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Original article
Surveillance or Safekeeping? How School Security Officer and Camera
Presence Influence Students’Perceptions of Safety, Equity, and
SupportI
D1X XSarah Lindstrom Johnson, D2X XPh.D.
a,
*,D3X XJessika Bottiani, D4X XPh.D.
b
,D5X XTracy E. Waasdorp, D6X XPh.D.
c
, and
D7X XCatherine P. Bradshaw, D8X XPh.D.
b
a
School of Social and Family Dynamics, Arizona State University, Tempe, Arizona
b
School of Education, University of Virginia, Charlottesville, Virginia
c
School of Public Health, Johns Hopkins University, Baltimore, Maryland
Article History: Received December 12, 2017; Accepted June 16, 2018
Keywords: School security; School surveillance; Violence prevention; School safety
ABSTRACT
Purpose: Target hardening, or increasing the use of security measures, is a frequently used response to
perceived safety concerns in schools. Studies are mixed as to their effectiveness on students’perceptions
of safety and little is known about their influence on other aspects of school climate, particularly for
minority students. This study will examine the association between observed security measures in sec-
ondary schools and students’perceptions of safety, equity, and support.
Methods: School climate surveys were completed by 54,350 students from 98 middle and high schools
across the state of Maryland beginning in Spring 2014. Concurrent observations of the school physical
environment, including security measures (i.e., officers and cameras), were conducted by trained outside
assessors. Multilevel regression analyses examined the association between school security officers and
cameras and students’perceptions of safety, equity, and support, while controlling for school and neigh-
borhood characteristics. Cross-level interactions explored differential effects of security measures for
Black students.
Results: Greater use of security cameras inside the school was related to lower perceptions of safety,
equity, and support. A moderate level of security camera use outside the school was related to higher
student perceptions of support. Security officer presence was associated with higher perceptions of
safety. For black students, cameras were associated with elevated perceptions of safety and support rela-
tive to white students.
Conclusions: Our findings may suggest that outside cameras and security may be perceived by students
as safekeeping, whereas inside cameras may evoke feelings of being viewed as potential perpetrators
who need surveillance.
© 2018 Society for Adolescent Health and Medicine. All rights reserved.
IMPLICATIONS AND
CONTRIBUTIONS
The presence of security
measures in schools has
increased in the past
decade, partly as a
response to high-profile
incidents of school vio-
lence. This research sug-
gests that schools should
be thoughtful about the
type, quantity, and location
of security measures as
they can negatively impact
students’perceptions of
the school.
As public concern has heightened following mass shootings and
other violent incidents on school grounds, the approach of target
hardening, or strengthening school security measures has become
increasingly favored in U.S. schools [1]. According to the U.S.
Department of Education, the use of these measures has increased
substantially since the early 2000s, with the vast majority of sec-
ondary schools currently reporting using security cameras to
IThis work was presented at the 2015 Society for Prevention Research Annual
Conference.
*Address correspondence to: Sarah Lindstrom Johnson, Ph.D.,Q3 X XSchool of Social and
Family Dynamics, Arizona State University, PO Box 873701, Tempe, AZ 85287.
E-mail address: sarahlj@asu.edu (S. Lindstrom Johnson),
Jessika.bottiani@virginia.edu (J. Bottiani), Twaasdo1@jhu.edu (T.E. Waasdorp),
Catherine.Bradshaw@virginia.edu (C.P. Bradshaw).
1054-139X/© 2018 Society for Adolescent Health and Medicine. All rights reserved.
https://doi.org/10.1016/j.jadohealth.2018.06.008
ARTICLE IN PRESS
Journal of Adolescent Health 000 (2018) 17
www.jahonline.org
monitor school grounds and deploying security staff at least once
per week [2]. Despite the prevalence of use, research drawing
upon large, nationally represented samples suggests null and even
iatrogenic effects of these types of security measures on rates of
school violence and victimization [36]. These findings may be
attributable to concomitant negative effects of security measures
on school climate, which can, when assessed as positive and sup-
portive, protect against school violence and victimization [7]. This
study will examine the association between observed security
measures in secondary schools and students’perceptions of school
climate.
