g., exhibitionism)
between either a child or adolescent and someone significantly older, or
between two peers who are children or adolescents when coercion is used.
Previous Literature Reviews
Numerous literature reviews have appeared over the last 15 years that have
attempted to synthesize the growing body of empirical investigations of CSA
effects and correlates (e.g., Bauserman & Rind, 1997 ; Beitchman, Zucker,
Hood, DaCosta, & Akman, 1991 ; Beitchman et al., 1992 ; Black & DeBlassie,
1993 ; Briere & Elliot, 1994 ; Briere & Runtz, 1993 ; Browne & Finkelhor,
1986 ; Constantine, 1981 ; Glod, 1993 ; Jumper, 1995 ; Kendall-Tackett,
Williams, & Finkelhor, 1993 ; Kilpatrick, 1987 ; Mendel, 1995 ; Neumann,
Houskamp, Pollock, & Briere, 1996 ; Rind & Tromovitch, 1997 ; Urquiza &
Capra, 1990 ; Watkins & Bentovim, 1992 ). These reviews have not been
unanimous in their conclusions. Below, we examine their conclusions
regarding the four commonly assumed properties of CSA discussed previously.
First we examine the qualitative literature reviews, then the fewer and more
recent quantitative (i.e., meta-analytic) reviews.
Qualitative Literature Reviews
Causality.
Some qualitative reviewers have been cautious regarding the issue of
causality (e.g., Bauserman & Rind, 1997 ; Beitchman et al., 1991 ; Beitchman
et al., 1992 ; Constantine, 1981 ; Kilpatrick, 1987 ), arguing that the
reliable confounding of family environment problems with CSA prevents
definitive conclusions regarding the causal role of CSA in producing
maladjustment. Other reviewers, although recognizing limitations of
correlational data, have nevertheless argued that causality is the likely
state of affairs (e.g., Briere & Runtz, 1993 ; Glod, 1993 ; Urquiza & Capra,
1990 ). Some reviewers have strongly implied that CSA causes maladjustment
by consistent use of phrases that imply causation (e.g., "effects of CSA,"
"impact of CSA") and by not addressing alternative explanations (e.g., third
variables, such as family environment) that could account for the
CSA-maladjustment link (e.g., Black & DeBlassie, 1993 ; Briere & Elliot,
1994 ; Kendall-Tackett et al., 1993 ; Mendel, 1995 ; Watkins & Bentovim,
1992 ).
Pervasiveness.
Some reviewers have concluded that CSA outcomes are variable, rather than
consistently negative (e.g., Bauserman & Rind, 1997 ; Beitchman et al., 1991
; Beitchman et al., 1992 ; Browne & Finkelhor, 1986 ; Constantine, 1981 ;
Kilpatrick, 1987 ). Constantine concluded that there is no inevitable
outcome or set of reactions and that responses to CSA are mediated by
nonsexual factors. Beitchman et al. (1991) argued that the prevalence of
negative outcomes may be overestimated because of overreliance on clinical
samples. Browne and Finkelhor noted that only a minority of both sexually
abused (SA) children seen by clinicians and adults with a history of CSA
show serious disturbance or psychopathology. Other reviewers, however, have
implied in several different ways that CSA effects or correlates are
prevalent among persons with a history of CSA. First, some reviewers have
claimed to have written "comprehensive" reviews of the literature or
summaries of "what is currently known" (e.g., Briere & Elliott, 1994 ;
Briere & Runtz, 1993 ; Glod, 1993 ; Urquiza & Capra, 1990 ; Watkins &
Bentovim, 1992 ); their conclusion that CSA is associated with numerous
symptoms then implies that negative correlates are prevalent. Second, some
reviewers have argued that studies showing a large percentage of
asymptomatic persons with a history of CSA can be explained by factors such
as insensitive measures or insufficient time for symptoms to have developed
(e.g., Briere & Elliot, 1994 ; Kendall-Tackett et al., 1993 ). This argument
implies that negative effects are prevalent, even if not yet observed in
many cases. Third, some reviewers have not discussed limitations on
generalizability from their sample of (usually clinical) studies to other
CSA populations (e.g., Black & DeBlassie, 1993 ; Kendall-Tackett et al.,
1993 ; Mendel, 1995 ), again implying that findings of negative correlates
apply to the entire population of persons with CSA experiences.
Intensity.
Some reviewers have concluded that the intensity of CSA outcomes varies,
rather than usually being intensely negative (e.g., Bauserman & Rind, 1997 ;
Beitchman et al., 1991 ; Beitchman et al., 1992 ; Browne & Finkelhor, 1986 ;
Constantine, 1981 ; Kilpatrick, 1987 ). Browne and Finkelhor noted that SA
persons in community samples tend to be either normal or only slightly
impaired on psychological measures. Constantine and Kilpatrick found that
negative outcomes were often absent in SA persons in nonclinical samples.
Other reviewers, however, have implied that negative psychological effects
are frequently intense by describing the "extreme psychic pain" ( Briere &
Runtz, 1993 , p. 320) or the "pronounced deleterious effects" ( Mendel, 1995
, p. 101) that CSA is assumed to produce. Some reviewers have further
implied the intensity of CSA effects or correlates by presenting long lists
of severe disorders (e.g., posttraumatic stress, self-mutilation) associated
with CSA (e.g.,
[Page 24]
Black & DeBlassie, 1993 ; Briere & Elliot, 1994 ; Briere & Runtz, 1993 ;
Glod, 1993 ; Kendall-Tackett et al., 1993 ; Mendel, 1995 ; Urquiza & Capra,
1990 ; Watkins & Bentovim, 1992 ).
Gender equivalence.
Several reviewers have argued that the data are insufficient to address the
issue of gender differences in outcomes (e.g., Beitchman et al., 1991 ;
Beitchman et al., 1992 ; Browne & Finkelhor, 1986 ). Constantine (1981)
concluded that girls react more negatively than boys, attributing this
difference to differences between girls' and boys' CSA
experiences. Bauserman and Rind (1997) , on the basis of a review of
college, national, and convenience samples, concluded that reactions and
outcomes for boys are more likely to be neutral or positive than for girls.
Many reviewers, however, have concluded or implied that CSA is an equivalent
experience for boys and girls in terms of its negative impact (e.g., Black &
DeBlassie, 1993 ; Briere & Runtz, 1993 ; Mendel, 1995 ; Urquiza & Capra,
1990 ; Watkins & Bentovim, 1992 ). Black and DeBlassie stated that CSA "has,
at the very least, an equivalent impact on males and females" (p. 128).
Watkins and Bentovim claimed that one prevalent myth about CSA is that boys
are less psychologically affected than girls. Mendel dismissed as an
"exercise in futility" efforts to determine whether boys or girls are more
adversely affected by CSA, and concluded that CSA "has pronounced
deleterious effects on its victims, regardless of their gender" (p. 101).
Limitations of Qualitative Literature Reviews
The qualitative literature reviews present a mixed view of causality,
pervasiveness, intensity, and gender equivalence. This inconsistency
suggests the need for additional work in synthesizing the literature. Two
other considerations also indicate such a need: sampling biases in many of
the qualitative reviews, and the vulnerability of qualitative reviews to
subjectivity and imprecision.
Sampling biases.
Qualitative literature reviews have been primarily based on clinical or
legal samples, which cannot be assumed to be representative of the
population of persons with a history of CSA (Bauserman & Rind, 1997 ; Okami,
1991 ; Rind, 1995 ). Some reviews were based exclusively or almost
exclusively on clinical and legal samples (e.g., Beitchman et al., 1991 ;
Black & DeBlassie, 1993 ; Glod, 1993 ; Kendall-Tackett et al., 1993 ;
Mendel, 1995 ; Watkins & Bentovim, 1992 ). Others were based on a majority
of clinical and legal samples but included a sizable minority of nonclinical
and nonlegal samples (e.g., Beitchman et al., 1992 ; Briere & Elliott, 1994
; Briere & Runtz, 1993 ; Browne & Finkelhor, 1986 ; Constantine, 1981 ;
Kilpatrick, 1987 ; Urquiza & Capra, 1990 ). Only one of the qualitative
reviews cited previously (Bauserman & Rind, 1997 ) included a majority of
nonclinical and nonlegal samples.
Drawing conclusions from clinical and legal samples is problematic not only
because these samples cannot be assumed to be representative of the general
population, but also because data coming from these samples are vulnerable
to several biases that threaten their validity ( Pope & Hudson, 1995 ; Rind
& Tromovitch, 1997 ). Okami (1991) studied adults who had experienced CSA as
negative, neutral, or positive. Negative responders included both clinical
and nonclinical subjects. Clinical negative responders showed substantially
more pronounced adjustment problems than nonclinical negative responders.
Okami argued that clinical participants with negative CSA experiences
constitute the negative extreme of CSA outcomes. Pope and Hudson argued that
reliance on clinical samples is problematic for several reasons. One problem
is information bias, in which clinical patients, in a search for the causes
of their problems (termed effort after meaning ), are more likely than
nonclinical participants to recall events that can be classified as CSA,
thus inflating the CSA-maladjustment relationship. Another potential bias is
investigator expectancies (cf. Rosenthal, 1977 ), in which clinical
researchers who believe that CSA is a likely cause of their patients'
difficulties may transmit this expectancy to patients, thereby increasing
confirming responses. Finally, Pope and Hudson argued that causality cannot
be inferred from clinical samples because CSA and family disruption are
highly confounded in this population ( Beitchman et al., 1991 ; Ney, Fung, &
Wickett, 1994 ). Legal samples are also likely to contain the more serious
cases, limiting their generalizability.
Subjectivity and imprecision.
Qualitative reviews are entirely narrative and therefore susceptible to
reviewers' own subjective interpretations ( Jumper, 1995 ). Reviewers who
are convinced that CSA is a major cause of adult psychopathology may fall
prey to confirmation bias by noting and describing study findings indicating
harmful effects but ignoring or paying less attention to findings indicating
nonnegative outcomes. For example, Mendel (1995) focused on results from
Fromuth and Burkhart's (1989) midwestern sample of males to argue that boys
are harmed by their CSA experiences but paid little attention to the
southeastern sample of males reported in the same article, for whom all
CSA-adjustment correlates were nonsignificant. In a quantitative review, the
latter sample would typically have received more weight because it had 30%
more participants than the former. Even when study results generally
indicate statistically significant differences in adjustment between CSA and
control participants, summarizing this information alone is inadequate (
Rosenthal & Rosnow, 1991 ). The sizes of these differences (i.e., effect
sizes) are also important; these effect sizes can be used to assess the
intensity of CSA effects or correlates (Rind & Tromovitch, 1997 ). Only
quantitative (i.e., meta-analytic) reviews can provide this important
information.
Quantitative Literature Reviews
Three recent quantitative literature reviews ( Jumper, 1995 ; Neumann et
al., 1996 ; Rind & Tromovitch, 1997 ) represent a significant advance in
assessing CSA-adjustment relations because they all (a) included a sizable
proportion of nonclinical and nonlegal samples and (b) avoided subjectivity
and imprecision by using meta-analysis. Meta-analysis is a statistical
technique in which statistics from a set of studies are converted to a
common metric (e.g., standard normal deviate z s, Cohen's d s, Pearson's r
s), which are then combined into one overall statistic that can be used to
(a) infer whether one variable (e.g., CSA) is significantly associated with
another (e.g., adjustment) and (b) estimate the strength of this association
(Rind & Tromovitch, 1997 ). Common metrics such as d and r are referred to
as effect sizes and can be interpreted as assessing the size of the
difference of some attribute between two groups or the magnitude of
association between two variables. As a guideline,
[Page 25]
Cohen (1988) has suggested that small, medium, and large effect sizes
correspond, respectively, to d s of .20, .50, and .80, and to r s of ..10,
.30, and .50. Thus, these reviews were well suited to examining not only
whether control and SA respondents differ in adjustment, but also to what
extent they differ. Two of the reviews ( Jumper, 1995 ; Rind & Tromovitch,
1997 ) were also able to precisely compare the genders in terms of CSA
outcomes.
Jumper (1995) examined CSA-adjustment relations from 26 published studies
with 30 samples. Of 23 samples with identified sources, 30% were clinical,
26% community, 22% student, and 22% mixed. Thus, at least 48% of the
identified samples were nonclinical and nonlegal. Most samples (83%)
consisted of female participants. Using a weighted means approach ( Shadish
& Haddock, 1994 ), Jumper meta-analyzed effect sizes ( r s) across samples
for depression, self-esteem, and symptomatology (i.e., psychological
difficulties other than depression and self-esteem problems). The overall
magnitude of the relation between CSA and symptomatology was of medium size,
r = .27. Community ( r = .29) and clinical samples ( r = .27) were similar
in magnitude, but student samples were substantially lower ( r = .09). For
self-esteem, community ( r = .34) and clinical samples ( r = .36) were also
similar, whereas student samples were much lower ( r = -.02). For
depression, the community samples ( r = .17) were closer to student ( r =
.09) than clinical samples ( r = .34). Jumper concluded that the student
samples were anomalous, possibly because symptoms had not yet manifested at
college age. The CSA-symptomatology relation was the same for men ( r = .29)
and women ( r = ..26); the CSA-self-esteem relation, however, was lower for
men ( r = -.02) than women ( r = .24). On the basis of the symptomatology
results, which were derived from nearly twice as many samples as the
self-esteem results, Jumper concluded that SA men and women do not differ in
terms of subsequent psychological adjustment.
Neumann et al. (1996) examined CSA-adjustment relations using 38 published
studies consisting exclusively of female participants, half of which were
based on nonclinical samples. These researchers computed an overall effect
size ( d ) for each study (i.e., a study-level effect size) and then
meta-analyzed them, obtaining a small to medium weighted mean effect size (
d = .37). Using Rosenthal's (1984) formula, and assuming a 19% CSA
prevalence rate for women in the general population based on Rind and
Tromovitch's (1997) estimate, we converted this d to an r . The obtained
result ( r = .14) was considerably smaller than Jumper's estimate of r =
.27. Neumann et al. also found that the magnitude of the effect sizes
differed between nonclinical ( d = .32) and clinical ( d = .50) samples.
Converting these values to r with the procedure described previously yielded
r = .12 and .19, respectively. Thus, whereas Jumper found that community and
clinical samples were similar in terms of mean effect sizes, Neumann et al.
found that nonclinical samples had a lower mean effect size than clinical
samples. This difference might be due to the fact that Neumann et al.'s
nonclinical samples included student samples (but see below). Finally,
Neumann et al. found virtually identical effect sizes for samples with a
mean age of 30 or below ( d = .39) and above 30 ( d = .40), casting doubt on
Jumper's speculation that her student results might be attributable to a
lack of time for symptoms to manifest.
Rind and Tromovitch (1997) examined CSA-outcome relations from 7 male and 7
female national probability samples from the United States, Canada, Great
Britain, and Spain. These results are especially important for estimating
population parameters because these samples were all chosen to be
representative of their national populations. Rind and Tromovitch
meta-analyzed mean effect sizes from each sample (i.e., sample-level effect
sizes) separately by gender and found that the magnitude of CSA-adjustment
relations was small for both men ( r = .07) and women ( r = .10). These mean
effect sizes were not statistically different. For self-reports of CSA
effects, significantly more women (68%) reported the presence of some type
of negative effect at some point after their CSA experience than did men
(42%); the size of this difference was small to medium ( r = .23).
Self-reports in Baker and Duncan's (1985) national study in Great Britain
suggested that lasting negative effects for SA persons are rare: 13% for
women and 4% for men. Several of the national studies also examined third
variables that might account for CSA-adjustment relations. In one study,
greater sexual activity in adulthood was confounded with CSA ( Laumann,
Gagnon, Michael, & Michaels, 1994 ). In two others ( Boney-McCoy &
Finkelhor, 1995 ; Finkelhor, Hotaling, Lewis, & Smith, 1989 ), most
CSA-adjustment relations remained statistically significant after
controlling for several possible confounds. However, nonsexual abuse and
neglect variables were not held constant in these analyses, weakening any
causal interpretations because CSA often occurs along with physical abuse or
emotional neglect ( Ney et al., 1994 ) and because CSA-adjustment relations
have been shown to disappear when these factors are held constant (e.g.,
Eckenrode, Laird, & Doris, 1993 ; Ney et al., 1994). Finally, Rind and
Tromovitch reviewed the results of another national study that found that SA
girls tended to have disruption in their family, school, and social
environments both before and after their CSA experience ( Ageton, 1988 ),
weakening causal interpretations regarding CSA effects in the general
population.
Synthesis of the Quantitative Reviews
Causality.
All three reviews expressed caution regarding causal inferences about
CSA-adjustment relations. Jumper (1995) noted that researchers need to
differentiate between effects related to CSA and those related to other
traumatic events, and to control for family variables. Neumann et al. (1996)
argued that third variables such as other forms of maltreatment may be
responsible for the CSA-adjustment relation, and that most studies in their
review did not consider the possible role of family dynamics. About 72% of
the studies in Jumper's review were also reviewed by Neumann et al.,
suggesting that most of Jumper's studies also did not consider the role of
family environment. Rind and Tromovitch (1997) found that the studies in
their review usually did not use statistical control, and when they did, it
was inadequate. Thus, a quantitative review of studies using statistical
control of important potential confounds (e.g., family environment) has yet
to be done and is needed to address the issue of causality.
Pervasiveness.
Only Rind and Tromovitch's (1997) review
[Page 26]
presented data relevant to how widespread negative outcomes are in the
population of persons with a history of CSA. Their findings suggest that
lasting negative effects are rare, but these results are based on only one
study ( Baker & Duncan, 1985 ). These considerations point to the need for
further attention to this issue.
Intensity.
The meta-analytic reviews were especially useful for assessing the intensity
of CSA correlates or effects, indicated by weighted mean effect sizes.
