Incorporating Unstructured Socializing Into the Study of Secondary Exposure to Community Violence: Etiological and Empirical Implications.

511702 research-article2013

JIVXXX10.1177/0886260513511702Journal of Interpersonal ViolenceZimmerman et al.

Article

Incorporating Unstructured Socializing Into the Study of Secondary Exposure to Community Violence: Etiological and Empirical Implications

Journal of Interpersonal Violence 2014, Vol. 29(10) 1802–1833 © The Author(s) 2013 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0886260513511702 jiv.sagepub.com

Gregory M. Zimmerman,1 Steven F. Messner,2 and Carter Rees3

Abstract Secondary exposure to community violence, defined as witnessing or hearing violence in the community, has the potential to profoundly impact long-term development, health, happiness, and security. While research has explored pathways to community violence exposure at the individual, family, and neighborhood levels, prior work has largely neglected situational factors conducive to secondary violence exposure. The present study evaluates “unstructured socializing with peers in the absence of authority figures” as a situational process that has implications for secondary exposure to violence. Results indicate that a measure of unstructured socializing was significantly associated with exposure to violence, net of an array of theoretically relevant covariates of violence exposure. Moreover, the relationships between exposure to violence and three of the most well-established correlates of violence exposure in the literature—age, male, and prior violence—were 1Northeastern

University, Boston, MA, USA at Albany, The State University of New York, USA 3Arizona State University, Phoenix, USA 2University

Corresponding Author: Gregory M. Zimmerman, School of Criminology and Criminal Justice, Northeastern University, 417 Churchill Hall, 360 Huntington Avenue, Boston, MA 02115, USA. Email: [email protected]

Downloaded from jiv.sagepub.com at NORTH DAKOTA STATE UNIV LIB on May 23, 2015

Zimmerman et al.

1803

mediated to varying degrees by unstructured socializing. The results suggest a more nuanced approach to the study of secondary violence exposure that expands the focus of attention beyond individual and neighborhood background factors to include situational opportunities presented by patterns of everyday activities. Keywords violence exposure, youth violence, community violence Being exposed to violence in childhood and adolescence has the potential to profoundly impact long-term development, health, happiness, and security. Exposure to violence exists in many forms, including sexual abuse, physical abuse, intimate partner violence, and community violence. While juvenile violent victimization has received significant attention in the theoretical and empirical literature (Lauritsen, Laub, & Sampson, 1992; Piquero & Hickman, 2003; Schreck, Stewart, & Fisher, 2006; Schreck, Wright, & Miller, 2002; Stewart, Elifson, & Sterk, 2004), secondary exposure to community violence, defined as witnessing or hearing violence in the community (see Buka, Stichick, Birdthistle, & Earls, 2001; Gardner & Brooks-Gunn, 2009; Gibson, Morris, & Beaver, 2009), is also of particular concern to the public health community. One out of every five U.S. youths witnesses violence in his or her community in any given year (Finkelhor, Turner, Ormrod, & Hamby, 2009a, 2009b), and research has consistently documented the negative mental health and behavioral consequences for youths exposed to community violence (see Boxer et al., 2008; Buka et al., 2001; Fowler, Tompsett, Braciszewski, Jacques-Tiura, & Baltes, 2009; Lewis et al., 2012; Lynch, 2003; Margolin & Gordis, 2000; McCart et al., 2007). The prevalence and consequences of exposure to neighborhood violence prompted the formation of a national task force on children exposed to violence in 2011. As part of the Department of Justice’s (DOJ) Defending Childhood initiative, the task force held four national hearings from 2011 to 2012 to examine the scope and nature of childhood exposure to violence, and to identify strategies to address the problem. The findings of the task force, published in December 2012, indicated that an increased understanding of the complex pathways to violence exposure is critical (Listenbee et al., 2012). The pathways to community violence exposure that are most well established in the literature are those at the individual level. Research has documented demographic characteristics, parenting variables, behavioral problems, and personality characteristics that increase the risk for


