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 ofJustice 

Statistics or the U.S. Department of Justice. The authors accept responsibility forerrors.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 ii

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 iii

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 Structure of Juvenile Facilities............................................ 7

4.2 Staff Characteristics.............................................................. 15

4.3 Compliance With PREA Standards................................... 21

4.4 Facility Reports of Youths’ History ................................... 40

4.5 Youth Reports of Involvement With Gangs and 

Fighting .................................................................................. 50

4.6 Youth Reports of Vulnerability .......................................... 57

4.7 Youth Reports of Facility Order and Disorder................ 65

4.8 Youth Reports of Facility Safety and Fairness................. 71

5 Facility Profiles of Sexual Victimization............................................ 78

5.1 Facility Characteristics Associated With Both 

Types of Sexual Assault (Youth-on-Youth and 

Staff Sexual Misconduct)..................................................... 78

5.2 Facility Characteristics Exclusively Associated 

With a Single Type of Sexual Assault ................................ 78

5.3 Summary of Facility Profiles of Sexual 

Victimization ......................................................................... 82

6 Individual-Level Findings.................................................................... 83

6.1 Youth Demographic Characteristics.................................. 83

6.2 Youth Risk Characteristics.................................................. 85

6.3 Most Serious Offense, Gang Involvement, and 

Fighting in the Facility ......................................................... 87

6.4 Youth Reports of Facility Order and Disorder................ 89

6.5 Youth Reports of Safety and Fairness............................... 90

6.6 Multivariate Findings for Youth-on-Youth 

Sexual Assault and Staff Sexual Misconduct .................... 91
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 iv

Contents (continued) 

Chapter Page

7 Individual Profiles of Sexual Victimization....................................... 97

7.1 Youth Characteristics Associated With Both 

Types of Sexual Assault (Youth-on-Youth and 

Staff Sexual Misconduct)..................................................... 97

7.2 Youth Characteristics Exclusively Associated 

With Youth-on-Youth Sexual Assault............................... 97

7.3 Youth Characteristics Exclusively Associated 

With Staff Sexual Misconduct............................................. 98

7.4 Summary of Individual Profiles of Sexual 

Victimization ......................................................................... 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 Individual-Level Predictors................................................. 105

13.2 Facility-Level Predictors...................................................... 107

14 Results of the Final Multilevel Model Estimation by 

Incident Type......................................................................................... 144

14.1 Youth-on-Youth Sexual Assault......................................... 144

14.2 Staff Sexual Misconduct ...................................................... 145

15 Discussion of Findings and Limitations............................................ 147
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 v

Contents (continued) 

Chapter Page

16 Methodology.......................................................................................... 150

16.1 Facility-Level Methodology................................................. 150

16.2 Individual-Level Methodology............................................ 154

16.3 Multilevel Methodology....................................................... 157

Appendix

A Facility Questionnaire ........................................................................................ A1

B Facility-Level Construct Measures .................................................................. B1

C Individual-Level Construct Measures ............................................................. C1

Table

1 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

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 ........................... 13

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 ...................................................................................................................... 14

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

characteristics, 2012............................................................................................ 15
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 vi

Contents (continued) 

Table Page

7 Multivariate stepwise regression models of facility sexual 

victimization, by youth-on-youth incidence and staff 

characteristics, 2012............................................................................................ 18

8 Multivariate stepwise regression models of facility sexual 

victimization, by staff sexual misconduct and staff characteristics, 

2012 ...................................................................................................................... 20

9 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

16 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 vii

Contents (continued) 

Table Page

17 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

20 Multivariate stepwise regression models of facility sexual 

victimization, by staff sexual misconduct and youths’ history, 

2012 ...................................................................................................................... 49

21 Facility-level victimization rate, by type of incident and youth 

reports of involvement with gangs and fighting, 2012.................................. 51

22 Multivariate stepwise regression models of facility sexual 

victimization, by youth-on-youth incidence and youth reports of 

involvement with gangs and fighting, 2012 .................................................... 54

