Fear of Crime Out West: Determinants of Fear of Property and Violent Crime in Five States

Abstract

Fear of crime research has been around for decades, and many studies of its extent, nature, and consequences have been published. In this study, we build upon existing research to examine the effects of vulnerability, disorder/incivilities, social cohesion, prior victimization, and perceptions of police upon fear of property crime and fear of violent crime. Using data from a random mail survey of residents from five different states, the current study offers a view of the determinants of fear of crime within an often overlooked population—residents of the Western United States. Results support leading theories of fear of crime, finding that women, perceptions of disorder/incivilities, perceptions of social cohesion, prior victimization, and assessments of police quality of service each influence fear of crime. Findings also suggest that the determinants of fear of crime vary somewhat according to crime type.

Keywords

fear disorder property crime violent crime social cohesion victimization

Introduction

Five decades have passed since the release of the President’s Commission on Law Enforcement and Administration of Justice report that identified fear of crime as a significant social problem in the United States (U.S. President’s Commission on Law Enforcement and the Administration of Justice, 1967). In that report, the Commission noted that fear of crime was pervasive and had “eroded the basic quality of life of many Americans” (U.S. President’s Commission on Law Enforcement and the Administration of Justice, 1967, p. v). Such strong statements sparked researchers’ interests in studying fear of crime, and in the years since the report’s release, innumerable studies of fear of crime have been published (e.g., Ferraro, 1995; Hale, 1996; Henson & Reyns, 2015; Warr, 2000).

These studies have answered many research questions about the extent, nature, and consequences of fear of crime and expanded the knowledge base in this area significantly (e.g., see Hale, 1996; Henson & Reyns, 2015; Lane et al., 2014; Warr, 2000, for reviews). At the same time, the United States is geographically and culturally diverse, and fear of crime research studies are needed that reflect this diversity. In particular, researchers have been slow to study the dynamics of fear of crime in states “West of the Mississippi.” Although existing theory does not suggest that criminological determinants of fear of crime may vary regionally, replication of findings from prior work is needed to establish the veracity of these findings and theories. Thus, the current study addresses four research questions related to predictors of crime-specific fear of crime using data from residents of five states—Idaho, Montana, South Dakota, Washington, and Wyoming. Although fear of crime research has been undertaken in some of these states, the current study is the first to utilize multistate data from the region (e.g., Crank et al., 2003; Rountree & Land, 1996).

First, the present study examines a vulnerability model of fear of crime. Theoretically, individuals who view themselves as vulnerable to criminal victimization are more likely to be fearful of falling prey to crime (e.g., Hale, 1996; Henson & Reyns, 2015; Katz et al., 2003; Killias & Clerici, 2000; Lane et al., 2014; Warr, 2000). Research suggests that the sources of that perceived vulnerability are derived from physical characteristics (e.g., age, gender) and social characteristics (e.g., income, education), and research has generally found that vulnerability is associated with fear of crime (e.g., C. A. Franklin & Franklin, 2009; Haynie, 1998; Henson & Reyns, 2015; Liska et al., 1988; Skogan & Maxfield, 1981). Therefore, the current study hypothesizes that physical and social vulnerability—operationalized as age, gender, income, and education—will be predictive of individuals’ fear of crime.

Second, the present research examines contextual influences upon fear of crime. Prior research and theory suggest that environmental characteristics send signals to individuals about the relative safety or danger of their environments (e.g., Brunton-Smith & Sturgis, 2011; Ferraro, 1995; Like, 2011; Maxfield, 1984; Swartz et al., 2011; Wilson & Kelling, 1982) and that specific signals or cues are associated with feelings of fear. In particular, the presence of physical signs of disorder and/or incivilities signal to site users that problems in this environment have not been addressed, and, therefore, any problems they encounter will also likely go unchecked. Overall then, the current study addresses whether signs of physical disorder and/or incivilities are associated with heightened fear of crime as reported in prior research (e.g., Covington & Taylor, 1991; LaGrange et al., 1992; Lewis & Salem, 1986; Skogan, 1990).

