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Aug 26, 2011 - The Role of Lifestyle and Personal Characteristics on Fear of Victimization among University Students. Daniel R. Lee & Carly M. Hilinski-Rosick.
Am J Crim Just (2012) 37:647–668 DOI 10.1007/s12103-011-9136-0

The Role of Lifestyle and Personal Characteristics on Fear of Victimization among University Students Daniel R. Lee & Carly M. Hilinski-Rosick

Received: 13 May 2011 / Accepted: 15 July 2011 / Published online: 26 August 2011 # Southern Criminal Justice Association 2011

Abstract The fear of crime has been both theoretically and empirically connected to a complex relationship of situational context (e.g., time of day, location) and personal characteristics (e.g., age, race, gender, personal and vicarious victimization). Building off of routine activities and lifestyle-exposure theory, this research extends the understanding of these relationships by examining the impact of lifestyle activities (e.g., consumption of alcohol, illicit drugs, and time away from residence) and personal characteristics (e.g., direct and vicarious victimization) on the fear of various crimes across temporal situations, among a sample of college and university students. The results indicate that fear of crime varies by crime type and that certain demographic and lifestyle characteristics and experiences with victimization affect students’ fear of crime. Although no evidence was found to suggest that fear of theft varies by temporal context (i.e., during the day or at night), certain characteristics, such as gender, perceived risk, and avoidance behaviors, have varying relationships with fear of violent crimes when considering time of day. The findings suggest that future research should examine more critically the relationship that lifestyles, personality, gender, and time of day have with the fear of crime. Keywords Fear . Routine activities theory . Lifestyle exposure . Victimization Research has consistently shown that there are certain individual characteristics that are related to fear of crime, including an individual’s sex, age, race, income, and residence (e.g., Baumer, 1978; Clemente & Kleiman, 1977; Kennedy & Silverman, D. R. Lee (*) Department of Criminology, Indiana University of Pennsylvania, 200 Wilson Hall, Indiana, PA 15705, USA e-mail: [email protected] C. M. Hilinski-Rosick School of Criminal Justice, Grand Valley State University, 251-C DeVos, 401 W. Fulton, Grand Rapids, MI 49504, USA e-mail: [email protected]

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1985; Miethe & Lee, 1984; Yin, 1985). This research has generally found that women, the elderly, nonwhites, the poor, and those who live in urban areas have higher levels of fear of crime than other groups in the population (e.g., Baumer, 1978; Clemente & Kleiman, 1977; Jennings, Gover, & Pudrzynska, 2007; Kennedy & Silverman, 1985; Miethe & Lee, 1984; Stanko, 1992; Yin, 1985). Beyond these demographic characteristics, there are also situational characteristics, lifestyle activities, and personal characteristics that have been theoretically and empirically linked to fear of crime. Situational factors related to the fear of crime include the time of day, location, potential hiding places for offenders, and lighting, among others. Research has suggested that fear of crime is greater at night than during the day and also varies based on the location of the individual and the characteristics of the surrounding environment (i.e., in an unsafe or disorderly neighborhood) (Day, 1994). Personal or lifestyle characteristics that affect fear of crime include risky lifestyle activities such as consuming alcohol and using illegal drugs, frequently partying and attending leisure activities outside of the home, engaging in criminal activities, employment, and prior experience with direct or vicarious victimization (Fisher, Sloan, Cullen, & Lu, 1998; Lasley, 1989; Mustaine, 1997). To explain the relationship between lifestyle activities and personal characteristics and fear of crime, routine activities theory and lifestyle/exposure theory are often offered as appropriate foundations. Routine activities theory states that a suitable target, a motivated offender, and a lack of a capable guardian all must converge in time and space for a crime to occur (Cohen & Felson, 1979). Lifestyle/exposure theory proposes that certain lifestyle characteristics either increase or decrease an individual’s risk for being the target of victimization (Hindelang, Gottfredson, & Garofalo, 1978). Together, these theories have been used by criminologists to explain how, where, and why criminal events occur. The research presented here extends the application of these theoretical perspectives beyond the understanding of criminal events by testing if lifestyle activities and personal characteristics affect the fear of crime among a national sample of college and university students and if these relationships vary significantly across time of day. Examining college and university students and their associated levels of fear separate from the general population is appropriate because of the unique characteristics of both college and university campuses and students. Many college and university students, perhaps because of their age or socially prolonged adolescence, engage in risky activities, such as excessively drinking alcohol, illicitly using drugs, partying, and committing criminal acts. They are also more likely than individuals in the general population to leave their belongings unattended, reside with individuals they do not know or have only known for a short time, and reside in dorm rooms or apartments with a large concentration of expensive and relatively portable belongings (e.g., computers, TVs, DVD players, and other electronics) in one place (Fisher et al., 1998; Schwartz & Pitts, 1995). It is likely that lifestyle characteristics increase the likelihood that students will be victims of property or violent crimes, but it is unknown how these relationships contribute to students’ levels of fear. While many studies have assessed the fear of crime in general and on college and university campuses, the research presented here addresses the need to study unique populations and how their lifestyle and routine behaviors contribute to their fear and perceptions of crime.

