Ametqcan Journal of Community Psychology, Vol. 20, No. 5, 1992
A Longitudinal Study of the Effects of Various Crime Prevention Strategies on Criminal Victimization, Fear of Crime, and Psychological Distress I Fran H. Norris 2 Georgia State University
Krzysztof Kaniasty Indiana Universify of Pennsylvania
Examined the effects of precautionary behavior on subsequent criminal victimization, fear of crime, and psychological distress. A sample of 538 adults was interviewed three times at 6-month intervals. Four different aspects of precaution were assessed: vigilance (alertness), locks (access control), neighbors (informal cooperation), and professionals (formal programs). In logistic regressions that controlled for 14 risk factors, precaution had no preventive effects on the occurrence of subsequent crimes. LISREL models revealed that use of neighbors was the only precaution not to increase fear of crime, although both locks and neighbors showed a capacity to buffer the effects of fear on generalized distress. It was concluded that the most promising strategy was protective neighboring. Altogether, however, the promotion of citizen-initiated prevention appears highly inadequate as a policy response to problems of cr(me..and, fear. Crime is viewed as one of our nation's most serious domestic problems. Beginning with the Presidential Crime Commission of 1967, this concern 1This research was supported by Grant No. MH41579, Fran H. Norris, Principal Investigator, from the Violence and Traumatic Stress Research Branch of the National Institute of Mental Health. Appreciation is extended to Barry Ruback for his comments on a previous draft of this manuscript. 2All correspondence should be sent to Fran H. Norris, Department of Psychology, Georgia State University, University Plaza, Atlanta, Georgia 30303. 625
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has prompted the development of diverse programs and strategies for crime prevention. In the 1970s and 1980s, the U.S. Department of Justice supported a variety of crime- and fear-reducing programs involving the police, individual citizens, and entire communities (Duncan, 1980; Rosenbaum, 1986). Perhaps the single most common initiative during this time was the promotion of self-help prevention measures among citizens. Many crime prevention programs, as one facet of their total effort, encouraged individuals to take deliberate precautionary measures such as locking doors and windows, installing alarms, or cooperating with neighbors to protect each others' homes. The assumption was that a vigilant and informed citizenry reduces crime by making it more difficult to commit (Lurigio & Rosenbaum, 1986). Previous research on precaution's crime-reducing function has yielded mixed results. Lindsay and McGillis (1986) assessed the effectiveness of a block watch program in Seattle, in which citizens were given advice about neighboring strategies as well as home security. They concluded that the program was successful in reducing the incidence of burglary in participating neighborhoods. Similar findings were reported by Schneider (1986) from an intervention in Portland. The Hartford Project also provided some evidence that increased social cohesion, created via changes in the physical environment, could lower burglary rates (Fowler & Mangione, 1986). Rosenbaum, Lewis, and Grant (1986) reported overall bleak results from an intervention involving eight Chicago neighborhoods (four experimental and four control) but in the neighborhood where the program appeared to have been best implemented (most block watches), crime was significantly reduced. Although none of these programs had strong effects, other neighborhood-level interventions have produced even less evidence of crime reduction (e.g., Bennett & Lavrakas, 1989; Garofalo & McLeod, 1989, Pennel, Curtis, Henderson, & Tayman, 1989). There is a tendency to explain negative findings in terms of implementation difficulties (Was precaution really increased?) or research difficulties (Was the control group equally cautious?) rather than to question the underlying program model (Is precaution really important?). Yet some evidence does challenge the assumption that precaution is an important factor in explaining who does or does not become a victim of crime. Norris and Johnson (1988) studied eight crime prevention practices taken at the individual or household level such as locking doors and windows, engraving valuables, and asking for identification. Regardless of whether they were analyzed separately or summed together, these practices had no effect on subsequent victimization (measured 1 year after precaution was assessed). Their study, however, was limited by its fairly narrow measure of precaution and its undifferentiated
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measure of crime. Thus more specific benefits (for example, that neighboring prevents burglary) may not have been evident from their research. From its beginnings, the community crime prevention movement has recognized that fear of crime is also a serious social problem. The initially optimistic position that precaution has a fear-reducing function (DuBow & Emmons, 1981; Rosenbaum, 1986) has generated almost no empirical support. For example, in the study of Chicago neighborhoods (Rosenbaum et al., 1986), fear of crime actually increased in three of the four experimental neighborhoods, including the one where the block watch program was successful in reducing crime. In a large-scale evaluation of the Eisenhower Foundation's Neighborhood Program, Bennett and Lavrakas (1989) found that fear decreased slightly in six experimental neighborhoods, increased in one, and showed no change in three. Two smaller scale interventions (Harel & Broderick, 1980; Norton & Courlander, 1982) that attempted to reduce fear among the elderly likewise failed to produce any evidence that crime prevention activities (home security surveys, safer locks) could reduce fear of crime. Findings from crime surveys concur: Whereas Norris and Johnson (1988) found that precautionary behavior did nothing to reduce fear, Taylor, Perkins, Shumaker, and Meeks (1989) found that precaution assessed at one point in time was actually associated with a subsequent increase in fear. In light of these studies, Kidder and Cohn's (1979) writings seem particularly perceptive. They argued that strictly individualized precautionary measures do little to promote a sense of security. They may make the home secure but leave the locality full of danger. Rather than reduce the fear, they may actually remind the occupants of the danger that lurks outside. More recently, Taylor and Shumaker (1990) explained these dynamics in terms of "perceptual adaptation." They proposed that individuals adapt to the presence of crime much like they do to chronic noise or other environmental hazards. Perceptual adaptation is a potentially useful concept for explaining the fact that as crime rates increase, fear first increases but then levels off. From this perspective, precaution would be expected to precipitate fear as it resensitizes individuals to the disorder around them. From the outset, there was a certain illogic to the view that precautionary behavior could serve to reduce the user's fear. Overall, it appears that fear of crime is what primarily drives precautionary behavior (Krahn & Kennedy, 1985; Okeefe, 1986; Riger, Gordon, & LeBailley, 1982; Skogan, 1989). If fear is what motivates persons to behave with caution, it would be difficult for precaution to produce lasting reversals in fear. Logically, if the fear lessened, then precaution would cease, and the fear would return. We propose that a more fruitful conceptualization would be to view precaution as a strategy used by citizens to cope with their fear rather than
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as a means to prevent it. This fear-buffering function follows from Riger's (1985) characterization of precaution as a form of coping behavior but, in this case, the function is palliative (emotional) rather than instrumental (problem-solving) in form. A growing body of evidence suggests that fear of crime may eventuate in impaired mental health (Norris & Kaniasty, 1991; Taylor et al., 1989). Perhaps precaution provides the individual with a way of encapsulating the fear---of living with the fear inherent in contemporary life----thereby blunting its impact on other aspects of mental health. Thus the function is the prevention of more generalized states of distress, rather than the reduction of fear itself.