Neumann et al. (1996) and Rind and Tromovitch (1997) found that the
magnitude of the relation between CSA and adjustment in the general
population is small. In contrast, Jumper's (1995) meta-analysis of community
samples suggests that the magnitude of the CSA-adjustment relation in the
general population is medium in size and equivalent to that in the clinical
population. To investigate this discrepancy, we examined the community
samples used by Jumper. For symptomatology, Jumper reported the following
effect sizes: Bagley and Ramsay (1986) , r = .13; Mullen, Romans-Clarkson,
Walton, and Herbison (1988) , r = .16; Murphy et al. (1988) , r = .13;
Peters (1988) , r = ..30; Stein, Golding, Siegel, Burnam, and Sorenson
(1988) , r = .31 for the female sample and r = .37 for the male sample. We
calculated the effect sizes for these samples and obtained, respectively, r
s = .21, .16, .16, .14, .15, and .12. Because we obtained substantially
lower effect sizes in the last three samples, we asked an expert
meta-analyst to calculate these values independently; his calculations
confirmed ours.1 We meta-analyzed the recomputed effect sizes, obtaining a
small weighted mean effect size ( r = .15), which is consistent with the
results of the other two meta-analytic reviews.
We next examined the four community samples in Jumper's meta-analysis of
depression and the three in her meta-analysis of self-esteem. Although we
obtained similar effect sizes, two of the samples used in each meta-analysis
(from Hunter, 1991 ) were not valid community samples. Hunter recruited
participants through newspaper advertisements and community notices asking
for volunteers who were "sexually molested as children" (p. 207). The
recruitment method suggests a convenience sample rather than a community
sample; further, the notice wording was likely to attract volunteers who had
more negative experiences. Thus, the results of Jumper's meta-analyses of
depression and self-esteem for community samples have limited
generalizability.
In sum, the quantitative reviews indicate that in the entire population of
persons with a history of CSA, the magnitude of the CSA-adjustment relation
is small, implying that CSA does not typically have intensely negative
psychological effects or correlates. The results from the Neumann et al.
(1996) andRind and Tromovitch (1997) meta-analyses, as well as results from
the recomputed meta-analysis of Jumper's (1995) community samples, suggest
that the student population is not anomalous with respect to CSA-adjustment
relations. Instead, it appears that the clinical population is anomalous.
Gender equivalence.
Using the recomputed effect sizes for Jumper's (1995) community samples, we
recalculated the weighted mean effect sizes for male and female participants
for symptomatology and found r s = .11 and .22, respectively, compared with
reported values of r = .29 and r = .26, respectively. These revised results
suggest a sex difference. Rind and Tromovitch's (1997) meta-analysis did not
reveal a sex difference in CSA-adjustment relations (although the direction
of the mean effect sizes was consistent with greater problems for SA women),
although it did show a sex difference in self-reported effects. Each
meta-analysis was based on only a small number of male samples (Jumper used
four; Rind and Tromovitch used five for CSA-adjustment relations and three
for self-reported effects). Neumann et al. (1996) examined only female
samples. The mixed results regarding CSA-adjustment relations, along with
the small number of samples used, suggest the need for a more extensive
meta-analytic examination of sex differences.
Current Review
The shortcomings of both the qualitative and quantitative literature reviews
point to the need for further investigation of the nature of CSA effects or
correlates. Qualitative reviews present mixed conclusions regarding the
commonly assumed CSA properties of causality, pervasiveness, intensity, and
gender equivalence and are limited by sampling bias, subjectivity, and
imprecision. The meta-analytic reviews, after correcting for Jumper's (1995)
community sample effect sizes, show low intensity of CSA effects or
correlates (in terms of effect size). However, their contributions regarding
causality, pervasiveness, and gender equivalence are either absent or
wanting because of inadequate reports in the primary studies or the small
number of samples included in the analyses. The purpose of the current
review was to address these shortcomings and to achieve a more accurate and
precise understanding of CSA in the general population. To do so, we
meta-analytically examined the literature on CSA-outcome relations in
college samples.
College samples were used for several reasons. First, this population
provides the largest group of studies on nonclinical populations, which are
essential for understanding CSA in the general population. The college
population is useful for addressing questions regarding the general
population because about 50% of U.S. adults have some college exposure (
Fritz, Stoll, & Wagner, 1981 ; U.S. Bureau of the Census, 1995 ). Second,
studies using college samples provide the most extensive data on moderators
of CSA-adjustment relations. Many of these studies have examined confounding
variables such as family environment, making them useful for examining
causality as well as the magnitude of CSA-adjustment relations. Third, many
of these studies have reported a rich variety of other results useful for
addressing the issues of pervasiveness of effects and gender equivalence.
The CSA literature on college students includes numerous male samples,
allowing for a more thorough comparison of the genders than previously
reported. In addition, this literature has never been systematically
reviewed before, and many studies based on college samples have never
[Page 27]
been published but should be more widely known to counteract a possible
publication bias.
A possible shortcoming of focusing on the college population is that college
students may be too young for symptoms to have appeared, or they may be
better able to cope with CSA stresses than persons in other populations (
Jumper, 1995 ). However, younger and older adults did not differ in
CSA-adjustment relations in Neumann et al.'s (1996) meta-analysis.
Furthermore, mean effect sizes from college samples, as reported by Jumper,
were similar to those from national samples (Rind & Tromovitch, 1997 ),
nonclinical samples ( Neumann et al., 1996 ), and community samples (
Jumper, 1995 , after corrections). Therefore, the argument that college
students are better able to cope and thus present fewer adverse reactions
than people in other nonclinical populations lacks empirical support.
We addressed the assumed CSA properties of causality, pervasiveness,
intensity, and gender equivalence in several ways. First, we meta-analyzed
effect sizes for CSA-symptom relations to estimate the magnitude (i.e.,
intensity) of the relationship between CSA and adjustment in the college
population. Second, we performed semipartial correlation and contrast
analyses on the effect sizes to examine gender differences (i.e., gender
equivalence), as well as other moderator variables. Third, we meta-analyzed
results from self-reported reactions to and effects from CSA to examine
gender differences further. Additionally, we analyzed these self-reports to
examine the prevalence of negative effects. Fourth, we meta-analyzed
relations between CSA and family environment, as well as between symptoms
and family environment, to examine the causal role of CSA in producing
symptoms. We addressed the issue of causality more directly by examining the
results of statistical control from studies that reported this information.
Method
Sample of Studies
Studies were obtained by conducting computerized database searches of
PsycLIT from 1974 to 1995, Sociofile from 1974 to 1995, PsycInfo from 1967
to 1995, Dissertation Abstracts International up to 1995, and ERIC from 1966
to 1995. Key terms entered for these databases were adjustment or effect or
effects, college or undergraduate or undergraduates, and sex abuse or sexual
abuse or child and adult and sexual. Studies that we already knew were also
included. Reference lists of all obtained studies were read to locate
additional studies.
To be included, studies must either have used samples exclusively of college
students, or, if noncollege subjects were also included, then results of
measures of college students had to be reported separately. For inclusion in
analyses of psychological correlates of CSA, studies had to (a) include a
control group that contained no students with CSA experiences; (b) use a
distinct CSA group, rather than a general "abused" group that could include
participants without a history of CSA; (c) report on at least one of the 18
symptoms described below; and (d) provide sufficient data to compute one or
more effect sizes. Studies not including reports of psychological correlates
were included if they contained data on reactions to CSA, either
retrospectively recalled or current reflections; these data had to be
classifiable into mutually exclusive negative, neutral, or positive
categories. Studies were also included if they contained data on
self-reported effects of CSA.
As in other meta-analyses (e.g., Jumper, 1995 ; Oliver & Hyde, 1993 ), a
single study could report data for more than one sample. Fromuth and
Burkhart (1989) examined two male student samples-one from the Midwest and
another from the Southeast-and reported separate statistics for these two
samples. These samples were thus treated as distinct. Further, male and
female samples within a single study were treated as distinct when results
were reported separately for them (cf. Rind & Tromovitch, 1997 ); this was
done to examine gender differences. Many studies reported more than one
result, using different measures, for the same psychological correlate
(e.g., a depression result from the Beck Depression Inventory and another
from the Symptom Checklist). In these cases, effect sizes ( r s) were
computed for each result and were then averaged using Fisher Z
transformations to obtain a single mean effect size. This practice has been
used in other meta-analyses (e.g., Erel & Burman, 1995 ) and has been
recommended by Rosenthal (1984) . The mean effect size thus computed for a
given sample for a particular psychological correlate constituted a
"symptom-level" effect size. Finally, numerous studies reported results for
more than one type of psychological correlate from a single sample (e.g.,
anxiety and depression). As in other meta-analyses (e.g., Neumann et al.,
1996 ), we treated multiple different correlates in two ways. First, we
computed for each sample with multiple different psychological correlates a
"sample-level" effect size by averaging the symptom-level effect sizes from
that sample using Fisher Z transformations. We later conducted a
meta-analysis on these sample-level effect sizes. Second, we analyzed
different psychological correlates (i.e., symptoms) separately in a series
of symptom-level meta-analyses.
Applying the above criteria produced 59 usable studies (see the Appendix ),
consisting of 36 published studies, 21 unpublished dissertations, and 2
unpublished master's theses. These studies yielded 70 independent samples
for estimating prevalence rates, 54 independent samples for computing 54
sample-level and 214 symptom-level effect sizes, 21 independent samples that
provided retrospectively recalled reaction data, 10 independent samples that
provided data on current reflections, and 11 independent samples that
provided data on self-reported effects. Prevalence rates were based on
35,703 participants (13,704 men and 21,999 women). Effect size data for
psychological correlates were based on 15,824 participants (3,254 men from
18 samples and 12,570 women from 40 samples)-actual numbers of participants
are somewhat higher than these because one study, not included in the above
totals ( Haugaard & Emery, 1989 ), failed to provide exact sample sizes for
men and women. Reaction and self-reported effects data were based on 3,136
participants (783 men from 13 samples and 2,353 women from 14
samples)-actual numbers of participants are somewhat higher because one
study, not included in the above totals ( Schultz & Jones, 1983 ), failed to
report exact sample sizes for men and women.
Coding the Studies
For each study, the following information was coded:
(a) all statistics, if provided, on psychological correlates of CSA,
including means, standard deviations, t tests, F ratios, correlations, chi
squares, degrees of freedom, and sample sizes;
(b) types of psychological correlates reported;
(c) all statistics regarding relations between moderator variables (e.g.,
force, penetration, frequency of CSA) and psychological correlates;
(d) sex of participants;
(e) definition of CSA, including ages that defined a "child" and an older
person, whether peer experiences were included, whether CSA experiences were
limited to contact sex or also included noncontact sexual experiences, and
whether CSA experiences were limited to unwanted sex or also included
willing sexual experiences;
(f) all reaction data, if provided, including both retrospectively recalled
reactions to and current reflections on the CSA experiences;
(g) all self-reported effects data, if provided, including responses to how
these experiences affected participants overall and how they affected their
sex lives;
(h) types of family environment measures used; and
(i) all statistics on family environment measures, including their
[Page 28]
relations with CSA and with psychological correlates.
Together, the three basic sets of statistics (differences between CSA and
control participants in adjustment, differences between CSA and control
participants in family environment, and the relationship between family
environment and adjustment) were used to address the question of whether
significant relationships between CSA and adjustment were spurious,
attributable to the confounding variable of family environment. Finally, the
results of all analyses using statistical control were coded (e.g.,
examining the relationship between CSA and adjustment, holding family
environment factors constant). These data were used to directly examine
whether any significant relations between CSA and psychological adjustment
were spurious.
Psychological Correlates of CSA
Coding of the studies resulted in 18 categories of psychological correlates
of CSA; several additional correlates were infrequently reported and were
therefore not considered in the meta-analyses. These 18 correlates, along
with the measures used to assess them in the various studies, were as
follows:
1. Alcohol problems-based on the Michigan Alcoholism Screening Test
(MAST; Brady, Foulks, Childress, & Pertschuk, 1982 ), the alcohol
subscale of the Millon Clinical Multiaxial Inventory (MCMI; Millon,
1982 ), and investigator-authored items.
2. Anxiety-based on the Anxiety subscale of the Symptom Checklist
(SCL-90-R; Derogatis, Lipman, & Covi, 1973 ), the Hopkins Symptom
Checklist (HSCL; Derogatis, Lipman, Rickels, Ulenhuth, & Covi, 1974 ),
the Brief Symptom Inventory (BSI; Derogatis & Spencer, 1982 ), the
Trauma Symptom Checklist (TSC-33 and TSC-40; Briere & Runtz, 1989 ),
the MMPI form R ( Hathaway & McKinley, 1967 ), the MCMI, the Institute
of Personality and Ability Testing Anxiety Scale Questionnaire (IPAT;
Krug, Scheier, & Cattell, 1976 ), the State-Trait Anxiety Inventory
(STAI; Spielberger, Gorsuch, & Lushene, 1970 ), and
investigator-authored items.
3. Depression-based on the Depression subscales of the SCL-90-R, the
HSCL, the BSI, the TSC-33 and 40, the MMPI form R, the Hugo Short Form
of the MMPI (HSF; Hugo, 1971 ), and the MCMI; depression-related items
from the Clinical Analysis Questionnaire (CAQ; Cattell, 1973 ); the
Beck Depression Inventory (BDI; Beck, Ward, Mendelson, Mock, & Erbaugh,
1961 ); and investigator-authored items.
4. Dissociation-based on the Dissociative Experiences Scale (DES;
Bernstein & Putnam, 1986 ), Briere's Dissociation Scale ( Briere &
Runtz, 1988b ), and the dissociation subscale from the TSC-33 and 40.
This symptom indicates experiences such as depersonalization, memory
loss, and not feeling like oneself.
5. Eating disorders-based on the Bulimia Test (BULIT; Smith & Thelen,
1984 ), the Bulimia Diagnostic Instrument ( Nevo, 1985 ), the Eating
Attitudes Test (EAT-26; Garner, Olmsted, Bohr, & Garfinkel, 1982 ), the
Eating Disorder Inventory (EDI; Garner, Olmsted, & Polivy, 1983 ), and
investigator-authored items.
6. Hostility-based on the Hostility subscale of the SCL-90-R and the
BSI. This symptom reflects thoughts, feelings, or actions that are
characteristic of anger.
7. Interpersonal sensitivity-based on the Interpersonal Sensitivity
subscale of the SCL-90-R, HSCL, and BSI. This symptom reflects feelings
of uneasiness and marked discomfort when interacting with others, as
well as feelings of personal inadequacy and inferiority, especially
compared with others.
8. Locus of control-based on the Locus of Control (LOC) scales by
Nowicki and Duke (1974) , Coleman et al. (1966) , and Rotter (1966) .
This scale measures the extent to which one feels in control of one's
life.
9. Obsessive-compulsive symptomatology-based on the
Obsessive-Compulsive subscales of the SCL-90-R, HSCL, and BSI. This
symptom is concerned with unremitting and irresistible thoughts,
impulses, and actions that are ego alien or unwanted.
10. Paranoia-based on the Paranoia subscales of the SCL-90-R, HSCL,
BSI, MCMI, MMPI form R, HSF, and CAQ. This symptom reflects a
disordered mode of thinking, consisting of thoughts involving, for
example, projection, hostility, suspiciousness, grandiosity, and
delusions.
11. Phobia-based on the Phobic Anxiety subscales of the SCL-90-R and
BSI. This symptom reflects a persistent fear response of an irrational
and disproportionate nature to a specific person, place, object, or
situation.
12. Psychotic symptoms-based on the Psychoticism subscales of the BSI,
SCL-90-R, MCMI, MMPI (form R and HSF, Sc scale), CAQ, and Tennessee
Self-Concept Scale (TSCS; Fitts, 1964 ). For these measures, high
scores indicate attributes such as mental confusion and delusions
(i.e., first-rank symptoms of schizophrenia such as hallucinations and
thought-broadcasting).
13. Self-esteem-based on the TSCS, Rosenberg Self-Esteem Scale (
Rosenberg, 1965 ), Self-Ideal Discrepancy subscale of the Family
Perception Grid ( Kelly, 1955 ), the Self subscales of the McPearl
Belief Scale ( McCann & Pearlman, 1990 ), subscales from the Erwin
Identity Scale ( Erwin & Delworth, 1980 ), and the Coopersmith
Self-Esteem Inventory ( Coopersmith, 1967 ).
14. Sexual adjustment-based on Finkelhor's Sexual Self-Esteem Scale (
Finkelhor, 1981 ), Reed's (1988) Romantic and Sexual Self-Esteem
Survey, the Derogatis Sexual Functioning Inventory (DSFI; Derogatis &
Melisaratos, 1979 ), the Psychosexual Functioning Questionnaire (
Schover, Friedman, Weiler, Heinman, & LoPiccolo, 1982 ), the Sexual
Arousability Inventory ( Hoon, Hoon, & Wincze, 1976 ), subscales from
the TSC-33 and 40 and the Erwin Identity Scale, and
investigator-authored items.
15. Social adjustment-based on the Social Support Questionnaire (
Sarason, Levine, Basham, & Sarason, 1983 ); the Interpersonal
Relationship Scale ( Schlein, Guerney, & Stover, 1971 ); the Inventory
of Interpersonal Problems ( Horowitz, Rosenberg, Baer, & Ureno, 1988 );
the Texas Social and Behavioral Inventory ( Helmreich & Stapp, 1974 );
the Social Adjustment Scale (SAS; Weissman & Bothwell, 1976 ); Rathus'
Assertiveness Schedule ( Rathus, 1973 ); Rotter's Interpersonal Trust
Scale ( Rotter, 1967 ); the Intimacy Attitude Scale ( Treadwell, 1981
); the Intimacy Behavior Scale ( Treadwell, 1981 ); subscales from the
TSCS, McPearl Belief Scale, the College Self-Expression Scale (
Galassi, DeLo, Galassi, & Bastien, 1974 ), the Student Development Task
and Lifestyle Inventory ( Winston, Miller, & Prince, 1987 ), and the
Miller Social Intimacy Scale (MSIS; Miller & Lefcourt, 1982 ); and
investigator-authored items.
