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Publications and Research John Jay College of Criminal Justice

2019

Private Security and CCTV Surveillance: A Systematic Review of Private Security and CCTV Surveillance: A Systematic Review of

Function and Performance Function and Performance

Brandon C. Welsh Northeastern University

Eric L. Piza CUNY John Jay College

Amanda L. Thomas

David P. Farrington Cambridge University

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Private Security and CCTV Surveillance: A Systematic Review of Function and

Performance

Brandon C. Welsh, a Eric L. Piza, b Amanda L. Thomas, b and David P. Farrington c

a Northeastern University, Boston, MA, USA

b John Jay College of Criminal Justice, New York, NY, USA

c Cambridge University, Cambridge, UK

Abstract

Private security personnel play an important but largely overlooked role in the operation of

CCTV surveillance to prevent crime in public and private areas. This role can take a number of

forms, including active monitoring of cameras. Drawing upon a global database of CCTV

evaluations (N=165), this article examines the function and performance of private security

personnel as related to the effectiveness of CCTV. Findings indicate that CCTV schemes

operated by private security personnel generated larger crime prevention effects than those

operated by police or those using a mix of police and security personnel. Policy and research

implications are discussed.

Keywords: private security; CCTV; surveillance; crime prevention; systematic review

Citation:

Welsh, B., Piza, E., Thomas, A. and Farrington, D. (2020). Private Security and CCTV

Surveillance: A Systematic Review of Function and Performance. Journal of Contemporary

Criminal Justice, 36(1): 56-69. https://doi.org/10.1177/1043986219890192

Introduction

Closed-circuit television (CCTV) surveillance cameras occupy a central role in contemporary

policing and crime prevention (Goold, 2004; Welsh and Farrington, 2009; Weisburd and

Majmundar, 2018). As the practical application of CCTV has increased in recent years, so has

the evidence-base on its crime prevention effect in public and private space. The cumulative

evidence demonstrates that CCTV surveillance is associated with a significant yet modest

reduction in crime. However, effects vary across a range of contextual factors, including

geographical setting (e.g., city and town centers, car parks), crime type, camera monitoring

strategy, use of complementary interventions, and country of origin (Piza et al., 2019).

Private security personnel play an important but largely overlooked role in the operation

of CCTV surveillance to prevent crime in public and private areas. This role can take a number

of forms, including on-site active monitoring of cameras and on-the-ground responses to crimes

in progress captured on cameras (e.g., Gill and Spriggs, 2005; Waszkiewcz, 2013).

In general, research on private security personnel in the context of CCTV surveillance

has focused on the operations of those who monitor the cameras, sometimes known as the

“watchers,” as well as on security guards working alongside or as a complementary intervention

to CCTV. Research on both fronts is rather limited, and neither has attempted to investigate the

relative effectiveness of CCTV systems monitored by private security personnel or police. In the

case of the latter research focus, this is distinguished from security personnel (i.e., security

guards) serving as the primary intervention to prevent crime (see Welsh et al., 2010), and is

really a matter of security guards exercising a formal surveillance function (Cornish and Clarke,

2003) and serving as a secondary or additional intervention to CCTV cameras. Unfortunately,

too few examples of this preclude an analysis of security guards as a moderating variable of the

effects of CCTV on crime (Piza et al., 2019). With respect to the other area, some qualitative

research has examined the day-to-day operations of those who monitor the cameras, with some

distinction among the different parties involved: private security, police, local government staff,

or volunteers (Gill and Spriggs, 2005; Wilson, 2005).

The main aim of this article is to examine the function and performance of private

security personnel as related to the effectiveness of CCTV surveillance. The chief question of

interest is: How effective is CCTV surveillance in preventing crime when it is operated by

security personnel compared to other parties? Using systematic review methods and

incorporating meta-analytic techniques, the article draws upon a recently updated database of

CCTV evaluations (N=165), covering 40 years of research (1978-2018) and drawn from the

United States, United Kingdom, Sweden, Canada, South Korea, and other industrialized

countries.