PRESENT STUDY In this study, we examined precautionary behavior as it is practiced at the individual or household level. Our measure of precaution encompassed four crime prevention strategies. The first strategy, vigilance, is most similar to the concept of risk management or street "savvy" advanced by Riger et al. (1982). Vigilance encompasses attempts to protect one's personal safety by means of a heightened alertness or awareness of crime. A second strategy is using locks and technology as methods of access control (e.g., Lavrakas & Lewis, 1980). The goal of this strategy is to reduce the opportunity for crime by making one's own household and vehicle secure. The third strategy, neighbors, is more public-minded (Conklin, 1975; Schneider, 1986). It incorporates acts such as surveillance (being alert to and reporting suspicious behavior) and "occupancy proxy" (making the home look occupied) and is explicitly cooperative in spirit. The final strategy, professionals, has both private and public elements. Subsuming programmatic solutions, such as home security surveys and police-sponsored block watch programs, this strategy may best capture the ideal of "co-production," wherein citizens and government work together in an active, collaborative fashion to produce public safety (e.g., Warren, Rosentraub, & Harlow, 1984). As for the effects of precaution, we considered its crime-reducing function, its fear-reducing function, and its fear-buffering function. Because the larger purpose of our study was to assess the long-term psychological consequences of crime and violence, we had detailed data on crime experiences that allowed reasonably fine distinctions between types of crimes (larceny, burglary, and violence) to be made when assessing the effects of precaution on crime. Perhaps most important, the availability of longitudinal data (3 waves, 6 months apart) was helpful with regard to addressing the cause-and-effect issues inherent in correlational research. For these rea-
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sons, we believed the study could contribute substantially to a growing body of knowledge concerning citizens' self-protective behavior.
METHOD Sample and Sampling Procedures T h e s e data are from a three-wave panel study of criminal victimization c o n d u c t e d in the state of Kentucky. In J a n u a r y 1988, a statewide sample of telephone households was generated using r a n d o m digit dialing procedures. A five-item screening instrument was used to classify all contacted households (N = 12,226) into three groups (Violent, Property, and Nonvictim) on the basis of crime incidence for the preceding 6 months. 3 Because the probability varied that a household would belong to a given category, the probability of selection for an interview also varied according to screener classification. All households reporting violent crime were selected for an interview, whereas only 2 in 5 Property households and 1 in 28 Nonvictim households were selected. Within selected households, res p o n d e n t s w e r e s e l e c t e d a c c o r d i n g to p r o c e d u r e s d e v e l o p e d by Kish (1949). 4 For Violent and Property households, one person was selected randomly from all adult household m e m b e r s experiencing the incident. F o r Nonvictim households, one person was selected randomly f r o m all adults residing in that household. Interviews were c o m p l e t e d for 175 Violent households (response rate = 71%), 328 Property households (71%), and 304 Nonvictim households (79%). Six months after the first interview, and again 6 months after that, a t t e m p t s were m a d e to reinterview all study participants, again by telephone. Response rates were reasonably high at both Wave 2 (82%) and W a v e 3 (81%). The sample of 538 persons who completed all three interviews was c o m p a r a b l e to the original sample on most characteristics.
3To establish contact with 12,226 households, it was necessary to complete 98 replicates of 224 randomly generated phone numbers. Each replicate provided a representative sample of telephone households in Kentucky. The vast majority of calls to other than the successfully contacted households were placed to nonworking or nonresidential numbers. The refusal rate at this stage was less than 5%. 4The study relied on both "informants" and "respondents." The informant was the person who answered the phone. Because calls were placed at different times of day and night and on different days of the week, there seemed to be little reason to expect a randomly selected household member to be better informed about crimes than any other member. Once a household was selected for the interview, the respondent was selected randomly, as described in the text.
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Measures
Individual and Household Characteristics The individual characteristics were age (scored in years, M = 39), sex (42% male = 0, 58% female = 1), race (93% white = 0, 7% nonwhite = 1), and education (also scored in years, M = 13). Household characteristics were another adult in household (19% one adult only = 1, 81% two or more adults = 2), children in household (49% none = 0, 51% one or more = 1), type of dwelling (79% single family = 1, 21% multiple family = 2), and tenure (18% residence less than 1 year = 1, 36% 1 to 5 years = 2, 46% more than 5 years = 3).
Crime Exposure and Fear A number of variables reflecting personal crime experiences were included in the study. Regardless of screener classification, all respondents were administered an 18-item crime incidence battery that was similar to the one used in the National Crime Survey (Lehnen & Skogan, 1984). This instrument, which was considerably more detailed than the five-item screening instrument used for household selection, 5 had a 6-month report period. At Wave 1 (January-February 1988) reports were elicited for crimes occurring "since the Fourth of July." At Wave 2 (July-August, 1988) and again at Wave 3 (January-February 1989), reports were elicited for crimes occurring "since the last time you were interviewed." Each measure of personal crime was scored as simply present (coded 1) or absent (coded 0). Larceny referred to a theft of personal property occurring outside the home. Burglary (or household theft) referred to either an illegal entry of the home or the theft of property from inside the home. Violence referred to all crimes involving force or threat of force, such as assault or robbery. These crimes will be described as prior or subsequent. Prior crimes are those that were reported in the first interview. At Wave 1, 35% of the sample reported larceny, 27% reported burglary, and 21% reported violence. Subsequent crimes are those that were reported after the first interview (i.e., at either Wave 2 or 3). At one or the other of these 5Of persons classified as violent crime victims by the screening instrument, 88% were also classified as such by the 18-item instrument, 6% were reclassified as property crime victims, and 6% were reclassified as nonvictims. O f persons classified by the screener as property crime victims, 90% were again classified as such, 3% were reclassified as violent crime victims, and 7% were reclassified as nonvictims. Of persons classified as nonvictims by the screener, 87% remained classified as nonvietims, 3% were reclassified as violent crime victims, and 10% were reclassified as property crime victims.