16. Somatization-based on MacMillan's Health Opinion Survey (
MacMillan, 1957 ); subscales from the HSCL, TSC-33 and 40, BSI,
SCL-90-R, MCMI, MMPI form R, HSF, and CAQ; and investigator-authored
questions. This symptom reflects bodily related distress such as
headaches and pain; it also includes gastrointestinal, respiratory, and
cardiovascular complaints and complaints of sleeping problems.
17. Suicidal ideation and behavior-based on the Reasons for Living
Inventory ( Linehan, Goodstein, Nielsen, & Chiles, 1983 ), the Suicide
Behaviors Questionnaire ( Linehan & Nielsen, 1981 ), and
investigator-authored items.
18. Wide adjustment-based on the General Well-Being Schedule ( McDowell
& Newell, 1987 ); total or global scores from the HSCL, TSC-33 and 40,
SCL-90-R, and BSI; subscales of the Comrey Personality Scales ( Comrey,
1970 ) and the TSCS; investigator-created variables derived from
combining scales of standard measures; and investigator-authored items.
This factor is a general measure of psychological adjustment or
symptomatology and, when derived by combining items or measures, is
analogous to Jumper's (1995) "psychological symptomatology" and Neumann
et al.'s (1996) "general symptomatology."
[Page 29]
Statistical Analyses
The effect size used in this review was r , the Pearson correlation
coefficient. For CSA-psychological adjustment relations, positive r s
indicated poorer adjustment for CSA participants compared to control
participants. For CSA-family environment relations, positive r s indicated
poorer family functioning for CSA subjects. For family
environment-adjustment relations, positive r s indicated that poorer family
functioning was associated with poorer adjustment. Pearson r s were also
computed to assess the magnitude of the relation between various moderating
variables (e.g., force) and outcome measures (i.e., psychological adjustment
and self-reported reactions). Positive r s indicated that higher levels of
moderators were associated with higher levels of symptoms or more negative
reactions to the CSA. Finally, Pearson r s were computed to assess the size
of the differences in reactions and self-reported effects between men and
women who had CSA experiences. In this case, positive r s indicated that men
reported fewer negative reactions or effects than women, or conversely, that
they reported more positive reactions or effects than women.
Formulas for calculating r were taken from Rosenthal (1984, 1995) . A number
of studies reported results separately for different types of CSA
participants (e.g., Collings, 1995 ; Roland, Zelhart, & Dubes, 1989 ; Sedney
& Brooks, 1984 ). To make the effect sizes in these cases comparable to
those in the majority of studies that compared participants with all types
of CSA experiences with controls, we combined all CSA subgroups in a given
study into a single CSA group and then compared this group with its control
group (cf. Neumann et al., 1996 ). 2
Sample-level and symptom-level effect sizes across studies were compared and
combined meta-analytically using formulas taken from Rosenthal (1984) and
Shadish and Haddock (1994) . Combining effect sizes involved transforming r
s into Fisher Z s and then weighting the Fisher Z s by the degrees of
freedom ( df = N - 3) associated with their samples. The mean weighted
Fisher Z was transformed back to a mean weighted effect size, referred to as
the unbiased effect size estimate (r u). This metric was used to estimate
the effect size in the population and is considered to be unbiased because
it weighs more heavily larger samples whose effect sizes are generally
considered to be more precise population estimates ( Rosenthal, 1984 ;
Shadish & Haddock, 1994 ). Statistical significance of the effect size
estimates was determined by computing their 95% confidence intervals; an
interval not including zero indicated an effect size estimate was
significant ( Shadish & Haddock, 1994 ).
To establish interrater reliability for coding, Bruce Rind and Philip
Tromovitch independently coded studies for psychological correlates,
reactions, self-reported effects, family environment-CSA relations, family
environment-adjustment relations, and results of statistical control.
Interjudge agreement for these codings ranged from 85% to 100%; all
disagreements were resolved by discussion.
Results
Definitions of CSA, Prevalence Rates, and Types of CSA
Definitions.
Definitions of CSA varied from one study to the next (see the Appendix ).
Most studies (70%) defined sexual experiences to be CSA if a sizable age
discrepancy existed between the child or adolescent and other person,
regardless of the younger person's willingness to participate; 20% of the
studies restricted their definition of CSA to unwanted sexual experiences
only. Most studies (73%) defined CSA to include both contact and noncontact
(e.g., exhibitionism) sexual experiences; 24% restricted their definition to
contact experiences only.
Most studies (88%) reported specific upper age limits for children or
adolescents in defining CSA. Of these studies, most (75%) focused on middle
to later adolescence with the oldest includable age for "child" usually
being 16 (35%) or 17 (25%); a minority of these studies (25%) included only
experiences that occurred when participants were younger than 14 or were
prepubescent. Regarding age discrepancy, more than half of the studies (59%)
defined sexual experiences with someone at least 5 years older to be CSA.
This criterion generally applied to experiences that occurred when
participants were less than 12 or 13. About a quarter of the studies (27%)
also defined adolescent sexual experiences with someone at least 10 years
older to be CSA. Others (17%) specified experiences with an adult, an
authority figure, someone over 16, or someone older to be CSA. About a third
of the studies (32%) also included in their definition peer experiences that
were unwanted or forced. Fourteen percent of the studies defined sexual
experiences with relatives as CSA, although this criterion generally
included an age discrepancy.
Prevalence rates.
For male participants, 26 samples provided data usable for estimating the
prevalence rate of CSA. Of the 13,704 male participants in these samples,
14% reported sexual experiences classifiable as CSA under the various
definitions. The unweighted mean prevalence was 17% ( SD = 10%), with a
range from 3% to 37%. For female participants, 45 samples provided data that
were usable for estimating the prevalence rate. Of the 21,999 women in these
samples, 27% reported sexual experiences classifiable as CSA. The unweighted
mean prevalence was 28% ( SD = 16%), with a range from 8% to 71% (see the
Appendix for listing of sample-level prevalence rates).
Types of CSA.
Twenty one (35.6%) of the 59 studies contained a breakdown of the types of
CSA that occurred along with their frequencies. Types listed varied from
study to study, including acts such as an invitation to do something sexual,
exhibitionism, fondling, masturbation, oral sex, attempted intercourse, and
completed intercourse. Many authors referred to this increasing level of
sexual intimacy as "severity" or "seriousness." Using the reported
prevalence rates of the various types of CSA from these studies, we
estimated the distribution of four basic types of CSA in the college
population: exhibitionism, fondling, oral sex, and intercourse. For
exhibitionism, we included reports of being shown or showing sex organs in a
sexual context. Researchers assessed exhibitionism by asking participants if
someone had shown, exhibited, or exposed to them his or her sex organs, or
if they had shown, exhibited, or
[Page 30]
exposed their sex organs to the other person at the other person's request.
For fondling, we included reports of sexual touching and masturbation.
Researchers assessed fondling usually by asking participants if they had
experienced fondling or genital touching; occasionally they included
nongenital touching as examples of fondling. For intercourse we included
both attempted and completed instances. Estimates were based on weighting
prevalence rates by sample size across samples. Some studies reported
prevalence rates for two combined types (e.g., exhibitionism and fondling)
rather than reporting their rates separately. In these cases, we divided the
rates evenly between the two types. Because a number of studies categorized
SA participants exclusively into the most "severe" type of CSA experienced,
the prevalence of less severe types is likely to be underestimated.
The top half of Table 1 shows the estimated prevalence rates in the college
population for the different types of CSA for SA women and men separately
and combined. To provide a frame of reference for these results, we
estimated corresponding prevalence rates for SA persons in the general
population based on reports from 3 national samples ( Baker & Duncan, 1985 ;
Laumann et al., 1994 ; López, Carpintero, Hernández, & Fuertes, 1995 ). Data
in these studies were obtained in face-to-face interviews of respondents
selected to be representative of their nations (Britain, United States, and
Spain, respectively). The strength of face-to-face interviews in obtaining
valid data along with the high response rates of these studies (unweighted
mean = 83%) suggest that their prevalence rates serve as good population
estimates. As with studies based on college samples, these studies used
varying definitions of CSA (e.g., contact only vs. both noncontact and
contact sex) and of types of CSA such as intercourse (i.e., completed only
vs. both attempted and completed). The bottom half of Table 1 displays the
estimated prevalence rates for the different types of CSA for SA persons in
the general population. Comparing the college and national distributions
indicates similar prevalence rates for intercourse for women; SA college
men, however, show a higher rate (33%) than SA men in the general population
(13%). Because intercourse is frequently viewed as the most severe or
serious type of CSA, these results imply that SA college students,
especially men, do not experience less severe CSA than SA persons in the
general population.
Table 1
Prevalence Rate Estimates of Four Types of CSA in College and National
Populations
Sample/Gender k N Exhibitionism Fondling Oral Sex Intercourse (a)
College
female 13 2172 32% 39% 3% 13%
male 9 506 22% 51% 14% 33%
combined (b) 26 2918 28% 42% 6% 17%
National (c)
female 3 590 38% 67% 9% 16%
male 3 366 25% 69% 22% 13%
combined 6 956 33% 68% 14% 15%
Note. k is the number of samples and N is the number of SA
respondents in these samples that prevalence rate estimates of
types of CSA are based on. Prevalence rate estimates are weighted
means of prevalences from individual samples. College estimates
come from studies included in the current review; national
estimates come from 3 studies of national samples (Baker & Duncan,
1985; Laumann et al., 1994; Lopéz et al., 1995)
(a) In some college and national studies, intercourse included
both attempted and completed acts
(b) Combined values were based on two additional studies (with a
male and female sample in each) that reported only combined
results
(c) For exhibitionism, only data from Lopéz et al. were reported
(female: k=1, N=203; male k=1, N=134; combined k=2, N=337); for
oral sex, only data from Laumann et al. and Lopéz et al. were
reported (female: k=2, N=476; male: k=2, N=291; combined k=4,
N=767).
[[Page 31]
Severity or seriousness of CSA is often not only viewed as a function of the
level of intimacy of the sexual act but also as a function of the closeness
of the relationship between the SA person and his or her partner or abuser
(e.g., Edwards & Alexander, 1992 ; Laumann et al., 1994 ). On the basis of
the studies providing relationship information, we estimated the proportion
of the college population that has experienced close family CSA (biological
or stepparents, grandparents, older siblings) and the proportion that has
experienced wider family CSA (including both close family CSA and CSA with
other relatives). Estimates were performed for SA women and men separately
and combined (see Table 2 ). Results indicate that only a small proportion
of SA college students experience close family CSA (16% for women and men
combined), with women experiencing it two and a half times as much (20%) as
men (8%).
Table 2
Prevalence Rate Estimates of Relationship Between CSA Respondents
and Partners/Abusers in College and National Populations
Wider Family CSA Close Family CSA
College (a) National (b) College (c) National (b)
Gender N % N % N % N %
female 2735 37 606 34 792 20 606 15
male 580 23 375 13 270 8 375 4
combined 3569 35 981 26 1275 16 981 11
Note. Close family CSA includes sexual relations with very close
relatives (e.g., biological or step parents, grandparents, older
siblings). Wider family CSA includes both close family CSA and
relations with other relatives. Prevalence rate estimates are
weighted means of prevalences from individual samples. College
estimates come from studies included in the current revies;
national estimates come from 3 studies of national samples (Baker
& Duncan, 1985; Laumann et al., 1994; Lopéz et al., 1995)
a Based on 21, 9, and 33 samples for females, males, and combined,
respectively
b Based on 3, 3, and 6 samples for females, males, and combined,
respectively
c Based on 10, 6, and 19 samples for females, males, and combiend,
respectively.
To provide a frame of reference, we estimated prevalence rates for SA
persons in the general population based on reports from the three national
samples used previously to estimate prevalence rates for different types of
CSA. As is shown in Table 2 , estimated prevalence rates for close and wider
family CSA are similar in the college and general populations. It is
important to note that estimates from the college samples do not
underestimate the occurrence of close or wider family CSA relative to
estimates based on national samples. This result further implies that SA
college students as a group do not experience less severe CSA than SA
persons in the general population.
Another commonly used indicator of severity of CSA is its frequency of
occurrence (i.e., multiple occurrences are viewed as more severe than a
single episode). We estimated the proportion of college students with a
history of CSA who experienced more than one CSA episode using all 11
studies that provided this information. We then compared these results with
national population estimates based on the same three studies of national
samples used above. In the college samples, based on 11 studies with 1,195
SA participants, the weighted mean percentage that had more than one CSA
experience was 46%; for the three national studies, based on 990 SA
respondents, the weighted mean percentage was 52%. The unweighted mean
percentages were identical in the two groups: 49% ( SD = 11%) for the
college samples and 49% ( SD = 15%) for the national samples. These results
further indicate similarity in CSA severity in the college and general
populations.
Finally, force or threat of force is commonly used as an indicator of CSA
severity. We estimated the proportion of SA college students whose CSA
involved force or threat of force based on the 10 studies (with six male and
six female samples) that provided this information. For 355 SA men in these
samples, the weighted mean percentage that experienced some degree of force
or threat was 23%. For 753 SA women, the weighted mean percentage
experiencing some degree of force or threat was nearly twice as much (41%).
Unweighted mean percentages across samples were 22% ( SD = 21%) for men and
42% ( SD = 26%) for women. The rather large standard deviations for the
unweighted estimates suggest that these estimates should be viewed
cautiously. An additional study reported that 31% of their SA students,
males and females combined, experienced some degree of force or threat of
force-a percentage intermediate to, and thus consistent with, the male and
female estimates just presented. National population estimates were not
possible in the case of force or threat of force, because none of the three
studies used above provided relevant data.
Magnitude of the Relationship Between CSA and Psychological Adjustment
Sample-level analysis.
To examine the intensity of CSA psychological effects or correlates, we
first meta-analyzed the sample-level effect sizes from the 54 samples for
which these could be computed (sample-level effect sizes are listed in the
Appendix ). 3 The resulting unbiased effect size estimate, based on 15,912
participants, was r u= .09, with a 95% confidence interval from .08 to .11.
Because this interval did not include zero, the obtained result was
statistically significant (i.e., SA students were less well adjusted than
controls). This difference in adjustment between SA and control students was
small, however, according to Cohen's (1988) guidelines; in terms of variance
accounted for, CSA accounted for less than 1% of the adjustment variance.
A chi-square test of the homogeneity of the sample-level effect sizes
revealed that they were not homogeneous, chi 2 (53) = 78, p < .01. In an
attempt to achieve homogeneity, we examined the distribution of sample-level
effect sizes to determine whether outliers existed. We defined outliers to
be effect sizes that were at least 1.96 standard deviations away from the
unweighted mean effect size (i.e., falling in the extreme 5% of the
distribution). Three outliers were found ( r = .36 in Jackson et al., 1990 ;
r = .40 in Roland et al., 1989 ; r = -.25 in Silliman, 1993 ) with z scores
of 2.71, 3.16, and -3.60, respectively. The Jackson et al. study included
only incest cases in the CSA group, and the Roland et al. study included a
large proportion of incest cases. Moreover, Neumann et al. (1996) also found
the Roland et al. result to be an outlier. Measures used in these studies
from which effect sizes were computed included: the SAS, BDI, RSE, and DSFI
( Jackson et al., 1990 ); the MMPI form R ( Roland et al., 1989 ); and the
LOC and TSCS ( Silliman, 1993 ). These measures were all used in other
studies whose effect sizes were not outliers, implying that the outlying
results were not a function of these measures. Removing these outliers
resulted in homogeneity, chi 2 (50) = 49.19, p > .50, based on k = 51
samples, with N = 15,635 subjects. The recalculated unbiased effect size
estimate (r u= .09) and the 95% confidence interval (.08 to .11) were
unchanged after rounding. The obtained small unbiased effect size estimate
implies that, in the college population, the magnitude of the relationship
between CSA and adjustment is small, which contradicts the assumption that
CSA is associated with intense harm in the typical case.
Symptom-level analysis.
Next we examined the magnitude of the relationship between CSA and
adjustment at the symptom level. Table 3 presents the results of the 18
symptom-level meta-analyses. The table shows for each meta-analysis the
number of independent samples ( k ), the total number of participants in
these samples ( N ), the unbiased effect size estimate (r u), the 95%
confidence interval of r u, and the homogeneity statistic ( H ) based on
the chi-square test.
Initial meta-analyses yielded 8 homogeneous and 10 heterogeneous results. In
an attempt to achieve homogeneity with heterogeneous sets, we examined the
distribution of effect sizes within each of these sets to detect outliers,
as defined previously. We removed all such deviant effect sizes and then
recomputed the meta-analyses. If homogeneity was achieved in a particular
set, then the search for outliers stopped for that set. Otherwise, the
[Page 32]
reduced set of effect sizes was examined for new outliers, and, if found,
the outliers were removed and the meta-analysis was performed again. If the
set of effect sizes was still heterogeneous and no additional outliers were
found, the set was considered to be heterogeneous. This procedure resulted
in achieving homogeneity in 7 of the 10 initially heterogeneous sets,
yielding 15 out of 18 homogeneous sets. Effect sizes remained heterogeneous
only for hostility, self-esteem, and sexual adjustment. Of the 9 effect
sizes removed in the 7 sets that became homogeneous, the majority came from
two of the studies that contributed to the heterogeneity of effect sizes in
the sample-level meta-analysis-5 from Roland et al. (1989) and 1 from
Jackson et al. (1990) . These six effect sizes and one additional effect
size from Bendixen et al.'s (1994) female sample were removed from the upper
end of their distributions. Two effect sizes were removed from the lower end
of their distribution ( Fishman, 1991 ; Fromuth & Burkhart, 1989 , Southwest
sample). Measures on which removed effect sizes were based in Jackson et
al.'s and Roland et al.'s studies were listed previously in the sample-level
meta-analysis section; Bendixen et al. and Fishman used
investigator-authored items, whereas Fromuth and Burkhart used the SCL-90-R.
