Fearfulness in the Community: Empirical Assessments of Influential Factors

Abstract

Fear of crime has been well studied; however, there has yet not been widespread consideration of the potential impact of both individual- and neighborhood-level factors on residents’ level of fear of crime. From a logistic-regression analytical standpoint, the present study empirically explores the contribution of several factors in explaining residents’ propensity for being fearful of crime. Precisely, the study tests the applicability and generalizability of three theoretical perspectives of fear of crime in the Ghanaian context and examines the effects of residents’ attitudes toward the police on their levels of fear of crime. Using large-scale cross-sectional data collected on more than 1,000 residents from 25 neighborhoods in Ghana, the results demonstrate significant predictive effects of both individual- and neighborhood-level factors on citizens’ rate of fearfulness. Findings from this study have both theoretical and practical implications, and provide important insights for the police to reduce levels of fear of crime in the community.

Keywords

fear of crime social disorder police visibility Ghana attitudes

Introduction

In recent times, numerous studies have made considerable efforts to advance our knowledge and understanding of fear of crime (Doran & Lees, 2005; Moore & Shepherd, 2007; Rader, 2004; Renauer, 2007; Sutton & Farrall, 2005; Vilalta, 2012). Most of these studies have utilized limited samples to help explain why citizens are more or less fearful of crime, and devise mechanisms for reducing fear of crime and helping to address issues pertaining to operationalization and conceptualization of fear of crime. However, despite the abundant studies on fear of crime, far less attention has been made to foster increased understanding of fear of crime in developing non-western societies. For instance, the majority of the extant studies focused largely on explaining the dynamics of fear of crime in developed societies, limiting our knowledge of the issue in developing, post-conflict, and emerging societies. To gain a thorough understanding of the concept of fear of crime, research must be conducted in all regions of the world (Adu-Mireku, 2002).

Despite the extensive focus of fear of crime studies in the West, there are some exceptions, which need to be acknowledged (see Adu-Mireku, 2002; Dammert & Malone, 2006; Hwang, 2006; Karakus, McGarrell, & Basibuyuk, 2010). These few non-western fear of crime studies have observed effects similar to what western studies have found. For instance, studies conducted in the non-western world have strongly observed the effects of vulnerability indicators on fear of crime, arguing that women and older people report greater levels of fear of crime than men and younger individuals do. Despite their important contributions to the fear of crime literature, non-western fear of crime studies have some limitations that call for further and in-depth analysis of the issue in societies beyond the western world. For instance, most of these studies treated fear of crime as a monolithic construct, as evidenced by the single item (“How fearful are you about crime in your neighborhood?”) used to measure fear of crime. A single question is not enough to capture the various dimensions within which fear of crime can manifest in the community (Moore & Shepherd, 2007).

Given the above limitations, the present effort supplements previous works by furthering the discussion on factors influencing residents’ fear of crime in the community. The primary purpose of the current study is to explore from a theoretical standpoint the contribution of both individual- and neighborhood-level characteristics in explaining residents’ propensity for being fearful of crime. Using a large-scale cross-sectional data collected on more than 1,000 residents from 25 neighborhoods in Ghana, the study aims to achieve two specific objectives. The first objective is to test the applicability and generalizability of three theoretical perspectives of fear of crime in the Ghanaian context and determine whether what has been observed in the West holds relevance elsewhere. The second objective is to explore the effects of residents’ attitudes toward the police on their levels of fear of crime, controlling for other individual-level factors. By achieving these objectives, the study will advance our knowledge regarding the etiology and nature of fear of crime in non-western societies. The next section discusses the various theoretical frameworks of fear of crime and stipulates specific assumptions tested in the current study.

Propensity for Fear of Crime: Underpinning Theoretical Explanations

Vulnerability Perspective

The vulnerability perspective has been consistently used to explain the influence of demographic characteristics on fear of crime. This perspective suggests a positive relationship between fear of crime and vulnerability, and theorizes that individuals who are more vulnerable to victimization will express greater feelings of fear of crime (Gibson, Zhao, Lovrich, & Gaffney, 2002; Will & McGrath, 1995). There are two main types of vulnerability in this perspective: physical vulnerability and social vulnerability. Physical vulnerability presupposes that persons who are physically vulnerable tend to be more fearful of crime (Braungart, Braungart, & Hoyer, 1980; Ferraro, 1995; Vanderveen, 2002; Wittebrood, 2002). Gender and age are the two demographic variables that have been used to explain the relationship between physical vulnerability and fear of crime. Findings from previous studies indicate that women and elderly people report greater levels of fear due to their physical vulnerability (Clemente & Kleiman, 1977; Wyant, 2008). Specifically, findings suggest that compared with men, women are more fearful of crime in their neighborhoods (Adu-Mireku, 2002; Chadee & Ditton, 2003; Rader, May, & Goodrum, 2007; Ribero, 1999; Scarborough, Like-Haislip, Novak, Lucas, & Alarid, 2010; Schafer, Huebner, & Bynum, 2006; Scott, 2003). This relationship was also observed in a study that utilized a Chinese sample. Liu, Messner, Zhang, and Zhuo (2009) investigated the relationship between fear of crime and demographic characteristics in Chinese urban areas and found that Chinese women were more fearful of crime than their male counterparts were. Paradoxically, the relationship between gender and fear of crime is surprising, because women are less likely than men to experience criminal victimization. However, some researchers believe that women’s fear of crime is largely related to their fear of being raped or sexually attacked (Fisher & Sloan, 2003; Schafer et al., 2006; Wilcox, Jordan, & Pritchard, 2006).