1804

Journal of Interpersonal Violence 29(10)

experiencing secondary violence (for an overview, see Buka et al., 2001). Research has also begun to examine neighborhood influences on exposure to violence, after taking into account individual risk factors (Gardner & BrooksGunn, 2009; Gibson et al., 2009; Zimmerman & Messner, 2013). However, prior work has largely neglected situational factors conducive to secondary violence exposure. We maintain that a full understanding of the etiology of secondary exposure to violence necessitates a situational component. We propose a situational approach to the study of secondary violence exposure, an approach that expands the focus of attention beyond individual and neighborhood background factors to include opportunities presented by patterns of everyday activities. Drawing upon prior research that has concentrated on criminal and delinquent offending (Maimon & Browning, 2010; Osgood & Anderson, 2004; Osgood, Wilson, O’Mally, Bachman, & Johnston, 1996), we argue that “unstructured socializing with peers in the absence of authority figures” represents a situational process that has implications for secondary exposure to violence. Specifically, secondary violence exposure should be particularly prevalent when individuals (a) spend more time with their friends, a known risk factor for delinquent conduct (see Felson, 2003; Reiss, 1986; Warr, 2002), (b) spend this time in unstructured activities that increase the opportunity time (see Gottfredson, 1981) for secondary violence exposure, and (c) spend more time with friends in unsupervised activities outside of the home, school, or purview of other adults (see Anderson, 2013), whose responsibility it is to exert social control in response to deviant behavior. Based on this reasoning, we anticipate that indicators of unstructured socializing will yield associations with violence exposure net of the relationships with individual and contextual measures. Moreover, we hypothesize that indicators of unstructured socializing will mediate some of the relationships between individual characteristics, contextual conditions, and secondary exposure to violence.

Secondary Exposure to Community Violence: Extent and Repercussions Rates of secondary exposure to community violence vary widely across race, sex, socioeconomic status, and geographic location. For example, studies have found that only 1% of middle to upper class White youths witness murder (Gladstein, Rusonis, & Heald, 1992), whereas more than 40% of lowincome Black youths witness a killing (Fitzpatrick & Boldizar, 1993). In addition, well more than half of urban children and adolescents report exposure to violence in their neighborhoods (McCart et al., 2007; Stein, Jaycox,


Zimmerman et al.

1805

Kataoka, Rhodes, & Vestal, 2003), elevated rates compared with nationally representative samples (Finkelhor et al., 2009a, 2009b; Zinzow et al., 2009. We also note that there is potential measurement error associated with rates of secondary violence reported in the literature. For example, estimates depend on whether reports of youth violence exposure come from parents or from youths (see Kuo, Mohler, Raudenbush, & Earls, 2000), with parents commonly reporting less exposure to community violence among youths than youths themselves (Ceballo, Dahl, Aretakis, & Ramirez, 2001; Hill & Jones, 1997; Kliewer, Lepore, Oskin, & Johnson, 1998; Lewis et al., 2012; Lynch & Cicchetti, 2002; Richters & Martinez, 1993). In addition, estimates depend on the method for aggregating single indicators of secondary violence exposure into scales. Most studies have constructed summative scales, thereby weighting events equally despite known variation in item severity (e.g., seeing someone hit versus seeing someone shot; see Buka et al., 2001). But, some recent work has used more sophisticated item response models that take into account variation in item severity across item responses (e.g., Kuo et al., 2000; Zimmerman & Messner, 2013). Despite these differences, most studies have used an adaptation of the same survey instrument—the Survey of Exposure to Community Violence— to assess the extent of youth violence exposure (see Richters & Martinez, 1993). These studies have demonstrated that secondary exposure to community violence is a particularly consequential aspect of youths’ reality, in particular, because youths are 2 to 4 times more likely to witness community violence than to be personally victimized (Kennedy, 2008; Richters & Martinez, 1993). Furthermore, in national samples, approximately 20% of all U.S. youth report witnessing violence in their communities annually (Finkelhor et al., 2009a, 2009b), and almost 40% of U.S. youth report witnessing violence in their lifetimes (Zinzow et al., 2009). Indirect exposure to violence is thus a frequent and often commonplace occurrence among U.S. youths (Bell & Jenkins, 1993; Buka et al., 2001; Gardner & Brooks-Gunn, 2009; Gibson et al., 2009; Kennedy, 2008; McCart et al., 2007; O’Keefe, 1997; Osofsky, 1995; Schwab-Stone, Koposov, Vermeiren, & Ruchkin, 2012; Zinzow et al., 2009). These prevalence estimates are particularly vexing given the extensive list of immediate and long-term problems associated with secondary violence exposure (see Boxer et al., 2008; Buka et al., 2001; Fowler et al., 2009; Lewis et al., 2012; Lynch, 2003; Margolin & Gordis, 2000; McCart et al., 2007). Adverse emotional problems include anxiety, depression, and posttraumatic stress disorder (Fitzpatrick, Piko, Wright, & LaGory, 2005; Lynch & Cicchetti, 2002; Rosario, Salizinger, Feldman, & Ng-Mak, 2008; Terr, 1990; Wilson & Rosenthal, 2003). Elevated heart rate, altered cortisol production,