Many studies with nonoutlying effect sizes used investigator-authored items
and the SCL-90-R, implying that the outlying results were not a function of
the measures used.
In Table 3 , the original numbers (i.e., number of samples, number of
participants in these samples, unbiased effect size estimate, and
homogeneity statistic) associated with the heterogeneous results for the
seven sets that became homogeneous are shown in parentheses, whereas the
numbers associated with the reduced homogeneous sets appear directly under
the column headings. Removing outliers showed itself to be productive in
achieving homogeneity; further, this procedure had little effect on effect
size estimates, indicating that the large majority of effect size estimates
can be considered to be reliable estimates of true effect sizes in the
college population. The unbiased effect size estimates for all 18 symptoms
were small according to Cohen's (1988) guidelines. The effect size estimates
ranged from r u= .04 to .13. Despite these small values, all effect size
estimates, except for one (locus of control), were statistically
significantly greater than zero, as is indicated by their 95% confidence
intervals. These findings indicate that, for all symptoms but one, CSA
participants as a group were slightly less well adjusted than control
participants. The small magnitude of all effect size estimates implies that
CSA effects or correlates in the college population are not intense for any
of the 18 meta-analyzed symptoms.
Table 3
Meta-Analysis of 18 Symptoms Associated With Child Sexual Abuse From College
Samples
95% confidence
Symptom k N ru interval for H
ru
Alcohol 8 1,645 .07 .02 to .12 2.97
Anxiety 16 (18) 6,870 .13 .10 to .15 4.62
(7,365) (.13) (28.72*)
Depression 22 (23) 7,778 .12 .10n to .14 25.71
(7,949) (.13) (49.72*)
Dissociation 8 1,342 .09 .04 to .15 1.86
Eating disorders 10 2,998 .06 .02 to .10 9.92
Hostility2 5 1,497 .11 .06 to .16 11.22*
Interpersonal
sensivity 7 1,934 .10 .06 to .15 11.78
Locus of control 6 1,354 .04 -.02 to .09 1.65
Obsessive-compulsive 7 1,934 .10 .06 to .15 5.01
Paranoia 9 (10) 1,881 .11 .07 to .16 10.34
(2,052) (.13) (20.07*)
Phobia 5 1,497 .12 .07 to .17 8.08
Psychotic symptoms 10 (11) 2,009 .11 .06 to .15 10.13
(2,180) (.13) (23.84*)
Self-esteem2 16 3,630 .04 .01 to .07 51.31*
Sexual adjustment2 20 7,723 .09 .07 to .11 39.49*
Social adjustment 15 (17) 3,782 .07 .04 to .10 20.37
(4,332) (.09) (40.62*)
Somatization 18 (19) 4,205 .09 .06 to .12 15.20
(4,376) (.10) (33.21*)
Suicide 9 5,425 .09 .06 to .12 10.94
Wide adjustment 14 (15) 3,620 .12 .08 to .15 18.77
(3,768) (.11) (24.25*)
Note
k represents the number of effect sizes (samples);
N is the total number of participants in the k samples;
ru is the unbiased effect size estimate (positive values indicate
better adjustment for control subjects);
H is the within-group homogeneity statistic (chi square based on
df = k - 1).
Cutting or trimming outliers was performed when effect sizes were
heterogeneous in an attempt to reach homogeneity. Original
numbers, before cuttinng ore trimming, are shown in parentheses.
95% confidence intervals are based on final (cut or trimmed)
distributions.
2 Cutting or trimming outliers failed to produce homogeneity;
thus, only original numbers are shown.
* p < .05 in chi-square test.
Moderator Analyses
Semipartial correlational analysis.
To examine whether the variability in sample-level effect sizes could be
accounted for by moderator variables, we performed multiple regression
analyses. We focused on the sample-level rather than symptom-level effect
sizes because of the substantially larger sample-level data set, which is
more appropriate for multiple regression analysis. As in other meta-analyses
(e.g., Oliver & Hyde, 1993 ), we performed multiple regression specifically
to obtain correlations between each moderator and the effect sizes while
controlling for other
[Page 33]
moderators, because of the possibility that the moderators were confounded.
We focused on semipartial correlations. This moderator analysis was based on
a weighted multiple regression procedure, using a weight of N - 3 for each
sample, which represents the reciprocal of the variance for an effect size r
, thereby producing the best linear unbiased estimate (cf. Hedges, 1994 );
this approach is consistent with the use of unbiased effect size estimates.
The sample-level effect sizes were regressed on the three variables that
were coded for each sample: level of contact (0 = both noncontact and
contact sex, 1 = contact sex only ), level of consent (0 = willing and
unwanted sex, 1 = unwanted sex only ), and gender (0 = male, 1 = female ).
Examining the relationship of gender with the effect sizes was done to
address the issue of gender equivalence. As discussed previously, it is
widely believed that contact sex is more severe or serious than noncontact
sex; therefore, it was of interest to test whether this factor would account
for variability in effect sizes. Finally, it was expected that unwanted sex
would be associated with larger effect sizes; hence, level of consent was
examined as a moderator. Results from this analysis regarding level of
consent and level of contact are likely to be conservative (i.e., their
relationship with the effect sizes may be underestimated) because the first
level of each variable overlaps with the second level (e.g., willing and
unwanted sex overlaps with unwanted sex only). Also entered into the
regression equation were two two-way interactions: Contact × Gender and
Consent × Gender. The Contact × Consent and Contact × Consent × Gender
interactions were not included because no male samples consisted exclusively
of cases of unwanted contact sex and only one female sample consisted
exclusively of unwanted contact sex. Finally, because outliers can skew
correlational results, we excluded from the multiple regression analysis the
three outliers identified previously in the sample-level meta-analysis. Four
studies containing both men and women were also excluded, because they did
not report results separately for the two genders.
The regression model was marginally significant, F (5, 41) = 2.09, p = .09.
Significance tests of predictors were based on adjusting their standard
errors to obtain a correct model for multiple regression involving effect
sizes (see Hedges, 1994 ). Three predictors were significantly related at
the .05 level to the effect sizes: consent, gender, and the Consent × Gender
interaction. The other two predictors, contact and Contact × Gender, were
not related. The semipartial correlations between these latter two
predictors and the effect sizes were, respectively, sr (41) = .15 and -.13
(two-tailed p s > .30). A second regression model was run, eliminating the
two nonsignificant predictors in the previous model. This new model was
statistically significant, F (3, 43) = 3.18, p = .03; all three predictors
were significantly related to the effect sizes at the .05 level. The
semipartial correlations between the effect sizes and the predictors of
consent, gender, and Consent × Gender were, respectively, sr (43) = .33,
.38, and -.36 (all two-tailed p s < .05). These results indicate that
unwanted sex and being female were each associated with poorer adjustment.
These results have to be qualified, however, because of the significant
Consent × Gender interaction.
Contrast analyses.
To investigate the Consent × Gender interaction, effect sizes for each of
the different levels of consent and gender were meta-analyzed separately,
and then contrast analyses were performed comparing the unbiased effect size
estimates between the different levels of each moderator. Next, effect sizes
within each of the four Consent × Gender combinations were meta-analyzed
separately, and then contrast analyses between unbiased effect size
estimates in appropriate combinations were performed. This procedure follows
the model of a main effects and then simple effects analysis in an analysis
of variance (ANOVA). The contrast analyses were based on the formula
presented by Rosenthal (1984) and used weighted Fisher Z transformations of
the effect sizes. Within each of the two sets of Fisher Z s being compared
in a given contrast analysis, the weight of a Fisher Z was its degrees of
freedom (i.e., N - 3) divided by the sum of degrees of freedom for all
Fisher Z s in that set. Weights in the first set were positive, whereas
those in the second were negative. This weighting method resulted in a
statistic (i.e., normal deviate z ) that is equivalent to Hedges's (1994)
between-groups heterogeneity statistic (i.e., Q BET, distributed as chi 2)
for testing differences between two sets of effect sizes, in that the square
of z is equal to the chi 2 value.
Table 4 presents the results of the four meta-analyses across the different
levels of gender and consent. Effect sizes were homogeneous in all four
groups and unbiased effect size estimates were all significantly greater
than zero, as is indicated by the 95% confidence intervals that did not
contain zero. The contrast between the female (r u= .10) and male (r u= .07)
unbiased effect size estimates, based on 14,578 participants, was
nonsignificant, z = 1.42, p > .10, two-tailed. The contrast between the
unwanted sex (r u= .10) and all levels of consent (r u= .10) unbiased effect
size estimates was also nonsignificant, z = .03, p > .10. These
nonsignificant main effects are attributable to the Consent × Gender
interaction, which is described next.
Table 4
Meta-Analyses of Sample-Level Effect Sizes Assessing CSA-ADjustment
Relations
in College Students for Each Level of Gender and Consent
Moderator and level k N ru 95% CI H
Male 14 2,947 .07 .04 to 17.05
.11
Gender
Female 33 11,631 .10 .08 to 23.83
.12
All types 35 11,320 .10 .08 to 30.12
.11
Consent2
Unwanted 12 3,258 .10 .06 to 12.78
.13
Note
k represents the number of effect sizes (samples);
N is the total number of participants in the k samples;
ru is the unbiased effect size estimate (positive values indicate
better adjustment for control participants);
95% CI is the 95% confidence interval for ru;
H is the within-group homogeneity statistic (chi square based on
df = k - 1).
All sets of effect sizes were homogeneous.
2 All types of consent included both willing and unwanted child
sexual abuse (CSA); unwanted CSA includes unwanted experiences
only.
[Page 34]
Table 5 presents the results of the four meta-analyses for the four
different Consent × Gender combinations. Effect sizes were homogeneous in
all four groups. The unbiased effect size estimate for men with all types of
consent (r u= .04) was not significantly different from zero. All other
unbiased effect size estimates, however, were significantly greater than
zero. For men, the contrast between the unwanted sex (r u= .13) and all
types of consent (r u= .04) effect size estimates, based on 2,947
participants, was statistically significant, z = 2.16, p < .05, two-tailed,
indicating that the association between CSA and adjustment problems was
stronger for men when the CSA was unwanted than when it included all levels
of consent. For women, the analogous contrast between the unwanted sex (r u=
.08) and all levels of consent (r u= .11) effect size estimates, based on
11,631 participants, was nonsignificant, however, z = -1.03, p > .10,
two-tailed. For unwanted sex only, the contrast between the female (r u=
.08) and male (r u= .13) unbiased effect size estimates, based on 3,258
participants, was nonsignificant, z = -1.21, p > .10, two-tailed. Finally,
for all types of consent, the contrast between the female (r u= .11) and
male (r u= .04) effect size estimates, based on 11,320 participants, was
statistically significant, z = 2.51, p < .02, two-tailed.
Table 5
Meta-Analyses of Sample-Level Effect Sizes Assessing CSA-Adjustment
Relations
in College Students for Each Gender × Consent Combination
Gender and
consent2 k N ru 95% CI H
All types 10 1,957 .04 -.00 to 9.29
.09
Male
Unwanted 4 990 .13 .07 to 3.08
.19
All types 25 9,363 .11 .09 to 14.50
.13
Female
Unwanted 8 2,268 .08 .04 to 8.23
.12
Note
k represents the number of effect sizes (samples);
N is the total number of participants in the k samples;
ru is the unbiased effect size estimate (positive values indicate
better adjustment for control participants);
95% CI is the 95% confidence interval for ru;
H is the within-group homogeneity statistic (chi square based on
df = k - 1).
All sets of effect sizes were homogeneous.
2 All types of consent included both willing and unwanted child
sexual abuse (CSA); unwanted CSA includes unwanted experiences
only.
These results help clarify the significant Consent × Gender interaction
found in the multiple regression analysis. Adjustment was associated with
level of consent for men, but not for women. Noteworthy is the finding that
SA men in the all-levels-of-consent group were unique in terms of not
differing from their controls in adjustment. Because all levels of consent
corresponds to social and legal definitions of CSA, these results imply
that, in the college population, the association between CSA and adjustment
problems is not equivalent for men and women. If the definition of CSA is
restricted to unwanted sex only, however, then these results imply a gender
equivalence between men and women in the association between CSA and
adjustment problems.
Simple correlations.
In a further attempt to explain variability in sample-level effect sizes, we
examined the association between several additional factors and the
sample-level effect sizes (the three outliers were not included in these
analyses). Associations were computed using weighted correlational analyses
(weights were N - 3 for each sample). We coded all studies for method of
assessment (e.g., face-to-face interview vs. questionnaire), type of
institution (e.g., public vs. private), sampling strategy (e.g., a
convenience sample of introductory psychology students vs. a broader sample
of students obtained by random or pseudorandom sampling), mean age of
students at time of assessment, the maximum age for a "child" in the study's
definition of CSA, and whether the study was published. No method variance
in assessment emerged because all studies were based on questionnaires.
Similarly, type of institution did not show itself to be useful for
correlational analysis because nearly all studies were conducted at state
universities. For sampling strategy, we categorized studies into two groups:
ones that used convenience samples of students (usually psychology or
sociology) and ones that used wider samples that included students in
nonsocial science courses or that were based on random or pseudorandom
sampling of all students at the school. Of the 38 studies for which sampling
strategy could be coded, 25 were of the first type and 13 were of the
second. Sampling strategy was not related to effect sizes, r (36) = .16, p >
.30, two-tailed. Regarding age of students, if CSA has early effects that
diminish over time, or if it has delayed effects that emerge only as
students get older, then a significant correlation between mean age of
students in the sample and effect sizes would be expected (the range of mean
ages in the samples went from 18.0 to 26.6 with an overall mean age of
20.8). The correlation, however, was nonsignificant, r (36) = .01, p > .90,
two-tailed. Similarly, maximum age of "child" in the study's definition of
CSA was not related to the effect sizes, r (44) = -.05, p > .70, two-tailed.
The relationship between whether a study was published and the sample-level
effect sizes was marginally significant, r (49) = .25, p = .08, two-tailed.
The 27 samples with published results had a slightly larger unbiased effect
size estimate (r u= .11) than that of the 24 samples whose results were
unpublished (r u= .08).
Moderators concerning aspects of the CSA experience.
Studies were inconsistent in providing statistics on aspects of the CSA
experience (e.g., force, penetration) that might affect adjustment among SA
participants. We examined all studies to search for such moderators and
found five types that were reported in at least two studies: force,
penetration, duration, frequency, and incest. Additionally, several studies
examined moderators that were composite measures that combined two or more
of the moderators just listed. Some researchers provided correlations
between a moderator and self-reported reactions or effects; other
researchers provided correlations between a moderator and symptoms among SA
participants. We meta-analyzed separately the moderator-reaction-effect and
moderator-symptom relations for the different types of moderators when
results for both types of relations were available (we considered
individually the results from the studies examining composite moderators).
In the case of moderator-symptom relations, if a study provided correlations
between a given moderator and more than one symptom, then all of these
correlations were averaged using Fisher Z transformations to create a single
moderator-symptom relation for that study. Some studies reported only beta
weights; these values were used as effect size estimates. A number of
studies reported only that the relation was nonsignificant or that it was
significant; in these cases, following recommended procedures by
meta-analysts (e.g., Rosenthal, 1984 ), we set the effect size to zero in
the former case and to the appropriate value corresponding to p = .05,
two-tailed, in the
[Page 35]
second case. Because most effect size assignments were of the former type,
some of the unbiased effect size estimates are likely to be underestimates
of the moderator-symptom relations.
Table 6 provides summaries of the meta-analyses of the moderator-outcome
relations. As shown in the table, only 3 of the 10 moderator-outcome
relations reached statistical significance. The presence of force was
associated with more negative reactions and self-reported effects; the
magnitude of this relation was medium, r u= .35. Incest (i.e., close
familial CSA) was associated with both symptoms, r u= .09, and negative
reactions-self-reported effects, r u= .13; the magnitudes of these relations
were small. Notably, force was unrelated to symptoms, and penetration was
unrelated to either outcome. Frequency (i.e., number of CSA episodes) and
duration (i.e., length of CSA involvement) were also not related to outcome.
The table also displays recalculated unbiased effect size estimates (shown
in parentheses next to original estimates) in cases where one or more effect
sizes were estimated. These new effect size estimates were computed using
only the known effect size values. The statistical significance of these
recalculated values changed in only one case. Symptoms associated with
penetration became statistically significant (95% confidence interval = .02
to .30). This result, however, should be viewed with caution, because it is
based on the removal of more than half the effect sizes for this outcome,
all of which were nonsignificant.