Previous studies have found a complex relationship between age and fear of crime. Some researchers argue that elderly individuals are more fearful of crime than their younger counterparts (Adu-Mireku, 2002; Ferraro & LaGrange, 1987), and yet, some scholars believe that age and fear of crime have a negative relationship. This group of scholars has found results suggesting that elderly people are less likely to report higher levels of fear of crime compared with younger individuals (Chadee & Ditton, 2003; McCoy, Wooldredge, Cullen, Dubeck, & Browning, 1996). Furthermore, some researchers are of the view that age and fear of crime have a curvilinear relationship, suggesting that the younger and the elderly report higher levels of fear of crime than those in the middle years (May, 2001; Moore & Shepherd, 2007; Pain, 2000).

The social vulnerability perspective argues that persons who are more vulnerable in society express greater levels of fear of crime. Based on this argument, it is assumed that the less educated, low-income earners, the unemployed, and racial/ethnic minority groups, who are the most vulnerable in society, will tend to be more fearful of crime (Cobbina, Miller, & Brunson, 2008; Zhao, Lawton, & Longmire, 2015). Studies testing this assumption have found mixed results. For instance, some studies have found a negative relationship between education and fear of crime (Covington & Taylor, 1991; Kennedy & Silverman, 1985; Rader, Cossman, & Porter, 2012), and income and fear of crime (Mathieu, 1995; McGarrell, Giacomazzi, & Thurman, 1997; Rader et al., 2012). These findings affirm the belief that individuals from lower social classes, because of their vulnerability, are more fearful of attack than those in the middle and upper classes.

Based on the arguments put forth by proponents of the vulnerability thesis, the current study explores the predictive powers of physical and social vulnerability indicators in explaining Ghanaians’ fear of crime using a large sample size selected from 25 neighborhoods across the country. The following hypotheses are to be tested:

Hypothesis 1 (H1): Fear of crime will be higher among women than men. It is expected that Ghanaian women will indicate being more fearful of victimization because of their vulnerability in the community.

Hypothesis 2 (H2): Older people will express being more fearful of crime in the community, compared with their younger counterparts.

Hypothesis 3 (H3): Citizens who are unemployed will indicate being more fearful of crime than those who are employed. It is expected that fear of crime and employment status will have an inverse relationship.

Victimization Perspective

The victimization perspective of fear of crime proposes a relationship between residents’ levels of fear of crime and previous criminal victimization (Balkin, 1979; Rountree, 1998; Skogan & Maxfield, 1981; Will & McGrath, 1995). Individuals who support this viewpoint argue that the relationship can be direct or indirect. The direct victimization thesis posits a positive relationship between fear of crime and previous victimization, implying that experiences of previous victimization increase one’s level of fear of future victimization. Several studies have found results supporting this argument (Karakus et al., 2010; Liu et al., 2009; Rader et al., 2007; Schafer et al., 2006). For example, Liu et al. (2009) observed that personal victimization increases Chinese residents’ fear of crime. This finding is consistent with the observation made by Karakus et al. (2010) when studying fear of crime among Turkish citizens. Although the authors observed a positive relationship between fear of crime and victimization, they concluded that the effect is stronger among Turkish women. Despite these convincing observations, some researchers claim that there is no relationship between fear of crime and previous victimization, or that if there is, the relationship is weak (Adu-Mireku, 2002; Liska, Sanchirico, & Reed, 1988; McGarrell et al., 1997).

According to the indirect victimization model, people with traits such as being female, elderly, low income, racial minorities, and less educated possess higher levels of fear because of their heightened physical and social vulnerability (Covington & Taylor, 1991). Derived from the victimization model is this hypothesis:

Hypothesis 4 (H4): Citizens who have experienced previous victimization will be more fearful of crime than those who have not been previously victimized. It is expected that previous victimization will have a significant positive relationship with fear of crime.