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This research identifies the complexity of these relationships first by presenting a brief review of the related literature. Then, using data collected across several US college and university campuses, levels of fear of crime for three specific victimizations separately measured across different times of day (i.e., day and night) are regressed on personal characteristics and measures of lifestyle activities. Finally, conclusions and suggestions for future research are offered.

Literature Review Routine Activities & Lifestyle/Exposure Theory At the root of the present investigation is the idea that there are certain lifestyle activities and personal characteristics that affect college and university students’ fear of crime. The theoretical perspective that might best explain this phenomenon includes the interrelated propositions of routine activities theory and lifestyle/ exposure theory. Cohen and Felson (1979) proposed a routine activities theory of crime to explain the rising crime rates in the United States after World War II. Their theory suggests that after World War II, Americans began spending more time outside of their homes, either working or engaging in leisure activities; these changes in lifestyle and behaviors put individuals at a greater risk for victimization. More suitable targets became available because homes were left unattended for extended periods of time and individuals often found themselves in unfamiliar places. Based on these assumptions, Cohen and Felson concluded that for a crime to occur, there had to be a convergence in time and space of a motivated offender, a suitable target, and a lack of a capable guardian. Hindelang et al. (1978) proposed a similar theory that used an individual’s lifestyle as a basis for victimization exposure. This lifestyle exposure theory argued that there are certain personal characteristics and lifestyle activities that increase or decrease an individual’s risk of victimization. These can include age, gender, employment status, and marital status. With this in mind, certain groups can be expected to have a higher risk for both property and violent victimization. That is, due to variations in lifestyle, individuals who are young, male, unemployed, and unmarried experience greater risks due to increased exposure. Subsequent research has shown that risky lifestyle activities, such as drinking, using illegal drugs, and frequenting bars and clubs, also puts individuals, particularly women, at a higher risk of victimization (Lasley, 1989; Messman-Moore, Coates, Gaffey, & Johnson, 2008; Mustaine & Tewksbury, 2002; Schwartz & Pitts, 1995; Tewksbury & Mustaine, 2000). Schwartz and Pitts (1995) conducted one of the first studies specifically examining the routine activities and lifestyle behaviors of college and university students that can be expected to predict victimization. They tested the suitable target component of routine activities to determine if lifestyle behaviors increased the likelihood of being the victim of rape or sexual assault among college and university women. They found that the most significant predictor of rape and sexual assault was the number of times a woman went out drinking; further, they also found that women who frequented bars more often experienced more unwanted advances from

