Multiple victimization of Spanish adolescents: a multilevel analysis.
Lila, Marisol ; Herrero, Juan ; Gracia, Enrique 等
Adolescents are among the most vulnerable to victimization (Hamby
& Finkelhor, 2001). Some studies indicate that adolescents are
victimized at two or three times the rate of adults, and experience
victimization episodes that are equally injurious as those perpetrated
against adults (Finkelhor, Ormrod, Turner, & Hamby, 2005a; Wells
& Rankin, 1995). Moreover, recent research confirms the pervasive
exposure of children and adolescents to violence, crime, maltreatment,
and other forms of victimization as a routine part of ordinary
childhood. For example, in a study using a United States representative
sample of adolescents, Finkelhor et al. (2005a) found that more than
half of the participants had experienced a physical assault, more than I
to 4 a property victimization, more than 1 in 8 a form of child
maltreatment, 1 in 12 a sexual victimization, and more than 1 in 3 had
witnessed violence or another form of indirect victimization.
Research on adolescents' victimization has increased, and most
of the studies pay attention to prevalence, antecedents and/or
consequences of specific forms of victimization (Finkelhor, Ormrod,
Turner, & Hamby, 2005a,b; Saunders, 2003). For example, there is a
growing number of studies on sexual abuse of adolescents (e.g.,
Finkelhor & Hashima, 2001; Kendall-Tackett, Williams, &
Finkelhor, 1993), bullying (e.g., Duncan, 1999; Nansel, Overpeck,
Puilla, Ruan, & Scheidt, 2003), or the witnessing of domestic
violence (e.g., Fantuzzo & Mohr, 1999; Kolbo, Blakely, &
Engleman, 1996). Likewise, various forms of adolescent victimization
have been linked to a multitude of negative outcomes (see Saunders,
2003, for a review). For example, youth victimization has been
associated with delinquent behavior (Howing, Wodarski, Lurtz, Gaudin,
& Herbst, 1990; Kilpatrick, Saunders, & Smith, 2002; Smith &
Thornberry, 1993), problematic substance use (Dembo, Williams,
Schmeidler, Berry, Wothke, Getreu et al., 1992; Kilpatrick, Acierno,
Saunders, Resnick, Best, & Schnurr, 2000; Kilpatrick, Ruggiero,
Acierno, Saunders, Resnick, & Best, 2003), mental health problems
(Epstein, Saunders, Kilpatrick, & Resnick, 1998; Kilpatrick,
Saunders, & Smith, 2002; Turner, Finkelhor, & Ormrod, 2006),
medical and physical problems (Hanson, Davis, Resnick, Saunders,
Kilpatrick, & Holmes et al., 2001) suicidality (Bryant & Range,
1995; Saunders, Kilpatrick, Hanson, Resnick, & Walker, 1999), risk
of revictimization (Saunders, Kilpatrick, & Resnick, 1998), and
other undesirable consequences. As Saunders (2003) pointed out, "It
is not uncommon for victims of violence to exhibit certain types of
psychiatric disorders or dysfunctional behaviors at rates three, four,
and even five times greater than nonvictims" (p. 358).
Additionally, a growing body of research suggests that many of the
types of violence are not unique, singular experiences. Rather, it is
common for children and adolescents to have been victims of several
types of violence on multiple occasions (Green, Goodman, Kupronick,
Corcoran, Petty, & Stocton et al., 2000; Kilpatrick & Saunders,
1999; Saunders, 2003). For example, Menard and Huizinga (2001), in their
high-risk sample of adolescents, found "chronic multiple
victimization" to be the norm. In fact, adolescents who have been
exposed to only a single episode of one type of violence are a minority
of victimized adolescents (Saunders, 2003). As Finkelhor et al. (2005a)
noted, recent research confirms that multiple victimization is common,
that different kinds of victimization are interrelated--adolescents who
experience one type are also likely to be exposed to other forms of
victimization--and that it is more likely that multiple victimized
adolescents present distress and other psychopathological symptoms
(Finkelhor, Ormrod, & Turner, 2007; Lauritsen & Quinet, 1995;
Manion & Wilson, 1995; Outlaw, Ruback, & Britt, 2002). Also, not
accounting for multiple victimization forms can make it difficult to
identify those adolescents with higher risk for victimization or those
victimized chronically (Kochenderfer Ladd & Ladd, 2001). In the
study cited above by Finkelhor et al. (2005b), nearly one half of the
sample had experienced more than one type of direct or indirect
victimization. In these authors' words "this suggests the
degree to which studies focusing on a single form of victimization miss
a much bigger picture" (p. 18).