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interviews, 21% reported larceny, 15% reported burglary, and 12% reported violence. County crime, included as an objective indicator of crime risk, reflected rates (per 1,000) of Part I crimes in the respondent's county of residence in 1987 (range = 2.23 to 69.32). "Part I" crimes, as defined by the Federal Bureau of Investigation, encompass murder, rape, robbery, aggravated assault, burglary, larceny-theft, motor vehicle theft, and arson. To create the measure of county crime, rates were derived for each of Kentucky's 120 counties, using the FBI's Uniform Crime Report data (U.S. Department of Justice, 1984) and unpublished population figures supplied by the University of Louisville's Urban Research Institute. In Kentucky, counties are small units and socially meaningful to the citizens involved. In the present study, county crime provided a reasonable measure of the broad environment in which respondents found themselves when out and about. County crime had a nonnormal distribution because Kentucky's most populous county also has the highest crime rate. Therefore, this variable was normalized using the SPSS-X RANK Procedure. Fear of crime may be considered a subjective indicator of crime risk. Our six-item scale (o~ = .75) combined items from earlier measures (Ferraro & LaGrange, 1987; Norris & Johnson, 1988). For the present study, this measure was separated into two. Unsafe was the mean of two items (r = .48) reflecting how safe respondents felt walking alone in their neighborhoods during the day and at night. This measure served to supplement the county crime measure by providing a measure of the immediate environment in which respondents found themselves when out and about. The second measure, worry, was the mean of four items (~ = .75) reflecting respondents' concerns about being personally victimized (e.g., "When you leave your house or apartment, how often do you think about being robbed or physically assaulted?"). All items had a 4-point response format (often to never) and were coded such that a high score indicated high fear of crime. Unsafe (M = 0.96, SD = 0.76) and worry (M = 0.68, SD = 0.70) correlated .43.
Crime Prevention Strategies Precautionary behavior can be described in terms of acts, strategies, and stance. Acts are the specific behaviors such as taking extra steps in crowds, bringing in a neighbor's mail, or using deadbolt locks. Strategies are the preferences for using Vigilance (alertness), Neighbors (informal cooperation), Locks (access control), or Professionals (formal programs) that underlie one's choice of particular acts. Underlying the overall use of these
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strategies is Precaution, an even more central stance toward being careless or cautious about crime. This conceptual framework guided the development of the Crime Precaution Scale. A review of previous surveys yielded 29 candidate items that were critiqued by staff at the National Crime Prevention Institute (Louisville, KY) for their completeness, face validity, and comprehensibility. Final scale items were selected from this pool of 29 on the basis of exploratory analyses of data collected from 244 students (mean age = 25). Excluded items were those that had excessively high frequency (e.g., lock doors when away from home) or low frequency (e.g., burglar alarm), that had relatively low loadings on a well-measured factor (e.g., taking something for protection like a dog, whistle, or weapon), that made no contribution to the internal consistency of the scale (e.g., having valuables engraved), or that showed poor test-retest reliability (e.g., received professional advice about personal safety). Of the surviving 14 items, 11 are scored on a 5-point scale (never = O, almost never = 1, sometimes = 2, most o f the time = 3, all o f the time = 4), and 3 are answered either no (coded 0) or yes (coded 4).
The total scale has an alpha of .76. Subscales are scored as the means of component items. 6 To examine the construct validity of the scale, a confirmatory factor analysis was conducted using the Linear Structural Relations Program (LISREL VII; Joreskog & Sorbom, 1989) and data from this sample of 807 Kentuckians. In this model, the acts were "caused" by the strategies (first-order factors) and the strategies were caused by precaution (a second-order factor). All hypothesized factor loadings were statistically significant according to the t-values provided by the LISREL program (see Table I). As hypothesized, the second-order factor explained considerable variance in the first-order factors (39-54%), resulting in a total coefficient of determination for the first-order factors of .849. The final model fit the data quite well, Z2 (66, N = 807) = 236.32, GFI = 0.96, AGFI = 0.94, CN = 293. Psychological Distress
Three measures of psychological distress were drawn from the Brief Symptom Inventory (BSI; Derogatis & Spencer, 1982). (A 28-item version 6Questions about home security are potentially quite threatening to respondents. Before answering these questions, located at about the midpoint of the interview, respondents were reassured about the confidentiality of the information they would share and given an 800 number (the Attorney General of Kentucky's hotline) that they could call if they later became concerned about the study. These steps were undertaken primarily for ethical considerations but may also have increased the accuracy of the information reported.
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Table I. The Crime Prevention Strategies: Consistency and Frequency of Use
Factor loadingsa
Strategies Vigilance (t~ = .67) When in crowd, take extra steps to protect belongings Get someone to go with you after dark Plan route to avoid dangerous places Phone back to say you arrived safe Neighbors (0~ = .69) Neighbors keep eye on each others' homes House-sit during events such as funerals When go away for a few days, neighbors bring in mail Neighbors report suspicions to police Locks (o~ = .64) Lock car when parked at home Lock car when parked away from home Keep doors, windows locked while in home Have deadbolt locks Professionals (r = .47) Police-sponsored Neighborhood Watch Received advice about home security
.72 .66 .62 .47 .69 .68 .67 .57 .80 .60 .54 .35 .81 .62
M
SD
2.16 2.88 1.64 1.92 2.14 2.47 2.80 1.58 2.47 3.08 2.91 2.61 3.54 2.97 2.52 0.68 0.95 0.43
0.99 1.41 1.43 1.43 1.27 1.04 1.29 1.46 1.72 1.15 0.98 1.60 0.96 1.09 1.93 1.18 1.71 1.24
aAll loadings are significant, p < .05. Each subscale was scored as the mean of component items.
o f the B S I was used with the p e r m i s s i o n o f L. D e r o g a t i s . ) T h e BSI has b e e n u s e d successfully in a variety o f c o m m u n i t y p o p u l a t i o n s a n d has b e e n p a r ticularly c o m m o n in studies o f crime a n d o t h e r t r a u m a t i c life events. D e r o gatis a n d S p e n c e r ' s r e s e a r c h i n t o t h e validity o f t h e scale h a s p r o d u c e d s e p a r a t e n o r m s for c o m m u n i t y , o u t p a t i e n t , a n d i n p a t i e n t p o p u l a t i o n s . M e a n s o f nonvictims in o u r s a m p l e m a t c h t h e c o m m u n i t y n o r m s a l m o s t perfectly, w h e r e a s t h e m e a n s o f c r i m e victims fall b e t w e e n c o m m u n i t y a n d p a t i e n t n o r m s . In t h e p r e s e n t study, all items h a d a 1-month r e p o r t p e r i o d a n d a 5 - p o i n t r e s p o n s e format. S c o r e d as t h e m e a n value o f c o n t r i b u t i n g items, t h r e e B S I scales w e r e used: D e p r e s s i o n (6 items, e.g., hopeless, blue, a = .85), G e n e r a l A n x i e t y (6 items, e.g., nervous, restless, ~t = .79), a n d P h o b i c A n x i e t y (5 items, e.g., afraid in o p e n spaces, u n e a s y in crowds, o~ = .64).