Table 6
Meta-Abalyses of Relations Between Aspects of the Child Sexual Abuse
Experience and
Outcome in Sexually Abused College Students
Moderator Outcome K Est. N ru 95% CI H
Duration Reactions/effects 4 1a 473 -.03 -.12 to 1.70
(-.04) .06
Symptoms 2 0 82 0.84
.21 -.01 to
.41
Force Reactions/effects 7 2b 694 .35 .28 to 29.70*
(.40) .41
Symptoms 4 1a 295 1.71
.11 -.01 to
(.14) .24
Frequency Reactions/effects 3 2a 328 -.02 -.13 to 0.49
(-.09) .09
Symptoms 3 0 174 0.53
.08 -.07 to
.23
Incest Reactions/effects 4 0 394 .13 .03 to 4.73
.22
Symptoms 9 1a 572 .09) 15.20
.11) .01 to
.17
Penetration Reactions/effects 2 0 253 -.03 -.15 to 0.30
.10
7 4a 594 .05 4.32
Symptoms (.16) -.03 to
.13
Note.
k represents the number of effect sizes (samples);
Est. is the number of effect sizes that had to be estimated
because statistics were neot provided or were inadequate;
N is the total number of participants in the k samples;
ru is the unbiased effect size estimate (positive values indicate
worse reactions or poorer adjustment for participants who
experienced greater degrees of the moderator);
values in parentheses after some rus represent unbiased effect
size estimates based on only known (i.e. nonestimated) rs;
95% CI is the 95% confidence interval for ru based on both known
and estimated rs;
H is the withwin-group homogeneity statstic (chi square based on
df = k - 1).
a Estimated effect sizes set at r = 0.
b Estimated effect sizes based on p = .05, two tailed.
* p < .05.
Five studies examined composite measure-symptom relations. In one, a
composite measure of paternal incest, force, and penetration was associated
with poorer adjustment ( Edwards & Alexander, 1992 ). Composite
measure-symptom relations in the other four studies, however, were
nonsignificant. In these studies, the composite measures consisted of
incest, frequency, force, and genital contact ( Greenwald, 1994 ); type of
CSA and frequency ( Smolak, Levine, & Sullins, 1990 ); extent of physical
contact and invasiveness of the sex ( Mandoki & Burkhart, 1989 ); factors
such as invasiveness, duration, and frequency ( Cole, 1988 ). The
inconsistency in results and in composition of the composite measures makes
it difficult to draw conclusions concerning the composite measure-symptoms
relations. Future research is required to address this issue by
systematically documenting which combinations of moderators are reliably
associated with symptoms.
Self-Reported Reactions to and Effects From CSA
To examine further whether CSA is an equivalent experience for males and
females, we compared the genders in terms of their self-reported reactions
to and effects from CSA. If a basic property of CSA is that it is an
equivalent experience for males and females, then it follows that correlates
of this experience (e.g., self-perceptions of negativity and harmfulness)
should be similar for men and women in the college population. These
subjective self-reports were also useful for addressing the assumption that
harmful effects are pervasive and intense in the population of persons with
a history of CSA.
Retrospectively recalled immediate reactions.
Fifteen studies presented data on participants' retrospectively recalled
immediate reactions to their CSA experiences that were classifiable as
positive, neutral, or negative. Table 7 presents the reaction data
separately for 10 female and 11 male samples. Some authors reported the
number of participants who reported positive, neutral, or negative
reactions; others reported the number of experiences reported to be
positive, neutral, or negative. We
[Page 36]
therefore treated reports of numbers of participants as numbers of
experiences (i.e., one participant equals one experience) so as to be able
to combine results. Overall, 72% of female experiences, but only 33% of male
experiences, were reported to have been negative at the time. On the other
hand, 37% of male experiences, but only 11% of female experiences, were
reported as positive. These overall percentages were obtained by weighting
the percentages of each sample by their sample size (only samples in which
all three reaction-types were reported were combined).
Table 7
Retrospectively Recalled Immediate Reactions of College Students to their
CSA Experiences
Study Females (%) Males (%)
Pos Neut Neg N Pos Neut Neg N
Brubaker, 1991 22 18 60 50 - - - -
Brubaker, 1994 10 17 73 99 - - - -
Condy et al., 1987 - - - - 58 14a 28 50
Finkelhor, 1979 7 27 66 119b n/a n/a 38 23
Fischer, 1991 5 n/a n/a 39 28 n/a n/a 18
Fishman, 1991 - - - - 27 43 30 30b
Fromuth, 1984 28 12 60 130b - - - -
Fromuth & Burkhart, - - - - 60 28 12 81
1989
Goldman & Goldman, 17 16 68 188b 39 32 30 40b
1988
Landis, 1956 2 16 82 493b 8 39 54 183b
Long & Jackson, 1993 4 28a 69 137 - - - -
O'Neill, 1991 10 6 84 83b 43 9 48 46b
Schultz & Jones, 1983 28 19 52 122b 69 24 7 67b
Urquiza, 1989 - - - - 39 27 33 51
West & Woodhouse, - - - - 45 29 26 58
1993
Totals 11 18 72 1421 37 29 33 606
Note.
Dashes indicate that participants of a given gender were not
included in the study.
n/a indicates information not available.
Totals include only samples for which all 3 reaction-types are
given. Total percents are weighted by sample size; total Ns
reflect a combination of number of experiences and number of
participants. Percentages do not sum exactly to 100 because of
rounding.
a Includes mixed reactions.
b Indicates number of experiences. Otherwise, N indicates number
of participants.
These results indicate that males and females did not react to CSA at the
time it occurred in an equivalent manner. The partial results reported by
Finkelhor (1979) and Fischer (1991) are consistent with the overall results.
Also consistent with these results are those obtained by Haugaard and Emery
(1989) , who reported mean retrospectively recalled immediate reactions
based on a 7-point scale (1 = very positive; 7 = very negative ). The mean
rating for men was 3.38, indicating a neutral to somewhat positive overall
reaction, and the mean rating for women was 5.83, indicating an overall
negative reaction. Aside from gender differences, the results show that
reactions were highly variable, rather than being exclusively negative.
Assuming that retrospectively recalled immediate reactions are associated
with later adjustment - a relation that was found by Long and Jackson (1993)
in their study using a college sample - these results imply that resulting
harm is not prevalent, at least for men, in the college population.
Current reflections.
Seven female and three male samples contained reports of positive, neutral,
and negative current reflections (i.e., current feelings) about CSA
experiences. Results were similar to retrospectively recalled immediate
reactions, with 59% of 514 female experiences being reported as negative
compared with 26% of 118 male experiences. Conversely, 42% of current
reflections of male experiences, but only 16% of female experiences, were
reported as positive. In addition to these results, Haugaard and Emery
(1989) reported mean current reflections based on a 7-point scale (1 = very
positive; 7 = very negative ). The mean rating for men was 3.95, indicating
neutral overall current reflections, and the mean rating for women was 5.82,
indicating current reflections that were negative overall. These data
further point to the nonequivalence of male and female CSA experiences and
imply that harmful effects may not be prevalent.
Self-reported effects.
In eight studies, comprising 11 samples, participants were asked whether
their CSA experiences had affected them. In some studies, effects pertained
to participants' adult sex lives or their sexual attitudes ( Condy et al.,
1987 ; Fishman, 1991 ; Fritz et al., 1981 ; Landis, 1956 ). In other
studies, questions about effects covered more general topics, for example,
amount of stress ( Fischer, 1991 ), effects on one's overall life ( Fishman,
1991 ), still feeling troubled ( Hrabowy, 1987 ), time to recover and damage
to emotional development ( Landis, 1956 ), how long they were affected (
Nash & West, 1985 ), and lasting effects ( West & Woodhouse, 1993 ). Table 8
provides the results of participants' responses to these questions.
For men, self-reported negative effects on their current sex lives or
attitudes were uncommon. In the five studies providing data regarding these
perceived effects, rates of negative sexual effects ranged from 0.4% of
participants to 16%, with an
[Page 37]
unweighted mean rate of 8.5%. For women, self-reported negative effects were
also in the minority; only two samples provided relevant data, with rates of
2.2% and 24%, yielding an unweighted mean of 13.1%. One study ( Landis, 1956
) also provided rates of temporary negative effects on sexual attitudes: 17%
for men and 26% for women.
Table 8
Self-Reported Effects of Child Sexual Abuse Experiences on College Students
Study Sex N Type of effect Response
Condy et al., m 51 Aldult sex life good = 37%; none = 28%; mixed = 9%; bad
1987 = 16%
Fisher, 1991 f 54 Stress then or no stress then or now = 7%; mean stress
now now = 3.00 on 1-10 scale
Fisher, 1991 m 24 Stress then or no stress then or now = 21%; mean stress
now now = 2.12 on 1-10
Fishman, 1991 m 30a Overall life positive = 17%; neutral = 57%; negative
= 27%
Current sex life positive = 24%; neutral = 63%; negative
= 13%
Fritz et al., f 42 Current sex life problems = 24%
1981
Fritz et al., m 20 Current sex life problems = 10%
1981
Hrabowy, 1987 f 107 Troubled over it minimal or trouble-free = 75%;
now moderately = 20%; very = 5%
Landis 1956 f 531a Time to recover No shock = 25%; little/no = 17%; days to
years = 51%; never = 4%
Damage to emot. none = 66%; temporary = 30%; permanent =
Developm. 3%
Affect on sex none = 70%; temporary = 26%; permanent =
attitudes 2.2%
Landis, 1956 m 215a Time to recover no shock = 68%; little/no = 10%; days to
years = 22%; never = 0%
Damage to emot. none = 81%; temporary = 19%; permanent =
Developm. 0%
Affect on sex none = 80%; temporary = 17%; permanent =
attitudes 0.4%
Nash & West, 1985 f 50 How long affectes not at all/ weeks = 52%; months = 16%;
year /+ = 10%; still = 22%
West & Woodhouse, m 67 Lasting effects "only one or two" out of 67 of a sexual
1993 nature
Note
m = male; f = female.
a Indicates number of experiences. Otherwise, N indicates number
of subjects.
Self-reports of lasting negative effects of a general nature for men were
also uncommon. About a quarter of male participants reported lasting
negative effects in one study, but none reported lasting effects in the
other two studies asking this question-in one of these latter studies ( West
& Woodhouse, 1993 ), 1 or 2 participants reported lasting negative effects
of a sexual, rather than general, nature. Landis (1956) reported that only a
minority of his male participants perceived themselves to have been
temporarily adversely affected. Fischer (1991) found that the mean amount of
stress that men reported they felt now as a result of their CSA was low.
Fischer found that her female participants who experienced CSA reported a
somewhat higher mean but were still on the low end of the scale. In other
female samples, Hrabowy (1987) found that only 5% of her participants
reported currently being very troubled over their CSA experiences; another
20% reported being moderately troubled. Landis found that fewer than 1 in 20
of his female participants with CSA experiences reported that they never
recovered or that they suffered permanent damage to their emotional
development. Nash and West (1985) found that 1 in 5 of their CSA
participants reported still being affected. Landis reported that about two
thirds of his female CSA participants felt themselves to have been
temporarily affected. Nash and West found that half of their CSA
participants perceived themselves to have been affected for a little or no
time, while another quarter were affected for a longer, but temporary,
period of time.
The overall picture that emerges from these self-reports is that (a) the
vast majority of both men and women reported no negative sexual effects from
their CSA experiences; (b) lasting general negative effects were uncommon
for men and somewhat more common for women, although still comprising only a
minority; and (c) temporary negative effects were more common, reported by a
minority of men and a minority to a majority of women. These data imply
that, in the college population: (a) CSA affects males and females
differently; (b) lasting negative effects are not prevalent; and (c) when
negative effects occur, they are often temporary, implying that they are
frequently not intense. These findings are inconsistent with the assumption
that CSA has the properties of gender equivalence, prevalence, and intensity
in terms of harmful effects.
Comparing male versus female reactions and self-reported effects via
meta-analysis.
In three meta-analyses, we examined the size of sex differences in (a)
retrospectively recalled immediate reactions, (b) current reflections, and
(c) self-reported effects of CSA. Studies included in these analyses
consisted of both male and female samples. In the case of Risin and Koss
(1987) , who reported on male participants, and Wisniewski (1990) , who
reported on female participants, all participants came from the same pool (a
random sample of 32 U.S. colleges and universities, designed to be
representative of the entire U.S. college population). In two other cases,
we combined results from separate studies that used different samples. The
first case was Fromuth (1986) and Fromuth and Burkhart (1989) , and the
second case was Nash and West (1985) and West and Woodhouse (1993) .
Combining appeared to make sense because the same principal researchers were
responsible for each set of studies (Fromuth and West, respectively), and
the samples were drawn from nearly the same geographic areas, although at
different times. In most cases, comparisons were made between the proportion
of men who reported negative reactions or effects and the corresponding
proportion of women. In the case of Haugaard and Emery (1989) , comparisons
were based on contrasting mean reaction ratings of men and women. Positive
effect sizes indicated that women reported proportionately more negative
reactions or effects, or had a higher mean negative response, than males.
Table 9 presents the results of the meta-analyses.
[Page 38]
Table 9
Meta-Analyses for Male versus Female Reactions to
and reactions to Self-Reported Effects from Child Sexual Abuse in College
Samples
Measurea k N ru 95% CI H
Reactions then 10 2,965 .31 .28 to .34 30.70*
Reactions now 424 .34 .25 to .42 2.13
3
Self-reported
effects 4 835 .22 .15 to .28 1.12
Note
k represents the number of effect sizes for a given meta-analysis;
N is the total number of participants in a given meta-analysis;
ru is the unbiased effect size estimate (positive ru indicates
more negative reactions pr effects for women;
H is the withi-group homogeneity statistic (chi square).
a Reactions then refers to retrospectively recalled immediate
reactions; reactions now refers to current reflexions.
* p < .05 in chi-square test.
In the case of retrospectively recalled immediate reactions, Risin and Koss
(1987) and Wisniewski (1990) presented percentages of participants who
responded to their CSA experiences with fear, guilt, anger, depression, or
feelings of being victimized. Each item was measured on a 5-point scale
whose values were 1 = not at all ; 2 = a little ; 3 = somewhat ; 4 = quite ;
and 5 = very . We averaged the proportion of men and women across the 5
items who reported anything from "a little" to "very" to compare the
proportions of each sex who made negative reports. The meta-analysis, based
on 10 effect sizes that ranged from r = .21 to .52, yielded a medium
unbiased effect size estimate, r u= .31, in which women reported
significantly more negative immediate reactions than men (indicated by the
95% confidence interval). The effect sizes were heterogeneous, however. The
meta-analysis of current reflections, based on 3 effect sizes ranging from
.24 to .38, also yielded a medium unbiased effect size estimate, r u= .34,
in which women's current reflections concerning their CSA experiences were
significantly more negative than those of males (indicated by the 95%
confidence interval). These effect sizes were homogeneous.
For the self-reported effects, effect sizes were derived as follows:
contrasting 21% of men with no stress then or now with 7% of women for
Fischer (1991) ; contrasting 10% of men with current sex problems reported
to have resulted from the CSA with 24% of women ( Fritz et al., 1981 ); for
Landis (1956) , averaging the effect sizes for self-reports of time to
recover, damage to emotional development, and effects on sexual attitudes
(in each case, proportions of men and women reporting any negative effects
at all were contrasted); and for Nash and West (1985) and West and Woodhouse
(1993) , the proportions of women and men reporting lasting negative effects
were contrasted. The meta-analysis, consisting of four effect sizes ranging
from r = .16 to .30, yielded a small to medium unbiased effect size
estimate, r u= .22, indicating that women reported significantly more
negative effects than men (indicated by the 95% confidence interval). The
effect sizes were homogeneous.
The results of these three meta-analyses imply that, in the college
population, men and women with experiences classifiable as CSA feel very
differently about them and perceive very different effects from them. The
assumption that CSA is an equivalent experience for men and women in the
population of persons who experience CSA is unsupported by these results.
Family Environment
Analyses of the CSA-symptom relations indicated that college students with a
history of CSA were, on average, slightly less well adjusted than college
students without such a history. The question arises as to whether these
relations were causal in nature. That CSA usually or inevitably causes harm
is a basic assumption of many mental health care workers and child abuse
researchers. The self-reported effects data, however, do not support this
assumption. Nevertheless, self-reports by themselves cannot be taken as firm
evidence for or against the role of CSA in causing harm, because people are
frequently unaware of the causes of their behavior or current states when
causal relations are ambiguous or complex (cf. Nisbett & Wilson, 1977 ).
Therefore, we addressed the issue of causation further by considering family
environment. Research using clinical samples has consistently shown that
family environment and CSA are confounded (e.g., Beitchman et al., 1991 ),
which weakens the argument that CSA-symptom relations in these samples are
causal. We analyzed the relationship between family environment and CSA in
the college samples to determine whether they were confounded as a first
step in examining whether CSA caused symptoms.
Family environment-CSA relations.
Each study that assessed family environment factors was coded for type of
factor, gender, number of participants used to compute the comparison
statistic, and the comparison statistic itself - the effect size r was
computed from this statistic. Once all the family environment factors had
been listed, Bruce Rind and Philip Tromovitch attempted to classify them
into a smaller number of distinct categories. Results were compared, and
discrepancies were resolved by discussion. Six general categories emerged:
nonsexual abuse and neglect, adaptability, conflict and pathology, family
structure, support and bonding, and traditionalism.
The effect sizes for each family environment category were meta-analyzed, as
shown in Table 10 . For all 6 categories, the effect size estimates were
statistically significant, indicated by
[Page 39]
the 95% confidence intervals. The unbiased effect size estimates ranged
from r u= .09 to .19, with a weighted mean r = .13. Effect sizes were
homogeneous in 4 of the 6 categories. Only adaptability and support-bonding
were heterogeneous. The positive values of the effect size estimates imply
that college students with a history of CSA come from more problematic home
environments than control students, implying that CSA and family environment
are confounded in this population.
Table 10
[Page 38]
Meta-Analyses of Six Family Environment Factors as a function of CSA Status
Family factor k N ru 95% CI H
Abuse and neglect 5 1,098 .19 .13 to .25 2.36
Adaptability 3 976 .13 .06 to .19 20.38*
Conflict or
pathology 9 4,906 .14 .12 to .17 0.74
Family structure 4 3,803 .09 .06 to .12 6.54
Support or bonding 13 3,288 .13 .09 to .16 36.46*
Traditionalism 5 836 .16 .09 to .22 8.26
Note
k represents the number of effect sizes (samples);
N is the total number of participants in the k samples;
ru is the unbiased effect size estimate;
95% CI is the 95% confidence interval for ru;
H is the within-group homogeneity statistic (chi square).
