Crime Prevention and Perception Camila Alvarado Cal Burton

Crime Prevention and Perception Camila Alvarado, Cal Burton, Vivey Chen, Jessica Cutler, Sasha Derkacheva, Luciana Debenedetti, Valentina Lopez, Stephanie von Numers Mentors: Charles Wellford, Ph. D. and Lt. Steven Kowa, Ph. D. Librarian: Barbara Lay

Agenda Introduction Research Overview Crime Data Surveys CPTED Scale Methodology Results Conclusion

Introduction

Disparity – Risk of Crime On & Off Campus (2006) 20742 20740 On Campus Off Campus Total Crime Risk . 03 x National Average . 63 x National Average Larceny . 05 x National Average . 81 x National Average Burglary . 04 x National Average . 25 x National Average Robbery . 02 x National . 70 x National

The Diamondback November 11, 2008 “Incidents of violent and property crime so far this year have fallen well below the six-year averages, but improving statistics have not necessarily translated into a greater perception of safety. ” "Perception can't be discounted even though crime rates are down. " -University Police Spokesperson Paul Dillon

The Importance of Perception Research has shown that fear of crime may lead to: Negative psychological effects Avoidance behavior (Liska et al. , 1982) Fear of crime negatively affects neighborhood cohesion Interpersonal distrust Leads to greater amount of crime (Garofalo, 1981)

Routine Activity Theory

Situational Crime Prevention Reduce opportunities for crime by Increasing risks Reducing rewards (Clarke, 1995) Defensible space to promote security Process (Clarke et al. , 1989) Collect Analyze Study prevention Implement Determine

Crime Prevention Through Environmental Design (CPTED) CPTED draws a relationship among the environmental factors in an area, the crime rate and perceived feelings of safety—or lack thereof (Cozens et al. , 2005) Based on the following overlapping principles: Territoriality Surveillability Target hardening Access control Image/maintenance Social cohesion/community culture

Research Overview

Research Questions 1. What is the relationship between a routine activitybased intervention and the rate of property crime and robberies in off-campus student residential areas? 2. What is the relationship between a routine activity based intervention and students’ perceptions of crime? 3. What is the relationship between crime and the environmental design of properties in the selected area?

Sub-Questions 1. Where are the off-campus student residential areas with high incidences of reported crime? 2. What is the specific nature of crime in these hot spots? 3. What are students’ perceptions of crime in the target area, pre-intervention?

Hypotheses Following the implementation of a routine activity-based intervention: Crime rates will be reduced Students’ perceptions will reflect a greater sense of safety Properties with lower levels of CPTED vulnerability will have fewer incidences of crime

Study Division

Methodology

Methodology Overview Longitudinal case study Interrupted time series design Data Collection Pre. Survey Data Collection Interruption Data Collection Post. Survey Data Collection

Target Area Selection

Crime Data Collection Burglaries, larcenies, and robberies Prince George’s County Police Department Crimes committed between 01/2008 – 02/2011 Coding key

Perception Survey Questions Sources Format Target population Residents of Old Town Non-resident students of UMD Convenience sampling Facebook Listservs Flyers Door-to-door

Perception Survey

CPTED Scale Divided into 7 sections intended to measure the categories of CPTED Published safety checklists CPTED training Designed as a checklist Each property received a score in each section Higher score = more CPTED vulnerability Each characteristic was weighted equally

CPTED Scale Lighting __ Street lighting not present within ~25 feet / poor street lighting __ Lighting is inconsistent __ No home exterior lighting __ Yard not illuminated __ Lighting is inadequate (brightness –could you see people far away? ) __ Darkness is persistent Yard Maintenance __ Trash is present __ Yard is unkempt __ Bushes obscuring visibility (sight lines / light obstructed) __ Bushes block sight completely __ Unseemly objects beyond trash present Home Exterior Maintenance __ Paint chipping __ Windows broken __ Home seems unkempt / unwelcoming __ Home seems about to die __ Need for major repair Accessibility of Valuables __ Valuables visible secured in yard __ Valuables visible unsecured outside __ Valuables within sight inside __ Door open / cracked __ Windows / open cracked within sight __ Blinds / curtains open Territoriality __ No barrier between yard or sidewalk __ No items that establish ownership (flowerboxes, fences) __ No evidence of human presence (newspapers), place feels abandoned __ No boundary with yard next door Guardianship __ There is no sidewalk present __ There is a narrow sidewalk present __ No blue light in vicinity __ Foot traffic not quantifiable __ Vehicle traffic not present __ No bus stop nearby __ No visible cameras Visibility / Sight Lines __ Hiding places present

CPTED Scale View completely obscured by foliage Hiding places present

CPTED Scale Curtains left open Valuables visible in front yard No separation between yard and sidewalk

CCTV Camera Intervention August 2009 Recommendation s by CP 2 helped the city of College Park receive a grant for security cameras October 2010 CCTV cameras installed in Old Town

Results

Crime Data N=169

Crime Data

Crime Data TIME PERIOD AVERAGE COUNT RATE (PER 1000 RESIDENTS) January ‘ 08 – October ‘ 10 4. 56 7. 46 November ’ 09 – February ‘ 10* 1. 67 2. 73 November ’ 10 – February ’ 11**T-TEST (α = 0. 05) 3. 67 TSCORE DF 6. 00 CRITICAL VALUE (January ‘ 08 – October ‘ 10) vs (November ’ 10 – February ‘ 11)** 0. 53 35 1. 69 (November ‘ 09 – February ‘ 10)* vs (November ‘ 10 – February ‘ 11)** -4. 22 4 2. 13 * : omitted January 2010 ** : omitted January 2011 Differences in crime levels are not statistically significant.