Disorder Perspective

The disorder model (also called the incivility model) assumes a positive correlation between disorder and fear of crime (Brunton-Smith & Sturgis, 2011; Giacomazzi, 1995; Markowitz, Bellair, Liska, & Liu, 2001; Skogan, 1990), suggesting that, as perception of disorder in a community increases, residents’ fear of crime also increases. Wilson and Kelling (1982) and Skogan (1990) argued that disorderly behavior creates fears, and when unchecked, can lead to criminal activities. Both authors contend that disorderly people are disreputable or unpredictable people—panhandlers, drunks, addicts, rowdy teenagers, prostitutes, loiterers, and the mentally disturbed—who engage in all kinds of disorderly behaviors that may develop into criminal acts such as robbery, mugging, raping, theft, drug use and sales, and so on.

Incivilities, “low-level breaches of community standards that signal an erosion of conventionally accepted norms and values” (LaGrange, Ferraro, & Supancic, 1992, p. 312), present themselves in two distinct forms: social and physical (Palmonari, 1999; Ross & Jang, 2000; Wilson & Kelling, 1982). These researchers have argued that both forms of incivilities are important factors affecting people’s feelings of fearfulness. Social incivilities involve behaviors that we can see happening (public drinking, drunkenness, or prostitution) and behaviors we can experience (catcalling or sexual harassment). Physical incivilities involve behaviors such as graffiti, vandalism, abandoning or neglecting buildings, breaking streetlights, filling lots with trash, and leaving alleys strewn with garbage and alive with rats (Ross & Jang, 2000; Skogan, 1990). These behaviors create an unpleasant atmosphere in the community, make community members feel more vulnerable to victimization, and subsequently increase their fear of being attacked (Markowitz et al., 2001; Skogan & Maxfield, 1981; Wyant, 2008).

Empirical studies that have tested the incivility/disorder perspective have found consistent results indicating that neighborhood decay heightens fear among residents (Covington & Taylor, 1991; Doran & Lees, 2005; Gibson et al., 2002; Moore & Shepherd, 2007; Rader et al., 2012; Williamson, Ashby, & Webber, 2006). These studies examined the linkage between the two variables using both structural- and individual-level data, and their results stem from the argument that incivilities reflect social degradation and are signs of menace (Ackermann, Dulong, & Jeudy, 1983; Roché, 1993). To test the disorder perspective of fear of crime, the following hypothesis is tested:

Hypothesis 5 (H5): It is hypothesized that citizens who perceive greater levels of neighborhood disorder will be more fearful of crime than individuals who perceive less disorder in their neighborhoods.

Other Determinants of Fear of Crime

In addition to examining the effects of disorder, victimization, and sociodemographic characteristics on fear of crime, researchers have explored the effects of several other variables that predict a person’s level of fear in the neighborhood. These variables include social cohesion (Markowitz et al., 2001; Ross & Jang, 2000; Sampson & Raudenbush, 2004; Sampson, Raudenbush, & Earls, 1997; Taylor, 2002) and attitudes toward the police, including confidence, satisfaction, effectiveness, and police visibility (Reisig & Parks, 2004; Skogan, 2009; Skogan & Hartnett, 1997). These studies have collectively found evidence suggesting a negative relationship between the aforementioned variables and fear of crime. Social cohesion, for instance, denotes the trust that community members have for one another (see Morenoff, Sampson, & Raudenbush, 2001; Rosenfeld, Messner, & Baumer, 2001; Taylor, 2002), and studies have observed that a reduction in social cohesion makes a person more fearful. This is because the lack of social cohesion reduces the bond that exists among residents, creating the atmosphere for potential criminals to flourish.

Regarding the influence of attitudes toward the police on fear of crime, Skogan (2009) believes that attitudes are important; Skogan examined the mutual connection between fear of crime and confidence in the police, and argued that confidence in the police reduces concern about crime. Similarly, Reisig and Parks (2004) concluded that individuals who hold positive perceptions about police-community partnership report less fear. The overall effectiveness of police in controlling neighborhood crime goes a long way to affect residents’ concern about crime. Studies have shown that police visibility increases confidence in the police and subsequently reduces fear of crime (Pate, 1986). However, Adu-Mireku’s (2002) study in Ghana did not observe a significant relationship between attitudes toward the police (satisfaction) and fear of crime among Ghanaians. Based on the above findings, the following hypotheses are to be tested:

Hypothesis 6 (H6): It is hypothesized that citizens who consider social cohesion stronger in their neighborhoods will report being less fearful of crime than those who think social cohesion is weak in their neighborhoods.

Hypothesis 7 (H7): It is hypothesized that citizens who consider police visibility higher in their neighborhoods will express less fear of crime.

Hypothesis 8 (H8): Citizens’ attitudes toward the police will negatively influence their levels of fear of crime. It is expected that:

Higher confidence in the police will reduce citizens’ fear of crime.

Favorable perception of police effectiveness will reduce citizens’ fear of crime.

