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Journal of Child Sexual Abuse
ISSN: 1053-8712 (Print) 1547-0679 (Online) Journal homepage: http://www.tandfonline.com/loi/wcsa20
Exposing School Employee Sexual Abuse and
Misconduct: Shedding Light on a Sensitive Issue
Molly M. Henschel & Billie-Jo Grant
To cite this article: Molly M. Henschel & Billie-Jo Grant (2018): Exposing School Employee Sexual
Abuse and Misconduct: Shedding Light on a Sensitive Issue, Journal of Child Sexual Abuse
To link to this article: https://doi.org/10.1080/10538712.2018.1483459
Published online: 20 Jun 2018.
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Exposing School Employee Sexual Abuse and Misconduct:
Shedding Light on a Sensitive Issue
Molly M. Henschel
a
and Billie-Jo Grant
a,b
a
Magnolia Consulting, LLC, Charlottesville, VA, USA;
b
Department of Statistics, California Polytechnic
State University, San Luis Obispo, CA, USA
ABSTRACT
While the media continue to report incidents of school
employee sexual misconduct, few empirical studies focus on
this issue. To address this gap in the literature, expand knowl-
edge and awareness around the problem, and inform future
research and programs, this research intends to document
and analyze the characteristics of school employee sexual
misconduct cases reported in the media. The authors con-
ducted a landscape analysis of 361 published school
employee sexual misconduct cases in the United States from
2014, documenting factors such as offender and victim char-
acteristics, type of incident, technology use, location of
offense, and resulting disciplinary actions by schools and
law enforcement. These analyses showed that offenders
were most often male and general education teachers, with
approximately a quarter identified as athletic coaches.
Offenders’average age was 36 years, while the average age
of victims was 15. More than half of incidents took place at
school or school-related events. Results also showed that
school employee sexual misconduct incidents most often
involved physical contact; however, technology (i.e., cell
phones, computers, cameras/video recorders, and storage
devices) played an important role in three out of four cases.
Finally, analyses of the criminal and school-related conse-
quences showed that over half of offenders were placed on
administrative leave or resigned immediately following their
arrest and almost all were convicted of their crimes.
Additional findings concerning this topic are also reported
in this article.
ARTICLE HISTORY
Received 12 September 2017
Revised 27 February 2018
Accepted 29 May 2018
KEYWORDS
School employee sexual
misconduct; sexual abuse;
school personnel; teachers;
student safety; education
policy
Introduction
Media headlines broadcasting cases of sexual abuse and misconduct by school
employees are far from uncommon in the United States. In 2014, the media
reported on the cases of 459 school employees arrested for sex crimes against
children (Google Alerts, 2014). This number swelled to 498 incidents reported in
2015, equivalent to almost three cases each day of the school year (Google Alerts,
2015). While this growth suggests the problem is increasing in the United States,
CONTACT Billie-Jo Grant billiejogrant@gmail.com Department of Statistics College of Science and
Mathematics, California Polytechnic State University, San Luis Obispo, CA 93407
JOURNAL OF CHILD SEXUAL ABUSE
https://doi.org/10.1080/10538712.2018.1483459
© 2018 Taylor & Francis
these numbers still underestimate the total number of cases, as not all incidents are
reported to child welfare or law-enforcement agencies. According to the most
recent and accurate prevalence data available, approximately one in 10 students
will experience sexual abuse or misconduct by a school employee, ranging from
sexual jokes to sexual intercourse, by the time they graduate from high school
(American Association of University Women [AAUW], 2001;U.S.Departmentof
Education [ED], 2004). Few other studies have been conducted in the 1990s with
convenience or voluntary samples
1
leaving the field in desperate need of updated
data to calculate the prevalence and characteristics of school employee sexual
misconduct, especially with regard to technology use.
According to a report commissioned by the U.S. Department of Education
[ED] (2004), educator sexual abuse isacommonphraseusedtodescribeadult-
to-student sexual abuse in schools
2
;however,thistermplacestheemphasison
whether the victim suffered as a result of the abuse and not on the responsi-
bility of the educator. Therefore, Charol Shakeshaft, the author of the U.S.
Department of Education report (2004) used the term educator sexual mis-
conduct to describe “any behavior of a sexual nature which may constitute
professional misconduct.”
3
While this term captures the educator’s inappropri-
ate, unacceptable, and unprofessional behaviors, it does not accurately encom-
pass all school employees. Therefore, this study uses the term, school employee
sexual misconduct to refer to a school employee (e.g., a teacher, coach, admin-
istrator, volunteer, or staff member) who sexually abuses or is involved in
misconduct with a child while caring for that child in a K-12 school setting.
Unfortunately, behaviors that start with a warm smile or a ride home from
practice can develop into much more. The characteristics of teacher–student
relationships that help foster a successful educational environment can create a
potentially abusive situation when a school employee uses that environment to
“groom”a student for eventual abuse,
4
usually by giving a student special
attention and rewards while slowly increasing the amount of touching or other
sexual behaviors (Robins, 2000; Salter, 2003;Shoop,2004). While complaints
of sexual abuse and misconduct occur, such as when a student informally tells
a friend, parent, or school employee, researchers have found that only 9% of
school employee sexual misconduct cases are reported (DOE, 2004). Therefore,
the majority of school employee sexual misconduct complaints are ignored,
distrusted or handled informally, allowing many offenders to continue abusing
children in schools (Shakeshaft & Cohan, 1994;Shoop,2004).