RESULTS
The Crime-Reducing Function T o t e s t t h e e f f e c t i v e n e s s o f p r e c a u t i o n a r y b e h a v i o r in p r e v e n t i n g c r i m e , t h r e e logistic r e g r e s s i o n m o d e l s w e r e d e r i v e d . T h e s e m o d e l s d i f f e r e d
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in the crime under consideration and in the particular respondents included in analysis. Persons reporting acquaintance crimes at Wave 2 or 3 (n = 18) were always excluded. One analysis included 317 nonvictims and 109 victims of larceny but excluded victims of burglary and violence. These crimes were those occurring subsequent to the measurement of precaution (i.e., at either Wave 2 or 3). A second analysis included the same 317 nonvictims and 72 burglary victims. The final model included only nonvictims and 57 victims of violence. Because precaution is likely to be confounded with risk, it was important to control for those risk factors. Here, the potential risk factors were organized into three sets: individual characteristics (age, sex, race, education), household characteristics (another adult in household, children in household, type of dwelling, tenure), and prior crime and fear (worry, unsafe, county crime, prior crime). As Table II shows, the crime prevention strategies did correlate with many of these indicators of risk. Vigilance was used more by women, older people, minorities, and others who were more fearful of crime. Protective neighboring was more common among older, long-term residents of single family dwellings. Use of neighbors also tended to be higher among those people who felt safe in their neighborhoods and who had not been previously victimized. Forming a very different profile, users of locks tended to be short-term residents of multiple family dwellings who felt unsafe in their neighborhoods. They were also more educated, had fewer children, and were more likely to have been previously victimized or to live in counties with high crime rates. Use of professionals was also higher given higher county crime and previous crime, specifically larceny. The regression analysis controlled for these potential confounds when the influence of precaution was assessed. As shown in Table III, larceny was significantly more common among respondents who were younger, who were more worried about crime, or who had been previously victimized (any type). The effects of higher education and of living with no other adult approached significance, p < .07. Altogether the 14 risk factors correctly classified 34 of 109 larceny victims (31%). As for burglary, respondents who lived with no other adult and prior victims of burglary or violence were at greatest risk. The effects of the two fear indicators, which shared variance, approached significance, p < .06 for unsafe and p < .09 for worry. These risk factors correctly classified 19 of 72 burglary victims (26%). Similarly, younger people, those who felt less safe in their neighborhoods, and prior victims of violence or burglary were at greatest risk for violence. This time, 22 of 57 victims (39%) were correctly classified. Thus, whereas these models misclassified relatively few nonvictims (respectively, 7, 4, and 4%), they misclassified the majority of victims. Although
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Table II. Correlations Between the Crime Prevention Strategies and Risk Factors a
Age
Sex Race Education Another adult in household Children in household Type of dwelling Tenure Worry (about crime) Unsafe (in neighborhood) County crime Prior larceny Prior b u r g l a r y Prior violence
Vigilance
Neighbors
Locks
Professionals
.12 c .44 c .16 c -.05 -.08 -.01 -.01 .05 .26 c .31 c -.01 .02 .01 -.03
.17 c .03 -.04 .01 .01 .01 -.15 c .13 c -.01 -.16 c -.04 -.09 b -.099 -.04
.04 -.01 .06 .12 -.08 -.10 b .20e - . 1 lb .20 c .23 c .29 c .lob .lob .09 b
-.01 -.01 .02 .07 -.01 .02 .07 .01 .06 .04 .15 c .10b .04 -.01
a All variables were assessed at Wave 1. < .05.
bp
~p < .oa.
these findings point to the random nature of many crimes, such incidents are those that precaution is believed to best prevent. As for the predictive power of precaution, all analyses yielded the same conclusion: With risk held constant, not one of the crime prevention strategies discriminated between those who did and did not experience crime over the ensuing year. In the larceny model, 2 additional victims were identified when these variables were added, but 3 more nonvictims were misclassified. In the burglary model, one more nonvictim was correctly classified, but one more victim was misclassified. In the violence model, the precaution variables identified one additional victim and correctly reclassified one nonvictim who had been misclassified in the previous step. 7 It is possible, however, that precautionary behavior matters only in the presence of high risk. To examine this possibility, new categorical predictor variables were created for each combination of crime-type and precaution. Each variable had three levels: (a) low risk, (b) high risk/high use, and (c) high risk/low use. For each type of crime, risk was considered high when a crime of the same type had been experienced in the 6-month period preceding Wave 1 or when two or more other risk factors were present. The other risk factors were variables having significant coefficients 7Supplementary regressions tested the joint contributions of formal strategies (Neighborhood Watch, security advice) and informal strategies (neighbors, locks). One might argue that neighboring behaviors are more effective in the presence of a formal Neighborhood Watch or that locks are more effective when installed under professional guidance. No significant interactions emerged.
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Table III, Predicting Crime at Wave 2 or 3 from Wave 1 Measures: Logistic Regression Analysesa Larceny Set of predictors and variables Ind~idual characteristics Age Sex Race Education
b
SE b
b
SE b
-.025 b .371 -.303 .096
0.12 .306 .504 .053
-.014 .198 -.470 .077
.014 .363 .601 .063
-.0.64 d .440 -.448 .093
.019 .441 .710 .085
24.60a
-.647 -.026 -.430 -.044
Model improvement: X2(4) Crime and fear Worry about crime Unsafe (in neighborhood) County crime Prior larceny Prior burglary Prior violence
Model improvement: Xz(4)
.342 .284 .363 .194
9.61b
-1.176 c .542 -.233 .094
5.06
.496c .317 -.136 765c .889c .739b
Model improvement: xz(6) Crime prevention strategies Vigilance Neighbors Locks Professionals
Violence
SE b
Model improvement: Z2(4)
Household characteristics Another adult in household Children in household Type of dwelling Tenure
Burglary
b
-.836 -.476 .083 -.086
.516 .407 .471 .281
12.93c
.200 .223 .164 .271 .286 .321
.405 .492 -.099 .532 1.115a .748b
61.26d
-.061 -.071 .113 .189
.381 .340 .416 .230
35.93d
.182 .142 ,157 .111
.237 .261 .193 .323 .330 .370
6.78
.243 .796c .028 -.389 1.0493 2.402d
49,96d
-.201 -.027 .073 .106
3.78
.223 .156 .188 .133 1.56
.279 .309 .248 .427 .458 ,413
68.62d
-.073 .109 .225 .285
.267 .206 ,253 .162 5.73
aTable entries are final unstandardized regression coefficients.