Despite this growing body of research on multiple victimization,
little attention has been paid to the multiple contexts were multiple
victimization may take place, as well as to the different correlates
associated with multiple victimization in different contexts. As some
research suggests, adolescents and youth may be multiply victimized in
more than one context--home, school or the street (see Finkelhor et al.,
2007). For example, connections between intrafamily and extra-family
victimization have been observed (Baldry, 2003; Perry, Hodges, &
Egan, 2001). Nonetheless, with some exceptions (e.g. Appel & Holden,
1998), studies of adolescent victimization have not incorporated these
interconnections between contexts. This paper aims to address this gap
in the literature by examining correlates of multiple victimization in
different contexts (home, school, and the street).
The Present Study
Whereas in other countries the study of adolescent victimization
and interest in multiple victimization are increasing, in Spain this
kind of research is scarce. Little is known about the incidence of
multiple victimization among adolescents in Spain, and almost no
research is available on the correlates of multiple victimization in
different contexts. The aim of this paper is threefold. First, to
explore the incidence of different types of victimization (stealing,
hitting, insulting, threatening, blackmailing, and weapon intimidation)
in three different contexts (home, school, and street) in a
representative sample of Spanish adolescents. Second, to analyze
intercorrelations between contexts of multiple victimization. Third, to
analyze correlates of multiple victimization in three contexts. Using a
multilevel approach, individual and school level correlates of multiple
victimization will be analyzed. At the individual (student) level,
sociodemographic factors (age, gender) will be explored as they have
been found to be related to victimization in adolescents (e.g., Brown
& Bzostek, 2003; Finkelhor & Hashima, 2001; Finkelhor et al.,
2005a; Herrero, Estevez, & Musitu, 2006; Khoury-Kassabri,
Benbenishty, & Astor, 2004; Owens, Daly, & Slee, 2005; Van Dorn,
2004). The quality of family relationships and deviant behavior also
will be analyzed, as they have been considered theoretically relevant
variables related to child and adolescent victimization (e.g., Gerard
& Buehler, 1999; Herrero et al., 2006; Lila, van Asken, Musitu,
& Buelga, 2006; Perry, Hodges, & Egan, 2001; Lauritsen, 2003;
Lauritsen, Sampson, & Laub, 1991; Shaffer & Ruback, 2002). At
the school level, the type of school (public or private) will also be
analyzed as it has been associated with the likelihood of being
victimized (e.g., Clark & Lab, 2000; Dinkes, Cataldi, Kena, &
Baum, 2006; Lab & Clark, 1997; U.S. Department of Education, 1993).
METHOD
Participants
We used data from 1,908 adolescents 13-18 years old of the
Valencian Community (Spain). Multi-stage sampling procedures were
followed to obtain a representative sample of adolescents studying at
the time of the survey (year 2002). In the first stage, a random
selection of public and private schools in the Valencian Community was
carried out. At this stage, 39 schools were selected (20 public and 19
private). Principals of these schools were invited to participate in the
study. Although the level of commitment to the study was high among
principals, some of them conditioned their participation to examination
of the questionnaire prior to its administration. Others directly asked
for the results of the study once they were available. In all cases,
researchers complied with these requirements.
In the second stage, a random selection of adolescents proportional
to students in each school was performed. Letters with a brief
description of the program and explaining the need to collect data were
sent to families. This letter also included a no-consent form if parents
did not wish their children to take part in the program. No students
returned the no-consent form. Finally, trained personnel administered
the questionnaires in each classroom according to the schedule agreed
upon by principals and researchers. Students completed questionnaires in
a regular class period (1 hour) with only the trained personnel present.
The final sample consisted of 1,908 adolescents 13-18 years old (M
= 14.51, SD = 1.20) of whom 50.52% were boys. Due to the larger size of
public schools, 54.6% of the sample were from this type of school.
Outcome variables
Multiple victimization. Self-reported multiple victimization was
measured by asking students whether they had experienced any of six
situations in the street, at school, and at home (see Table 1). Three
measures of multiple victimization (range 0-6) were obtained summing up
the number of situations experienced in each context: multiple
victimization in the street, multiple victimization at school, and
multiple victimization at home. Means and standard deviations for these
measures of multiple victimization are presented in Table 1.
Insults (46.3%) and thefts (32.1%) were the most frequent
victimizations experienced in the street. A majority of students
indicated they had been insulted at school (63.4%)--clearly the most
common type of victimization in this context. Regarding the home
context, the percentage of situations experienced sharply decreased as
compared to the other two contexts.
Overall, adolescents experienced more types of victimization in the
street than at school and, at home. Victimization in the street (1.39)
and at school (1.22) double the level of victimization at home (0.53).
Only 10.8% (N = 207) of the sample noted no victimization at all in
all of the contexts analyzed; 22.7% (N = 434) experienced some
victimization in the three contexts; 35.6% (N = 680) experienced
victimization simultaneously in two contexts, and 30.8% (N = 587) in
only one context.
Student-level Variables
Family relationships. Participants were asked to estimate the
quality of relationships with family members: In general, how is your
relationship with persons in the household? Possible responses were: 1 =
very bad, 2 = bad, 3 = neither bad nor good, 4--good, and 5 = very good.