Third, and in a related manner, past research and theory into the determinants of fear of crime suggest that environmental signals—beyond the absence of disorder and incivilities—can affect individuals’ feelings of safety or fear. Specifically, socially cohesive locations are associated with feelings of safety and a decrease in fear of crime (e.g., Alper & Chappell, 2012; Covington & Taylor, 1991; Gibson et al., 2002; Hale, 1996; Henson & Reyns, 2015). For instance, residents in neighborhoods that have strong social ties among neighbors and a sense of collective efficacy are less likely to experience fear of crime because they have a sense that others will help them if trouble arises. Therefore, the present study tests this hypothesis within our Western population by examining the relationship between social cohesion and fear of crime.

Fourth and finally, the relationship between previous experiences with crime and fear of crime is explored. Studies of victimization indicate that the consequences of being a crime victim are varied, and can be severe (e.g., Black et al., 2011; Shapland & Hall, 2007; Truman, 2011). Fear of crime is among these consequences. Principally, this is because those who have been victimized estimate or perceive their likelihood of subsequent victimization to be high—and perceived risk of victimization is among the strongest correlates of fear of crime (e.g., T. W. Franklin et al., 2008; Gainey et al., 2011; Rountree & Land, 1996). The present research tests this possibility, hypothesizing a significant and positive relationship between prior victimization and fear of crime.

In sum, the present study aims to replicate findings in the extant literature regarding contemporary explanatory models of fear of crime. Specifically, we assess the effects of vulnerability, disorder/incivilities, social cohesion, and prior victimization upon two crime-specific models of fear of crime—fear of violent crime and fear of property crime. Taking this more targeted approach to fear of crime promotes a more comprehensive understanding of fear of crime and its nuances (e.g., LaGrange & Ferraro, 1989; Rountree & Land, 1996; Yuan & McNeeley, 2017). To do so, we analyze survey data collected through the Western Regional Institute of Community Oriented Public Services’ 2001 Community Policing Survey. These data provide an opportunity to consider leading models of fear of crime within previously unexamined populations in the fear of crime literature, including residents of Idaho, Montana, South Dakota, Washington, and Wyoming.

Theoretical Framework

Vulnerability Model

The vulnerability model posits that one’s personal characteristics are associated with perceptions that they are as less physically capable to defend against victimization experiences, and as such are more fearful of crime (e.g., Barton et al., 2016; Bolger & Bolger, 2019; Ceccato & Bamzar, 2016; Lane & Fox, 2013; Lytle & Randa, 2015; Weinrath, 2000). Research designs employing a vulnerability model note that in regard to gender, females exhibit higher levels of fear (e.g., Clemente & Kleiman, 1976; McGarrell et al., 1997; Scarborough et al., 2010; Weinrath, 2000; Zhao et al., 2015). In regard to age, it has been reported that older persons tend to exhibit higher levels of fear (Abdullah et al., 2013; Lane & Fox, 2013; Scarborough et al., 2010; Weinrath, 2000). Other factors considered by vulnerability models generally find that non-Whites and persons with lower levels of education exhibit higher levels of fear (Like, 2011; Scarborough et al., 2010; Yuan et al., 2017); yet, these results are not always consistent across studies.

Disorder/Incivilities Model

The disorder and incivilities models posit that fear of crime is driven by perceptions of disorder witnessed by persons within their neighborhoods and communities. These concepts are similar to those established by Wilson and Kelling (1982) regarding metaphorical and literal broken windows as signs of decay. These theories generally differentiate between social disorder (e.g., public intoxication, vagrancy, corner gangs) and physical disorder (e.g., graffiti, damaged buildings, litter) as a means of explaining fear, noting that persons often perceive such disorder as a lack of societal cohesion in regard to responding to such problems, which, in turn, increases fear (e.g., Abdullah et al., 2013; Doran & Lees, 2005; Ferraro, 1996; Luo et al., 2016; Lytle & Randa, 2015; Renauer, 2007; Roh & Oliver, 2005; Scarborough et al., 2010; Scheider et al., 2003; Wyant, 2008). Overall, then, disorder and incivilities are hypothesized to be associated with higher fear of crime.