bp
A Longitudinal Study of the Effects of Various Crime Prevention Strategies on Criminal Victimization, Fear of Crime, and Psychological Distress I Fran H. Norris 2 Georgia State University
Krzysztof Kaniasty Indiana Universify of Pennsylvania
Examined the effects of precautionary behavior on subsequent criminal victimization, fear of crime, and psychological distress. A sample of 538 adults was interviewed three times at 6-month intervals. Four different aspects of precaution were assessed: vigilance (alertness), locks (access control), neighbors (informal cooperation), and professionals (formal programs). In logistic regressions that controlled for 14 risk factors, precaution had no preventive effects on the occurrence of subsequent crimes. LISREL models revealed that use of neighbors was the only precaution not to increase fear of crime, although both locks and neighbors showed a capacity to buffer the effects of fear on generalized distress. It was concluded that the most promising strategy was protective neighboring. Altogether, however, the promotion of citizen-initiated prevention appears highly inadequate as a policy response to problems of cr(me..and, fear. Crime is viewed as one of our nation's most serious domestic problems. Beginning with the Presidential Crime Commission of 1967, this concern 1This research was supported by Grant No. MH41579, Fran H. Norris, Principal Investigator, from the Violence and Traumatic Stress Research Branch of the National Institute of Mental Health. Appreciation is extended to Barry Ruback for his comments on a previous draft of this manuscript. 2All correspondence should be sent to Fran H. Norris, Department of Psychology, Georgia State University, University Plaza, Atlanta, Georgia 30303. 625
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has prompted the development of diverse programs and strategies for crime prevention. In the 1970s and 1980s, the U.S. Department of Justice supported a variety of crime- and fear-reducing programs involving the police, individual citizens, and entire communities (Duncan, 1980; Rosenbaum, 1986). Perhaps the single most common initiative during this time was the promotion of self-help prevention measures among citizens. Many crime prevention programs, as one facet of their total effort, encouraged individuals to take deliberate precautionary measures such as locking doors and windows, installing alarms, or cooperating with neighbors to protect each others' homes. The assumption was that a vigilant and informed citizenry reduces crime by making it more difficult to commit (Lurigio & Rosenbaum, 1986). Previous research on precaution's crime-reducing function has yielded mixed results. Lindsay and McGillis (1986) assessed the effectiveness of a block watch program in Seattle, in which citizens were given advice about neighboring strategies as well as home security. They concluded that the program was successful in reducing the incidence of burglary in participating neighborhoods. Similar findings were reported by Schneider (1986) from an intervention in Portland. The Hartford Project also provided some evidence that increased social cohesion, created via changes in the physical environment, could lower burglary rates (Fowler & Mangione, 1986). Rosenbaum, Lewis, and Grant (1986) reported overall bleak results from an intervention involving eight Chicago neighborhoods (four experimental and four control) but in the neighborhood where the program appeared to have been best implemented (most block watches), crime was significantly reduced. Although none of these programs had strong effects, other neighborhood-level interventions have produced even less evidence of crime reduction (e.g., Bennett & Lavrakas, 1989; Garofalo & McLeod, 1989, Pennel, Curtis, Henderson, & Tayman, 1989). There is a tendency to explain negative findings in terms of implementation difficulties (Was precaution really increased?) or research difficulties (Was the control group equally cautious?) rather than to question the underlying program model (Is precaution really important?). Yet some evidence does challenge the assumption that precaution is an important factor in explaining who does or does not become a victim of crime. Norris and Johnson (1988) studied eight crime prevention practices taken at the individual or household level such as locking doors and windows, engraving valuables, and asking for identification. Regardless of whether they were analyzed separately or summed together, these practices had no effect on subsequent victimization (measured 1 year after precaution was assessed). Their study, however, was limited by its fairly narrow measure of precaution and its undifferentiated
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measure of crime. Thus more specific benefits (for example, that neighboring prevents burglary) may not have been evident from their research. From its beginnings, the community crime prevention movement has recognized that fear of crime is also a serious social problem. The initially optimistic position that precaution has a fear-reducing function (DuBow & Emmons, 1981; Rosenbaum, 1986) has generated almost no empirical support. For example, in the study of Chicago neighborhoods (Rosenbaum et al., 1986), fear of crime actually increased in three of the four experimental neighborhoods, including the one where the block watch program was successful in reducing crime. In a large-scale evaluation of the Eisenhower Foundation's Neighborhood Program, Bennett and Lavrakas (1989) found that fear decreased slightly in six experimental neighborhoods, increased in one, and showed no change in three. Two smaller scale interventions (Harel & Broderick, 1980; Norton & Courlander, 1982) that attempted to reduce fear among the elderly likewise failed to produce any evidence that crime prevention activities (home security surveys, safer locks) could reduce fear of crime. Findings from crime surveys concur: Whereas Norris and Johnson (1988) found that precautionary behavior did nothing to reduce fear, Taylor, Perkins, Shumaker, and Meeks (1989) found that precaution assessed at one point in time was actually associated with a subsequent increase in fear. In light of these studies, Kidder and Cohn's (1979) writings seem particularly perceptive. They argued that strictly individualized precautionary measures do little to promote a sense of security. They may make the home secure but leave the locality full of danger. Rather than reduce the fear, they may actually remind the occupants of the danger that lurks outside. More recently, Taylor and Shumaker (1990) explained these dynamics in terms of "perceptual adaptation." They proposed that individuals adapt to the presence of crime much like they do to chronic noise or other environmental hazards. Perceptual adaptation is a potentially useful concept for explaining the fact that as crime rates increase, fear first increases but then levels off. From this perspective, precaution would be expected to precipitate fear as it resensitizes individuals to the disorder around them. From the outset, there was a certain illogic to the view that precautionary behavior could serve to reduce the user's fear. Overall, it appears that fear of crime is what primarily drives precautionary behavior (Krahn & Kennedy, 1985; Okeefe, 1986; Riger, Gordon, & LeBailley, 1982; Skogan, 1989). If fear is what motivates persons to behave with caution, it would be difficult for precaution to produce lasting reversals in fear. Logically, if the fear lessened, then precaution would cease, and the fear would return. We propose that a more fruitful conceptualization would be to view precaution as a strategy used by citizens to cope with their fear rather than
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as a means to prevent it. This fear-buffering function follows from Riger's (1985) characterization of precaution as a form of coping behavior but, in this case, the function is palliative (emotional) rather than instrumental (problem-solving) in form. A growing body of evidence suggests that fear of crime may eventuate in impaired mental health (Norris & Kaniasty, 1991; Taylor et al., 1989). Perhaps precaution provides the individual with a way of encapsulating the fear---of living with the fear inherent in contemporary life----thereby blunting its impact on other aspects of mental health. Thus the function is the prevention of more generalized states of distress, rather than the reduction of fear itself.