Approaches to school violence prevention
Target hardening is a form of situational crime prevention,
which attempts to reduce opportunities for crime. It is based on
the broader criminological theory, Routine Activities Theory [8],
which focuses crime prevention efforts on the situation rather
than on the individual perpetrating the crime. Studies have found
aspects of the school physical environment, such as lighting and
disorder, to be related to students’and teachers’reports of crime
and violence [9]. Studies more specifically examining the impact of
security measures have found mixed results. Some longitudinal
studies have found no relationship between the presence of secu-
rity officers or cameras and student report of peer victimization
[4], larceny, or assault [5] and other studies have found that
increasing security guards was associated with an increase in
administrator report of nonserious violence [3]. Taken together,
more research is needed to understand how target hardening, spe-
cifically the use of security measures, relates to violent and other
delinquent behaviors.
Improving school climate has also been suggested as a mecha-
nism to reduce school violence. In its most fundamental conceptu-
alization, school climate refers to the shared beliefs, values, and
attitudes that shape interactions between students, teachers, and
administrators and set the parameter of acceptable behavior and
norms for the school [10]. A favorable school climate has been
associated with both improved behavioral and academic outcomes
for students [7]. Some definitions of school climate, including the
U.S. Department of Education’s, expand the construct to include
safety and the environment, while others see it as a factor that
influences school climate [10,11]. Regardless, as safety and the
physical environment are intentionally impacted by target harden-
ing initiatives, the influence of security measures on students’per-
ceptions of these domains is important to understand. For
example, such security measures could promote students’sense
that they are protected and that their safety is important to the
school [9]. In contrast, the presence of security measures may sig-
nal to students that they are not safe at their school [12]. More-
over, students may perceive security measures as an indicator of
the disciplinary environment of the school, where adults at school
view them as potential perpetrators who require surveillance [13].
Finally, as security measures are disproportionately present in
poor, predominantly black schools [14,15] they may result in per-
ceptions of inequitable treatment.
Effects of security measures on perceptions of school climate
An often-studied effect of security measures is on students’per-
ceptions of safety. In one multilevel analysis, such practices did not
significantly reduce perceptions of risk or fear of crime [16]; other
studies employing longitudinal national survey data found that
school security efforts were associated with decreases in percep-
tions of safety [12,17]. Conversely, research suggests students and
faculty see physical characteristics, in particular school security
officers and cameras, as important contributors to a safe school
[18,19], especially when students feel unsafe [20]. It may be that
regardless of the actual effectiveness of security measures, stu-
dents perceive them as safekeeping measures. Given the apparent
contradiction between student and staff preferences for security
and research suggesting possible iatrogenic effects of security on
perceptions of safety, it is important to examine related aspects of
safety (i.e., perceptions of support).
Increased security measures may unfairly contribute to the
criminalization of black students’behavior (e.g., the “school to
prison pipeline”)[21]. The differential implementation of security
measures may also promote feelings of inequitable treatment,
which can impact students’sense of connectedness to their school
[11]. Indeed, a growing literature highlights racial gaps in students’
perceptions of school climate [22,23]. Interestingly, one study
examined differences by race and found security officers increased
fear for white students but not for black students [24]; yet research
examining the role of security measures in explaining racial dis-
parities in school climate is limited.
Overview of the current study
Although public debate on use of security measures often spikes
following traumatic events like the shootings at Marjory Stoneman
Douglas High and Sandy Hook Elementary schools, more work is
needed to understand whether such security measures signal safety or
greater concern for students [25]. The overarching goal of this paper
was to explore how independently assessed school security practices
relate to student perceptions of safety, support, and equity. A novel
contribution of this study is its use of an observational measure of the
school physical environment; this methodological approach has many
advantages over the prior work, which has largely relied on student
and principal report of security measures [3,4]. Based on the existing
literature we hypothesized that the presence of security measures
wouldbeassociatedwithlowerperceivedsafety[9,12], but higher per-
ceived support [1820]. We also aimed to broaden our understanding
of these associations by exploring differential perceptions by student
ethnicity, given the increased use of such security measures in more
disadvantaged schools [15].Specifically, we considered potential dif-
ferences in effects for black students, while adjusting for school contex-
tual features like neighborhood disadvantage. Based on prior work
[11], we expected the presence of security measures to be associated
with decreases in equity for black students. These findings have the
potential to inform policies and practices related to school safety, par-
ticularly in light of growing disparities between black and white stu-
dents on a range of academic and behavioral outcomes [7,26].
Specifically, the use of security measures may negatively influence per-
ceptions of school climate, which may in turn negatively influence stu-
dent health and well-being [7] and exacerbate health and educational
disparities.
