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Bureau of Justice Statistics
Working Paper Series

Facility-level and Individual-level
Correlates of Sexual Victimization
in Juvenile Facilities, 2012
Leanne Heaton
David Cantor
Carol Bruce
Weijia Ren
John Hartge
WESTAT®, 1600 Research Boulevard, Rockville, MD 20850, www.westat.com
Allen J. Beck
Bureau of Justice Statistics
NCJ 249877

WP-2016-01
June 28, 2016

The authors acknowledge the support of the Bureau of Justice Statistics, Award #2009-RP-Bx-K001

Disclaimer: This paper is released to inform interested parties of research and to encourage discussion.
The views expressed are those of the authors and not necessarily those of the Bureau of Justice
Statistics or the U.S. Department of Justice. The authors accept responsibility for errors.

Abstract
This report examines facility impact on youth sexual victimization and also takes into account critical
youth-level predictors. The objectives are to examine the facility-level correlates of youth sexual
victimization, identify significant youth characteristics that can predict sexual victimization, and
describe the contextual circumstances surrounding youth victimization. This includes analysis of facility
attributes that correspond to the Prison Rape Elimination Act standards. Findings are based on the
2012 National Survey of Youth in Custody and a companion facility survey.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

ii

Table of Contents

Chapter

Page

NSYC-2 Findings Report: Correlates of Youth Sexual Victimization
(Part I) Facility- and Individual-Level Results .................................

1

1

Overview ................................................................................................

1

2

Research Questions ..............................................................................

2

3

Highlights and Key Findings ...............................................................

3

4

Facility-Level Findings .........................................................................

6

4.1
4.2
4.3
4.4
4.5

Structure of Juvenile Facilities ............................................
Staff Characteristics ..............................................................
Compliance With PREA Standards ...................................
Facility Reports of Youths’ History ...................................
Youth Reports of Involvement With Gangs and
Fighting ..................................................................................
Youth Reports of Vulnerability ..........................................
Youth Reports of Facility Order and Disorder ................
Youth Reports of Facility Safety and Fairness .................

7
15
21
40

Facility Profiles of Sexual Victimization ............................................

78

4.6
4.7
4.8
5

5.1
5.2
5.3
6

Facility Characteristics Associated With Both
Types of Sexual Assault (Youth-on-Youth and
Staff Sexual Misconduct) .....................................................
Facility Characteristics Exclusively Associated
With a Single Type of Sexual Assault ................................
Summary of Facility Profiles of Sexual
Victimization .........................................................................

50
57
65
71

78
78
82

Individual-Level Findings ....................................................................

83

6.1
6.2
6.3

83
85

6.4
6.5
6.6

Youth Demographic Characteristics ..................................
Youth Risk Characteristics ..................................................
Most Serious Offense, Gang Involvement, and
Fighting in the Facility .........................................................
Youth Reports of Facility Order and Disorder ................
Youth Reports of Safety and Fairness ...............................
Multivariate Findings for Youth-on-Youth
Sexual Assault and Staff Sexual Misconduct ....................

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

87
89
90
91

iii

Contents (continued)

Chapter

Page
7

Individual Profiles of Sexual Victimization .......................................
7.1
7.2
7.3
7.4

Youth Characteristics Associated With Both
Types of Sexual Assault (Youth-on-Youth and
Staff Sexual Misconduct) .....................................................
Youth Characteristics Exclusively Associated
With Youth-on-Youth Sexual Assault ...............................
Youth Characteristics Exclusively Associated
With Staff Sexual Misconduct.............................................
Summary of Individual Profiles of Sexual
Victimization .........................................................................

97

97
97
98
100

8

Discussion of Findings by Research Question .................................

101

9

Overall Discussion ................................................................................

102

NSYC-2 Findings Report: Correlates of Youth Sexual Victimization
(Part II) Multilevel Results ................................................................

103

10

Overview ................................................................................................

103

11

Research Questions ..............................................................................

104

12

Highlights and Key Findings ...............................................................

104

13

Multilevel Predictor Section ................................................................

105

13.1
13.2

Individual-Level Predictors .................................................
Facility-Level Predictors ......................................................

105
107

Results of the Final Multilevel Model Estimation by
Incident Type.........................................................................................

144

14.1
14.2

Youth-on-Youth Sexual Assault .........................................
Staff Sexual Misconduct ......................................................

144
145

Discussion of Findings and Limitations ............................................

147

14

15

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

iv

Contents (continued)

Chapter

Page
16

Methodology ..........................................................................................

150

16.1
16.2
16.3

Facility-Level Methodology .................................................
Individual-Level Methodology............................................
Multilevel Methodology .......................................................

150
154
157

A

Facility Questionnaire ........................................................................................

A1

B

Facility-Level Construct Measures ..................................................................

B1

C

Individual-Level Construct Measures .............................................................

C1

Facility-level victimization rate, by type of incident and selected
measures of facility structure, 2012 ..................................................................

8

2

Facility-level victimization rate, by type of incident and type of
treatment provided, 2012 ..................................................................................

10

3

Facility-level victimization rate, by type of incident and unit
assignment factors, 2012....................................................................................

11

Multivariate stepwise regression models of facility sexual
victimization, by youth-on-youth incidence and selected measures
of facility structure and type of treatment provided, 2012 ...........................

13

Multivariate stepwise regression models of facility sexual
victimization, by staff sexual misconduct incidence and selected
measures of facility structure and type of treatment provided,
2012 ......................................................................................................................

14

Facility-level victimization rate, by type of incident and staff
characteristics, 2012............................................................................................

15

Appendix

Table
1

4

5

6

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

v

Contents (continued)

Table
7

Page
Multivariate stepwise regression models of facility sexual
victimization, by youth-on-youth incidence and staff
characteristics, 2012............................................................................................

18

Multivariate stepwise regression models of facility sexual
victimization, by staff sexual misconduct and staff characteristics,
2012 ......................................................................................................................

20

Screening procedures for hiring new staff by primary facility type,
2012 ......................................................................................................................

21

10

Compliance with PREA standards: Monitoring procedures by
primary facility type, 2012 .................................................................................

22

11a

Compliance with PREA standards: Staffing ratio standards by
shift across all facilities, 2012 ............................................................................

22

11b

Compliance with PREA standards: Staffing ratio standards by
shift and primary facility type, 2012 .................................................................

23

12a

Compliance with PREA standards: Staffing ratio standards by
shift across secure facilities, 2012 .....................................................................

24

12b

Compliance with PREA standards: Staffing ratio standards by
shift across nonsecure facilities, 2012 ..............................................................

24

13

Facility-level victimization rate, by type of incident and facility
reports of compliance with PREA standards, 2012 ......................................

26

14

Facility-level victimization rate, by type of incident and youth
reports of facility compliance with PREA standards, 2012..........................

28

15

Multivariate stepwise regression models of facility sexual
victimization, by youth-on-youth incidence and facility and youth
reports of compliance with PREA standards, 2012 ......................................

36

Multivariate stepwise regression models of facility sexual
victimization, by staff sexual misconduct and facility and youth
reports of compliance with PREA standards, 2012 ......................................

38

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

vi

8

9

16

Contents (continued)

Table
17

Page
Facility-level victimization rate, by type of incident and youths’
history, 2012 ........................................................................................................

41

18

Facility-level victimization rate, by type of incident and facility
offense profile, 2012...........................................................................................

44

19

Multivariate stepwise regression models of facility sexual
victimization, by youth-on-youth incidence and youths’ history,
2012 ......................................................................................................................

46

Multivariate stepwise regression models of facility sexual
victimization, by staff sexual misconduct and youths’ history,
2012 ......................................................................................................................

49

Facility-level victimization rate, by type of incident and youth
reports of involvement with gangs and fighting, 2012..................................

51

Multivariate stepwise regression models of facility sexual
victimization, by youth-on-youth incidence and youth reports of
involvement with gangs and fighting, 2012 ....................................................

54

Multivariate stepwise regression models of facility sexual
victimization, by staff sexual misconduct and youth reports of
involvement with gangs and fighting in the facility, 2012 ............................

55

24

Facility-level victimization rate, by type of incident and youth
reports of vulnerability, 2012 ............................................................................

58

25

Multivariate stepwise regression models of facility sexual
victimization, by youth-on-youth incidence and youth reports of
vulnerability, 2012 ...............................................................................................

62

Multivariate stepwise regression models of facility sexual
victimization, by staff sexual misconduct and youth reports of
youth vulnerability, 2012 ...................................................................................

64

Facility-level victimization rate, by type of incident and youth
reports of facility order and disorder, 2012 ....................................................

66

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

vii

20

21
22

23

26

27

Contents (continued)

Table
28

Page
Multivariate stepwise regression models of facility sexual
victimization, by youth-on-youth incidence and youth reports of
facility order and disorder, 2012 .......................................................................

68

Multivariate stepwise regression models of facility sexual
victimization, by staff sexual misconduct and youth reports of
facility order and disorder, 2012 .......................................................................

70

Facility-level victimization rate, by type of incident and youth
reports of facility safety and fairness, 2012 .....................................................

72

Multivariate stepwise regression models of facility sexual
victimization, by youth-on-youth incidence and by youth reports
of safety and fairness, 2012 ...............................................................................

74

Multivariate stepwise regression models of facility sexual
victimization, by staff sexual misconduct and youth reports of
safety and fairness, 2012 ....................................................................................

76

33

Individual-level victimization rate, by type of incident and youth
demographic characteristics, 2012....................................................................

84

34

Individual-level victimization rate, by type of incident and youth
risk characteristics, 2012 ....................................................................................

85

Individual-level victimization rate, by type of incident and most
serious offense history, gang involvement, and fighting in the
facility, 2012 .........................................................................................................

87

36

Individual-level victimization rate, by type of incident and youth
reports of facility order and disorder, 2012 ....................................................

89

37

Individual-level victimization rate, by type of incident and youth
reports of safety and fairness, 2012..................................................................

90

38

Final weighted multivariate logistic stepwise regression models,
by type of incident and individual youth factors, 2012 .................................

92

39

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of structure of
juvenile facilities, 2012 .......................................................................................

108

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

viii

29

30
31

32

35

Contents (continued)

Table
40

41

42

43

44

45

46

47

48

49

Page
Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of type of treatment
and assignment factors used in juvenile facilities, 2012 ................................

109

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of staff
characteristics, 2012............................................................................................

112

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of compliance with
PREA standards, 2012 .......................................................................................

113

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of youths’ history,
2012 ......................................................................................................................

116

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of youth offense
history, 2012 ........................................................................................................

117

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of youth reports of
involvement with gangs and fighting, 2012 ....................................................

119

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of youth reports of
vulnerability, 2012 ...............................................................................................

120

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of youth reports of
facility order and disorder, 2012 .......................................................................

121

Multivariate logistic regression models of sexual victimization, by
incident type and facility predictor selection of youth reports of
facility safety and fairness, 2012 .......................................................................

122

Weighted multilevel logistic regression models, by youth-onyouth sexual victimization and level 2 one-by-one predictor
selection, 2012 .....................................................................................................

124

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

ix

Contents (continued)

Table
50

Page
Weighted multilevel logistic regression models, by staff sexual
misconduct and level 2 one-by-one predictor selection, 2012 .....................

127

51

Weighted multilevel logistic regression models, by staff sexual
misconduct and level 2 stepwise predictor selection, 2012 ..........................

133

52

Final weighted multilevel logistic stepwise regression models, by
youth-on-youth sexual victimization and combined individual
youth and facility factors, 2012 .........................................................................

141

Final weighted multilevel logistic stepwise regression models, by
staff sexual misconduct and combined individual youth and
facility factors, 2012............................................................................................

142

Facility characteristics associated with youth-on-youth sexual
assault ...................................................................................................................

80

2

Facility characteristics associated with staff sexual misconduct ..................

81

3

Youth characteristics associated with youth-on-youth sexual
assault ...................................................................................................................

98

4

Youth characteristics associated with staff sexual misconduct ....................

99

5

Stepwise selection process for weighted logistic regression
models ..................................................................................................................

155

53

Figure
1

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

x

NSYC-2 Findings Report:
Correlates of Youth Sexual Victimization (Part I)
Facility- and Individual-Level Results
1.

Overview

The second cycle of the National Survey of Youth in Custody (NSYC-2) was completed in 2012.
Youth in 326 facilities were selected, and 8,707 youth completed usable surveys about the nature of
sexual victimization within the facility. The Bureau of Justice Statistics (BJS) published the first
NSYC-2 report in June 2013. It included the nationwide prevalence of sexual victimization for
adjudicated youth in juvenile facilities, rankings of facilities with the highest and lowest rates of
sexual assault, and state-level estimates of sexual victimization.
This report examines the facility’s impact on youth sexual victimization and also takes into account
critical youth-level predictors. The objectives are to (1) examine the facility-level correlates of youth
sexual victimization, (2) identify significant youth characteristics that can predict sexual
victimization, and (3) describe the contextual circumstances surrounding youth victimization. This
includes analysis of facility attributes that correspond to the Prison Rape Elimination Act (PREA)
standards.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

1

2.

Research Questions

To accomplish these objectives, the analyses were guided by the following research questions:
a.

Does the rate of youth sexual victimization vary across facilities?

b.

What facility-level attributes are associated with sexual victimization?

c.

What youth characteristics are correlated with sexual victimization?

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

2

3.

Highlights and Key Findings
Facility Characteristics Associated With all Types of Sexual Assault (Youth-onYouth and Staff Sexual Misconduct)


Facilities with higher rates of sexual assault have more youth who have submitted
written complaints against staff, do not have enough staff to monitor what takes place
in the facility, and have higher levels of gang fights—as reported by the youth.
Conversely, sexual victimization is less prevalent in facilities where youth report that
there are enough staff to monitor what takes place in the facility, there is little or no
gang fighting, and there are fewer complaints against staff.



In facilities with the highest prevalence of sexual assaults, youth report worrying about
being physically assaulted by another youth. These facilities are more likely to house
youth who have not previously been incarcerated.

Facility Characteristics Exclusively Associated With Youth-on-Youth Sexual
Assault


Facilities that house only females have the highest rates of youth-on-youth sexual
assault.



Youth in facilities with higher rates of youth-on-youth sexual assault are more likely to
have histories of prior sexual assault victimization. These youth are more likely to selfidentify as having a lesbian, gay or bisexual orientation.



Facilities with a high prevalence of youth-on-youth sexual assault tend to house youth in
multiple living units.



Facilities with the highest rates of sexual assault by another youth are more likely to
have youth with violent sexual assault as their most serious offense. These facilities also
are more likely to provide sex offender treatment.



Sexual assault by another youth is more prevalent in facilities when youth are informed
that sexual activity is not allowed more than 7 days after their arrival.



Rates of youth-on-youth sexual assault are highest in facilities when youth might not
report rule breaking about sexual activity because they are embarrassed or ashamed.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

3

Facility Characteristics Exclusively Associated With Staff Sexual Misconduct

1



Facilities with higher rates of staff sexual misconduct tend to be male-only facilities.



Facilities with higher rates of staff sexual misconduct are more likely to be larger in size,
i.e., 25 or more youth. These facilities tend to be detention or training/long-term secure
facilities compared to group homes and residential treatment facilities (based on the
primary function of the facility on the facility questionnaire). They are also less likely to
house only minors.



Facilities with a higher prevalence of staff sexual misconduct have higher staff turnover,
which leads to a loss in staff.



Facilities with higher rates of staff sexual misconduct have problems related to gang
membership, and youth report feeling pressured by the gang to do things they normally
would not do.



Staff sexual misconduct is more prevalent in facilities when youth are never told that
sexual activity is not allowed.



Rates of staff sexual victimization are highest in facilities when youth might not report
rule breaking about sexual activity because they are afraid of being punished by facility
staff.



Facilities with higher rates of staff sexual misconduct tend to house more youth with
person offenses as their most serious offense.



Staff sexual misconduct is more common in facilities where staff share personal
information with youth in their care.



In facilities with the highest rates of sexual misconduct, more youth are written up for
threatening1 or fighting with staff and/or other youth.



Facilities with low rates of staff sexual misconduct have more indicators of PREA
compliance, such as youth who would report sexual activity directly to a facility staff
member. There is also an indication that youth knowing how to make a report if a staff
member or youth is breaking the rules is associated with staff sexual misconduct;
however, the results are inconclusive and need further research.

Threatening is specific to staff only and was not assessed for threats against other youth.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

4

Youth Characteristics Associated With all Types of Sexual Assault (Youth-onYouth and Staff Sexual Misconduct)


Youth who have a history of prior sexual assault are at greatest risk for both types of
assault. These youth are more likely to report a pattern of physical victimization in the
facility, such as being physically hurt by another youth and worrying about physical
assault by staff.



Youth were most at risk for both types of sexual victimization in facilities where youth
report gang fights in the facility and that the staff provide special treatment.

Youth Characteristics Exclusively Associated With Youth-on-Youth Sexual
Assault


Rates of youth-on-youth sexual assault were highest for youth self-identifying as lesbian,
gay, or bisexual.



Youth with violent sexual assault as their most serious offense were at greater risk for
sexual assault by another youth. Higher risk is also associated with lower levels of welldefined structure in the facility.

Youth Characteristics Exclusively Associated With Staff Sexual Misconduct


Males and black youth are much more likely to be victims of staff sexual misconduct.



Youth most at risk of staff sexual misconduct tend to have a history of prior
incarceration lasting 6 months or more. Youth who report active gang involvement in
the facility are associated with higher rates of staff sexual misconduct.



Youth who experience higher rates of staff sexual misconduct reported little to no
positive perceptions of staff, high levels of lack of fairness, and staff sharing personal
information. These youth were also more likely to experience physical assault and to be
physically hurt by staff.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

5

4.

Facility-Level Findings

The analysis of facility-level predictors began by examining the characteristics of the facilities
participating in the NSYC-2. During the survey period, each facility administrator (or designee)
completed a brief paper-and-pencil questionnaire about the facility. The facility questionnaire (FQ)
included information about the total number of youth in the facility, staffing in the facility, number
of living units, treatment programs provided, and types of youth housed in the facility (i.e., offense
history, histories of problems/conditions/patterns of behavior, etc.) (See Attachment 1 for the
complete FQ.) The facility data provided on the FQ are more extensive than data collected by the
Office of Juvenile Justice and Delinquency Prevention’s biennial censuses (i.e., Census of Juveniles
in Residential Placement and Juvenile Residential Facility Census). Of the 326 facilities, 322
completed the FQ. There were 189 surveys from youth within the 4 facilities that declined to
participate, and these surveys were excluded from the analyses for this report.
Facility-level analyses included two sources of data: (1) facility responses to specific items on the FQ
and (2) aggregated responses from the surveys that reflect youth perceptions of facility
characteristics. Responses from the FQ were analyzed to create four sets of conceptual predictors:


overall facility structure (e.g., facility type, facility size, sex of youth housed)2



staff characteristics (number of male/female staff, positions of staff, years of
experience)



compliance with PREA standards (e.g., screening, monitoring, youth-to-staff ratios)



facility reports of youths’ history (most serious offense3 and
problems/conditions/patterns of behaviors).

Youth survey data were aggregated for each facility to create distinct facility-level predictors based
on youth self-reported characteristics and youth perceptions. (See Methodology section for more
details.) The aggregated data were organized into five thematic areas:


Youth reports of compliance with PREA standards;



Fighting/gang activities;



Order and disorder;



Safety and fairness in each facility; and

2

The facility provided these data during the enrollment phase of the study.

3

The facility provided these data on the youth rosters prior to the survey.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

6



The proportion of youth in each facility with self-identified vulnerability characteristics
such as lesbian, gay or bisexual orientation, history of sexual victimization, and those
below expected grade level.

These two sets of data (FQ items and facility-level youth aggregates) were combined and analyzed
together for a comprehensive analysis of facility characteristics associated with the facility-level rate
of victimization (i.e., the proportion of youth reporting victimization within each facility).
Total rates of victimization were lower for youth-on-youth sexual assault than for staff sexual
misconduct. The average facility rate for sexual assault by another youth was 2.1%, and it was
reported by youth in a third of the facilities (31.4%). The average rate for staff sexual misconduct
was 5.2%, and it occurred in about half (49.4%) of the facilities.
The facility-level analyses are organized into the eight content areas (predictors and themes)
described above. This report presents the factors representing each area, followed by illustrations
and discussions of the individual factors associated with sexual victimization using bivariate group
mean comparisons and tests of significance. Finally, for each area, the report identifies which factors
best predict each type of sexual victimization based on tests of significance in multivariate models.
(See Methodology for a full explanation of the analytic process.)

