CONDUCTING CRIMINOLOGICAL RESEARCH IN A HOSPITAL
• 75
Research Note
*  Conducting Criminological Research in a
Hospital: The Results of Two Exploratory
Studies and Implications for Prevention
Connie Hassett-Walker
Douglas J. Boyle
Violence Institute of New Jersey
University of Medicine and Dentistry of New Jersey
* Abstract
This article discusses the results of two exploratory studies using hospital data
on intentional assault injury. Study #1 was a two-year gunshot wound (GSW)
surveillance effort (N = 920). A map of the EMS dispatch addresses revealed that
certain neighborhoods were “hotspots” for gun violence. Hierarchical regression
analysis revealed that poverty, vacant housing and rental housing were significant
predictors of a neighborhood’s GSW rate. Study #2 involved interviews with
assaulted patients (N = 30). More than half of the sample had been incarcerated,
which is striking considering their young age (i.e., 21 years old and younger).
Prevention implications of both studies are discussed.
JUSTICE RESEARCH AND POLICY, Vol. 9, No. 1, 2007
© 2007 Justice Research and Statistics Association
76 • JUSTICE RESEARCH AND POLICY
Criminologists use a variety of data sets and types, each with its own
strengths and weaknesses—including the Uniform Crime Reports (UCR); the
UCR’s Supplemental Homicide Reports (SHR) and the National Incident-Based
Reporting System (NIBRS); the National Crime Victimization Survey (NCVS);
and the Monitoring the Future Survey of students’ drug use, to list a few examples
(Maxfield, 1999). Consulting different data sources can lead to diverse conclusions about whether crime is increasing, decreasing, or remaining stable (O’Brien,
1996; Boggess & Bound, 1997).
The UCR are valid measures of serious crime that is reported to the police,
particularly for homicide, burglary, robbery, and motor vehicle theft (Gove,
Hughes, & Geerken, 1985). For other types of crime (e.g., aggravated assault,
rape), however, the evidence is more qualified. For instance, Gove and colleagues
note that many aggravated assaults—particularly those committed by friends
and family—are not recorded in the UCR. Critics of arrest data note that they
likely underestimate the true incidence of crime, as many acts are undetected and
unreported to police, thereby resulting in no arrest (Jenson & Howard, 1999).
Victimization survey data such as the NCVS are useful for measuring unreported activity, that is, the “dark figure” of crime (Maxfield, 1999). Because
victimization surveys have revealed that most crimes are not reported to the police, these findings have called into question the validity of arrest data (Gove et
al., 1985). Victimization surveys are not without problems. For instance, people
may be reluctant to report being victimized by someone they know, such as a
family member or close friend (Strom, 2000; Cook, 1985). In addition, because
it focuses on victimization of individuals living in households, the NCVS would
likely miss incidents involving the homeless (for instance) as well as “victimless”
crimes (e.g., prostitution, gambling) (Maxfield, 1999).
Other survey instruments, such as the Monitoring the Future Survey and
the Youth Risk Behavior Survey (YRBS), ask youth to self-report their drug use,
delinquency, and non-fatal violent behavior (e.g., fighting), among other things
(Jenson & Howard, 1999). A disadvantage of self-report data is that they tend to
underestimate socially unacceptable behaviors and traits (e.g., deviant behaviors,
racial prejudice) (Singleton & Straits, 2005). In addition, Gove and colleagues
(1985) note that self-report studies include a high rate of non-serious crime.
A search of criminal justice abstracts found few studies using medical and
public health data on intentional assault injury, suggesting these data are not widely
utilized by criminologists. While some research involving hospital-based injury surveillance has been conducted (e.g., Graitcer, 1987; Hutson, Anglin, & Pratts, 1994;
Litaker, 1996; Wilt & Gabrel, 1998; Gotsch, Annest, Mercy, & Ryan, 2001), the
results of such efforts have been published largely in public health and medical journals. Exceptions include the work of Rand (1997); Strom (2000); Decker, Curry,
Catalano, Watkins, and Green (2005); and most recently Cohen and Lynch (2007).