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strangers, supporting the idea that women who place themselves in risky situations are more likely to be victimized. This research suggests that certain groups or individuals are at a higher risk for victimization because they might represent an easier target, but Schwartz and Pitts specifically did not consider offender motivation or presence of capable guardianship. To further the understanding of the ability of routine activities and lifestyle/ exposure theory to explain victimization, Fisher et al. (1998) examined a combined routine activity-lifestyle approach to explain crime on college and university campuses. Their study offers an extension of prior research by comprehensively examining the source and level of all types of student victimizations rather than just crimes against women, which most previous studies examining this theoretical perspective have done. They tested four components of this combined perspective (i.e., proximity to crime, exposure to crime, target attractiveness, and lack of capable guardianship) using a large, nationally representative sample of college and university men and women. The results from Fisher et al.’s (1998) research suggested that crime does occur on college and university campuses with some frequency and that specific personal characteristics made certain students more likely to be victimized. Their results suggest that college students might underestimate their risk of having their belongings stolen, because many reported leaving their property unattended and unprotected; this perception or misperception of risk could be critically important. Students’ property victimization also could be due to the frequency with which they have a large concentration of valuable items (e.g., computers, books, stereos, TVs, and other electronics) confined to one small personal place, such as a dorm room or apartment. In general, Fisher at al. (1998) found that the rate of on-campus victimizations was higher than the off-campus victimization rate, but this varied by specific victimization events. Assault and burglary more frequently occurred offcampus, but rape and sexual assault, larceny/theft, and harassment were committed more frequently on-campus; this suggests that a more complex and contextual causal process could exist for specific crimes and victimization events. In a partial identification of this process, Fisher et al. (1998) found that certain lifestyle characteristics predicted victimization. Students who lived in an all-male dorm or a coed dorm were at an increased risk for on-campus theft victimization compared to those who lived off-campus or in an all-female dorm. Males are frequently found to be more active participants in criminal events, and living in greater proximity to a higher concentration of males could be a plausible explanation for this increased likelihood of victimization. Among other findings, it is interesting to note that students who attended parties several nights per week on campus and students who engaged in recreational drug use had a higher likelihood of experiencing a violent victimization. They also found that taking preventive measures to protect their possessions and participating in campus crime-prevention seminars coincided with a lower level of victimization among the students in their sample. In general, Fisher et al. found support for the combined routine activitieslifestyle approach to explaining victimization on college and university campuses. Although academic campuses have long been considered safe and isolated from the horrors of the real world, this research affirms that crimes are committed within their borders and the complexity of these events warrants further study.

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Mustaine and Tewksbury (1998) also used a routine activities-lifestyle approach to attempt to explain larceny theft victimization among college and university students. With a sample that included students enrolled in twelve different colleges and universities across eight states, they found that in addition to gender and race, larceny theft victimizations were predicted by several lifestyle activities including smoking marijuana, eating out frequently, engaging in athletic activities on public courts, belonging to many clubs and organizations, and leaving home often for studying. In a subsequent analysis of college and university women victimization, Mustaine and Tewksbury (2002) integrated components of routine activities theory into a feminist framework. One finding that emerged from this research (and is contrary to routine activities theory) indicated that protective behaviors of women, such as carrying a self-protective device like mace, an alarm, gun, or knife, did not decrease their attractiveness as suitable targets. This could be explained by research that has shown that between 84 % and 90% of rapes and sexual assaults are committed by offenders who are known to their victims (Koss, 1985; Koss, Gidycz, & Wisniewski, 1987; Fisher et al., 1998); these offenders can include current or former boyfriends, acquaintances, coworkers, and classmates. Because of the nature of their relationship with the potential offenders, women who were more inclined to use self-protective behaviors in general were less likely to utilize these behaviors when they were with people they knew; this reduced their ability to protect themselves from their most likely offenders. This is further evidence that college students misperceive their actual victimization risk. An additional finding from Mustaine and Tewksbury’s (2002) research was that certain leisure activities, such as spending time with friends and going out at night increased a woman’s risk of being sexually assaulted. In general, participation in clubs, organizations, and athletic teams also increased victimization rates for women. These findings support prior research that indicated that people who leave their homes often, particularly in the evening, experience higher rates of victimization (Miethe, Stafford, & Sloane, 1990). Similar to Schwartz and Pitts (1995), the results of Mustaine and Tewksbury’s (2002) research provided limited support for a routine activities explanation of rape and sexual assault, as objective measures of target attractiveness and guardianship behaviors were not significantly related to victimization. The results from studies attempting to explain the victimization of college and university students using a routine activities and/or a lifestyle approach have indicated that at least some support for the theories exists, but the research has consistently found that there are certain components of routine activities and lifestyle theories that increase college and university students risk of victimization. Going out at night, frequenting bars or clubs, consuming alcohol and using illegal drugs, participation in many clubs, organizations, or athletic teams, and living with all males or in a co-ed dormitory increase victimization risks for students. What these analyses have not determined is if these relationships to victimization also explain students’ fear. Based upon some of this research (e.g., Fisher et al., 1998; Mustaine & Tewksbury, 2002) it is likely that students’ familiarity with their surroundings or their acquaintances decreases their perceptions of risk for victimization and this could be associated with decreased measures of fear of crime. Warr (2000) has