1
Cameron, Coburn, Larson, Proctor, Forde, and Cameron (1986); Stein, Marshall & Tropp (1993).
2
According to U.S. law (18 U.S.C. §2242), sexual abuse includes any nonconsensual sexual activity involving a child
(i.e., indecent liberties, sexual abuse, rape, or child pornography) that occurs through force or threat.
3
Sexual misconduct, which includes both contact (e.g., sexual intercourse) and noncontact (e.g., showing sexual
pictures) behaviors, is not necessarily against the law (i.e., misconduct with a student who is over the age of
consent may not be illegal); however, these behaviors violate ethical codes and are prohibited by school policy.
4
Grooming refers to activities intended to establish an emotional connection with a student and normalize sexual
behavior.
2M. M. HENSCHEL AND B.-J. GRANT
Although extensive research has been done on various characteristics
associated with sexual abuse and misconduct by sexual predators within
the family unit, the victims and offenders of sexual abuse and misconduct
in the school setting have been studied far less frequently (Moulden,
Firestone, Kingston, & Wexler, 2010). An early study by Cameron and
colleagues (1986), which has since been confirmed in subsequent studies,
shows that high school students are more at risk of being victims of school
employee sexual misconduct crimes than students in elementary or middle
schools (Fazel, Sjostedt, Grann, & Langstrom, 2010; Hendrie, 1998; Moulden
et al., 2010; Vandiver & Kercher, 2004). Moulden et al. (2010) also found that
school employee sexual misconduct victims were more likely to be female.
Unfortunately, additional information regarding the characteristics of school
employee sexual misconduct victims remains sparse. However, we know that
victims of sexual abuse by any adult generally experience serious and long-
term effects, including psychological, physical, academic, and behavioral
issues, that can be detrimental to their well-being (AAUW, 2001; Dube
et al., 2003; Felitti et al., 1998; Kendall-Tackett, Williams, & Finkelhor,
1993; Macmillan, 2001; Monnat & Chandler, 2015; ED, 2014).
While significant gaps still exist in the literature, some research does
suggest common characteristics of school personnel who commit abuse and
misconduct against students. Research indicates that teachers whose jobs
include one-on-one time with students (e.g., music teachers and coaches)
are more likely to engage in sexual abuse and misconduct behaviors with
students (Gallagher, 2000; Jennings & Tharp, 2003; Willmsen & O’Hagan,
2003). However, the U.S. Department of Education [ED] (2004) notes that
educators who are in contact with students for greater periods of time, such
as general education teachers, are more likely to be reported for sexual
misconduct. While female teachers make up about 70% of all teachers,
offenders of school employee sexual misconduct crimes are most often
male (Hendrie, 1998; Jennings & Tharp, 2003; Shakeshaft & Cohan, 1994;
U.S. Department of Education [ED], 2014). Hendrie (1998) found that
offenders ranged in age from 21 to 75 years with an average age of 28,
while Moulden et al. (2010) found the mean age of offenders to be
37.28 years. The discrepancies in findings reflect that these studies did not
use representative samples (e.g., Moulden et al. (2010) included only male
offenders) or explore the relationships among school employee sexual mis-
conduct offender and victim characteristics. Therefore, more research exam-
ining sexual abuse and misconduct by school employees is needed.
Finally, the use of technology for personal communication is a relatively
new factor in school employee sexual misconduct, making it easier for offen-
ders to access students outside of school and more privately (Lane, 2015). For
the purposes of this study, technology includes the use of electronic devices
such as cell phones, computers, cameras/video recorders, and storage devices.
JOURNAL OF CHILD SEXUAL ABUSE 3
Offenders can also use applications such as texting, camera phones, email, or
social media networks to communicate with their victims outside of school or
record their inappropriate behaviors. While Lane (2015) examines the impact
of emerging technologies on society, no studies have been published on
technology’s involvement in school employee sexual misconduct cases.
Consequently, empirical research is needed to examine how technology plays
into school employee sexual misconduct offenses.
Clearly, more recent, empirical studies are needed to explore common
patterns associated with school employee sexual misconduct and provide
policymakers and school officials with information they need to protect
children from sexual abuse and misconduct in schools. While it would have
been ideal to collect an updated student survey, an administrator survey, or a
representative sample of court cases, there are budgeting limitations, ethical
concerns, and challenges which may affect participant honesty. For example,
researchers of school employee sexual misconduct have experienced issues
with accessibility of minors, honesty on self-reported surveys, issues related to
representativeness, and lack a national database of court records. One avenue
to provide this needed analysis is to examine and compare published school
employee sexual misconduct cases to existing research, analyzing the cases for
characteristics of offenders and victims, location of school employee sexual
misconduct offenses, actions, and behaviors associated with school employee
sexual misconduct, the use of technology in committing offenses, and the
consequences of the offender’s arrest. This article undertakes such an analysis,
examining published school employee sexual misconduct cases from 2014; the
goal is to enhance knowledge and awareness of the problem and inform future
research and programs.