Social Integration/Collective Efficacy Models

Another means of assessing causal factors for fear of crime is the social integration model, which essentially represents the inverse of the disorder/incivilities perspective. The social integration or collective efficacy model of fear of crime focuses on one’s cohesion and cooperation with neighbors, as well as police, in an effort to establish informal social controls at the neighborhood level. Greater social controls are hypothesized to inhibit crime, thus decreasing fear of crime (e.g., Barton et al., 2016; Hale, 1996; Lane & Fox, 2012; Yuan et al., 2017; Yuan & McNeeley, 2017). This model suggests that when one perceives their neighborhood support as capable of preventing crime or operating for a collective good, on a neighborhood level, fear of crime is reduced.

Victimization Model

Research has also found that victimization experiences have the potential to increase fear of crime. Yet, the conceptualization of victimization tends to vary between direct victimization, wherein one’s own experiences being victimized increase future levels of fear, and vicarious victimization, wherein the victimization experiences of friends, family, and coworkers increase one’s own level of fear (e.g., Cook & Fox, 2011; Fox et al., 2009; Garofalo, 1981; Luo et al., 2016; May et al., 2010; Taylor & Hale, 1986; Rountree & Land, 1996; Yuan & McNeeley, 2017). Still, victimization, whether direct or vicarious, has often been found to increase both fear of violent and property crimes in recent studies (e.g., Alper & Chappell, 2012; Henson et al., 2013; Lane & Fox, 2013; Randa, 2013), although findings are somewhat mixed as research has also shown that victimization may have no effect on, or even decrease fear (Cook & Fox, 2011; Fox et al., 2009).

Literature Review

Factors Affecting Fear of Property Crime

The study of crime-specific fear has risen in prominence in recent years among researchers, who note the shortcomings of nonspecific measures of “fear of crime” (e.g., Pleggenkuhle & Schafer, 2018; Yuan & McNeeley, 2017). Studies have thus begun to employ crime-specific models, acknowledging that factors inhibiting or promoting fear of larceny may differ from those affecting assault, for instance. Studies examining fear of property-related crime—generally operationalized as burglary or theft—report that several factors are associated with increases in fear.

When analyzing personal characteristics, including race, age, and gender, research has reported that White persons indicate higher levels of fear of property crime than do persons of Other races (e.g., Lane & Fox, 2013; Mrozla et al., 2018). When analyzing age in regard to property crime, researchers consistently contend that age has a positive relationship with fear of property crime (e.g., Chon & Wilson, 2016; Ferraro, 1996; Henson & Reyns, 2015; Lane & Fox, 2012). Finally, researchers have often reported that females are more fearful of property crime across studies (e.g., Chon & Wilson, 2016; Cossman & Rader, 2011; Ferraro, 1996; Lane et al., 2009).

The presence of disorder, whether physical or social, is commonly examined in many studies regarding fear of crime (e.g., Scarborough et al., 2010; Wilson & Kelling, 1982). These studies find that the increased perception by citizens of physical and social signs of decay present in a community is associated with fear of crime, with little evidence to the contrary (e.g., LaGrange et al., 1992; Lane & Fox, 2012; Luo et al., 2016; Wyant, 2008). This theme is exemplified in C. A. Franklin and Franklin’s (2009) analysis, wherein disorder was cited as mediating fear of crime to a greater extent than aforementioned vulnerability or social integration models among respondents.

Social cohesion is also a factor considered by many researchers when analyzing fear of property crime (e.g., Baron, 2011; Covington & Taylor, 1991; Lane & Fox, 2012; Renauer, 2007; Yuan & McNeeley, 2017). Social cohesion models typically posit that willingness to assist neighbors, high degrees of social capital among communities, and informal social control among residents serve to inhibit the onset of fear of crime (e.g., Scarborough et al., 2010; Yuan & McNeeley, 2017). Renauer’s (2007) analysis confirms this notion, identifying social cohesion as having an inverse relationship, noting that residents who perceive high levels of trust and value sharing with neighbors are significantly less fearful.

