Skip to main content
Log in

The effects of merging proactive CCTV monitoring with directed police patrol: a randomized controlled trial

  • Published:
Journal of Experimental Criminology Aims and scope Submit manuscript

Abstract

Objectives

This study was designed to test the effect of increased certainty of punishment on reported crime levels in CCTV target areas of Newark, NJ. The experimental strategy was designed for the purpose of overcoming specific surveillance barriers that minimize the effectiveness of CCTV, namely high camera-to-operator ratios and the differential response policy of police dispatch. An additional camera operator was deployed to monitor specific CCTV cameras, with two patrol cars dedicated to exclusively responding to incidents of concern detected on the experimental cameras.

Methods

A randomized controlled trial was implemented in the analysis. A randomized block design was used to assign each of the 38 CCTV schemes to either a treatment or control group. Schemes were grouped into pairs based upon their levels of three types of calls for service: violent crime, social disorder, and narcotics activity. Negative binomial regression models tested the effect that assignment to the treatment group had on levels of the aforementioned crime categories.

Results

The experimental strategy was associated with significant reductions of violent crime and social disorder in the treatment areas relative to the control areas. Incidence Rate Ratio (IRR) and Total Net Effect (TNE) values suggest that the number of crime incidents prevented was sizable in numerous instances. The experiment had much less of an effect on narcotics activity.

Conclusions

Overall, the findings support the hypothesis that the integration of CCTV with proactive police activity generates a crime control benefit greater than what research suggests is achievable via “stand-alone” camera deployment, particularly in the case of street-level crime.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. We recognize the debate regarding researcher involvement in the design and implementation of interventions. Some scholars have argued that close working relationships between practitioners and academics may create a conflict of interest, which can threaten the validity of the analysis (Eisner 2009). Others have argued that such collaboration is necessary in order to develop, test, and disseminate evidence-based practices (Braga 2010; Olds 2009). While the debate is ongoing, a meta-analysis of experimental and quasi-experimental evaluations of police interventions by Welsh et al. (2012) found no evidence that evaluator involvement in program implementation biased the results. Furthermore, the recent study of Telep et al. (2012) focused on a field experiment carried out primarily by the Sacramento Police Department, adding further support for researcher/practitioner relationships.

  2. This grid is the standard deviation ellipse discussed below.

  3. See Piza et al. (2014a) and Piza (2012) for more detailed descriptions of viewshed and catchment zone creation.

  4. The ellipse was extended slightly to the northeast so that it encompassed the catchment zones of each scheme.

  5. The CONSORT Checklist was also used for this report. The checklist provides 25 items that must be included in a Randomized Controlled Trial report to comply with CONSORT standards. We referenced the checklist to ensure that each of the applicable items was presented within this report (see: http://www.consort-statement.org/consort-2010).

  6. Violent crime included the following incident types: assault, carjacking, fight, robbery, shooting (including shots fired), stabbing, and weapons possession. Social disorder included the following incident types: disorderly persons, drinking in public, noise complaint, obstruction of public passage, panhandling, prostitution, and urinating in public. Narcotics activity included the following incident types: Drug activity reported via the anonymous tip line, street-level drug activity, and unverified drug activity (meaning the complainant did not directly witness the drug transaction, but has ample reason to believe a drug transaction occurred).

  7. Calls-for-service may provide advantages over Part 1 crime data since they are less influenced by police discretion (Braga, et al. 1999; Warner and Pierce 1993). However, a potential shortcoming of calls data is they are subject to over reporting due to multiple citizens calling about the same incident (Klinger and Bridges 1997). To protect against this, we deleted duplicate calls-for-service (identified by their police-assigned event numbers) prior to our analysis.

  8. The standard deviation ellipse, rather than the entirety of Newark, was considered the control area in the LQ formula. Therefore, the crime count and square footage of the ellipse were used as X and T, respectively, in the denominator of the LQ formula.

  9. As will be discussed later in the text, experiment effect on crime was measured across three different time periods. Additional t tests conducted for each of these time periods further demonstrated balance between treatment and control areas, with test statistics not achieving significance in a single instance. Due to limited space, the t tests results are not presented in text, but are available from the lead author upon request.