Media reports do have limitations. First, media reports represent an
underestimated sample of cases and do not include cases that were not
reported to law enforcement or made public. Second, the media reports
may not have included verified information and articles lack information,
resulting in a high rate of missing data for some variables. While media
reports are not representative of the true number of cases of school employee
sexual misconduct and have reporting limitations, they are one accessible
source of data in a very limited field and can provide a more recent cross-
country dataset to explore.
To guide this study, the authors examined five research questions:
(1) What are the characteristics of offenders and victims involved in
school employee sexual misconduct crimes?
(2) When and where do school employee sexual misconduct offenses
occur?
(3) What actions and behaviors characterize school employee sexual mis-
conduct incidents?
4M. M. HENSCHEL AND B.-J. GRANT
(4) What role does technology play in school employee sexual misconduct
crimes?
(5) What consequences do school employee sexual misconduct offenders
encounter as the result of their arrest?
Method
Sample
The authors conducted a landscape analysis of school employee sexual mis-
conduct characteristics in 459 cases from the United States in 2014. These cases
were originally archived using Google alerts
5
of online media sources by Stop
Educator Sexual Abuse Misconduct and Exploitation (S.E.S.A.M.E.), a non-
profit organization dedicated to preventing school employee sexual miscon-
duct. After reviewing the database, the authors conducted additional searches
of online documents and published reports for these cases to confirm content
validity of the S.E.S.A.M.E. information and to retrieve additional information
related to the offenses, including (1) the schools or districts where offenders
were employed, (2) details of the incidents, (3) characteristics of the offenders,
and (4) characteristics of the victims. Cases in which the offender did not
commit a crime against a student (e.g., a general education teacher was
arrested for sexual acts with a family member who was a minor) were elimi-
nated from the sample. As a result, 96 cases were removed, leaving a final
sample of 361 school employee sexual misconduct cases from 2014.
Data coding, procedures, and analyses
The authors performed data cleaning and preparation procedures to ensure the
most accurate and complete data possible. These practices included examining
the data set for precision of data entry and missing data and identifying
outliers. Cases were initially recorded in S.E.S.A.M.E.’s database using qualita-
tive descriptors. To prepare the data for quantitative analyses, qualitative
descriptors were coded into nominal or continuous variables of interest.
Each nominal variable contained at least two items (e.g., male and female).
Some variables were coded dichotomously with items indicating the presence
or absence of the characteristics because these variables could be categorized
across multiple descriptors. After all cases were coded, the authors reviewed
the quantitative data and compared them to the original qualitative descriptors
to ensure accuracy of coding. Finally, the authors ran preliminary frequencies
and crosstabs to reveal any remaining entry errors.
5
Google alerts is an automated service that generates search engine results based on specified criteria and delivers
the results to an assigned email address.
JOURNAL OF CHILD SEXUAL ABUSE 5
Next, the authors investigated the data for missing variables to address any
potential systematic differences between cases with missing values and those
without missing values. Analyses revealed that there was an average of 27% missing
data across all variables, with a range of 0%–94%. The high percentage of miss-
ingness for some variables was due to limited public data, the protection of
juveniles’identities, and budgetary and time constraints preventing the obtain-
ment of official court files. For the key variables of interest to the research questions
there were low rates of missingness, whereas variables secondary to the research
questions, such as the legal consequences, had higher rates of missingness. Further
data collection on these variables was not pursued because it was outside the scope
of this study. For further information on missing data, the authors suggest
examining the descriptive tables (Table 1–5) for precise missing values.
Finally, the authors identified outliers using z-scores. A value was con-
sidered an outlier and examined for potential impacts on the data using
Tabchnick & Fidell’s(2013) guidelines for outliers, in which a value of 3.29
SD from the mean or greater is considered an outlier. Results indicated there
were very few outliers that biased data and had a major impact on descriptive
analyses. Therefore, based on research-based recommendations for handling
outliers (Osborne & Overbay, 2004), the authors included most outliers in
analyses. The authors then examined further cases where the outliers influ-
enced data analyses (i.e., total school enrollment, total number of arrest
counts, months sentenced to jail, and months sentenced to probation).
After examination, the authors determined that the cases did not reflect the
target population and were likely from sampling errors; therefore, these
outliers were excluded from the analyses.
After data preparation procedures were completed, the authors conducted
descriptive analyses to examine school employee sexual misconduct charac-
teristics using SPSS version 24.0. Descriptive statistics included calculations
of percentages, means, and standard deviations. Given the small sample size
and varying levels of data missingness, the authors did not examine any
relationship or predictor questions warranting inferential statistics.
Results
What are the characteristics of offenders and victims involved in school
employee sexual misconduct crimes?
To address the first research question, descriptive data for the offenders and
victims were analyzed. While no two school employee sexual misconduct
offenders or victims are the same, this sample provides insights into who is
typically involved. Table 1 provides descriptive data of the offenders and
victims involved in school employee sexual misconduct crimes reported in
the media during 2014.