Victimization is a consistently employed factor when studying fear of crime, but its effects on fear tend to differ based on how it is operationalized (Fox et al., 2009; May et al., 2010; Miethe & Lee, 1984). Lane et al.’s (2009) study, which addressed this issue, reported an increase of fear of property crime by respondents with prior victimization experiences. A related determinant of fear of property crime is satisfaction among citizens with the quality of police services, wherein it is argued that community satisfaction with police will reduce fears of crime (e.g., Lai et al., 2012; Luo et al., 2016; Lytle & Randa, 2015; May et al., 2010; Renauer, 2007; Scheider et al., 2003). In a recent study, Bolger and Bolger (2019) confirm this, identifying low levels of police satisfaction as contributing to increased levels of fear of crime among respondents.

Factors Affecting Fear of Violent Crime

Fear of violent crime has typically been conceptualized as fear of forcible sexual crimes, assault, or threats of violence and may be more broadly understood as differing from property-specific fear of crime in that losses suffered are physical rather than material (e.g., Grubb & Bouffard, 2015; Lane & Fox, 2013). In his seminal study, Garofalo (1981) defines fear of crime as applying generally to violent crime, whereas factors concerning property crime are generally referred to as worry regarding crime, as fear is synonymous with danger.

With respect to the links between personal characteristics and fear of violent crime, non-White persons generally rank higher in regard to fear of crime, with African American and Hispanic persons reportedly being most fearful (e.g., Lane et al., 2009; Lane & Fox, 2013; Lane & Meeker, 2003; Yuan et al., 2017). Gender is perhaps the most frequently cited correlate of fear of violence, with research reporting that females are more fearful than males, which is consistent with the vulnerability thesis (e.g., Cossman & Rader, 2011; Lane & Fox, 2012; Lane & Meeker, 2003; Mrozla et al., 2018; Pleggenkuhle & Schafer, 2018; Yuan et al., 2017). Pleggenkuhle and Schafer’s (2018) analysis support this, identifying females with lower educational achievement as substantially more fearful. Furthermore, Rader et al. (2012) noted the value of age as a factor in explaining fear of crime, finding older persons as typically more fearful among respondents.

The presence of disorder, when analyzed in conjunction with fear of crime, generally demonstrates similar findings to those of property crime–related fear, in that, disorder, both physical and social, tends to increase perceived fear of violent crime (e.g., Luo et al., 2016; Renauer, 2007). This is consistent with Lane and Fox’s (2012) study, which discovered fear of both violent and property crime as positively related to the perceived presence of social and physical disorders among respondents.

Social cohesion and collective efficacy, cited previously as common factors regarding fear of property crime, are similarly common when analyzing violent crime. As previously noted, studies analyzing social cohesion alongside fear of violent crime tend to demonstrate similar patterns as that of cohesion affecting property crime, in that, social cohesion and collective efficacy tend to demonstrate a negative relationship with fear of violent crime (e.g., Alper & Chappell, 2012; Renauer, 2007). Yuan and McNeeley’s (2017) analysis confirms notions outlined above, identifying perceived collective efficacy as related to decreased levels of fear of violent crime.

Regarding the effect of victimization and vicarious victimization toward fear of violent crime, findings typically identify victimization as significantly contributing to fear (Garofalo, 1979, 1981; Miethe & Lee, 1984; Rader, 2004; Taylor & Hale, 1986). An additional factor found to frequently affect fear of crime is quality of police services—often referred to as police satisfaction. As previously cited in regard to fear of property crime, police satisfaction is hypothesized to decrease levels of fear because individuals with confidence in the police have faith that the police will be effective in responding to and preventing neighborhood crime (e.g., Luo et al., 2016; Renauer, 2007).