4.1

Structure of Juvenile Facilities

Facilities were examined by key contextual or structural characteristics. These included whether the
facility had single or multiple living units; size (i.e., all youth and only adjudicated youth); capacity in
relation to the number of assigned youth and the number of assigned beds; primary type (detention
center, training school/long-term secure, group home/halfway house, residential treatment center,
or other type); operating status of the facility (state or other type of operating agency); sex of the
youth housed (males only, females only, or both); type of treatment programs offered; and factors
used to assign youth to specific living units.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

7

Table 1
Facility-level victimization rate, by type of incident and selected measures of facility
structure, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

8



Most facilities housed youth in multiple living units (82%).



Almost a third (32%) of the facilities were small, housing 1 to 25 total youth. Seventeen
percent of the facilities housed 101 or more youth.



Similar trends were noted for the number of adjudicated youth. Thirty-nine percent of
the facilities housed 25 or fewer adjudicated youth and 16% had 101 or more youth.



The residential population in most facilities (93%) was at or below capacity. Seven
percent had at least one housing unit with more youth than standard beds.



Facilities were represented by five different types of primary functions:

–

residential treatment center (42%);

–

detention center (14%);

–

training school/long-term secure facility (31%);

–

group home/halfway house (6%); and

–

boot camp, ranch/forestry camp/wilderness/marine program/farm, runaway,
and homeless shelter, or other nonspecific (7%) (due to the small numbers, these
types of facilities were combined into one “other” category).

–

None of the facilities listed reception or diagnostic center as their primary
function, but some noted it as a secondary function (not shown in table).



Most facilities reported that they were state owned or operated (80%).



More than two-thirds (71%) of the facilities housed males only. Twenty-one percent
housed both males and females and 9% housed only females.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

9

Table 2
Facility-level victimization rate, by type of incident and type of treatment provided, 2012



Facilities offered a variety of specialized treatment programs. Mental health treatment
(43%) and substance abuse treatment (41%) were the most common, followed by sex
offender treatment (25%), arson treatment (6%), violent offender treatment (21%), and
other specialized treatment (18%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

10

Table 3
Facility-level victimization rate, by type of incident and unit assignment factors, 2012

Facilities with multiple living units (82%) used a variety of youth-level factors to assign youth to
specific living units. These included offense history (66%), risk of escape (56%), danger to self
(66%), danger to others (67%), age (59%), sex (42%), sexual orientation (35%), special needs (67%),
and other factors such as diagnosis/assessment, gang history, predatory/victim typology, pregnancy,
physical size, and space available (25%).
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

11

Bivariate Association With Youth-on-Youth Sexual Assault
Four individual structural characteristics were found to be associated with youth-on-youth sexual
assault: facilities with multiple living units, training/long-term secure facilities, facilities with female
youth (either females only or both males and females) (see table 1), and those offering sex offender
treatment (see table 2). None of the assignment factors within multiple-unit facilities were significant
(see table 3).


Multiple-unit facilities (2.5%) had higher rates of youth-on-youth sexual assault than
single-unit facilities (0.5%).



Training/long-term secure facilities had the highest prevalence (3.2%) comparatively.



Rates in female-only facilities (5.3%) were more than three times greater than those in
male-only facilities (1.5%).



The percentage of youth-on-youth sexual assault was double (3.5%) in facilities that
offer sex offender treatment, compared to facilities that do not offer this type of
treatment (1.7%) (see table 2).

Bivariate Association With Staff Sexual Misconduct
A number of facility structural characteristics were uniquely associated with staff sexual misconduct:
facilities with multiple living units, larger facilities (25 or more youth), detention centers or
training/long-term secure facilities, state-operated facilities, facilities housing male youth (either
males only or both males and females), and those providing violent offender treatment (see table 2).


Staff sexual misconduct was reported by 5.9% of youth in facilities with multiple living
units, compared to 2.1% of youth in facilities with single units.



The proportion of youth reporting staff sexual misconduct was highest in the largest
facilities: 10.3% in facilities containing 101 or more adjudicated youth, 6.7% in facilities
with 51 to 100 adjudicated youth, 5.4% in facilities with 26 to 50 adjudicated youth, and
2.3% in facilities with less than 25 adjudicated youth.



Staff sexual misconduct was most prevalent in detention centers (7.4%) and
training/long-term secure facilities (7.3%) and lowest in residential treatment centers
(3.1%) and non-state-operated facilities (3.1%).



In facilities with only male residents, 5.7% of youth reported staff sexual misconduct,
compared to 1.4% in facilities with only female residents.



Staff sexual misconduct was reported by more youth (7.1%) in facilities that offer
violent offender treatment, compared to facilities that do not offer this type of
treatment (4.7%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

12

Multivariate Findings for Youth-on-Youth Sexual Assault

Table 4
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and selected measures of facility structure and type of treatment provided, 2012

In order to assess which structural factors best predicted youth-on-youth sexual victimization (see
table 4), the four significant factors were entered together in a multivariate regression model (see
Methodology section for a detailed discussion of the stepwise modeling approach and calculation of
predicted rates). Facilities with only female residents (5.8%), those offering sexual offender
treatment (3.4%), and those with multiple living units (2.5%) had considerably higher predicted rates
than facilities without these characteristics. Although the primary type of facility (e.g., training/longterm secure) was significant in the bivariate findings, it was no longer significant in the multivariate
model.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

13

Multivariate Findings for Staff Sexual Misconduct

Table 5
Multivariate stepwise regression models of facility sexual victimization, by staff sexual
misconduct incidence and selected measures of facility structure and type of treatment
provided, 2012

For prediction of staff sexual misconduct, three of six factors remained important in the multivariate
models (see table 5). Youth in larger facilities (5.8% in those with 26 or more adjudicated youth,
7.0% in those with 51 to 100 youth, and 9.6% in those with 101 or more youth), detention centers
(9.2%), and training/long-term secure facilities (7.3%), and in male-only facilities (7.2%) were
significantly more likely to experience sexual victimization by staff. Multiple living units, violent
offender treatment, and operating agency (state or nonstate) were no longer important factors after
adjusting for other facility structural characteristics.
Because facility-level structural characteristics were predictive of each type of victimization, all
significant factors in each facility structural multivariate model were included as controls in the
remaining multivariate models. Since significant predictors vary by the type of victimization, the
controls also differ by the type of sexual assault.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

14

4.2

Staff Characteristics

Staff characteristics in the facility were assessed by the level and type of staffing changes over the
past 12 months (none, added only, added and lost, or lost staff only), the ratio of the total number of
youth to all staff, the ratio of the total number of youth to frontline staff only, the total proportion
of female staff members in the facility, the total proportion of frontline female staff members in the
facility, and the years of experience for all staff and for frontline staff.

Table 6
Facility-level victimization rate, by type of incident and staff characteristics, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

15

Table 6
Facility-level victimization rate, by type of incident and staff characteristics, 2012 (continued)



The majority of facilities (71%) reported a change in staff over the past 12 months. Of
these, 10% only added staff, 31% both added and lost staff, and 29% only lost staff.



At least 75% of facilities had more total staff than youth.



Approximately a quarter of the facilities had substantially more frontline staff with ratios
of 0.10 to 0.83 youth per staff. A quarter of the facilities had proportional numbers of
frontline staff and youth with ratios from 0.83 to 1.16 youth per staff, and half of the
facilities had considerably more youth than frontline staff with ratios of 1.16 and more
youth per staff.



Most facilities had more male than female frontline staff with about a quarter having
more female than male staff (0.53 to 0.96).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

16



The majority of facilities (76%) contained high proportions of staff with more than 1
year of experience (0.74 and higher). Similar trends were also evident for frontline staff
experience. More than half (51%) had 0.84 and higher proportions of frontline staff
with more than 1 year of experience.

Bivariate Association With Youth-on-Youth Sexual Assault and Staff Sexual
Misconduct
Youth-on-youth sexual assault was significantly associated with lower ratios of staff to youth and the
overall proportion of female staff (see table 6), while staff sexual misconduct was related to changes
in staff and lower ratios of youth to staff. Staff experience was not relevant to either type of
victimization.


Sexual assault by another youth was highest (2.9%) in facilities where staff outnumber
youth (i.e., youth-to-staff ratio for frontline staff only less than 0.83).



Sexual assault by another youth was more prevalent in facilities where the proportion of
female staff was more than half (i.e., 0.53 and above) (3.2%) and frontline female staff
was greater than a third (i.e., .0.44 and above) of the total staff (3.3%).



Facilities with no change in staffing over the past 12 months had the lowest percentage
of staff sexual misconduct (3.1%). A higher percentage of youth (5.5%) reported staff
sexual misconduct in facilities that both added and lost staff, and the highest rates
(7.1%) were reported in facilities that lost staff but did not add any staff.



Rates of staff sexual misconduct were significantly lower (3.9%) in facilities that had
more staff than youth (i.e., youth-to-staff ratio for frontline staff only less than 0.83).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

17

Multivariate Findings for Youth-on-Youth Sexual Assault

Table 7
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and staff characteristics, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

18

After controlling for significant facility structural characteristics in the multivariate model, staff
characteristics4 were no longer predictive of youth-on-youth sexual assault (see table 7). However, all
facility structural controls remained significant.

4

Due to multicollinearity, the total proportion of female staff and the total proportion of frontline female staff could
not be entered into the same model. Total proportion of frontline female staff was chosen because the assault rates
were higher overall.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

19

Multivariate Findings for Staff Sexual Misconduct

Table 8
Multivariate stepwise regression models of facility sexual victimization, by staff
sexual misconduct and staff characteristics, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

20

In the multivariate staff sexual misconduct model, after adjusting for controls, facilities losing and
not adding staff had significantly higher rates (7.7%) than facilities with other staffing changes (see
table 8). Similarly, all structural characteristics remained relevant predictors of staff sexual
victimization.

4.3

Compliance With PREA Standards

Facilities’ overall compliance with specific PREA standards was examined using two sources of data,
(1) facility responses to specific items on the facility questionnaire (FQ) and (2) aggregated responses
from the youth survey. The youth survey asked for youth perceptions of how facilities enforce these
standards. Responses from the FQ included staff screening practices, monitoring/surveillance
practices, and compliance with staff to youth ratios. The following compliance standards are applied
to all facilities in the survey, even though some facilities are not legally covered under PREA.

4.3.1

Compliance With PREA Standards – Facility Reports

Table 9
Screening procedures for hiring new staff by primary facility type a, 2012



Almost all facilities conduct criminal record checks (99%), screen for convictions for
child abuse/sexual abuse (98%), and check for convictions for drug use (97%). Sixtythree percent of facilities test for current drug use, and 17% require psychological
evaluations (see table 9).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

21

Table 10
Compliance with PREA standards: Monitoring procedures by primary facility typea, 2012



The majority of facilities (77%) use video camera surveillance. Detention centers (96%)
and training/long-term secure (96%) facilities were the most likely to use monitoring
compared to other primary facility types (see table 10).



Of the facilities using monitoring, 95% of all facilities had video monitoring in sleeping
areas; 87% of facilities included monitoring in the entrance and/or actual area of
bathrooms and showers, 71% in classrooms, 96% in other indoor areas, and 92% in
outdoor recreation areas. Group home facilities were the most likely to have monitoring
in all these locations when compared to other primary facility types.

Table 11a
Compliance with PREA standards: Staffing ratio standards by shift across all facilitiesa, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

22

Table 11b
Compliance with PREA standards: Staffing ratio standards by shift and primary facility
typea f, 2012



Most facilities (secure and non-secure facilities) were in compliance with the PREA
staff-to-youth ratio standards (see table 11a). More than 79% of facilities were
compliant with day-shift ratio standards (1 staff per 8 youth), 83% were in compliance
with evening-shift ratio standards (1 staff per 8 youth), and 88% were in compliance
with night-shift ratio standards (1 staff per 16 youth).



There were small differences in compliance rates between primary facility types (see
table 11b). Detention centers (87%) and training/long-term secure facilities (85%) were
the most compliant for day shifts; training/long-term secure (87%), group homes
(90%), and other (87%) were most compliant for evening shifts; and training/long-term
secure (89%) and group homes (95%) were most compliant for night shifts.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

23

Table 12a
Compliance with PREA standards: Staffing ratio standards by shift across secure facilitiesa,b,
2012

Table 12b
Compliance with PREA standards: Staffing ratio standards by shift across nonsecure
facilitiesa,b, 2012

5



PREA compliance for frontline staffing5 was much more apparent in secure facilities,
where the standards are required (see table 12a). Eighty-four percent of secure facilities
were at the day and evening ratios, and 88% were in compliance with night-shift staff
ratios.



Comparatively, nonsecure facilities had 68% compliance with day-time ratios, 83%
compliance for evening, and 88% compliance nighttime (see table 12b).

Frontline staff includes: all correctional officers and any frontline staff member with direct supervision responsibilities
over youth.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

24

Bivariate Association With Youth-on-Youth Sexual Assault and Staff Sexual
Misconduct
Facility reports of PREA staff screening practices, monitoring/surveillance practices, and
compliance with staff-to-youth ratios were tested, but most were not relevant to either type of sexual
victimization. Only video surveillance6 was associated with both types of sexual assault. Testing for
current drug use was related to staff sexual misconduct (see table 13).

6

Screening for staff criminal records, conviction for child/sexual abuse, and convictions for drug use were not included
in the bivariate tests because almost all facilities engaged in these practices.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

25

Table 13
Facility-level victimization rate, by type of incident and facility reports of compliance with
PREA standards, 2012

Facility reports of compliance with PREA standards
All facilities
100.0 %
Types of screening
Testing of staff for current drug use
Yes
No *
Psychological evaluation
Yes
No *
Monitoring
Video surveillance
Yes
No *
Location of monitoring
All sleeping areas
Yes
No *
Bathrooms and shower areas
Yes
No *
Classrooms and library
Yes
No *
Other indoor areas
Yes
No *
Outdoor recreation areas
Yes
No *
Staff to youth ratios compliance - all facilities a
1:8 Compliance day
Yes
No *
1:8 Compliance evening
Yes
No *

Youth-on-youth
victimization rate
Mean
Standard
Percent
Error
2.1 %
0.3

Staff sexual
misconduct
victimization rate
Mean
Standard
Percent
Error
5.2 %
0.4

63.2 %
36.8

2.4 %
1.7

0.3
0.4

6.4 % **
3.1

0.5
0.5

17.1 %
82.9

1.4 %
2.3

0.4
0.3

6.3 %
5.0

1.1
0.4

76.7 %
23.3

2.5 % **
1.0

0.3
0.3

5.8 % **
3.2

0.5
0.8

95.1 %
4.9

2.4 %
2.8

0.3
1.3

5.8 %
5.2

0.5
2.1

87.0
13.0

2.5 %
2.2

0.3
0.7

5.8 %
5.9

0.5
1.4

70.9
29.2

2.5 %
2.3

0.3
0.6

5.9 %
5.5

0.5
0.9

96.4
3.6

2.5 %
1.5

0.3
1.0

5.8 %
5.5

0.5
2.7

91.9
8.1

2.6 %
1.1

0.3
0.5

5.8 %
5.7

0.5
1.5

79.2 %
20.8

2.1 %
2.2

0.3
0.5

5.3 %
5.1

0.5
0.8

82.6 %
17.5

2.2 %
1.9

0.3
0.6

5.3 %
0.5
4.7
0.8
Continued on next page

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

26

Table 13
Facility-level victimization rate, by type of incident and facility reports of compliance with
PREA standards, 2012 (continued)

4.3.2



Facilities testing staff for drug use had higher rates of staff sexual misconduct (6.4%)
than other facilities (3.1%).



The prevalence of youth-on-youth (2.5%) and staff sexual misconduct (5.8%) was
elevated in facilities that use monitoring, although rates were not significantly different
by location of monitoring.

Compliance With PREA Standards – Youth Reports

Aggregated survey responses from the youth survey included perceptions of how facilities enforce
PREA standards along several dimensions. Youth were asked about whether they knew how to
report rule breaking, when and how they learned sexual activity was not allowed, and the methods
they could use to report and their willingness to report rule breaking about sexual activity.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

27

Table 14
Facility-level victimization rate, by type of incident and youth reports of facility compliance
with PREA standards, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

28

Table 14
Facility-level victimization rate, by type of incident and youth reports of facility compliance
with PREA standards, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

29

Table 14
Facility-level victimization rate, by type of incident and youth reports of facility compliance
with PREA standards, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

30

Table 14
Facility-level victimization rate, by type of incident and youth reports of facility compliance
with PREA standards, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

31

Table 14
Facility-level victimization rate, by type of incident and youth reports of facility compliance
with PREA standards, 2012 (continued)



In the majority of facilities (75%), at least 70% of youth (0.70 and above) indicated that
they were told how to report if a staff member or youth was breaking the rules. In 73%
of facilities, most youth (0.60 and above) said they were told they would not get into
trouble if they reported a staff member or youth breaking the rules.



Almost three-quarters of youth (0.72 and above) in 75% of facilities confirmed that they
learned sexual activity was not allowed within the first 24 hours of their arrival to the
facility. Twenty-six percent of facilities had some youth (0.08 to 0.50) indicating they
learned this between their first and seventh day, and 38% of facilities had some youth
(0.01 to 0.33) reporting they learned more than 7 days after arrival. In 26% of facilities,
there was wide variability in the number of youth (0.18 up to 1) reporting that they were
never told sexual activity was not allowed.



In about a quarter of the facilities, almost two-thirds (0.61 and above) of youth learned
sexual activity was not allowed through a one-on-one session with a staff member. In
approximately 75% of facilities, more than a third (below 0.41) of youth learned sexual
activity was not allowed in a one-on-one session with a youth mentor, less than half of
all youth (below 0.44) learned in a small group session with 6 or fewer youth, close to
half of youth (below 0.50) learned in a group session with more than 6 youth, and the
majority of youth (below 0.80) learned through written materials such as
posters/handouts. Twenty-eight percent of facilities, had more than half of their youth
(0.50 up to 1) learning that sexual activity was not allowed in some other way.



Many youth (0.73 and above) in 75% of facilities said that they could report sexual
activity by talking face-to-face with a staff member. In approximately a quarter of
facilities, more than two-thirds of youth (0.68 up to 1) indicated they would report
sexual activities to someone who works outside the facility or who visits from outside
the facility, and almost all youth (0.96 and above) would make a written report to facility
staff or administrators. About half of all facilities had almost 50% (0.49 and above) of

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

32

youth who said they would use a phone to call someone, and more than two-thirds
(0.67 and above) of youth said they would use some other way to report sexual activity.


Forty-nine percent of facilities had almost half or more of their youth (0.46 and above)
who indicated that they definitely would report rule breaking about sexual activity to a
facility staff member.



There were varying reasons about why youth would not report rule-breaking sexual
activities in the facilities.

–

In about two-thirds of facilities, between 10% and 12% (0.10 to 0.12) of youth
said they were afraid of the youth involved, afraid of being punished by facility
staff, or embarrassed or ashamed that it happened.

–

In approximately half of all facilities, at least 13% of youth (0.13 and above) said
that would not report rule-breaking sexual activity because they did not think staff
would investigate. At least 11% of youth (0.11 and above) thought that the youth
involved would not be punished, at least 15% (0.15 and above) thought they
would not be believed, at least 33% (0.33 and above) did not want to be a snitch
or tattletale, at least 29% (0.29 and above) said it wasn’t something they cared
about, and at least 24% (0.24 and above) said they might have some other reason.

Bivariate Association With Youth-on-Youth Sexual Assault
Some aggregated youth responses about how facilities enforce PREA standards were associated with
youth-on-youth sexual assault. These included when youth first learned sexual activity was not
allowed, how they would report sexual activity, and reasons why they would not report.


Youth-on-youth sexual assault was lowest in facilities (1.1%) when almost all youth in
the facility reported that they first learned sexual assault was not allowed within the first
24 hours of arriving at the facility. Rates increased in facilities when more youth
reported learning between 1 and 7 days (3.1%) or after more than 7 days (2.9%).