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 ............................ 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

26 Multivariate stepwise regression models of facility sexual 

victimization, by staff sexual misconduct and youth reports of 

youth vulnerability, 2012 ................................................................................... 64

27 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 viii

Contents (continued) 

Table Page

28 Multivariate stepwise regression models of facility sexual 

victimization, by youth-on-youth incidence and youth reports of 

facility order and disorder, 2012....................................................................... 68

29 Multivariate stepwise regression models of facility sexual 

victimization, by staff sexual misconduct and youth reports of 

facility order and disorder, 2012....................................................................... 70

30 Facility-level victimization rate, by type of incident and youth 

reports of facility safety and fairness, 2012..................................................... 72

31 Multivariate stepwise regression models of facility sexual 

victimization, by youth-on-youth incidence and by youth reports 

of safety and fairness, 2012 ............................................................................... 74

32 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

35 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 ix

Contents (continued) 

Table Page

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 ................................ 109

41 Multivariate logistic regression models of sexual victimization, by 

incident type and facility predictor selection of staff 

characteristics, 2012............................................................................................ 112

42 Multivariate logistic regression models of sexual victimization, by 

incident type and facility predictor selection of compliance with 

PREA standards, 2012....................................................................................... 113

43 Multivariate logistic regression models of sexual victimization, by 

incident type and facility predictor selection of youths’ history, 

2012 ...................................................................................................................... 116

44 Multivariate logistic regression models of sexual victimization, by 

incident type and facility predictor selection of youth offense 

history, 2012 ........................................................................................................ 117

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 .................................................... 119

46 Multivariate logistic regression models of sexual victimization, by 

incident type and facility predictor selection of youth reports of 

vulnerability, 2012............................................................................................... 120

47 Multivariate logistic regression models of sexual victimization, by 

incident type and facility predictor selection of youth reports of 

facility order and disorder, 2012....................................................................... 121

48 Multivariate logistic regression models of sexual victimization, by 

incident type and facility predictor selection of youth reports of 

facility safety and fairness, 2012 ....................................................................... 122

49 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 x

Contents (continued) 

Table Page

50 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

53 Final weighted multilevel logistic stepwise regression models, by 

staff sexual misconduct and combined individual youth and 

facility factors, 2012............................................................................................ 142

Figure

1 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
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 1

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 2

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 3

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 4

 Facility Characteristics Exclusively Associated With Staff Sexual Misconduct 

 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.

 

 

1 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 5

 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 6

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 offense3and 

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 7

 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 8

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 9

 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 10

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 11

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 12

 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 13

 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 14

 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 15

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 16

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 17

 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 18

 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 19

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 20

 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 21

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 typea, 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 22

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 23

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 24

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

 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).

 