Method

Data

In 2001, the Western Regional Institute Community Oriented Public Safety (WRICOPS) survey was sponsored by the Western Regional Institute and administered in five states (Idaho, Montana, South Dakota, Washington, and Wyoming). Data were collected for a period of nearly 1 year (October 1999 to August 2000) via mail surveys to respondents’ residences. From the states that were chosen, a random sample of households was selected to receive the survey, which resulted in a final sample of 923 randomly selected households. Due to the small sample size in the data and using listwise deletion, this decreased the sample size by a 30%. In result, mean imputation was used to treat the missing cases for the analysis. Mean imputation was used for the following variables: fear of violent crime, fear of property crime, age, education, income, social disorder physical disorder, service quality, and victimization. Test for normality assumptions, multicollinearity, and homoscedasticity was conducted.¹

Measures

Dependent variables

This study has two dependent variables: fear of property crime and fear of violent crime. The fear of property crime variable was created by summing responses to two survey questions. The two survey questions were as follows: “do you worry about (1) being burglarized with someone at home; (2) being burglarized with no one at home.” A value of 1 indicated never, a value of 2 indicated seldom, a value of 3 indicated frequently, and a value of 4 indicated very frequently. The questions were coded so that a lower score indicated a lower level of worry. The range for fear of property crime was 2 to 8 with a mean of 4.18.

A measure of fear of violent crime was created by summing responses to four survey questions. The four survey questions were as follows: “do you worry about (1) being attacked while driving; (2) getting mugged; (3) getting beat up, knifed or shot; (4) getting murdered.” A value of 1 indicated never, a value of 2 indicated seldom, a value of 3 indicated frequently, and a value of 4 indicated very frequently. The questions were coded so that a lower score indicated a lower level of fear. The range for fear of violent crime was 4 to 15 with a mean of 6.39. Descriptive statistics for the dependent variables are provided in Table 1.

Table 1.

Descriptive Statistics.

	Fear of property crime		Fear of violent crime
	%/M	Scale	%/M	Scale
Dependent variable
Fear of violent crime (N = 829)			6.39	4–15
Fear of property crime (N = 829)	4.18	2–8
Independent variables
Respondent demographics
Age (year)	52.50	18–98	52.50	18–98
Race (White = 1)	92.64%	0–1	92.64%	0–1
Gender (male = 1)	59.11%	0–1	59.11%	0–1
Education	3.70	1–6	3.70	1–6
Non–high school	5.9%		5.9%
High school	21.3%		21.3%
Some college	28.7%		28.7%
Associate	9.4%		9.4%
Bachelors	14.4%		14.4%
Some graduate and graduate	20.7%		20.7%
Income	3.74	1–6	3.74	1–6
Less than US$9,999	5.5%		5.5%
US$10,000–US$19,999	13.6%		13.6%
US$20,000–US$29,999	18.4%		18.4%
US$30,000–US$49,999	26.8%		26.8%
US$50,000– and above	35.5%		35.5%
Social cohesion	8.62	2–10	8.62	2–10
Social disorder	12.95	6–24	12.95	6–24
Physical disorder	4.32	2–8	4.32	2–8
Quality of service	2.65	1–4	2.65	1–4
Victimization (yes = 1)	12.36%		12.36%

Independent variables

The demographic variables utilized in the analyses include age, race, gender, education, and income. Age was measured as a continuous variable and ranges between 18 and 98 years. Race was recoded into two groups where 0 indicated non-White and 1 indicated White. Gender was measured dichotomously where 0 indicated female and 1 indicated male. Education was measured as a six-category ordinal variable: A value 1 indicated non–high school, a value of 2 indicated high school, a value of 3 indicated some college, a value of 4 indicated associate degree, a value of 5 indicated bachelor degree, and a value of 6 indicated some graduate and graduate degree. Income was measured as a five-category ordinal variable: A value of 1 indicated less than US$9,999, a value of 2 indicated US$10,000 to US$19,999, a value of 3 indicated US$20,000 to US$29,999, a value of 4 indicated US$30,000 to US$49,999, a value of 5 indicated US$50,000 and above.

Indicators of social and physical disorders were used to measure disorder and incivilities. The social disorder variable was derived from a multipart question, which asked respondents about 16 types of disorder. For the social disorder variable, six questions were taken from this 16-part question. The questions asked respondents about the specific problems they viewed in their community, including (a) drunk drivers on the road, (b) people drinking to excess in public, (c) groups of teenagers or others hanging out and harassing people, (d) youth gangs are present, (e) people using illegal drugs, (f) noise. A measure of physical disorder was created using questions derived from the same 16-part question. This variable was operationalized by summing two questions: (a) vandalism and (b) garbage/litter. A value of 1 indicated no problem, a value of 2 indicated uncertain, a value of 3 indicated a problem, and a value of 4 indicated serious problem. Higher values of both social and physical disorders indicated higher levels of social and physical disorders in their community.