Rates were lowest in facilities (1.1%) with the large proportions of youth (0.83 up to
0.94) reporting they would report sexual activities by talking face-to-face with a staff
member.



Youth-on-youth sexual assault was most prevalent in facilities when greater numbers of
youth indicated they would not report sexual activity due to the following reasons:

–

Afraid of youth involved (3.3%);

–

Afraid of being punished by facility staff (3.1%);

–

Embarrassed/ashamed that it happened (3.4%);

–

Didn’t think staff would investigate (2.6%);

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

33

–

Didn’t think youth involved would be punished (3.3%);

–

Didn’t think would be believed (3.0%); and

–

Some other reason (3.2%).

Bivariate Association With Staff Sexual Misconduct
Almost all aggregated youth responses about how facilities enforce PREA standards were associated
with staff sexual misconduct. Facilities had lower rates when larger concentrations of youth reported
that they knew how to report rule breaking, reported that they learned sexual activity was not
allowed within the first 24 hours, reported they that learned sexual activities was not allowed by
some method other than talking one-on-one with a staff member, reported that they would report
sexual activity in a variety of ways, and that they definitely would report rule breaking about sexual
activity. Facilities with the highest rates of staff sexual misconduct had larger numbers of youth who
would not report rule breaking for a variety of reasons.


Facilities had lower rates of staff sexual misconduct when almost all youth said that they
were told how to report if a staff member or youth is breaking the rules (3.2%) and they
were told they would not get in trouble if they report that a staff member or youth is
breaking the rules (1.7%).



Facilities had lower rates of staff sexual misconduct (1.8%) when almost all youth in the
facility reported that they first learned sexual assault was not allowed within the first 24
hours of arriving at the facility. Rates increased in facilities where more youth reported
learning between their first and seventh day (7.8%) or after more than 7 days (7.1%),
and were highest in facilities where youth indicted they were never told the rules on
sexual activities (9.1%).



Facilities with lower prevalence of staff sexual misconduct had an increased number of
youth that learned sexual activity was not allowed through a one-on-one session with a
youth mentor (3.6%), in a small group session with 6 or fewer youth (4.0%), in a group
session with more than 6 youth (3.1%), and through written materials such as
posters/handbooks (3.4%).



Staff sexual misconduct was lower in facilities where greater proportions of youth
reported that they would report sexual activity in the following ways:

–

Face-to-face with a staff member (1.7%);

–

Face-to-face with someone who works or visits outside the facility (3.2%);

–

A written report to facility staff or administrators (2.3%); and

–

Some other way (2.9%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

34



Facilities had the lowest rates of staff sexual misconduct (2.3%) when the majority of
youth indicated they would definitely be willing to report rule breaking about sexual
activity.



Staff sexual misconduct was most prevalent in facilities when greater numbers of youth
indicated they would not report sexual activity due to the following reasons:

–

Afraid of youth involved (7.9%);

–

Afraid of being punished by facility staff (8.8%);

–

Embarrassed/ashamed that it happened (5.8%);

–

Didn’t think staff would investigate (8.5%);

–

Didn’t think youth involved would be punished (7.1%);

–

Didn’t think they would be believed (7.1%);

–

Didn’t want to be a snitch or tattletale (5.2%);

–

Not something they care about (5.7%); and

–

Some other reason (6.7%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

35

4.3.3

Compliance With PREA Standards- Combined Facility and Youth Reports
Multivariate Findings for Youth-on-Youth Sexual Assault

Table 15
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and facility and youth reports of compliance with PREA standards, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

36

Table 15
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and facility and youth reports of compliance with PREA standards, 2012 (continued)

After controlling for facility structural characteristics in the multivariate models, two indicators of
compliance with PREA standards were associated with youth-on-youth sexual assault (see table 15).
Facility structural characteristics such as the sex of youth housed (female-only facilities) and facilities
providing sex offender treatment remained significant for increased rates of youth-on-youth
victimization.


Facilities had higher rates of youth-on-youth sexual assault (2.6%) when greater
numbers of youth reported that they learned sexual activity was not allowed more than
7 days after their arrival in the facility, and when more youth indicated that they would
not report breaking rules about sexual activity because they would be embarrassed or
ashamed (2.9%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

37

Multivariate Findings for Staff Sexual Misconduct

Table 16
Multivariate stepwise regression models of facility sexual victimization, by staff sexual
misconduct and facility and youth reports of compliance with PREA standards, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

38

Table 16
Multivariate stepwise regression models of facility sexual victimization, by staff sexual
misconduct and facility and youth reports of compliance with PREA standards, 2012
(continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

39

Several indicators of compliance with PREA standards were associated with staff sexual misconduct
after controlling for structural characteristics in the multivariate models (see table 16). Structural
characteristics such as sex of youth housed (male-only and facilities with both males and females),
and size of the facility remained relevant predictors of staff sexual victimization.

4.4



Facilities had lower rates of staff sexual misconduct when more youth acknowledged
that they would report sexual activity by talking face-to-face with a staff member (5.5%).
Conversely, facilities had higher rates of staff sexual misconduct (7.4%) when more
youth were told how to report if a staff member or youth is breaking the rules.7



Facilities had an elevated prevalence of staff sexual misconduct when increased
numbers of youth reported never being told about rules on sexual activity (8.0%) and
when more youth were afraid or scared of being punished by facility staff for reporting
rule breaking about sexual activity (8.0%).

Facility Reports of Youths’ History

Facilities reported on the percentage of youth in their care with specific histories of problems,
conditions, or patterns of behavior (see table 17). These included a history of self-injury/suicidal
behavior, violence toward others, abuse by parents, predatory sexual behavior, rape victimization,
prostitution, gang memberships/affiliation, psychiatric condition, and developmental disability.

7

The positive direction of this variable in the multivariate model seems to be related to its correlation with other
variables in the model rather than a true reflection of higher rates. As shown in table 14 this variable was associated
with the reduced likelihood of staff sexual misconduct in the bivariate tests; therefore, the authors are hesitant to put
too much interpretation of the positive direction of the coefficient in the multivariate model.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

40

Table 17
Facility-level victimization rate, by type of incident and youths' history, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

41



Most facilities (80%) reported that a quarter or less of their youth population had a
history of self-injury/suicidal behavior.



The percentages of youth with histories of violence towards others were almost evenly
distributed across facilities. More than a quarter of facilities had low numbers of youth
with histories of violence toward others (25% or less). Conversely, 20% of facilities had
more than three-quarters of their youth population with this history (76% to 100%).



Thirty-five percent of the facilities had low percentages of youth (25% or less) with
histories of abuse by parents while 29% of all facilities had large percentages (more than
50%) with this background.



The percentages of youth with predatory sexual behavior were low (up to 25%) in the
majority of facilities (89%).



The majority of facilities contained small percentages (25% or less) of youth with
histories of rape victimization and prostitution (83% and 95% respectively).



Concentrations of youth with histories of gang membership/gang affiliation were
moderate to high (26% and above) across two-thirds (67%) of all facilities.



Similarly, the majority of facilities (71%) had moderate to high percentages (26% and
above) of youth with histories of psychiatric conditions.



Percentages of youth with histories of developmental disabilities were low (up to 25%)
in more than two-thirds of all facilities (70%).

Bivariate Association With Youth-on-Youth Sexual Assault
Youth-on-youth assault rates were higher in facilities housing greater concentrations of youth with
histories of victimization and/or psychiatric conditions (see table 17).


Sexual assault by another youth (5.0%) was more common in facilities where more than
half of their youth population (51% to 75%) had a history of self-injury/suicidal
behavior.



Nearly 4% of youth experienced sexual assault by another youth in facilities where more
than three-quarters of the youth population was identified as having been abused by a
parent.



Facilities with more than three-quarters of the youth population having histories of rape
victimization had significantly higher rates (8.4%) of youth-on-youth sexual assault.



Almost 8% (7.8%) of youth reported sexual assault by another youth in facilities where
the proportion of youth with a history of prostitution was a quarter to half of the
population.



Youth-on-youth sexual assault was lowest (1.0%) in facilities when more than threequarters of the youth had a history of gang membership/affiliation.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

42



More youth (4.0%) were sexually assaulted by another youth in facilities that reported
greater concentrations of youth with a history of psychiatric conditions (76% to 100%).

Bivariate Association With Staff Sexual Misconduct
Opposite factors were associated with staff sexual misconduct. Facilities with more concentrations
of youth with histories of violence towards others and histories of gang membership/affiliation had
the highest rates of staff sexual misconduct (see table 17).


Staff sexual misconduct was more prevalent in facilities (6.5%) when three-quarters of
the youth population had a history of violence toward others.



Facilities with more than half of the youth with a history of gang
membership/affiliation were more likely to have more incidents of staff sexual
misconduct (6.9%, 6.5%).

In addition to collecting histories of youth problems, conditions, or patterns of behavior on the FQ,
facilities also provided information about each youth’s most serious offense leading to the current
placement (see table 18). This information was then aggregated to the facility level so that the
average rate (i.e., mean) of youth with a particular most serious offense could be calculated across all
facilities. (See Methodology section for a more thorough description of facility aggregation.) Facilities
were assessed to determine if their concentrations of youth were higher or lower than the average
across facilities. The most serious offense factors were then tested individually with sexual
victimization.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

43

Table 18
Facility-level victimization rate, by type of incident and facility offense profile, 2012
Staff sexual
Youth-on-youth
misconduct
victimization rate
victimization rate
Mean
Standard Mean
Standard
Percent
Error
Percent
Error

Facility offense profile
All facilities

100 %

Most serious offense responsible for current placement
Murder (mean = 1%)

2.1 %

0.3

5.2 %

0.4

a

High b

25 %

3.4 % **

0.6

7.4 % **

0.8

Low c *

75

1.7

0.3

4.5

0.5

29 %

3.3 % **

0.5

6.8 % **

0.8

71

1.6

0.3

4.6

0.5

18 %

2.8 %

0.6

5.2 %

0.8

82

2.0

0.3

5.2

0.5

49 %

2.2 %

0.4

6.2 % **

0.6

51

2.1

0.3

4.3

0.5

49 %

1.7 %

0.3

5.1 %

0.6

51

2.5

0.4

5.4

0.6

35 %

1.6 %

0.4

4.4 %

0.6

65

2.4

0.3

5.7

0.5

38 %

1.7 %

0.4

4.5 %

0.6

62

2.4

0.3

5.6

0.5

Violent sex assault (mean = 10%)
High b
c

Low *
Non-violent sex offense (mean = 2%)
High b
c

Low *
Person offense (mean = 32%)
High b
c

Low *
Property offense (mean = 29%)
High b
c

Low *
Drug offense (mean = 6%)
High b
c

Low *
Other (mean = 17%)
High b
c

Low *

d

Note: Based on 322 unweighted juvenile facilities that returned a Facility Questionnaire. Four facilities were excluded from
analysis.
**Difference with comparison group is significant at the 95%- confidence level.
*Comparison group.
a

Proportion of youth in the facility with the identified most serious offense

b
c

Proportion of youth with this offense is greater than or equal to the mean of other facilities

Proportion of youth with this offense is less than the mean of other facilities

d

Includes status offenses, probation/parole violations, public order offenses

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

44



The percent of youth with murder as their most serious offense was low across all
facilities (average 1%).



Violent sexual assault (average 10%) was more common than nonviolent sexual assault
(average 2%) as the most serious offense for youth across all facilities.



Person offenses were the most prevalent (average 32%) most serious offense and
property offenses were the second most prevalent most serious offense (average 29%).



On average, 6% of youth had a drug-related as their crime most serious offense, and
17% had other types of crimes.

Bivariate Association With Youth-on-Youth Sexual Assault and Staff Sexual
Misconduct
Facilities with greater concentrations of youth with violent offense histories (murder and violent
sexual assault) had higher rates of sexual victimization (see table 18).


Both types of sexual victimization were more prevalent in facilities with higher-thanaverage concentrations of youth with murder (3.4% and 7.4%) and violent sexual assault
(3.3% and 6.8%) as their most serious offense. Staff sexual misconduct was also
associated with greater-than-average numbers of youth with person offenses (6.2%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

45

Multivariate Findings for Youth-on-Youth Sexual Assault

Table 19
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and youths' history, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

46

Table 19
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and youths' history, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

47

All youth history factors including problems, conditions, patterns of behaviors, and most serious
offenses were tested in the same multivariate models.8 After controlling for facility structural
characteristics, two of these factors remained significantly predictive of youth-on-youth sexual
assault, while multiple living units and sex of youth housed remained highly relevant (see table 19).


8

Rates of youth-on-youth sexual assault (5.7%) were most prevalent in facilities with
large concentrations of youth with histories of rape (76% or more youth) and greaterthan-average numbers of youth with violent sexual assault (2.9%) as their most serious
offense.

To increase the overall model strength (i.e., adjusted R square) and ease of interpretation, all proportional categorical
aggregate factors were included in the model using the continuous version. High/low categories were used to calculate
the predicted rates (see Methodological section for more details).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

48

Multivariate Findings for Staff Sexual Misconduct

Table 20
Multivariate stepwise regression models of facility sexual victimization, by staff sexual
misconduct and youths' history, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

49

Facilities with greater-than-average numbers of youth with person offenses as their most serious
offense (7.0%) were more likely to have higher levels of staff sexual misconduct after controlling for
facility structural characteristics in the same multivariate models. Some structural factors also
remained highly predictive.

4.5

Youth Reports of Involvement With Gangs and Fighting

The level of fighting and gang activity in the facilities was assessed based on the proportion of youth
reporting these activities. These include the number of youth being written up for fighting, number
of youth reporting the presence of gangs in the facility, gang fighting in the facility, being a member
of a gang while in the facility, feeling pressure to do things they wouldn’t otherwise do as a member
of a gang while in the facility, and feeling safer being a member of a gang while in the facility. The
number of times youth were written up for fighting was measured using a three-item scale. Higher
numbers represented more sanctions (see Appendix B for scale).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

50

Table 21
Facility-level victimization rate, by type of incident and youth reports of involvement with
gangs and fighting, 2012
Youth-on-youth
victimization rate
Mean
Standard
Percent
Error

Youth reports of involvement with
gangs and fighting
All facilities

100 %

2.1 %

0.3

5.2 %

0.4

0.9 %
2.6 **
2.1
2.9 **

0.3
0.5
0.5
0.6

1.4
4.9
5.6
9.0

%
**
**
**

0.5
0.8
0.7
0.9

1.5 %
1.6
2.4
3.0 **

0.5
0.4
0.5
0.6

1.6 %
3.4
6.2 **
9.8 **

0.5
0.6
0.9
0.9

1.2 %
1.9
2.6 **
2.8 **

0.4
0.4
0.6
0.5

1.4 %
3.3
5.7 **
10.6 **

0.6
0.6
0.8
0.9

28 %
21
25
26

1.7 %
2.0
2.4
2.5

0.5
0.4
0.5
0.5

1.5
5.1
5.7
8.8

%
**
**
**

0.6
0.7
0.8
0.9

65 %
35

2.0 %
2.4

0.3
0.3

3.2 %
8.9 **

0.4
0.7

32 %
18
24
26

1.8 %
1.9
2.3
2.5

0.5
0.4
0.6
0.5

2.2
5.9
5.1
8.6

0.6
1.0
0.7
0.9

Discipline for physical assault or threats
Written up for fighting a
0 up to 0.17 *
26 %
0.17 up to 0.48
24
0.48 up to 0.77
25
0.77 up to 1
25
Gang activity
Gangs in facility
0 up to 0.29 *
25 %
0.29 up to 0.58
25
0.58 up to 0.82
24
0.82 up to 1
25
Gang fights in facility
0 up to 0.03 *
25 %
0.03 up to 0.25
26
0.25 up to 0.55
25
0.55 up to 1
25
Gang member in facility b
0*
>0 up to 0.13
0.13 up to 0.25
0.25 up to 1
Gang pressure
0*
0.01 -0.25
Safer in gang
0*
>0 up to 0.09
0.09 up to 0.17
0.17 up to 1

Staff sexual
misconduct
victimization rate
Mean
Standard
Percent
Error

%
**
**
**

Note: Based on 322 unweighted juvenile facilities that returned a Facility Questionnaire. Four facilities were excluded from
analysis.
*Comparison group.
**Difference with comparison group is significant at the 95%- confidence level.
a

This measure is a construct and the data represents an overall score across several survey items (see appendix 2 for a
listing of the items). The score was generated by summing all positive responses by each individual youth in a facility, and
then computing an average score for all youth within a facility.
b

Youth report gang activity in the facility and that they are a member of the gang

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

51



Most facilities (75%) had low levels of youth reporting being written up for fighting
behavior (0 to 0.77 items for all youth in the facility).



The presence of gangs was reported by more than half of all youth (0.58 and above) in
at least 50% all facilities. A quarter of facilities had the majority of their youth (0.82 and
above) reporting gangs in the facility.



In half (51%) of all facilities, less than a quarter of youth (below 0.25) reported gang
fights. Levels of gang membership were relatively low in the majority of facilities (74%).
In more than one-quarter of facilities (28%), no youth identified as a member of a gang.
Less than 25% of youth (less than 0.25) in almost half (46%) of facilities reported being
a member of a gang.



Throughout the majority of facilities (65%), youth reported that they did not experience
gang pressure.



Approximately a third of facilities (32%) had no youth that felt safer in a gang. More
than a quarter had at least 17% (0.17 and above) of youth reporting that they felt safer
in a gang.

Bivariate Association With Youth-on-Youth Sexual Assault
Fighting and gang activity were significantly associated with increased rates of youth-on-youth sexual
assault. Facilities with larger proportions of youth receiving sanctions for fighting, endorsing gangs
in the facility, and gang fights had the highest rates (table 21).


Facilities with less than 17.0% (0.17 and below) of youth with a history of being written
up for fighting had low rates of youth-on-youth victimization (0.9%), while those with
the highest number of youth receiving sanctions had the highest levels (2.9%).



High concentrations of youth (0.82 and above) reporting gang activity in the facility was
significantly associated with elevated rates (3.0%) of sexual assault by another youth.



Similar levels of youth-on-youth sexual assault (2.8%) were evident when the majority
of youth (0.55 and above) report gang fights in the facility.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

52

Bivariate Association With Staff Sexual Misconduct
Staff sexual misconduct was significantly related to fighting and all gang factors. Rates of staff sexual
misconduct were greatest in facilities that had high concentrations of youth receiving sanctions for
fighting and reporting any type of gang activity (see table 21).


Staff sexual misconduct rates were almost double in facilities where the most youth
received sanctions for fighting (9.0%) and reported the presence of gangs in the facility
(9.8%).



In facilities where the majority of youth (0.55 and above) reported gang fights, the
prevalence of staff sexual misconduct was more than double (10.6%) the facility average
(5.2%).



Gang membership was directly related to staff sexual misconduct. As the overall
concentration of youth reporting membership in a gang increased, so did the likelihood
of staff sexual misconduct.



In facilities with any proportion of youth reporting gang pressure, the likelihood of staff
sexual misconduct was almost three times greater (8.9% vs. 3.2%) than facilities with no
youth experiencing gang pressure.



Staff sexual misconduct was directly related to the proportion of youth who reported
feeling safer in a gang. The lowest rates were in facilities with no youth saying they felt
safer (2.2%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

53

Multivariate Findings for Youth-on-Youth Sexual Assault

Table 22
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and youth reports of involvement with gangs and fighting, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

54

After controlling for facility structural characteristics, only gang fights were significant in predicting
youth-on-youth sexual assault in the multivariate model (see table 22). Facilities had elevated rates
(2.8%) where the majority of youth report gang fights. Female-only residential facilities and facilities
providing sex offender treatment remained robust predictors of youth-on-youth assault.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

55

Multivariate Findings for Staff Sexual Misconduct

Table 23
Multivariate stepwise regression models of facility sexual victimization, by staff sexual
misconduct and youth reports of involvement with gangs and fighting in the facility, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

56

Fighting and gang factors remained significantly predictive of staff sexual misconduct after adjusting
for facility structural characteristics (see table 23).

4.6



Higher-than-average concentrations of youth receiving sanctions for fighting (8.7%),
reporting gang pressure (7.1%), and gang fights (8.2%) were significantly predictive of
staff sexual misconduct.