5 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 25

 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 26

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

Standard 

Error 

Standard 

Error 

All facilities 100.0 % 2.1 % 0.3 5.2 % 0.4

Types of screening

Testing of staff for current drug use

Yes 63.2 % 2.4 % 0.3 6.4 % ** 0.5

No * 36.8 1.7 0.4 3.1 0.5

Psychological evaluation

Yes 17.1 % 1.4 % 0.4 6.3 % 1.1

No * 82.9 2.3 0.3 5.0 0.4

Monitoring 

Video surveillance

Yes 76.7 % 2.5 % ** 0.3 5.8 % ** 0.5

No * 23.3 1.0 0.3 3.2 0.8

Location of monitoring

All sleeping areas

Yes 95.1 % 2.4 % 0.3 5.8 % 0.5

No * 4.9 2.8 1.3 5.2 2.1

 Bathrooms and shower areas

Yes 87.0 2.5 % 0.3 5.8 % 0.5

No * 13.0 2.2 0.7 5.9 1.4

Classrooms and library

Yes 70.9 2.5 % 0.3 5.9 % 0.5

No * 29.2 2.3 0.6 5.5 0.9

Other indoor areas

Yes 96.4 2.5 % 0.3 5.8 % 0.5

No * 3.6 1.5 1.0 5.5 2.7

Outdoor recreation areas

Yes 91.9 2.6 % 0.3 5.8 % 0.5

No * 8.1 1.1 0.5 5.7 1.5

Staff to youth ratios compliance - all facilities a

1:8 Compliance day

Yes 79.2 % 2.1 % 0.3 5.3 % 0.5

No * 20.8 2.2 0.5 5.1 0.8

1:8 Compliance evening

Yes 82.6 % 2.2 % 0.3 5.3 % 0.5

No * 17.5 1.9 0.6 4.7 0.8

Continued on next page

Youth-on-youth 

victimization rate 

Staff sexual 

misconduct 

victimization rate

Mean 

Percent 

Mean 

Percent 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 27

Table 13

Facility-level victimization rate, by type of incident and facility reports of compliance with 

PREA standards, 2012 (continued)

 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.

4.3.2 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 28

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 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)
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 32

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 33

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 34

– 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 35

 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 36

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 37

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 38

 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 39

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 40

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.

 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%).

4.4 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 41

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 42

 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 43

 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 44

Table 18

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

 Facility offense profile

Standard 

Error 

Standard 

Error 

All facilities 100 % 2.1 % 0.3 5.2 % 0.4

Most serious offense responsible for current placement a

 Murder (mean = 1%)

High b

2 5 % 3.4 % ** 0.6 7.4 % ** 0.8

Low c * 7 5 1.7 0.3 4.5 0.5

Violent sex assault (mean = 10%)

High b

2 9 % 3.3 % ** 0.5 6.8 % ** 0.8

Low c * 7 1 1.6 0.3 4.6 0.5

Non-violent sex offense (mean = 2%)

High b

1 8 % 2.8 % 0.6 5.2 % 0.8

Low c * 8 2 2.0 0.3 5.2 0.5

Person offense (mean = 32%)

High b

4 9 % 2.2 % 0.4 6.2 % ** 0.6

Low c * 5 1 2.1 0.3 4.3 0.5

Property offense (mean = 29%)

High b

4 9 % 1.7 % 0.3 5.1 % 0.6

Low c * 5 1 2.5 0.4 5.4 0.6

Drug offense (mean = 6%)

High b

3 5 % 1.6 % 0.4 4.4 % 0.6

Low c * 6 5 2.4 0.3 5.7 0.5

Other (mean = 17%) d

High b

3 8 % 1.7 % 0.4 4.5 % 0.6

Low c * 6 2 2.4 0.3 5.6 0.5

Mean 

Percent 

Mean 

Percent 

Youth-on-youth 

victimization rate 

Staff sexual 

misconduct 

victimization rate

**Difference with comparison group is significant at the 95%- confidence level.

Note: Based on 322 unweighted juvenile facilities that returned a Facility Questionnaire. Four facilities were excluded from 

analysis. 

d

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

c

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

b

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

a

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

*Comparison group.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 45

 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 46

 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 47

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 48

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).

 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.

 

8 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 49

 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 50

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 51

Table 21

Facility-level victimization rate, by type of incident and youth reports of involvement with 