Methods
Participants
Data come from a statewide project focused on measuring and
improving school climate called the Maryland Safe and Supportive
Schools Initiative [27]. Data were collected from 54,350 students
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2S. Lindstrom Johnson et al. / Journal of Adolescent Health 00 (2018) 17
in 98 middle and high schools across 13 school districts within the
state of Maryland (see Table 1).
Procedure
The Maryland State Department of Education conducted dis-
trict-wide meetings with principals to recruit schools to voluntar-
ily participate in the project. An anonymous web-based survey
was administered during the spring semester of 2014 (high
schools) and 2016 (middle schools) to students in grades 6-12
using passive parent consent and youth assent. School staff admin-
istered the voluntary and anonymous survey to students in lan-
guage arts classrooms following a written script; 25 classrooms
were sampled from the high schools and 18 classrooms sampled
from the middle schools. Data collectors hired and trained by the
research team conducted systematic observations of the school
physical environment during the same spring semester when the
student data were collected. All data were entered in real-time on
a handheld tablet using the Pendragon mobile data collection soft-
ware. Observers were trained and reliability and recalibration pro-
cedures were conducted to ensure consistency of collection [28].
De-identified data were used for these analyses. The Institutional
Review Boards at Johns Hopkins University and the University of
Virginia approved this project.
Measures
Outcomes. Student self-report data come from the Maryland Safe
and Supportive Schools Initiative School Climate Survey that was
developed around the U.S. Department of Education’s model of
school climate [29] and includes items regarding safety, engage-
ment, and environment [27]. Specifically, student perceptions of
school safety were measured by 4 items assessing their sense of
physical safety at school (e.g., I feel safe at this school”;a= .60).
Perceived school equity was measured by four items assessing stu-
dents’perceptions of fair treatment and cultural inclusion at school
by race and ethnicity, gender, socioeconomic status, and cultural
background (e.g., “At this school, students of all races are treated
the same”;a=.82). Student perceptions of school support were
measured by three items assessing perceptions of the availability
of help for personal problems (e.g., "Students who need help for
their problems are able to get it through school”;a= .77). For all
three outcomes, item response options were on a 4-point Likert
scale from disagree strongly (1) to agree strongly (4), with higher
scores indicating higher levels of the construct.
Predictors. The School Assessment for Environmental Typology is
an observational tool which draws on several previously validated
measures and assesses three broad dimensions of the school envi-
ronment, including surveillance [28]. Specifically, officer presence
was measured as a count of the instances of whether in a security
capacity was present at each of two locations, entrance to the
school grounds and the school entrance. Inside cameras were
counted using the aggregate of six observed interior locations
within the school building, including two hallways, two stairwells,
the school entrance, and the cafeteria. Outside cameras were
counted using the aggregate of five observed exterior locations on
school grounds, including entrance to the school grounds, the
physical layout (e.g., perimeter of the school), playing fields, and
parking lots. Due to the skewed distribution, for each variable (out-
side and inside), the count was binned into tertiles, and dummy
variables were created to allow comparisons to the lowest tertile
bin as the reference group.
Covariates. Students were asked to self-identify their grade, gen-
der and their race (i.e., white, black, Hispanic, Asian, other). The
Maryland State Department of Education provided information
about the number of enrolled students and the percent minority
rate in each school. We also used the community disadvantage
index from the 20082013 American Community Survey to assess
the larger community context [30,31]. The community disadvan-
tage index is calculated using Census-tract level items. The items
used to create the index include the percentages of: (a) adults >24
years with a college degree, (b) owner-occupied housing, (c)
households with incomes below the federal poverty threshold,
and (d) female-headed households with children. Each school was
assigned a Census tract using ArcMap.
Data analysis
To account for the multilevel structure of the data, represented
by students within classrooms within schools, three-level hierar-
chical linear models were conducted in the HLM software [32].At
the individual level, we included gender (female), grade, and race/
ethnicity (dummy coded with white as the reference group). Given
students took the survey within classrooms, this cluster was
accounted for the modeling (i.e., level 2); however, no other varia-
bles were assessed at this level. At the school level, we included
school security measures of officer presence and security cameras,
the latter of which were assessed separately as inside cameras or
outside cameras (broken into tertiles with the lowest tertile as the
reference group). We adjusted for the disadvantage index score,
enrollment, and percentage of non-white students (% minority). For
main effect models, student-level and school-level variables were
grand-mean centered. Due to our hypotheses that camera and
security officer presence would differentially relate to student-
reported safety, equity, and support among black relative to white
students, cross-level effects between black race and the school
security features were tested for each outcome. For these cross-
level interactions, the student-level variable (race/ethnicity) in the
tested interactions was group-mean centered. Each student-level
variable was individually tested for randomly varying slopes.