The present article discusses the results of two exploratory studies that use
hospital data on intentional assault injury. Study #1 is a two-year, gunshot wound
CONDUCTING CRIMINOLOGICAL RESEARCH IN A HOSPITAL
• 77
(GSW) surveillance effort (N = 920) conducted in a level one Trauma Center located in Newark, New Jersey, a mid-size urban center. Similar to the methodology
adopted by Strom (2000) and Rand (1997), the data used in Study #1 were extracted from patients’ medical charts and medical histories, to record information such
as prior violent injuries. In other words, the data extracted are based on medical
staff notations regarding prior violent injuries (for instance), rather than patient
self-report. This is an advantage of working with hospital data on assault—despite
a patient’s potential reluctance to discuss their victimization, concrete evidence
of a crime exists (e.g., bullet holes or fragments present in the body). In addition,
the geographic locations of the shootings (i.e., the EMS patient retrieval address)
are included in map form, a unique contribution for studies using hospital data.
Implications for prevention planning at the neighborhood level (e.g., city housing
policies to alleviate concentrated poverty and vacant housing) are discussed.
Study #2 (N = 30) was conducted subsequent to the first study, in the same
facility, and involved more detailed interviews with assaulted adolescent and
young adult patients. The results are presented, followed by a discussion of the
next steps to plan a re-injury prevention program with this population.
* Description of Present Studies
Setting
The University Hospital Trauma Center (hereafter Trauma Center), where
both studies took place, is located in Newark, NJ, which has a population of just
over 273,000 residents (U.S. Census, 2000). Of the top 15 urban centers profiled
by the State Police for 2005, Newark had the highest crime index and the largest
number of violent crimes of any city statewide (State of New Jersey, Division of
State Police, 2006). The Trauma Center is a level one trauma treatment facility
that serves more than one million individuals statewide. Within its catchment
area, more than 90% of violence victims with injuries requiring hospitalization
receive treatment at the Trauma Center (Lavery et al., 1999). The studies to
be described grew out of an earlier effort to study and prevent violence in the
greater Newark area (Boyle & Hassett-Walker, in press). That initiative was
broader in scope, and involved collecting data on all assault-related visits at six
local hospitals providing emergency medical care.
Description of the Studies1
Study #1: The study’s authors collected data on non–self-inflicted GSW victims treated at the Trauma Center and/or the hospital’s emergency room from
1
Both studies had prior approval from the University’s Institutional Review Board.
78 • JUSTICE RESEARCH AND POLICY
January 1, 2004 through December 31, 2005. Medical students, as well as the
project’s data coordinator, reviewed daily the medical charts of GSW patients.
Data extracted from the medical records included patient demographics (i.e., gender, age, race/ethnicity); seriousness of injury (e.g., whether the patient was treated and released, admitted to the hospital, or died); any past medical treatment for
intentional assault injuries; any evidence of current or past criminal involvement;
and the address at which the ambulance (i.e., EMS) retrieved the patient.
Study #2: The second study developed out of recognition that data gathered
only from patient medical records (i.e., Study #1) would provide better information about gun violence at the city level, particularly the spatial distribution of
GSWs. However, data were still needed about individual-level, contextual factors
related to assault. As a result, in Study #2 semi-structured interviews were conducted with consenting patients 13 to 21 years of age, who received treatment for
an intentional assault-related injury (e.g., GSW, stabbing, assaulted with fists). The
interviews were conducted from September 2005 through September 2006. The
interviewer, a licensed clinical social worker, asked patients about their education,
work history, and family environment, including cohabitation with younger siblings and other younger relatives who were likely affected by the assault. Patients
were also asked about the context for the assault, and any role the patient may
have played in the assault event; alcohol and drug use; violence in the patient’s
residential neighborhood; and past involvement in the criminal justice system.