A positive ru indicates better family adjustment or functioning in
the control than sexual child abuse (CSA) group.
* p < .05 in chi-square test.
[Page 39 continues]
Family environment-symptom relations.
The confounding of CSA and family environment raises the possibility that
CSA may not be causally related to symptoms in the college population or may
be related in a smaller way than uncontrolled analyses have indicated. To
address this issue, we examined the relationship between family environment
and symptoms. All studies providing statistics assessing the relationship
between these two factors were coded. For each study, effect sizes were
computed for all family environment-symptom relations. Additionally, for
each study, a study-level effect size was computed; this value represents
the mean effect size based on Fisher Z transformations of all family
environment-symptom relations in that study. A series of symptom-level
meta-analyses and a study-level meta-analysis were then performed.
Table 11 provides the results of the meta-analyses of the symptom-level and
study-level effect sizes. Symptoms that had only one effect size were not
meta-analyzed. The effect sizes ranged from r = .04 to .49. All effect size
estimates based on two or more effect sizes were significantly greater than
zero, as indicated by their 95% confidence intervals. Five of the seven
effect sizes based on single samples were significantly greater than zero.
In the majority of cases, effect size estimates were based on a small number
of samples and the effect sizes used to derive these estimates were
heterogeneous. This latter finding is not surprising, given the
heterogeneous collection of family environment measures for any given
symptom. These estimates should therefore be viewed with caution.
Nevertheless, with the exception of two measures based on single samples,
the effect sizes were generally medium in size, in contrast to the
CSA-symptom and CSA-family environment effect sizes, which were generally
small. The study-level effect size estimate was r u= .29, indicating an
overall medium association between family environment and symptoms. In terms
of variance accounted for, family environment outperformed CSA in explaining
symptoms by a factor of 9. These results imply that, in the college
population, family environment is a more important predictor of symptoms
than is CSA (see below for a discussion of the statistical validity of
comparing CSA-symptom and family environment-symptom relations).
Table 11
Meta-Analyses of Symptoms as a Function of Family Environment Factors
Symptoms k N ru 95% CI H
Alcohol 1 383 .04 -.06 to --
.14
Anxiety 3 788 .34 .28 to 19.80
.40
Depression 5 1,279 .38 .33 to 22.28*
.43
Dissociation 1 251 .49 .39 to --
.58
Eating disorders 4 822 .21 .15 to 10.05*
.28
Hostility 1 383 .15 .05 to --
.25
Interpersonal .24 to
sensivity 2 634 .32 .38 20.25
Locus of control 1 383 .07 -.03 to --
.17
Obsessive - .20 to
compulsive 2 634 .27 .34 4.02*
Paranoia 1 383 .16 .06 to --
.26
Phobia 1 383 .18 .08 to --
.28
Psychotic symptoms 1 383 .22 .12 to --
.31
Self-esteem 5 1,345 .26 .20 to 37.13*
.30
Sexual adjustment 2 337 .23 .13 to 0.24
.33
Social adjustment 3 653 .41 .35 to 20.50*
.47
Somatization 2 634 .22 .15 to 12.59
.29
Suicide 2 634 .26 .18 to 1.41
.33
Wide adjustment 4 992 .31 .25 to 12.95*
.37
Study level 13 2,846 .29 .26 to 62.56*
.33
Note
k represents the number of effect sizes (samples);
N is the total number of participants in the k samples;
ru is the unbiased effect size estimate (positive values indicate
greater degrees of symptoms are associated with poorer family
functioning);
95% CI is the 95% confidence interval for ru;
H is the within-group homogeneity statistic (chi square).
-- dashes indicate H was not computed because only one sample was
involved.
Meta-analyses were performed when k > 1.
Study-level effect sizes are mean effect sizes, based on Fisher Z
transformations, of all symptom-family environment relations in a
given study.
* p < .05 in chi-square test.
Statistical control.
Results of the three sets of analyses just presented (i.e., meta-analyses of
the relationships between CSA and symptoms, CSA and family environment, and
family environment and symptoms) are consistent with the possibility that
the small but statistically significant CSA-symptom associations found in
the studies reviewed may have been spurious. This possibility is suggested
by the logic of semipartial correlational analysis, or equivalently,
hierarchical regression analysis ( Keppel & Zedeck, 1989 ). These analyses
are useful for determining whether a significant relationship between two
variables remains significant after controlling for extraneous factors. The
necessary conditions for a significant relationship to be reduced to
nonsignificance are as follows: (a) the independent variable (e.g., CSA) is
related to the dependent variable (e.g., symptoms), (b) the independent
variable is related to a third variable (e.g., family environment), (c) the
third variable is related to the dependent variable, and (d) the significant
relation between the independent and dependent variables is rendered
nonsignificant when the third variable is statistically controlled for. The
analyses presented above demonstrate that the first three of these
conditions were generally satisfied. Further, the finding that the mean
correlation between CSA and symptoms ( r = .09) was somewhat smaller than
that between CSA and family environment ( r = .13), which in turn was
substantially smaller than that between family environment and symptoms ( r
= .29), suggests that many significant CSA-symptom relations might be
reduced to nonsignificance with statistical control. To address this
possibility directly, we coded all studies that employed statistical control
(see Table 12 ).
Table 12
[Page 40]
Results of Statistical Control on CSA-Symptoms Relations
Study Type of control Significant results
N Before After % reduction
Brubaker, 1999 Separated categories 1 1 0 100
Cole, 1988 Hierarch. Regression 5 3 0 100
Collings, 1995 ANCOVA 10 8 6 25
Fromuth & Burk, Hierarch. Regression 13 6 6 0
1989, mw
Fromuth & Burk, Hierarch. Regression 13 0 0 -
1989, se
Fromuth, 1986 Hierarch. Regression 13 4 1 75
Gidycz et al., 1995 Path analysis 3 0 0 -
Greenwald, 1994 Hierarch. Regression 1 0 0 -
Harter et al., 1988 Path analysis 2 1 0 100
Higgins & McCabe, Hierarch. Regression 2 2 0 100
1994
Lam, 1995 Multiple regression 3 0 0 -
Long, 1993 Multiple regression 2 1 0 100
Pallotta, 1992 ANCOVA 13 6 0 100
Yama et al., 1992 ANCOVA 2 2 1 50
Totals 83 34 14 59a
Note. N indicates the number of symptom measures whose relation to
child sexual abuse (CSA) status was examined (or was intended to
be by the study authors) by using statistical control. "Before"
indicates the number of relations significant before applying
statistical control; "After" indicates the number of significant
relations after applying statistical control. "Reduction"
indicates the percent of significant relations that became
nonsignificant after statistical control.
-- Dashes indicate that persentage reduction was not computed
because all results were initially nonsignificant;
ANCOVA = analysis of covariance;
mw = Midwest; se = Southeast.
a Based on the percent of total significant relations that became
nonsignificant after control. The unweighted percent reduction was
83%.
Page 39 continued]
Coding involved recording for each study the type of statistical control
used, the number of symptoms whose relationships with CSA were controlled
for, the number
[Pasge 40]
of significant CSA-symptom relations before statistical control, and the
number of significant CSA-symptom relations after statistical control. 4
Table 12 displays the results of this coding. In the last column the
percentage of reduction from before to after statistical control is
provided. Statistical control was used in 13 studies with 14 samples-in some
cases control was not used because nonsignificant correlations between
symptoms and family environment obviated this procedure, although the
researchers had planned to use statistical control; these samples are
included in this analysis. In all cases but one (i.e., Brubaker, 1991 ),
statistical control involved using statistical procedures such as
hierarchical regression or analysis of covariance (ANCOVA). Brubaker (1991)
imposed control by separating her participants into mutually exclusive
categories (i.e., no abuse, CSA only, psychological abuse only, physical
abuse only, followed by combinations of these abuse types). This
deconfounding procedure has been used recently by other researchers
examining noncollege samples, who have shown that when CSA is isolated, its
negative correlates tend to shrink considerably or disappear (e.g.,
Eckenrode, Laird, & Doris, 1993 ; Ney et al., 1994 ).
Of 83 CSA-symptom relations, 34 (41%) were significant before statistical
control. Only 14 (17%) remained significant after statistical control. It is
important to note that, within any given study, multiple CSA-symptom
relations were not independent, because they were based on the same sample.
It may therefore be more appropriate to use only one result per study (e.g.,
percentage of reduction) to evaluate the effects of statistical control.
Using this approach, the overall reduction from statistical control was 83%
(as opposed to the 59% reduction using dependent relations). One additional
study, not shown in the table and not included in the above analysis, also
used statistical control ( Wisniewski, 1990 ). This study was based on 3,187
female college students drawn from 32 colleges and universities that were
fairly representative of all institutions of higher learning in the United
States. Unlike the other studies using statistical control, which held
extraneous factors constant for all participants (with or without CSA) in a
single analysis, Wisniewski conducted four separate analyses using path
analysis, one for each separate group of participants (i.e., no CSA,
nonincest CSA, incest CSA, and nonincest CSA with adult revictimization).
For all CSA participants, she constructed a CSA severity score that
reflected the degree of felt victimization from and negative reactions to
the CSA. Results of her analyses revealed that CSA did not contribute to
current adjustment for nonincest or incest CSA participants and contributed
to only a small degree ( b weight = .02) in the case of incest with adult
revictimization subjects. Wisniewski found that other factors, particularly
family violence, best explained current adjustment.
Results from studies using statistical control supplement the analyses of
the intercorrelations among CSA, symptoms, and family environment. They
provide direct evidence that the majority of significant CSA-symptom
relations examined in the college samples may have been spurious. These
results imply that significant CSA-symptom relations in studies based on
[Page 41]
college samples cannot be assumed to represent effects of CSA. Although the
results of the analyses of statistical control, as well as analyses of the
CSA-symptom-family environment relations, do not prove that CSA-symptom
relations are spurious in the college population, they specifically do not
support the assumption that a basic property of CSA is that it causes
psychological injury.
Statistical validity..
In comparing CSA-symptom and family environment-symptom relations, as well
as statistically controlling for family environment when assessing
CSA-symptom relations, several statistical issues may relate to the validity
of these analyses. It is possible that the CSA-symptom association may be
underestimated relative to the family environment-symptom association.
First, often unstandardized measures of CSA may have less reliability than
measures of family environment. Lower reliabilities translate into
attenuated correlations ( Glass & Hopkins, 1996 ; Hunter & Schmidt, 1994 ).
Second, CSA is usually measured as a dichotomous variable (i.e., present or
absent), whose distribution tends to be skewed with a strong mode in the
absent category. Low base rates for a category of interest (e.g., CSA) can
attenuate correlations ( Glass & Hopkins, 1996 ; Rosenthal & Rosnow, 1991 ).
Further, the artificial dichotomization of an independent variable (e.g.,
CSA) can also attenuate correlations ( Glass & Hopkins, 1996 ; Hunter &
Schmidt, 1994 ).
Regarding the first point, although most studies on CSA have not assessed
the reliability of their measures of CSA, several have, all of which were
based on college samples. Messner et al. (1988) reported that 2-week
test-retest reliabilities for characteristics of CSA experiences (e.g.,
duration, frequency, age of onset) were all greater than .69. Long and
Jackson (1993) reported that 2-week test-retest reliabilities for emotional
reactions to CSA at the time it occurred ranged from .70 to .96, with a mean
of .83. Pallotta (1992) reported that 2-week test-retest reliabilities for
CSA characteristics (e.g., duration, age of onset) ranged from .93 to 1.00,
with a mean of .97. She also reported corresponding reliabilities for
negative family environment characteristics, with a mean of .90. Koss and
Gidycz (1985) reported that 1-week test-retest agreement on a measure of
unwanted sexual experiences since age 14 was 93%. These results point to
acceptable reliabilities for measures of CSA, which are comparable to
reliabilities for family environment measures-for example, 8-week
test-retest reliabilities on the Family Environment Scale have ranged from
.68 to .86 ( Cole, 1988 ). Furthermore, the reliability results from the
first three of the studies just discussed are especially relevant, because
their measures of CSA were modified versions of Finkelhor's (1979) measure;
about half of the studies in the current review used modifications of
Finkelhor's measure. Thus, support for acceptable reliability extends to a
sizable portion of the studies under review.
The second issue concerns attenuating effects from low base rates. The more
the split between CSA and control participants deviates from 50-50, the
greater the attenuation in the CSA-symptom association will tend to be (cf.
Rosenthal & Rosnow, 1991 ). This attenuation is quite small for a 27-73
split (e.g., female CSA), but it is somewhat larger for a 14-86 split (e.g.,
male CSA). However, the attenuation is small in absolute magnitude for small
effect sizes. For the small CSA-symptom effect size estimates obtained in
the current review, adjusted effect size estimates based on a 50-50 split
increase at most by .03 (based on formulas provided by Rosenthal & Rosnow,
1991 ), indicating that adjusted effect size estimates are still small in
magnitude and are considerably smaller than the family environment-symptom
effect size estimate of r u= .29. From an empirical point of view, it is
noteworthy that, in the current review, base rates were not positively
related to effect size estimates, r (48) = -.04, p > .70, two-tailed,
contrary to expectations that they would be.
Finally, the relevance of artificial dichotomization to the CSA variable is
weakened by the fact that CSA has generally been conceptualized as a
categorical rather than continuous variable (i.e., one experiences CSA or
one does not). Nevertheless, despite this common conceptualization of CSA,
several researchers have attempted to construct continuous measures of CSA
and have used these measures to compare CSA with family environment in terms
of their relative contribution to adjustment variance (e.g., Cole, 1988 ;
Wisniewski, 1990 ). Wisniewski's severity score of CSA discussed previously
is one example. For nonincestuous SA students who were not revictimized as
adults, a path analysis revealed that family violence was related to current
levels of emotional distress ( b = .13), whereas CSA was not ( b = -.02).
Likewise, for incestuous CSA, family violence ( b = .27) was related to
emotional distress, but CSA was not ( b = -.01). Cole constructed a severity
index for CSA (composed of factors such as degree of invasiveness), which
can also be viewed as a continuous measure of CSA. She found that CSA did
not explain adjustment variance above and beyond that explained by various
family environment factors in a hierarchical regression. It is important to
note that a continuous measure for physical abuse, constructed similarly to
the severity index for CSA, was entered along with CSA in the last step of
the analysis; this family environment factor, but not CSA, accounted for
additional adjustment variance. Results from these studies in which CSA was
constructed to be continuous are consistent with results from studies in
which CSA was treated dichotomously in terms of pointing to family
environment, rather than CSA, as a significant contributor to current
adjustment.
In sum, CSA-symptom relations could be underestimated relative to family
environment-symptom relations because of unreliability of CSA measures, low
base rates for CSA, and artificial dichotomization of CSA. The foregoing
discussion suggests that reliability is not problematic and that attenuation
due to low base rates is of very low magnitude because effect size estimates
were small to begin with. In a similar vein, attenuation due to
dichotomization, if artificial, would also be of very low magnitude because
of the small effect size estimates that were obtained (cf. Glass & Hopkins,
1996 ). Empirically, low base rates were not associated with lower effect
size estimates, and CSA was relatively unimportant compared with family
environment when CSA was treated as a continuous variable. These
considerations support the validity of comparing CSA-symptom and family
environment-symptom relations and of assessing CSA-symptom relations when
controlling for family environment. Nevertheless, precise, as opposed to
relative, estimates of the contributions of CSA and family environment to
adjustment may be somewhat problematic because of the possibility of low
magnitude attenuations of CSA-symptom relations.
[Page 42]
Discussion
Commonly expressed opinions, both lay and professional, have implied that
CSA possesses four basic properties: causality (it causes harm),
pervasiveness (most SA persons are affected), intensity (harm is typically
severe), and gender equivalence (boys and girls are affected equally).
Qualitative and quantitative literature reviews of CSA have offered mixed
conclusions regarding these properties but have suffered from various
shortcomings. Problems in qualitative reviews have generally included
sampling bias (i.e., overreliance on clinical and legal samples),
subjectivity, and imprecision. Quantitative reviews have included larger
proportions of nonclinical and nonlegal samples, reduced subjectivity, and
increased precision and indicate that the intensity of CSA effects or
correlates is of low magnitude in the general population. These reviews,
however, have offered less clarification regarding issues of causality,
pervasiveness, and gender equivalence. To address the shortcomings of the
qualitative and quantitative reviews, we reviewed the CSA literature based
on college samples. The advantages of this literature were (a) it contains
the largest set of studies conducted on nonclinical and nonlegal
populations; (b) it offers the most extensive database on moderating
influences (e.g., family environment), useful for examining the issue of
causality; (c) it provides a large number of male samples, facilitating
gender comparisons; and (d) it provides a large database on self-reported
reactions and effects, enabling examination of the pervasiveness of negative
outcomes.
Review of the college samples revealed that 14% of college men and 27% of
college women reported events classifiable as CSA, according to the various
definitions used. Results from the college data do not support the commonly
assumed view that CSA possesses the four basic properties outlined
previously. CSA was associated with poorer psychological adjustment across
the college samples, but the magnitude of this association (i.e., its
intensity) was small, with CSA explaining less than 1% of the adjustment
variance. Further, this small association could not be attributed to CSA for
several reasons: (a) family environment was confounded with CSA, (b) family
environment predicted adjustment problems better than CSA by a factor of
nine, and (c) statistical control tended to eliminate significant relations
between CSA and adjustment. Results also revealed that lasting negative
effects of CSA were not pervasive among SA students, and that CSA was not an
equivalent experience for men and women. These results imply that, in the
college population, CSA does not produce pervasive and intensely negative
effects regardless of gender. Therefore, the commonly assumed view that CSA
possesses basic properties regardless of population of interest is not
supported. These findings are consistent with Constantine's (1981 , p. 238)
conclusion that CSA has "no inbuilt or inevitable outcome or set of
emotional reactions" associated with it. It is important to add that
analysis at the population level estimates the typical case and therefore
obscures individual cases. That is, the findings of the current review
should not be construed to imply that CSA never causes intense harm for men
or women-clinical research has well documented that in specific cases it
can. What the findings do imply is that the negative potential of CSA for
most individuals who have experienced it has been overstated.