Table 1
Student and school demographic characteristics for full sample
Student characteristics (N = 54,350) N (%)
Gender
Male 27,040 (49.8)
Female 27,310 (50.2)
Race/Ethnicity
Black 15,904 (29.3)
White 23,195 (42.7)
Hispanic 6,031 (11.1)
Asian 3,209 (5.9)
Other/Combined 6,011 (11.1)
Grade
Lower 24,017 (44.2)
Upper 30,333 (55.8)
School characteristics (N = 98 schools) M(SD)
Community disadvantage index ¡1.99 (1.08)
Total enrollment 1,136.51 (443.74)
% Minority 55.82 (24.65)
% Locations with 1+ Officers present 37.8%
Count of inside cameras 15.6 (7.5)
Count of outside cameras 19.5 (14.3)
SD = standard deviation.
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S. Lindstrom Johnson et al. / Journal of Adolescent Health 00 (2018) 173
Model fit indices (Akaike information criteria (AIC) and Bayesian
information criterion (BIC)) for the unconditional and conditional
models are reported on the tables; smaller values indicate better
fit[33].
Sample weighting
When computing the multilevel analyses, we weighted the stu-
dent self-reported school climate data to reflect the entire student
population in the 98 participating schools. Specifically, sampling
weights were created using the raking method [34], an iterative
procedure that produces weights based on marginal results from
multiple variables (i.e., grade level, sex, and race/ethnicity).
Results
Descriptive analyses
Across all 98 schools in the sample, the range of indoor cameras
observed was 524 (M= 15.6, standard deviation = 7.5) cameras. The
range of outdoor cameras was larger, 069 (M= 19.5.5, standard
deviation = 14.3) cameras. For officer presence at the time of obser-
vation, 37.8% of the school sample had one or more officers present
at the entrances inside and outside of the school building.
Multilevel analyses
Safety. In schools with the greatest number of cameras inside the
building, students had lower perceptions of safety (b = ¡.07) rela-
tive to schools with the fewest number of cameras inside the
building. There was no significant association overall for outside
cameras. However, cross-level interactions examining whether the
number of cameras present outside the school moderated differen-
ces in perceived safety for black students were found to be signifi-
cant (b = .07). Specifically, the positive association between high
count of outside cameras and perceived safety for black students
was significantly greater than it was for white students (see Figure
1A). Conversely, the negative association between high count of
indoor cameras and perceived safety for black students was signifi-
cantly less than it was for white students (see Figure 1B). In our
analysis of school security officer presence, we found that in
schools with a greater number of locations with an officer present,
students had significantly higher perceptions of safety (b = .05).
Females and younger students perceived school to be less safe rel-
ative to males and older students; Latino and Other race/ethnici-
ties perceived school to be less safe as compared to white
students. Regarding the school-level variables, higher community
disadvantage index, higher enrollment, and higher percentage of
minority students in a school were significantly associated with
lower perceived school safety.
Equity. In schools with the greatest number of cameras inside the
building, students had lower perceptions of equity (b = ¡.08). No
associations between number of outdoor cameras or security offi-
cer presence and student perceptions of equity were found. None
of the cross-level interactions were significant. Females, younger
students, and all racial/ethnic groups perceived school as less equi-
table. Regarding the school-level control variables, higher commu-
nity disadvantage index was significantly associated with lower
perceived school equity.
Support. In schools with the greatest number of cameras inside the
building, students had lower perceptions of support (b = ¡.10).
Conversely, in schools in the middle tertile of number of outside
cameras present, students had higher perceptions of support
(b = .08). No associations between security officer presence and
student perceptions of support were found. Cross-level interac-
tions between black and number of cameras present in the school
were found to be significant. Specifically, an inverse pattern of
association was found for black and white students (b = .06). For
black students, perceived support was higher for students in
schools within the mid tertile of inside cameras, whereas for white
students, perceived support was lower for students in schools
within the mid tertile of inside cameras (see Figure 1C). At the stu-
dent-level, females and younger students perceived school to be
less supportive. Black and Other race/ethnicities perceived school
to be less supportive compared to white students. Regarding the
school-level covariates, the higher the community disadvantage
index and the percentage of minority students in the school were
associated with lower perceived school support (see Table 2).