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suggested a similar relationship exists, in more general terms, between over- and under-exaggerated perceptions of risk for specific crimes and the associated fear of crime. Victimization and Fear A separate body of research has suggested that individuals who have been directly victimized are more likely to have heightened perceptions of victimization risk (Taylor & Hale, 1986). Also, an individual who knows someone who has been victimized, such as a family member or friend, is likely to be more fearful of victimization than one who does not know someone who has been victimized. Among individuals in the general population, research assessing the relationship between vicarious and direct victimization and an individuals’ fear of crime has been mixed. Within this literature, research has found that prior victimization is a strong predictor of perceived risk and fear (Fisher, Sloan, & Wilkins, 1995; LaGrange, Ferraro, & Supancic, 1992; Smith & Hill, 1991; Ollenburger, 1981); however, there are several studies that have indicated prior victimization is a poor predictor of fear of crime or is not related to fear of crime at all (Hindelang et al., 1978; Garofalo, 1979; Hill, Howell, & Driver, 1985). There is also some limited evidence that vicarious victimization is related to fear of crime (Ollenburger, 1981; Skogan & Maxfield, 1981). With this evidence in mind, it is difficult to determine which type of victimization experiences has the strongest relationship with fear. It would seem reasonable to suspect that college and university students who frequently engage in risky behaviors would have a lesser fear of crime than college and university students who do not engage in these behaviors, because those students who engage in risky behaviors might be doing so because they have a diminished expectation for the consequences of their behaviors. The body of research focusing on fear of crime among college and university students is fairly limited, and much of the literature that does exist has specifically examined fear of rape and sexual assault of college and university women (e.g., Day, 1994; Fisher & Sloan, 2003; Hickman & Muehlenhard, 1997; Hughes, Marshall, & Sherrill, 2003; McCreedy & Dennis, 1996). One important finding that has emerged from this research, however, is the relationship between the fear of rape and sexual assault and fear of other crimes. Examinations of this relationship, termed the shadow of sexual assault, have consistently found that fear of rape and sexual assault is related to fear of other, nonsexual crimes, including theft, robbery and assault (Ferraro, 1995, 1996; Fisher & Sloan, 2003; Hilinski, 2009; Wilcox, Jordan, & Pritchard, 2007). Thus, it is important to consider this unique relationship when measuring fear of crime. The few studies that have examined fear of crime on college and university campuses more generally have found that students are fearful of crime and that there are a variety of factors that affect students’ levels of fear of crime. These factors include prior direct and vicarious victimization, perceived risk of crime, constrained behaviors, perceptions of crime and disorder, gender, time of day, situational variables, such as the number of people around, and factors pertaining to the physical environment of the campus, such as the amount of green space on campus, lighting, and the number of potential hiding places (Fisher & Sloan, 2003; Fisher &