gangs and fighting, 2012

Youth reports of involvement with 

gangs and fighting

Standard 

Error 

Standard 

Error 

All facilities 100 % 2.1 % 0.3 5.2 % 0.4

Discipline for physical assault or threats

Written up for fighting a

0 up to 0.17 * 2 6 % 0.9 % 0.3 1.4 % 0.5

0.17 up to 0.48 2 4 2.6 ** 0.5 4.9 ** 0.8

0.48 up to 0.77 2 5 2.1 0.5 5.6 ** 0.7

0.77 up to 1 2 5 2.9 ** 0.6 9.0 ** 0.9

Gang activity 

Gangs in facility

0 up to 0.29 * 2 5 % 1.5 % 0.5 1.6 % 0.5

0.29 up to 0.58 2 5 1.6 0.4 3.4 0.6

0.58 up to 0.82 2 4 2.4 0.5 6.2 ** 0.9

0.82 up to 1 2 5 3.0 ** 0.6 9.8 ** 0.9

Gang fights in facility 

0 up to 0.03 * 2 5 % 1.2 % 0.4 1.4 % 0.6

0.03 up to 0.25 2 6 1.9 0.4 3.3 0.6

0.25 up to 0.55 2 5 2.6 ** 0.6 5.7 ** 0.8

0.55 up to 1 2 5 2.8 ** 0.5 10.6 ** 0.9

Gang member in facility b

0 * 2 8 % 1.7 % 0.5 1.5 % 0.6

>0 up to 0.13 2 1 2.0 0.4 5.1 ** 0.7

0.13 up to 0.25 2 5 2.4 0.5 5.7 ** 0.8

0.25 up to 1 2 6 2.5 0.5 8.8 ** 0.9

Gang pressure

0 * 6 5 % 2.0 % 0.3 3.2 % 0.4

0.01 -0.25 3 5 2.4 0.3 8.9 ** 0.7

Safer in gang 

0 * 3 2 % 1.8 % 0.5 2.2 % 0.6

>0 up to 0.09 1 8 1.9 0.4 5.9 ** 1.0

0.09 up to 0.17 2 4 2.3 0.6 5.1 ** 0.7

0.17 up to 1 2 6 2.5 0.5 8.6 ** 0.9

Youth-on-youth 

victimization rate 

Staff sexual 

misconduct 

victimization rate

Mean 

Percent 

Mean 

Percent 

b

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

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. 

**Difference with comparison group is significant at the 95%- confidence level.

*Comparison group.

Note: Based on 322 unweighted juvenile facilities that returned a Facility Questionnaire. Four facilities were excluded from 

analysis. 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 52

 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 53

 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 54

 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 55

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 56

 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 57

Fighting and gang factors remained significantly predictive of staff sexual misconduct after adjusting 

for facility structural characteristics (see table 23).

 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%).

4.6 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 58

Table 24

Continued on next page
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 59

Table 24

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

(continued)

 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.

Youth reports of vulnerability %

Standard 

Error 

Standard 

Error 

Previous detention history

No history

 0 up to 0.12 * 2 5 1.5 % 0.4 3.5 % 0.7

0.12 up to 0.19 2 4 1.9 0.4 4.8 0.8

0.19 up to 0.31 2 6 1.9 0.4 6.7 ** 0.8

0.31 to 1 2 5 3.1 ** 0.7 5.9 ** 0.9

Length of time in the facility 

Less than 6 months

0 up to 0.47 2 5 3.4 % ** 0.7 6.5 % ** 0.8

0.47 up to 0.61 2 4 2.7 ** 0.6 6.7 ** 0.8

0.61 up to 0.82 2 6 1.6 0.4 3.9 0.7

0.82 to 1 * 2 5 0.7 0.3 3.9 0.8

Mean 

Percent 

Youth-on-youth 

victimization rate 

Staff sexual misconduct 

victimization rate

Mean 

Percent 

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 60

 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 61

 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 62

 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 63

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 64

 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 65

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).

 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%).