Social cohesion was created by summing two survey items. Respondents were asked the following:

(1) If you were in need of help with your car stuck in the mud or snow in front of your residence, do you have faith that your neighbors would come to your assistance? (2) Overall, how satisfied are you with your neighborhood as a place to live?

For Question 1, a value of 1 indicated very little faith, a value of 2 indicated little faith, a value of 3 indicated undecided, a value of 4 indicated some faith, and a value of 5 indicated a high level of faith. For Question 2, a value of 1 indicated very dissatisfied, a value of 2 indicated dissatisfied, a value of 3 indicated somewhat satisfied, a value of 4 indicated satisfied, and a value of 5 indicated very satisfied. Higher measures of this variable indicated a higher level of social cohesion among respondents.

Previous victimization was operationalized by asking respondents to indicate whether they were victimized in the past 12 months. Respondents were asked, “have you been the victim of a crime in the last 12 months?” A value of 0 indicated no and a value of 1 indicated yes. Respondents were also asked about their opinion of the quality of service provided by their local police department. Service quality was measured with the following statement: “please indicate your opinion of the quality of service provided by your local police department.” A value of 1 indicated poor, a value of 2 indicated fair, a value of 3 indicated good, and a value of 4 indicated excellent. Higher values on the scales indicated higher quality of service received by the respondents.

Results

Two sets of ordinary least squares (OLS) regression models were estimated for the two dependent variables: fear of property crime and fear of violent crime. According to Table 2, three demographic variables were significantly correlated to fear of property crime. Some (21%) of the variation was explained in this model (R² = .210). Age was a significant determinant of fear of property crime (b = −.007, p < .05). Gender was significant with males reporting lower fear of property crime (b = −.377, p < .001) and income was also significant (b = .061, p < .001). In addition, physical disorder was positively related to fear of property crime, with those who perceived more physical disorder (b = .160, p < .001) being more fearful of property crime. In addition, social cohesion was negatively associated with fear of property crime, with those with more social cohesion displaying less fear of property crime (b = −.126, p < .001). Quality of police service was negatively associated with fear of property crime, which suggests that higher levels of quality of police service decreased respondents’ level of fear of crime (b = −.137, p < .05). Finally, victimization was positively associated with fear of property crime as those who had been victims of a crime were more fearful of property crime (b = .567, p < .001).

Table 2.

Fear of Property Crime and Fear of Violent Crime.

Variables	Fear of property crime (N = 829)	Fear of violent crime (N = 829)
Variables	b (SE)	b (SE)
Age	−.007 (0.003)*	.003 (0.005)
Race (White = 1)	.057 (0.182)	.050 (0.281)
Gender (male = 1)	−.377 (0.098)***	−.490 (0.151)***
Education	.022 (0.033)	.083 (0.050)
Income	.061 (0.043)***	.044 (0.069)
Physical disorder	.160 (0.043)***	.188 (0.066)**
Social disorder	.069 (0.017)***	.077 (0.026)**
Social cohesion	−.126 (0.034)***	−.191 (0.052)***
Quality of service	−.137 (0.067)*	−.298 (0.102)**
Victimization	.567 (0.147)***	.258 (0.225)
Intercept	4.205 (0.450)***	6.601 (0.686)***
F test	21.742***	12.315***
R ²	.210	.131

p < .05. **p < .01. ***p < .001.

Table 2 also identifies determinants of fear of violent crime, 13.1% of the variation was explained. First, gender was significant and negatively associated with fear of violent crime (b = −.490, p < .001). Social disorder was significant with those who perceived more social disorder being more fearful of violent crime (b = .077, p < .01). Social cohesion was negatively related to fear of violent crime, with those with more social cohesion displaying less fear of violent crime (b = −.191, p < .001). Finally, those who rated police service quality as high were significantly less likely to have fear of violent crime (b = −.298, p < .01).