A main goal of Study #2 was to use the data gathered to plan an intervention to prevent reinjury. Moscovitz, Degutis, Bruno, & Schriver (1997) note
that 30% of individuals injured through interpersonal violence sustain subsequent violence-related injuries. There are advantages to establishing a violence
intervention within a hospital setting, including a prolonged period of providerpatient contact and the resulting potential to form patient-caregiver bonds
(Hausman, Prothrow-Stith, & Spivak, 1995). Although the field is relatively
new, some hospital-based violence interventions have evidence to support their
effectiveness (e.g., Zun, Downey, & Rosen, 2006; Cooper, Eslinger, & Stolley,
2006; Becker, Hall, Ursic, Jain, & Calhoun, 2004).
* Statistical Analyses and Variables
Statistical analyses were performed using SPSS 14.0 software for Windows. The
hotspots map shown in Figure 1 was generated using Arcview Spatial Analyst
9.1 geographical mapping software, and hierarchical nearest neighbor clustering in CrimeStat software. A one-tailed probability level of .05 was selected.
A hotspot is an area where residents have a higher than average risk of being
victimized (Eck, Chainey, Cameron, Leitner, & Wilson, 2005).
The results of Study #1 are presented first, and include GSW patients’ prior
assault injuries and evidence of criminal activity. We also examine socio-structural
CONDUCTING CRIMINOLOGICAL RESEARCH IN A HOSPITAL
• 79
predictors of a neighborhood’s GSW rate per 1,000 residents using both correlational analysis and hierarchical regression. Statistical analysis revealed a positive
skew in the rate of GSW injury by block group, and thus we transformed the
rate using the logarithmic function in SPSS.
The socio-structural variables were taken from the U.S. Census 2000, at the
level of patients’ residential block group.2 These were:
• concentration of poverty (i.e., the ratio of the population with income in
1999 below poverty level to the population for whom poverty status is
determined);
• percentage of vacant housing units; and
• percentage of rental housing units.
The two latter variables—percentage of vacant housing and rental housing
units—are proxy indicators of residential mobility, an element of social disorganization theory (Shaw & McKay, 1942; Bursik, 1988; Sampson & Groves,
1989; Sampson & Wilson, 1995). Past research has shown that residential instability and low rates of home ownership correlate with many problem behaviors
(Sampson, Morenoff, & Gannon-Rowley, 2002).
* Results of Study #1
Patients’ Prior Assault Injuries
As shown in Table 1, around 40% of GSW patients sought previous medical attention for some illness or injury prior to treatment for their GSW injury.
Nearly 15% of patients had previously received Trauma Center medical treatment specifically for a prior assault-related injury (e.g., being previously shot
and/or stabbed). This percentage increases slightly to 20% when patients’ prior
assault injury treatment at other hospitals, as well as the Trauma Center, is considered. In other words, nearly one in five GSW patients had some notation—
either in their medical chart (e.g., existing bullet fragments from a previous
shooting may have been found in the patient’s body) or in one of the hospital’s
databases—about having sustained a prior assault-related injury. Analyses using
other criminal justice datasets also find support for the idea of repeat victimization, including the National Youth Survey (NYS; Lauritsen & Davis Quinet,
1995); the British Crime Survey (Ellingworth, Hope, Osborn, Trickett, & Pease,
1997); and the NCVS (Tseloni & Pease, 2004).
2
A subdivision of a census tract (or, prior to 2000, a block numbering area), a block
group is the smallest geographic unit for which the Census Bureau tabulates sample
data. (See http://www.metrokc.gov/gis/mapportal/CV_glossary.htm#cbg and also http:
//www.census.gov/geo/www/cob/bg_metadata.html.)
80 • JUSTICE RESEARCH AND POLICY
* Table 1
Study #1: Patients’ Prior Injury and Criminal Behavior (N = 920)
Patient History
Prior Trauma Center (TC) visits, any reasona
Prior TC assault-related visits
Any priorb
Current or prior criminal involvement
Patients (n)
364
134
183
72
Percent
39.6%
14.6
19.9
7.8
GSW patients had past usage of University Hospital for a variety of reasons, including toothaches,
kidney stones, sexually transmitted diseases, fever, pregnancy-related visits, alcohol and drug
overdoses, and motor vehicle crashes.
a
Any prior includes a patient’s prior treatment at the Trauma Center (n = 134) as well as at other
hospitals (n = 49) for assault-related injury.