In the multivariate model, most facility structural factors were no longer relevant with
the exception of male-only residential facilities (7.0%).

Youth Reports of Vulnerability

Facilities were assessed by the concentrations of vulnerable youth populations. These include
proportions of youth reporting lesbian, gay, or bisexual orientation, histories of prior sexual assault,
lower educational performance (such as two or more levels below the expected school grade level),
age mixture of youth in the facility (proportion of youth 14 and younger, 18 and older, and mixing
younger and older youth), no prior detention history, and the length of time in the facility (see table
24).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

57

Table 24

Continued on next page

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

58

Table 24
Facility-level victimization rate, by type of incident and youth reports of vulnerability, 2012
(continued)

Youth reports of vulnerability

%

Youth-on-youth
victimization rate

Staff sexual misconduct
victimization rate

Mean
Percent

Mean
Percent

Standard
Error

Standard
Error

Previous detention history
No history
0 up to 0.12 *

25

1.5 %

0.4

3.5 %

0.7

0.12 up to 0.19

24

1.9

0.4

4.8

0.8

0.19 up to 0.31

26

1.9

0.4

6.7 **

0.8

0.31 to 1

25

3.1 **

0.7

5.9 **

0.9

0 up to 0.47

25

3.4 % **

0.7

6.5 % **

0.8

0.47 up to 0.61

24

2.7 **

0.6

6.7 **

0.8

0.61 up to 0.82

26

1.6

0.4

3.9

0.7

0.82 to 1 *

25

0.7

0.3

3.9

0.8

Length of time in the facility
Less than 6 months

Note: Based on 322 unweighted juvenile facilities that returned a Facility Questionnaire. Four facilities were excluded from analysis.
**Difference with comparison group is significant at the 95%- confidence level.
*Comparison group.



In half of all facilities (50%), less than 7% of youth (0.07 and less) self-identified as
lesbian, gay, or bisexual .



Almost a third (29%) of facilities had no youth with a history of prior sexual assault,
compared to a quarter that had at least 25% (0.24 and above) with this history.



The majority of facilities (75%) had at least 9% of their youth (0.09 and above) two or
more grade levels below expected. A quarter had almost a third (0.32 and above) of
their youth population two or more grade levels below expected.



Half of all facilities had mixtures of much younger youth (less than 15) with older youth
(18 and older). Twenty-three percent housed only minor youth, and 1% housed only
adult youth (18 and older).



Approximately two-thirds of all facilities contained some proportion of youth 14 or
younger.



A quarter of all facilities had more than a third of their population (0.36 and above) 18
or older.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

59



Seventy-five percent of the facilities had large proportions of youth with previous
detention histories. Twenty-five percent of the facilities had approximately a third or
more (0.31 and above) of their population with no previous detention history.



The majority of youth (0.47 and above) in many facilities (75%) were there less than
6 months.

Bivariate Association With Youth-on-Youth Sexual Assault
Facilities with the highest rates of sexual assault by another youth were those with greater
proportions of youth with vulnerability characteristics, no history of prior incarceration, and longer
lengths of stay (see table 24).


Sexual assault by another youth was more prevalent in facilities with the highest
concentrations of lesbian, gay, or bisexual youth (5.0%) and youth with a prior history
of sexual assault (4.5%).



Facilities with moderate numbers of youth (0.09 to 0.18) two or more grade levels
below expected had the highest rates (3.2%).



Sexual assault by another youth was also more prevalent in facilities with greater
proportions of youth (0.31 and above) with no prior detention history (3.1%), and lower
proportions of youth (0 to 0.47) in the facility less than 6 months (3.4%).

Bivariate Association With Staff Sexual Misconduct
Vulnerability factors associated with staff sexual misconduct were opposite the factors associated
with youth-on-youth sexual assault. Lesbian, gay, or bisexual youth and those with histories of sexual
assault had the lowest rates. Similar to youth-on-youth assault, rates were lowest when the
proportion of youth had histories of incarceration, and shorter lengths of stay. Unlike youth-onyouth sexual assault, staff sexual misconduct was associated with the age mixture of youth in the
facility (see table 24).


Staff sexual misconduct was lowest in facilities with the highest concentrations of
lesbian, gay, or bisexual youth (3.1%) and youth with histories of prior sexual assault
(2.7%).



Facilities with less than 10% (0.09 or less) of youth below their expected grade level had
the lowest rates of staff sexual misconduct (3.6%).



The rate of staff sexual misconduct was higher (6.7%) in facilities that mix younger
minors (up to 14 years) with adults (18 or older).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

60



Staff sexual misconduct was most prevalent (8.9%) in facilities with smaller proportions
of youth ages 14 or younger (>0 up to 0.04) and in facilities where more than a third of
the youth (0.36 and above) population was 18 or older (7.1%).



Staff sexual misconduct was also less frequent in facilities when the proportions of
youth with no prior detention history (3.5%) were the smallest (0 to 0.12) and when
large concentrations of youth (0.61 and above) were in the facility less than 6 months
(3.9%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

61

Multivariate Findings for Youth-on-Youth Sexual Assault

Table 25
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and youth reports of vulnerability, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

62

After controlling for facility characteristics and entering all significant youth vulnerability factors into
the multivariate model, all remained predictive of youth-on-youth sexual assault (see table 25) with
the exception of length of time in the facility. Most structural characteristics were no longer relevant
with the exception of facilities with multiple living units.


Facilities had higher rates of youth-on-youth assault with greater-than-average
concentrations of lesbian, gay, or bisexual youth (2.9%), youth with histories of prior
sexual assault (3.0%), and those with no prior detention history (2.7%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

63

Multivariate Findings for Staff Sexual Misconduct

Table 26
Multivariate stepwise regression models of facility sexual victimization, by staff sexual
misconduct and youth reports of youth vulnerability, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

64

In the staff sexual misconduct multivariate models, two vulnerability factors remained predictive
after adjusting for structural characteristics. Facilities housing only male and larger facilities remained
important predictors of staff sexual misconduct (See table 26).


4.7

Staff sexual misconduct was lower in facilities that housed only minor youth (4.9%) but
higher when the majority of youth had no prior detention history (7.6%).

Youth Reports of Facility Order and Disorder

The level of order and disorder in the facility was measured along several dimensions: written
complaints against staff, youth perceptions of enough staff to monitor what was going on in the
facility, whether it was easy to break rules in the facility, and staff grooming behaviors, such as
sharing personal information with youth and providing special treatment to youth.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

65

Table 27
Facility-level victimization rate, by type of incident and youth reports of facility order and
disorder, 2012
Youth-on-youth
victimization rate
Mean
Standard
Percent Error

Youth reports of facility order and disorder
All facilities

Staff sexual
misconduct
victimization rate
Mean
Standard
Percent Error

100 % 2.1 %

0.3 %

5.2 %

0.4 %

0 up to 0.11*

25 % 0.6 %

0.3 %

1.1 %

0.3 %

0.11 up to 0.31

24

1.7

0.5

4.1 **

0.6

0.31 up to 0.50

25

2.6 **

0.5

7.6 **

0.8

26

3.5 **

0.7

7.9 **

1.1

Proportion of youth filed a written written complaint
against staff member

0.50 up to 1
Proportion of youth who report enough staff to monitor
what is going on
0 up to 0.60*

24 % 3.7 %

0.8 %

7.6 %

1.0 %

0.60 up to 0.74

26

2.4

0.4

6.9

0.8

0.74 up to 0.86

25

1.5 **

0.4

4.7 **

0.7

0.86 up to 1

25

0.9 **

0.3

1.6 **

0.5

Not easy to break rules
0 up to 0.43

24 % 3.2 % ** 0.7 %

5.4 % ** 0.9 %

0.43 up to 0.53

26

2.2

0.5

6.2 **

0.8

0.53 up to 0.67

29

1.6

0.3

5.9 **

0.8

0.67 - 1 *

21

1.6

0.5

2.9

0.6

Staff boundaries
Staff share personal information
0 up to 0.22 *

25 % 1.2 %

0.4 %

1.6 %

0.4 %

0.22 up to 0.33

18

2.8 **

0.6

5.1 **

0.6

0.33 up to 0.45

30

2.4

0.5

7.6 **

0.8

0.45 up to 1

27

2.2

0.6

6.0 **

1.0

Staff provide special treatment
0 up to 0.17 *

29 % 0.9 %

0.3 %

2.4 %

0.6 %

0.17 up to 0.25

16

2.4

0.5

4.2

0.6

0.25 up to 0.37

30

2.2

0.4

6.5 **

0.8

0.37 up to 1

25

3.2 **

0.7

7.6 **

0.9

Note: Based on 322 unweighted juvenile facilities that returned a Facility Questionnaire. Four facilities were excluded from analysis.
*Comparison group.
**Difference with comparison group is significant at the 95%- confidence level.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

66



In about three-quarters of all facilities (74%), less than half of all youth (less than 0.50)
reported filing a written complaint against a staff member.



In more than three-quarters of all facilities (76%), more than half of all youth (0.60 and
above) indicated that there was enough staff to monitor what was going on in the
facility.



In half of the facilities, the majority of all youth (0.53 and above) believed it was not
easy to break rules. In a quarter of the facilities, less than half of the youth population
reported it was not easy to break rules (less than 0.43).



There were varying reports of potential staff grooming behavior across facilities. In 27%
of the facilities, less than half or more (0.45 and above) of the youth reported staff
sharing personal information. In 30% of the facilities, at least a third (0.33 to 0.45)
reported staff sharing personal information, and in 25% of facilities, less than a quarter
(0.22 and below) of youth reported staff sharing personal information. Twenty-nine
percent of facilities had less than a fifth (less than 0.17) of youth reporting staff
providing special treatment, while more than half of the facilities (55%) had at least onequarter (0.25 and above) of youth reporting staff providing special treatment.

Bivariate Association With Youth-on-Youth Sexual Assault and Staff Sexual
Misconduct
All facility order and disorder factors were associated with increased prevalence of youth-on-youth
sexual assault and staff sexual misconduct. Rates of victimization were lowest in facilities when less
youth filed written complaints against staff, when there is sufficient staff to monitor the facility,
when there is consistent enforcement of rules, and when there is reduced staff grooming behaviors
(table 27).


Facilities had lower rates of victimization when less than 11% (below 0.11) of youth
filed a written complaint against a facility staff member.



The prevalence of victimization was lowest in facilities when most youth (0.86 and
above) reported that there were enough staff to monitor what was taking place in the
facility (0.9%, 1.6%) and when the majority of youth (0.67 and above) believed it was
not easy to break rules (1.6%, 2.9%).



Similar trends were also evident for staff grooming behaviors. The risk of victimization
was significantly lower (1.2%, 1.6% and 0.9%, 2.4%) when smaller numbers of youth
reported staff sharing personal information (0 to 0.22) and staff providing special
treatment (0 to 0.17).

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67

Multivariate Findings for Youth-on-Youth Sexual Assault

Table 28
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and youth reports of facility order and disorder, 2012

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68

After controlling for facility structural characteristics in the multivariate models, two predictors of
facility order and disorder were associated with victimization by another youth. Facilities with higher
rates of youth-on-youth sexual assault had more youth who reported filing written complaints
against a staff member (2.8%) (See table 28). Facilities had lower rates when more youth reported
that there was enough staff to monitor what was taking place in the facility (1.9%). Structural
characteristics such as housing only female residents and those providing sex offender treatment
remained significantly predictive of youth-on-youth sexual assault.

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69

Multivariate Findings for Staff Sexual Misconduct

Table 29
Multivariate stepwise regression models of facility sexual victimization, by staff sexual
misconduct and youth reports of facility order and disorder, 2012

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70

After adjusting for facility structural characteristic, the same factors of facility order and disorder
were predictive of staff sexual misconduct. In addition, staff grooming behaviors were also
associated with increased rates of staff sexual misconduct. Structural factors such as primary facility
type (e.g., detention centers, training/long-term secure), facilities housing male residents, and larger
facilities retained significance (see table 29) in the multivariate models.

4.8



Rates of staff sexual misconduct were higher in facilities when the majority of youth
reported filing written complaints against a staff member (8.3%) and when more youth
reported staff engaging in grooming behaviors such as sharing personal information
(7.4%).



Rates of staff sexual misconduct were lower in facilities when more youth reported that
there was enough staff to monitor what was taking place (6.0%).

Youth Reports of Facility Safety and Fairness

Fairness in the facility was measured using scales assessing positive perceptions of staff (eight items,
see Appendix B) and the level of lack of fairness (seven items, see Appendix B). Higher scores
indicate higher levels of positive perceptions and higher levels of lack of fairness. Physical safety was
captured by a three-item scale evaluating direct physical assault by another youth and/or staff (see
Appendix B), and a single item assessing worrying about being physically assaulted by another youth
and/or staff (see table 30).

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71

Table 30
Facility-level victimization rate, by type of incident and youth reports of facility safety and
fairness, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

72



The majority of youth in facilities reported moderate to high levels of positive
perceptions of staff. Half of all facilities had moderate levels (4.11 to 6.5 items) and one
quarter of facilities had high levels of positive perceptions of staff (6.5 to all 8 items).
Twenty-five percent of facilities had youth endorsing low levels of positive perceptions
of staff.



Similar trends were evident for lack of fairness with half of facilities with low to
moderate levels (0 to 2.89) and a quarter with higher levels (3.73 to 6).



More than half of all facilities, had low episodes of youth being assaulted by another
youth (less than one incident, 0 to 0.69, reported by the majority of youth in the facility).
In almost one third of all facilities (32%) there were no reports of youth assaulted by
staff and low incidents in the remaining facilities.



Most facilities had small numbers of youth (less than one item reported by most youth)
reporting worry about physical assault by another youth (74% of the facilities) or by
staff (73% of the facilities).

Bivariate Association With Youth-on-youth Sexual Assault and Staff Sexual
Misconduct
All of safety and fairness factors were associated with both types of victimization. Rates of youthon-youth assault and staff sexual misconduct were highest in facilities when youth had fewer positive
impressions of staff and perceived the facility to be unfair (see table 30). Reports of victimization
were also elevated in facilities when more youth reported being physically assaulted by other youth
and/or staff, or worrying about being assaulted by other youth and staff.


The prevalence of youth-on-youth sexual assault was twice (3.1% vs. 1.4%) as high and
for staff sexual misconduct was 10 times greater (9.7% vs. 0.9%) in facilities with the
fewest positive perceptions of staff compared to facilities with the most favorable
perceptions of staff.



In facilities with the highest concentrations of youth that perceived the facility to be
unfair, the rates of both types of victimization were significantly higher (4.0%, 10.3%)
than facilities with moderate to low concentrations of youth with these perceptions.



Rates of youth-on-youth and staff sexual misconduct are highest in facilities when more
youth reported physical assault by another youth (3.9%, 9.1%), physical assault by staff
(3.3%, 10.5%), worry about physical assault by another youth (4.3%, 8.2%) and/or
worry about physical assault by staff (3.3%, 11.2%).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

73

Multivariate Findings for Youth-on-youth Sexual Assault

Table 31
Multivariate stepwise regression models of facility sexual victimization, by youth-on-youth
incidence and by youth reports of safety and fairness, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

74

After controlling for the facility structural characteristics, only one safety and fairness factor was still
predictive of youth-on-youth sexual assault. Sexual assault by another youth was almost twice the
rate (3.0% vs. 1.6%) in facilities when the majority of youth worry about physical assault by another
youth (see table 31). Facilities housing only female residents and those providing sex offender
treatment remained significantly associated with elevated rates of youth-on-youth sexual assault in
the multivariate model.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

75

Multivariate Findings for Staff Sexual Misconduct

Table 32
Multivariate stepwise regression models of facility sexual victimization, by staff sexual
misconduct and youth reports of safety and fairness, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

76

In the staff multivariate model, three safety and fairness factors remained predictive of sexual
misconduct after adjusting for facility structural characteristics (see table 32). The highest rates of
victimization were in facilities where the majority of youth had less favorable perceptions of staff
(8.1%), when the majority of youth reported physical assault by staff (8.5%), and/or when the
majority of youth worried about physical assault by another youth (7.6%). Most structural factors
were no longer relevant with the exception of facilities with male residents.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

77

5.

Facility Profiles of Sexual Victimization

As shown in the previous section, the multivariate analysis examined facility characteristics and other
factors collected by the National Study of Youth in Custody (NSYC) surveys to assess the ability of
these factors to predict youth sexual victimization. These results present facility profiles that
describe the characteristics of facilities that are most likely to have higher rates of youth-on-youth
sexual assault (see figure 1) and staff sexual misconduct (see figure 2). These profiles present the
facility characteristics that have the strongest association with each type of sexual assault. Each
profile lists two sets of facility characteristics: (1) those that are common to high incidence of both
youth- and staff-perpetrated assaults and (2) those that are significant for one but not the other.
Below, the authors describe each of these sets.

5.1

Facility Characteristics Associated With Both Types of Sexual
Assault (Youth-on-Youth and Staff Sexual Misconduct)

There are several features of facilities that are associated with both youth and staff sexual assault.
Two features are related to facility order/disorder and gang fights. Facilities with higher rates of
sexual assault have more youth-based written complaints against staff, do not have enough staff to
monitor what takes place within the facility, and have higher levels of gang fights. Conversely, sexual
victimization is less prevalent in facilities where youth report that there are enough staff to monitor
what takes place within the facility, there is little to no gang fighting, and there are fewer complaints
against staff.
Other factors associated with both types of assault are indicators of safety, fairness and vulnerability
within the facilities. Facilities have the highest rates sexual assault when youth report worrying about
being physically assaulted by another youth. Facilities with more youth who have not previously
been incarcerated are also more likely to have high rates of sexual assault. This could be because
these youth are easier targets for perpetrators of assault or that no previous detention history is
correlated with other facility characteristics that are not measured in this study.

5.2

Facility Characteristics Exclusively Associated With a Single Type of
Sexual Assault

There are a number of differences between the characteristics of facilities with higher rates of sexual
assault by another youth and facilities with higher rates of staff sexual misconduct. Many of these
differences stem from the observation that youth-on-youth sexual assault is committed by female
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

78

youth against other female youth while staff sexual misconduct is primarily committed by female
staff against male youth. This general pattern is supported by the association between the gender
composition of the facility and the type of assault that is most prevalent. All-male facilities have
higher rates of staff sexual misconduct, while facilities that house only females have the highest rates
of youth-on-youth sexual assaults.
Aside from gender, facility differences in victimization type are evident when and if youth are
informed sexual activity is not allowed in the facility and the reasons why youth might not report
rule breaking about sexual activity in the facility. Sexual assault by another youth is more prevalent in
facilities when youth are informed that sexual activity is not allowed more than 7 days after their
arrival. Conversely, staff sexual misconduct is more prevalent when youth are never told that sexual
activity is not allowed. Rates of youth-on-youth sexual assault are highest in facilities when youth
might not report rule breaking about sexual activity because they are embarrassed or ashamed;
whereas, rates of staff sexual victimization are highest when youth might not report rule breaking
about sexual activity because they are afraid of being punished by facility staff.
Youth-on-Youth Sexual Assault. Youth in facilities with high rates of youth-on-youth sexual
assault are different in two other ways. This population is more likely to be lesbian, gay, or bisexual
and have histories of prior sexual assault and rape victimization. These have all been found to be risk
factors for sexual victimization in non-incarcerated populations, and sexual victimization history is
more predominate in females.
The other difference is in the type of structural characteristics. Facilities with high prevalence of
youth-on-youth sexual assault also house youth in multiple living units, and their youth populations
are more likely to have a most serious offense of violent sexual assault. These facilities also are more
likely to have a sex offender treatment program. These characteristics may be indicative of potential
perpetrators of assault and make these youth more prone to be victimized while incarcerated.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

79

Figure 1.

Facility characteristics associated with youth-on-youth sexual assault

Facility order
- written complaints about staff
- not enough staff

Gang fights
Worry about phy. asslt. by youth
No history of incarceration
Female residents
Informed sexual activity not allowed
>7 days

Might not report (embarrassed/
ashamed)
Risk factors associated with sexual abuse/victimization
- prior sexual assault
-LGB orientation

Multiple living units

Serious offenders
- violent sexual assault offense
- sexual offender treatment program

+
+
+
+
+
+
+
+

Youth-on-youth
Sexual
Assault

+
+
+
+
+

Italicized font indicates factors associated with
both youth-on-youth and staff sexual misconduct.