  10. X 2 goodness-of-fits tests conducted after exploratory Poisson regression models confirmed that each crime type was distributed as a negative binomial process. For the “Tours” models: Violence, Pearson X 2 = 57.05, p = 0.01; Disorder, Pearson X 2 = 65.18, p = 0.001; Narcotics, Pearson X 2 = 56.06, p = 0.01. For the “Days” models: Violence, Pearson X 2 = 62.75, p = 0.002; Disorder, Pearson X 2 = 92.98, p = 0.000; Narcotics, Pearson X 2 = 67.39, p = 0.001. For the “11-Week” models: Violence, Pearson X 2 = 63.89, p = 0.001; Disorder, Pearson X 2 = 133.19, p = 0.000; Narcotics, Pearson X 2 = 106.10, p = 0.000. For all tests df = 34.

  11. We recognize that another option was to conduct a multi-level analysis treating the number of events in the pretest period as a random effect across the 19 pairs of schemes. However, due the small size of the level one sample (pairs of schemes) and the fact that a single measurement was made during the “pre” and “post” periods, we concluded that a multi-level model was inappropriate for this data (Snijders 2005). This decision aligns with prior place-based policing experiments (see Braga and Bond 2008: p. 589, footnote 10).

  12. Separate correlation matrices were created for the main and residual models, which are discussed below. Given limited space, the correlation matrices are not presented in text, but are available from the lead author upon request.

  13. It should be noted that, since these events were not reported via CAD, the operator activity was not captured within the calls-for-service counts. Thus, the analysis of outcome measures was not influenced by operator activity.

  14. Record checks refer to incidents where police officers detain a suspect at the scene and contact the communications division via radio to ascertain whether the individual has any open warrants, or is otherwise wanted for a crime. Field interrogations refer to instances where police officers detain a suspect at the scene and question them regarding the incident observed by the CCTV operator. In most cases, record checks and field interrogations were conducted in unison, so we report them both together as “other enforcement”. In the event an arrest occurred as a result of a record check or field interrogation, the incident was counted as an arrest. Therefore, the enforcement categories are mutually exclusive.

  15. While each of these 64 enforcement actions occurred within the treatment area, there were two incidents (which are not reflected in these figures) where patrol officers enacted a proactive enforcement action outside of the treatment area. In one instance, a patrol unit was flagged down by a pedestrian who reported that he had just been robbed at gunpoint. The officers thus pursued and apprehended the suspect. In the other instance, officers observed what they believed to be a hand-to-hand narcotics transaction between two males in front of a house. After detaining the suspects, the officers found both individuals to be in possession of narcotics and placed both of them under arrest. It is important to note that these two incidents had no bearing on the evaluation since both arrests occurred outside of both the treatment and control schemes.

  16. As explained by Lipsey (1990), in statistical power calculations “[s]ample size refers to the number of subjects in each group—for example, ten treatment subjects compared with ten control subjects is represented as a sample size of 10” (p. 71: emphasis in original text).

  17. Increasing sample size is typically considered as the most straightforward way to increase statistical power. However, as noted by Weisburd et al. (1993), increasing sample size may negatively affect field experiments by creating a treatment group too large for each case to receive proper dosage. Indeed, Buerger (1993) reported that such an instance occurred in the Minneapolis RECAP experiment (Sherman et al. 1989). We, therefore, decided to not increase our sample size at the outset of the experiment in order to protect against spreading the treatment too thinly across the treatment area.

  18. It is common practice for a pre-intervention power analysis, identifying the necessary sample size to achieve statistical power, to guide the scope of experimental studies. Unfortunately, the changing fiscal situation of the Newark Police Department reduced the anticipated scope of the experiment. The grant funding this experiment provided funds for officers to work the experiment over 20 separate 4-h tours of duty. The Newark Police Department originally agreed to dedicate additional resources towards the experiment so that more tours-of-duty could be implemented. Unfortunately, prior to the start of the experiment extreme budget cuts led to the termination of 167 police officers in Newark (Star Ledger 2010). This led the newly appointed police leadership to determine that the Department could no longer afford to dedicate additional resources towards the experiment.