1806


and delayed pubertal development are among the medical ailments associated with exposure to secondary violence (see Buka et al., 2001; Eunice Kennedy Shriver National Institute of Child Health and Human Development, 2002). Social repercussions include disassociation from meaningful and secure relationships (Osofsky, 1995). And, secondary violence exposure increases the risk of school failure, substance use, and aggressive interpersonal behavior (Bingenheimer, Brennan, & Earls, 2005; Buka et al., 2001; Dodge, Bates, & Petit, 1990; Margolin & Gordis, 2000; Ozer, Richards, & Kliewer, 2004; Selner-O’Hagan, Kindlon, Buka, Raudenbush, & Earls, 1998). Understanding the etiology of exposure to community violence therefore warrants the attention of public safety and mental health professionals.

Correlates of Secondary Exposure to Violence: What We Know Research on the correlates of secondary exposure to community violence has been conducted primarily at the individual level. The strongest documented covariates of violence are demographic characteristics (for an overview, see Buka et al., 2001). Exposure to violence is disproportionately concentrated among racial and ethnic minorities, particularly African Americans and Hispanics (see Fitzpatrick & Boldizar, 1993; Gladstein et al., 1992; Martin, Gordon, & Kupersmidt, 1995); age accounts for approximately 25% of the variation in lifetime exposure to community violence (see Selner-O’Hagan et al., 1998), with violence exposure increasing from childhood through young adulthood (e.g., Bell & Jenkins, 1993; Gardner & Brooks-Gunn, 2009; Gibson et al., 2009; Richters & Martinez, 1993); and male youths disproportionately report being exposed to violence (see Kennedy, 2008; Kuo et al., 2000). Individual difference factors such as low self-control (Gibson et al., 2009), delinquency (Gardner & Brooks-Gunn, 2009), and violent peer associations (Zimmerman & Messner, 2013) also appear to increase the risk of secondary violence exposure. Furthermore, structural family characteristics, such as residential instability, low socioeconomic status, and non-intact family structure, are associated with exposure to violence (see Fitzpatrick & Boldizar, 1993; Martin et al., 1995; Richters & Martinez, 1993; Schubiner, Scott, & Tzelepis, 1993). However, parent–child relations appear to be largely unassociated with exposure to violence (Gorman-Smith & Tolan, 1998; Miller, Wasserman, Neugebauer, Gorman-Smith, & Kamboukos, 1999; see also Buka et al., 2001). We note, however, that high levels of family support may mitigate the detrimental consequences of exposure to violence


Zimmerman et al.

1807

(Gorman-Smith, Henry, & Tolan, 2004; Hammack, Richards, Luo, Edlynn, & Roy, 2004; T. N. Sullivan, Kung, & Farrell, 2004). Research has also begun to examine neighborhood influences on secondary exposure to violence, after taking into account individual risk factors. Studies using hierarchical models have demonstrated that higher levels of concentrated disadvantage and a lack of community youth services contribute to secondary violence exposure, net of individual characteristics (Gardner & Brooks-Gunn, 2009; Gibson et al., 2009; Zimmerman & Messner, 2013). However, situational factors conducive to secondary violence exposure are unaccounted for in the literature. We maintain that a full understanding of the etiology of secondary exposure to violence necessitates a situational component. Below, we propose a situational approach to the study of violence exposure, an approach that expands the focus of attention beyond individual and neighborhood background factors to include opportunities presented by patterns of everyday activities.

A Situational Approach to Understanding Secondary Violence Exposure The friendship group is a key developmental context during adolescence (Bagwell & Schmidt, 2011; Hansell, 1981). Play-based friendships in childhood transition to more complex relationships, based on intimacy, self-disclosure, closeness, trust, and social/emotional support, in adolescence (Berndt, 1986; Corsaro & Eder, 1990; Hartup, 1993; Newcomb & Bagwell, 1995; H. S. Sullivan, 1953). Maintaining these relationships requires significant time investment. In fact, across age, gender, and race/ethnicity (see Bagwell & Schmidt, 2011; Cairns & Cairns, 1995; Rubin, Bukowski, & Laursen, 2009), “peers are by far the greatest presence in an adolescent’s life” (Csikszentmihalyi & Larson, 1984, p. 71). A natural consequence of increased time spent with friends is a corresponding decrease in time spent with parents (Larson, Richards, Moneta, Holmbeck, & Duckett, 1996; Richards, Crowe, Larson, & Swarr, 1998). This shift in time allocation is highly correlated with time spent with peers in afterschool programs, volunteer work, and other structured activities out of the home (Anderson, 2013). However, as adolescents seek autonomy from parents and other authority figures (Steinberg, 1990), they also spend more time with friends in unsupervised activities such as pickup games (Gold, 1970) and hanging out (Agnew & Peterson, 1989). Moreover, these activities often occur without adult supervision in the community, which becomes an organizing and situational context for the development and maintenance of