4.7 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 66

Table 27

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

disorder, 2012

Youth reports of facility order and disorder

All facilities 100 % 2.1 % 0.3 % 5.2 % 0.4 %

Proportion of youth filed a written written complaint 

against staff member

0 up to 0.11* 2 5 % 0.6 % 0.3 % 1.1 % 0.3 %

0.11 up to 0.31 2 4 1.7 0.5 4.1 ** 0.6

0.31 up to 0.50 2 5 2.6 ** 0.5 7.6 ** 0.8

0.50 up to 1 2 6 3.5 ** 0.7 7.9 ** 1.1

Proportion of youth who report enough staff to monitor 

what is going on

0 up to 0.60* 2 4 % 3.7 % 0.8 % 7.6 % 1.0 %

0.60 up to 0.74 2 6 2.4 0.4 6.9 0.8

0.74 up to 0.86 2 5 1.5 ** 0.4 4.7 ** 0.7

0.86 up to 1 2 5 0.9 ** 0.3 1.6 ** 0.5

Not easy to break rules

0 up to 0.43 2 4 % 3.2 % ** 0.7 % 5.4 % ** 0.9 %

0.43 up to 0.53 2 6 2.2 0.5 6.2 ** 0.8

0.53 up to 0.67 2 9 1.6 0.3 5.9 ** 0.8

0.67 - 1 * 2 1 1.6 0.5 2.9 0.6

Staff boundaries 

Staff share personal information

0 up to 0.22 * 2 5 % 1.2 % 0.4 % 1.6 % 0.4 %

0.22 up to 0.33 1 8 2.8 ** 0.6 5.1 ** 0.6

0.33 up to 0.45 3 0 2.4 0.5 7.6 ** 0.8

0.45 up to 1 2 7 2.2 0.6 6.0 ** 1.0

Staff provide special treatment

0 up to 0.17 * 2 9 % 0.9 % 0.3 % 2.4 % 0.6 %

0.17 up to 0.25 1 6 2.4 0.5 4.2 0.6

0.25 up to 0.37 3 0 2.2 0.4 6.5 ** 0.8

0.37 up to 1 2 5 3.2 ** 0.7 7.6 ** 0.9

*Comparison group.

**Difference with comparison group is significant at the 95%- confidence level.

Youth-on-youth 

victimization rate 

Staff sexual 

misconduct 

victimization rate

Mean 

Percent 

Standard 

Error 

Mean 

Percent 

Standard 

Error 

Note: Based on 322 unweighted juvenile facilities that returned a Facility Questionnaire. Four facilities were excluded from analysis. 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 67

 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).
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 68

 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
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 69

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 70

 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
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 71

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.

 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%).

4.8 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).
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 72

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 73

 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 74

 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 75

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 76

 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 77

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 78

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 79

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 80

Figure 1. Facility characteristics associated with youth-on-youth sexual assault 

No history of incarceration

Female residents

- prior sexual assault

Serious offenders 

Youth-on-youth

Sexual

Assault

Risk factors associated with sexual abuse/victimization

Multiple living units

Facility order

- violent sexual assault offense 

- sexual offender treatment program

Italicized font indicates factors associated with 

both youth-on-youth and staff sexual misconduct.

- written complaints about staff

- not enough staff

+

Informed sexual activity not allowed 

>7 days

Might not report (embarrassed/ 

ashamed)

+

+

+

+

+

+

Gang fights

Worry about phy. asslt. by youth +

+

+

+

-LGB orientation

+

+

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 81

Figure 2. Facility characteristics associated with staff sexual misconduct 

 

Facility Type

- large, long-term/detention

- not exclusively minors

No history of incarceration

Staff relations

- positive perceptions

Staff turnover (loss)

Facility order

Gang fights

Worry about phy asslt. by youth

Staff 

Sexual 

Misconduct

Male residents

+

Staff screening for drug use

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

Gang membership/pressure

Person offense 

- sanctions for fighting

- staff grooming

- physical assault by staff

Never informed, sexual activity not 

allowed

Might not report (afraid of staff) +

- written complaints about staff

- not enough staff +

+

- know how to report rule breaking

- would report sexual activity (faceto-face staff)

PREA compliance

+

+

+

+

+

+

+

+

+

+

+

+

+

-

+

-

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 82

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.

 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 83

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).
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 84

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 85

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 86

 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 87

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 88

 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%).

 

 

10 Includes status offenses, probation/parole violations, or public order offenses
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 89

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%).