  19. Crime in both the treatment and catchment zones experienced a reduction (from 80 to 38 incidents and from 87 to 77 incidents, respectively) during the “residual days” period. However, the control area also experienced a sizable decline (from 42 to 28 incidents), which led to the negative WDQ.

References

  • Ariel, B., & Farrington, D. (2010). Randomized block designs. In A. Piquero & D. Weisburd (Eds.), Handbook of quantitative criminology. New York: Springer.

    Google Scholar 

  • Armitage, R., Smythe, G., & Pease, K. (1999). Burnley CCTV evaluation. In N. Tilley & K. Painter (Eds.), Surveillance of public space: CCTV, street lighting and crime prevention (Crime Prevention Studies, Vol. 10, pp. 225–249). Monsey: Criminal Justice Press.

    Google Scholar 

  • Barr, R., & Pease, K. (1990). Crime placement, displacement and deflection. In M. Tonry & N. Morris (Eds.), Crime and justice: a review of research (Vol. 12, pp. 277–218). Chicago: University of Chicago Press.

    Google Scholar 

  • Belkap, J. (1992). Empirical estimates of Bonferroni corrections for use in chromosome mapping studies with the BXD recombinant inbred strains. Behavior Genetics, 22(6), 677–684.

    Article  Google Scholar 

  • Bowers, K., & Johnson, S. (2003). Measuring the geographical displacement and diffusion of benefit effects of crime prevention activity. Journal of Quantitative Criminology, 19, 275–301.

    Article  Google Scholar 

  • Braga, A. (1997). Solving violent crime problems: an evaluation of the Jersey City Police Department’s pilot program to control violent places. Doctoral Dissertation submitted to the Graduate School-Newark, Rutgers, The State University of New Jersey.

  • Braga, A. (2010). Setting a higher standard for the evaluation of problem-oriented policing initiatives. Criminology & Public Policy, 9(1), 173–182.

    Article  Google Scholar 

  • Braga, A., & Bond, B. J. (2008). Policing crime and disorder hot spots: a randomized controlled trial. Criminology, 46(3), 577–607.

    Article  Google Scholar 

  • Braga, A., & Weisburd, D. (2010). Policing problem places: crime hot spots and effective prevention. New York: Oxford University Press.

    Book  Google Scholar 

  • Braga, A., Weisburd, D., Waring, E., Mazerolle, L., Spelman, W., & Gajewski, F. (1999). Problem-oriented policing in violent crime places: a randomized controlled experiment. Criminology, 37(3), 541–580.

    Article  Google Scholar 

  • Braga, A., Papachristos, A., & Hureau, D. (2012). The effects of hot spots policing on crime: an updated systematic review and meta-analysis. Justice Quarterly. Advance online publication. doi: 10.1080/07418825.2012.673632.

  • Brantingham, P.L., & Brantingham, P.J. (1998). Mapping crime for analytic purposes: location quotients, counts and rates. In Weisburd, D., & McEwen, T. (Eds) Crime Mapping and Crime Prevention. Crime Prevention Studies, 8, 263–288.

  • Britt, C., & Weisburd, D. (2010). Statistical power. In P. Alex & D. L. Weisburd (Eds.), Handbook of quantitative criminology. New York: Springer.

    Google Scholar 

  • Brown, B. (1995). CCTV in town centres: three case studies (Crime Detection and Prevention Series, Paper 68). London: Home Office.

    Google Scholar 

  • Buerger, M. (1993). Convincing the recalcitrant: reexamining the Minneapolis RECAP experiment. Doctoral dissertation, Rutgers University.

  • Butler, G. (1994). Shoplifters’ views on security: lessons for crime prevention. In M. Gill (Ed.), Crime at work: studies in security and crime prevention. London: Perpetuity Press.

    Google Scholar 

  • Cameron, A., Kolodinski, E., May, H., & Williams, N. (2008). Measuring the effects of video surveillance on crime in Los Angeles. Report prepared for the California Research Bureau. USC School of Policy, Planning, and Development.

  • Caplan, J., Kennedy, L., & Petrossian, G. (2011). Police-monitored cameras in Newark, NJ: a quasi-experimental test of crime deterrence. Journal of Experimental Criminology, 7(3), 255–274.