The validity of using studies based on the college population to assess
characteristics of CSA in the general population is of particular concern.
Objections to such an approach have included claims that SA college students
may be too young for symptoms to appear, typically experience less severe
forms of CSA and consequently are less harmed, or are better able to cope
with their experiences than persons in the general population (e.g., Briere,
1988 ; Jumper, 1995 ; Pallotta, 1992 ). Evidence from the current review of
similarities in CSA between the college and general populations, however,
contradicts these views. Compared with SA persons in national samples, SA
college students experienced intercourse, close family CSA, and multiple
incidents of CSA just as often, and the overall prevalence of CSA was not
lower in the college samples. The magnitudes of CSA-adjustment relations in
the college samples and in the national samples meta-analyzed by Rind and
Tromovitch (1997) were identical: r u= .07 for men, r u= .10 for women.
Thus, college students do not appear to present fewer symptoms, experience
less severe CSA, or show better coping. Against claims that college students
may be too young for symptoms to manifest, Neumann et al. (1996) found that
persons under 30 years of age and over 30 years of age did not differ in
CSA-adjustment relations, and age also failed to moderate CSA-adjustment
relations in the current review. These results demonstrate the relevance of
college data to CSA in the broader population and point to the value of
using the college data to evaluate the commonly assumed properties of
causality, pervasiveness, intensity, and gender equivalence. 5
The Four Assumed Properties of CSA Revisited
Gender Equivalence
The gender differences found in current adjustment, retrospectively recalled
immediate reactions, current reflections, and self-reported effects
demonstrate that the experience of CSA is not comparable for men and women,
at least among those who go on to attend college. The relation between CSA
and adjustment problems was generally stronger for women than men. Two
thirds of male CSA experiences, but less than a third of female CSA
experiences, were reported not to have been negative at the time. Three of
every eight male experiences, but only one of every 10 female experiences,
were reported to have been positive at the time. Patterns for current
reflections about these events were similar. The magnitude of gender
differences in
[Page 43]
self-reported effects was virtually identical in the college samples in the
current review (r u= .22) and in the national samples (r u= .23) examined
by Rind and Tromovitch (1997) , which lends further support to the relevance
of the college data to the general population.
A number of researchers have commented on differences in male and female
reactions to CSA. Schultz and Jones (1983) noted that men tended to see
these sexual experiences as an adventure and as curiosity-satisfying,
whereas most women saw it as an invasion of their body or a moral wrong.
Fritz et al. (1981) made nearly identical observations. West and Woodhouse
(1993) , comparing their male sample with Nash and West's (1985) female
sample, observed that women's remembered reactions at the time were
"predominantly of fear, unpleasant confusion, and embarrassment . . . [while
men's] remembered reactions were mostly either indifference, tinged perhaps
with slight anxiety, or of positive pleasure, the latter being particularly
evident in contacts with the opposite sex" (p. 122). These gender
differences in reactions to CSA experiences are consistent with more general
gender differences in response to sex among young persons. For example, boys
and girls report very different reactions to their first experience of
sexual intercourse ( Sorensen, 1973 ), with girls predominantly reporting
negative reactions such as feeling afraid, guilty, or used, and boys
predominantly reporting positive reactions such as feeling excited, happy,
and mature. These differences are likely due to an interaction between
biologically based gender differences and social learning of traditional sex
roles ( Fischer & Lazerson, 1984 ). Researchers (e.g., Kinsey et al., 1948 ;
Sorensen, 1973 ) have repeatedly reported that boys are more sexually active
than girls, masturbate more frequently, and require less physical
stimulation for arousal. Social norms tend to encourage sexual expression in
adolescent boys but have traditionally emphasized romance and nurturance in
girls ( Fischer & Lazerson, 1984 ). Thus, it is unsurprising that men and
women should show similar differences in their reactions to CSA.
It is important to add that men and women may react differently to CSA
experiences because they tend to experience different kinds of CSA. For
example, Baker and Duncan (1985) commented that girls in their national
survey in Great Britain may have found their CSA experiences to be more
damaging than boys did because they had more intrafamilial CSA and
experienced CSA at younger ages. In the current review, college men and
women also tended to have different experiences; SA women experienced close
family CSA more than twice as often as SA men and experienced force about
twice as often.
It is important to note that the separate meta-analyses of the four Gender ×
Consent combinations revealed a stronger association between CSA and
adjustment problems for women than for men when all levels of consent were
considered, but not when unwanted sex only was contrasted. These findings
suggest that some types of CSA (e.g., unwanted experiences) are equivalent
between the genders, but that other types (e.g., willing) may not be. The
overall difference between male and female college students in the
CSA-adjustment relationship is not surprising, because men experienced
coercion less frequently than women. The CSA-adjustment results, however,
reflect both the effects of CSA and of confounding variables. For this
reason, the self-reported reactions and effects data are valuable as direct
measures of impact. These data point to gender nonequivalence but must be
qualified because of potential biases in recalling past events.
Nevertheless, the two sets of analyses converge to suggest that when using
current sociolegal definitions for CSA, which include both unwanted and
willing experiences, men and women are not equivalent in their reactions and
outcomes.
Causality
Two approaches were used to examine whether poorer adjustment for CSA
students compared with control students reflected the effects of CSA. First,
examination of the interrelations among CSA, adjustment, and family
environment revealed that weighted mean effect sizes for CSA-adjustment,
CSA-family environment, and family environment-adjustment relations were r
u= .09, .13, and .29, respectively. The finding that family environment was
confounded with CSA and explained nine times more adjustment variance than
did CSA is consistent with the possibility that the CSA-adjustment relation
may not reflect genuine effects of CSA. Second, analysis of studies that
used statistical control further supported the possibility that many or most
CSA-symptom relations do not reflect true effects of CSA, because most
CSA-adjustment relations became nonsignificant under statistical control.
Some researchers ( Briere, 1988 ; Briere & Elliott, 1993 ) have questioned
the validity of statistically controlling for family environment when
examining CSA-adjustment relations, arguing that such analyses may be
invalid when the control variable (e.g., family environment) is unreliable,
the sample size is small, the causal relationship between the control and
CSA variables is unknown, or the sample underrepresents abuse severity.
These concerns do not appear to be problematic in the current review.
Whether measured by standard instruments or by author-written items, family
environment was reliably related to adjustment. Sample sizes were not small
in the studies using control ( M = 309, SD = 173). Regarding the direction
of causality, Ageton's (1988) national sample showed that family problems
preceded, rather than followed, CSA. Burnam et al. (1988) , using the same
large community sample as Stein et al. (1988) , found that SA persons tended
to be symptomatic both before and after experiencing CSA. These researchers
noted that a third variable such as family or community environment might
have been responsible for both the CSA and the adjustment problems. Pope and
Hudson (1995) detailed the potential role of third variables in accounting
for obtained CSA-adjustment associations (e.g., genetic factors can both
predispose individuals to adjustment problems and make them vulnerable to
CSA events). CSA may be most likely to cause family dysfunction when it is
incestuous; when it is extrafamilial, however, then family dysfunction may
contribute to CSA by making children vulnerable to this experience ( Briere
& Elliott, 1993 ). 6
[Page 44]
In clinical studies, which often include high proportions of patients with
incestuous CSA, causality is therefore more problematic. In the college
samples, however, close family CSA was the exception, not the rule. Only 16%
of SA students had close family CSA; the percentage of cases of paternal
incest is even lower because the overall value includes sibling incest.
These considerations do not prove causal direction in the college population
but suggest that in most cases the direction is more likely to go from
family environment to CSA. Finally, the college samples did not
underrepresent abuse severity. Compared with the general population, as
indicated by studies based on national samples, SA students experienced as
much intercourse, close family CSA, and multiple episodes of CSA; moreover,
college students were just as likely to have experienced CSA as persons in
the general population. Briere's arguments seem most appropriate for
clinical samples with large proportions of incest cases. In this situation,
Briere's (1988 , p. 84) argument that "abuse without family dysfunction may
have little construct validity" may be applicable; in the general population
and in the college population, however, this argument is less valid. These
considerations support the validity of using statistical control in the
studies under review.
Aside from validity issues, however, the statistical control analyses do not
rule out causality for several reasons. First, in a minority of cases,
CSA-symptom relations remained significant after statistical control.
Second, when nonsignificance did result from statistical control, low power
rather than a zero effect may have been responsible. Third, a small minority
of students with a history of CSA did report self-perceived lasting harm,
implying genuine negative effects of CSA for these persons. Fourth, for male
participants, unwanted CSA was associated with greater symptomatology. If
unwanted CSA had been contrasted with willing CSA only, instead of a
combination of unwanted and willing CSA, then consent would likely have
moderated CSA-symptom relations more strongly. These results suggest that
unwanted CSA does have negative effects, although confounding variables must
still be considered. Despite these caveats, the current results imply that
the claim that CSA inevitably or usually produces harm is not justified.
The finding that family environment is more important than CSA in accounting
for current adjustment in the college population is consistent with the
results of several recent studies using participants from noncollege
populations (e.g., Eckenrode et al., 1993 ; Ney et al., 1994 ). Eckenrode et
al. categorized children and adolescents obtained from a large
representative community sample in a small-sized city in New York state into
six groups: not abused, CSA, physical abuse, neglect, CSA and neglect, and
physical abuse and neglect. They found that SA children and adolescents
performed as well in school as nonabused controls in all areas measured,
including standardized test scores, school performance, and behavior.
Neglect and physical abuse, on the other hand, were associated with poorer
performance and more behavior problems. Ney et al. (1994) separated their
mostly clinical sample of children and adolescents into categories of CSA,
physical abuse, physical neglect, verbal abuse, emotional neglect, and
combinations of these. They found that the combination of abuse that
correlated most strongly with adjustment problems was physical abuse,
physical neglect, and verbal abuse. In the top 10 worst combinations, verbal
abuse appeared seven times, physical neglect six times, physical abuse and
emotional neglect five times each, whereas CSA appeared only once.
The greater importance of nonsexual negative childhood experiences in
explaining later adjustment was clearly demonstrated in a study of a large,
representative sample of female college students throughout the United
States. Wisniewski (1990) used path analyses to assess the relative
contributions of CSA and family environment to current adjustment. She
concluded that the data did not support CSA "as a specific explanation of
current emotional distress [but instead are] best interpreted as supportive
of other factors such as family violence . . . as having the greatest
impact" (p. 258). Other researchers who used college samples and used
statistical control reached similar conclusions regarding the role of family
violence, rather than CSA, in explaining current adjustment problems (e.g.,
Higgins & McCabe, 1994 ; Pallotta, 1992 ). One reason CSA may have been
overshadowed by other childhood experiences such as verbal and physical
abuse in explaining adjustment is that participants may have experienced the
latter type of events more frequently than CSA. Nevertheless, the results
from these studies highlight the relatively greater importance of family
environment compared with CSA in accounting for adjustment problems-a point
that has been ignored or underemphasized in much of the CSA literature to
date.
Pervasiveness and Intensity of Negative Effects or Correlates
Self-reported effects from CSA revealed that lasting psychological harm was
uncommon among the SA college students. Perceived temporary harm, although
more common, was far from pervasive. In short, the self-reported effects
data do not support the assumption of wide-scale psychological harm from
CSA. This conclusion is further suggested by students' self-reported
reactions. The finding that two thirds of SA men and more than one fourth of
SA women reported neutral or positive reactions is inconsistent with the
assumption of pervasive and intense harm. It is not parsimonious to argue
that boys or girls who react neutrally or positively to CSA are likely to
experience intense psychological impairment. To argue that positive or
neutral reactions are consistent with intense harm, it seems logical to
first demonstrate that negative reactions are consistent with intense harm.
However, the magnitude of the CSA-adjustment relation was small for women,
despite the reporting of negative reactions by a majority of SA women. This
low intensity finding for generally negative CSA experiences is inconsistent
with an expectation of intense harm from nonnegative CSA experiences.
Moderators
Multiple regression analyses showed that the intensity of the relationship
between CSA and adjustment varied reliably as a function of gender, level of
consent, and the interaction of these
[Page 45]
two factors. It is noteworthy that neither the level of contact nor the
interaction between gender and level of contact was related to intensity.
These latter results failed to provide support for the common belief that
contact sex is more harmful than noncontact sex or that contact sex for
girls is especially harmful. These conclusions, however, should be viewed
cautiously because of the overlapping nature of the two levels of the
contact variable (i.e., contact only versus contact and noncontact sex).
This same caveat applies to consent because its two levels (unwanted versus
willing and unwanted) were overlapping as well. The finding that most women
(72%) reacted negatively to their CSA at the time it occurred implies that
most of this CSA was unwanted and that the overlap between the two levels of
consent was high. Thus, even though consent did not moderate intensity for
women, a true difference as a function of consent may have been obscured.
The finding that level of consent did moderate intensity for men is
consistent with less overlap between the two levels of consent for men,
because the majority of men (67%) reacted nonnegatively at the time.
Importantly, CSA was not related to adjustment for men in the willing and
unwanted level of the consent variable.
In separate moderator analyses, we examined how aspects of the CSA
experience moderated self-reported reactions and effects, as well as
symptoms. Although these results should be viewed cautiously because they
were usually based on a small number of samples, we found that only force
and incest moderated outcomes. The largest relation occurred between force
and self-reported reactions or effects, but force was unrelated to symptoms.
Incest moderated both symptoms and self-reported reactions and effects.
Penetration, duration, and frequency did not moderate outcomes. The
near-zero correlation between penetration and outcome is consistent with the
multiple regression analysis finding that contact sex did not moderate
adjustment. This result provides empirical support for Finkelhor's (1979 ,
p. 103) observation that our society's view of intercourse as the most
damaging form of CSA is "a well-ingrained prejudice" unsupported by
research. Composite measures consisting of various combinations of
moderators (e.g., incest, force, penetration) showed no association with
symptoms in four of five studies that constructed such measures. This
finding is consistent with Laumann et al.'s (1994) failure to find an
association between their composite variable (consisting of penetration,
number of older partners-abusers, relatedness of partner-abuser, frequency
of contacts, age when having contacts, duration of contacts) and adjustment
for SA respondents in their study of a U.S. national sample. It is important
to note, however, that these nonsignificant results may be attributable to
the additive nature of the composite variables. Composites based on two-way
or higher order interactions of moderators might have been more likely to
yield significant results, particularly if the interactions included incest
and force.
Child Sexual Abuse as a Construct Reconsidered
In light of the current findings, it is appropriate to reexamine the
scientific validity of the construct of CSA as it has been generally
conceptualized. In most studies examined in the current review, CSA was
defined based on legal and moral, rather than empirical and
phenomenological, criteria. This approach may form a defensible rationale
for legal restrictions of these behaviors, but is inadequate and may be
invalid in the context of scientific inquiry ( Okami, 1994 ). In science,
abuse implies that particular actions or inactions of an intentional nature
are likely to cause harm to an individual (cf. Kilpatrick, 1987 ; Money &
Weinrich, 1983 ). Classifying a behavior as abuse simply because it is
generally viewed as immoral or defined as illegal is problematic, because
such a classification may obscure the true nature of the behavior and its
actual causes and effects.
The history of attitudes toward sexuality provides numerous examples.
Masturbation was formerly labeled "self-abuse" after the 18th century Swiss
physician Tissot transformed it from a moral to a medical problem ( Bullough
& Bullough, 1977 ). From the mid-1700s until the early 1900s the medical
profession was dominated by physicians who believed that masturbation caused
a host of maladies ranging from acne to death ( Hall, 1992 ; Money, 1985 ),
and medical pronouncements of dangerousness were accompanied by moral
tirades (e.g., Kellogg, 1891 ). This conflation of morality and science
hindered a scientifically valid understanding of this behavior and created
iatrogenic victims in the process ( Bullough & Bullough, 1977 ; Hall, 1992 ;
Money, 1985 ). Kinsey et al. (1948) argued that scientific classifications
of sexual behavior were nearly identical with theological classifications
and the moral pronouncements of English common law in the 15th century,
which were in turn based on medieval ecclesiastic law, which was itself
built on the tenets of certain ancient Greek and Roman cults and Talmudic
law. Kinsey et al. noted that "[e]ither the ancient philosophers were
remarkably well-trained psychologists, or modern psychologists have
contributed little in defining abnormal sexual behavior" (p. 203). Behaviors
such as masturbation, homosexuality, fellatio, cunnilingus, and sexual
promiscuity were codified as pathological in the first edition of the
American Psychiatric Association's (1952) Diagnostic and Statistical Manual
of Mental Disorders. The number and variety of sexual behaviors labeled
pathological has decreased, but mental health professionals continue to
designate sexual behaviors as disorders when they violate current sexual
scripts for what is considered acceptable ( Levine & Troiden, 1988 ). This
history of conflating morality and law with science in the area of human
sexuality by psychologists and others indicates a strong need for caution in
scientific inquiries of sexual behaviors that remain taboo, with child
sexual abuse being a prime example (Rind, 1995 ).