b
Patients’ Prior Criminal Activity
Notations were found in nearly 8% of GSW patients’ medical charts
indicating they had current or past criminal involvement (see Table 1). This
figure is most likely an underestimate—underscored in particular by the findings from Study #2, discussed shortly—since the Trauma Center staff is not
required to document this information, as it is non-medical in nature. The following are some examples of crime-related notations extracted from the GSW
patients’ charts: (a) discharged into custody of police; (b) attempted robbery;
(c) during prior Trauma Center visit, patient was a detainee at county juvenile
detention; (d) inmate identification found on patient; (e) patient is on house
arrest, parole officers stop by to see patient; and (f) patient pulled gun on
police and was shot. It should be noted that these are medical staff notations
with regard to patient processing rather than the patients’ self-report about
their behavior. In at least one instance, both the criminal and the police officer were wounded by gunfire during the same incident, and both ended up
as patients receiving treatment at the Trauma Center. Other criminological
research similarly suggests that victims and offenders are not mutually exclusive groups (e.g., Rapp-Paglicci & Wodarski, 2000; Lauritsen & Davis Quinet, 1995; Lauritsen, Laub, & Sampson, 1992; Jenson & Brownfield, 1986;
Singer, 1981).
Spatial and Time Distribution of GSWs
Figure 1 illustrates the hotspots of GSWs during the two-year study period.
The map was created using addresses of EMS dispatch locations, which were
CONDUCTING CRIMINOLOGICAL RESEARCH IN A HOSPITAL
• 81
only available for patients transported to the Trauma Center via ambulance. As
seen in Figure 1, the data’s geographical distribution reveals that certain areas
of the city were significantly more likely to produce GSW victims—including
those neighborhoods located near the Trauma Center (i.e., at University Hospital). Other criminological research also shows that crime clusters geographically (e.g., Shaw & McKay, 1942; Land, McCall, & Cohen, 1990; National
Research Council, 2001).
* Figure 1
GIS Hotspot Map of GSWs Based on EMS Dispatch Location in Newark,
East Orange, and Irvington (1/1/04 - 12/31/05)
The distribution of GSW victims by time (Figure 2) reveals that the late
night/early morning hours are peak times for local gun violence. An analysis of
the distribution of GSW victims by day of the week (not shown in table or figure format) reveals that Sundays and Mondays are peak days for gun violence:
39% of GSW patients were admitted on those two days. An additional 15% of
patients were admitted on Saturdays.
82 • JUSTICE RESEARCH AND POLICY
* Figure 2
Distribution of Gunshot Victims by Time of Day
10%
8%
6%
4%
2%
0
12 1 2 3 4 5 6
7 8 9 10 11 12 1 2 3
AM
Noon
4 5 6 7 8 9 10 11
PM
Socio-Structural Characteristics of GSW Hotspot Neighborhoods
In an effort to ascertain what neighborhood-level factors might be related to
the GSW hotspots, we conducted correlational and regression analyses using socio-structural factors from the U.S. Census. Table 2 presents the Pearson’s correlations between the log of a block group’s GSW rate per 1,000 residents and the
three socio-structural indicators described earlier (i.e., poverty concentration,
percentage of vacant housing units, and percentage of rental housing units),
which were operationalized from social disorganization theory. The correlational analyses revealed significant, positive relationships between a neighborhood’s
GSW rate and its concentrated poverty and percentage of vacant housing units,
but not the percentage of rental housing units.
* Table 2
Correlation of GSW Rate (log) per 1,000 Residents by Block Group and
Socio-Structural Indicators (n = 193)
GSW Rate
GSW Rate
Poverty Concentration
Percentage of Vacant Housing Units
Percentage of Rental Housing Units
*p ≤ .01
.38 *
.21 *
.03
Poverty
Concentration
.24 *
.50 *
Percentage of
Vacant Housing Units
.17 *
CONDUCTING CRIMINOLOGICAL RESEARCH IN A HOSPITAL
• 83
The hierarchical regression is shown in Table 3. We decided to enter poverty
concentration first, as it was the strongest predictor in the correlational analyses.