Staff Sexual Misconduct. The distinguishing characteristics of facilities with high rates of staff
sexual misconduct fall into three categories: (1) facility structural factors, (2) factors related to gangs
and person offenses, and (3) relationships between youth and staff. Structural factors include the
type and size of the facility, stability of staff within the facility, staff screening practices, and the age
of the youth within the facility. Facilities with high rates of staff sexual misconduct are more likely to
have 25 or more youth and their primary function is detention or a training/long-term secure
facility. They are also less likely to house only minors. Facilities with staff turnover that leads to a
reduction in staff size have a higher prevalence.
Second, high-rate facilities have particular difficulties related to gang membership and youth with
most serious offense histories that include person offenses, such as assault. As noted above, both
types of sexual assaults are positively related to gang activity and gang fights, but the occurrence of
staff sexual misconduct has a greater association with gang membership within the facility. Facilities
have elevated rates of staff sexual misconduct when a high proportion of youth report gang
membership and/or feeling pressured by the gang to do things they normally would not do.
Facilities housing more youth with person offenses as their most serious offense also have the
highest prevalence.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

80

Figure 2.

Facility characteristics associated with staff sexual misconduct

Facility order
- written complaints about staff
- not enough staff

Gang fights
Worry about phy asslt. by youth
No history of incarceration
Never informed, sexual activity not
allowed

Might not report (afraid of staff)
Facility Type
- large, long-term/detention
- not exclusively minors

Staff turnover (loss)
Staff screening for drug use
Gang membership/pressure

Person offense
Male residents
Staff relations
- positive perceptions
- physical assault by staff
- sanctions for fighting
- staff grooming

PREA compliance
- know how to report rule breaking
- would report sexual activity (faceto-face staff)

+
+
+
+
+
+
+
+
+
+
+
+
+
+

Staff
Sexual
Misconduct

+
+
+
+
-

Italicized font indicates factors are associated with youthon-youth and staff sexual misconduct

A third distinguishing characteristic of facilities with high rates of staff sexual misconduct is the
relationship between the staff and youth. Staff sexual misconduct is less prevalent in facilities where
youth report positive perceptions of staff. Staff sexual misconduct is more prevalent in facilities
where youth report being physically assaulted by staff, receiving sanctions for fighting, and staff
grooming behavior. Rates are elevated when staff share personal information to youth in their care
and when more youth are written up for threatening9 or fighting with staff and/or other youth.

9

Threatening is specific to staff only and was not assessed for youth.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

81

Finally, facilities with low rates of staff sexual misconduct have more indicators of PREA
compliance, such as youth that would report sexual activity face-to-face to a facility staff member.
These facilities may be more effective in preventing victimization because they create a climate
where youth are more likely to report sexual activity because they trust staff. There is also some
indication that youth knowing how to make a report if a staff member or youth is breaking the rules
is associated with staff sexual misconduct; however, as previously noted, the results are inconclusive
and need further research.

5.3

Summary of Facility Profiles of Sexual Victimization

As presented in the above profiles, facilities with high rates of sexual assault are distinguished by
operational characteristics, such as staffing instability, youth-based written complaints against staff,
staff grooming behavior, and the characteristics of the youth they serve and their impact on the
environment (e.g., gang activity, gang membership, and pressure). There are also factors that might
make youth more vulnerable to victimization, such as a history of sexual assault or rape and their
sexual orientation. These profiles provide with a clear description of the types of facilities where
youth are at highest risk of sexual assault.
However, some of these characteristics could be a function of who has been victimized within the
facility, rather than a general characteristic of the facility. For example, it might be that individual
youth who have experienced grooming on the part of the staff are the ones reporting victimization.
Grooming might not be prevalent throughout the facility. While in this case grooming is still a
problematic behavior, it could be individual staff that need targeting, rather than something that
occurs among all the staff members. In order to further explore these distinctions, the next section
discusses the correlates of individual reports of victimization.

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82

6.

Individual-Level Findings

In addition to identifying facility-level characteristics, as presented in the above sections, this analysis
explored individual-level factors to determine which characteristics placed youth at greatest risk.
Individual demographic characteristics, risk factors known to be associated with sexual victimization
(i.e., lesbian, gay, or bisexual orientation, sexual victimization history), and other factors identified
through the facility-level analysis (e.g., offense history, gang involvement, fighting, and perceptions
of facility order and disorder) were tested at the bivariate level to assess which best predicted
individual reports of victimization. All individual-level factors were then entered into a final
multivariate model to determine which characteristics place individual youth at greatest risk for
sexual assault. All results are weighted and represent 17,469 youth. The following sections and tables
describe each of the analytic steps.

6.1

Youth Demographic Characteristics

Youth demographic characteristics such as sex, age, race, and body mass index (BMI) were
examined. Bivariate results showed that sex and race were associated with both types of sexual
victimization (See table 33).

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83

Table 33
Individual-level victimization rate, by type of incident and and youth demographic
characteristics, 2012



Rates of youth-on-youth sexual assault were significantly higher for females (5.4%) than
males (2.2%) and higher for whites (3.9%) than for blacks (1.5%) and Hispanics (2.1%).
Even though rates were greater among youth 14 and younger and those with a BMI
score of 1 to 22, these factors were not significant.



Rates of staff sexual misconduct were counter to the youth-on-youth rates with males
(8.1%) having significantly higher rates than females (2.9%) and black youth (9.4%)
more at risk than whites (6.5%). Youth 14 and younger were at significantly lower risk
(3.8%) than those 18 and older (8.6%). Youth with a BMI score of 1 to 22 had the
highest rates but this factor was not significant.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

84

6.2

Youth Risk Characteristics

The relationship between specific youth risk characteristics was assessed with sexual victimization,
including sexual-assault history, whether their last grade completed was below their expected grade
level, lesbian, gay, or bisexual orientation, previous detention history, and whether their time in the
facility was less than 6 months (see table 34).

Table 34
Individual-level victimization rate, by type of incident and youth risk characteristics, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

85



Youth-on-youth sexual assault was significantly more likely for youth with a history of
sexual assault (9.4%), those reporting lesbian, gay, or bisexual orientation (10.5%), and
those spending 6 months or more in the facility (3.3%). Expected grade level and
previous detention history was not associated with assault by another youth.



Similar patterns were also apparent for staff sexual misconduct. Rates were significantly
higher for youth with a sexual assault history (9.8%) and for youth spending 6 months
or more in the facility (9.4%). Expected grade level, previous detention history, and
lesbian, gay, or bisexual orientation were not significant with staff sexual misconduct.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

86

6.3

Most Serious Offense, Gang Involvement, and Fighting in the Facility

Most serious offense, reports of gang fighting and gang involvement, and fighting in the facility were
examined with each type of victimization (see Table 35).

Table 35
Individual-level victimization rate, by type of incident and most serious offense history, gang
involvement, and fighting in the facility, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

87

10



Youth with violent sexual assault (7.2%) as their most serious offense had significantly
higher incidents of youth-on-youth sexual assault. Youth with a most serious offense of
murder or person offenses (8.8%) and other (8.1%) crimes10 had higher rates of staff
sexual misconduct, but these associations were not significant.



Reports combining gang involvement, gang pressure and feelings of safety were all
significantly related to higher rates of youth-on-youth sexual assault, as was being
written up for fighting one time (3.3%) or three or more times (7.0%) and reports of
gang fighting (3.8%).



Reports combining gang involvement, gang pressure, and feelings of safety were all
significantly related to higher incidents of staff sexual misconduct, as was being written
up for fighting three or more times (22.0%) and reports of gang fights (13.0%).

Includes status offenses, probation/parole violations, or public order offenses

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

88

6.4

Youth Reports of Facility Order and Disorder

Table 36
Individual-level victimization rate, by type of incident and youth reports of facility order and
disorder, 2012



Youth reports of a lack of a well-defined structure11 in their facility had significantly
higher rates of both types of assault—6.3% for youth-on-youth and 32.4% for staff
sexual misconduct (see Table 36).



Similar significant patterns are also evident for youth in facilities where it was easy to
break rules (3.1% and 9.8%), where staff shared personal information (3.8% and
15.2%), and where staff provided special treatment (4.7% and 15.7%).

Since all the items related to PREA standards in the youth portion of the survey were assessed as facility-level
indicators, most of these items were excluded from the individual-level analyses. However, there was a need to create a
similar parallel measure that could be tested at the individual level. The well-defined indicator uses three items related
to youth perceptions of PREA standards and the one item about enough staff to monitor what takes place in the
facility. The four items were summed together to create a scale with higher scores indicating more structure (see
Appendix C for item).

11

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

89

6.5

Youth Reports of Safety and Fairness

Table 37
Individual-level victimization rate, by type of incident and youth reports of safety and
fairness, 2012



Youth without positive perceptions of staff and those who reported an overall lack of
fairness in the facility had the highest rates of both types of sexual assault, 3.5% and
3.6% for youth-on-youth and 21.4% and 16.2% for staff sexual misconduct (see table
37).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

90

6.6



Youth experiencing physical assault and/or worrying about physical assaults, either by
youth or by staff, were also more likely to report incidences of sexual assault by another
youth. Youth physically assaulted by another youth (4.5%), physically hurt by another
youth (6.2%), physically assaulted by staff (6.1%), physically hurt by staff (6.4%), and
those worrying about physical assault by another youth (5.5%), and/or worrying about
physical assault by staff (5.8%) had elevated rates of youth-on-youth sexual assault.



Similar results were also noted for staff sexual misconduct with youth physically
assaulted by another youth (12.5%) and/or staff (27.3%), those physically hurt by
another youth (14.7%) and/or staff (28.3%), and those worrying about physical assault
by another youth (13.2%) and/or by staff (22.9%) with the highest rates.

Multivariate Findings for Youth-on-Youth Sexual Assault and Staff
Sexual Misconduct

Individual-level youth characteristics and perceptions were entered into weighted multivariate
logistic regression models to identify key predictors associated with each type of sexual
victimization. The report presents the findings by individual demographics, risk factors, and other
factors such as offense history, gang involvement, fighting, perceptions of facility order and
disorder, etc. using the predicted probabilities based on observations (PPO) approach (see
Methodology section for more information about the stepwise procedure and calculating predicted
probabilities).12

Predictors used in the statistical analyses were tested for multicollinearity in various models. For some predictors, the
correlation was significant, making it difficult to disentangle the separate effects. For example, females were much
more likely to report a lesbian or bisexual orientation than males to report gay or bisexual orientation. This covariation
makes the relative importance of sexual orientation in the final models less certain and likely to be interchangeable with
gender.

12

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

91

Table 38
Final weighted multivariate logistic stepwise regression models, by type of incident and
individual youth factors, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

92

Table 38
Final weighted multivariate logistic stepwise regression models, by type of incident and
individual youth factors, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

93

Table 38
Final weighted multivariate logistic stepwise regression models, by type of incident and
individual youth factors, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

94

Table 38
Final weighted multivariate logistic stepwise regression models, by type of incident and
individual youth factors, 2012 (continued)

After assessing the relevant strength and contribution of each predictor using the stepwise selection
method, race and gender were associated with staff sexual misconduct (see Table 38).


The rate of staff sexual misconduct was more than twice as high for males (8.1%) than
for females (3.5%), and was significantly higher for black, non-Hispanic youth (8.4%)
than all other racial groups (7.1%). Race and sex of youth were not significant factors in
the youth-on-youth model.

After adjusting for other factors, several youth vulnerability characteristics were significantly
associated with both types of sexual victimization.


Youth with a history of sexual assault were more likely to experience youth-on-youth
(4.8%) and/or staff sexual misconduct (10.5%) compared to youth without
victimization history (1.8% and 7.3%).



Lesbian, gay, or bisexual youth (7.0%) were more than four times more likely that
heterosexual youth (1.6%) to be assaulted by another youth.



Youth with a detention history of 6 months or more (8.2%) and youth with no previous
detention history (8.2%) were more likely to experience staff sexual assault than youth
with a previous history of less than 6 months (6.8%).

Based on the individual youth-level models, most serious offense and gang fighting in the facility
were predictive of youth-on-youth assault while gang involvement and gang fighting were predictive
of staff sexual misconduct.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

95



Youth with a history of violent sexual assault (5.0%) as their most serious offense were
more than twice as likely to experience youth-on-youth sexual assault compared to
youth with other types of most serious offense histories (2.1%). Offense history was not
significant in the staff multivariate model.



Youth reporting gang fighting in the facilities had elevated rates of youth-on-youth
sexual assault (3.0%) and staff sexual misconduct (8.4%).



Youth reporting gang involvement with pressure and feeling safer (15.8%) had the
highest rates of staff sexual misconduct compared to other types of gang involvement.

A lack of structure in the facility, staff with poor boundaries, and youth perceptions of staff were
related to elevated rates of sexual assault after controlling for other factors.


Facilities with youth reports of high structure (1.7%) had significantly lower youth-onyouth sexual assault rates than all other levels of structure (3.0%). Conversely, rates were
higher when staff provided special treatment (3.3%). Similar trends with significantly
higher rates were also noted for staff sexual misconduct with staff sharing personal
information (10.0%) and staff providing special treatment (9.8%).



Youth reports of an overall lack of fairness in the facility (9.8%) and lack of positive
perceptions of staff (8.3%) were also indicative of staff sexual misconduct.

Reports of being physically hurt and worrying about physical assault were predictive of both types of
sexual assault in the logistic regression models.


Youth physically hurt by another youth (4.0%) and worrying about physical assault by
staff (4.1%) were indicators of youth-on-youth assault.



Similarly, being physically hurt by another youth (8.9%), physically assaulted by staff
(9.2%), physically hurt by staff (10.4%), and worrying about physical assault by staff
(8.7%) were predictive of staff sexual misconduct.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

96

7.

Individual Profiles of Sexual Victimization

In this section, the report provides the results of the individual-level reports of assault, highlighting
the most significant variables found in the multivariate models. The report presents two sets of
youth characteristics: (1) those that are common to high incidence of both youth and staff
perpetrated assaults and (2) those that are significant for one but not the other. Below, each of these
sets is described.

7.1

Youth Characteristics Associated With Both Types of Sexual Assault
(Youth-on-Youth and Staff Sexual Misconduct)

There are several factors that placed youth at greater risk for all types of sexual assault. One such
feature is a pattern of overall victimization. Youth at greatest risk for both types of assault have a
history of prior sexual assault and are more likely to report a pattern of physical victimization while
in the facility. This pattern includes being hurt by another youth and also worrying about physical
assault by staff. Other features are related to the climate of the facility and staff boundaries. Youth
reports of gang fights in the facility and staff providing special treatment were most at risk for both
types of sexual victimization.

7.2

Youth Characteristics Exclusively Associated With Youth-on-Youth
Sexual Assault

There are a number of differences between the types of youth with higher rates of sexual assault by
another youth and those with higher rates of staff sexual misconduct. One such difference is related
to sexual orientation (see figure 3). Youth-on-youth assault rates were highest for youth selfidentifying as lesbian, gay, or bisexual. Other differences include youths’ most serious offense
history and youth perceptions of facility structure. Youth having violent sexual assault as their most
serious offense were at greater risk for sexual assault by another youth. This characteristic may
indicate a perpetrator profile, but it also places them at greater risk for victimization. Youth
reporting lower levels of well-defined structure were also at greater risk, while those reporting the
highest level of structure were at the lowest risk.

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97

Figure 3.

Youth characteristics associated with youth-on-youth sexual assault

Pattern of victimization
- prior sexual assault
- hurt by youth
- worry about phy asslt by staff

Gang fights

Staff provide special treatment
LGB orientation

+
+
+
+
+

+

Violent sexual assault offense

+

Well defined structure

-

Youth-on-youth
Sexual
Assault

Italicized font indicates factors are associated with youth-on-youth
and staff sexual misconduct

7.3

Youth Characteristics Exclusively Associated With Staff Sexual
Misconduct

There are several distinguishing characteristics of youth who are at greater risk of staff sexual
misconduct (see figure 4). One such characteristic is related to gender. Males are much more likely
to be victims of staff sexual misconduct than females. Other characteristics include youth profiles
that make them appear to be institutionalized or more adapted to facility environments. These
include a history of prior incarceration lasting 6 months or more and active gang involvement in the
facility. These types of characteristics may make these youth more vulnerable to inappropriate sexual
relationships with female staff perpetrators.
Race was one unique characteristic that placed some youth at an increased risk for staff sexual
misconduct. Black, non-Hispanic youth were more likely to experience staff sexual misconduct than
other racial groups. One possible explanation for the higher rates among black youth may be related
to race of the staff perpetrator. Staff may choose to have inappropriate sexual relationships with
youth of the same race and many facilities may have more black staff placing youth of the same
racial background at higher risk. Future exploration is recommended to thoroughly test the
possibility of this explanation.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

98

Finally, youth experiencing higher rates of staff sexual misconduct also report challenging facility
environments that include little to no positive perceptions of staff, lack of fairness, and overall
problematic staff behavior. Rates were highest for youth when they reported no positive perceptions
of staff, high levels of a lack of fairness, and staff sharing personal information. These youth were
also more likely to experience physical assault and being physically hurt by staff.
Figure 4.

Youth characteristics associated with staff sexual misconduct

Pattern of Victimization
-prior sexual assault
- hurt by youth
- worry about phy.asslt by staff

Gang Fights

+
+
+
+

Staff provide special treatment

+

Male youth

+

Prior incarceration of less than 6
months
Gang involvement
Youth demographic characteristics
-youth race

+
+

Positive perceptions of staff

-

Lack of fairness

+

Staff behavior

Staff
Sexual
Misconduct

- staff share personal information

+

- phy asslt/phy hurt by staff

+

Italicized font indicates factors are associated with
youth-on-youth and staff sexual misconduct

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

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7.4

Summary of Individual Profiles of Sexual Victimization

Youth most at risk for sexual assault by another youth are more likely to fit a victimization profile.
They are lesbian, gay, or bisexual and are more likely to be physically hurt by another youth. Their
offense history of violent sexual assault also places them at greater risk for victimization of other
youth as a method of retaliation for their crime.
Conversely, youth at greatest risk for staff sexual misconduct fit a more institutionalized profile.
These youth are more likely to have longer histories of prior incarceration and are involved in gang
activity in the facility. They also report more problematic and chaotic facility environments. This
type of climate, in addition to more antisocial behavior (i.e., gang involvement), may make them
more likely to be susceptible to inappropriate sexual relationships with staff as a way to gain status
or safety while in the facility. Because these youth may also be more institutionalized, they may be
more likely to be targets for female staff. This information provides distinct profiles of youth most
at risk for different types of sexual victimization.

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8.

Discussion of Findings by Research Question
a.

Does the rate of youth sexual victimization vary across facilities?

Results show that there is significant variation in the rates of all types of sexual victimization across
facilities. The average facility-level rate of sexual assault by another youth was 2.1% and was
reported in a third of the facilities. This means that a third of all facilities account for all incidents of
youth-on-youth sexual assault. Similar results were also evident for staff sexual misconduct. The
average rate of staff sexual misconduct at the facility level was 5.2%, but about half of the facilities
had any youth who reported incidents.
b.

What facility-level attributes are associated with sexual victimization?

The facility analyses demonstrated several facility-level attributes that are associated with sexual
victimization. One of the strongest is the association between the gender composition of the facility
and the type of assault. All-male facilities have higher rates of staff sexual misconduct, while facilities
that house only females have the highest rates of youth-on-youth sexual assaults. Facilities with high
rates of sexual assault are also distinguished by other attributes including operational characteristics,
such as staffing instability, lack of order, and staff grooming behavior. Lastly, these attributes include
the concentrated characteristics of the youth population and their impact on the environment
through antisocial behavior such as gang activity, gang membership, and pressure, as well as other
clustering of qualities that make youth more vulnerable to victimization, including a history of sexual
assault or rape and sexual orientation.
c.

What youth characteristics are correlated with sexual victimization?