    Article  Google Scholar 

  • Clarke, R. (1997). Introduction. In R. Clarke (Ed.), Situational crime prevention, successful case studies (2nd ed.). Monsey: Criminal Justice Press.

    Google Scholar 

  • Clarke, R., & Eck, J. (2005). Crime analysis for problem solvers in 60 small steps. Washington, DC: U.S. Department of Justice Office of Community Oriented Policing Services.

    Google Scholar 

  • Clarke, R., & Weisburd, D. (1994). Diffusion of crime control benefits. In R. Clarke (Ed.), Crime prevention studies (Vol. 2, pp. 165–183). Monsey: Criminal Justice Press.

    Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for behavioral sciences (2nd ed.). Hillsdale: Lawrence Erlbaum.

    Google Scholar 

  • Cornish, D., & Clarke, R. (Eds.). (1986). The reasoning criminal: rational choice perspectives on offending. New York: Springer.

    Google Scholar 

  • Cowan, N. (2000). The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behavioral and Brain Sciences, 42, 87–185.

    Google Scholar 

  • Ditton, J., & Short, E. (1998). Evaluating Scotland’s first town centre CCTV scheme. In C. Norris, J. Moran, & G. Armstrong (Eds.), Surveillance, closed circuit television and social control. Aldershot: Ashgate.

    Google Scholar 

  • Ditton, J., & Short, E. (1999). Yes, it works, no it doesn’t: comparing the effects of open-street CCTV in two adjacent Scottish town centres. In N. Tilley & K. Painter (Eds.), Surveillance of public space: CCTV, street lighting and crime prevention (Crime Prevention Studies, Vol. 10, pp. 201–223). Monsey: Criminal Justice Press.

    Google Scholar 

  • Durlauf, S., & Nagin, D. (2011). Imprisonment and crime: can both be reduced? Criminology and Public Policy, 10(1), 13–54.

    Article  Google Scholar 

  • Eisner, M. (2009). No effects in independent prevention trials: can we reject the cynical view? Journal of Experimental Criminology, 5(2), 163–184.

    Article  Google Scholar 

  • Farrington, D., Gill, M., Waples, S., & Argomaniz, J. (2007). The effects of closed-circuit television on crime: meta-analysis of an English national quasi-experimental multi-site evaluation. Journal of Experimental Criminology, 3, 21–28.

    Article  Google Scholar 

  • Faul, F., Erdfelder, E., Buchner, A., & Lang, A. (2009). Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160.

    Article  Google Scholar 

  • Feise, R. (2002). Do multiple outcome measures require p-value adjustment? BMC Medical Research Methodology, 2, 8–11.

    Article  Google Scholar 

  • Fyfe, N., & Bannister, J. (1996). City watching: closed circuit television surveillance in public spaces. Area, 28(1), 37–46.

    Google Scholar 

  • Gajewski, F. (1994). The drug market analysis program: a participant observation study. Unpublished master’s thesis, Seton Hall University: South Orange, NJ.

  • Garcia, L. (2004). Escaping the Bonferroni iron claw in ecological studies. Oikos, 105(3), 657–663.

    Article  Google Scholar 

  • Gill, M., & Hemming, M. (2004). Evaluation of CCTV in the London borough of Lewisham. Leicester: Perpetuity Research & Consultancy International (PRCI).

    Google Scholar 

  • Gill, M., & Loveday, K. (2003). What do offenders think about CCTV? Crime Prevention and Community Safety: An International Journal, 5(3), 17–25.

    Article  Google Scholar 

  • Gill, M., & Spriggs, A. (2005). Assessing the impact of CCTV (p. 292). London: Home Office Research Study No.

    Google Scholar 

  • Gill, M., & Turbin, V. (1998). CCTV and shop theft: towards a realistic evaluation. In N. Clive, M. Jade, & A. Gary (Eds.), Surveillance, closed circuit television and social control. Aldershot: Ashgate.

    Google Scholar 

  • Gill, M., Spriggs, A., Allen, J., Hemming, M., Jessiman, P., & Kara, D. (2005). Control room operation: findings from control room observations. London: Home Office.

    Google Scholar 

  • Grant, S., Mayo-Wilson, E., Hopewell, S., MacDonald, S., Moher, D., & Montgomery, P. (2013). Developing a reporting guideline for social and psychological intervention trials. Journal of Experimental Criminology, 9(3), 355–367.