Because rental housing was non-significant in the correlational analyses, we excluded it from the regression. The overall model is significant, explaining 16% of
the variance in the GSW rate by block group. Significant at the p ≤ .05 level, both
poverty and vacant housing influence the GSW rate in the theoretically expected direction, although poverty concentration is the stronger predictor. These results are
consistent with the findings of prior research (Boyle & Hassett-Walker, in press).
* Table 3
Socio-Structural Predictors of GSW Rate (log) per 1,000 Residents by
Block Group (n=193)
Predictor
Beta
ΔF
ΔR2
Sig.
Poverty concentration
Vacant housing units
Constant
.35
.14
32.14
4.62
.14
.02
.00
.03
.36
R2
Adjusted R2
DF
F
P
.16
.16
2
18.69
.00
Comparing GSW and Arrest Data
Table 4 shows how the GSW data compare with State Police arrest data collected during the same time period. While it is not possible to assess a trend from
only two years’ worth of data, it should be noted that both the GSW and Newark arrest data increased during the 2004–2005 period. Arrests also increased
slightly from 2004–2005 in Irvington (for murder), but not East Orange (for
either murder or aggravated assault). These data reflect the overall crime situation in the state’s urban areas during the 2004–05 period. According to police
data, the overall violent crime index for New Jersey’s “Urban Fifteen”3 cities
increased from 15,916 (2004) to 16,657 (2005) (State of New Jersey, Division
of State Police, 2006). That said, 8 of the state’s 15 urban centers had increases
in the violent crime index, 6 had decreases, and one city remained virtually the
same. In other words, what is seen in the GSW data reflects the state of affairs
of violent crime in New Jersey’s urban centers during the same time period—a
mixed bag of sorts.
The three cities referenced in Table 2 – Newark, Irvington, and East Orange – are
among the New Jersey “Urban Fifteen.”
3
84 • JUSTICE RESEARCH AND POLICY
* Table 4
Comparing Trauma Center GSW Data and Police Violent Crime Arrest Data
2004–2005
Period
Year 2005
Year 2004
124
796
69
419
55
377
Police Arrest Data, Newark
Arrests for murder
Arrests for aggravated assault
184
2,848
98
1,441
86
1,407
Police Arrest Data, Irvington
Arrests for murder
Arrests for aggravated assault
54
1,243
28
618
26
625
Police Arrest Data, East Orange
Arrests for murder
Arrests for aggravated assault
31
975
14
470
17
505
Data Type
Trauma Center Data
Fatal GSW
Non-fatal GSW
Note. Source of police violent crime arrest data is the State of New Jersey, Division of State
Police (2006)
The Trauma Center GSW data and the arrest data are to some extent intertwined. For instance, some of the Newark, Irvington, and East Orange assault
and homicide victims (who were attacked by the offenders reflected in the police
arrest data) turn up at the Trauma Center. That said, the two datasets do not
deal with identical incidents; nor are the counts intended to be exactly the same.
Not all fatal GSW patients arrive at the Trauma Center, for instance; some are
transported directly to the city morgue. In addition, not all homicides are committed with a firearm.
Other Patient Characteristics
Males (n = 854) comprise nearly 93% of GSW patients. The majority (i.e.,
85%) of GSW victims in Study #1 are African American (n = 785). These results
reflect other research that shows an overrepresentation by both males (e.g., Frazier, Bock, & Henretta, 1983; Broidy & Agnew, 1997; Jenson & Howard, 1999;
Walklate, 2001) and African Americans (e.g., LaFree 1995, 1998; Hawkins,
Laub, & Lauritsen, 1998; Harrison & Beck, 2002; Federal Bureau of Investigation, 2001) in criminal justice statistics. In addition, 4% (n = 40) of GSW patients
are white. Ethnically, 9% (n = 86) of GSW patients are Hispanic.