Youth at greatest risk for both types of assault have a history of prior sexual assault and are more
likely to report a pattern of physical victimization while in the facility. This pattern includes being
hurt by another youth and worrying about being hurt by staff. These youth also report gang fights in
the facility and staff providing special treatment.
Youth targeted by other youth for assault are more likely to be lesbian, gay, or bisexual and are more
likely to have a most serious offense history of violent sexual assault.
Youth victims of staff sexual misconduct seem to fit a different profile. For example, they are
disproportionately male. These youth are more likely to have longer histories of prior incarceration
and are the ones involved in gang activity in the facility. They also report more problematic facility
environments such as high levels of lack of fairness, staff sharing personal information, and no
positive perceptions of staff. These youth are also more likely to experience physical assault by staff
and to be physically hurt by staff.

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9.

Overall Discussion

These results separately analyzed facility and individual victimization rates. To get a complete picture
of what characteristics are most associated with sexual assault, the second part of this report will
combine these two levels of analysis into a single statistical model. Part II of this report will identify
how these facility and individual characteristics interact together. This will clarify the role the facility
factors in the occurrence of sexual victimization.
For example, the combined analysis will provide some perspective on the importance of facility
structural characteristics (i.e. sex of youth housed and size and type of facility), controlling for the
types of youth that reside in the facility. It might be that facilities that house females have higher
rates of youth-on-youth victimization because females are also more likely to be lesbian or bisexual,
an important individual risk factor. Similarly, larger facilities may have higher rates of both types of
victimization because they tend to house youth who become members of gangs in the facility.
The above analysis also identified characteristics related to youth perceptions in both the facility and
individual results. Higher rates of both types of sexual assault seem to be related to youth
perceptions of facility environments that have lack of structure and safety. Staff sexual misconduct
appears to be connected to negative interactions with staff. Facility victimization rates are
characterized by youth reporting gang fights and worrying about being physically assaulted by
another youth. These same characteristics are significantly related to individual reports of
victimization. Youth with high rates of victimization are also more likely to report a pattern of
assault in the facility such as being physically hurt by another youth and worrying about physical
assault by staff.
Youth perceptions specifically related to staff sexual misconduct also included additional factors
related to gangs. Facilities with higher rates of staff sexual misconduct have problems related to
gangs. Youth in these facilities are also more likely to experience staff sharing personal information
with youth in their care. Facilities with high rates of staff sexual misconduct have more youth who
receive sanctions for threating or fighting with staff and/or other youth (e.g., written up for
fighting). Similarly, high facility rates are also associated with youth having little to no positive
perceptions of staff and perceiving high levels of lack of fairness, and believe they experience more
physical assault and incidents of being physically hurt by staff. Many of these same factors are also
related to individual victimization risk. Clearly the behavior of the staff, how youth perceive them,
and the general climate of the facility are important correlates of victimization. The second part of
this analysis will test whether these perceptions are primarily related to those who report being
victimized, a prevalent characteristic of the facility, or both.

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NSYC-2 Findings Report:
Correlates of Youth Sexual Victimization (Part II)
Multilevel Results
10.

Overview

Part I of this report examined separate facility and individual characteristics in order to identify a
profile of places and individuals at highest risk of sexual assault. Facilities with high rates of both
types of assault share characteristics such as perceptions of disorder within the facility. Similarly,
high rates of individual risk of both types of sexual assault are characterized by reports of physical
assaults within the facility, as well as the occurrence of grooming behavior where staff provide
individuals with special treatment. Nonetheless, a number of characteristics are unique to either
youth-on-youth or staff sexual misconduct. With respect to the youth-on-youth sexual assault, being
female, being lesbian, gay, or bisexual, and having a history of sexual assault victimization are among
the more significant correlates. With respect to staff sexual misconduct, being in larger facilities,
having poor relationships with staff, and the occurrence of staff grooming in the form of sharing
personal information are among the more significant correlates.
To more fully develop a risk profile of facilities and youth, this second part of this report examines
both facility factors and individual youth characteristics in a single statistical model (see
Methodology section for more detailed discussion of the modeling approach). This approach further
clarifies the role of facility factors in predicting sexual victimization for individual youth. For
example, staff sexual misconduct appears to be connected to negative interactions with staff.
Facilities with high rates of staff sexual misconduct have youth with poor relationships with staff in
the form of more grooming, physical assaults, and negative perceptions. However, many of these
same characteristics also predict individual risk. Clearly the behavior of the staff, how youth perceive
them, and the general climate of the facility are important correlates of victimization. This set of
analyses tested whether these perceptions were primarily related to the youth who report being
victimized, to general characteristics of the facility, or both.

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11.

Research Questions

For this set of analyses, the report seeks to answer the following research question:


12.

What are the most important predictors of victimization at any level–facility factors,
youth characteristics, or both?

Highlights and Key Findings

Individual youth characteristics are more important than facility factors in the prediction of sexual
victimization in juvenile facilities.






Youth characteristics associated with all types of sexual assault. Youth with the
highest rates of sexual victimization:

–

have a history of prior sexual assault victimization

–

are more likely to report a pattern of non-sexual assault victimization while in the
facility that includes being hurt by another youth and worrying about being hurt
by staff

–

report gang fights in the facility

–

report staff providing special treatment to them.

Important individual youth characteristics associated with youth-on-youth
sexual assault:

–

Lesbian, gay, or bisexual youth have higher rates of youth-on-youth sexual
victimization compared to heterosexual youth.

–

Youth that have a most serious offense history of violent sexual assault are more
likely to experience sexual assault by another youth compared to youth without
this type of most serious offense.

–

Youth reporting high structure in the facility were less likely to experience youthon-youth sexual assault compared to youth reporting lower levels of structure.

Important individual youth characteristics associated with staff sexual
misconduct:

–

Males are more likely to be victims of staff sexual misconduct than females.

–

Youth with the highest rates of staff sexual misconduct report being a member of
a gang in the facility, high levels of a lack of fairness among staff, and staff sharing
personal information.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

104

–

Youth experiencing higher rates of staff sexual misconduct are more likely to
experience physical assault by staff, be physically hurt by staff, and do not have
positive perceptions of staff.

There are more facility factors that are important correlates of staff sexual misconduct when
compared to youth-on-youth sexual assault.


There was one significant facility factor associated with youth-on-youth sexual
assault victimization.

–


Youth in facilities with larger proportions of youth with a prior history of sexual
assault victimization had higher rates of youth-on-youth sexual victimization.

There are multiple facility factors that are important correlates of staff sexual
misconduct.

–

Youth in facilities that test staff for current drug use have higher rates of staff
sexual misconduct.

–

Youth in facilities that have higher proportions of youth filing written complaints
against a staff member have higher rates of staff sexual misconduct.

–

Youth in facilities that have higher proportions of youth with a most serious
offense of a person offense (e.g., assault) are more likely to have incidents of staff
sexual misconduct.

–

Youth in facilities with higher proportions of youth with no previous detention
history are more likely to experience staff sexual misconduct.

–

Youth who first learned sexual activity not allowed between 1 and 7 days of their
arrival at the facility have lower rates of staff sexual misconduct.

13.

Multilevel Predictor Section

13.1

Individual-Level Predictors

Individual-level predictors for the multilevel models were selected based on the findings of the final
individual-level multivariate logistic regression models (see table 38). All significant individual-level
predictors for each type of sexual assault were included as level 1 predictors in the multilevel
models.13

13

Variable label is bolded for emphasis

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105

For the youth-on-youth, significant predictors included:


Individual reports of sexual assault history;



Individual reports of lesbian, gay, or bisexual orientation;



Individual youth’s most serious offense responsible for current placement;



Individual reports of gang fights in facility;



Individual reports of a well-defined structure within the facility;



Individual reports that staff provide special treatment to the youth;



Individual reports that the youth was physically hurt by another youth; and



Individual reports that the youth worries about physical assault by staff.

For staff sexual misconduct, significant predictors included:


Sex of youth (male);



Individual reports of sexual assault history;



Individual youth’s previous detention history status;



Individual reports of being a gang member in facility;14



Individual report of gang fights in facility;



Individual reports that staff share personal information with the youth;



Individual reports that staff provide special treatment to the youth;



Individual reports of positive perceptions of staff;



Individual reports of lack of fairness in the facility;



Individual reports that the youth was physically hurt by another youth;



Individual reports that the youth was physically assaulted by staff;



Individual reports that the youth was physically hurt by staff; and



Individual reports that the youth worries about physical assault by staff.

One update was applied to the weighted logistic regression models (level 1) for staff sexual misconduct (see table 38).
To aid in interpretability of the results the multilevel “gang involvement-pressure and safety” predictor was collapsed
into two dichotomous predictor “gangs in facility”(not significant) and “gang member in facility” and the model reestimated to verify the results. Consequently, “youth race” became non-significant in the weighted logistic regression
model and was excluded from all multilevel models.

14

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

106

13.2

Facility-Level Predictors

The identification and selection of facility-level predictors were conducted using a series of steps.

13.2.1

Step 1: Block-by-Block, Facility-Level Predictor Selection

The analysis in Part I divided the variables into blocks based on their content. Step 1 selected the
facility-level predictors and involved using the same content groupings of predictors found in the
facility-level analyses (see Part I, page 6 for a full explanation of these content areas).15 To decide
which facility variables would be included in the multilevel model, a series of logistic regressions
were estimated for each block predicting individual-level victimization status. To find the significant
predictors in each block, stepwise procedures were used. First, all predictors listed in each block
were entered into the logistic regression. All predictors with a p<0.1 were retained. Next, all of the
significant predictors with a p<0.1 from each block were entered and predictors retaining
significance at the p<0.05 level are shown with an odds ratio16 and two asterisks in each table.
Results of the block-by-block analyses are presented below in tables 39 through 48.

13.2.1.1

Structure of Juvenile Facilities

Several key facility-level structural characteristics were correlated with the individual-level rate of
victimization (see tables 39 and 40)17,18 and are listed below by incident type.

Variations between the number/types of predictors presented in this report (Part II) versus Part I are discussed in the
footnotes throughout this report

15

Odds ratios greater than 1.0 represent a statistically higher rate of victimization, while an odds ratio less than 1.0
represents a statistically lower rate

16

Two structural predictors, “size of the facility by number of youth” and “size of the facility by number of adjudicated
youth,” were highly correlated and could not be entered into the same model. For consistency with Part I results, “size
of the facility by number of adjudicated youth” was included in the model and shown in table 1.

17

Table 39 and 40 findings are presented together because they are facility structural characteristics but each table
illustrates a separate model that includes only the predictors listed in the table.

18

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107

Table 39
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of structure of Juvenile Facilities, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

108

Table 40
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of type of treatment and assignment factors used in juvenile facilities,
2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

109

Table 40
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of type of treatment and assignment factors used in juvenile facilities,
2012 (continued)



For youth-on-youth sexual assault:

–

Facility over capacity (lower rates);

–

Primary facility type—detention or training/long-term secure (higher rates);

–

Operating agency—non-state (higher rates);

–

Sex of youth housed—males only (lower rates);

–

Sex offender treatment program (higher rates);and

–

Assignment factors to units—risk of escape (lower rates), danger to self (higher
rates), and gender (higher).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

110



For staff sexual misconduct:

–

Size of the facility by number of adjudicated youth (higher rates);

–

Facility over capacity (lower rates);

–

Primary facility type—detention or training/long-term secure (higher rates);

–

Sex of youth housed—males only and both (higher rates);

–

Sex offender treatment program (lower rates);

–

Violent offender treatment program (higher rates); and

–

Assignment factors to unit—age (higher rates).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

111

13.2.1.2

Staff Characteristics

A single staff characteristic for each type of assault was associated with individual-level victimization.

Table 41
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of staff characteristics, 2012



For staff sexual misconduct: Staff changes in the past 12 months—added and lost, lost
staff only (higher rates) 19



For youth-on-youth: Total proportion of frontline female staff (higher rates)20

“Location of monitoring” predictors were excluded from the model since these were highly correlated with overall
“monitoring.” “Staff to youth ratios compliance—secure facilities only” was excluded since it is a subset of all facilities.

19

The “total proportion of female staff” and the “total proportion of frontline female staff” were highly correlated so
the “total proportion of frontline female staff” was kept in the model to maintain consistency with Part I results.

20

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

112

13.2.1.3

Compliance With PREA Standards

Several facility-level factors related to compliance with PREA standards were associated with
individual-level victimization.

Table 42
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of compliance with PREA standards, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

113

Table 42
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of compliance with PREA standards, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

114



Staff screening—testing current drug use was correlated with higher rates of both types
of individual-level victimization.



For youth-on-youth sexual assault:



–

Facilities using video surveillance (higher rates);

–

Proportion of youth who first learned sexual activity was not allowed—more than
7 days (higher rates);

–

Proportion of youth willing to report breaking rules about sexual activity—
definitely (higher rates); and

–

Proportion of youth whose reason not reporting breaking rules about sexual
activity—embarrassed/ashamed (higher rates).

For staff sexual misconduct:

–

Staff to youth ratios compliance—1:8 evening (higher rates);

–

Staff to youth ratios compliance—1:16 night (lower rates);

–

Proportion of youth who first learned sexual activity was not allowed—within
first 24 hours (lower rates);

–

Proportion of youth who first learned sexual activity was not allowed—between 1
and 7 days (lower rates);

–

Proportion of youth who learned how sexual activity not allowed—one-on-one
with session staff (higher rates);

–

Proportion of youth who learned how sexual activity not allowed—group session
with more than 6 youth (lower rates);

–

Proportion of youth who would report sexual activity in the following way—faceto-face with staff member (lower rates);

–

Proportion of youth who would report sexual activity in the following way—use a
phone to call someone (higher rates);

–

Proportion of youth whose reasons for not reporting breaking rules about sexual
activity—afraid of being punished by staff involved (higher rates); and

–

Proportion of youth whose reason for not reporting breaking rules about sexual
activity—did not want to be a snitch or tattletale (lower rates).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

115

13.2.1.4

Youths’ History

Several facility-level youth history problems, conditions, patterns of behavior, and most serious
offense leading to current placement were associated with individual-level victimization.

Table 43
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of youths' history, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

116

Table 44
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of youth offense history, 2012



For youth-on-youth sexual assault:21
–
Percentage of youth in the facility with history of prostitution (higher rates);



–

Proportion of youth with a most serious offense of murder (higher rates); and

–

Proportion of youth with a most serious offense of violent sexual assault (higher
rates).

For staff sexual misconduct:

–

Percentage of youth in the facility with a history of violence toward others (lower
rates);

–

Percentage of youth in the facility with a history of abuse by parents (higher
rates);

–

Percentage of youth in the facility with a history of predatory sexual behavior
(higher rates);

–

Percentage of youth in the facility with a history of gang membership/affiliation
(higher rates);

–

Percentage of youth in the facility with a history of a psychiatric condition (lower
rates);

Table 43 and 44 findings are presented together because they are part of youths’ history, but each table illustrates a
separate model that includes only the predictors listed in the table.

21

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

117

13.2.1.5

–

Proportion of youth with a most serious offense of murder (higher rates);

–

Proportion of youth with a most serious offense of violent sexual assault (higher
rates);

–

Proportion of youth with a most serious offense of a person offense (higher
rates);

–

Proportion of youth with a most serious offense of a property offense (higher
rates); and

–

Proportion of youth with a most serious offense as other offense22 (higher rates).

Youth Reports of Involvement With Gangs and Fighting

The proportion of youth reporting gangs in facility (higher rates) was the only facility-level predictor
significantly correlated with youth-on-youth sexual assault. The proportion of youth written up for
fighting and the proportion of youth reporting gang membership in the facility (higher rates) were
related to staff sexual misconduct.

22

Includes status offenses, probation/parole violations, public order offenses

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

118

Table 45
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of youth reports of involvement with gangs and fighting, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

119

13.2.1.6

Youth Reports of Vulnerability

Several facility-level predictors were correlated with individual-level sexual victimization.

Table 46
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of youth reports of vulnerability, 2012





For youth-on-youth sexual assault:

–

Proportion of youth reporting lesbian, gay, or bisexual orientation (higher rates);

–

Proportion of youth reporting prior sexual assault (higher rates);

–

Proportion of youth with no previous detention history (higher rates); and

–

Proportion of youth in the facility for less than 6 months (lower rates).

For staff sexual misconduct:

–

Proportion of youth reporting prior sexual assault (lower rates);

–

Age mixture of youth in the facility—only minors (lower rates);

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

120

13.2.1.7

–

Proportion of youth 14 and younger (lower rates);

–

Proportion of youth with no previous detention history (higher rates); and

–

Proportion of youth length in the facility for less than 6 months (lower rates).

Youth Reports of Facility Order and Disorder

Youth reports of facility order and disorder were associated with both types of individual-level
victimization.

Table 47
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of youth reports of facility order and disorder, 2012





For youth-on-youth sexual assault:

–

Proportion of youth who filed a written complaint against staff member (higher
rates);

–

Proportion of youth reporting that it was not easy to break rules (lower rates);

–

Proportion of youth reporting staff shared personal information (lower rates); and

–

Proportion of youth reporting staff provided special treatment (higher rates).

For staff sexual misconduct:

–

Proportion of youth who filed a written complaint against a staff member (higher
rates); and

–

Proportion of youth reporting staff provided special treatment (higher rates).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

121

13.2.1.8

Youth Reports of Facility Safety and Fairness

The only facility-level predictor significantly associated with youth-on-youth sexual assault was the
proportion of youth worrying about physical assault by another youth (higher rates). Several
predictors were correlated with staff sexual misconduct.

Table 48
Multivariate logistic regression models of sexual victimization, by incident type and facility
predictor selection of youth reports of facility safety and fairness, 2012



For staff sexual misconduct:

–

Proportion of youth reporting positive perceptions of staff (lower rates);

–

Proportion of youth reporting a physical assault by youth (higher rates); and

–

Proportion of youth reporting a physical assault by staff (higher rates).

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13.2.2

Step 2: Level 2 One-by-One Predictor Selection

Step 2 involved testing each significant facility-level predictor found in step 1 (e.g., the block-byblock selection) with all individual-level predictors (level 1). This was completed by entering each
facility predictor individually23 (level 2) with all individual-level predictors (level 1) and assessing if
significance was retained. This procedure maximized the possibility of retaining significant facilitylevel predictors with individual-level predictors. Tables 49 and 50 provide the results when each of
the level 2 predictors were entered into the equation without any other level 2 predictors, but
included all level 1 predictors (see tables 49 and 50).

In step 2, all levels of categorical predictors were entered into the model if at least one of the categories was
statistically significant in step 1.

23

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123

Table 49
Weighted multilevel logistic regression models, by youth-on-youth sexual victimization and
level 2 one-by-one predictor selection, 2012

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124

Table 49
Weighted multilevel logistic regression models, by youth-on-youth sexual victimization and
level 2 one-by-one predictor selection, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

125

For youth-on-youth sexual assault, the only facility-level predictor retaining significance (e.g.,
p<0.05) in the multilevel modeling one-by-one selection procedure was the proportion of youth
with a history of prior sexual assault victimization. All individual youth (level 1) predictors remained
significant throughout the one-by-one level 2 selection process.

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126

Table 50
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2 one-byone predictor selection, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

127

Table 50
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2 one-byone predictor selection, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

128

Table 50
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2 one-byone predictor selection, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

129

Table 50
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2 one-byone predictor selection, 2012 (continued)

For staff sexual misconduct, several facility-level predictors retained significance in the multilevel
model one-by-one selection procedure. There were:


Size of the facility by number of adjudicated youth;



Primary facility type;



Sex offender treatment;



Staff changes in the past 12 months;



Staff screening—testing for current drug use;

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

Proportion of youth who first learned sexual activity not allowed in the first 24 hours;



Proportion of youth who first learned sexual activity not allowed between 1 and 7 days;



Proportion of youth who would report sexual activity face-to-face with staff member;



Proportion of youth whose reason for not reporting breaking rules about sexual
activity—afraid of being punished by staff involved;



Proportion of youth with most serious offense as person offense;



Proportion of youth written up for fighting;



Age mixture of youth in the facility;



Proportion of youth with no previous detention history;



Proportion of youth who filed a written complaint against a staff member; and



Proportion of youth reporting positive perceptions of staff.

All individual-level (level 1) predictors remained significant throughout the one-by-one facility
selection process (level 2) with the exception of no previous detention history, which was
consistently non-significant throughout all models. Consequently, it was eliminated from the
analyses.