1808


adolescent friendships (see Dishion, Andrews, & Crosby, 1995; Giordano, 2003). Drawing upon prior research that has concentrated on criminal and delinquent offending (Maimon & Browning, 2010; Osgood & Anderson, 2004; Osgood et al., 1996), we hypothesize that “unstructured socializing with peers in the absence of authority figures” represents a situational process that has implications for secondary exposure to violence. Specifically, research has found that delinquent behavior increases as time spent with peers increases, regardless of the behavior of the peers (Regnerus, 2002). If delinquency is indeed an inherently social activity involving associates (see Felson, 2003; Reiss, 1986; Warr, 2002), then individuals who spend more time with friends should witness violence more frequently. In addition, spending time with peers in unstructured activities, as compared with structured activities, should increase the opportunity time (see Gottfredson, 1981) available for violence exposure. Finally, inadequate monitoring reduces the potential for social control responses that could prevent exposure to violence (e.g., Cohen & Felson, 1979). Unstructured activities with friends are thus likely to be particularly conducive to secondary violence exposure. While time spent with peers, time spent in unstructured activities, and unsupervised socializing may matter independently, it is their combination in which we are interested. This comports with recent work by Weerman, Bernasco, Bruinsma, and Pauwels (2013), who found that time spent with peers is relevant only in conjunction with socializing (e.g., hanging out), being in public (i.e., engaging in unstructured activity), and being unsupervised. Ultimately, we argue that unstructured socializing with peers in the absence of authority figures represents a routine activity in the pattern of an adolescent’s everyday life (Cohen & Felson, 1979; Hindelang, Gottfredson, & Garofalo, 1978), and that this normative adolescent process (Bagwell & Schmidt, 2011; Hansell, 1981) increases the likelihood of being exposed to secondary violence. We therefore hypothesize that unstructured socializing will be associated with secondary violence exposure, net of the relationships with individual and contextual measures. We also hypothesize that indicators of unstructured socializing will mediate some of the relationships between individual characteristics, contextual conditions, and exposure to violence. This theoretical framework is predicated on the premise that some of the known correlates of exposure to violence will be strongly associated with unstructured socializing, and that their relationships with secondary exposure to violence will therefore operate indirectly through unstructured socializing.


Zimmerman et al.

1809

Method1 Participants The analysis uses data from the Project on Human Development in Chicago Neighborhoods (PHDCN), a study designed to understand how a range of individual, family, and contextual factors contribute to youth development. The PHDCN consists of several components, two of which are used in this study: a Community Survey and a Longitudinal Cohort Study. The Community Survey was constructed as a probability sample of 8,782 Chicago residents within 343 researcher-defined neighborhood clusters. These neighborhood clusters, designed to approximate local neighborhoods, averaged 8,000 people and represented all of Chicago’s 865 census tracts with respect to spatial contiguity, according to ecological boundaries, and internal homogeneity, with respect to race/ethnicity and socioeconomic status. A multi-stage sampling design was used to select city blocks within neighborhood clusters, households within city blocks, and 1 adult (18 or above) per household. This design yielded approximately 25 cases per neighborhood cluster, which allows for the estimation of neighborhood characteristics based on aggregate individual-level data (see Sampson, Raudenbush, & Earls, 1997). The Longitudinal Cohort Study was constructed as a stratified probability sample of participants in seven cohorts defined by age at baseline (0, 3, 6, 9, 12, 15, and 18). Eligible respondents in each cohort were identified using a multi-stage sampling design, which selected a simple random sample of households within 80 of the 343 neighborhood clusters. Up to three waves of data were collected during interviews with respondents and their primary caregivers from 1994 and 2002; the average time between interviews was 2.5 years. Our sample consists of all 2,344 subjects from the 9-, 12-, and 15-yearold cohorts who were interviewed at Wave 1, representing 80 neighborhood clusters across Chicago. We take advantage of the longitudinal nature of the PHDCN and model exposure to violence at Wave 3 with unstructured socializing at Wave 2 and endogenous variables at Wave 1. As with most longitudinal surveys, data were missing due to non-response (14.4% of our sample), and there was attrition between Wave 1 and Wave 3 of the study (19.5% of our sample). To address potential bias produced by missing data due to non-response and attrition, we used multiple imputation techniques to produce 10 data sets using a missingness equation that included the dependent variable, the independent variables, and theoretically and empirically relevant auxiliary variables. Results were combined across the 10 imputed data sets (Allison, 2002; Raudenbush & Bryk, 2002; Royston, 2005). We examined the robustness of