Method

Study Population and Participants

Data analyzed in the current study were collected on individuals aged 18 years and above, living in the urban areas of Ghana at the time of the survey administration. The survey collected information on residents’ opinions about their level of fear of crime and several other topics through an in-person approach. Respondents were selected randomly from five communities in the capital cities of five administrative regions. Each respondent participating in the study was selected from one household. Survey administration in all the five regions lasted approximately 4 months, from March 2014 to June 2014. Specifically, in each region, fieldwork, including training offered to research assistants, lasted 3 weeks. The remaining 4 weeks were spent on training of data entry personnel and entry of data in an Excel format.

Sampling Techniques and Procedure

Several stages were involved in the selection of final respondents for participation in this study. First, five regions were purposively selected from the 10 administrative regions in Ghana. Although Ghana as a country is highly diverse, the various regions differ in their level of diversity. While some are highly homogeneous, others are more diverse because of economic and industrial activities. This study was focused on five regions with highly heterogeneous populations. The capital city of each region was purposively selected for the study. These cities, because of widespread economic activities and urbanization, have several characteristics that can be sources of fear: population and residential density; ethnic, age, and income heterogeneity; lack of services; poor social integration; and heavy pedestrian traffic (Kuo, Bacaicoa, & Sullivan, 1998; Perkins, Wandersman, Rich, & Taylor, 1993; Skogan & Maxfield, 1981).

The next stage involved selecting five communities purposively from each regional capital in the five regions for two main reasons: First, certain areas in Ghana are typically for commercial activities and are not residential areas; hence, they are not useful for reaching populations. Second, some communities are reserved for specific types of government officials such as police officers, correctional officers, fire officials, and ministers. These individuals often have extended security in their homes and in the community, so including such areas in the study may bias the results.

Following the selection of communities, is the selection of 250 households randomly from the five communities (50 households from each community). A household, according to Hailand (2003), constitutes one or more people who live in the same house and share meals or living accommodation. The final stage involved the selection of an individual respondent from each household. In this selection, the use of the birthday methods—which involve selecting the individual from a household with the most recent or next upcoming birthday—was highly desirable, as they are quick, easy, and less intrusive as well as maximizing cooperation rates (Battaglia, Link, Frankel, Osborn, & Mokdad, 2008; Gaziano, 2005; Oldendick, Bishop, Sorenson, & Tuchfarber, 1988). The last-birthday method was used to select an individual who was at least 18 years old and was the last to celebrate his or her birthday in the household at the time of the survey administration. The next-birthday method was used to select an individual whose birthday was nearest to the date of the survey administration and was 18 years old or older.

Questionnaires were administered to the selected individuals, and were collected at the time of administration. This procedure ensured that the sampled individuals were the ones who actually filled out the questionnaires. Overall, 1,024 questionnaires out of the 1,250 were completed and collected, obtaining a response rate of about 82%.

Measures

Dependent variable

The dependent variable, fear of crime, was measured using a 4-item Likert-type scale asking respondents to indicate whether they agreed or disagreed with the following statements: “I am afraid to walk in my neighborhood at day time,” “I am afraid to walk in my neighborhood at nighttime by myself,” “The level of security in my neighborhood is very low,” and “Overall, I am afraid to be attacked in my neighborhood.” The response categories were (1) strongly disagree, (2) disagree, (3) undecided, (4) agree, and (5) strongly agree. A factor analysis with a maximum likelihood estimator indicated that the items measured the same underlying construct. As a result, the responses to the four items were combined to form an ordinal measure of fear of crime, with options ranging from 1 = strongly disagree to 4 = strongly agree. As shown in Table 1, majority of the respondents reported being afraid of crime in their communities (60% agreed or strongly agreed).

Table 1.

Descriptive Statistics of Study Variables (N = 1,024).

Variables	Minimum	Maximum	M (SD)
Fear of crime
Strongly disagree	0.00	1.00	0.10 (0.31)
Disagree	0.00	1.00	0.29 (0.46)
Agree	0.00	1.00	0.18 (0.39)
Strongly agree	0.00	1.00	0.18 (0.39)
Confidence in the police	5.00	25.00	14.67 (4.46)
Police effective	5.00	25.00	14.99 (4.49)
Previous victimization	0.00	1.00	0.48 (0.50)
Neighborhood disorder	8.00	24.00	18.52 (3.87)
Social Cohesion	7.00	28.00	14.34 (4.20)
Police visibility	0.00	3.00	1.45 (1.06)
Age	18	75	28.14 (10.31)
Male	0	1	0.58 (0.49)
Employed	0.00	1.00	0.53 (0.50)
Income—More than GHC 10,000	0.00	1.00	0.36 (0.48)
Education
No formal education	0.00	1.00	0.07 (0.26)
Junior high school	0.00	1.00	0.12 (0.33)
Senior high school	0.00	1.00	0.41 (0.49)
Post Senior High School	0.00	1.00	0.40 (0.49)

Note. SD = Standard deviation of the mean. GHC = Ghana Cedi.

