shane johnson

Predicting and Preventing (near) repeat victimisation

Professor Shane D Johnson

UCL Department of Security and Crime Science [email protected]

Overview

•  What do we know about the prevention of repeat victimization and policing hotspots?

•  Enhancing predictions

•  Near repeat reduction strategy example

Repeat Victimisation (RV) Strategies Systematic Review

•  The predictability of patterns of repeat victimisation suggests that “targeting repeat victimization provides a means of allocating crime prevention resources in an efficient and informed manner.” (Grove et al., 2012)

•  Previous reviews have been descriptive or employed vote counting

•  Systematic reviews –  Replicable, transparent review of the evidence –  Meta-analysis reduces Type II statistical error –  Campbell, What Works Centre for Crime Reduction

Grove, L., Farrell, G., Farrington, D.F., and Johnson, S.D. (2012). Preventing Repeat Victimization: A Systematic Review. bra Swedish National Council for Crime Prevention.

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What Works Package Structure

Map of existing Systematic Reviews

Rating and ranking criteria

Guidance on costing interventions and their effects

Searchable database of rated and ranked systematic reviews

12 new mixed method systematic reviews

Design police development programme on evidence appraisal

Primary research

Pilot police development programme on evidence appraisal

Assessing the impact of the WWCCR

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“The proper agenda for the next generation of treatment effectiveness research, for both primary and meta-analytic studies, is investigation into which treatment variants are most effective, the mediating causal processes through which they work, …..”

(Lipsey and Wilson, 1993)

RV Strategies Systematic Review Boolean search terms

•  Key search terms and combinations thereof were used to identify studies within each of >12 databases (e.g. PsychINFO, UK Home Office, Criminal Justice Abstracts) as follows:

(repeat** victim*******) or (multi*** victim*******) or (recidivist victim) or (repeat** burglary) or (repeat** sexual**) or (repeat**racial**) or (poly victim*******) or (repeat** target**) or (prior target**) or (multi*** target**) or (recur**** target**) or (recur**** victim*******) or (multi*** burglary) or (multi*** sexual**) or (multi*** racial**)


Inclusion Criteria

1. Data had to be available for a period before, during or after intervention. 2. A comparison group was required.

3. A focus on repeat victimization on an individual level rather than a hot spot/area basis had to form a significant part of the study.


Repeat Victimisation Strategies Systematic Review


Types of strategies

Residential (19) and commercial burglary (3) •  Target hardening of households •  Property marking •  Neighbourhood or cocoon watch

Sexual victimization prevention (4) •  Education programmes

Domestic violence (1) •  Personal safety plan, some duress alarms and police patrols


Effect sizes - Odds Ratio

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Meta-Analysis

Implementation Success

Do geographically focused policing initiatives reduce but displace crime? A Systematic Review

•  Hotspots policing experiments (e.g. Sherman et al., 1989) suggest that geographically focused police patrols reduce crime.

•  What does the weight of the evidence suggest? (see also Braga et al., 2012)

•  What about crime displacement?

Background

•  Dispositional theories predict displacement

•  Earlier research suggested that crime displacement is rarely total

•  At the other end of the displacement continuum is the possibility of a diffusion of crime control benefits

•  Two (or more) mechanisms for diffusion (Clarke and Weisburd, 1994):

–  Deterrence - a carryover effect; offenders perceive that there is an elevated risk of detection and arrest

–  Discouragement – offenders perceive that the effort exceeds anticipated rewards

•  Incapacitation

•  Easy to assume a homogenous group of motivated offenders

The need for a review

•  Literature Reviews: –  Barr and Pease, 1990; Eck, 1993; and Hesseling, 1994 –  Vote counting not meta-analysis

•  No systematic review of diffusion of benefit (Weisburd et al., 2006) –  Bias in favour of looking for displacement

Bowers, K, Johnson, S.D., Guerette, R.T., Summers, L. and Poynton, S. (2011). Spatial Displacement and Diffusion of Benefits Among Geographically Focused Policing Initiatives: A Meta-Analytical Review. Journal of Experimental Criminology. 7(4), 347-374.