Table 5 illustrates the age groupings of the GSW victims in Study #1. Young
adults 20 to 24 years of age comprise about one quarter of GSW victims, where-
CONDUCTING CRIMINOLOGICAL RESEARCH IN A HOSPITAL
• 85
as they make up less than 8% of Newark’s population (as well as the populations of Irvington and East Orange, respectively), according to the U.S. Census
American Community Survey for 2005.4
* Table 5
GSW Victims by Age Range (n = 903)
Years of Age
Patients (n)
Percent
Under 15
15–19
20–24
25–29
30–34
35–44
45–54
55–64
65–74
Over 74
15
146
247
208
107
133
33
8
2
4
1.7%
16.2
27.4
23.0
11.8
14.7
3.7
0.9
0.2
0.4
Total
903
100
Note. Data on patient age are missing for 17 patients. This may be, for instance, because the patient was admitted to the emergency room unconscious, subsequently died, and no identification
was found on his/her body.
The GSW data regarding victim age reflect the age-victimization curve found
in other criminal justice data. In 2000, individuals in their early 20s comprised
19% of murder victims nationwide (Federal Bureau of Investigations, 2001). In
the 2005 NCVS data, aggravated assault rates were highest for individuals 20
to 24 years of age (Bureau of Justice Statistics, 2006: Table 3). By contrast, the
young adult peak among the GSW victims is older than the peak teenage offending years typically described by criminologists discussing the age-crime curve
(e.g., Steffensmeier, Allan, Harer, & Streifel, 1989; Hirschi & Gottfredson,
1989; Farrington, 1986).
* Results of Study #2
Patients’ Prior Assault Injuries
Twenty percent of interviewed assault-injured patients (n = 6) showed up in
the hospital database as having received prior treatment at the Trauma Center
for an assault-related injury. In addition, half (n = 15) said they had had a physical
4
The American Community Survey is a service provided by the U.S. Census. It is
available online at http://factfinder.census.gov/home/saff/main.html.
86 • JUSTICE RESEARCH AND POLICY
fight (or fights) during the past year. When asked about prior victimization, the
subjects did not always perceive a previous assault in the context of being a victim. Rather, they saw themselves as an equally matched and active participant
in a violent event. This finding ties in with what Fagan and Wilkinson (1998)
learned from their interviews with young, inner-city males who had previously
been involved in a violent event. In terms of self-conceptualization, the young
men largely saw themselves as being able to hold their own in social situations,
as opposed to being a punk (i.e., a weaker person, frequent victim).
Evidence of Patients’ Criminal Activity
Three out of four interviewed patients (n = 23) said they had been previously arrested; and 53% (n = 16) had been previously incarcerated.5 During one
trip to a hospital room to obtain consent from a potential study participant, it
was revealed that the victim had outstanding warrants for his arrest, and that
he would be discharged from the Trauma Center to jail. Although the sample
size is small, the results echo the findings of other criminal justice research (e.g.,
Rapp-Paglicci & Wodarski, 2000; Lauritsen & Davis Quinet, 1995; Lauritsen
et al., 1992) that criminals are at risk for assault. What is particularly striking
about the incarceration finding is how young the subjects are (i.e., no older than
21 years at the time of the interview).
Other Patient Characteristics
Ninety percent of patients interviewed in Study #2 were male (n = 27).
Mean patient age was 18.3 years, although as previously noted, subjects’ age
range was only 13 to 21 years as per the study design. Seventy percent of assault
injury victims were African American.
In their longitudinal study of adolescent risk factors, Sege, Stringham, Short,
and Griffith (1999) found that adolescents who were not in school, or reported
both fighting and illicit drug use, were at highest risk for violence-related injury.
Many of the patients interviewed for Study #2 fit with this description. Nearly
half of the sample (n = 14) were not currently in school, and had neither graduated from high school nor obtained their GED. Of the adult subjects (i.e., 18
years of age or older), only one third were employed at the time of the interview. As was mentioned earlier, half of the sample had fought physically during
the prior year. Twenty percent (n = 6) of the sample indicated that they drink
regularly, and more than half (n = 16) said they use drugs (mostly marijuana).
Interviewed subjects had been incarcerated at both juvenile and adult detention
facilities. Length of time of stay varied. One subject reported being locked up several
times at the county youth house for truancy, each time staying less than a week. Another
subject had spent five months at a youth house, and at the time of the interview was out
on bail awaiting sentencing for drug possession and weapon-related charges.