    Article  Google Scholar 

  • Guerette, R. (2009). Analyzing crime displacement and diffusion. Problem-oriented guides for police. Problem-solving tools series. No. 10. U.S. Department of Justice Office of Community Oriented Policing Services. Center for Problem-Oriented Policing.

  • Guerette, R., Steinus, V., & McGloin, M. (2005). Understanding offending specialization and versatility: a re-application of the rational choice perspective. Journal of Criminal Justice, 33(1), 77–87.

    Article  Google Scholar 

  • Halford, G., Baker, R., McCredden, J., & Bain, J. (2005). How many variables can humans process? Psychological Science, 16(1), 70–76.

    Article  Google Scholar 

  • Harocopos, A., & Hough, M. (2005). Drug dealing in open air markets (Problem-Oriented Guides for Police. Problem-Specific Guides Series: No. 31). Washington, DC: U.S. Department of Justice. Office of Community Oriented Policing Services.

    Google Scholar 

  • Hipp, J., Bauer, D., Curran, P., & Bollen, K. (2004). Crimes of opportunity or crimes of emotion? Testing two explanation of seasonal change in crime. Social Forces, 82, 1333–1372.

    Article  Google Scholar 

  • Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6, 65–70.

    Google Scholar 

  • Kennedy, D. (2006). Old wine in new bottles: policing and the lessons of pulling levers. In D. Weisburd & B. Anthony (Eds.), Police innovation. Contrasting perspectives. Cambridge: Cambridge University Press.

    Google Scholar 

  • Kennedy, D., & Wong, S. (2009). The high point drug market intervention strategy. Washington, DC: Office of Community Oriented Policing Services, U.S. Department of Justice.

    Google Scholar 

  • Keval, H., & Sasse, M. (2010). “Not the usual suspects”: a study of factors reducing the effectiveness of CCTV. Security Journal, 23(2), 134–154.

    Article  Google Scholar 

  • King, J., Mulligan, D., & Raphael, S. (2008). CITRIS report: the San Francisco community safety camera program. An evaluation of the effectiveness of San Francisco’s community safety cameras. Research in the interest of society. Berkeley: Center for Information Technology Research in the Interest of Society. University of California.

    Google Scholar 

  • Klinger, D., & Bridges, G. (1997). Measurement error in calls-for-service as an indicator of crime. Criminology, 35, 705–726.

    Article  Google Scholar 

  • La Vigne, N., Lowry, S., Markman, J., & Dwyer, A. (2011). Evaluating the use of public surveillance cameras for crime control and prevention. Washington, DC: US Department of Justice, Office of Community Oriented Policing Services. Urban Institute, Justice Policy Center.

    Google Scholar 

  • Law Enforcement Information Technology Standards Council [LEITSC] (2008). Standard functional specifications for law enforcement computer aided dispatch (CAD) systems. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Assistance, and the National Institute of Justice.

  • Lipsey, M. (1990). Design sensitivity. Statistical power for experimental research. Newbury Park: Sage.

    Google Scholar 

  • Lomell, H. (2004). Targeting the unwanted: video surveillance and categorical exclusion in Oslo, Norway. Surveillance & Society, 2, 346–360.

    Google Scholar 

  • Luck, S., & Vogel, E. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279–281.

    Article  Google Scholar 

  • Lum, C., Koper, C., & Telep, C. (2011). The evidence-based policing matrix. Journal of Experimental Criminology, 7(3), 3–26.

    Article  Google Scholar 

  • Mazerolle, L., Hurley, D., & Chamlin, M. (2002). Social behavior in public space: an analysis of behavioral adaptations to CCTV. Security Journal, 15(3), 59–75.

    Article  Google Scholar 

  • McDowall, D., Loftin, C., & Pate, M. (2012). Seasonal cycles in crime, and their vulnerability. Journal of Quantitative Criminology, 28, 389–410.

    Article  Google Scholar 

  • McLean, S., Worden, R., & Kim, M. (2013). Here’s looking at you: an evaluation of public CCTV cameras and their effects on crime and disorder. Criminal Justice Review, 38(3), 303–334.