PRESENT STUDY In this study, we examined precautionary behavior as it is practiced at the individual or household level. Our measure of precaution encompassed four crime prevention strategies. The first strategy, vigilance, is most similar to the concept of risk management or street "savvy" advanced by Riger et al. (1982). Vigilance encompasses attempts to protect one's personal safety by means of a heightened alertness or awareness of crime. A second strategy is using locks and technology as methods of access control (e.g., Lavrakas & Lewis, 1980). The goal of this strategy is to reduce the opportunity for crime by making one's own household and vehicle secure. The third strategy, neighbors, is more public-minded (Conklin, 1975; Schneider, 1986). It incorporates acts such as surveillance (being alert to and reporting suspicious behavior) and "occupancy proxy" (making the home look occupied) and is explicitly cooperative in spirit. The final strategy, professionals, has both private and public elements. Subsuming programmatic solutions, such as home security surveys and police-sponsored block watch programs, this strategy may best capture the ideal of "co-production," wherein citizens and government work together in an active, collaborative fashion to produce public safety (e.g., Warren, Rosentraub, & Harlow, 1984). As for the effects of precaution, we considered its crime-reducing function, its fear-reducing function, and its fear-buffering function. Because the larger purpose of our study was to assess the long-term psychological consequences of crime and violence, we had detailed data on crime experiences that allowed reasonably fine distinctions between types of crimes (larceny, burglary, and violence) to be made when assessing the effects of precaution on crime. Perhaps most important, the availability of longitudinal data (3 waves, 6 months apart) was helpful with regard to addressing the cause-and-effect issues inherent in correlational research. For these rea-
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sons, we believed the study could contribute substantially to a growing body of knowledge concerning citizens' self-protective behavior.
METHOD Sample and Sampling Procedures T h e s e data are from a three-wave panel study of criminal victimization c o n d u c t e d in the state of Kentucky. In J a n u a r y 1988, a statewide sample of telephone households was generated using r a n d o m digit dialing procedures. A five-item screening instrument was used to classify all contacted households (N = 12,226) into three groups (Violent, Property, and Nonvictim) on the basis of crime incidence for the preceding 6 months. 3 Because the probability varied that a household would belong to a given category, the probability of selection for an interview also varied according to screener classification. All households reporting violent crime were selected for an interview, whereas only 2 in 5 Property households and 1 in 28 Nonvictim households were selected. Within selected households, res p o n d e n t s w e r e s e l e c t e d a c c o r d i n g to p r o c e d u r e s d e v e l o p e d by Kish (1949). 4 For Violent and Property households, one person was selected randomly from all adult household m e m b e r s experiencing the incident. F o r Nonvictim households, one person was selected randomly f r o m all adults residing in that household. Interviews were c o m p l e t e d for 175 Violent households (response rate = 71%), 328 Property households (71%), and 304 Nonvictim households (79%). Six months after the first interview, and again 6 months after that, a t t e m p t s were m a d e to reinterview all study participants, again by telephone. Response rates were reasonably high at both Wave 2 (82%) and W a v e 3 (81%). The sample of 538 persons who completed all three interviews was c o m p a r a b l e to the original sample on most characteristics.
3To establish contact with 12,226 households, it was necessary to complete 98 replicates of 224 randomly generated phone numbers. Each replicate provided a representative sample of telephone households in Kentucky. The vast majority of calls to other than the successfully contacted households were placed to nonworking or nonresidential numbers. The refusal rate at this stage was less than 5%. 4The study relied on both "informants" and "respondents." The informant was the person who answered the phone. Because calls were placed at different times of day and night and on different days of the week, there seemed to be little reason to expect a randomly selected household member to be better informed about crimes than any other member. Once a household was selected for the interview, the respondent was selected randomly, as described in the text.
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Measures
Individual and Household Characteristics The individual characteristics were age (scored in years, M = 39), sex (42% male = 0, 58% female = 1), race (93% white = 0, 7% nonwhite = 1), and education (also scored in years, M = 13). Household characteristics were another adult in household (19% one adult only = 1, 81% two or more adults = 2), children in household (49% none = 0, 51% one or more = 1), type of dwelling (79% single family = 1, 21% multiple family = 2), and tenure (18% residence less than 1 year = 1, 36% 1 to 5 years = 2, 46% more than 5 years = 3).
Crime Exposure and Fear A number of variables reflecting personal crime experiences were included in the study. Regardless of screener classification, all respondents were administered an 18-item crime incidence battery that was similar to the one used in the National Crime Survey (Lehnen & Skogan, 1984). This instrument, which was considerably more detailed than the five-item screening instrument used for household selection, 5 had a 6-month report period. At Wave 1 (January-February 1988) reports were elicited for crimes occurring "since the Fourth of July." At Wave 2 (July-August, 1988) and again at Wave 3 (January-February 1989), reports were elicited for crimes occurring "since the last time you were interviewed." Each measure of personal crime was scored as simply present (coded 1) or absent (coded 0). Larceny referred to a theft of personal property occurring outside the home. Burglary (or household theft) referred to either an illegal entry of the home or the theft of property from inside the home. Violence referred to all crimes involving force or threat of force, such as assault or robbery. These crimes will be described as prior or subsequent. Prior crimes are those that were reported in the first interview. At Wave 1, 35% of the sample reported larceny, 27% reported burglary, and 21% reported violence. Subsequent crimes are those that were reported after the first interview (i.e., at either Wave 2 or 3). At one or the other of these 5Of persons classified as violent crime victims by the screening instrument, 88% were also classified as such by the 18-item instrument, 6% were reclassified as property crime victims, and 6% were reclassified as nonvictims. O f persons classified by the screener as property crime victims, 90% were again classified as such, 3% were reclassified as violent crime victims, and 7% were reclassified as nonvictims. Of persons classified as nonvictims by the screener, 87% remained classified as nonvietims, 3% were reclassified as violent crime victims, and 10% were reclassified as property crime victims.