Discussion and Conclusion

The purpose of the present research was to address four research questions within the fear of crime literature using data from a previously unexplored population in the United States. In particular, we examine a comprehensive model of fear of crime that draws on leading theoretical perspectives to identify the predictors of fear of property crime and fear of violent crime among residents of five states. Overall, results suggest that the determinants of fear of crime “Out West” are similar to what has been reported in prior research, reinforcing the utility of these theoretical perspectives. At the same time, minor differences emerged across models of fear of property crime and fear of violent crime, which support the contention that fear of crime is crime specific (Lane & Fox, 2013; Yuan & McNeeley, 2017). Based on our findings, at least four conclusions are warranted.

First, as hypothesized, particular demographic characteristics were significantly related to fear of crime. Specifically, consistent with prior research, females were more likely to report feeling fear of both property and violent crime (Box et al., 1988; Britto et al., 2018; Pryce et al., 2018). Although gender is not a perfect measure of perceived vulnerability, it provides insights into the vulnerability perspective, potentially suggesting that females perceive a greater vulnerability to crime, and thus exhibit a higher fear of crime (Cossman & Rader, 2011; Rader et al., 2012). Interestingly, race and education were not significantly related to fear of either property crime or violent crime; although prior research has often reported inconsistent results with respect to race and education, the null effects of age are of special note (Cook & Fox, 2011; Smith & Hill, 1991). Age has been identified as a robust predictor of fear of crime in past work (LaGrange & Ferraro, 1989; Lindquist & Duke, 1982), and yet, it appears that among residents of these Western states, there is no age–fear paradox for fear of violent crime. This may be due to differences in crime rates in these specific states, and although further addressing this finding is beyond the scope of the present study, it certainly warrants further exploration in future research.

Second, perceptions of physical and social disorders were statistically significant in both models estimated. Consistent with prior research, physical and social disorders were identified as strong predictors of both fear of property crime and fear of violent crime (Brunton-Smith, 2011; Gainey et al., 2011; Markowitz et al., 2001). Reducing perceived incivilities and improving the minor quality-of-life issues in the community may decrease fear of property and violent crime for community members. Thus, our findings support the utility of these theoretical perspectives as explanations of fear of crime in general, as well as crime-specific fears.

Third and similarly, social cohesion was negatively related to fear of property crime and fear of violent crime. Once again, this is consistent with theoretical expectations and prior research (Lee & Earnest, 2003; Renauer, 2007). Taken together, these variable effects suggest that contextual influences on fear of crime, whether considered generally or with crime-specific measures, are universal. In other words, environmental factors influence individuals’ perceptions of safety across the United States and across communities within the United States.

Fourth, the present study considered the effects of prior victimization and assessments of the quality of police services as possible explanations of fear of crime. These variable effects offer a nuanced view of fear of crime. In particular, prior victimization influenced fear of property crime but not fear of violent crime. Here, it may be prior property victimization is driving individuals’ perceptions of their likelihood of further property victimization, thus affecting their fear of property crime. After all, property crime is substantially more common than violent crime (Truman, 2011). However, this is a measurement issue that cannot be addressed further with the present data, as the survey item used to measure prior victimization simply asked about “crime” without specifying a type of crime. In addition, individuals who rated the quality of their police services highly were less likely to report fear of violent crime and property crime. This suggests a dynamic similar to that observed for social cohesion. Namely, residents have confidence that any problems with violent crime will be effectively addressed by the police in their community. It may also be that residents view violent crimes as those most likely to get a concerted police response. Regardless, the effects of residents’ satisfaction with police upon fear of crime is mostly consistent with prior research (Lai et al., 2012; Lytle & Randa, 2015).