Discussion
Given the wide use of security officers and cameras, and their
potential to influence students’school experiences, this paper
examined associations of observed security measures on students’
perceptions of school safety, equity, and support using a multilevel
framework. Our findings suggested that the associations with cli-
mate perceptions varied as a function of the locations, extent, and
type of security measures utilized. Specifically, a higher number of
security cameras inside the school building was negatively associ-
ated with students’perceptions of safety, equity, and support; this
suggests potential iatrogenic effects of cameras within the school.
In contrast, outside cameras produced mixed findings, including
null effects for safety and equity and positive associations with
perceptions of support at moderate levels. Interestingly, in schools
with higher levels inside and outside cameras, black students
tended to have significantly more favorable views of school safety
and support, but not equity, relative to white students.
One possible interpretation of our findings is that students may
perceive a difference in the use of security cameras—either as pro-
tecting them from harm coming from outside the school (e.g., safe-
keeping, as with outside cameras) or monitoring them (e.g.,
surveillance, as with inside cameras). Specifically, the highest level
of inside camera use was associated with lower perceptions of
safety, equity, and support. Qualitative studies provide insight into
this finding as students perceive certain security measures (like
metal detectors) as unnecessary inconveniences and feel misbe-
having students are not deterred by this security presence [9,35].
It is interesting that there appeared to be a threshold above which
a certain number of inside cameras were negatively associated
with school climate. In contrast, outside cameras were associated
with higher perceived school support. Studies have found that stu-
dents who feel unsafe tend to rate security measures (e.g., surveil-
lance) as more important [20], with students recognizing the role
of neighborhood violence in school safety [18]. This critical finding
of differential effect by camera location suggests the importance of
context (here captured by inside and outside), and may help us
better understand prior mixed findings on the effects of cameras.
Other aspects of context, such as the discernibility of cameras, rep-
resent important future research questions.
With regard to the second form of security measures examined,
we found that security officer presence was positively associated
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4S. Lindstrom Johnson et al. / Journal of Adolescent Health 00 (2018) 17
2.92
2.94
2.96
2.98
3
3.02
3.04
3.06
3.08
3.1
White Black
ytefaSloohcSfosnoitpecreP
Low-Tertile Outside Camera High-Tertile Outside Camera
2.92
2.94
2.96
2.98
3
3.02
3.04
3.06
3.08
3.1
White Black
ytefaSloohcSfosnoitpecreP
Low-Tertile Inside Camera High-Tertile Inside Camera
2.66
2.67
2.68
2.69
2.7
2.71
2.72
2.73
2.74
2.75
2.76
White Black
troppuSloohcSf
osnoitpecreP
Low-Tertile Inside Camera Mid-Tertile Inside Camera
A
B
C
Figure 1. (A) Outside cameras and perceptions of school safety. (B) Inside cameras and perceptions of school safety. (C) Inside cameras and perceptions of school support.
ARTICLE IN PRESS
S. Lindstrom Johnson et al. / Journal of Adolescent Health 00 (2018) 175
with student perceptions of safety, but was not associated with
perceptions of equity or support. These findings are in contrast to
previous work which has found no association between school
security officers and students’perceptions of safety [12,16,17];
however, the prior studies have relied on administrator or parent
report of security measures, whereas our observational measure
may have better captured student exposure to security officers.
Other studies exploring the association between school security
and victimization have found this relationship to vary by type of
security personal and use of force capabilities [36]. Additional
research is needed to explore in greater depth the characteristics
of officers (e.g., values, beliefs, skills, and race), and their relation-
ships with students, which may help clarify our findings.
Our findings also suggested that associations with security cam-
eras may differ based on students’race, with the conceptualization
of race in the present research as a social position variable and a
construct signifying the potential for exposure to racial bias. Given
this view of race we did not anticipate our finding that the negative
association of inside cameras on perceptions of safety was less for
black students or that the positive association of outside cameras on
support was greater than it was for white students. Although these
findings are surprising they are consistent with some prior studies
[33,34]. Notably, we found no significant moderating effect of secu-
rity measures on perceptions of equity among black relative to white
students, suggesting that disparities in perceived school equitable
treatment were not sensitive to differences in quantity of security
cameras or presence of officers. Given black students’exposure to
harmful bias and discrimination in schools settings [33,35,36],and
the history of negative interactions with police in black communities
[34,37], further research focused on black students’experiences
involving school security officers and cameras is critical.