6M. M. HENSCHEL AND B.-J. GRANT
Offender Characteristics
School employee sexual misconduct offenders were most often general educa-
tion teachers, male, white, and heterosexual. They averaged 36 years of age.
As presented in Table 1, general education teachers (68%) were more likely to be
arrested for school employee sexual misconduct offenses than any other school
personnel; coaches were involved in nearly a quarter (22%) of all school
employee sexual misconduct offenses resulting in an arrest. For this sample, a
general education teacher could also be employed by the school as an athletic
coach (i.e., dichotomously coded), so some cases might be represented in both
categories because the media reports did not always delineate the specific
relationship between the school employee whether the victim was a student or
Table 1. Descriptive data for offenders and victims in reported cases (N= 361).
Variable NPercentages Percent missing
Type of school personnel* 361 0%
General education teacher 247 68.42%
Coach 79 21.88%
Music/Art teacher 33 9.14%
Assistant teacher 23 6.37%
Substitute teacher 18 4.99%
Exceptional education teacher 11 3.05%
PE teacher 9 2.49%
Elective teacher 6 1.66%
Administrator 6 1.66%
Extra nonschool-affiliated position with children 4 1.11%
Retired/Former teacher 3 0.83%
Custodian 2 0.55%
Other school staff 2 0.55%
Resource officer 1 0.28%
Counselor/School psychologist/Peer evaluator 1 0.28%
Contracted worker 1 0.28%
Offender’s gender (male) 243 67.31% 0%
Offender’s race 120 67%
White 94 78.33%
Black 13 10.83%
Not reported 8 6.67%
Hispanic 4 3.33%
Asian 1 0.83%
Average offender’s age, M(SD) 355 36.27 (10.83) 1%
Offender had multiple victims 116 33.33% 4%
Average number of known victims, M(SD) 315 1.72 (2.31) 13%
Sexual relationship between offender and victim 331 8%
Male offender, female victim 190 57.40%
Female offender, male victim 92 27.79%
Male offender, male victim 34 10.27%
Female offender, female victim 14 4.23%
Male offender, male and female victim 1 0.30%
Offender was arrested previously 6 6.52% 75%
Prior allegations were made about offender 46 50.00% 75%
Average age of victim, M(SD) 288 14.88 (2.52) 20%
Gender of victim (female) 201 55.68% 8%
Note: *Total may equal more than 100% because some cases could be represented in more than one
category; M= mean; SD = standard deviation.
JOURNAL OF CHILD SEXUAL ABUSE 7
student-athlete. Results also indicate that males (67%) were more likely to be
arrested for school employee sexual misconduct offenses than females (33%),
even though female teachers make up the majority of the teacher workforce.
Furthermore, this sample suggests that three out of four offenders were white
(78%) and the majority of offenders (85%) were heterosexual. Finally, the mean
age of offenders was 36.27 (SD = 10.83), with ages ranging from 20 to 73.
Half of offenders had a history of abuse or misconduct with students. In half
of the cases (50%), the offender had been the subject of previous allegations
of inappropriate relationships with students. Furthermore, in six cases,
offenders also had criminal records for previous arrests that were unrelated
to school employee sexual misconduct behaviors. For example, one offender
was arrested in 2002 for third-degree assault and second-degree harassment.
Nevertheless, these offenders with previous accusations and criminal records
continued to work in schools until their 2014 arrests.
A third of school employee sexual misconduct offenders had multiple victims.
The number of victims in a given case ranged from one to 29, with an average of
1.72 (SD = 2.31) victims. One out of three (33%) offenders had two or more known
victims at the time of their arrest; almost half of offenders who had multiple victims
(47%) had two victims. Figure 1 offers a visual depiction of this relationship.
Victim Characteristics
School employee sexual misconduct victims were most often female and
teenagers. Because media reports generally protect the identity of minor
victims, few details of victim characteristics were available in the data.
However, the age and gender of the victims were reported in most cases.
In this sample, a little over half of the victims were female (56%). The average
age of victims was 14.88 (SD = 2.52), with ages ranging from 5 to 18. Figure 2
Figure 1. Percentage of offenders with multiple victims.
8M. M. HENSCHEL AND B.-J. GRANT
provides a visual representation of descriptive data regarding the ages of
victims and offenders in this sample.
When and where do school employee sexual misconduct offenses occur?
The second research question considered both the location and character-
istics of the schools where offenders were employed and the location of the
offense in relation to the schools. Further, the year or years that the school
employee sexual misconduct offense occurred were also examined. Table 2
provides full descriptive data regarding these variables.
School characteristics
Most schools were located in the southern region of the United States. School
employee sexual misconduct incidents occur across the United States. In our
2014 sample, school employee sexual misconduct incidents were reported in
49 states and the District of Columbia. Over half (52%) of these incidents
occurred in the southern region of the United States,
6
with the majority of
those cases in Texas. Figure 3 graphically depicts all 361 school employee
sexual misconduct incidents in the sample. Individual cases are represented
by dots and states are shaded in gray based on the number of incidents in the
state, from light gray for those with the fewest incidents to dark gray for
those with the highest number of occurrences.