Independent variables

Individual-level variables: The effects of five individual demographic variables were examined in the present analysis. Age was measured as respondents’ actual age in years at the time of the survey. Gender was measured as 0 = female, 1 = male. For employment status, respondents were asked to indicate their current employment status and response categories were 0 = unemployed and 1 = employed. Education was measured as a categorical variable (1 = no formal education, 2 = Junior high school, 3 = Senior high school and 4 = Post senior high scool) with no formal education as the reference category. Income was measured by asking respondents to indicate their household’s income per year (0 = GHC 10,000 or less and 1 = more than GHC 10,000; GHC = Ghana Cedi). Any respondent whose household income was GHC 10,000 or below was considered a low-income earner.¹

Table 1 indicates that the majority of the respondents were males (58%) and employed (53%). The average age of the respondents was 28 years; the youngest respondent was 18 years old, while the oldest was 75. Slightly more than one third (36%) of the respondents earned more than GHC 10,000 a year, and only 40% had attained a post-senior high school education.

Perceptual variables

These variables measured respondents’ perceptions of the police in their communities. Two perceptual variables were included in the analysis. Confidence in the police was an index variable created from five items in the survey: “Overall, I trust the police in my neighborhood to protect lives and property”; “the police can be trusted to make decisions that are right for the people in your neighborhood”; “the police in your neighborhood are generally honest”; “I have absolute confidence that the police can do their job well”; “the police care about the well-being of everyone they deal with.” Response categories were (1) strongly disagree, (2) disagree, (3) undecided, (4) agree, and (5) strongly agree. A factor analysis with a maximum likelihood estimator indicated that all these items measured the same underlying construct. Therefore, the responses to all the items were summed to form an additive trust in the police scale. The scale had a mean of 14.67 (SD = 4.46) and an alpha value of .79, suggesting good internal reliability.

Five items asking respondents to indicate the extent to which the police were effective in controlling crime in the neighborhood measured police effectiveness. The five items had the same response categories: (1) strongly disagree, (2) disagree, (3) undecided, (4) agree, and (5) strongly agree. These items included the following: “The police are effective in controlling violent crime in your neighborhood?” “The police are effective at arresting criminal suspects in your neighborhood?” “The police are effective at controlling theft (mobile phone, purse, or bag snatching) in your neighborhood?” “The police are effective at controlling burglary in your neighborhood?” “The police are effective in controlling disturbances in your neighborhood?”

In a factor analysis, all five items loaded on the same factor, indicating that the items measure the same construct. Therefore, the five items were combined to form the police effectiveness scale, with a mean of 14.99 (SD = 4.49) and an alpha value of .81, suggesting good internal reliability.

Previous victimization was measured as a dichotomous variable created out of six items with yes (1) and no (0) options. The items asked respondents to indicate whether they had been victims of the following offenses in the year 2013: physical attack, purse/mobile snatching, burglary, auto theft, motorcycle/bicycle theft, and sexual attack. Responses to these items were combined to form a dichotomous variable (0 = have no previous victimization and 1 = have previous victimization). Overall, 48% of the respondents claimed they had previously been victimized, and 52% had no previous victimization.

Neighborhood variables

Three neighborhood variables were expected to influence fear of crime. These included neighborhood disorder, social cohesion, and police visibility.

Neighborhood disorder measured the extent of neighborhood disorderly problems perceived by the respondents. It was measured using eight items, which accounted for both physical and social dimensions of disorder: litter/trash, hanging around, vandalism, abandoned buildings, dirty gutters, gangs, unrepaired streetlights, and drug dealing. Each of these items had a three-point response set (1 = not a problem, 2 = minor problem, and 3 = major problem). A factor analysis indicated that all these items measured the same underlying construct; as a result, the responses were summed to form an additive neighborhood disorder scale. The scale had a mean of 18.52 (SD = 3.87) and an alpha value of .79, suggesting good internal reliability.

Police visibility was measured by three dichotomous items, asking respondents to indicate the extent to which police presence was felt in their community. Specific items asked were, “Based on your own assessment, will you say there is a police station close to where you live?” “Have you seen a police officer in this community within the past week?” “Have you seen a police officer in this area at all?” Respondents were asked to choose from 0 = no and 1 = yes. A factor analysis confirmed that these items measured the same construct; hence, they were combined to form the police visibility scale with a mean of 1.45 (SD = 1.06) and an alpha value of .57.