 

11 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). 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 90

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 91

 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.

6.6 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

 

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. 
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
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)
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 95

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 96

 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 97

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 98

Figure 3. Youth characteristics associated with youth-on-youth sexual assault 

Youth-on-youth

Sexual

Assault

- hurt by youth

+

+

Pattern of victimization 

+

- worry about phy asslt by staff

+

-

- prior sexual assault

+

+

Gang fights

+

LGB orientation

Well defined structure

Staff provide special treatment

Violent sexual assault offense 

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 99

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 

Male youth

-youth race

Staff 

Sexual 

Misconduct

+

Youth demographic characteristics

Gang Fights

+

-prior sexual assault

- hurt by youth

+

+

Pattern of Victimization

- worry about phy.asslt by staff +

Positive perceptions of staff -

Lack of fairness +

- staff share personal information

- phy asslt/phy hurt by staff

+

+

Staff behavior

Staff provide special treatment +

Prior incarceration of less than 6 

months

Gang involvement +

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 100

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.

 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 101

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 102

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 103

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.

 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 104

11. Research Questions 

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

 What are the most important predictors of victimization at any level–facility factors, 

youth characteristics, or both?

 

12. 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 105

– 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
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 106

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.

 

14 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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 107

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.

 

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

footnotes throughout this report 

16 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

17 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. 

18 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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 108

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 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
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 110

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 111

 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 112

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

 

19 “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. 

20 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. 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 113

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 114

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 115

 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 116

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 117

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);

 

21 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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 118

– 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).

13.2.1.5 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 119

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 120

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 121

– 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).

13.2.1.7 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 122

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).
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 123

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).

 

23 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. 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 124

Table 49

Weighted multilevel logistic regression models, by youth-on-youth sexual victimization and 

level 2 one-by-one predictor selection, 2012
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 125

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 126

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.
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
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)
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 130

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;
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 131

 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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 132

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.

 

24 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. 

25 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. 
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
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)
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 135

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 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

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 139

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 140

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 141

Table 52

Final weighted multilevel logistic stepwise regression models, by youth-on-youth sexual 

victimization 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
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 143

Table 53

Final weighted multilevel logistic stepwise regression models, by staff sexual misconduct and 

combined individual youth and facility factors, 2012 (continued)
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 144

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).

 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.

 

26 For categorical predictors, only significant levels were included in the model and non-significant levels were excluded.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 145

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 146

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.

 

27 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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 147

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 148

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 149

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 150

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

1 + 1 + 1 + 1 + 1 + 1 + 1

=

3

7

= 0.43

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 151

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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 152

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 153

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 + х1β̂

1 + 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 , β̂

1, 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 х1is 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 154

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 155

Figure 5. Stepwise selection process for weighted logistic regression models 

 

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:

 

29 Research Triangle Institute (2008). SUDAAN Language Manual Release 10.0. Research Triangle Park, NC, Section 

4.8.3, pp. 209-211.

Start

Binary weighted logistic regression

Predictors with p-value <= 0.1

Predictors with p-value > 0.1

Drop Multivariate weighted logistic regression

Enter one-by-one

Predictors with p- value <= 0.05

Predictors with p-value > 0.05

Keep
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 156

PPCM =

exp(α̂ + х1β̂

1 + х̅

∗ β̂ ∗

))

1 + exp(α̂ + х1β̂

1 + х̅

∗ β̂∗))

where х1 is the particular characteristic of interest, х̅

∗

is a vector of mean values of the rest 

predictors. α̂ , β̂

1, 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 =

1

w++++

∑∑∑∑

exp(α̂ + хhijk

∗ β̂)

1 + exp(α̂ + хhijk

∗ β̂)

Khij

k=1

Jhi

j=1

Ih

i=1

H

h=1

where w++++ is equal to ∑ ∑ ∑ ∑ whijk

Khij

k=1

Jhi

j=1

Ih

i=1

H

h=1

. 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 

 

30 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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 157

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.