Taken collectively, results from the present study largely support findings from previous research. This suggests that the determinants of fear of crime are essentially the same in Western states as they are throughout the United States—or at least in regions and states that have been examined in the extant fear of crime research. However, some of our variable effects differ from results reported in prior work. This may be due, in part, to cultural differences as this region has been identified as culturally and behaviorally distinct within the larger United States (Gastil, 1973). Furthermore, as Pain (2000) has suggested, “fear of crime is historically and socially specific” (p. 379), and that influences on fear should be considered together along with their geographically situated context. In other words, although existing criminological perspectives on fear of crime do not argue for variability in theoretical effects by culture or region, it is entirely possible that this variation exists, and future research should continue to test the validity of leading theories of fear with an eye toward these cultural and contextual effects.

Limitations

Although the present study addressed four research questions and largely replicated findings from prior research related to the determinants of fear of crime within a unique population, the results should nevertheless be considered in light of the study’s potential limitations. Primarily, as with much research, this study utilized secondary data, and as such, ideal measures of theoretical concepts of interest were not always available. Specifically, we rely on demographic proxies to represent perceptions of vulnerability. Although it would have been preferable to ask survey respondents about their actual perceived vulnerability, the survey did not include such questions. Similarly, it would have been useful to identify which types of crime were experienced by those who indicated prior criminal victimization, but again, such measures were not available in the current data set. Another methodological issue involves the use of cross-sectional data. Although this is common in fear of crime research, it is possible that the time order between variables could be confounded (Boateng, 2019; Lytle & Randa, 2015). For instance, perhaps respondents rated their neighborhoods as socially disorganized because they were fearful of crime, rather than the other way around. Nevertheless, as most of the variables behaved according to theory, we can be reasonably confident that the cross-sectional nature of the data did not dramatically affect the results.

Implications for Research and Policy

The results of the present study suggest implications for researchers and for policy makers. First, we view the present study as advancing knowledge by reaffirming the usefulness of vulnerability, disorder/incivilities, and social cohesion as theories of fear of crime. Furthermore, examining each of these perspectives collectively provides for a more comprehensive view of the determinants of fear. However, Rader (2004) suggests that many fear of crime studies are incomplete because fear of crime is only one component of a larger threat of victimization construct, which includes fear of crime, perceived, risk, and constrained behaviors. Theoretically, these three components of the threat of victimization are related to each other in reciprocal ways, suggesting that the current approach provides only a limited view of the full dynamics of the larger threat of victimization (e.g., Rader, 2004; Rader et al., 2007). Therefore, future researchers are advised to consider Rader’s threat of victimization among other populations—including in Western states.

Second, the results involving perceptions of police services highlight the impact that local police can have upon residents’ quality of life. As fear of crime reportedly reduces quality of life for a significant number of Americans (Garofalo, 1981; Skogan, 1986, 1990), policy makers and practitioners may consider the importance of initiatives such as community-oriented policing and quality-of-life policing—police strategies that address physical disorder, social disorder, and social cohesion within communities. For example, programs involving police and other local agency personnel to develop physical cleanup, the presence of outdoor trees and grass, and evictions of problematic renters may reduce incivilities. Indeed, after a successful decade of community-oriented policing, the city of Chicago abandoned the strategy in favor of a reorientation toward get tough policies (Skogan, 2006, 2008). The results of the present study suggest that community-oriented policies—or at least policies that increase citizens’ satisfaction and confidence in the police—may have benefits beyond the immediate crime rate, and should, therefore, be nurtured for the betterment of the community.

Lastly and related to this, policy makers may consider programs to increase social cohesion and local networks. The current study suggests a negative relationship between social cohesion and fear of crime. Therefore, it is possible that a program that builds neighborhood trust would be effective to reduce fear of crime. Sampson and Raudenbush (1999) proposed the notion of collective efficacy, which includes trust among residents in a community and their shared expectations about their informal social control. Social control has been defined in a variety of ways as social cohesion, informal social control, social capital, or collective efficacy. Therefore, it is plausible that those communities can benefit from shared positive ties among acquaintances and friends and have the capacity to regulate community fear. Local governments may find it beneficial to support strategies that encourage these local networks, such as community meetings, home association meetings, block parties, or similar local community events where community members can share values and concerns while they strongly build up the neighborhood trust, cohesion, interaction, and attachment. Future research may examine the effectiveness of social policies that encourage local neighborhood networking.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Heeuk D. Lee

Notes

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