Methods

The primary list of studies was compiled by Piza et al. (2019) as part of their updated systematic

review and meta-analysis of the effects of CCTV on crime. Studies were identified and located

following a comprehensive set of search strategies, and studies were included in the systematic

review if they met the following criteria: (a) CCTV was the main focus of the intervention; (b)

the evaluation used an outcome measure of crime; (c) the research design involved, at minimum,

before-and-after measures of crime in treatment and comparable control areas; and (d) both the

treatment and control areas experienced at least 20 crimes during the pre-intervention period.

Building upon the prior systematic review conducted by Welsh and Farrington (2009), Piza et al.

(2019) amassed a database of 161 CCTV studies (80 included and 81 excluded). In line with the

scope of the present review, four additional studies were eligible for consideration, bringing the

total number of CCTV studies to 165 (84 included and 81 excluded; see Appendix 1 for all

included studies). Of the 84 included studies, 76 could be used in the meta-analysis. Four did not

provide the requisite data for an effect size to be calculated. The other four did not provide

enough detailed information about the nature of the CCTV operation to allow for coding of the

scheme operation variable (i.e., police, mixed-police, or security).

“Scheme operation” is the primary variable of interest in the present review. We

reviewed each study to determine the personnel primarily in charge of carrying out surveillance

functions and notifying the appropriate parties when an offense was observed on camera. CCTV

schemes that exclusively incorporated sworn police officers in the surveillance function were

coded as “police.” Thirty-seven studies fit this criterion. Twelve studies reported on schemes

incorporating both police officers and civilian security personnel in the surveillance operation.

These evaluations were coded as “mixed-police.” Twenty-seven studies reported that civilian

security personnel were solely involved in surveillance functions, and were coded as “security.”

Given the scope of this review, we pay particular attention to the effect of security schemes as

compared to that of the police and mixed-police schemes. Authors of the primary studies were

contacted via email when a determination could not be made from the study text.

It should be noted that we were unable to distinguish the nature of civilian security

personnel used in the CCTV schemes beyond our typology: security, police, and mixed-police.

This was owing to a general lack of detail reported in the studies. The majority of studies

reported the use of police and/or civilian operators without discussing a number of related

processes, such as the nature of operator training, the policies guiding monitoring practices, and

whether civilian security personnel were in-house or contracted. From the available information

there seems to be a high level of variance across civilian security operators. For example, the

civilian security operators working alongside police officers in Newark were hired, trained, and

supervised directly by the Newark Police Department. The Burnley CCTV scheme used retired

British Legion personnel hired directly by the local authority who monitored cameras from a

separate facility, with the police having no authority over the CCTV operators (see Appendix 1).

Meta-analytic techniques were used to compare the effect of CCTV across the three

scheme operations (police, mixed-police, and security). The odds ratio (OR) is used as the

measure of effect size. The OR indicates the proportional change in crime in the control area

compared with the treatment area. An OR greater than 1.0 indicates a desirable effect of the

intervention, and an OR less than 1.0 indicates an undesirable effect. The inverse of the OR

communicates the crime difference within the treatment area, with a value of 1.25, for example,

indicating that crime decreased by 20% (1/1.25 = 0.8) in the treatment area compared to the

control area.

Analyses were conducted using BioStat’s Comprehensive Meta-Analysis software

(version 3.0). We conducted all analyses as random effects models under the assumption that

effect sizes are heterogeneous across individual evaluations as well as sub-populations of

evaluations (Lipsey and Wilson, 2001). In each case, observed Q statistics and associated p

values supported this assumption, demonstrating significantly heterogeneous effect sizes across

categories of our “scheme operation” variable. Also, to account for the potential influence of

outcome measures on observed effect sizes, we followed the analytic approach of recent

systematic reviews of using three approaches to report meta-analytic results (e.g., Braga et al.,

2018). In the first approach, all reported outcomes are summed to present an overall average

effect size statistic. This is a conservative measure of the effect of each type of CCTV scheme

operation. In the second approach, the largest reported effect size for each study is used, which

presents a “best-case” estimate. In the third approach, the smallest reported effect size for each

study is used, representing the lower bound estimate of effect.