School employee sexual misconduct cases were more frequently reported in
public, suburban, and high schools, as well as schools with high percentages
of minorities and students eligible for free and reduced price lunch. Using
2013–2014 school demographic data from the National Center for Education
Figure 2. Victim and offender age characteristics.
6
For this study, the southern region of the United States included Delaware, the District of Columbia, Florida,
Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia, Alabama, Kentucky, Mississippi,
Tennessee, Arkansas, Louisiana, Oklahoma, and Texas.
JOURNAL OF CHILD SEXUAL ABUSE 9
Table 2. Descriptive data for school characteristics, location, and timing of school employee
sexual misconduct offense and arrest in reported cases (N= 361).
Variable NMean or percentage Percent missing
U.S. region of offense 361 0%
South 189 52.35%
Northeast 62 17.17%
West 61 16.90%
Midwest 49 13.57%
Type of school 358 1%
Public 333 93.02%
Private 25 6.98%
Locale (city, rural, suburb, town) 344 5%
Suburb 126 36.63%
City 89 25.87%
Rural 86 25.00%
Town 43 12.50%
Percent free/Reduced lunch, M(SD) 317 53.38 (24.81) 12%
Percent minority, M(SD) 326 48.89 (31.30) 10%
Total students enrolled in school/District, M(SD) 338 1079.27 (790.79) 6%
School grade levels (grade span) 345 4%
High, 9–12 214 62.03%
Middle, 6–8 55 15.94%
Elementary, K-5 25 7.25%
Multigrade (all), K-12 22 6.38%
Multigrade (secondary), 6–12 or 8–12 17 4.93%
Multigrade (primary), K-8 12 3.48%
Incident occurred outside of school* 149 53.41% 23%
Incident occurred at school or school event* 143 51.25% 23%
Incident occurred online* 53 18.79% 22%
Most recent incident occurred (year) 307 15%
2014 248 80.78%
2013 28 9.12%
2012 10 3.26%
2011 3 0.98%
2009 3 0.98%
2008 3 0.98%
2006 3 0.98%
2010 2 0.65%
2004 2 0.65%
1999 2 0.65%
1984 2 0.65%
2007 1 0.28%
Incident occurred in more than 1 year 91 30.03% 16%
Month of arrest 360 0%
May 43 11.94%
April 42 11.67%
March 39 10.83%
January 35 9.72%
February 32 8.89%
October 32 8.89%
June 29 8.06%
September 29 8.06%
November 23 6.39%
July 22 6.11%
August 19 5.28%
December 15 4.17%
Note: *Total may equal more than 100% because some cases could be represented in more than one
category; M= mean; SD = standard deviation.
10 M. M. HENSCHEL AND B.-J. GRANT
Statistics’Common Core of Data (CCD, n.d.), this study supported previous
work in showing that high schools (62%) were more likely to have cases of
school employee sexual misconduct than other schools. In addition, the
majority of schools that reported incidents (93%) were classified as public
schools. While the locales of schools varied, suburban schools had the highest
incidents, with 37% of cases, followed by city (26%) and rural schools (25%).
Furthermore, schools reporting school employee sexual misconduct incidents
averaged 53.38% (SD = 24.81) of students eligible for free or reduced price
lunch, with a range of 0%–100%. Schools also ranged in their percentages of
students considered minorities, with an average of 48.49% (SD = 31.30) and a
range from 0% to 100%. Finally, the schools or school districts
7
where school
employee sexual misconduct cases occurred ranged in size from 28 to 5457
students, with an average of 1079.27 (SD = 790.79) students (see Table 2).
Location of incidents
School employee sexual misconduct incidents occurred both outside of school
and at school or school-related events. In this sample, offenders could have
inappropriate interactions with victims as isolated events or across multiple
occurrences. Therefore, the location of the incident was dichotomously
coded to represent the presence or absence of an offense occurring either
at school or a school-related event, outside of school, or virtually. Over half
of the incidents reported in our sample set (53%) occurred off school
Figure 3. Geographic representation of criminal complaints of school employee sexual miscon-
duct in 2014 (N = 361).
7
For this study, the primary level of characterization was the school where the offender was employed, however,
some school employees worked across a school district (e.g., substitute teacher). Therefore, district demographics
were reported in those cases because the possibilities of victim interaction spanned across more than one school.
JOURNAL OF CHILD SEXUAL ABUSE 11
grounds, such as at the offender’s home or a vacant parking lot. Half of cases
(51%) had at least one incident occurring at school or a school-related event
(e.g., school locker room, staff closet). Although virtual offenses were not as
frequent, 19% of cases also involved virtual activity, such as sending sexually
explicit messages via email or text.
Timing of incidents and arrests
Most inappropriate interactions between offenders and victims occurred in
2014. While this sample included offenders who were arrested in 2014, their
inappropriate interactions with victims could have occurred at any time or
even across multiple years. Results indicate that the majority of incidents
reported (81%) had a most recent occurrence in 2014, followed by 2013 (9%).