    Article  Google Scholar 

  • Nagin, D., & Weisburd, D. (2013). Evidence and public policy. The example of evaluation research in policing. Criminology & Public Policy, 12(4), 651–679.

    Article  Google Scholar 

  • Norris, C. (2003). From personal to digital: CCTV, the panopticon, and the technological mediation of suspicion and social control. In L. David (Ed.), Surveillance as social sorting: privacy, risk and digital discrimination. London: Routledge.

    Google Scholar 

  • Norris, C., & Armstrong, G. (1999a). CCTV and the social structuring of surveillance. In T. Nick & P. Kate (Eds.), Surveillance of public space: CCTV, street lighting and crime prevention (Crime Prevention Studies, Vol. 10, pp. 157–178). Monsey: Criminal Justice Press.

    Google Scholar 

  • Norris, C., & Armstrong, G. (1999b). The maximum surveillance society. The rise of CCTV. Berg: Oxford.

    Google Scholar 

  • Norris, C., & McCahill, M. (2006). CCTV: beyond penal modernism? British Journal of Criminology, 46, 97–118.

    Article  Google Scholar 

  • Olds, D. (2009). In support of disciplined passion. Journal of Experimental Criminology, 5(2), 201–214.

    Article  Google Scholar 

  • Olejnik, S., Li, J., Supattathum, S., & Huberty, C. (1997). Multiple testing and statistical power with modified Bonferroni procedures. Journal of Education and Behavioral Statistics, 22, 389–406.

    Article  Google Scholar 

  • Pease, K. (1999). A review of street lighting evaluations: crime reduction effects. In N. Tilley & K. Painter (Eds.), Surveillance of public space: CCTV, street lighting and crime prevention. Crime prevention studies (Vol. 10). Monsey: Criminal Justice Press.

    Google Scholar 

  • Perneger, T. (1998). What’s wrong with Bonferroni adjustments? British Medical Journal, 316(7139), 1236–1238.

    Article  Google Scholar 

  • Perneger, T. (1999). Multiple testing. British Medical Journal, 322, 226–231.

    Google Scholar 

  • Piza, E. (2012). Identifying the ideal context for CCTV camera placement: an analysis of micro-level features. Doctoral Dissertation submitted to the Graduate School-Newark, Rutgers, The State University of New Jersey.

  • Piza, E., & O’Hara, B. (2014). Saturation foot-patrol in a high-violence area: a quasi-experimental evaluation. Justice Quarterly, 31(4), 693–718.

    Article  Google Scholar 

  • Piza, E., Caplan, J., & Kennedy, L. (2012). Is the punishment more certain? An analysis of CCTV detections and enforcement. Justice Quarterly. Advance online publication. doi:10.1080/07418825.2012.723034.

  • Piza, E., Caplan, J., & Kennedy, L. (2014a). Analyzing the influence of micro-level factors on CCTV camera effect. Journal of Quantitative Criminology, 30(2), 237–264.

    Article  Google Scholar 

  • Piza, E., Caplan, J., & Kennedy, L. (2014b). CCTV as a tool for early police intervention: preliminary lessons from nine case studies. Security Journal. doi:10.1057/sj.2014.17.

    Google Scholar 

  • Ratcliffe, J. (2006). Video surveillance of public places. Problem-oriented guides for police. Response guide series. Guide No. 4. U.S. Department of Justice Office of Community Oriented Policing Services. Center for Problem-Oriented Policing.

  • Ratcliffe, J., & Breen, C. (2008). Spatial evaluation of police tactics in context (SEPTIC) spreadsheet, version 3 (spring 2010). Downloaded from www.jratcliffe.net.

  • Ratcliffe, J., Taniguchi, T., & Taylor, R. (2009). The crime reduction effects of public CCTV cameras: a multi-method spatial approach. Justice Quarterly, 26(4), 746–770.

    Article  Google Scholar 

  • Ratcliffe, J., Taniguchi, T., Groff, E., & Wood, J. (2011). The Philadelphia foot patrol experiment: a randomized controlled trial of police patrol effectiveness in violent crime hotspots. Criminology, 49(3), 795–831.