Finally, we conducted meta-regression models to further explore how effects differ across

the scheme operation categories. When combined with traditional meta-analysis methods, meta-

regression provides the benefit of controlling for moderator variables that researchers believe

may partially explain observed effect sizes. The scheme operation covariate is the independent

variable of primary interest in the present review. “Police” was set as the reference category,

generating covariates that measure whether the mixed-police and security schemes outperform

police-led schemes. Five additional variables were included as control variables, because Piza et

al. (2019) found each of them to be significantly related to CCTV effects on crime. Two binary

variables identify whether the CCTV scheme was deployed in a car park or a residential setting.

A binary variable identifies whether the study was conducted in the United Kingdom. The two

final covariates are binary measures identifying whether the scheme incorporated active

monitoring of surveillance cameras and whether multiple complementary interventions were

deployed alongside CCTV. Similar to the meta-analyses, all meta-regressions were conducted as

random effects models to account for the heterogeneity not explained by the covariates

(Thompson and Higgins, 2002).

Results

All three scheme operations exhibited statistically significant crime reducing effects. However,

the operations differed in terms of the proportion of evaluations reporting desirable effects as

well as the magnitude of the pooled effects. For the 37 police-led schemes, eight reported

desirable effects, one reported undesirable effects, and 28 reported non-significant effects (see

Figure 1).

Figure 1: Forest plot of police schemes (average effects)

For the 12 mixed-police schemes, three reported desirable effects while the remaining

nine reported non-significant effects (see Figure 2). Eleven of the 27 security schemes reported

desirable effects, a higher proportion (40.7%) than what was observed for both the police

(21.6%) and mixed-police (25.0%) schemes. Two of the security schemes reported undesirable

effects and 14 reported null effects (see Figure 3).

Figure 2: Forest plot of mixed-police schemes (average effects)

Figure 3: Forest plot of security schemes (average effects)

Table 1 displays the findings of the meta-analysis comparing the pooled effect sizes

across scheme operations. In the average-effects meta-analysis (see Table 1a) security schemes

exhibited the largest effect (OR=1.225), indicating a crime reduction of approximately 18% in

treatment compared to control areas. Pooled effect sizes for mixed-police (OR=1.164) and police

(OR=1.081) indicated crime reductions of approximately 14% and 7%, respectively. ORs

achieved statistical significance (p<0.05) for each of the scheme operations. Security schemes

once again demonstrated the strongest effects in the largest-effects meta-analysis (OR=1.208; see

Table 1b), indicating an approximately 17% reduction of crime in treatment compared to control

areas. However, the effect of police schemes was nearly identical (OR=1.206) when the

outcomes exhibiting the largest effects are considered. The mixed-police schemes exhibited the

smallest effect (OR=1.186), which was not substantially smaller than either the security or police

schemes, with a reduction of about 16% in treatment compared to control areas. As with the

average-effects models, all ORs achieved statistical significance (p<0.05) for each of the scheme

operations in the largest-effects meta-analysis. The smallest-effects meta-analysis again indicated

security schemes as having the largest effect size (OR=1.136), followed by mixed police

(OR=1.100) and police (OR=1.026).

Table 1: Effect on crime by scheme operation

(a) Average Effects

95% Confidence Interval

Category N Odds Ratio Lower Upper p

Police 37 1.081 1.007 1.160 0.031

Mixed-Police 12 1.164 1.314 2.450 0.014

Security 27 1.225 1.059 1.419 0.006

Q=24.898, df=2, p<0.001

(b) Largest Effects

95% Confidence Interval

Category N Odds Ratio Lower Upper p

Police 37 1.206 1.097 1.326 <0.001

Mixed-Police 12 1.186 1.022 1.378 0.025

Security 27 1.208 1.072 1.361 0.002

Q=7.219, df=2, p=0.027

(c) Smallest Effects

95% Confidence Interval

Category N Odds Ratio Lower Upper p

Police 37 1.026 0.955 1.103 0.483

Mixed-Police 12 1.100 0.943 1.283 0.226

Security 27 1.136 0.973 1.327 0.107

Q=14.087, df=2, p=0.001

Table 2 displays the meta-regression results. The independent variables of primary

interest are mixed-police and security, which measure the crime prevention effect of these

scheme types compared to police schemes. These variables achieved statistical significance in

only the largest-effects meta-regression model. In this model, both security schemes and mixed-

police schemes were positively related to effect size. However, the coefficient for security

schemes (0.363) was more than twice as large as the coefficient for mixed-police schemes