(M = 4.21, SD = 0.75).
Deviant behavior. This is a global concept that reflects behavior
that differs from accepted standards and bring disapproval; it comprises
both antisocial behavior (theft, vandalism, and damage to property),
aggression (verbal and physical), and substance use (see Herrero,
Estevez, & Musitu, 2006). A 33-item checklist was used to measure
deviant behavior. Items in this list were adapted from Emler and
Reicher's (1995) self-reported delinquencies checklist, that
measures deviant behavior such as theft (e.g., stole from a large store
while it was open), vandalism (e.g., broke windows of empty houses),
aggression (attacked an enemy in a public space), or drugs (e.g., took
illegal drugs), (M = 7.56, SD = 6.17).
Sociodemographic variables. Age (in years) and gender (1 = boy, 2 =
girl) were used as the variables.
Type of school was coded 1 for public school, and 2 for private
school.
ANALYTIC STRATEGY
Date present a hierarchical structure with students (level 1)
nested within schools (level 2). Multilevel modeling was used to allow
for inclusion of additional error terms that reflect the complex pattern
of variation introduced by the hierarchical structure of the data
(random effects) (Raudenbusch & Bryk, 2002). Since our interest was
in analyzing the associations of the covariates of the study with the
three outcome variables (three contexts of multiple victimization) we
estimated multivariate multilevel models using the HMLM2 module of the
statistical package HLM 6.02. Multivariate multilevel modeling allows
for estimation of the association of each covariate with a set of
intercorrelated outcome variables, while accounting for the hierarchical
structure of the data. This procedure has several advantages as compared
to analysis of three separate regression equations for each outcome
variable. Among them, it allows for statistical tests of the difference
in magnitude for each of the regression coefficients across outcome
variables. For instance, it allows us to answer such questions as: Is
the association of age and multiple victimization the same for all
contexts of victimization (street, school, and home)?
We checked for multicollinearity problems among predictors
examining the Variance Inflation Factor (VIF), all off-diagonal elements
in the variance-covariance (Tau) matrix for correlations close to 1 or
-1, and the diagonal elements for any elements close to zero, with no
indication of multicollinearity.
The multilevel analysis was performed in two steps. The starting
point was an empty model without explanatory variables in which the
total variance of victimization was partitioned into a component at each
level. This model (empty model) was used to test for random variation of
the outcome variables at different levels and, consequently, if a
multilevel approach was reasonable. In the second step we explored fixed
effects of variables at the student and school level and tested for
significant differences of coefficients across the three outcome
variables.
RESULTS
Table 2 presents zero-order correlations among the outcomes
variables and the zero-order correlations with the student and school
level covariates of the study.
As for correlations among the outcome variables and both student
and school level covariates, Table 2 shows a different pattern for each
context of victimization. Thus, while some covariates are highly
correlated with all contexts of victimization (family relationships),
others are correlated only with some contexts of victimization (gender,
age, deviant behavior, and type of school). Results noted in Table 2
suggest that those adolescents who experience victimization in one
context tend also to experience victimization in other contexts. These
results, however, do not take into account the hierarchical structure of
the data, and they also do not provide statistical significance of the
strength of association of each covariate with each context of
victimization relative to other contexts.
Results shown in Table 3 take into account these circumstances and
allow us to compare the relative strength of the association of each
covariate with the three contexts of victimization while also taking
into account the hierarchical structure of the data. At the bottom of
Table 3 random variation is shown of the outcome variables at the
student and school level for both the empty and final model. In first
examining the results for the empty model (with no predictors), we find
random variation of victimization both between students and schools.
This suggests that we need to control for the hierarchical structure of
the data (multilevel approach). Adding all covariates reduces random
variation both at the student and school level. For the student level,
the reduction is 42% (0.29/0.40 + 0.29 = 0.42). For the school level it
is 33%
In examining the statistical significance of random effects for the
model presented in Table 3, we can conclude that although the covariates
substantially reduced random variation at the student level, there is
still some variation that the model cannot account for, and that the
inclusion of other relevant student-level covariates would be
appropriate. For the school level, we note that no random variation is
left by the model, suggesting that both student-level and school-level
covariates account for all the between-schools variations. In other
words, once we controlled for characteristics of students within school
and type of school, all of the sampled schools showed similar levels of
victimization.
Since parameters in Table 3 are centered around the grand mean, the
intercept may be interpreted as the level of victimization of an average
student of the sample. Adding (or subtracting) statistically significant
parameters to the intercept give us the estimated level of victimization
for specific sociodemographic groups and/or specific levels of other
covariates. For instance, the average student in this sample experienced
1.38 situations of victimization in the street. An 18-year-old boy with
poor family relationships, who is highly engaged in delinquent behaviors
will experience an estimated 4.12 situations in the street. The maximum
level of victimization at school would be for a boy with the poorest
family relationships and the highest level of deviant behavior
(estimated at 2.06). Likewise, adolescents with the poorest family
relationships and higher levels of delinquency, mainly students
attending private schools, would experience an estimated 1.54 situations
of victimization at home.