    Article  Google Scholar 

  • Reid, A., & Andresen, M. (2014). An evaluation of CCTV in a car park using police and insurance data. Security Journal, 27, 57–79.

    Article  Google Scholar 

  • Sankoh, A., Huque, M., & Dubey, S. (1997). Some comments on frequently used multiple endpoint adjustment methods in clinical trials. Statistics in Medicine, 16(22), 2529–3542.

    Article  Google Scholar 

  • Sarno, C., Hough, M., & Bulos, M. (1999). Developing a picture of CCTV in Southwark Town Centres: final report. London: Criminal Policy Research Unit, South Bank University.

    Google Scholar 

  • Sasse, M. (2010). Not seeing the crime for the cameras? Why it is difficult but essential to monitor the effectiveness of security technologies. Communications of the ACM, 53(2), 22–25.

    Article  Google Scholar 

  • Schulz, K. F., Altman, D. G., & Moher, D. (2010). CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. British Medical Journal, 340, 698–702.

    Article  Google Scholar 

  • Sherman, L. (1990). Police crackdowns: initial and residual deterrence. In M. Tonry & N. Morris (Eds.), Crime and justice: a review of research (Vol. 12, pp. 1–48). Chicago: University of Chicago Press.

    Google Scholar 

  • Sherman, L. (2010). An introduction to experimental criminology. In A. Piquero & D. Weisburd (Eds.), Handbook of quantitative criminology (pp. 399–436). New York: Springer.

    Chapter  Google Scholar 

  • Sherman, L., & Eck, J. (2002). Policing for crime prevention. In L. Sherman, D. Farrington, B. Welsh, & D. MacKenzie (Eds.), Evidence-based crime prevention (pp. 295–329). New York: Routledge.

    Google Scholar 

  • Sherman, L., Buerger, M., & Gartin, P. (1989). Repeat call address policing: the Minneapolis RECAP experiment. Washington, DC: Crime Control Institute.

    Google Scholar 

  • Skogan, W., & Frydl, K. (eds) (2004). Fairness and effectiveness in policing: the evidence. Committee to Review Research on Police Policy and Practices. Committee on Law and Justice, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

  • Smith, S., & Bruce, C. (2008). CrimeStat III user workbook. Washington, DC: The National Institute of Justice.

    Google Scholar 

  • Snijders, T. (2005). Power and sample size in multilevel linear models. In B. Everitt & D. Howell (Eds.), Encyclopedia of statistics in behavioral science (Vol. 3, pp. 1570–1573). Chicester: Wiley.

    Google Scholar 

  • Sorg, E., Haberman, C., Ratcliffe, J., & Groff, E. (2013). Foot patrol in violent crime hot spots: the longitudinal impact of deterrence and posttreatment effects of displacement. Criminology, 51(1), 65–102.

    Article  Google Scholar 

  • Star Ledger, The (2010). Newark finalizes 167 police layoffs after union refuses Booker’s plea to return to negotiating table. Tuesday, November 30th. Retrieved at: http://www.nj.com/news/index.ssf/2010/11/union_head_expects_167_newark.html.

  • Taylor, E. (2010). Evaluating CCTV: why the findings are inconsistent, inconclusive and ultimately irrelevant. Crime Prevention and Community Safety: An International Journal, 12(4), 209–232.

    Article  Google Scholar 

  • Taylor, B., Koper, C., & Woods, D. (2011). A randomized controlled trial of different policing strategies at hot spots of violent crime. Journal of Experimental Criminology, 7(2), 149–181.

    Article  Google Scholar 

  • Telep, C., Mitchell, R., & Weisburd, D. (2012). How much time should the police spend at crime hot spots? Answers from a police agency directed randomized field trial in Sacramento, California. Justice Quarterly. Advance online publication. doi:10.1080/07418825.2012.710645.

    Google Scholar 

  • Tilley, N. (1993). Understanding car parks, crime and CCTV. London: Crime Prevention Unit Series Paper 42 Home Office.

    Google Scholar 

  • Tuttle, B. (2009). How Newark became Newark. Piscataway: Rutgers University Press.

    Google Scholar 

  • U.S. Census Bureau (2010). State and county quick facts. Washington, DC: United States Census Bureau. http://quickfacts.census.gov. Accessed 9 Sept 2013.