Limitations and Strengths
The cross-sectional nature of our data limits any causal inferences
about the associations observed. It is possible that the associations
may reflect that high levels of disorder may cause school administra-
tors to install more security cameras and deploy security personnel
while also causing students to have more negative views of school
climate [5]; however, we did control for a place-based measure of
community disadvantage to address this potential confounding.
Moreover, the use of data from multiple informants (student self-
report, independent observer report, and census tract data) is a
strength of this study. Nonetheless, in designing the observation,
choices were made as to the locations to assess security measures.
For example, school security officers were only recorded at their
most visible locations (i.e., entrance to the school grounds and the
entrance to the school building). Like our finding with cameras it
may be that security officers in different locations of the school could
be associated with differential findings [35]. As previously noted, the
observational measure did not account for the characteristics of
security officers or the nature of their relationships with students.
Table 2
Associations between observations of security measures and student perceptions of safety, equity, and support
Safety Equity Support
b Standard
error
pb Standard
error
pb Standard
error
p
Student-level variables
Female (vs. male) ¡.04 .01 .001 ¡.05 .01 <.001 ¡.02 .01 .022
Grade (6th through 12th) ¡.02 .01 .007 ¡.04 .01 <.001 ¡.04 .01 <.001
Black
a
.00 .02 .971 ¡.06 .02 .006 ¡.03 .01 .019
Latino ¡.03 .01 .008 ¡.08 .02 <.001 ¡.03 .02 .092
Asian/Pacific Islander ¡.04 .02 .051 ¡.06 .02 .009 .04 .02 .065
Other
b
¡.09 .02 <.001 ¡.15 .02 <.001 ¡.11 .01 <.001
School-level variables
Mid inside cameras (vs. low tertiles) ¡.01 .03 .707 .04 .04 .263 ¡.02 .03 .515
High inside cameras (vs. low tertiles) ¡.07 .03 .044 ¡.08 .04 .046 ¡.10 .03 .003
Mid outside cameras (vs. low tertiles) .05 .03 .183 .07 .04 .062 .08 .03 .008
High outside cameras (vs. low tertiles) .03 .04 .502 .09 .04 .052 .05 .04 .139
Officer presence .05 .02 .010 .02 .02 .260 .01 .02 .620
% Minority ¡.002 .00 <.001 .00 .001 .457 ¡.00 .001 .017
Enrollment .00 .00 .024 .00 .00 .396 .00 .00 .299
Community disadvantage index ¡.06 .01 <.001 ¡.04 .01 .002 ¡.03 .01 .015
Cross-level interactions
Mid inside cameras £black .04 .03 .189 .00 .04 .936 .06 .03 .034
High inside cameras £black .06 .03 .042 .00 .04 .994 .04 .03 .190
Mid outside cameras £black ¡.01 .03 .693 .02 .04 .679 .00 .03 .997
High outside cameras £black .07 .03 .030 .01 .04 .884 .03 .03 .416
Officer presence £black ¡.03 .02 .067 ¡.02 .02 .498 .00 .02 .830
AIC unconditional 86,537.94 108,756.8 106,784
AIC final 85,373.46 107,979.9 106,237.4
BIC unconditional 86,534.52 108,753.4 106,780.5
BIC final 107,838.5 85,232.04 106,131.9
ICC .030 .048 .016
Low tertile of inside cameras = 511; Mid tertile of inside cameras = 1216; High tertile of inside cameras = 1742. Low tertile of outside cameras = 010; Mid tertile of out-
side cameras =1124; High tertile of outside cameras = 2569.
All analyses controlled for intervention status. AIC = Akaike information critieria; BIC = Bayesian information criteria.
yp<.10, *p<.05, **p<.01, ***p<.001.
a
White is the reference group.
b
Other represents American Indian/Alaska Native, Native Hawaiian and Other.
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Implications
Concerns remain about the overall effectiveness of security offi-
cers and cameras, which represent a potentially significant finan-
cial investment for schools and districts [25]. One understudied
potentially harmful effect of security measures on health and men-
tal health is their influence on school climate, particularly for black
students. These findings suggest important differences in the influ-
ence of security measures on students’perceptions of the school by
type, location, and extent of their use. Taken together, our findings
may suggest that outside cameras and security may be perceived
by students as safekeeping, whereas inside cameras may evoke
feelings of being regarded as potential perpetrators who need sur-
veillance. School administrators and district leaders should care-
fully weigh the research evidence supporting the use of various
security measures, including consideration of the location and
extent of their use, and how those decisions may vary as a function
of student and school contextual factors.