Approximately 30% of offenses spanned multiple years (e.g., 1997–2014).
Finally, most school employee sexual misconduct offender arrests occurred
towards the end of the school year. For instance, the beginning half of the
year (January–May) saw the highest instances of arrests, while the summer
months (June–August) and December had the lowest number.
What actions and behaviors characterize school employee sexual
misconduct incidents?
The third research question investigated the type of school employee sexual
misconduct incidents and information around the report to school personnel
or law enforcement authorities. Descriptive data providing insights into types
of actions and behaviors are displayed in Table 3.
Type of offenses
Most interactions between offenders and victims involved physical contact.
For this sample, the majority (79%) of incidents involved physical contact
with the victim (e.g., inappropriate touching or sexual intercourse), while
fewer offenses (14%) were considered noncontact incidents (e.g., inappropri-
ate text messages to a minor) and 7% included both contact and noncontact
behaviors.
Reporting parties
Victims or victims’family members were most likely to report school
employee sexual misconduct incidents to law enforcement. Sexual abuse
and misconduct were reported by a variety of persons, sometimes even including
the offender. However, the majority of allegations came from either the victim or
a family member of the victim; approximately a quarter of reports (27%) came
from victims and another quarter from family members (27%). Generally,
allegations resulting in an arrest were first reported to law enforcement agencies
(56%), with the remaining reported to school personnel (44%) or other (<1%).
12 M. M. HENSCHEL AND B.-J. GRANT
What role does technology play in school employee sexual misconduct
crimes?
Given technological advancements in recent years, the fourth research ques-
tion examined the use of technology and applications in school employee
sexual misconduct cases. A full description of data specifying how technology
was used during school employee sexual misconduct offenses in 2014 is
displayed in Table 4.
Most offenders used technology to communicate with victims
Nearly three out of four offenders (71%) used technology to communicate
with their victims, whether the charged offense occurred virtually or not. For
instance, over half of offenders (52%) used a mobile device such as a cell
phone or tablet to communicate with victims. In addition, a variety of digital
applications, including mobile software apps, online programs, and email,
were used by over half of offenders (55%) to communicate with victims.
Figure 4 provides a full description of this data.
What consequences do school employee sexual misconduct offenders face
as the result of arrest?
Research question five was designed to examine both school-related and
criminal consequences experienced by offenders as a result of arrests for
school employee sexual misconduct. Table 5 provides descriptive data per-
taining to arrests and subsequent outcomes.
Table 3. Descriptive data for type of school employee sexual misconduct offense in reported
cases (N= 361).
Variable description NPercentages Percent missing
Type of incident 359 1%
Contact 282 78.55%
Noncontact 50 13.93%
Both (contact and noncontact) 27 7.52%
First person to make allegation of offense 207 43%
Victim 55 26.57%
Victim’s family member 55 26.57%
School employee 18 8.70%
Anonymous tip 18 8.70%
Other 15 7.25%
Policy agency 14 6.76%
Students/Parents from school 12 5.80%
Victim’s friend 10 4.83%
Offender 6 2.90%
Offender’s friend/Family member 2 0.97%
Online agency 2 0.97%
First agency informed of allegation of offense 205 43%
Police agency 114 55.61%
School district 90 43.90%
Other 1 0.49%
JOURNAL OF CHILD SEXUAL ABUSE 13
Most offenders were placed on paid administrative leave immediately
following arrest and were eventually convicted
After their school employee sexual misconduct arrests, 36% of employees were
placed on paid administrative leave immediately following their arrest, but
maintained their position at the school; and 24% resigned from their positions.
A full list of school-related consequences for offenders can be found in Table 5.
On average, offenders were arrested for two different school employee sexual
misconduct-related offenses (SD =1.17), such as improper relationship between
a school employee and a student and sexual assault, with a range from 1 charge
Table 4. Descriptive data for technology used to assist in school employee sexual misconduct
offense in reported cases (N= 361).
Variable description NMean or percentage Percent missing
Technology was used 174 70.73% 32%
Type of technology* 246 32%
Mobile device (cell phone/tablet/iPod) 129 52.44%
Device not specified 36 14.63%
Computer 15 6.10%
Camera/Video camera 14 5.69%
Storage device (CD/DVD/USB/Cloud) 2 0.81%
Application was used 134 54.47% 32%
Type of application* 246 32%
Texting 87 35.37%
Facebook 18 7.32%
Snapchat 10 4.07%
Kik 9 3.66%
Email 9 3.66%
Online chatting (not specified) 5 2.03%
Camera application 3 1.22%
Twitter 3 1.22%
Application (not specified) 3 1.22%
Social media (not specified) 3 1.22%
Grindr 1 0.41%
Instagram 1 0.41%
Pinger 1 0.41%
Skype 1 0.41%
Note: *Total may equal more than 100% because some cases could be represented in more than one category.
Figure 4. Offenders most often used mobile devices (cell phone/tablet/iPad) to communicate
with their victims.