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Nasar, 1995; Fisher et al. 1995; Hilinski, 2009; Hilinski, 2010; Sloan, Fisher, & Wilkins, 1996). Absent from these studies is a direct examination of risky behaviors and other lifestyle characteristics. The preceding discussion has established that college and university students engage in risky behaviors, that risky behaviors increase the risk of victimization but also might be associated with diminished perceptions of risk, and that prior victimization experiences result in higher levels of fear. To date, there has not been a study that has attempted to connect the link between these three factors. That is, no research has examined simultaneously the impact of lifestyle characteristics and victimization experiences on fear of crime among college students. The present research seeks to fill this gap by determining if the risky lifestyle behaviors of college and university students are related to a decreased measure of fear of victimization.

Methods Sample This investigation examined the complex relationship that situational and personal characteristics have with college and university student’s fear of crime and victimization. The sample for the current research includes college and university students enrolled at twelve different colleges and universities across the nation and is drawn from data collected by Fisher, Sloan, and Cullen (2000). Fisher, Sloan, and Cullen used a stratified random sampling strategy by first compiling a list of all fouryear institutions that were included in the Department of Education’s State Higher Education Profiles. These schools were stratified across total enrollment and school location. Four enrollment strata (1,000-2,499; 2,500-9,999; 10,000-19,999; 20,000 or more) and three school location strata (urban, suburban, small town/rural) were identified, and one school was randomly selected from each stratum for a total of twelve different institutions (for a more in-depth discussion of the sampling and data collection procedures, see Fisher et al., 1998). The final sample consisted of 3,472 college and university men and women who were enrolled full-time or part-time at the colleges and universities included in the sample. Descriptive statistics and construct coding strategies are reported in Table 1. Dependent Variables Several dependent variables are examined in the following analyses that represent measures of each student’s fear of larceny/theft, aggravated assault, and rape/sexual assault. The data allow for separate measurements of fear across temporal situations (i.e., during the day and at night) to assess more specifically the fear of victimization experiences. Analytical comparisons between fear of crime at night and during the day are presented after an analysis of the fear of crime at night. These disaggregated measures of fear are used because research has found that fear of crime varies across temporal situations (Day, 1994) and that the majority of crimes on the college campus occur after 6 p.m. (Fisher et al., 1998). Each of the dependent variables was measured with a ten-point scale ranging from (1) not at all afraid to (10) very afraid.

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Table 1 Descriptive statistics