An important feature of multivariate multilevel models is the
possibility of comparing the strength of association of the covariates
with each of the outcome variables, once we take into account that these
outcome variables are intercorrelated (see note in Table 3). Table 3
also shows that some covariates are statistically associated with all
different outcomes while others are associated only with some of the
outcome variables. This had been forecasted in Table 2, but the
multilevel results of Table 3 allow us to formally test the multivariate
associations among covariates and outcomes.
When we take into account the adolescent scores in all the
covariates of the study, we see that the association of age with
multiple victimization at home is no longer significant. Family
relationships are a significant covariate of all contexts of multiple
victimization, suggesting that victimized adolescents have poorer
quality family relationships. When testing for the statistical
significance of these associations across different contexts of multiple
victimization, we can conclude that those victimized at home have the
strongest association, while those victimized at school or in the street
have similar associations. Deviant behavior is also a significant
correlate of all contexts of multiple victimization. Adolescents who
engage in more deviant behaviors are also more victimized in the three
contexts analyzed in this study (street, school, and home). This
positive association is greater for victimization in the street.
As for the covariates that are related only to some contexts of
victimization, gender is associated with victimization in the street and
at school. Girls have lower levels of victimization in these contexts
than do boys, although both genders present similar levels of home
victimization. Also, the gender-victimization relationship is greater
for multiple victimization in the street. The average boy will
experience 1.38 experiences of victimization in the street whereas an
average girl will experience 0.86 (1.38-0.52 = 0.86). This means that
average girls are 48% less exposed to victimization experiences in the
street than are boys. For victimization at school, this percentage
decreases sharply to 15%.
As to age, there is a positive association with victimization in
the street but not with the remaining two contexts of victimization
(school and home). The older participants of the study experience more
victimization in the street but their level of victimization at school
and at home remained similar to that of, the younger participants. We
also found that students from private schools experienced more
victimization at home than those attending public schools (20% more),
but their levels in other contexts of victimization equaled those of
adolescents attending public schools.
DISCUSSION
The present study aimed to explore multiple victimization in a
representative sample of 1,908 students 13-18 years old living in the
Valencian Community, Spain. First we analyzed the incidence of different
types of victimization (stealing, hitting, insulting, threatening,
blackmailing, and weapon intimidation) in three different contexts
(home, school, and street). We found that multiple victimization in the
street was the most frequent, followed by school, and finally, with the
lowest levels in the sample, at home. Among the students analyzed, the
number of victimization experiences in the street and at school was
twice the number of victimization experienced at home. We also found
that only a minority (10.8%) of adolescents were not victimized in any
context, and that most respondents experienced victimization at least in
two (36.6%) or three (22.7%) of the contexts. These results support
other research conducted in different countries indicating that multiple
victimization in adolescence appears to be the rule rather than the
exception (Green, Goodman, Kupronick, Corcoran, Petty, & Stocton et
al., 2000; Kilpatrick & Saunders, 1999; Menard & Huizinga, 2001;
Saunders, 2003). As several scholars have pointed out (e.g., Green et
al., 2000; Kilkpatrick & Saunders, 1999; Saunders, 2003), multiple
victimization in adolescence is not uncommon and adolescents who
experience one type of victimization are likely to be exposed to other
types. For example, Finkelhor et al. (2007) observed that previously
victimized children, particularly those experiencing child maltreatment
or family violence, also appear to be at greater risk of subsequent
victimizations (Duncan, 1999a,b). Moreover, when observed over time in
schools, some children appear to be chronically targeted year aider year
(Perry et al., 2001). In this respect, we also found that the three
contexts of multiple victimization were intercorrelated, suggesting that
those adolescents who experience multiple victimization in one context
tend also to experience multiple victimization in other contexts (Appel
& Holden, 1998; Finkelhor et al., 2007). To account for the fact
that some adolescents tend to be victimized in different contexts,
Finkelhor et al. (2007) suggest that the clustering of victimization may
be explained by a number of factors that increase the risk; e.g.,
families and neighborhoods (Cicchetti & Lynch, 1993),
characteristics of children, such as pre-existing psychological problems
or poor social interactional skills (e.g., Finkelhor, Ormrod, &
Turner, in press; Perry et al., 2001; Tseloni & Pease, 2003), poor
supervision, or social isolation (e.g., Korbin, 2003; Gracia &
Musitu, 2003).
In this study we also analyzed correlates of multiple victimization
using a multivariate multilevel regression approach. This allowed us to
control both for the intercorrelation of the outcome variables (multiple
victimization in the street, at school, and at home) and the
hierarchical structure of the data (students nested within schools).