Funding Sources
This work was funded in part by grants from the U.S. Depart-
ment of Education to the Maryland State Department of Education
and the National Institute of Justice (2014-CK-BX-0005) to Cather-
ine Bradshaw.
References
[1] Addington LA. Cops and cameras public school security as a policy response to
columbine. Am Behav Sci 2009;52:1426–46. https://doi.org/10.1177/
0002764209332556.
[2] Musu-Gillette L, Zhang A, Wang K, et al. In: Indicators of School Crime and
Safety: 2016; 2017 http://nces.ed.gov.
[3] Na C, Gottfredson DC. Police officers in schools: effects on school crime and
the processing of offending behaviors. Justice Q 2013;30:619–50. https://doi.
org/10.1080/07418825.2011.615754.
[4] Blosnich J, Bossarte R. Is there an associated between school safety measures and
peer victimization. J Sch Health 2011;81:107–13. https://doi.org/10.1111/j.1746-
1561.2010.00567.x.
[5] Burrow JD, Apel R. Youth behavior, school structure, and student risk of victimi-
zation. Justice Q 2008;25:349–80. https://doi.org/10.1080/07418820802025181.
[6] Crawford C, Burns R. Preventing school violence: assessing armed guardians,
school policy, and context. Polic Int J Police Strateg Manag 2015;38:631–47.
https://doi.org/10.1108/pijpsm-01-2015-0002.
[7]ThapaA,CohenJ,GuffeyS,Higgins-D’Alessandro A. A review of school
climate research. Rev Educ Res 2013;83:357–85. https://doi.org/10.3102/
0034654313483907.
[8] Cohen LE, Felson M. Social change and crime rate trends: a routine activities
approach. Am Sociol Rev 1979;44:588–608. https://doi.org/10.2307/2094589.
[9] Lindstrom Johnson S, Waasdorp TE, Cash AH, et al. Assessing the association
between observed school disorganization and school violence: implications
for school climate interventions. Psychol Violence 2017;7:181–91. https://doi.
org/10.1037/vio0000045.
[10] Payne A. Creating and sustaining a positive and communal school climate:
contemporary research, present obstacles, and future directions. Washington,
DC: National Institutes of Justice. p. .1–30. https://www.ncjrs.gov/pdffiles1/
nij/250209.pdf.
[11] Debnam KJ, Lindstrom Johnson S, Waasdorp TE, Bradshaw CP. Equity, connec-
tion, and engagement in the school context to promote positive youth devel-
opment. J Res Adolesc 2014;24:447–59. https://doi.org/10.1111/jora.12083.
[12] Schreck CJ, Miller JM. Trouble in the school yard: a study of the risk factors of
victimization at school. J Sch Violence 2003;2:57–79. https://doi.org/10.1300/
J202v02n04_04.
[13] Spencer MB, Fegley S, Harpalani V. A theoretical and empirical examination of
identity as coping: linking coping resources to the self processes of African
American youth. J Appl Dev Sci 2003;7:181–8. https://doi.org/10.1207/
S1532480XADS0703_9.
[14] Kupchik A, Ward G. Race, poverty, and exclusionary school security: an empir-
ical analysis of US elementary, middle, and high schools. Youth Violence Juv
Justice 2013;12:332–54. https://doi.org/10.1177/1541204013503890.
[15] Mowen TJ, Parker KF. Minority threat and school security: assessing the
impact of Black and Hispanic student representation on school security meas-
ures. Secur J 2017;30:504–22. https://doi.org/10.1057/sj.2014.42.
[16] Tillyer MS, Fisher BS, Wilcox P. The effects of school crime prevention on stu-
dents’violent victimization, risk perception, and fear of crime: a multilevel
opportunity perspective. Justice Q 2011;28:249–77. https://doi.org/10.1080/
07418825.2010.493526.
[17] Perumean-Chaney SE, Sutton LM. Students and perceived school safety: the
impact of school security measures. Am J Crim Justice 2013;38:570–88.
https://doi.org/10.1007/s12103-012-9182-2.
[18] Bosworth K, Ford L, Hernandez D. School climate factors contributing to stu-
dent and faculty perceptions of safety in select Arizona schools. J Sch Health
2011;81. https://doi.org/10.1111/j.1746-1561.2010.00579.x, 2011.