Social cohesion measured the extent to which community members trusted one another. The variable was measured as an index of trust in people, which was created from seven items, five of which were adapted from the 2005-2008 World Value Survey. The seven items had the same lead-in question:

I now want to ask you how much you trust various groups of people. Using the responses 1 = no trust at all, 2 = not very much, 3 = somewhat, and 4 = trust completely, could you tell me how much you trust: (1) your neighbors, (2) people you know personally, (3) people you meet for the first time, (4) people of another religion, (5) people from different ethnic groups, (6) people from different regions, and (7) people of another nationality.

The order of the answers was reversed in this study, with a higher score indicating a greater degree of trust: 4 = trust completely, 3 = somewhat, 2 = not very much, and 1 = no trust at all. The eight items, which loaded on the same factor, were combined to form the social trust scale. This scale had a mean of 14.34 (SD = 4.20) and an alpha value of .86.

Results

Plan of Analysis

To achieve the objectives of study, two types of analyses were conducted. First, descriptive analysis was conducted to examine the distribution among the study variables. Second, given the ordinal nature of the dependent variable, an ordinal logistic regression model was used to explore the effects of the independent variables—demographic variables, confidence, effectiveness, previous victimization, disorder, police visibility, and social cohesion—on residents’ fear of crime.

Determinants of Fear of Crime in the Neighborhood

Table 2 presents the results of an ordinal logistic regression that was conducted to examine factors that influence residents’ level of fear of crime. The overall model fit was significant (χ² = 46.17, p < .001) and explains 12% of the variance in fear of crime. Several variables were found to have a statistically significant relationship with fear of crime. When controlling for the effects of other variables in the model, citizens who had previously experienced victimization expressed greater fear of crime than those with no prior victimization (Wald = 27.09, p < .001). This finding supports the study’s hypothesis (H4) that citizens who had experienced previous victimization will be more fearful of crime than those who have not been previously victimized. In addition, the two perceptual variables—confidence in the police (Wald = 3.07, p < .05) and perception of police effectiveness (Wald = 6.01, p < .05)—had negative influence on fear of crime. Citizens who reported having higher confidence in the police and perceived higher police effectiveness were less likely to express being fearful of crime in the neighborhood, lending support for the hypothesized relationship between attitudes toward the police and fear of crime (H8).

Table 2.

Ordinal Logistic Regression Predicting the Effects of Individual and Neighborhood Level Characteristics on Fear of Crime (N = 1,024).

Variables	b (SE)	Wald
Previous victimization	0.87 (0.17)	27.09***
Perceptual variables
Confidence in the police	−0.04 (0.02)	3.07*
Police effectiveness	−0.05 (0.02)	6.01*
Neighborhood variables
Disorder	0.05 (0.02)	4.77*
Social Cohesion	0.01 (0.02)	0.35
Police Visibility	−0.17 (0.08)	4.17*
Physical vulnerability indicators
Age	0.05 (0.02)	0.27*
Male	−0.10 (0.17)	0.37
Social vulnerability indicators
Income—More than GHC 10,000	−0.15 (0.17)	0.83
Employed	−0.09 (0.18)	2.25*
Education: No formal education (RC)
Junior high school	0.69 (0.47)	2.16
GED or Senior high school	0.49 (0.41)	1.40
Post senior high school	0.65 (0.41)	2.55
Thresholds
Strongly disagree	−0.04 (0.78)	0.12
Disagree	1.57 (0.78)	4.00*
Agree	3.61 (0.80)	20.53***
Model Fit
−2 log likelihood	1,299.57
χ²	46.17***
df	13
Negelkerke R²	.12

Note. OR = odds ratios; GED = General Educational Development; GHC = Ghana Cedi; RC = Reference Category.

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

Moreover, the effects of two neighborhood indicators were observed. Residents’ perception of neighborhood disorder had a statistically significant relationship with levels of fear of crime (Wald = 4.77, p < .05). This observation supports the study’s fifth hypothesis and suggests that fear of crime is highest among people who perceived greater rates of disorder. Similarly, police visibility was significant (Wald = 4.17, p < .05), and having a negative relationship, citizens who reported higher presence of the police in the neighborhood tended to be less fearful of crime, a finding that offers credence to H7. The lack of significance for the social cohesion variable indicates that residents’ level of fear of crime does not vary by their assessments of weak or stronger cohesion in the neighborhood. This lack of observation failed to provide support for the hypothesized relationship between social cohesion and fear of crime (H6).

Finally, two demographic variables were also found to have predictive effects on levels of fear of crime. Age was found to predict a person’s level of fear of crime in his or her community (Wald = 0.27, p < .05). With a positive coefficient (b = .05), older persons reported being highly afraid of crime compared with their younger counterparts. Employment status of an individual also influences his or her levels of fear of crime (Wald = 2.25, p < .05). Possessing a negative coefficient of .09, persons who were employed were less likely to indicate that they were fearful of crime compared with the unemployed. These two observations supported H2 and H3, respectively. However, as there was no statistically significant relationship between gender and fear of crime, H1 was not supported.