This also allowed testing for the significantly statistical differences
of the strength of each covariate with each context of victimization.
Results indicated that some covariates were significantly associated
with victimization in all contexts (family relationships and deviant
behavior) while other covariates were statistically related to only some
contexts of victimization (gender, age, and type of school).
In relation to gender, we found that this variable was related to
victimization in the street and at school. Boys were more victimized
than girls in this context. These results are consistent with previous
research showing a greater victimization risk for boys (e.g., Brown
& Bzostek, 2003; Finkelhor & Hashima, 2001; Finkelhor et al.,
2005b; Herrero et al., 2006). We also found age-related differences in
victimization, but only for multiple victimization in the streets. Our
findings show that multiple victimization in the streets is more common
among older adolescents. A possible explanation is that as children get
older they acquire greater autonomy and use the streets without parental
supervision, which in turn makes them more vulnerable to victimization
(Bilchik, 1999). In this respect, we agree with Finkelhor et al. (2007)
in that future research should further examine whether multiple
victimization is a condition that is more difficult to escape at older
ages. Adolescents reporting poorer quality of family relationships also
reported higher levels of victimization in each context. These results
are consistent with previous studies showing a relationship between a
negative family environment and a greater risk of victimization (Gerard
& Buchler, 1999; Smith, Bowers, Binney, & Cowie, 1993).
According to Perry, Hodges and Egan (2001) a possible explanation of
this relationship is that negative family relationships set up
internalized cognitive "victim schemas" in some children, that
may lead adolescents to behave in a manner that make them more
vulnerable to victimization by peers. Deviant behavior was also
positively associated with all types of victimization, although this
association was greater in the street. A substantial body of research
reports a positive association between deviant behavior and
victimization (see Herrero et al., 2006, for a review).
Finally, we found a relationship only between type of school and
multiple victimization at home (not in the schools or the streets), with
multiple victimization at home being greater for students of private
schools. This finding is somewhat surprising as results of previous
studies found that adolescents who attended public schools had more
knowledge of and experience with crime and threats than did those in
private schools (e.g., De Voe, Peter, Noonan, Snyder, & Baum, 2005).
This is an issue that deserves further study.
Research on multiple victimization in different contexts also has
implications for future research on basic issues such as its impact on
the psychological and social adjustment of adolescents. As Finkelhor et
al. (2005a) suggested, the total number of different victimizations is a
more important predictor of negative outcomes than the presence of any
particular type of victimization. However, most studies do not control
for the effects of other types of victimization when evaluating the
potential impact of a particular type of violence (Rossman &
Rosenberg, 1998; Saunders, 2003). Not taking into account multiple
victimization leads to problems such as the underestimation of the
number and diversity of adolescents' victimization or to difficulty
in understanding the relationship among different victimization forms
(Finkelhor et al., 2005b). Outcomes apparently associated with one type
of violence might well be the result of another type of violence, the
cumulative result of exposure to multiple types of violence, and/or a
complex interaction of violence types (Saunders, 2003). Furthermore,
adolescents victimized in different ways and in different contexts might
be more affected than children repeatedly victimized by just one person
or in just one context (Cohen, Perel, DeBellis, Friedman, & Putnam,
2002; Finkelhor, Ormrod, & Turner, 2007). In this regard Finkelhor
et al. (2007) suggest that it is important for practitioners to identify
children who have experienced multiple victimizations: "Because of
their higher levels of traumatic symptomatology, poly-victims may merit
priority attention" (p. 20).
Overall, our findings suggest the need for a more multidimensional
approach to adolescent victimization than the one that has been
characteristic of the field to date. Researchers and policy makers
concerned about victimization in adolescence need to be more aware of
the multiple contexts of victimization, its mutual connections, and its
correlates. This multidimensional approach would more importantly yield
benefits for victimized adolescents by suggesting intervention and
prevention strategies.
REFERENCES
Appel, A., & Holden, G. W. (1998). The co-occurrence of spouse
and physical child abuse: A review and appraisal. Journal of Family
Psychology, 12(4), 578-599.
Baldry, A. C. (2003). Bullying in schools and exposure to domestic
violence. Child Abuse & Neglect, 27, 713-732.
Bilchik, S. (1999). Violence after school. Juvenile Justice
Bulletin, November (NJC 178992).
Brown, B. V., & Bzostek, S. (2003). Violence in the lives of
children. Child Trends DataBank: Cross Currents, 1, 1-13.
Bryant, S., & Range, L. M. (1995). Suicidality in college women
who were sexually and physically punished by parents. Violence and
Victims, 10, 195-201.
Cicchetti, D., & Lynch, M. (1993). Toward an
ecological/transactional model of community violence and child
maltreatment: Consequences for children's development. Psychiatry,
56, 96-118.
Clark, R. D., & Lab, S. P. (2000). Community characteristics
and in-school criminal victimization. Journal of Criminal Justice,
28(1), 33-42.