  • Uitenbroek, D. (1997). SISA binomial. Southampton. http://www.quantitativeskills.com/sisa/calculations/bonfer.htm. Accessed 5 May 2014.

  • Waples, S., & Gill, M. (2006). The effectiveness of redeployable CCTV. Crime Prevention and Community Safety, 8, 1–16.

    Article  Google Scholar 

  • Warner, B., & Pierce, G. (1993). Reexamining social disorganization theory using calls to the police as a measure of crime. Criminology, 31, 493–518.

    Article  Google Scholar 

  • Weisburd, D. (2008). Place-based policing (Ideas in Policing Series). Washington, DC: Police Foundation.

    Google Scholar 

  • Weisburd, D., & Eck, J. (2004). What can police do to reduce crime, disorder, and fear? Annals of the American Academy of Political and Social Science, 593, 42–65.

    Article  Google Scholar 

  • Weisburd, D., & Gill, C. (2014). Block randomized trials at places: rethinking the limitations of small n experiments. Journal of Quantitative Criminology, 30(1), 97–112.

    Article  Google Scholar 

  • Weisburd, D., & Green, L. (1995). Policing drug hot spots: the Jersey City drug market analysis experiment. Justice Quarterly, 12, 711–736.

    Article  Google Scholar 

  • Weisburd, D., Petrosino, A., & Mason, G. (1993). Design sensitivity in criminal justice experiments. In T. Michael (Ed.), Crime and justice: an annual review of research (Vol. 17). Chicago: University of Chicago Press.

    Google Scholar 

  • Weisburd, D., Wyckoff, L., Ready, J., Eck, J., Hinkle, J., & Gajewski, F. (2006). Does crime just move around the corner? A controlled study of spatial displacement and diffusion of crime control benefits. Criminology, 44(3), 549–592.

    Article  Google Scholar 

  • Welsh, B., & Farrington, D. (2002). Crime prevention effects of closed circuit television: a systematic review. London: Home Office (Research Study No. 25).

    Google Scholar 

  • Welsh, B., & Farrington, D. (2007). Closed-circuit television surveillance and crime prevention: a systematic review. Stockholm: National Council for Crime Prevention.

    Google Scholar 

  • Welsh, B., & Farrington, D. (2009). Public area CCTV and crime prevention: an updated systematic review and meta-analysis. Justice Quarterly, 26(4), 716–745.

    Article  Google Scholar 

  • Welsh, B., Braga, A., & Hollis-Peel, M. (2012). Can “disciplined passion” overcome the cynical view? An empirical inquiry of evaluator influence on police crime prevention program outcomes. Journal of Experimental Criminology, 8(4), 415–431.

    Article  Google Scholar 

  • Wilson, O. W. (1963). Police administration. New York: McGraw-Hill.

    Google Scholar 

  • Wyant, B., Taylor, R., Ratcliffe, J., & Wood, J. (2012). Deterrence, firearm arrests, and subsequent shootings: a micro-level spatio-temporal analysis. Justice Quarterly, 29(4), 524–545.

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the National Institute of Justice, Grant Number 2010-IJ-CX-0026. We are truly indebted to a number of individuals at the Newark Police Department whose support made this project possible, including former Director Garry McCarthy, former Director Samuel DeMaio, former Chief-of-Staff Gus Miniotis, Captain Phil Gonzalez, Lieutenant Joseph Alferi, Lieutenant Brian O’Hara, Lieutenant Angelo Zamora, Sergeant Marvin Carpenter, and Sergeant Catherine Gasavage. We are especially grateful to the CCTV operators, patrol supervisors, and patrol officers who worked on the experiment for diligently carrying out their experimental tasks. We also thank Editor-in-Chief Lorraine Mazerolle, Associate Editor Emma Antrobus, and the anonymous reviewers for their helpful comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eric L. Piza.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOC 217 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Piza, E.L., Caplan, J.M., Kennedy, L.W. et al. The effects of merging proactive CCTV monitoring with directed police patrol: a randomized controlled trial. J Exp Criminol 11, 43–69 (2015). https://doi.org/10.1007/s11292-014-9211-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11292-014-9211-x

Keywords

Navigation