Sample RESIDENTS DEMOGRAPHI CS NON-RESIDENTS ALL Pre. Survey Post. Survey N 85 110 354 163 439 275 MEDIAN AGE 21 21 20 21 WHITE 76. 5% 76% 65% 69% 67% 72% NON-WHITE 23. 5% 24% 35% 31% 33% 28% MALES 48% 44% 37% 29% 35% FEMALES 52% 56% 63% 71% 65%

Sample PRE-SURVEY POST-SURVEY Non-Resident Sample vs. UMD Population Resident Sample vs. Resident Population RACE X ✔ X X GENDER X DEMOGRAPHI CS MEDIAN AGE 20 vs. 21 X 21 vs. 23 : Representative X: Unrepresentative 21 vs. 21 21 vs. 23

Survey RESIDENTS Question How afraid are you of being a victim of crime? [1=Not afraid at all, 10=Very afraid] How likely do you think you will be a victim of crime? [1=Not likely at all, 10=Very likely] To what extent are you worried about crime in this neighborhood? [1=Not at all worried, 4=Very worried] Would you say you feel less safe or safer in your neighborhood than you did 12 months ago? [1=Much less safe, 5=Much safer] Mean pre 5. 20 post 5. 43 pre 4. 62 post 4. 32 pre 2. 73 t-score NON-RESIDENTS Mean 5. 17 -0. 73 5. 53 0. 61 4. 8 -3. 11 2. 79 2. 83 pre 2. 88 --- -1. 49 * α = 0. 10, significant when |t| ≥ 1. 29 -3. 48 2. 63 post 2. 65 -1. 75 4. 17 -0. 58 post t-score -----

Survey Non-residents in the post-survey reported being More worried about crime More fearful of being a victim And thought they were more likely to be victimized “Would you say you feel less safe or safer in your neighborhood than you did 12 months ago? ” Pre-survey vs. post-survey responses

Survey Prominent crimes in fall 2010: 9/4: Off-campus strong arm robbery 9/16: Bank robbery on Route 1 10/3: On-campus robbery 10/12: Quadruple stabbing on Route 1 11/20: Off-campus strong arm robbery These highly publicized crimes may have heightened students’ fear of crime on a general level

Survey RESIDENTS NON-RESIDENTS Question Mean In general, how do you feel about security cameras? pre [1=very negatively, 10=very positively] post Security cameras would help to deter criminal activity. pre [1=strongly disagree, 3=neutral, 5=strongly agree] t-score 6. 46 Mean 6. 75 0. 51 1. 33 6. 65 7. 04 3. 47 3. 44 -0. 93 post I would feel safer if my building implemented more security cameras. pre [1=strongly disagree, 3=neutral, 5=strongly agree] post 0. 93 3. 32 3. 52 3. 44 -1. 04 * α = 0. 10, significant when |t| ≥ 1. 29 3. 25 t-score 2. 41 3. 66

Survey In the post-intervention survey, Residents reported a greater use of home security systems Non-residents reported feeling safer walking around in Old Town at night

CPTED Site Assessments

Conclusions 1. Following the implementation of a routine activity-based intervention, crime rates will be reduced 2. Following the implementation of a routine activity-based intervention, students‘ perceptions will reflect a greater sense of safety 3. Residences with lower levels of CPTED vulnerability will have fewer incidences of crime Conclusive evidence was not found to support these hypotheses

Limitations Surveys Volunteer bias Generalization of crime perception CPTED No weighting No access to personal property

Limitations Fallibility of CPTED principles on crime Homogenous area External factors Delay of camera implementation

Contribution to the Field Testing the level of CPTED vulnerability in relation to crime rates Study of student-occupied, off-campus residential neighborhoods Integration of perception with crime rates and camera use

Future Research Control area Larger study population More time after intervention Access to personal property Manipulating CPTED variables

Acknowledgements Team CP 2 would like to thank the following individuals and organizations for their contributions to our research: Dr. Charles Wellford and Lt. Steven Kowa, Ph. D. , our mentors Gemstone Program staff Barbara Lay, our team librarian Maj. Liberati and the Prince George’s County Police Department The University of Maryland Police Department Bob Ryan and the City of College Park Office of the Vice President for Administrative Affairs, UMD Dr. John Firman, Dr. Joel Garner, Maj. Robert Liberati, Dr. Jean

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