Cohen, J. A., Perel, J. M., DeBellis, M. D., Friedman, M. J., &
Putnam, F. W. (2002). Treating traumatized children: Clinical
implications of the psychobiology of posttraumatic stress disorder.
Trauma Violence & Abuse, 3(2), 91-108.
Dembo, R., Williams, L., Schmeidler, J., Berry, E., Wothke, W.,
& Getreu, A. et al. (1992). A structural model examining the
relationship between physical child abuse, sexual victimization and
marijuana/hashish use in delinquent youth: A longitudinal study.
Violence and Victims, 7, 41-62.
DeVoe, J. F., Peter, K., Noonan, M., Snyder, T. D., & Baum, K.
(2005). Indicators of School Crime and Safety: 2005 (NCES 2006-001/NCJ210697). U.S. Departments of Education and Justice.
Washington, DC: National Center for Education Statistics.
Dinkes, R., Cataldi, E. F., Kena, G., Baum, K., & Zinder, T. D.
(2006). Indicators of School Crime and Safety, 2006 (NCJ 214262).
Justice Department's Bureau of Justice Statistics (BJS) and the
Department of Education's National Center for Education Statistics.
Duncan, R. D. (1999). Peer and sibling aggression: An investigation
of intra- and extra-familial bullying. Journal of Interpersonal Violence, 14, 871-886.
Emler, N., & Reicher, S. (1995). Adolescence and delinquency:
The collective management of reputation. Oxford: Blackwell.
Epstein, J. N., Saunders, B. E., Kilpatrick, D. G., & Resnick,
H. S. (1998). PTSD as a mediator between childhood rape and alcohol use
among women. Child Abuse & Neglect, 22, 223-234.
Fantuzzo, J., & Mohr, W. (1999). Prevalence and effects of
child exposure to domestic violence. The Future of Children, 9(3),
21-32.
Finkelhor, D., & Hashima, P. (2001). The victimization of
children and youth: A comprehensive overview. In S. O. White (Ed.),
Handbook of youth and justice (pp. 49-78). New York: Kluwer
Academic/Plenum.
Finkelhor, D., Ormrod, R. K., & Turner, H. A. (2007).
Poly-victimization: A neglected component in child victimization trauma.
Child Abuse & Neglect, 31, 7-26.
Finkelhor, D., Ormrod, R. K., & Turner, H. A. (in press).
Revictimization patterns in a national logitudinal sample of children
and youth. Child Abuse & Neglect.
Finkelhor, D., Ormrod, R. K., Turner, H. A., & Hamby, S. L.
(2005a). The victimization of children and youth: A comprehensive,
national survey. Child Maltreatment, 10, 5-25.
Finkelhor, D., Ormrod, R. K., Turner, H. A., & Hamby, S. L.
(2005b). Measuring poly-victimization using the Juvenile Victimization
Questionnaire. Child Abuse & Neglect, 29, 1297-1312.
Gerard, L. M., & Buehler, C. (1999). Multiple risk factors in
the family environment and youth problem behaviors. Journal of Marriage
and the Family, 61, 343-361.
Gracia, E., & Musitu, G. (2003). Social isolation from
communities and child maltreatment: A cross-cultural comparison. Child
Abuse & Neglect, 27, 153-168.
Greeen, B. L., Goodman, L. A., Kupronick, J. L., Corcoran, C. B.,
Petty, R. M., & Stocton, P. et al. (2000). Outcomes of single versus
multiple trauma exposure in a screening sample. Journal of Traumatic
Stress, 13, 271-286.
Hamby, S. L., & Finkelhor, D. (2001). Choosing and using child
victimization questionnaires. Juvenile Justice Bulletin, March.
Hanson, R. F., Davis, J. L., Resnick, H. S., Saunders, B. E.,
Kilpatrick, D. G., & Holmes, M. et al. (2001). Predictors of medical
examinations following child and adolescent rapes in a national sample
of women. Child Maltreatment, 6, 250-259.
Herrero, J., Estevez, E., & Musitu, G. (2006). The
relationships of adolescent school-related deviant behavior and
victimization with psychological distress: Testing a general model of
the mediational role of parents and teachers across groups of gender and
age. Journal of Adolescence, 29, 671-690.
Howing, P. T., Wodarski, J. S., Lurtz, P. D., Gaudin, J. M., &
Herbst, E. N. (1990). Child abuse and delinquency: The empirial and
theoretical links. Social Work, 26, 244-249.
Kendall-Tackett, K. A., Williams, L. M., & Finkelhor, D.
(1993). Impact of sexual abuse on children: A review and synthesis of
recent empirical studies. Psychological Bulletin, 113, 164-180.
Khoury-Kassabri, M., Benbenishty, R., & Aster, R. (2004). The
contributions of community, family, and school variables to student
victimization. American Journal of Community Psychology, 34, 187-204.