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interviews, 21% reported larceny, 15% reported burglary, and 12% reported violence. County crime, included as an objective indicator of crime risk, reflected rates (per 1,000) of Part I crimes in the respondent's county of residence in 1987 (range = 2.23 to 69.32). "Part I" crimes, as defined by the Federal Bureau of Investigation, encompass murder, rape, robbery, aggravated assault, burglary, larceny-theft, motor vehicle theft, and arson. To create the measure of county crime, rates were derived for each of Kentucky's 120 counties, using the FBI's Uniform Crime Report data (U.S. Department of Justice, 1984) and unpublished population figures supplied by the University of Louisville's Urban Research Institute. In Kentucky, counties are small units and socially meaningful to the citizens involved. In the present study, county crime provided a reasonable measure of the broad environment in which respondents found themselves when out and about. County crime had a nonnormal distribution because Kentucky's most populous county also has the highest crime rate. Therefore, this variable was normalized using the SPSS-X RANK Procedure. Fear of crime may be considered a subjective indicator of crime risk. Our six-item scale (o~ = .75) combined items from earlier measures (Ferraro & LaGrange, 1987; Norris & Johnson, 1988). For the present study, this measure was separated into two. Unsafe was the mean of two items (r = .48) reflecting how safe respondents felt walking alone in their neighborhoods during the day and at night. This measure served to supplement the county crime measure by providing a measure of the immediate environment in which respondents found themselves when out and about. The second measure, worry, was the mean of four items (~ = .75) reflecting respondents' concerns about being personally victimized (e.g., "When you leave your house or apartment, how often do you think about being robbed or physically assaulted?"). All items had a 4-point response format (often to never) and were coded such that a high score indicated high fear of crime. Unsafe (M = 0.96, SD = 0.76) and worry (M = 0.68, SD = 0.70) correlated .43.
Crime Prevention Strategies Precautionary behavior can be described in terms of acts, strategies, and stance. Acts are the specific behaviors such as taking extra steps in crowds, bringing in a neighbor's mail, or using deadbolt locks. Strategies are the preferences for using Vigilance (alertness), Neighbors (informal cooperation), Locks (access control), or Professionals (formal programs) that underlie one's choice of particular acts. Underlying the overall use of these
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strategies is Precaution, an even more central stance toward being careless or cautious about crime. This conceptual framework guided the development of the Crime Precaution Scale. A review of previous surveys yielded 29 candidate items that were critiqued by staff at the National Crime Prevention Institute (Louisville, KY) for their completeness, face validity, and comprehensibility. Final scale items were selected from this pool of 29 on the basis of exploratory analyses of data collected from 244 students (mean age = 25). Excluded items were those that had excessively high frequency (e.g., lock doors when away from home) or low frequency (e.g., burglar alarm), that had relatively low loadings on a well-measured factor (e.g., taking something for protection like a dog, whistle, or weapon), that made no contribution to the internal consistency of the scale (e.g., having valuables engraved), or that showed poor test-retest reliability (e.g., received professional advice about personal safety). Of the surviving 14 items, 11 are scored on a 5-point scale (never = O, almost never = 1, sometimes = 2, most o f the time = 3, all o f the time = 4), and 3 are answered either no (coded 0) or yes (coded 4).
The total scale has an alpha of .76. Subscales are scored as the means of component items. 6 To examine the construct validity of the scale, a confirmatory factor analysis was conducted using the Linear Structural Relations Program (LISREL VII; Joreskog & Sorbom, 1989) and data from this sample of 807 Kentuckians. In this model, the acts were "caused" by the strategies (first-order factors) and the strategies were caused by precaution (a second-order factor). All hypothesized factor loadings were statistically significant according to the t-values provided by the LISREL program (see Table I). As hypothesized, the second-order factor explained considerable variance in the first-order factors (39-54%), resulting in a total coefficient of determination for the first-order factors of .849. The final model fit the data quite well, Z2 (66, N = 807) = 236.32, GFI = 0.96, AGFI = 0.94, CN = 293. Psychological Distress
Three measures of psychological distress were drawn from the Brief Symptom Inventory (BSI; Derogatis & Spencer, 1982). (A 28-item version 6Questions about home security are potentially quite threatening to respondents. Before answering these questions, located at about the midpoint of the interview, respondents were reassured about the confidentiality of the information they would share and given an 800 number (the Attorney General of Kentucky's hotline) that they could call if they later became concerned about the study. These steps were undertaken primarily for ethical considerations but may also have increased the accuracy of the information reported.
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Table I. The Crime Prevention Strategies: Consistency and Frequency of Use
Factor loadingsa
Strategies Vigilance (t~ = .67) When in crowd, take extra steps to protect belongings Get someone to go with you after dark Plan route to avoid dangerous places Phone back to say you arrived safe Neighbors (0~ = .69) Neighbors keep eye on each others' homes House-sit during events such as funerals When go away for a few days, neighbors bring in mail Neighbors report suspicions to police Locks (o~ = .64) Lock car when parked at home Lock car when parked away from home Keep doors, windows locked while in home Have deadbolt locks Professionals (r = .47) Police-sponsored Neighborhood Watch Received advice about home security
.72 .66 .62 .47 .69 .68 .67 .57 .80 .60 .54 .35 .81 .62
M
SD
2.16 2.88 1.64 1.92 2.14 2.47 2.80 1.58 2.47 3.08 2.91 2.61 3.54 2.97 2.52 0.68 0.95 0.43
0.99 1.41 1.43 1.43 1.27 1.04 1.29 1.46 1.72 1.15 0.98 1.60 0.96 1.09 1.93 1.18 1.71 1.24
aAll loadings are significant, p < .05. Each subscale was scored as the mean of component items.
o f the B S I was used with the p e r m i s s i o n o f L. D e r o g a t i s . ) T h e BSI has b e e n u s e d successfully in a variety o f c o m m u n i t y p o p u l a t i o n s a n d has b e e n p a r ticularly c o m m o n in studies o f crime a n d o t h e r t r a u m a t i c life events. D e r o gatis a n d S p e n c e r ' s r e s e a r c h i n t o t h e validity o f t h e scale h a s p r o d u c e d s e p a r a t e n o r m s for c o m m u n i t y , o u t p a t i e n t , a n d i n p a t i e n t p o p u l a t i o n s . M e a n s o f nonvictims in o u r s a m p l e m a t c h t h e c o m m u n i t y n o r m s a l m o s t perfectly, w h e r e a s t h e m e a n s o f c r i m e victims fall b e t w e e n c o m m u n i t y a n d p a t i e n t n o r m s . In t h e p r e s e n t study, all items h a d a 1-month r e p o r t p e r i o d a n d a 5 - p o i n t r e s p o n s e format. S c o r e d as t h e m e a n value o f c o n t r i b u t i n g items, t h r e e B S I scales w e r e used: D e p r e s s i o n (6 items, e.g., hopeless, blue, a = .85), G e n e r a l A n x i e t y (6 items, e.g., nervous, restless, ~t = .79), a n d P h o b i c A n x i e t y (5 items, e.g., afraid in o p e n spaces, u n e a s y in crowds, o~ = .64).