Fear of Theft-Night

Coding

Mean

Median

Standard Deviation

Range

1=not at all afraid

2.54

2.00

1.987

1–10

2.52

2.00

2.135

1–10

2.49

1.00

2.318

1–10

24.16

22.00

6.630

Percent

10=very afraid

Fear of Aggravated Assault-Night

10=very afraid

1=not at all afraid

Fear of Rape/Sexual Assault-Night

10=very afraid

Age

Years

Gender

0=male

1=not at all afraid

17–60 0–1

56% female

0–1

78 % white

0–1

87.4% full-time

1=female Race

0=nonwhite 1=white

Enrollment Status

0=full-time 1=part-time

Partying

# Nights partying on- and off-campus per week

3.70

3.00

1.698

2–12

Activities & Entertainment

events attended

4.444

5.00

1.757

2–8

Employment

per month 0=employed

0–1

1=unemployed Money Spent on Nonessentials

Dollar value

33.62

25.00

27.280

1–150

Likelihood of Drinking

1=not very likely

4.29

3.00

3.496

1–10

5.31

4.00

3.137

4–40

3.2607

4.0

1.03495

1–4

2.7342

2.8

.47076

1–4

Criminal Propensity

38% unemployed

10=very likely 1=not very likely 40=very likely

Avoidance Behaviors

1=always 2=frequently 3=sometimes 4=never

Defensive Behaviors

1=always 2=frequently 3=sometimes 4=never

Theft Rate

per 1,000 students

11.1529

4.0500

12.29837

1.51–15.80

Robbery Rate

per 1,000 students

3.4759

1.5600

4.22384

.48–15.80

Assault Rate

per 1,000 students

2.6418

.9200

2.65990

.34–8.20

Sexual Assault Rate

per 1,000 students

1.1598

.3720

1.57446

Direct Property Victimization

0=no

Direct Violent Victimization

0=no

.09–4.50 0–1

27% victimized

0–1

10% victimized

1=yes 1=yes

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Table 1 (continued) Coding

Vicarious Property Victimization

Mean

Median

Standard Deviation

0=no

Range

Percent

0–1

38% exposed

0–1

19% exposed

1=yes

Vicarious Violent Victimization

1=yes

0=no

Perceived Risk of Theft

10=very likely

1=not at likely 1=not at likely

Perceived Risk of Aggravated Assault

10=very likely

Perceived Risk of Rape/Sexual Assault

10=very likely

1=not at likely

3.0416

3.0

1.94498

1–10

1.7268

1.0

1.27298

1–10

1.7211

1.0

1.37421

1–10

Independent Variables Existing research has identified that there are certain lifestyle characteristics, such as drinking, using illegal drugs, and frequenting bars and clubs, that put individuals at an increased risk for both violent and property victimization (Day, 1994; Fisher et al., 1998; Mustaine & Tewksbury, 1998, 2002) and certain lifestyle characteristics that might reduce their risk of victimization, such as constrained behaviors (Fisher, et al., 1998). Based on these findings, the following lifestyle characteristics are included in the analysis as independent variables: engaging in parties on- and offcampus, participation in recreational activities, employment status, amount of money spent each week on nonessential items, the respondent’s likelihood of drinking, criminal propensity, which includes a composite measure of the likelihood of driving under the influence, using illegal drugs, committing vandalism, and committing larceny/theft, and constrained behaviors, which include a variable for avoidance behaviors (avoiding certain areas because of fear) and defensive behaviors (e.g., carrying keys in a defensive manner, utilizing campus safety programs, asking someone to watch your belongings when leaving them unattended).1 Existing research also has suggested that both direct and vicarious victimization has a complex relationship with fear of crime. Considering the mixed conclusions reviewed above, measures of direct and vicarious victimizations are included in this analysis in an attempt to further examine and specify these relationships. These measures include prior direct property and violent victimization and prior vicarious property and violent victimization. The official theft, robbery, assault, and sexual assault rates for each of the twelve institutions also are included in the analysis to provide an objective measure of localized victimization risk. Perceived risk of crime also was included as an independent variable. The parallel measure of perceived risk was included in the models assessing fear (e.g., in the model estimating fear of theft, 1

These composite variables are based on the conceptual similarity of survey items.

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the measure of perceived risk of theft was included). Further, fear of rape and sexual assault also was included in the models estimating fear of theft and fear of aggravated assault; this measure was included to control for any possible relationships fear of rape and sexual assault might have with fear of theft or aggravated assault, and this strategy is similar to research conducted by Ferraro (1995, 1996), Fisher and Sloan (2003), Hilinski (2009), and Wilcox et al. (2007). Additional control variables also have been included in the analysis. These include the age, gender, race, and enrollment status (full-time or part-time) of each student. These are included to control for the anticipated relationships that certain segments of the population are likely to have with victimization and fear based on extant research.