32 Tabachnick, B.G. & Fidell, L.S (2007). Using multivariate statistics (5th ed.). Boston, MA: Pearson Education, Inc. pg. 

782.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 158

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:

0 1 1 2 2

0

1

( )

Level 1: logit[ ( )] ln[ ] ...

1 ( )

Level 2: 

q

ij

ij ij j j ij j ij Qj Qij

ij

S

qj q qs sj qj

s

x

x X X X

x

W u



     



  



     



   

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.

 

33 Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). 

Newbury Park, CA: Sage.

34 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.

35 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.

36 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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 159

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)

from the sampling frame l2wtj =

1

Pj

. The level 1 weights were computed as the inverse of the 

probability that youth i was selected given that facility j was selected l1wti|j =

1

Pi|j

=

1/Pi

1/Pj

, where 

Piis 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 

 

37 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.

38 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.

39 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.
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 160

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 

π

2

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.
Appendices 
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 A 

Facility Questionnaire 
Facility-level and Individual-level Correlates of Sexual Victimization in Juvenile Facilities, 2012 B1

Appendix B 

Facility-Level Construct Measures 

 

Construct name a Item number Item text 

Written up for fighting B15 Have you ever been written up or charged with physically 

fighting with youth here?

B23 Have you ever been written up or charged with physically 

fighting with a facility staff member?

B24 Have you ever been written up or charged with threatening a 

facility staff member?

Positive perceptions of staff B1a Are facility staff good role models?

B1b Are the facility staff friendly?

B1c Do the staff seem to genuinely care about you?

B1d Are the staff helpful?

B1e Are the staff disrespectful (reversed)?

B1f Are the staff hard to get along with (reversed)?

B1g Are the staff mean (reversed)?

B1h Are the staff fun to be with?

Lack of fairness B2a Youth here are punished even when they don’t do anything 

wrong.

B2b Facility staff use force when they don’t really need to.

B2c Problems between facility staff and youth here can be 

worked out (reversed).

B2d Something bad might happen to me if I file a complaint 

against a staff member.

B2e I usually deserve any punishment that I receive (reversed).

B2f Punishments given are fair (reversed).

B2g The staff treat youth fairly (reversed). 

Physical assault by youth B9 Have you ever been hit, punched, or assaulted by another 

youth here?

B11 Has another youth here physically hurt you on purpose?

B14 Did you see a doctor, nurse, or other health care person for 

any of these injuries?

Physical assault by staff B17 Have you ever been hit, punched, or assaulted by facility 

staff here?

B19 Has a staff member physically hurt you on purpose?

B22 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 C1

Appendix C 

Individual-Level Construct Measures 

 

Construct name a Item number Item text 

Written up for fighting B15 Have you ever been written up or charged with physically 

fighting with youth here?

B23 Have you ever been written up or charged with physically 

fighting with a facility staff member?

B24 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

Well-defined structure B2i There are enough staff to monitor what is going on in this 

facility.

B26 Were you told how to report if a staff member or youth is 

breaking the rules?

B27 Were you told that you would not get into trouble if you 

report that a staff member or youth is breaking the rules?

B28 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

Positive perceptions of staff B1a Are facility staff good role models?

B1b Are the facility staff friendly?

B1c Do the staff seem to genuinely care about you?

B1d Are the staff helpful?

B1e Are the staff disrespectful (reversed)?

B1f Are the staff hard to get along with (reversed)?

B1g Are the staff mean (reversed)?

B1h 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

Lack of fairness B2a Youth here are punished even when they don’t do anything 

wrong.

B2b Facility staff use force when they don’t really need to.

B2c Problems between facility staff and youth here can be 

worked out (reversed).

B2d Something bad might happen to me if I file a complaint 

against a staff member.

B2e I usually deserve any punishment that I receive (reversed).

B2f Punishments given are fair (reversed).

B2g 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.