Study inclusion criteria

•  Study must evaluate a focused policing intervention (e.g. hotspot policing/ directed patrol, police crackdown)

•  Quantitative measure of crime pre- and post-intervention (for both the ‘treatment’ ‘catchment’ and ‘control’ areas).

•  Published and grey literature

•  Systematic search of databases and relevant articles, hand searches of journals etc

Boolean Search Term (displac* OR “diffusion of benefit” OR “diffusion of benefits” OR “multiplier

effect” OR “free side benefit” OR “ halo effect” OR “spill over*” OR “free rider effect” OR “bonus effect” OR “spill-over”)

AND (police OR policing OR law enforcement) AND (“hot spot policing” OR ‘hot spots policing” OR crackdown* OR “problem

oriented policing” OR “problem solving” OR “focused policing” OR “targeted policing” OR “directed patrol” OR “enforcement swamping” OR “intelligence led policing” OR “broken windows” OR “compstat” OR “community policing”)

AND (evaluat* OR impact OR assessment OR test)

Hierarchy of Evidence

All effect sizes (N=52, 15 studies)

Odds Ratio

Weighted Mean OR (RDM effects)Allatt1984 (Pre-Dur, Catch 1)Allatt1984 (Pre-Dur, Catch 2)

Allatt1984 (Pre-Post, Catch 1)Allatt1984 (Pre-Post, Catch 2)

Braga 1999 (CFS)Braga 1999 (Crime)Braga&Bond2008

Cummings2006 (Treatment 1)Cummings2006 (Treatment 2)

Esbensen1987 (All Crime)Esbensen1987 (Disorder)

Esbensen1987 (Index Crimes)FarrellEtAl1998 (Pre-During)

FarrellEtAl1998 (Pre-Post)Grogger2002 (No Catchment Ctrl)

Grogger2002 (Catchment Ctrl)Higgins&Coldren2000

MazerollePriceEtAl2000McGarrellEtAl2001

Press1971 (Assault, Inside)Press1971 (Robbery, Inside)

Press1971(Assaults, Outside)Press1971(Auto theft, Inside)

Press1971(Auto Theft, Outside)Press1971(Burglary, Inside)

Press1971(Burglary, Outside)Press1971(G Larceny, Inside)

Press1971(G Larceny, Outside)Press1971(Misdemeanors, Inside)

Press1971(Misdemeanors, Outside)Press1971(Other Felony, Inside)

Press1971(Other Larceny, Outside)Press1971(Other Misdemeanors, Inside)

Press1971(Other Misdemeanors, Outside)Press1971(Robbery, Outside)

Press1971(Total Felonies, Inside)Press1971(Total Larc, Outside)

Press1971(Total Misdemeanors, Inside)Press1971(Total misdemeanors, Outside)

Segrave&Collins2005 (Dis, Catch 1)Segrave&Collins2005 (Dis, Catch 2)Segrave&Collins2005 (Dis, Catch 3)

Segrave&Collins2005 (Prop, Catch 1)Segrave&Collins2005 (Prop, Catch 2)Segrave&Collins2005 (Viol, Catch 1)Segrave&Collins2005 (Viol, Catch 2)Segrave&Collins2005 (Viol, catch 3)

Segrave&Collins2005(Prop, Catch 3)Sherman&Rogan1995 (Catch 1)Sherman&Rogan1995 (Catch 2)

Wagers2007Weisburd&Green1995

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Monte Carlo (re)samples from all Permutations

Summary of results

Conclusions so far •  Repeat burglary victimisation strategies reduce crime

–  Dosage is important –  Little known about the prevention of near repeats

•  On average geographically focused policing initiatives (for which data were available) are:

–  associated with significant reductions in crime and disorder

–  overall, changes in catchment areas are non-significant but there is a trend in favor of a diffusion of benefit (particularly for RCTs and where there are treatment effects)

•  Understanding where benefits diffuse can help inform where resources can be moved from and to

Predicting future patterns

•  Hotspots research assumes a regularity in spatial crime patterns, with variation by time of day

•  RV and NRV research suggests a regularity in the space-time distribution of risk, with variation by time of day –  Optimal foraging patterns

Bowers, K.J., Johnson, S.D., and Pease, K. (2004). Prospec:ve Hot-‐spo?ng: The Future of Crime Mapping? The Bri$sh J. of Criminology, 44, 641-‐658.