Results Analyses were conducted over three stages using SPSS. First, bivariate correlations were computed and analyzed. The bivariate correlations2 computed for each of the variables reveal that none of the variables were highly correlated with each other. Tolerance statistics and variance inflation factors also were computed for each of the variables used in subsequent multivariate analyses. For all models, tolerance statistics exceeded .2, and the variance inflation factors were all below 4, indicating that all of the variables are independent of each other. Thus, collinearity was determined not to be an issue (Mertler & Vannatta, 2002). The second stage of analysis included multivariate analysis beginning with a series of Ordinary Least Squares (OLS) regression models that were estimated to identify the baseline relationship between fear of various forms of crime at night while controlling for demographic variables (identified as Model 1 across tables). Subsequent models added variables of interest in conceptually-related blocks, beginning with measures of lifestyle characteristics (reported as Model 2). Regressions identified as Model 3 estimated the impact of the students’ victimization experiences as well as the measures for the official crime rates for each student’s institution and the control variables, and the fourth and full model included the control variables, lifestyle characteristics, and victimization variables, including campus victimization rates. The final analytical stage included the estimation of full regression models with the dependent variables being measured as the fear of crime during the day. These models were then compared to the models estimating the lifestyle and victimization relationships with fear of crime at night to determine empirically if fear of crime varies by time of day. Multivariate Analysis The bulk of the analysis proceeded by estimating a series of OLS regression models; these results are presented in Tables 2 through 4. Each table presents a series of models that separately examine fear of distinct crimes committed on campus at night; regression models for fear of crimes during the day were estimated for comparison purposes but are not presented here to conserve space.3 Within these 2 3

A full correlation matrix is available upon request from the first author. Tables presenting the stepwise results from these regression models are available upon request.

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Table 2 Predicting the fear of theft while on campus at night Independent Variables Model 1

Model 2

B (Se)

β

Age

−.014** (.006)

−.045 .009 (.035)

Gender

.368** (.070) .092

Race

−.401** (.085)

Enrollment Status

−.353** (.123)

B (Se)

Model 3

Model 4

β

B (Se)

β

B (Se)

β

.012

.001 (.005)

.002

−.032 (.036)

−.044

Demographics

−.129 (.205)

−.033 −.505** (.082)

−.125 −.539† (.266)

−.132

−.083 −.391† (.224)

−.077 −.263** (.090)

−.051 .221 (.302)

.037

−.056 −.904 (.702)

−.054 −.073 (.111)

−.013 −.767 (.763)

−.050

Lifestyle Partying

−.097† (.059)

−.077

−.101(.071)

−.075

Activities & Entertainment

.038 (.049)

.033

−.039 (.060)

−.032

Employment

.005 (.168)

.001

.168 (.195)

.041

Money Spent on Nonessentials

.004 (.004)

.051

.004 (.004)

.045

Likelihood of Drinking

.013 (.028)

.023

−.068† (.035)

−.113

Criminal Propensity

.092** (.032)

.136

.118** (.041)

.156

Avoidance Behaviors

−.601** (.098)

−.295

−.325** (.122)

−.157

Defensive Behaviors

−.648* (.262)

−.128

−.010 (.337)

.002 −.391

Victimization Theft Rate

.011 (.028)

.068

−.055 (.077)

Robbery Rate

.030 (.022)

.068

.038 (.054)

Assault Rate

−.057 (.059)

−.081 .063(.173)

.096

−.099 .271 (.407)

.241

.096

Sexual Assault Rate

−.127 (.136)

Direct Property

.173** (.062) .050

.069(.178)

.011

Direct Violent

.186† (.107)

.031

−.076 (.293)

−.013

Vicarious Property

.283** (.068) .068

.503* (.203)

Vicarious Violent

−.058 (.069)

−.016 −.098(.154)

.126 −.033

Perceived Risk

.318** (.020) .306

.321** (.056)

.298

Fear of Rape/ Sexual Assault

.385** (.018) .435

.345** (.058)

.393

1.023** (.190)

2.391†(1.418)

Constant

2.031** (.131)

6.613** (1.167)



.021

.140

.355

.406

F

17.371**

6.614**

85.678****

8.675**

Significance: p