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13.2.3

Step 3: Level 2 Stepwise Predictor Selection

In Part I of this report, the stepwise selection method was applied to all multivariate models to
eliminate non-significant predictors and estimate parsimonious models. For consistency, this
approach was also applied to the Part II multilevel analysis using the following stages:
a.

All significant individual-level predictors (level 1) from step 2 were entered all at once
into the model.

b.

Significant facility-level predictors (level 2) identified in step 2 were entered sequentially.
based on the p-values generated in the multilevel one-by-one testing phase.24

c.

In each model, level 2 predictors with smaller p-values25 were tested first, while
predictors with larger p-values were entered later. As each was added, all predictors with
a p-value of 0.05 or less were retained while all predictors with a p-value of >0.05 were
excluded.

The order of entry and the results are shown in table 51, and the findings are summarized below.

This part of the analysis was only applicable to staff sexual misconduct because there was only one significant level 2
predictor in the youth-on-youth model.

24

For all categorical predictors, the level with the smallest p value was used to determine order of entry. All levels of
categorical predictors were tested first, but only significant levels were included in subsequent models.

25

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132

Table 51
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2
stepwise predictor selection, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

133

Table 51
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2
stepwise predictor selection, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

134

Table 51
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2
stepwise predictor selection, 2012 (continued)

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135

Table 51
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2
stepwise predictor selection, 2012 (continued)

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136

Table 51
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2
stepwise predictor selection, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

137

Table 51
Weighted multilevel logistic regression models, by staff sexual misconduct and level 2
stepwise predictor selection, 2012 (continued)

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

138

1.

Proportion of youth who would report sexual activity face-to-face with staff member
had the lowest p-value and was tested first in model 1. Significance was retained until
model 4, where it was not significant and subsequently eliminated.

2.

Staff screening—testing for current drug use was tested next in model 2. Significance
was retained throughout all models.

3.

Proportion of youth with a most serious offense as a person offense was tested next in
model 3. Significance was retained throughout all models, except in model 16 due to
entry of the proportion of youth who first learned sexual activity was not allowed in the
first 24 hours, which was not significant. Therefore, it was advanced to the final model
where significance was retained.

4.

Proportion of youth that filed a written complaint against staff member was tested in
model 4. Significance was retained throughout all models.

5.

Proportion of youth written up for fighting was tested in model 5. It was not significant
and was eliminated.

6.

Size of the facility was tested in model 6. A size of 26 to 50 and 101 or more were
significant and were tested separately in model 7. In model 7, size of facility was not
significant and was eliminated.

7.

Proportion of youth whose reason for not reporting breaking rules about sexual
activity—afraid of being punished by staff involved was tested in model 8. It was not
significant and was eliminated.

8.

Primary facility type was tested in model 9. It was not significant and was eliminated.

9.

Proportion of youth reporting positive perceptions of staff in a facility was tested in
model 10. It was not significant and was eliminated.

10.

Staff changes in past 12 months was tested in model 11. It was not significant and was
eliminated.

11.

Sex offender treatment was tested in model 12. It was not significant and was
eliminated.

12.

Proportion of youth who first learned sexual activity not allowed between 1 and 7 days
was tested in model 13. Significance was retained throughout the remaining models.

13.

Age mixture of youth in the facility was tested in model 14. It was not significant and
was eliminated.

14.

Proportion of youth with no previous detention history was tested in model 15.
Significance was retained throughout the remaining models.

15.

Proportion of youth who first learned sexual activity was not allowed in the first 24
hours was tested in model 16. It was not significant and was eliminated.

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13.2.4

Step 4: Final Model Predictor Selection

Step 4 included final model estimation of all individual-level predictors (level 1) and the significant
facility-level predictors (level 2) identified in steps 1 through 3. For youth-on-youth sexual assault,
there was one significant level 2 predictor (proportion of youth reporting prior sexual assault) (see
table 52). For staff sexual misconduct, the following level 2 predictors remained significant with
individual-level victimization (see table 53) and were included in the final multilevel model:


Staff screening—testing for current drug use;



Proportion of youth with a most serious offense of person offense;



Proportion of youth with no previous detention history;



Proportion of youth who first learned sexual activity not allowed between 1 and 7 days;
and



Proportion of youth who filed a written complaint against a staff member.

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Table 52
Final weighted multilevel logistic stepwise regression models, by youth-on-youth sexual
victimization and combined individual youth and facility factors, 2012

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141

Table 53
Final weighted multilevel logistic stepwise regression models, by staff sexual misconduct and
combined individual youth and facility factors, 2012

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

142

Table 53
Final weighted multilevel logistic stepwise regression models, by staff sexual misconduct and
combined individual youth and facility factors, 2012 (continued)

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14.

Results of the Final Multilevel Model Estimation by Incident
Type

One final model was estimated for each type of victimization (youth, staff) and the results are
presented below.26

14.1

Youth-on-Youth Sexual Assault

14.1.1

Individual Youth Characteristics

After adjusting for facility-level factors, the following youth characteristics were predictive of youthon-youth sexual assault (see table 14).

26



Youth vulnerability characteristics: Youth with a prior history of sexual assault
victimization were more than twice as likely to experience youth-on-youth sexual assault
as youth without a history of sexual victimization.



Sexual orientation: Lesbian, gay, or bisexual youth were more than five times as likely
as heterosexual youth to be assaulted by another youth.



Youths’ documented history of most serious offense: Youth with violent sexual
assault as their most serious offense were more than twice as likely to experience youthon-youth sexual assault as youth with other types of most serious offense histories.



Youth reports of gang fights in the facility: Youth reporting gang fights in the facility
were almost twice as likely to be victims of youth-on-youth assault as youth who did not
report gang fights.



Youth reports of well-defined facility structure: Youth reporting high structure were
less likely to experience youth-on-youth sexual assault than youth reporting lower levels
of structure.



Youth reports of poor staff boundaries: Youth-on-youth sexual assault rates were 1.4
times higher for youth reporting that staff provided special treatment than youth who
did not report staff providing special treatment.



Youth reports of being physically hurt and worrying about physical assault:
Youth reporting being physically hurt by another youth and worrying about physical
assault by staff were more than twice as likely to be victims of youth-on-youth sexual
assault than youth without these experiences.

For categorical predictors, only significant levels were included in the model and non-significant levels were excluded.

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144

14.1.2

Facility Factors

After adjusting for individual-level characteristics, one level 2 predictor was predictive of youth-onyouth sexual assault:


Facilities with higher numbers of vulnerable youth: Facilities with larger
proportions of youth with a prior history of sexual assault victimization had an assault
rate more than three times greater than facilities with lower proportions of youth with
sexual assault histories.

14.2

Staff Sexual Misconduct

14.2.1

Individual Youth Characteristics

After adjusting for facility-level factors, the following youth characteristics were predictive of staff
sexual misconduct (see table 15):


Youth gender: Males were almost four times more likely to be victims of staff sexual
misconduct than females.



Youth vulnerability characteristics: Youth with a prior history of sexual assault
victimization were 1.6 times more likely to experience staff sexual misconduct than
youth without sexual victimization history.



Youth reports of gang membership and gang fighting: Youth reporting being a
member of a gang in the facility (1.8 times) and gang fights in the facility (1.4 times)
were more likely to be victims of staff sexual misconduct than youth who did not report
these events.



Youth reports of lack of fairness in the facility and staff with poor boundaries:
Youth reports of an overall lack of fairness in the facility were more than twice as likely
to experience staff sexual misconduct as youth who did not report this. Similar trends
were also noted for youth reports of staff sharing personal information and staff
providing special treatment.



Youth reports of positive perceptions of staff: Youth reporting positive perceptions
of staff had significantly lower rates of staff sexual misconduct than youth who had no
positive perceptions.



Youth reports of being physically hurt and worrying about physical assault:
Youth reporting being physically hurt by another youth (1.6 times), physically assaulted
by staff (1.5 times), physically hurt by staff (1.8 times), and worrying about physical
assault by staff (1.3 times) were more likely to report staff sexual misconduct than youth
without these experiences.

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145

14.2.2

Facility Factors

After adjusting for significant individual-level characteristics, four facility-level factors (level 2) were
predictive of staff sexual misconduct:


Facility compliance with PREA standards: Youth in facilities that test staff for
current drug use were 1.5 times more likely to experience staff sexual misconduct than
facilities that do not. Conversely, youth in facilities that first learned sexual activity was
not allowed between 1 and 7 days of their arrival27 at the facility were less likely to
experience staff sexual misconduct that those in facilities that did not learn within this
time frame.



Facilities with a high proportion of youth filing written complaints against a staff
member: Youth in facilities that have higher proportions of youth filing written
complaints against a staff member were more than three times more likely to experience
staff sexual misconduct than those in facilities with lower numbers of youth filing
complaints.



Facilities with high proportions of youth with no previous detention histories:
Youth in facilities with higher proportions of youth with no previous detention history
were almost three times more likely to experience staff sexual misconduct than youth in
facilities with greater numbers of youth with detention histories.

The coefficient for this variable is highly unstable, due to a small number of youth who reported being in this
particular circumstance (see table 14 for the mean rate and proportional distribution for this variable). For example, the
odds ratio of 0.1 has a lower confidence bound that is close to 0. The authors have retained this variable in the
equation because it is significant, but do not interpret it below.

27

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146

15.

Discussion of Findings and Limitations

This report sought to answer the question “what are the most important correlates of victimization
at any level—facility factors, youth characteristics, or both?” The results indicate that individual
characteristics are more important than facility factors in the prediction of sexual victimization in
juvenile facilities. Youth at greatest risk for both types of assault have a history of prior sexual
assault victimization and are more likely to report a pattern of non-sexual assault victimization while
in the facility. This pattern includes being hurt by another youth and worrying about being hurt by
staff. These youth also report gang fights in the facility and staff providing special treatment to
youth who are victimized.
Youth with higher rates of youth-on-youth sexual victimization are more likely to be lesbian, gay, or
bisexual, are more likely to have a most serious offense history of violent sexual assault, and are
more likely to report lower levels of facility structure. Youth victims of staff sexual misconduct are
disproportionately male. They report more problematic facility environments, including gang
activity, high levels of lack of fairness, and staff sharing personal information with them. These
youth are also more likely to experience physical assault by staff, be physically hurt by staff, and have
negative perceptions of staff.
Characteristics that place youth at greater risk include previous sexual victimization history, lesbian,
gay, or bisexual orientation, a most serious offense of violent sexual assault, and gender. Moreover,
youth who have higher rates of victimization perceive their environment as one that is unsafe, as
demonstrated by reports of being physically hurt by other youth and worrying about assault by
youth and/or staff. It might be that the same traits that place them at greater risk for sexual
victimization also place them at increased risk for other types of victimization. Alternatively, youth
who are sexually victimized could perceive their environments as unsafe because of the sexual
victimization. For example, youth who have been violated sexually while in a facility might view staff
and conditions of that facility less favorably due to the sexual violation. In either scenario, individual
youth characteristics, the behavior of individual staff, how individual youth perceive them, and the
individual victim’s perception of the climate of the facility are important correlates of individuallevel sexual victimization.
Facility factors appear to have a reduced role in the prediction of sexual victimization as evidenced
by the reduced number of significant correlates after accounting for individual-level factors. For
youth-on-youth sexual assault, the only significant facility factor was increased proportions of youth
with a prior history of sexual assault victimization. This is also a significant predictor at the
individual level. This means that individual youth in a facility with a high proportion of youth with a
prior history of sexual assault victimization are at elevated risk for sexual assault by another youth.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

147

Facility factors are more important in incidents of staff sexual misconduct. Facilities that house
greater proportions of youth with a person offense as their most serious offense, greater proportions
of youth with no previous detention history, greater proportions of youth filing written complaints
against a staff member, and facilities that test their staff for current drug use have higher rates of
staff sexual misconduct than facilities that do not have these features. There is also some suggestion
that informing youth that sexual activity is not allowed in the facility soon after their arrival reduces
victimization risk. However, as noted above, the coefficient for this variable is unstable and needs
further research.
Having established that characteristics of youth seem most important in explaining sexual
victimization, the above analysis did find selected facility characteristics to be important. The
importance of these characteristics vary by incident type. For youth-on-youth sexual assault, facility
factors have little role. The only significant factor relies on the composition of youth in the facility
(e.g., high numbers of youth reporting prior sexual assault) rather than a general operating
characteristic of the facility.
Facilities most at risk for sexual assault are distinguished by a combination of operational
characteristics and the composition of youth within the facilities. Operational characteristics such as
those that test staff for current drug use and those with large numbers of youth filing written
complaints against staff are at much higher risk than other facilities without these features. These
might be indicators of facilities experiencing problems. These difficulties increase the likelihood of
inappropriate sexual behavior by staff. Other facility factors contributing to staff sexual misconduct
pertain to the composition of youth in the facility, such as high proportions of violent youth and
those lacking previous detention histories.
Facilities with the lowest risk are those that inform youth relatively soon after arrival that sexual
activity is not allowed. This process could provide a clear message to youth and to staff that there is
no tolerance of sexual misconduct thereby reducing the risk to youth. However, as noted above, this
particular result needs further research.

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148

There are several limitations of the above analyses. Perhaps the most important is that the study
might not have captured the most important facility characteristics, operational procedures, and
facility climate related to the risk of sexual assault. A second limitation is the cross-sectional nature
of the analysis. This makes it difficult to disentangle the causal relationship between victimization
and the correlates. For example, youths’ opinion that there is a lack of fairness is positively related to
staff sexual misconduct. The above analysis cannot disentangle whether youth who have been
victimized view the facility as unfair because they have been victimized or if the lack of fairness leads
to victimization risk.
A final limitation is that the predictors used in the statistical analysis were correlated with each other.
The analysis did test for multicollinearity at various stages, but inherent in any observational analysis
like this, it is difficult to disentangle characteristics that are highly correlated. For example, sexual
orientation was highly correlated with gender. Females were much more likely to report a lesbian or
bisexual orientation. While the above models found sexual orientation to be highly significant,
another data-set might have found gender to be more significant. Future analyses are needed to
further explore how these two characteristics interact when explaining youth-on-youth victimization.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

149

16.

Methodology

16.1

Facility-Level Methodology

16.1.1

Facility Aggregates

The facility-level analysis use responses to specific items on the facility questionnaire (FQ) and youth
survey. Data were aggregated for each facility to create distinct facility-level predictors. To create the
aggregates, the proportion of youth indicating a positive response for an individual item were
summed together and divided by the total number of youth in the facility who provided a response
to the item. Youth with missing data or with a response of “don’t know” or “refusal” on an item
were excluded from aggregate procedure. For example, in the survey youth were asked “is there
gang activity in this facility?” (see predictor “gangs in the facility,” table 21). All youth in a facility
responding positively to this item were given a value of 1 then summed together to create a value for
the numerator. All youth responding “yes” or “no” to the item were also given a value of 1 and
summed together to create the denominator. This way the total number of youth in a facility
reporting gang activity in a facility could be divided by the total number of youth responses. For a
facility with seven total youth responses and three out of the seven reporting gang activity the
calculation would be:

𝑃𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 𝑦𝑜𝑢𝑡ℎ =

# 𝑦𝑜𝑢𝑡ℎ 𝑒𝑛𝑑𝑜𝑟𝑠𝑖𝑛𝑔 𝑓𝑎𝑐𝑖𝑙𝑖𝑡𝑦 𝑐ℎ𝑎𝑟𝑎𝑐𝑡𝑒𝑟𝑖𝑠𝑡𝑖𝑐
=
# 𝑦𝑜𝑢𝑡ℎ 𝑟𝑒𝑠𝑝𝑜𝑛𝑑𝑖𝑛𝑔 𝑡𝑜 𝑠𝑢𝑟𝑣𝑒𝑦 𝑖𝑡𝑒𝑚

1+1+1
3
= = 0.43
1+1+1+1+1+1+1 7

Each facility then has an assigned proportional value for the condition (gangs in the facility) or
youth characteristic (e.g., proportion of youth with previous sexual assault history) between 0 and 1,
creating a continuous predictor of the item. A categorical version of each of these continuous
predictors was created by defining equal quartiles based on 0-25, 26-50, 51-75, and 76-100. This was
done to better understand the distribution of the predictors and the bivariate relationship with
sexual victimization. Using the same example of “gangs in the facility,” facilities in the lowest
quartile (0-25) had no youth through 0.29 (e.g., 0 to 29%) of the population reporting gang activity.
Conversely, facilities in the highest quartile (76-100) had .82 to 100 (82 to 100%) of their youth
reporting gang activity.

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150

Facility staffing proportions were created using the same aggregated method based on the staffing
totals provided by facility administrators in the facility questionnaire (FQ). Using table 6 as an
illustration, the predictor “total proportion of female staff” was calculated for each facility by taking
the total number of all female staff and dividing it by the total of all staff. Likewise, youth-to-staff
ratios were calculated taking the total number of youth in a facility and dividing it by the total
number of staff. Ratios less than 1 represent more staff than youth while ratios greater than 1 mean
there are more youth than staff.

16.1.2

Facility-Level Bivariate Tests of Significance

The rate of sexual victimization for each facility was calculated by taking the total number of youth
reporting each incident type (e.g., youth-on-youth or staff sexual misconduct) and then dividing it by
the total number of youth in the facility (excluding missing, “don’t know,” and “refusal”). The
proportion was then multiplied by 100 to create a percentage rate. Mean assault rates and standard
errors for each type of victimization were calculated for each facility predictor. Bivariate tests of
significance were performed using the SAS 9.3 general linear model (GLM) least square means
procedure. This procedure analyzes data within the framework of general linear models and was
selected because the facility assault rate is a proportional measure (e.g., continuous). Models were
estimated using each type of assault as the continuous dependent variable and one facility predictor
as the independent variable. This method allows for classification of the predictor variables (e.g.,
class statement) so that multiple assault rate comparisons between the discrete groups within each
categorical variable could be performed. Significant differences between discrete groups were
identified comparing t-statistics on the means, using a minimum criteria of p<0.05. For example, in
table 1, the mean youth-on-youth assault rate for training/long-term secure facilities (3.2%) is
significantly different than group homes (0.4%) and residential treatment facilities (1.7%). Predictors
identified as significant in bivariate tests were included in the multivariate models. Non-significant
predictors were excluded from further analyses. Note that significant predictors varied between the
two types of victimization, so that some predictors were included in the youth-on-youth models and
excluded from the staff sexual misconduct models and vice versa.

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151

16.1.3

Facility-Level Multivariate Stepwise Regression Models

Multivariate regression estimation was used to determine what facility-level factors were significant
in predicting sexual victimization. This particular analysis method was chosen because the outcome
is continuous. The stepwise selection procedure was used in SAS 9.3 regression procedure to reduce
the number of predictors in each model. SAS adds predictors one by one to the model, and assesses
the F-statistic to determine if it should be selected (entry criteria was specified at 0.1). After each
predictor is added, the procedure continues to assess all predictors already included in the model and
deletes any predictor that does not produce an F-statistic significant at the p<0.05 or exit level. Only
after this check is made and the necessary deletions are accomplished can another predictor be
added to the model. The stepwise process ends when none of the predictors outside the model has
an F-statistic significant at the 0.1 level for entry and every predictor in the model is significant at
the p<0.05 level.28
All categorical predictors were dummy coded by assigning each discrete level a value of 1 or 0. This
resulted in only significant discrete levels remaining in the model and created the most parsimonious
and best-fitting models. When feasible, the continuous version of all proportional variables was
included in the modeling phase (as opposed to the quartile categorical version) to increase overall
model fit. Goodness of model fit was assessed by the adjusted R square value which calculates the
percentage of variation explained by the independent variables (e.g., facility predictors) in predicting
each type of facility assault. A weighted least-square adjustment was applied to each stepwise
regression model to account for the differences in facility size in the multivariate analyses. This was
calculated by (step 1) taking the square root of the total number of completed interviews for each
facility, (step 2) summing these together across all the responding facilities, then (step 3) dividing 322
(the total number of facilities) by the summed total and then multiplied by the value created in step
1. This adjustment weights each facility for two reasons: (1) weighting by the square root of the
number of completed interviews accounts for the unequal sample sizes within each facility and
reduces the possibility of heteroscedasticity in the regression estimates, and (2) it multiplies each
weight by a constant so that the weights sum to the original sample size of 322.