RESULTS
The Crime-Reducing Function T o t e s t t h e e f f e c t i v e n e s s o f p r e c a u t i o n a r y b e h a v i o r in p r e v e n t i n g c r i m e , t h r e e logistic r e g r e s s i o n m o d e l s w e r e d e r i v e d . T h e s e m o d e l s d i f f e r e d
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in the crime under consideration and in the particular respondents included in analysis. Persons reporting acquaintance crimes at Wave 2 or 3 (n = 18) were always excluded. One analysis included 317 nonvictims and 109 victims of larceny but excluded victims of burglary and violence. These crimes were those occurring subsequent to the measurement of precaution (i.e., at either Wave 2 or 3). A second analysis included the same 317 nonvictims and 72 burglary victims. The final model included only nonvictims and 57 victims of violence. Because precaution is likely to be confounded with risk, it was important to control for those risk factors. Here, the potential risk factors were organized into three sets: individual characteristics (age, sex, race, education), household characteristics (another adult in household, children in household, type of dwelling, tenure), and prior crime and fear (worry, unsafe, county crime, prior crime). As Table II shows, the crime prevention strategies did correlate with many of these indicators of risk. Vigilance was used more by women, older people, minorities, and others who were more fearful of crime. Protective neighboring was more common among older, long-term residents of single family dwellings. Use of neighbors also tended to be higher among those people who felt safe in their neighborhoods and who had not been previously victimized. Forming a very different profile, users of locks tended to be short-term residents of multiple family dwellings who felt unsafe in their neighborhoods. They were also more educated, had fewer children, and were more likely to have been previously victimized or to live in counties with high crime rates. Use of professionals was also higher given higher county crime and previous crime, specifically larceny. The regression analysis controlled for these potential confounds when the influence of precaution was assessed. As shown in Table III, larceny was significantly more common among respondents who were younger, who were more worried about crime, or who had been previously victimized (any type). The effects of higher education and of living with no other adult approached significance, p < .07. Altogether the 14 risk factors correctly classified 34 of 109 larceny victims (31%). As for burglary, respondents who lived with no other adult and prior victims of burglary or violence were at greatest risk. The effects of the two fear indicators, which shared variance, approached significance, p < .06 for unsafe and p < .09 for worry. These risk factors correctly classified 19 of 72 burglary victims (26%). Similarly, younger people, those who felt less safe in their neighborhoods, and prior victims of violence or burglary were at greatest risk for violence. This time, 22 of 57 victims (39%) were correctly classified. Thus, whereas these models misclassified relatively few nonvictims (respectively, 7, 4, and 4%), they misclassified the majority of victims. Although
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Table II. Correlations Between the Crime Prevention Strategies and Risk Factors a
Age
Sex Race Education Another adult in household Children in household Type of dwelling Tenure Worry (about crime) Unsafe (in neighborhood) County crime Prior larceny Prior b u r g l a r y Prior violence
Vigilance
Neighbors
Locks
Professionals
.12 c .44 c .16 c -.05 -.08 -.01 -.01 .05 .26 c .31 c -.01 .02 .01 -.03
.17 c .03 -.04 .01 .01 .01 -.15 c .13 c -.01 -.16 c -.04 -.09 b -.099 -.04
.04 -.01 .06 .12 -.08 -.10 b .20e - . 1 lb .20 c .23 c .29 c .lob .lob .09 b
-.01 -.01 .02 .07 -.01 .02 .07 .01 .06 .04 .15 c .10b .04 -.01
a All variables were assessed at Wave 1. < .05.
bp
~p < .oa.
these findings point to the random nature of many crimes, such incidents are those that precaution is believed to best prevent. As for the predictive power of precaution, all analyses yielded the same conclusion: With risk held constant, not one of the crime prevention strategies discriminated between those who did and did not experience crime over the ensuing year. In the larceny model, 2 additional victims were identified when these variables were added, but 3 more nonvictims were misclassified. In the burglary model, one more nonvictim was correctly classified, but one more victim was misclassified. In the violence model, the precaution variables identified one additional victim and correctly reclassified one nonvictim who had been misclassified in the previous step. 7 It is possible, however, that precautionary behavior matters only in the presence of high risk. To examine this possibility, new categorical predictor variables were created for each combination of crime-type and precaution. Each variable had three levels: (a) low risk, (b) high risk/high use, and (c) high risk/low use. For each type of crime, risk was considered high when a crime of the same type had been experienced in the 6-month period preceding Wave 1 or when two or more other risk factors were present. The other risk factors were variables having significant coefficients 7Supplementary regressions tested the joint contributions of formal strategies (Neighborhood Watch, security advice) and informal strategies (neighbors, locks). One might argue that neighboring behaviors are more effective in the presence of a formal Neighborhood Watch or that locks are more effective when installed under professional guidance. No significant interactions emerged.
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Table III, Predicting Crime at Wave 2 or 3 from Wave 1 Measures: Logistic Regression Analysesa Larceny Set of predictors and variables Ind~idual characteristics Age Sex Race Education
b
SE b
b
SE b
-.025 b .371 -.303 .096
0.12 .306 .504 .053
-.014 .198 -.470 .077
.014 .363 .601 .063
-.0.64 d .440 -.448 .093
.019 .441 .710 .085
24.60a
-.647 -.026 -.430 -.044
Model improvement: X2(4) Crime and fear Worry about crime Unsafe (in neighborhood) County crime Prior larceny Prior burglary Prior violence
Model improvement: Xz(4)
.342 .284 .363 .194
9.61b
-1.176 c .542 -.233 .094
5.06
.496c .317 -.136 765c .889c .739b
Model improvement: xz(6) Crime prevention strategies Vigilance Neighbors Locks Professionals
Violence
SE b
Model improvement: Z2(4)
Household characteristics Another adult in household Children in household Type of dwelling Tenure
Burglary
b
-.836 -.476 .083 -.086
.516 .407 .471 .281
12.93c
.200 .223 .164 .271 .286 .321
.405 .492 -.099 .532 1.115a .748b
61.26d
-.061 -.071 .113 .189
.381 .340 .416 .230
35.93d
.182 .142 ,157 .111
.237 .261 .193 .323 .330 .370
6.78
.243 .796c .028 -.389 1.0493 2.402d
49,96d
-.201 -.027 .073 .106
3.78
.223 .156 .188 .133 1.56
.279 .309 .248 .427 .458 ,413
68.62d
-.073 .109 .225 .285
.267 .206 ,253 .162 5.73
aTable entries are final unstandardized regression coefficients.
bp