Discussion and Conclusion

In the past few years, criminologists and sociologists have developed models—the victimization, disorder, and vulnerability perspectives—to understand the etiology and dynamics of fear of crime in the neighborhood. Research conducted to test the key assumptions of these models has mainly focused on the West and has found compelling evidence supporting the claims of the theories. It has been widely documented that the elderly, women, lower-class citizens, and the victimized often report higher levels of fear of crime. Moreover, researchers have also confirmed the significant contribution of neighborhood conditions—disorder—to shaping a person’s feeling of fearfulness (Doran & Lees, 2005; Williamson et al., 2006). Analyzing data collected from a non-western sub-Saharan African country, the findings indicated that theories of fear of crime developed and tested in western societies are applicable and generalizable to the Ghanaian context. Specifically, the vulnerability, victimization, and disorder models are all important in explaining the causes of fear of crime among Ghanaians.

In the ordinal logistic regression analysis, the relationship observed between age and fear of crime was as expected. Older Ghanaians were more fearful of crime than the younger ones, a finding that supports the physical vulnerability thesis. This finding is also consistent with findings from prior research conducted in other sociocultural contexts (Ferraro & LaGrange, 1987; Karakus et al., 2010). However, the finding contradicts the argument of some researchers (Adu-Mireku, 2002; Chadee & Ditton, 2003) that the elderly report less fear of crime. An in-depth understanding of the modern-day Ghanaian social structure will reveal why Ghanaian elderly persons are more fearful of crime. Modern Ghana has undergone a drastic social developmental process of modernization, industrialization, and urbanization (see Amuzu & Leitmann, 1991; Asiama, 1984), and this has affected the routine activities and lifestyles of Ghanaians (Appiahene-Gyamfi, 2002), resulting in a gradual disintegration of unique and cherished Ghanaian cultural practices. Due to this social change process, young people no longer stay at home to take care of the elderly, leaving the elderly at home alone. According to the vulnerability thesis, because the elderly stay home alone and to some extent have a limited ability to defend themselves, they become more vulnerable to victimization, which increases their fear of crime. It is, therefore, not surprising that fear of crime is higher among the Ghanaian older population.

Contrary to previous findings (Rader et al., 2007; Scarborough et al., 2010; Schafer et al., 2006), Ghanaian women in this study were not significantly more fearful of crime than men. Stated differently, this study did not observe any gender effect on fear of crime. A plausible explanation could be that the dominant fear of sexual assault and rape argument used to explain women’s fear of crime (Fisher & Sloan, 2003; Wilcox et al., 2006) may not apply in the Ghanaian context because women in this society, it can be safely argued, experience less sexual assault. In Ghana, the majority of sexual assault cases are spousal-assault-related incidents, which are not often reported (see Adinkrah, 2011; Amoakohene, 2004; Tenkorang, Owusu, Yeboah, & Bannerman, 2013). Most Ghanaian women consider sexual coercion in marriage to be normal and see no reason to talk about it with third parties (Boateng, 2015).

Another aspect of the vulnerability perspective that is supported by the findings from the current analysis is the social vulnerability thesis. To recap, the social vulnerability model relates higher levels of fear of crime to increased vulnerability in society (Rader et al., 2012; Zhao et al., 2015). This perspective suggests that lower-class individuals, such as the less educated, those who earn less income, and the unemployed, because of their conditions, tend to report higher levels of fear of crime. Consistent with this argument is the finding that unemployed Ghanaians were more fearful of crime in the neighborhood than the employed. In Ghana, being employed is directly linked to people’s ability to protect themselves and their property. Security is more or less for sale, and only available to those who can afford it. As a result, the unemployed who have no social capital are less able to protect themselves and their property against victimization, making them more susceptible to victimization, and subsequently report greater levels of fear of crime.

Related to the above observation is the finding that persons who have previously been victimized are more likely to be afraid of crime compared with those without such experiences. This observation is consistent with the propositions of the victimization perspective of fear of crime, as well as consistent with findings from prior research conducted elsewhere (Karakus et al., 2010; Liu et al., 2009; Rader et al., 2007). The victimization perspective makes a relatively intuitive argument about fear of crime, because it is apparent that any person who has previously been victimized will be afraid of future victimization and act in ways to avert such victimization.

The study further observed a significant relationship between citizens’ attitudes toward the police and fear of crime. Specifically, findings revealed that greater confidence in the police and favorable perceptions of police effectiveness reduce fear of crime among residents. These results are not only in line with prior research (Reisig & Parks, 2004; Skogan, 2009) but also consistent with the reassurance model of policing. Originally developed in the United Kingdom, the reassurance model of policing proposes a unique relationship between fear of crime and attitudes toward the police (see Fitzgerald, Hough, Joseph, & Qureshi, 2002; Millie & Herrington, 2005; Povey, 2001; Quinton & Morris, 2008). According to this model, the public sense of security is tied to whether the public believe the police are doing something about crime. Individuals who believe that the police are working assiduously to prevent crime and to reduce insecurity and risk of victimization will be less likely to report being fearful.