[19] Brown B. Controlling crime and delinquency in the schools: an exploratory
study of student perceptions of school security measures. J Sch Violence
2006;4:105–25. https://doi.org/10.1300/J202v04n04_07.
[20] Booren LM, Handy DJ, Power TG. Examining perceptions of school safety strat-
egies, school climate, and violence. Youth Violence Juv Justice 2011;9:171–87.
https://doi.org/10.1177/1541204010374297.
[21] Theriot MT. School resource officers and the criminalization of student behavior. J
Crim Justice 2009;37:280–7. https://doi.org/10.1016/j.jcrimjus.2009.04.008.
[22] Bottiani JH, Bradshaw CP, Mendelson T. Inequality in black and white high
school students’perceptions of school support: an examination of race in con-
text. J Youth Adolesc 2016;45:1176–91. https://doi.org/10.1007/s10964-015-
0411-0.
[23] Voight A, Hanson T, O’Malley M, Adekanye L. The racial school climate gap:
within-school disparities in students’experiences of safety, support, and con-
nectedness. Am J Community Psychol 2015;56:252–67. https://doi.org/
10.1007/s10464-015-9751-x.
[24] Bachman R, Randolph A, Brown BL. Predicting perceptions of fear at school
and going to and from school for African American and white students: the
effects of school security measures. Youth Soc 2011;43:705–26. https://doi.
org/10.1177/0044118X10366674.
[25] Cornell D. Our schools are safe: challenging the misperception that schools are
dangerous places. Am J Orthopsychiatry 2015;85:217–20. https://doi.org/
10.1037/ort0000064.
[26] Dankwa-Mullan I, Rhee KB, Williams K, et al. The science of eliminating health
disparities: summary and analysis of the NIH summit recommendations. Am J
Public Health 2010;100:12–8. https://doi.org/10.2105/AJPH.2010.191619.
[27] Bradshaw CP, Waasdorp TE, Debnam KJ, Lindstrom Johnson S. Measuring
school climate in high schools: a focus on safety, engagement, and the envi-
ronment. J Sch Health 2014;84:593–604. https://doi.org/10.1111/josh.12186.
[28] Bradshaw CP, Milam AJ, Furr-Holden CDM, Lindstrom Johnson S. The school
assessment for environmental typology (SAfETy): an observational measure
of the school environment. Am J Commun Psychol 2015;56:280–92. https://
doi.org/10.1007/s10464-015-9743-x.
[29] U.S. Department of Education. Safe and supportive schools model. https://
safesupportivelearning.ed.gov/
[30] Ross CE, Mirowsky J. Neighborhood disadvantage, disorder, and health. J
Health Soc Behav 2001;42:258–76.
[31] United States Census Bureau. American community survey 5-year estimates:
2005-2009. https://factfinder.census.gov/faces/tableservices/jsf/pages/pro-
ductview.xhtml?src=bkmk.
[32] Raudenbush SW, Bryk AS, Congdon R. HLM 5 for Windows. Scientific Software
International, Inc.
[33] Raudenbush SW, Spybrook J, Congdon R, et al. Optimal design software for
multi-level and longitudinal research; 2011. www.wtgrantfoundation.org.
[34] Battaglia MP, Izrael D, Hoaglin DC, Frankel MR. Tips and tricks for raking sur-
vey data (a.k.a. Sample Balancing). 2004 https://www.researchgate.net/pro-
file/Michael_Battaglia/publication/228976550_Tips_and_Tricks_for_Raking_-
Survey_Data_aka_Sample_Balancing/links/09e4150b740d7d9ece000000/
Tips-and-Tricks-for-Raking-Survey-Data-aka-Sample-Balancing.pdf.
[35] Bracy NL. Circumventing the law: student’s rights in schools with police. J Con-
temp Crim Justice 2010;26:294–315. https://doi.org/10.1177/1043986210368645.
[36] Maskaly J, Donner CM, Lanterman J, Jenn ings WG. On the associa tion
between SROs, private security guards, use-of-force capabilities, and vio-
lent crime in schools. J Police Crisis Negot 2011;11:159–76. https://doi.
org/10.1080/15332586.2011.587381.
[37] Ruck MD, Wortley S. Racial and ethnic minority high school students’percep-
tions of school disciplinary practices: a look at some canadian findings. J Youth
Adolesc 2002;31:185–95. https://doi.org/10.1023/A:1015081102189.
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