As discussed previously, abuse implies that harm is likely to result from a
behavior. The results for SA male college students, using this scientific
conceptualization of abuse, highlight the questionable validity of the
construct CSA as defined and used in the studies examined in the current
review. For these male college students, 37% viewed their CSA experiences as
positive at the time they occurred; 42% viewed these experiences as positive
when reflecting back on them; and in the two studies that inquired about
positive self-perceived effects, 24% to 37% viewed their CSA experiences as
having a positive influence on their current sex lives. Importantly, SA men
across all levels of consent (i.e., both willing and unwanted experiences)
did not differ from controls in current psychological adjustment, although
SA men with unwanted experiences only did, implying that willingness was
associated with no impairment to psychological adjustment. The positive
reports of reactions and effects,
[Page 46]
along with normal adjustment for willing participants, are scientifically
inconsistent with classifying these male students as having been abused.
Their experiences were not associated with harm, and there appears to be no
scientific reason to expect such an association (i.e., predicting
psychologically harmful effects from events that produced positive reactions
lacks face validity). On the other hand, a minority of SA men did report
retrospectively recalled negative reactions, negative current reflections,
and negative self-perceived effects; moreover, unwanted CSA was associated
with adjustment problems. Assuming that negative reactions were associated
with unwanted CSA, the term abuse may be scientifically valid for the latter
students. Combining positive and negative responders into a single category
of abuse may incorrectly suggest harm for the former and simultaneously
dilute harm for the latter (Bauserman & Rind, 1997 ).
Some researchers have questioned their original definitions of sexual abuse
after assessing their results. For example, Fishman (1991) borrowed from
Finkelhor's (1979) definition to classify sexual abuse of boys mostly on the
basis of age discrepancies (i.e., sex between a boy of 12 or less and
someone at least 5 years older, or between a boy aged 13 to 16 with someone
at least 10 years older), stating that age differences implied sufficient
discrepancy in developmental maturity and knowledge to indicate
victimization. He found that SA men in his study did not differ from
controls on measures of adjustment and reported a wide range of reactions to
and effects from their CSA experiences (mostly positive or neutral).
In-depth interviews confirmed and elaborated the quantitative findings,
leading Fishman to question his original assumptions. He noted that the
men's stories altered his universal beliefs about the impact of
inappropriate sexual experiences on children, and stated that "to impose a
confining definition onto someone's experience does nothing to alter the
realities of that experience for the person" (pp. 284-285). Fishman
concluded by arguing for the use of language of a more neutral nature rather
than labels such as abuse, victim, and molestation-in short, for use of
empirical and phenomenological criteria in conceptualizing early sexual
relations, rather than legal or moral criteria.
The foregoing discussion does not imply that the construct CSA should be
abandoned, but only that it should be used less indiscriminately to achieve
better scientific validity. Its use is more scientifically valid when early
sexual episodes are unwanted and experienced negatively-a combination
commonly reported, for example, in father-daughter incest. 7 In general,
findings from the current review suggest that sociolegal definitions of CSA
have more scientific validity in the case of female children and adolescents
than for male children and adolescents, given the higher rate of unwanted
negative experiences for women. Nevertheless, as Long and Jackson (1993)
argued, because some women perceive their early experiences as positive, do
not label themselves as victims, and do not show evidence of psychological
impairment, it is important for researchers to be cautious in defining abuse
for both men and women in attempts to validly examine the antecedents and
effects of these experiences.
Summary and Conclusion
Beliefs about CSA in American culture center on the viewpoint that CSA by
nature is such a powerfully negative force that (a) it is likely to cause
harm, (b) most children or adolescents who experience it will be affected,
(c) this harm will typically be severe or intense, and (d) CSA will have an
equivalently negative impact on both boys and girls. Despite this widespread
belief, the empirical evidence from college and national samples suggests a
more cautious opinion. Results of the present review do not support these
assumed properties; CSA does not cause intense harm on a pervasive basis
regardless of gender in the college population. The finding that college
samples closely parallel national samples with regard to prevalence of CSA,
types of experiences, self-perceived effects, and CSA-symptom relations
strengthens the conclusion that CSA is not a propertied phenomenon and
supports Constantine's (1981) conclusion that CSA has no inbuilt or
inevitable outcome or set of emotional reactions.
An important reason why the assumed properties of CSA failed to withstand
empirical scrutiny in the current review is that the construct of CSA, as
commonly conceptualized by researchers, is of questionable scientific
validity. Overinclusive definitions of abuse that encompass both willing
sexual experiences accompanied by positive reactions and coerced sexual
experiences with negative reactions produce poor predictive validity. To
achieve better scientific validity, a more thoughtful approach is needed by
researchers when labeling and categorizing events that have heretofore been
defined sociolegally as CSA ( Fishman, 1991 ; Kilpatrick, 1987 ; Okami, 1994
; Rind & Bauserman, 1993 ).
One possible approach to a scientific definition, consistent with findings
in the current review and with suggestions offered by Constantine (1981) ,
is to focus on the young person's perception of his or her willingness to
participate and his or her reactions to the experience. A willing encounter
with positive reactions would be labeled simply adult-child sex, a
value-neutral term. If a young person felt that he or she did not freely
participate in the encounter and if he or she experienced negative reactions
to it, then child sexual abuse, a term that implies harm to the individual,
would be valid. Moreover, the term child should be restricted to
nonadolescent children ( Ames & Houston, 1990 ). Adolescents are different
from children in that they are more likely to have sexual interests, to know
whether they want a particular sexual encounter, and to resist an encounter
that they do not want. Furthermore, unlike adult-child sex, adult-adolescent
sex has been commonplace cross-culturally and historically, often in
socially sanctioned forms, and may fall within the "normal" range of human
sexual behaviors ( Bullough, 1990 ; Greenberg, 1988 ; Okami, 1994 ). A
willing encounter between an adolescent and an adult with positive reactions
on the part of the adolescent would then be labeled scientifically as
adult-adolescent sex, while an unwanted encounter with negative reactions
would be labeled adolescent sexual abuse. By drawing these distinctions,
researchers are likely to achieve
[Page 47]
a more scientifically valid understanding of the nature, causes, and
consequences of the heterogeneous collection of behaviors heretofore labeled
CSA.
Finally, it is important to consider implications of the current review for
moral and legal positions on CSA. If it is true that wrongfulness in sexual
matters does not imply harmfulness ( Money, 1979 ), then it is also true
that lack of harmfulness does not imply lack of wrongfulness. Moral codes of
a society with respect to sexual behavior need not be, and often have not
been, based on considerations of psychological harmfulness or health (cf.
Finkelhor, 1984 ). Similarly, legal codes may be, and have often been,
unconnected to such considerations ( Kinsey et al., 1948 ). In this sense,
the findings of the current review do not imply that moral or legal
definitions of or views on behaviors currently classified as CSA should be
abandoned or even altered. The current findings are relevant to moral and
legal positions only to the extent that these positions are based on the
presumption of psychological harm.
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Notes
[The notes are originally placed at the same page they appear]
* Bruce Rind, Department of Psychology, temple University;
Philip Tromovitch, Graduate School of Education, University of Pennsylvania;
Robert Bauserman, Department of Psychology, University of Michigan.
We thank Ralph Rosnow for his meta-analytic advice and comments on an
earlier draft and Steve Wexler for his helpful comments.
Correspondence concerning this article should be addressed to Bruce Rind,
Department of Psychology, Temple University, Philadelphia, Pensylvania 19122
[USA].
Electronic mail may be sent to rind@vm.temple.edu
1 Ralph Rosnow served as the expert meta-analyst. In an attempt to resolve
our discrepancies with Jumper, we contacted her. She informed us that her
meta-analysis came from her master's thesis and that all her data and
calculations were in storage in a different part of the country. She
therefore advised us that she would be unable to help but nevertheless
suggested that we proceed with our report, mentioning that we were unable to
resolve the discrepancies with her.
2 Combination of CSA subgroups was achieved by computing a weighted mean,
and by computing the "true" variance of all CSA participants. The "true"
variance is the value that would have resulted from computing the variance
of the scores of all CSA participants irrespective of their subgrouping.
This value was obtained by (a) adding the sum of the squares of the CSA
subgroups to get the within sum of squares for these subgroups, (b)
calculating the between-means sum of squares for the CSA subgroups, (c)
adding the within and between sum of squares to get the sum of squares total
for the subgroups, and (d) dividing the sum of squares total by the number
of CSA scores minus 1. Using the derived mean and variance, the CSA group
was then compared with the control group. This procedure produced results
that were comparable to those of most other studies that used one overall
CSA group and was thus chosen over contrasting the means of the CSA
subgroups with the control mean.
3 Appendixes containing other effect sizes for other analyses in the Results
section (i.e., symptom-level, moderator analyses, male-female differences,
family environment-CSA relations, and family environment-symptom relations)
can be obtained by writing to Bruce Rind.
4 It would have been preferable to code and examine effect sizes before and
after statistical control, rather than the number of (non)significant
relations. Because of inadequate reporting of the statistics that resulted
from statistical control, this procedure could not be used.
5 Despite all the empirically based similarities between the college and
national populations, it is tempting to speculate that certain differences
exist. Persons with extremely harmful CSA episodes may be unable to attend
college or remain there once they have begun. In this way, surveys of
college students may miss extreme cases of CSA, limiting the
generalizability of findings from the college population. Nevertheless, the
results of the current review, while not demonstrating equivalence between
the two populations, strongly suggest that the gulf between them is narrow,
and much narrower than child abuse researchers have generally acknowledged.
6 It is important to note that, under certain circumstances, extrafamilial
CSA may be likely to affect adversely family functioning, as in cases where
CSA episodes become known to the family and to the police. In this
situation, tension may arise in the family, representing secondary
consequences of the CSA (cf. Baurmann, 1983 ). Most commonly, however, CSA
episodes do not come to the attention of the family or police; for example,
Laumann et al. (1994) , in their national probability sample, found that
only 22% of their SA respondents ever told anyone. Addition- ally, it should
be noted, because of its salience, the revelation, or even fear of
revelation, of CSA events may inflate a SA person's perception of negative
aspects of family environment, particularly in retrospective measures.
7 Two of the three outliers identified in the sample-level meta-analysis
involved samples consisting largely of incest cases ( Jackson et al., 1990 ;
Roland et al., 1989 ). The CSA experiences of these women, associated with
relatively large effect sizes, may capture more accurately the essence of
abuse in a scientific sense-that is, more persuasive evidence of harm
combined with the likely contextual factors of being unwanted and perceived
negatively.
Appendix
Definitions of Child Care Abuse (CSA), Prevalence Rates, and Sample-Level
Effect Sizes (i.e.) Psychological Correlatesm in Using College Student
Samples
Note
a [In 'column' 1:] U = only unwanted sex included in definition;
a = all types of sex, unwanted and willing, included.
[In 'column' 2:] C = only physical contact sex included in definition;
b = both contact and noncontact experoenced included.
Next, upper age of "child" is given first; then, the minimum age of other
person is given
(e.g., w/ 5+ means with someone at least 5 years older); last, other
conditions for CSA are
given.
b Ns are number of subjects used for prevalences; may be different from
effect size Ns.
Under CSA, percentage of sample with CSA experiences is provided.
c Ns are numbers of subjects in analysis of psychological correlates of CSA;
rs are the sample-level effect sizes. "Reaction data only" indicates data
were availble only
for self-reported reaction of effects.
d Dashes indicate that an effect size for psychological correlates was not
computable - only
data for self-reported reactions or effects were provided.
e Represents N and r for female and male students combined; rsults were not
reported separately, thus the dashes on the next row.
Sample-level
Operational definition Prevalenceb effect
Study Gen- of CSAa sizesc
der
N CSA N r
Alexander & Lupfer U C (not specified),
(1978) F relative 586 25% 431 .02
Bailey & Gibbons a ? self-labeled as
(1989) F "sexually molested" 294 13% 294 .04
Beckman & Burns
(1990) F a b <12 w/ "adult" 198 10% 182 .04
Bendixen, Muus &
Schei (1994) F U b <18 510 19% 510 .15
Bendixen, Muus &
Schei (1994) M U b <18 486 3% 486 .08
Bergdahl (1983) F a b <18 w/ "adult" 430 36% 355 .11
Brieree & Runtz
(1988a, 1988b, F a C <15 w/ 5+ 278 15% 224 .12
1990
Brubaker (1991) F a C <16 w/ 5+ 284 18% 155 .13
Brubaker (1994) F a C <16 w/ 5+ 400 25% -- --d
Cole (1988) F a C <18 w/ 5+; unwanted 2,740 21% 128 .10e
peer
Cole (1988) M a C <18 w/ 5+; unwanted 2,279 17% -- --
peer
Collings (1995) M U b <18 284 29% 284 .17
Condy et al. a C <16 w/5+ or 16 or --d
(1987) M over 359 16% --
Edwards & a C <16 w/5+ or force;
Alexander (1992) F 16-18 w/10+ or wanted 103 44% 97 .14
Everill & Waller
(1995) F U b <18 69 71% 69 .09
Finkelhor (1979, a b <13 w/ > 16;
1984) F 13-16 w/ 10+ (relative 530 19% 536 .11
or unwanted)
Finkelhor (1979, a b <13 w/ > 16;
1984) M 13-16 w/ 10+ (relative 226 9% 260 .12
or unwanted)
Fisher (1991) F a b 17 w/
Greenwald (1994) F 10+; unwanted; 214 41% 214 .03
intrafamilial
a b <17 w/ 5+; >17 w/
Greenwald (1994) M 10+; unwanted; 213 32% 213 -.09
intrafamilial
Harter, Alexander a C <18 w/ relative who
&Neimeyer (1988) F was 5+ 1,066 13% 85 .16
Hatfield (1988) M a C <14 w/ 5+ 213 12% 213 .06
Hauhaard & Emery a b <16 w/ 5+ or 16 or
(1989) F over 672 12% 186 .11e
Hauhaard & Emery a b <16 w/ 5+ or 16 or
(1989) M over 420 5% -- --
Higgins & McCabe a b <13 w/ 5+; 13-18 w/
(1994) F 10+ 199 24% 199 .16
Hrabrowy (1987) F U b <16 383 28% 383 .05
Jackson et al. a C <18 w/ relative who
(1990) F was 5+ 40 n/a 40 .36
Kinzl et al. a b <18, unwanted peer,
(1994, 1995) F sex now considered 202 22% 201 .08
abuse
Klein-Trull (1990) F a C <17wW/ 5+ or 271 11% .19
unwanted 58
Lam (1994) F a b <14 w/ adult or 264 18% 260 .01
unwanted
Landis (1956 F a b through adolescence 1,029 35% -- --d
w/ older partner
Landis (1956 M a b through adolescence 467 30% -- --d
w/ older partner
Long (1993) F a b <13 w/ 3+, 305 18% 305 .10
authority figure
Long & Jackson a b <13 w/ 5+; 13-16 w/ --d
(1993) F 10+ 137 n/a --
Maggio (1984) F a b <17 w/ 6+ 244 35% 477 -.02e
Maggio (1984) M a b < 17 w/ 6+ 233 36% -- --
Moor (1992) F U b <17 w/ 5+ 437 18% 321 .16
Nash & West (1985) F a b <16 w/ 5+ 54% -- --d
92
O'Neill (1991) F a b <13 w/ 5+, 13-16 w/ 365 17% -- --d
10+
O'Neill (1991) M a b <13 w/ 5+, 13-16 w/ 206 17% -- --d
10+
a C <13 w/ 5+; 13-16 w/
Pallotta (1992) F 10+; 275 20% 257 .13
<17 unwanted relative
Peters & Range
(1995) F U b <12 w/ 5+ 135 20% 266 .11e
Peters & Range
(1995) M U b <12 w/ 5+ 131 8% -- --
a b <13 w/ 5+; 13-16
Pizzolo (1990) F w/10+; relative, 308 23% 298 .13
unwanted peer
Predieri (1992) M a b <13 w/ 5+; 13-16 w/ 557 6% .15
8+; unwanted peer 62
Preuss (1988) F a b <13 w/ 5+; 13-17 w/ 402 50% 402 .05
10+; force
Preuss (1988) M a b <13 w/ 5+; 13-17 w/ 288 20% 288 .04
10+; force
Rau (1994) M U b <12 w/ 5+; 12-16 w/ n/a .10
10+ 60 60
Rew, Esparza & U b <18 w/ older
Sands (1991) F partner 111 50% 111 .11
Rew, Esparza & U b <18 w/ older
Sands (1991) M partner 160 23% 160 .21
Risin & Koss a b <13 w/ 5+; 13 w/ --d
(1987) M 8+; unwanted peer 2,922 7% --
Roland, Zelhart &
Dubes (1989) F U b 16; <16 w/ 154 40% 154 .02
relative > 16; unwanted
Sarbo (1985) M a b <12 w/ > 16; <16 w/ 112 22% 112
relative > 16; unwanted .055
Schultz & Jones --d
(1983) F a b <12 w/ 16 or over n/a n/a --
Schultz & Jones --d
(1983) M a b <12 w/ 16 or over n/a n/a --
Sedney & Brooks
(1984) F a b "while growintg up" 301 17% 102 .15
Silliman (1993) F ?? (not specified) n/a -.25
66 66
Smolak, Levine & a b <13 w/ 5+; 13-16 w/
Sullins (1990) F 10+ 298 23% 269 .12
Urquiza (1989) M a C <18 w/ 5+ 2,016 17% .16
88
West & Woodhouse a b <11 w/ 16 or over; --d
(1993) M 11-16 w/ 18 or over 182 37% --
White & Strange U b <17 w/ 18 or over
(1993) F who was 5+ 131 14% 105 -.01
Wisniewski (1990) F a b <14 w/ 5+; unwanted 3,187 29% 3,187 .11
Yama et al. (1992, a b <13 w/ 5+; 13-16 w/
1993) F 10+ 420 10% 156 .21
Zetzer (1991) F U b <18; relative 338 64% 338 .02