Kilpatrick, D. G., & Saunders, B. E. (1999). Prevalence and
consequences of child victimization: Results from the National Survey of
Adolescents: Final report. Charleston, SC: Author.
Kilpatrick, D. G., Acierno, R., Saunders, B. E., Resnick, H. S.,
Best, C. L., & Schnurr, P. P. (2000). Risk factors for adolescent
substance abuse and dependence: Data from a national sample. Journal of
Consulting and Clinical Psychology, 68, 19-30.
Kilpatrick, D. G., Ruggiero, K. J., Acierno, R., Saunders, B. E.,
Resnick, H. S., & Best, C. L. (2003). Violence and risk of PTSD,
major depression, substance abuse/dependence, and comorbidity: Results
from the national survey of adolescents. Journal of Consulting and
Clinical Psychology, 71, 692-700.
Kilpatrick, D. G., Saunders, B. E., & Smith, D. W. (2002).
Research in brief: Youth victimization: Prevalence and implications (NCJ
194972). Washington, DC: U.S. Department of Justice, National Institute
of Justice.
Kochenderfer Ladd, B., & Ladd, G. W. (2001). Variations in peer
victimization: Relations to children's maladjustment. In J. Juvonen
& S. Graham (Eds.), Peer harassment in school: The plight of the
vulnerable and victimized (pp. 25-48). New York: Guilford.
Kolbo, J. R., Blakely, E. H., & Engleman, D. (1996). Children
who witness domestic violence: A review of empirical literature. Journal
of Interpersonal Violence, 11(2), 281-293.
Korbin, J. E. (2003). Neighborhood and community connectedness in
child maltreatment research. Child Abuse & Neglect, 27, 137-140.
Lab, S. P., & Clark, R. D. (1997). Discipline, Control and
School Crime: Identifying Effective Intervention Strategies. Washington,
DC: National Institute of Justice.
Lauritsen, J. L. (2003). How families and communities influence
youth victimization (Juvenile Justice Bulletin). Washington, DC: Office
of Juvenile Justice and Delinquency Prevention.
Lauritsen, J. L., & Quinet, K. F. D. (1995). Repeat
victimization among adolescents and young adults. Journal of
Quantitative Criminology, 11(2), 143-166.
Lauritsen, J. L., Sampson, R. J., & Laub, J. H. (1991). The
link between offending and victimization among adolescents. Criminology,
29(2), 265-292.
Lila, M. S., van Aken, M., Musitu, G., & Buelga, S. (2006).
Family and adolescence. In S. Jackson & L. Goosens (Eds.), Handbook
of adolescent development (pp. 154-174). Hove: Psychology Press.
Manion, I. G., & Wilson, S. K. (1995). An examination of the
association between histories of maltreatment and adolescent risk
behaviors. Ontario:
Minister of National Health and Welfare.
Menard, S., & Huizinga, D. (2001). Repeat victimization in a
high-risk neighborhood sample of adolescents. Youth & Society, 32,
447-472.
Nansel, T. R., Overpeck, M. D., Pilla, R. S., Ruan, W. J., &
Scheidt, P. C. (2003). Relationships between bullying and violence among
US youth. Archives of Pediatrics and Adolescent Medicine, 157(4),
348-353.
Outlaw, M., Ruback, B., & Britt, C. (2002). Repeat and multiple
victimizations: The role of individual and contextual factors. Violence
and Victims, 17(2), 187-204.
Owens, L., Daly, A., & Slee, P. (2005). Sex and age differences
in victimization and conflict resolution among adolescents in a South
Australia School. Aggressive Behavior, 31, 1-12.
Perry, D. G., Hodges, E. V. E., & Egan, S. K. (2001).
Determinants of chronic victimization by peers: A review and new model
of family influence. In J. Juvonen & S. Graham (Eds.), Peer
harassment in school: The plight of the vulnerable and victimized (pp.
73-104). New York: Guilford Press.
Raudenbusch, S., & Bryk, A. (2002). Hierarchical linear and
nonlinear models: Applications and data analysis methods. London: Sage.
Rossman, B. B. R., & Rosenberg, M. S. (1998). Maltreated
adolescents: Victims caught between childhood and adulthood. Journal of
Aggression, Maltreatment & Trauma, 2(1), 107-129.
Saunders, B. E. (2003). Understanding children exposed to violence:
Toward an integration of overlapping fields. Journal of Interpersonal
Violence, 18(4), 356-376.
Saunders, B. E., Kilpatrick, D. G., & Resnick, H. S. (1998).
Victim, incident, and offender characteristics of child rape as risk
factors for adult rape among women: Results from the National
Women's Study. Paper presented at the annual meeting of the
International Society for Traumatic Stress Studies, Washington, DC.
Saunders, B. E., Kilpatrick, D. G., Hanson, R. F., Resnick, H. S.,
& Walker, M. E. (1999). Prevalence, case characteristics, and
long-term psychological correlates of child rape among women: A national
survey. Child Maltreatment, 4, 187-200.