14 M. M. HENSCHEL AND B.-J. GRANT
to 9. The total number of counts (e.g., two counts of sexual battery) ranged from
1 to 37, with an average of 3.41. Nearly all of the offenders (90%) were convicted
of school employee sexual misconduct crimes; however, over half of the offen-
ders were convicted of lesser crimes than they were charged with at their arrest.
As of January 2017, nearly 2% of offenders were still awaiting trial.
In this sample, offenders could have conviction sentences that included both jail
time and probation periods. Therefore, sentencing was dichotomously coded to
represent the presence or absence of an offender serving jail and probation time.
Of those who were convicted of their crimes, approximately three-quarters of
offenders (73%) were sentenced to jail, prison, or house arrest time; over half
(54%) were sentenced to time on probation, either instead of or in addition to
other punishment. Removing those offenders with sentences greater than 25 years
(44.5%), the median jail sentencing for those who were convicted was approxi-
mately 1.5 years (17.63 months) with a maximum sentence of 300 months
(25 years). Only 39% were required to register as sex offenders. Finally, a few of
the offenders (13%) were levied fines for their school employee sexual misconduct
crimes. These fines ranged from $250 to $85,715 with an average of $11,064.
Discussion
This study provides knowledge of school employee sexual misconduct cases
from 2014 to increase awareness of this issue. Specifically, this study provides
further evidence to support common characteristics already identified in the
limited literature on school employee sexual misconduct and contributes new
Table 5. Descriptive data for school and legal consequences of school employee sexual mis-
conduct offenses in reported cases (N= 361).
Variable description NPercentages Percent missing
Number of total counts for charges at arrest, M(SD) 356 3.41 (4.38) 1%
Number of charge types at arrest, M(SD) 356 1.81 (1.17) 1%
Offender was convicted of crimes 191 89.67% 41%
Number of total conviction counts for charges, M(SD) 173 2.77 (4.36) 52%
Number of conviction charge types, M(SD) 175 1.51 (.83) 52%
Conviction charges less than arrest charges 103 56.28% 49%
Months served in jail/Prison/House arrest, M(SD) 166 46.66 (65.30) 54%
Months of probation, M(SD) 169 49.72 (76.03) 53%
Required to register as sex offender 71 39.23% 50%
Offender charged a fine 23 13.37% 52%
Amount of fine, M(SD) 20 11,064.66 (24,607.61) 94%
Employment status immediately after arrest 284 21%
Administrative leave (paid) 101 35.56%
Resigned 68 23.94%
Terminated 38 13.38%
Suspended (unpaid) 35 12.32%
No longer employed (not specified) 20 7.04%
Not teaching/Retired 14 4.93%
Reassigned 8 2.82%
JOURNAL OF CHILD SEXUAL ABUSE 15
information to the field in investigating the role of technology in school
employee sexual misconduct cases.
Regarding those involved in sexual abuse and misconduct in the school
setting, this study confirmed the findings reported in existing literature. For
instance, this analysis corroborated findings from other research indicating
that high school students and females are at increased risk of involvement in
school employee sexual misconduct crimes over males and students at other
kinds of schools (Cameron et al., 1986; Fazel et al., 2010; Hendrie, 1998;
Moulden et al., 2010; Vandiver & Kercher, 2004). These results also corro-
borate findings that general education teachers are more often reported for
school employee sexual misconduct cases (ED, 2004). Teachers whose jobs
include individualized time with students, such as coaches, teacher aides, and
music teachers, were also well represented in this sample, with approximately
four out of 10 offenders falling into one of those three categories (Gallagher,
2000; Jennings & Tharp, 2003; Willmsen & O’Hagan, 2003). The study also
corroborated a number of other findings, for example that offenders were
more likely to be male (Hendrie, 1998; Jennings & Tharp, 2003; Shakeshaft &
Cohan, 1994; U.S. Department of Education [ED], 2004,2014), range in age
from 21 to 75 years (Hendrie, 1998), and average about 37 years (Moulden
et al., 2010). Disappointingly, analysis of this data suggests that offenders are
persistent and are often not removed from contact at the first sign of
inappropriate behavior. Half of offenders in this data had been the subject
of prior complaints about inappropriate relationships or behavior with their
victim or victims before their eventual arrest.
The study went beyond descriptive data for offenders and their victims to
examine a number of other factors in school employee sexual misconduct
offenses, including the location and nature of the behaviors in the incidents
in the data. While some studies, such as the U.S. Department of Education
[ED] (2004), found that sexual abuse of students most often occurs within
schools (e.g., storage closets, empty classrooms, or hallways), this study found
that a similar number of incidents occurred outside of school (e.g., offender’s
home or a parked car). Furthermore, findings from this study indicate that
79% of victims experienced school employee sexual misconduct involving
physical contact (e.g., touching or rape), while fewer offenses (14%) were
considered noncontact incidents (e.g., inappropriate text messages to a
minor) and 7% included both contact and noncontact behaviors. In
AAUW (2001) and the U.S. Department of Education [ED] (2004), results
indicated that 6.9% of victims experience physical contact interactions with
their offenders and 9.6% experience both contact or noncontact relation-
ships. Some of the differences in findings may result from variations in data
sources. For instance, the current study may have higher instances of contact
behaviors between offender and victim because the authors used media
reports for data, which likely had high-profile cases that attracted media
16 M. M. HENSCHEL AND B.-J. GRANT
attention and/or proceed to legal action. The American Association of
University Women [AAUW] (2001) survey relied on self-report data that
likely included more low-profile offenses that did not gain media attention or
were not reported to law-enforcement agencies.