5
CONDUCTING CRIMINOLOGICAL RESEARCH IN A HOSPITAL
• 87
Twenty percent had used drugs shortly before the assault that led to their most
recent treatment6 at the Trauma Center. Finally, 90% had witnessed violence in
their community, and a quarter said they had lost friends or family to violence.
In short, the interviewed patients in Study #2 seem at high risk for future violence-related injuries, and prime candidates for an intervention.
* Prevention Implications
Prevention Implications from Study #1: Increase Neighborhood-Level
Collective Efficacy
Prevention implications can be inferred from the findings of the regression
analysis. The block groups with higher GSW rates tended to be poorer and
have greater numbers of vacant housing units. The significance of vacant housing units as a predictor of a neighborhood’s GSW rate suggests that there may
be something about an area having less collective efficacy (i.e., residents and
neighbors looking out for one another, and each other’s property and children)
that facilitates more gun violence occurring there (Land et al., 1990; Parker,
1989; Sampson, Raudenbush & Earls, 1997; Marciniak, 1994). By contrast,
other neighborhoods may be similarly poor, but have fewer vacant apartments
or buildings, and more people residing there who are willing to look out for one
another (i.e., greater collective efficacy). This could lead to less gun violence in
such a block group, and generally greater neighborhood-level safety.
City-level housing policies that target areas with more vacant housing
could potentially help lessen local gun violence. In addition, because the effect
of poverty concentration was so strong, a solution might be to offer financial
incentives to facilitate greater class diversity among Newark residents (i.e.,
working- and middle-class residents residing in the same block groups with
more impoverished residents). Wilson (1987) describes this as the vertical integration of families at different socioeconomic levels, which can socially buffer
against concentrated poverty.
Prevention Implications from Study #2: Reinjury Prevention Planning
In addition to treatment for their physical injuries, assault-injured patients
also need substance abuse and mental health treatment, the latter for both preexisting conditions as well as for the trauma associated with being the victim of
a violent crime. An advantage of a hospital-based intervention lies in the “teachable moment” concept; that is, life transitions such as health events that inspire
That is, during the September 2005-September 2006 study period, at which point
they enrolled in Study #2
6
88 • JUSTICE RESEARCH AND POLICY
individuals to spontaneously adopt risk-reducing behaviors (McBride, Emmons,
& Lipkus, 2003). Various references to the teachable moment idea show up in
medical and public health literature (e.g., Mitka, 1998; Stevens, Severson, Lichtenstein, Little, & Leben, 1995). Offering an intervention to patients admitted
for a violent injury may help reach a population not accessible in other settings,
and one that is ready to change.
A common element of hospital-based reinjury prevention programs with
evidence of effectiveness (i.e., Caught in the Crossfire, Becker et al., 2004; the
Violence Intervention Program (VIP), Cooper et al., 2006; and an “ED-based
violence prevention program,” Zun et al., 2006, p. 12) is heavy staff involvement
with the injured youth. In the case of the VIP (Cooper et al., 2006), for instance,
team members met weekly for group encounter sessions. Teams consisted of two
social workers and two case workers; a program manager; probation and parole
agents; and staff from myriad hospital departments. Zun and colleagues (2006)
note that the case managers met with participating youth weekly for the first two
months, every other week for the second two months, and monthly thereafter.
Among the next steps for Study #2 is to seek funding to hire a licensed clinical social worker to coordinate the planning and start-up of an intervention. A
multi-pronged approach will likely be used, including reaching out to patients
treated through the Trauma Center, as well as their families, particularly younger siblings, cousins, and other youth who cohabitate with the patient. (Seventythree percent of interviewed patients indicated that they live with and/or have
younger siblings or cousins; 13% had children of their own.) In addition, a
prevention and/or intervention program may be offered in schools located in the
high-violence neighborhood(s) identified through mapping, similar to that used
in Study #1.