(0.136). These variables were non-significant in both the average-effects and smallest-effects

meta-regression models. However, we should note that the use of multiple complementary

interventions alongside CCTV was significantly related to larger effect sizes in both the average-

effects and smallest-effects regression models. This suggests that implementing multiple

interventions alongside CCTV perhaps should be the primary consideration for practitioners and

policymakers. This has important implications for security-led CCTV schemes and is discussed

in the next section.

Table 2: Meta-regression in predicting crime

95% Confidence Interval

Covariate Coefficient S.E. Lower Upper p

(a) Average Effects

Mixed-Police1 0.056 0.095 -0.131 0.243 0.557

Security1 0.046 0.085 -0.121 0.213 0.592

Car Park 0.265 0.146 -0.021 0.550 0.069

Residential 0.057 0.084 -0.109 0.222 0.501

United Kingdom 0.032 0.080 -0.125 0.190 0.687

Active Monitoring 0.055 0.077 -0.095 0.205 0.473

Multiple Interventions 0.198 0.100 0.001 0.394 0.049*

(a) Largest Effects

Mixed-Police1 0.136 0.112 -0.090 0.3618 0.238

Security1 0.363 0.124 0.121 0.606 0.003*

Car Park -0.338 0.208 -0.746 0.070 0.104

Residential -0.069 0.096 -0.256 0.119 0.474

United Kingdom -0.424 0.125 -0.669 -0.180 0.001*

Active Monitoring 0.127 0.096 -0.060 0.315 0.183

Multiple Interventions -0.046 0.081 -0.204 0.112 0.567

(a) Smallest Effects

Mixed-Police1 0.057 0.099 -0.137 0.250 0.565

Security1 0.003 0.088 -0.170 0.176 0.975

Car Park 0.371 0.158 0.061 0.681 0.020

Residential 0.052 0.085 -0.114 0.217 0.540

United Kingdom 0.086 0.083 -0.077 0.249 0.302

Active Monitoring -0.016 0.077 -0.168 0.135 0.832

Multiple Interventions 0.213 0.105 0.008 0.419 0.042* Notes: Log odds ratio is the dependent variable for each model. Each regression ran as a random effects model.

1“Police” used as the reference category.

*p.<0.05

The analysis concludes with a test of potential publication bias of the meta-analysis

results. We used BioStat’s trim-and-fill procedure to estimate how reported effects would change

if bias was discovered and addressed (Duval, 2005). This is based on the assumption that effect

sizes should show symmetry around the mean when a representative collection of studies has

been obtained. When there is asymmetry, the trim-and-fill procedure inputs the hypothesized

missing studies and re-computes a mean effect size. The analysis showed that asymmetry is

present (results not shown), and that nine studies should be added to create symmetry. When the

effect size is re-computed to include these additional studies, the mean effect size increased from

1.140 to 1.187. However, the 95% confidence intervals of the observed and adjusted ORs

overlap, suggesting that the effect sizes are not significantly different. The smallest- and largest-

effect versions of the trim-and-fill procedure similarly produced estimates with overlapping

confidence intervals (results not shown). From the results of these tests, we can conclude that

publication bias did not influence the meta-analysis results.

Discussion and Conclusions

This review’s findings reflect positively on CCTV schemes operated by security personnel. In

each of the meta-analyses, security-led CCTV schemes exhibited the largest reduction in crime.