1810


our findings to estimation strategy by re-estimating all models using a listwise deletion approach and found no substantive changes from those presented in the “Results” section.

Dependent Variables Secondary exposure to community violence. The dependent variable was constructed using items from the PHDCN’s My Exposure to Violence questionnaire (Gardner & Brooks-Gunn, 2009; Gibson et al., 2009; Kindlon, Wright, Raudenbush, & Earls, 1996; Kuo et al., 2000; Selner-O’Hagan et al., 1998). This questionnaire was adapted from the Survey of Children’s Exposure to Community Violence, the most widely used measure of exposure to community violence (Richters & Martinez, 1993). Respondents reported whether they had witnessed a series of violent events in the community (1 = yes, 0 = no) in the 12 months prior to the Wave 3 interview: (a) seeing someone shoved, kicked, or punched; (b) seeing someone attacked with a weapon; (c) seeing someone shot at; (d) seeing someone shot; (e) seeing someone hurt in a serious accident; (f) seeing someone chased with the intention of injury; (g) seeing someone threatened; (h) seeing someone killed; and (i) hearing a gunshot. This scale comports with those used in prior research (e.g., Howard, Cross, Li, & Huang, 1999; Johnston, Steele, Herrera, & Phipps, 2003; Kuo et al., 2000) and has shown adequate validity and reliability in related studies (see Mohler, Kuo, Kindlon, Buka, & Earls, 1999). In our study, the reliability for each of the subject participants was .74. The dichotomous items were incorporated into a scale of exposure to violence as described in the “Analysis Strategy” section. Respondents on average were exposed to 2.5 of the 9 violent events (median = 2.0, standard deviation = 2.1, range = 0-9). Unstructured socializing. Following Osgood et al. (1996), we constructed a measure of “unstructured socializing with peers in the absence of responsible authority figures” (p. 642; see also Maimon & Browning, 2010, p. 452). At Wave 2 of data collection, adolescents responded to the following five questions: “How often do you ride around in a car/motorcycle for fun?” “How often do you hang out with friends?” “How often do you go to parties?” “How many days a week do you go out after school/at night?” and “How often do you go out with a date?” Responses to the items ranged from 1 (never) to 6 (almost every day). The items were summed and the resulting scale was standardized to form an index on which higher values represent more unstructured socializing. This scale was developed and assessed for validity and reliability by Osgood et al. and has shown adequate validity and


Zimmerman et al.

1811

reliability in subsequent research using the PHDCN (Maimon & Browning, 2010). In our study, the reliability of the items was .61.

Model Covariates Previous research on unstructured socializing (Maimon & Browning, 2010; Osgood & Anderson, 2004; Osgood et al., 1996) and exposure to community violence (see Buka et al., 2001; Gardner & Brooks-Gunn, 2009; Gibson et al., 2009; Kuo et al., 2000) guided the inclusion of individual- and neighborhood-level covariates in this study. Specifically, only theoretically relevant variables that have been shown to correlate empirically with unstructured socializing or exposure to violence are considered in this study. The inclusion of these variables can be used to examine mediating processes and protect against model misspecification and confounding. Demographic covariates. Demographic variables include age, sex (male = 1), race/ethnicity (Hispanic, African American, Caucasian, and “Other”), and immigrant status (first generation, second generation, and third generation or higher). Individual difference covariates. Behavioral and cognitive factors assessed at Wave 1 include verbal/reading ability, lack of self-control, violent peer exposure, and previous violent offending. Verbal/reading ability was constructed as the standardized sum of youths’ scores on the widely used Wechsler Intelligence Scale for Children (WISC) vocabulary test (Wechsler, 1979) and the Wide Range Achievement Test (WRAT) for reading (Wilkinson, 1993). This is a well-established tool to measure reading/verbal ability that has been used in previous research with the PHDCN (see Sampson, Morenoff, & Raudenbush, 2005). Lack of self-control was constructed as the standardized sum of parents’ responses to 17 items in the Achenbach Child Behavior Checklist. These items, scored on a scale from 1 (uncharacteristic) to 5 (characteristic), represent a respondent’s lack of inhibitory control (five items; for example, has trouble controlling impulses), present orientation (four items; for example, does not like to make detailed plans before doing something), sensation seeking (four items; for example, seeks new and exciting experiences and sensations), and lack of persistence (four items; for example, tends to give up easily). This scale had a reliability of .74 and was derived based on published research (see Achenbach, 1991; Buss & Plomin, 1975). For the violent peer exposure measure, respondents were asked how many of their friends (from 1 = none to 3 = all) engaged in each of four violent behaviors in the year preceding the baseline interview: getting into a fist fight, hitting someone