An interesting finding from the evaluation of the VIP (Cooper et al., 2006)
is that the treatment participants may have been intrinsically motivated to participate in the intervention, as many of them had just survived a second or third
life-threatening assault. They may have believed their odds of survival were declining. The fact of their older age (i.e., 40% of subjects were 30 years of age or
older) may have helped motivate them to want to change their life. The active
participation of probation and parole officers may have provided an additional
incentive. The implications of that study (Cooper et al.) for the present re-injury
prevention planning are that it may be worthwhile to consider different program
approaches for different age groups.
In addition, because the majority of patients interviewed in Study #2 had
prior histories of criminal activity and criminal justice involvement, parole and
probation officers may be part of the intervention planning team (as was done
in the Cooper et al., [2006] study). As Lauritsen and colleagues (1992, p. 101)
note, adolescent victims and offenders “do not constitute mutually exclusive
groups.” The implication is that victimization and delinquency prevention efforts should be combined (at least for the adolescent victims).
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* Limitations
Project staff faced certain limitations. It is unfortunately not possible to directly
compare the GSW data with police data about the shooting incidents, as it was
not part of the study’s design. We attempted to address this issue by contacting local police, but were unable to obtain a copy of their electronic data file
of police shooting-hits. In other words, while hospital injury surveillance data
may catch some crimes missing in other criminal justice data sources, it is not
possible to conduct that analysis with these data. That said, we feel that the
inclusion of the socio-structural variables helps illuminate some of the neighborhood social and economic characteristics related to gun violence rates.
Maps could only be created for those patients who were brought to the
Trauma Center via EMS (i.e., about half of the GSW sample). The locations
of the shooting for those patients brought to the Trauma Center via private
car, for instance, are unknown. Despite the missing data, the spatial and day/
time analyses revealed that certain areas of the city were significantly more
likely to produce GSW victims; and that more GSW victims were admitted to
the Trauma Center on Sunday and Monday, as well as during the late night/
early morning hours. Data like these can help inform the resource allocation
planning of local police. To that end, during the study period monthly reports
were issued to a local safety planning coalition composed of police and various community agencies.
In Study #1, data such as the context for the shooting remained elusive.
Contextual information about the incidents was sometimes found in supplemental sources (e.g., local newspapers). Notations by medical staff regarding
the circumstances tended to be short and non-illustrative (e.g., “patient heard
one shot;” “patient recalls events of the assault,” with no further details provided). Details about the victim-perpetrator relationship were typically not
recorded in the patient medical charts. This realization provided the impetus
for undertaking Study #2, to be able to obtain these contextual factors.
Because Study #2 involved direct questioning of patients, more detail
was obtained about the circumstances related to the attack. Some patients
were reluctant to disclose full details about their assault (similar to criticisms, discussed earlier, of victimization self-report data). One subject, for
instance, said he was approaching a bus stop and noticed some kids fighting. He noted that “someone punched me and I was stabbed by a stranger,”
suggesting he was neither involved nor knowledgeable about why this happened. Fortunately, other patients were more forthcoming: one subject said
he was shot by the boyfriend of a young woman he had flirted with (after
he beat up the boyfriend, who subsequently left and returned with a gun).
Another subject thought he might have been stabbed because his friends are
either gang members or gang-friendly (although he claimed not to be a gang
member himself).
90 • JUSTICE RESEARCH AND POLICY
* Conclusion
Hospital surveillance data on assault injury have not been in the forefront of
many criminologists’ thoughts. Perhaps that should change, however. This article presents the results from, and prevention implications of, two studies using
hospital data on intentional assault injury. Hospital data on serious assault such
as being shot offer undeniable evidence of a crime, thereby addressing some of
the validity problems of self-report victimization data, for instance. While some
of the findings from the present studies support what is already known from
other criminal justice research (e.g., repeat victimization), the visual presentation of the geographic locations of the shootings is a new contribution for studies using hospital data.
The studies highlight the intersection of the medical/public health and
criminal justice fields. Assault-injured patients, as well as their families, are
vulnerable individuals in great need of assistance. The hospitals that treat them
represent a catchment point through which the victims can be reached. The
authors would encourage criminologists to venture into nontraditional settings to plan prevention and intervention programs, as well as to conduct their
research. In a similar vein, medical staff can think of themselves as part of the
criminal justice community.
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