16.1.4

Facility-Level Conditional Predicted Rates

In each of the regression models, the conditional predicted rate represents the rate of sexual
victimization (e.g., youth-on-youth, staff sexual misconduct) of a facility, with a specific
characteristic conditional on the mean value for all the other predictors in the model. More

28

http://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_reg_sect030.htm

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

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specifically, the conditional predicted rate is defined as the estimator of the expected response of a
facility, conditional on its belonging to a particular group and having the mean values of the rest of
predictors. The conditional predicted rates can be calculated as:

𝑝̂ = exp(𝛼̂ + х1 𝛽̂1 + х̅∗ 𝛽̂ ∗ )

In this equation, х1 is the particular characteristic of interest, х̅∗ is a vector of mean values of the
remaining predictors in the model. 𝛼̂ , 𝛽̂1, and 𝛽̂ ∗ stand for the corresponding estimate intercept and
slopes of the model. Predicted rates can be calculated for both categorical and continuous
predictors.
For example, viewing the categorical predictor multiple living units in table 3, the value of the
multiple living unit predictor х1 , (i.e., 1 vs. 0) is used directly in the calculation. The predicted facility
youth-on-youth sexual assault rate for facilities with multiple living units is around 2.5 percent
(х1 =1) and it is 1 percent (х1 =0) for a facilities with a single living unit, given that the facility is at
the mean of the joint distribution of the other three predictors х̅∗ (e.g., primary facility type, sex of
youth housed, and sex offender treatment program).
When х1 is a continuous predictor, the proportion of youth are divided into two levels (e.g., high vs.
low) based on the weighted median (for example, the proportion of youth in a facility reporting gang
fights, as is shown in table 22). Dividing at the median creates two equally distributed groups of
facilities. The facility youth-on-youth assault rate for those higher than the median is 2.8 percent (х1
= mean value of the high category) and for those lower than the median the rate is 1.8 percent (х1 =
mean value of the low category) given that the facility is at the mean of the joint distribution of the
other two predictors х̅∗ (i.e., sex of youth housed and sex offender treatment program).

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

153

16.2

Individual-Level Methodology

16.2.1

Individual-Level Bivariate Tests of Significance

For the individual-level analyses, sexual assault rates were calculated for each individual-level
predictor and each type of victimization. These were performed using crosstabular analyses in SAS
9.3 using the weighted youth level data. Significance testing was performed using logistic regression
modeling techniques since the outcome variable (e.g., individual-level victimization) is dichotomous.
Models were estimated using each type of assault as the dependent variable and one individual-level
predictor as the independent variable. This method also allows for classification of the predictor
variables (e.g., class statement) so that multiple assault rate comparisons between the discrete groups
within each categorical variable could be performed. All models were computed with weights in SAS
9.3 survey logistic regression procedure using the Jackknife variance estimation method. Wald Fstatistics (p<0.05) were calculated to test the effects of each discrete group within each categorical
variable with each type of victimization.

16.2.2

Individual-Level Stepwise Logistic Regression Models

Multivariate logistic regression estimation was used to determine what individual-level factors were
significant in predicting sexual victimization. This analysis method was chosen because the outcome
is dichotomous. For the individual-level models, all individual-level predictors were included in the
logistic regression models (regardless of significance in the bivariate tests). A manual stepwise
selection procedure was used to reduce the number of predictors in each model. This procedure was
replicated manually because the models were estimated using the weights in the survey logistic
procedure and the stepwise procedure was not available. The manual stepwise procedure applied the
steps below. Figure 5 illustrates this process.
1.

First, bivariate sets of weighted logistic regressions were conducted for each of the two
outcomes (youth-on-youth sexual assault rate and staff sexual misconduct) with each of
the predictors. The Jackknife estimation method was used. Predictors with p-value ≤
0.1 were kept and ordered ascending by the p-value.

2.

The predictors from step 1 were then entered into the weighted logistic regression one
by one based on the order generated in step 1. If the predictor remained significant (i.e.,
p-value≤ 0.05) it was retained in the model.

3.

All significant predictors in step 2 were entered simultaneously into one final weighted
logistic model to ensure all predictors were still significant.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

154

Figure 5.

Stepwise selection process for weighted logistic regression models
Start

Binary weighted
logistic regression

Predictors with
p-value > 0.1

Predictors with
p-value <= 0.1

Drop

Enter one-by-one

Multivariate
weighted logistic
regression

Predictors with
p-value > 0.05

Predictors with pvalue <= 0.05

Keep

16.2.3

Predicted Probabilities for the Individual-Level Analyses

Two approaches are commonly used to calculate predicted probabilities at the individual level:
(1) the predicted probability based on the conditional means (PPCM), similar to that in the facilitylevel analysis; and (2) the predicted probability based on observations approach (PPO).29 For the
individual-level models, both PPCM and PPO were calculated to demonstrate the differences
between the two methods. The PPCM approach represents the probability that a youth with a
particular characteristic has experienced sexual victimization (youth-on-youth and staff sexual
misconduct) conditional on the youth having the mean value for all the other predictors in the
model. The mathematical equation is:

Research Triangle Institute (2008). SUDAAN Language Manual Release 10.0. Research Triangle Park, NC, Section
4.8.3, pp. 209-211.

29

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

155

exp(𝛼̂ + х1 𝛽̂1 + х̅∗ 𝛽̂ ∗ ))
𝑃𝑃𝐶𝑀 =
1 + exp(𝛼̂ + х1 𝛽̂1 + х̅∗ 𝛽̂ ∗ ))

where х1 is the particular characteristic of interest, х̅∗ is a vector of mean values of the rest
predictors. 𝛼̂ , 𝛽̂1, and 𝛽̂ ∗ stand for the corresponding estimate intercept and slopes of the model.
On the other hand, the PPO approach is defined as the average predicted response, if all the
observations have been in a given group or are at a specified value for a continuous variable.

𝑃𝑃𝑂 =

𝐻

1
𝑤++++

𝐼

𝐽

𝐼ℎ 𝐽ℎ𝑖 𝐾ℎ𝑖𝑗

∑∑∑∑
ℎ=1 𝑖=1 𝑗=1 𝑘=1

exp(𝛼̂ + х∗ℎ𝑖𝑗𝑘 𝛽̂ )
1 + exp(𝛼̂ + х∗ℎ𝑖𝑗𝑘 𝛽̂ )

𝐾

ℎ𝑖𝑗
∗
ℎ
ℎ𝑖
where 𝑤++++ is equal to ∑𝐻
ℎ=1 ∑𝑖=1 ∑𝑗=1 ∑𝑘=1 𝑤ℎ𝑖𝑗𝑘 . хℎ𝑖𝑗𝑘 represents the vector of covariates for a

given observation in the dataset. For a categorical predictor, the vector has a “1” corresponding to
the group of interest and a “0” for all other groups of that variable. For a continuous variable, it is
the user-specified value of interest for that variable such as the median. 𝛼̂ and 𝛽̂ stand for the
corresponding estimate intercept and slopes of the model. In this approach, each observation’s
predicted probabilities is generated first and then a weighted mean is calculated across all
observations.
PPCM is not the most suitable approach in nonlinear models (i.e., logistic regression).30 In certain
cases, PPCM will result in predictions that are not logical (e.g., means that are significantly below or
above the observed means). For example, when using the PPCM for the model with gang fights as a
predictor (see table 36) the predicted probability of youth-on-youth sexual assault for youth who
report gang fights (e.g., gang fights=1) is 1%, and for those who report no gang fights (e.g., gang
fights=0), it is 0.6%. These predictions are lower than the overall average assault rate (e.g., 2.5%)
even though gang fights is significant in the model. On the other hand, when the PPO approach is
used, each youth’s individual predicted probability is generated first, and then a weighted average is
calculated across the individual predicted probabilities for those youth in the group of interest. The
predicted probabilities are then distributed across the mean assault rate (e.g., 2.5%) with the assault
rate at 3.0% for youth reporting gang fights and 1.9% for youth not reporting gang fights. This
pattern is evident for other predictors across both the youth-on-youth and staff sexual misconduct
models. The disadvantage of the PPO approach is that it does not hold the other variables in the

Muller, C. J. and MacLehose, R. F. (2014). Estimating predicted probabilities from logistic regression: different
methods correspond to different target populations. International Journal of Epidemiology, 43(3), 962-970.

30

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

156

model constant the same way as the PPCM approach does. Nonetheless, it does provide estimates
one would expect from the interaction of all the variables that are found to be important in
predicting victimization.

16.3

Multilevel Methodology

16.3.1

Block-by-Block Predictor Section

The second report analyses used two different sets of modeling techniques. In the block-by-block
facility predictor selection phase, multivariate logistic regression estimation was used to identify
significant facility-level factors in predicting each type of sexual victimization. All models were
computed with the final survey weights in SAS 9.3 survey logistic regression procedure using the
Jackknife variance estimation method. A manual stepwise selection procedure was used to reduce
the number of predictors in each model (see Section 4.2.1 for a more extensive explanation of the
stepwise selection process).

16.3.2

One by One, Stepwise, and Final Model Estimation

In order to examine both facility factors and individual youth characteristics together in a single
statistical model, a series of multilevel logistic regression models were estimated. Multilevel modeling
can simultaneously test for the significance of individual characteristics (level 1) and facility factors
(level 2) in the prediction of sexual victimization.31 If the statistical model does not explicitly account
for the different levels, it is possible that the conclusions may not be correct. Multilevel linear
modeling allows intercepts (means) and slopes to vary between higher level units so that
“independence of errors is not required.”32 This analytic technique is of particular relevance since
youth in facilities are more likely to be similar than youth in different facilities. For instance, youth in
training/long-term secure facilities are likely to have similar criminal offenses and are likely to differ
from youth in group homes. Likewise, staff in the same facility is likely to behave in certain ways
that may influence the attitudes and behaviors of youth in comparable ways. Therefore, attitudes of
youth and behavior of staff are prone to be similar within facilities but different across facilities.

31

Tabachnick, B.G. & Fidell, L.S (2007). Using multivariate statistics (5th ed.). Boston, MA: Pearson Education, Inc.

Tabachnick, B.G. & Fidell, L.S (2007). Using multivariate statistics (5th ed.). Boston, MA: Pearson Education, Inc. pg.
782.

32

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

157

Multilevel analysis takes this into account so that interpretations of grouped data are more likely to
be accurate.
Multilevel logistic regression was selected because the sexual victimization outcome is binary.33 The
full model with a binary outcome is expressed as:

Level 1: ij  logit[ ij ( x)]  ln[

 ij ( x)
]   0 j  1 j X 1ij   2 j X 2ij  ...Qj X Qij
1   ij ( x)

Sq

Level 2:  qj   q 0    qsWsj  uqj
s 1

where 𝜂𝑖𝑗 represents the logit of the outcome variable (i.e., “youth-on-youth sexual assault” or “staff
sexual misconduct”), 𝑋𝑄𝑖𝑗 stands for the Qth individual-level predictor, and 𝑊𝑠𝑗 stands for the Wth
facility-level predictor. 𝛾𝑞0 and 𝛾𝑞𝑠 represent the fixed effects of the intercept and slopes. 𝑢𝑞𝑗
indicates the random effects which can be either fixed or random. To acquire better accuracy, an
adaptive quadrature estimation method (with 5 quadrature points) (AQ) was used as the estimation
method instead of the penalized quasi-likelihood (PQL) method or the Laplace method.34 The PQL
method is an approximation to maximum likelihood estimation to optimize a quasi-likelihood with a
penalty term on the random effects while the AQ method is a numeric method for evaluating multidimensional integrals. Many studies have shown that AQ preforms considerably better than PQL
and provides more accurate fixed and random effect coefficients,35 therefore the AQ method was
used in this analysis.
Missing cases were list-wise deleted and all multilevel analyses were performed in the Hierarchical
Linear Modeling (HLM v. 7) software package. The HLM program was chosen because it offers the
option to apply weights in the multilevel model. The weighting procedure uses a method of
computation devised by Pfeffermann and colleagues36 for hierarchical data and is based on the
information of each case in the framework of maximum likelihood.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.).
Newbury Park, CA: Sage.

33

O’Connell, A. A., Reed, S., Ren, W., & Li, J. (2010). Estimation methods and software comparison for hierarchical
generalized linear models. Presented at the 2010 American Educational Research Association Annual Meeting in
Denver, CO.

34

Raudenbush, S. W., Yang, M.l., & Yosef, M. (2000). Maximum likelihood for hierarchical models via high order,
multivariate LaPlace approximation. Journal of Computational and Graphical Statistics, 9(1), 141-157.

35

Pfefferman, D., Skinner, C.J., Homes, D.J., Goldstein, H., & Rasbash, J. (1998). Weighting for unequal selection
models in multilevel models. Journal of the Royal Statistical Society, Series B, 60, 1, 23-40.

36

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

158

In these analyses, two sets of weights (level 1 and level 2) were constructed and applied in all
multilevel model estimations.
The level 2 weights were computed as the inverse of the probability that facility j was selected (𝑃𝑗 )
1

from the sampling frame 𝑙2𝑤𝑡𝑗 = 𝑃 . The level 1 weights were computed as the inverse of the
𝑗

1

1/𝑃

probability that youth i was selected given that facility j was selected 𝑙1𝑤𝑡𝑖|𝑗 = 𝑃 = 1/𝑃 𝑖 , where
𝑖|𝑗

𝑗

𝑃𝑖 is the probability that youth i was selected. The two sets of weights are automatically scaled in the
HLM v.7 software.37
For final models (youth-on-youth sexual assault and staff sexual misconduct), the fixed and random
effects were estimated. Both level 1 and level 2 predictors were assumed to be fixed, and the level 1
intercepts were assumed to vary randomly across facilities. The fixed effects assess each predictor’s
average relationship with the outcome. The significant fixed effect results were presented in odds
ratios and corresponding confidence intervals. The random effects assess the variation of each
facility’s mean predicted assault rates across facilities, and the results were presented showing a total
value of variance with a standard error term. An intra-class correlation (ICC) was also calculated to
demonstrate how much of the variation of the outcome (i.e., youth-on-youth assault rate and staff
sexual misconduct assault rate) can be attributed to variability across facilities.38
For youth-on-youth sexual assault, the odds ratios of the significant fixed effects were presented in
table 52. For example, lesbian, gay, or bisexual youth were about 5.5 times more likely to experience
youth-on-youth sexual assault than heterosexual youth after controlling for other level 1 and level 2
predictors. The intercept random effect is 0.12 with a standard error term of 0.12. This indicates that
a small non-significant amount of variance remains in the intercept of the youth-on-youth model
(see table 52), and it is reasonable to assume that the model is fully explained by the included
predictors.39
The ICC suggests that 3.5% of the youth-on-youth assault rate is a result of variability across
facilities. The ICC for the model was calculated as the level 2 variance divided by the sum of the
level 2 variance and the level 1 variance or (0.12)/(0.12+3.29)=3.5%. In this equation, the

Chantala, K & Suchindran, C. (2006) Adjusting for Unequal Selection Probability in Multilevel Models: A Comparison
of Software Packages. Proceedings of the American Statistical Association, Seattle, WA: American Statistical
Association.

37

The ICC is not technically applicable for binary data. Nonetheless, it provides a sense of the mount of variance in the
data that is attributable to between facilities.

38

Significance test of the random effects was calculated by an approximate chi-square test of the deviation of group
means from the grand mean as discussed in Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models:
Applications and data analysis methods (2nd ed.). Newbury Park, CA: Sage.

39

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

159

dichotomous outcome can be considered as a dichotomization of an unknown latent continuous
variable with a level 1 residual following the logistic distribution of mean equals to 0, and variance
equals to

𝜋2
3

(i.e., 3.29) respectively.40

Similarly, the fixed effects in table 53 show that male youth are 3.8 times more likely to experience
staff sexual misconduct than female youth after controlling for other level 1 and level 2 predictors.
For the random effects, the variance is 0.02 with a standard error term of 0.04 demonstrating little
variance left in the staff sexual misconduct model (see table 53) and that the model is fully explained
by the current predictors. The ICC was calculated as (0.02)/(0.02+3.29)=0.6%. Therefore, 0.6% of
the staff sexual misconduct assault rate can be attributed to variability across facilities.

40

Evans, M., Hastings, N., & Peacock, B. (2000). Statistical distributions (3rd ed.). New York: Wiley.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

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Appendices

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A1

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A2

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A3

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A4

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A5

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A6

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A7

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A8

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A9

Appendix A
Facility Questionnaire

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

A10

Appendix B
Facility-Level Construct Measures
Construct name a
Written up for fighting

Item number
B15
B23
B24

Positive perceptions of staff

Lack of fairness

B1a
B1b
B1c
B1d
B1e
B1f
B1g
B1h
B2a
B2b
B2c
B2d

Physical assault by youth

B2e
B2f
B2g
B9
B11
B14

Physical assault by staff

B17
B19
B22

Item text
Have you ever been written up or charged with physically
fighting with youth here?
Have you ever been written up or charged with physically
fighting with a facility staff member?
Have you ever been written up or charged with threatening a
facility staff member?
Are facility staff good role models?
Are the facility staff friendly?
Do the staff seem to genuinely care about you?
Are the staff helpful?
Are the staff disrespectful (reversed)?
Are the staff hard to get along with (reversed)?
Are the staff mean (reversed)?
Are the staff fun to be with?
Youth here are punished even when they don’t do anything
wrong.
Facility staff use force when they don’t really need to.
Problems between facility staff and youth here can be
worked out (reversed).
Something bad might happen to me if I file a complaint
against a staff member.
I usually deserve any punishment that I receive (reversed).
Punishments given are fair (reversed).
The staff treat youth fairly (reversed).
Have you ever been hit, punched, or assaulted by another
youth here?
Has another youth here physically hurt you on purpose?
Did you see a doctor, nurse, or other health care person for
any of these injuries?
Have you ever been hit, punched, or assaulted by facility
staff here?
Has a staff member physically hurt you on purpose?
Did you see a doctor, nurse, or other health care person for
any of these injuries?

a Constructs

were developed by summing all positive responses by each individual youth in a facility, and then computing an average
score for all youth within a facility.

6/5/2015

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

B1

Appendix C
Individual-Level Construct Measures
Construct name a
Written up for fighting

Item number
B15
B23
B24

Well-defined structure

B2i
B26
B27
B28

Positive perceptions of staff

B1a
B1b
B1c
B1d
B1e
B1f
B1g
B1h

Lack of fairness

B2a
B2b
B2c
B2d
B2e
B2f
B2g

Item text
Have you ever been written up or charged with physically
fighting with youth here?
Have you ever been written up or charged with physically
fighting with a facility staff member?
Have you ever been written up or charged with threatening a
facility staff member?
Never=never written up for fighting, 1 time= 1 positive
response, 2 times= 2 positive responses, 3 times=3 positive
responses
There are enough staff to monitor what is going on in this
facility.
Were you told how to report if a staff member or youth is
breaking the rules?
Were you told that you would not get into trouble if you
report that a staff member or youth is breaking the rules?
After you got to the facility (this time), when did you first
learn that sexual activity is not allowed? Was it.. (all options
vs. never)
No=no response to all items, Low=1 positive response,
Medium=2 positive responses, Medium High=3 positive
responses, High=all positive responses
Are facility staff good role models?
Are the facility staff friendly?
Do the staff seem to genuinely care about you?
Are the staff helpful?
Are the staff disrespectful (reversed)?
Are the staff hard to get along with (reversed)?
Are the staff mean (reversed)?
Are the staff fun to be with?
No=no response to all items, Low=1-4 positive responses,
Medium=5-7 positive responses, High=all positive responses
Youth here are punished even when they don’t do anything
wrong.
Facility staff use force when they don’t really need to.
Problems between facility staff and youth here can be
worked out (reversed).
Something bad might happen to me if I file a complaint
against a staff member.
I usually deserve any punishment that I receive (reversed).
Punishments given are fair (reversed).
The staff treat youth fairly (reversed).
No=no response to all items, Low=1-3 positive responses,
Medium=4 positive responses, High=5-7 positive responses

a Constructs

were developed by summing all positive responses by each individual youth in a facility and creating categories based on
the number of responses.

Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012

C1

 

 

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