Finally, the effects of two neighborhood variables were also observed. First, findings revealed that Ghanaians who consider disorder higher and a significant problem in the areas where they live tend to be more fearful of crime than those who believe disorder is less of a problem in their communities. This observation suggests that the disorder model of fear of crime is valid in the Ghanaian context. Wesley Skogan (1990) argued decades ago that neighborhood disorder creates fear and, when unchecked, could lead to more serious criminal acts. Research findings, including those from the current study, have demonstrated that this argument is not context-specific but holds true in all social contexts. Second, consistent with the reassurance model, results from the regression analysis revealed that police visibility is a significant contributor to understanding the dynamics of fear of crime in Ghana. Ghanaians who live in areas where police visibility and presence are high report lower levels of fear of crime. A plausible explanation for this observed pattern of behavior could be that the presence of the police in the community signals that the police are working hard and are accessible, and subsequently reduces insecurity felt by the residents. According to Povey (2001), perceptions of security and order are produced by policing that is visible, accessible, and familiar to residents. One strategy for increasing police visibility to maximize security and order is to have more police officers patrolling the neighborhood around the clock.

A major limitation of the study that needs to be acknowledged is the use of cross-sectional data to disentangle the complex relationships among fear of crime and the independent variables. Using cross-sectional data limited the study’s ability to establish a causal relationship and make causal inferences. It is, therefore, suggested that future research must make the effort to study the causes of fear of crime using a longitudinal approach.

Despite this limitation, findings from the current analysis have several theoretical and practical implications for policymakers and law enforcement administrators in Ghana. Theoretically, findings from this study demonstrate that fear of crime models developed and tested in western societies can be used to predict patterns of fear of crime among residents in other sociocultural contexts. Specifically, these theories have general applicability in homogeneous and traditional societies such as Ghana. Practically, the findings offer several clues to policymakers to reduce fear of crime in their communities. First, the results show that higher confidence in the police and police effectiveness are important considerations in reducing fear of crime.

Therefore, police administrators are obliged to consider ways to build citizens’ confidence and provide effective services to the citizenry. Dissatisfaction with the police simply implies that the public is not satisfied with police services, partly because of apparent ineffectiveness or nonperformance on the part of the police (Boateng, 2013). To enhance police performance and increase public satisfaction with the Ghana police, police administrators must develop effective and reliable communication systems that will increase public accessibility to the police. Quick response to citizens when called for help as well as fair treatment of citizens during encounters would be great steps in improving public satisfaction with police work (Boateng, 2013). With regard to enhancing citizens’ confidence, several strategies could be adopted. For instance, the police can foster positive relationships with the communities they serve by eschewing unethical behavior, which undoubtedly destroys good relations. In addition, the police can organize meetings and seminars with the public to discuss mutually relevant issues. These types of meetings will allow the public to express their grievances and feelings about the police and their activities, while the police attempt to address such complaints. Finally, policymakers and police administrators should consider reducing fear of crime by incorporating fear reduction strategies into the daily routines of the police service. Strategies may include increasing police presence in the neighborhoods, ensuring constant patrolling in the neighborhoods, reducing disorderly behavior, and ensuring rapid response to calls for service (Cordner, 2010). These strategies are aimed at reducing fear of crime and insecurity, and when properly adopted will restore a sense of security and safety.

In conclusion, this study used data from Ghana to improve the understanding of fear of crime among people from non-western countries. Findings obtained generally demonstrated that both individual-level and neighborhood-level factors are important in understanding the nature of fear of crime expressed by Ghanaians. For instance, it was observed that being older, unemployed, and previously victimized enhances people’s fear of crime in their neighborhoods. Moreover, it has been demonstrated that residents’ perceptions of the police as well as neighborhood variables such as disorder and police visibility all influence fear of crime. These findings variously support some of the major fear of crime theories in the literature, demonstrating the global utility of such theories.

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.

Notes

Author Biography

Francis D. Boateng is an assistant professor of criminal justice and criminology in the Liberal Arts and Education Department at the University of Minnesota Crookston. He received his PhD in criminal justice and criminology from Washington State University. His main research interests include comparative criminal justice, comparative policing, police legitimacy, international security, sexual assault, quantitative research, crime, law, and justice. His most recent publications have appeared or are forthcoming in International Criminal Justice Review; Journal of the Institute of Justice and International Studies; Victims & Offenders: An International Journal of Evidence-based Research, Policy, and Practice; International Review of Victimology; Police Practice and Research: An International Journal; Police Journal: Theory, Practice, and Principles; Asian Journal of Criminology; and Journal of Interpersonal Violence.

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