1812


with the intent of injury, attacking someone with a weapon, and robbing someone with a weapon. Based on prior research (Zimmerman & Messner, 2013), these items were summed to form a scale with a reliability of .67. Previous violent offending was measured as the count of eight violent crimes respondents engaged in during the year preceding the initial interview. Behaviors ranged from “throwing rocks at people” to “attacking someone with a weapon.” This scale is well established in the literature (see Raudenbush, Johnson, & Sampson, 2003) and has a reliability of .70. We also control for lagged secondary violence exposure. Respondents reported whether they had witnessed the same nine violent events comprising the dependent variable in the 12 months prior to the Wave 2 interview. These items were summed to form a count variable ranging from zero to nine. Similar to the dependent variable, this scale has a reliability of .74. Family-level covariates. Standard family background factors assessed at the Wave 1 interview include parents’ marital status (1 = married), family structure, and socioeconomic status. Family structure was created with the following classification scheme: (a) two parents, both biological; (b) two parents, one/both non-biological; (c) one parent, biological; and (d) one parent, nonbiological. Following established procedures (see Sampson et al., 2005), socioeconomic status was constructed from a principal components factor analysis of parental income, parental education, and parental occupation. We also measured parental supervision at the baseline interview using 13 binary (1 = yes; 0 = no) items capturing parental control (e.g., parent sets curfews), parental supervision (e.g., subject is not allowed to wander in public places without adult supervision for more than 3 hr), and parental monitoring (e.g., parent knows child’s friends). These items were adapted from the Home Observation for Measurement of the Environment (HOME) Inventory, which was designed to capture parent–child relations in the home environment (Caldwell & Bradley, 1984; Leventhal et al., 2004). These items were summed and the resulting scale was standardized to form an index with a reliability of .88. Structural neighborhood covariates. Two neighborhood structural characteristics were constructed from the 1990 decennial census: concentrated disadvantage and ethnic heterogeneity. Concentrated disadvantage is comprised of the percent of families below the poverty line, percent of households receiving public assistance, percent of non-intact families with children, percent of population unemployed, median household income in 1989, and percent of Black population. These variables were combined using a weighted factor regression score (all loadings ≥ 0.83 using principal components analysis


Zimmerman et al.

1813

with oblique rotation), such that high values of the factor score reflect high levels of concentrated disadvantage. Immigrant concentration, constructed by the sum of z scores for percent Latino and percent foreign-born (r = .91), captures neighborhood heterogeneity. These are well-established scales agreed upon by experts in the field and were constructed following established procedures previously used with this data set (Morenoff & Sampson, 1997; Raudenbush & Sampson, 1999; Sampson et al., 1997; Wikström & Loeber, 2000). Neighborhood social processes. Two variables capturing social processes occurring in the neighborhoods of subject participants were constructed from the 1995 Community Survey: collective efficacy and youth services. Collective efficacy was constructed by combining social cohesion/trust with shared expectations for social control (Sampson et al., 1997). Social cohesion/trust was measured as the sum of five items asking neighborhood residents how strongly they agreed that “this is a close-knit neighborhood,” “people are willing to help their neighbors,” “people in the neighborhood can be trusted,” “people don’t get along,” and “people in the neighborhood do not share the same values” (last two items reverse-coded). The reliability of these items was .78. Shared expectations for social control was measured by asking residents how likely neighbors would be to “do something about kids skipping school,” “do something about kids defacing a building,” “scold a child for not showing respect,” “break up a fight in front of their house,” and “organize to keep a local fire station.” The reliability of these items was .78. These scales were strongly related across neighborhood clusters (r = .80). Responses of respondents answering all 10 questions were averaged. For respondents who answered at least one but not all of the questions, a linear item response model was used to account for the number and difficulty of the answered items. The “ecometric” or aggregate-level reliability of collective efficacy (the conceptual equivalent of Cronbach’s α) was .85, meaning that the analysis can reliably tap the variance in collective efficacy at the neighborhood level. This is a validated tool that has been used extensively in prior research (see Raudenbush & Sampson, 1999; Sampson et al., 1997). A measure of youth services reflects the presence of services in the neighborhood (i.e., youth centers, recreational programs, after-school programs, mentoring and counseling services, mental health services, and crisis intervention services) aimed at keeping youths off the streets and providing youths with the resources to avoid neighborhood conflict. Luther and Goldstein (2004) discussed the importance of such services in protecting youths from violence exposure, and this scale has been validated in prior research using the PHDCN (Gardner & Brooks-Gunn, 2009; Gibson et al., 2009). This scale has a reliability of .86.2 Downloaded from jiv.sagepub.com at NORTH DAKOTA STATE UNIV LIB on May 23, 2015