This analysis also looked at a relatively new avenue for school employee sexual
misconduct crimes—the use of technology for personal communication (Lane,
2015). Unsurprisingly, given the newness of this technology, there is no other
research on the role of technology in school employee sexual misconduct cases, or
the nature or frequency of its use in the context of school employee sexual
misconduct behaviors. The current findings indicate that most victims and
offenders used technology to communicate, regardless of whether the actual
offense occurred virtually or not. This suggests an urgent need for more research
around the intersection of technology and sexual abuse and misconduct by school
employees.
One encouraging note in the study is the frequency and speed with which
identified offenders were removed from their schools. Over half of employees
were placed on paid administrative leave or resigned immediately after their
arrest, which most often occurred towards the end of the school year
(January–May). This timing provides interesting insight into the grooming
behaviors of offenders; as the U.S. Department of Education [ED] (2004)
suggests, offenders require time to select a victim and groom him or her into
allowing increased touching or other sexual behaviors. The frequency of
arrests late in the school year offers some insight into how much time
offenders actually take to groom their victim. Furthermore, once they were
arrested, 90% of offenders in the sample were convicted.
The present study comes with a number of limitations that may reduce the
generalizability of findings. First, in the absence of extensive empirical studies,
media accounts are among the few sources of information about this problem,
but this data source presents unique challenges for researchers. While these
sources provide valuable information about incidents, they are not empirically
based, can be presented in inflammatory ways, and often lack information. And
they are clearly incomplete. The sample for this study included only those cases
that attracted media coverage, were posted on the Internet, and were reported to
criminal authorities. Given the 55.4 million students enrolled in K-12 education
during the 2013–2014 school year, the 361 cases of school employee sexual
misconduct that gained media coverage in 2014 is far less than what would be
predicted based on the estimated prevalence of 1in 10 students experiencing
sexual abuse and misconduct by a school employee (American Association of
University Women [AAUW], 2001; U.S. Department of Education [ED], 2004,
2016). This strongly suggests that there are an unknown and likely large number
of cases not represented in this sample.
In addition, the authors were often forced to rely on media accounts for
data because gaining access to full files was costly and time consuming, often
JOURNAL OF CHILD SEXUAL ABUSE 17
due to measures meant to protect juvenile victims. As a result, there were
numerous times when data missing from public documents was unobtainable
due to time and budget constraints. Therefore, the authors recommend
examining the descriptive tables for information on missing data.
Finally, data for this study is based on cases from 2014 and analyses were
performed in 2017. Given that technology is constantly changing and cases
are evolving, these cases may not be representative of cases in the future.
Therefore, the authors should not generalize these findings past this parti-
cular year of research. For these reasons, our data should be considered
preliminary and should be replicated in future larger samples with a wider
range of measures or a more thorough record review (i.e., pulling cases from
court clerks).
Despite these limitations, this study represents an important first step.
Future work is needed to continue conversations about school employee
sexual misconduct and establish a starting point for communities, whether
research-oriented, policy-oriented, or school-based, to address this issue.
Specifically, the characteristics described in this study can be used by school
boards and lawmakers to learn about the characteristics of school employee
sexual misconduct cases and develop policies and procedures to prevent
future incidents. Continued research into this topic is critical for bringing
light to the issue and as a first step in understanding its prevalence in order
to pave the way to prevention. Future research needs to examine larger
samples of school employee sexual misconduct cases that have lower occur-
rences of data missingness, span multiple years, and include cases not
reported by media or law enforcement.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This project is supported by Award No. 2015-CK-BX-0009 awarded by the National Institute
of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and
conclusions, or recommendations expressed in this publication are those of the authors(s)
and do not necessarily reflect those of the Department of Justice. This study was awarded to
and completed by Magnolia Consulting.
Notes on contributors
Molly Henschel has a Ph.D. in Research and Evaluation Studies from Virginia
Commonwealth University and is a researcher and evaluator with Magnolia Consulting
where she supports quantitative, qualitative, and mixed-methods studies. Dr. Henschel served
as a researcher on a study funded by the Department of Justice and awarded to Magnolia
18 M. M. HENSCHEL AND B.-J. GRANT
Consulting from 2015 –2017 that examined school employee sexual misconduct policy
implementation nationwide.
Billie-Jo Grant has a Ph.D. in Educational Research, Statistics and Evaluation from the Curry
School at the University of Virginia and is an experienced quantitative and qualitative
methodologist, researcher, and evaluator as well as an expert on school employee sexual
misconduct. She has led multiple national efficacy studies and was the principal investigator
on a 2015 –2017 Department of Justice funded study awarded to Magnolia Consulting which
examined school employee sexual misconduct policy implementation nationwide.
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