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Forecas,ng -‐ ProMap

Bowers, K.J., Johnson, S.D., and Pease, K. (2004). Prospec:ve Hot-‐spo?ng: The Future of Crime Mapping? The Bri$sh J. of Criminology, 44, 641-‐658.

Prediction - basic approach

Grid (50m cells)

Spatial Buffers

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Forecasting (static and dynamic factors) (7- day forecast)

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Johnson, S.D., Bowers, K.J., Birks, D. and Pease, K. (2009). Predictive Mapping of Crime by ProMap: Accuracy, Units of Analysis and the Environmental Backcloth, Weisburd, D. , W. Bernasco and G. Bruinsma (Eds) Putting Crime in its Place: Units of Analysis in Spatial Crime Research, New York: Springer.

Bowers, K. J., Johnson, S. D., & Pease, K. (2004). Prospective Hot-Spotting The Future of Crime Mapping?. British Journal of Criminology, 44(5), 641-658.

Repeat Vic,misa,on – Road to Reduc,on

Disrup,ng the Op,mal Forager Predic,ve Mapping & Super Cocooning

Trafford – Tackling Burglary Dwelling

Inspector Vincent Jones ,Greater Manchester Police Matthew Fielding, Greater Manchester Police

“In domes$c burglary, for example, the danger of a further crime is greatest at the home of the original vic$m and spreads out to some 400 metres, but disappears over six weeks to two months … instead of mapping past events in the conven$onal way we should map the risk they generate for nearby homes, with the map being dynamic to reflect how the risk declines over <me.”

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Every day 00:00-04:00, Particularly 02:00-03:00 Also 16:00-19:00 Friday and Monday

Original Theory vs Output

Intervention

•  Shift-specific maps each Wednesday to Neighbourhood inspectors (previous patrol plans often at officer discretion)

•  Increasing guardianship –  Neighbourhood police team patrol plans (PCSOs door to door –

inform, reassure, advise, gather intelligence) –  Council community safety patrols patrol areas –  Fire service –  Police driving school

§  Average of 48% decrease in the target areas of Orange and Red (373 to 194 BDW)

Results

BDW Count Orange Red Yellow Blue Outside Total 2009/10 139 234 218 159 479 1229 2010/11 66 128 141 97 470 902

Change -52.5% -45.3% -35.6% -38.8% -1.9% -26.6%

12 month review – •  Trafford saw 902 burglaries, 2nd lowest count across GMP •  YTD 2009, Trafford saw a significant 26.6% decrease (1229 to 902 BDW) (GMP – 9.8%, MSG BCU GMP saw an increase of 7%)

Fielding, M., and Jones, V. (2012). ‘Disrupting the optimal forager’: predictive risk mapping and domestic burglary reduction in Trafford, Greater Manchester. International Journal of Police Science & Management, 14(1), 30-41.

Results

Fielding, M., and Jones, V. (2012). ‘Disrupting the optimal forager’: predictive risk mapping and domestic burglary reduction in Trafford, Greater Manchester. International Journal of Police Science & Management, 14(1), 30-41.

Enhancements •  Tac<cal Interven<ons: ‘Super Cocooning’ – within a manageable area (24-‐48 hrs)

Target hardening – via both Police and Partnership Resources (24 hrs)

•  Extension to theft from vehicles – 29% reduction

Final thoughts

•  Replication in West Yorkshire (48% reduction)

•  Notification of Community Crime (NOCC) intervention to increase community empowerment in Edmonton, Canada (66% reduction in burglary in 6 months)

•  Implementation fidelity (timing and dosage) and accountability

•  More evaluations of near repeat strategies needed

Resources

•  JDi Briefs (http://www.ucl.ac.uk/jdibrief/analysis)

•  POP guide (http://www.popcenter.org/tools/repeat_victimization/)

•  Risk Terrain Modelling (http://www.rutgerscps.org/rtm/)

•  Near Repeat Calculator (http://www.temple.edu/cj/misc/nr/)

shane johnson

Documents

systematic reviews replicable

crime reduction grove

transparent review

sexual victim

crime science

bra swedish national

poly victim

recidivist victim