The differences in OR effect sizes were particularly magnified in the average-effects meta-

analysis. In this model, security schemes generated crime reductions of approximately 18%

compared to approximately 16% for mixed-police schemes and approximately 7% for police

schemes.

It is important to note that the effect of security-led CCTV schemes was less magnified in

the meta-regression, which controlled for key factors related to the effects of CCTV on crime.

Security schemes and mixed-police schemes were significantly more effective than police

schemes in only the largest-effects meta-regression model. On the one hand, this suggests that

these schemes may be preferable to police schemes when the maximum potential effect is

achievable. On the other hand, some may give more emphasis to the average-effects and

smallest-effects meta-regression models given that they represent more conservative estimates.

In both of these models, the use of multiple complementary interventions alongside

CCTV was significantly related (car parks also related, especially in smallest) to the CCTV

effect. We feel that this finding tangentially supports the increased use of security personnel in

CCTV operations.

Using security personnel in the CCTV monitoring function may help to achieve the

“force multiplier” effect that policymakers have long sought from video surveillance cameras

(Norris, 2003). Traditionally, policymakers have considered video surveillance cameras a force

multiplier because they provide more “eyes on the street,” which theoretically increases police

presence. However, research has shown that standard CCTV operations detect rather low levels

of criminal activity (Piza et al., 2014), which calls into question CCTV’s role as a proactive

place-based strategy for increasing guardianship (Weisburd and Majmundar, 2018). In this

context, the presence of CCTV alone does not seem to do much to deliver the force multiplier

effect that policymakers envision.

Conversely, having security personnel monitoring CCTV cameras may free up police

officers to conduct proactive operations in support of surveillance functions, which would serve

as a much stronger force multiplier than the conspicuous presence of CCTV cameras alone. In

recognition of prior research analyzing the effect of integrating proactive policing units within

CCTV operations (La Vigne et al., 2011; Piza et al., 2015), such a strategy would likely

strengthen CCTV’s overall crime prevention effect.

This review has two limitations. One has to do with missing information in the included

studies, resulting in eight studies that could not be included in the meta-analysis. We can take

some comfort that only four of these eight studies were missing information about the scheme

operation variable. This bears directly on poor descriptive validity in the reporting of primary

studies, something that confronts other systematic reviews. A second limitation concerns the lack

of details in some studies about the main roles that security personnel and police play in the

deployment of CCTV surveillance and in what capacities security personnel interact with the

other parties. Process evaluations could furnish some of this valuable information, and they

should be carried out in concert with outcome evaluations.

The findings of this systematic review should provide policymakers with the beginning of

an evidence base in considering security-led CCTV schemes as a viable option in deploying

CCTV to prevent crime. Until now, little research has been available to help guide decision-

making on the use of security personnel, police, or some combination of these two parties in the

monitoring of surveillance cameras. Additional factors should also be considered, including

financial costs, intervention context, and police-community relations.

There is also a need to better understand why security-led CCTV schemes are more

effective in reducing crime. Is it the specialized training of security personnel? Is there

something to do with the targeted duties assigned to security personnel? Does it have to do with

the role of operating procedures and overall governance for security personnel? Unfortunately,

these questions could not be investigated as part of this review. However, we feel there are

opportunities for future research to rigorously explore these issues through randomized

experiments. For example, Piza et al. (2015) randomly assigned an additional CCTV operator

and proactive directed patrol units across preexisting CCTV sites. In a similar fashion, we feel

that existing CCTV sites can be randomly assigned experimental factors related to operator

functions. Such experiments can involve random assignment of procedural aspects (e.g., training,

monitoring policies, hiring in-house vs. outside security operators) of the operator function to

better isolate the effect such factors have on the crime prevention effect of CCTV. Furthermore,

there is a real need for qualitative research to explore the day-to-day operations and behind-the-

scenes activities that guide security personnel working in CCTV projects. Importantly, the

findings of qualitative studies need to be integrated with evaluation research findings. We think

this is long overdue and much needed to guide policy and practice on the use of CCTV

surveillance.

Acknowledgments

We wish to thank the co-editors of this special issue and the anonymous reviewers for insightful

comments.

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