1814


See Table 1 for study statistics. More detailed descriptions of study measures can be found in Gibson et al. (2009) and Zimmerman and Messner (2013).

Analysis Strategy Our analysis proceeds in two stages. First, we consider the individual, family, and contextual correlates of unstructured socializing. For this stage of analysis, we estimate a two-level regression model (a hierarchical linear model [HLM]), which generates efficient slope estimates and unbiased standard errors when level-one units (i.e., persons) nested within level-two groups (i.e., neighborhoods) share similar traits (i.e., are clustered; Raudenbush & Bryk, 2002).3 Second, we examine the relationship between unstructured socializing and secondary exposure to community violence, and whether known covariates of secondary exposure to violence operate indirectly through unstructured socializing. For this stage of analysis, we estimate a hierarchical item response model with logit form (using generalized estimating equations Hierarchical Generalized Linear Model [HGLM]) to predict the odds of witnessing each act of violence in the community. This method simultaneously utilizes the benefits of item response and HLMs, applying item response theory to the dependent variable in a random-effects setting. This approach takes into account the varying frequency and seriousness of the exposure to violence items, and estimates the relationships between violence exposure and individual, family, and neighborhood characteristics (see Raudenbush & Bryk, 2002). This model has three levels nesting items within persons within neighborhoods. The Level 1 model represents the item response measurement model and nests the dichotomous exposure to violence item responses within persons. In the Level 2 model, representing the person-level model, all individual and family characteristics are included as covariates of exposure to violence within neighborhoods. The Level 3 model, or neighborhood-level model, examines the relationship between individual variation in exposure to violence and the neighborhood-level variables (see Raudenbush et al., 2003). All models are estimated in the HLM program.

Results The Correlates of Unstructured Socializing Table 2 presents standardized coefficient estimates and confidence intervals from the two-level regression model discussed in the “Analysis Strategy” Downloaded from jiv.sagepub.com at NORTH DAKOTA STATE UNIV LIB on May 23, 2015

1815

Zimmerman et al.

Table 1. Sample Descriptive Statistics (N = 2,344 Individuals, 80 Neighborhoods).

Continuous individual-level variables Age (Wave 1) Parental supervision (Wave 1) Socioeconomic status (Wave 1) Verbal/reading ability (Wave 1) Lack of self-control (Wave 1) Violent peers (Wave 1) Prior violence (Wave 1) Unstructured socializing (Wave 2) Exposure to violence (Wave 2) Neighborhood-level variables Neighborhood disadvantage (1990 census) Immigrant concentration (1990 census) Youth services (1995 community survey) Collective efficacy (1995 community survey) Binary individual-level variables Secondary exposure to community violence (Wave 3) Seeing someone shoved, kicked, or punched Seeing someone attacked with a weapon Seeing someone shot Seeing someone shoot Seeing someone hurt in a serious accident Seeing someone chased with the intention of injury Seeing someone threatened Seeing someone killed Hearing a gunshot Male (Wave 1) Race/ethnicity (Wave 1) Hispanic African American White (reference category) Other Immigrant status (Wave 1) First Second Third (or higher; reference category) Family structure (Wave 1) Two parents, non-biological Two parents, biological (reference category) One parent, non-biological One parent, biological Married parents (Wave 1)