Shaffer, J. N., & Ruback, R. B. (2002). Violent victimization
as a risk factor for violent offending among juveniles. Juvenile Justice
Bulletin, December (NCJ 195737).
Smith, P. K., Bowers, L., Binney, V., & Cowie, H. (1993).
Relationships of children involved in bully/victim problems at school.
En S. Duck (Ed.), Learning about relationships, understanding
relationship processes (pp. 184-212). Londres: Sage Publications.
Smith, C. A., & Thornberry, T. P. (1993). The relationship
between childhood maltreatment and adolescent involvement in
delinquency. Paper presented at the annual conference of Society for
Research in Child Development. New Orleans, LA.
Tseloni, A., & Pease, K. (2003). Repeat personal victimization:
"Boosts" or "flags"? British Journal of Criminology,
43, 196-212.
Turner, H. A., Finkelhor, D., & Ormrod, R. (2006). The effect
of lifetime victimization on the mental health of children and
adolescents. Social Science & Medicine, 62, 13-27.
U.S. Department of Education, National Center for Education
Statistics (1993). National Household Education Survey.
Van Dorn, R. (2004). Correlates of violent and non-violent
victimization in a sample of public high school students. Violence &
Victims, 19, 303-320.
Wells, L. E., & Rankin, J. H. (1995). Juvenile victimization:
Convergent validation of alternative measurements. Journal of Research
in Crime and Delinquency, 32(3), 287-307.
Juan Herrero. Department of Psychology, University of Oviedo,
Oviedo, Spain.
Enrique Gracia. Department of Social Psychology, University of
Valencia, Valencia, Spain.
Requests for reprints should be sent to Marisol Lila, Department de
Psicologia Social, Facultad de Psicologia, Avd. Blasco Ibanez, 21,
46010-Valencia, Spain. E-mail:
[email protected]
Table 1. Percentage of students by type and context of multiple
victimization. Means and standard deviations for victimization in
the street, at school and at home (n = 1908).
Contexts
Type of Street School
victimization
Thefts 32.1 12.0
Hits 16.7 18.4
Insults 46.3 63.6
Threats 22.8 15.1
Blackmails 8.2 10.5
Intimidation with weapon 11.2 1.0
Multiple Victimization (1) 1.39 (1.41) (a) 1.22 (1.16) (b)
[Mean (S.D.)]
Contexts
Type of Home
victimization
Thefts 6.2
Hits 10.0
Insults 18.8
Threats 4.0
Blackmails 11.8
Intimidation with weapon 0.5
Multiple Victimization (1) 0.53 (0.92)
[Mean (S.D.)]
(1) Number of types of victimization experienced by individuals
(a) > (b) > (c), p <.001
Table 2. Correlations of student and school-level covariates of the
study with multiple victimization (street, school, and home) and
correlations among outcome variables (n = 1908).
Contexts
Street School Home
Girls -0.25 *** -0.11 *** -0.02
Age 0.18 *** -0.02 0.08 ***
Quality of family relationships -0.15 *** -0.10 *** -0.28 ***
Deviant behavior 0.09 *** 0.03 0.06 *
Private Schools 0.01 0.02 0.08 **
Correlations among
outcome variables
School 0.31 *** --
Home 0.28 *** 0.34 *** --
a > b > c, p <.001
* p < .05; ** p < .01; *** p < .001
Table 3. Results from multivariate multilevel regression analysis
of correlates of different contexts of adolescent multiple
victimization (n = 1908). Parameters are unstandardized. All
covariates are centered around the grand mean. (1)
Contexts
Street School
Intercept 1.38 (a) 1.22 (b)
Student-level
Girls -0.52 *** (a) -0.18 *** (b)
Age 0.12 *** (a) -0.03 (b)
Family relationships -0.17 *** (b) -0.12 *** (b)
Deviant behavior 0.07 *** (a) 0.04 *** (b)
School-level
Private Schools -0.06 (b) -0.01 (b)
Random effects
Student-level 0.29(0.02) ***
School-level 0.01
(0.01)*
Model deviance 16.400
Contexts
Home
Intercept 0.54 (c) a > b > c, p < .001
Student-level
Girls -0.06 a > b, p < .001
Age -0.01 (b) a > b, p < .001
Family relationships -0.27 *** (a) a > b, p < .001
Deviant behavior 0.03 *** (b) a > b, p < .001
School-level
Private Schools 0.11 * (a) a < b, p < .001
Random effects
Student-level empty model = 0.40 (0.02) ***
School-level empty model = 0.02 (0.01) *
Model deviance empty model = 17.007
(1) Correlations among outcome variables are: street-school = 0.25,
street-home =0.20, school-home = 0.29, all significant at p < .001
* p < .05; ** p < .01; *** p < .001