M

SD

Range

12.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.5

2.4 1.0 1.0 1.0 1.0 1.0 1.0 1.0 2.1

7.8-16.4 −6.5-0.9 −2.2-2.6 −2.8-3.4 −2.6-3.4 −1.3-4.0 −0.6-7.4 −2.3-2.8 0-9

0.0 0.0 0.0 0.0

1.0 1.0 1.0 1.0

−1.7-2.2 −1.3-2.5 −2.2-2.6 −1.9-2.5

n

%

978 1,410 433 208 357 1,339 530 105 554 1,181

41.7 60.1 18.5 8.9 15.2 57.1 22.6 4.5 23.6 50.4

1,074 840 333 97

45.8 35.8 14.2 4.2

294 731 1,319

12.5 31.2 56.3

503 1,074 84 683 1,310

21.5 45.8 3.6 29.1 55.9


1816


Intercept Neighborhood variables Disadvantage Immigrant concentration Youth services Collective efficacy Demographic variables Male Age Race/ethnicitya Hispanic African American Immigrant statusb First Second Family factors Family structurec Two parents, non-biological One parent, non-biological One parent, biological Married parents Parental supervision Socioeconomic status

[−0.03, 0.05] [−0.06, 0.03] [−0.09, 0.01] [−0.04, 0.05] [0.01, 0.11]

−.01 −.04 .01 .06*

95% CI

.01

β

Model 1

[−0.14, 0.01] [−0.13, 0.00] [−0.09, 0.02] [−0.12, 0.01]

[−0.04, 0.07] [−0.06, 0.04] [−0.10, 0.08] [−0.11, 0.05] [−0.01, 0.08] [−0.03, 0.08]

−.04 −.06†

.02 −.01 −.01 −.03 .03 .02

[0.08, 0.16] [0.31, 0.39]

[−0.08, 0.03] [−0.03, 0.07] [−0.03, 0.05] [−0.03, 0.08]

[−0.03, 0.04]

95% CI

−.07† −.06†

.12*** .35***

−.02 .02 .01 .03

.00

β

Model 2

.01 −.01 −.01 −.03 .04† .02

−.03 −.06†

−.07† −.07†

.11*** .31***

−.02 .03 .01 .03

.00

β

95% CI

(continued)

[−0.04, 0.07] [−0.06, 0.04] [−0.11, 0.07] [−0.11, 0.05] [0.00, 0.09] [−0.03, 0.07]

[−0.08, 0.02] [−0.12, 0.01]

[−0.14, 0.01] [−0.13, 0.00]

[0.07, 0.15] [0.27, 0.36]

[−0.08, 0.03] [−0.03, 0.08] [−0.03, 0.05] [−0.02, 0.09]

[−0.03, 0.04]

Model 3

Table 2. Multilevel Regression Model Regressing Unstructured Socializing at Wave 2 on Neighborhood and Individual Measures at Wave 1 (N = 2,344 Individuals, 80 Neighborhoods).


1817

β

Model 1 95% CI .01 .04 .06**

β 95% CI [−0.04, 0.06] [−0.01, 0.08] [0.02, 0.10]

Model 2

.00 .03 .01 .12***

β

Note. β = standardized regression coefficient; CI = confidence interval. aWhite = reference category. bThird generation or higher = reference category. cTwo parents, both biological = reference category; Models 2 and 3 also control for “Other race” (ns at p = .05); significant findings are in bold. †p < .10. *p < .05. **p < .01. ***p < .001 (two-tailed tests).

Individual differences Verbal/reading ability Lack of self-control Violent peers Prior violence

Table 2. (continued)

95% CI [−0.05, 0.05] [−0.02, 0.07] [−0.03, 0.06] [0.06, 0.18]

Model 3

1818


section. Model 1 in this table investigates the neighborhood-level covariates of unstructured socializing with peers. Examination of this model indicates that collective efficacy is positively and significantly associated with unstructured socializing (β = .06, p < .05). Model 2 incorporates the demographic, family-level, and individual difference characteristics. The results indicate that male (β = .12, p < .001) and age (β = .35, p < .001) are positively and significantly associated with unstructured socializing. In addition, exposure to violence increases as exposure to violent peers (β = .06, p < .01) increases. Note that controlling for these individual variables diminishes the coefficient of collective efficacy to non-significance. Overall, these findings comport with prior research on the correlates of unstructured socializing with peers (see Maimon & Browning, 2010; Osgood & Anderson, 2004; Osgood et al., 1996). We note, however, a difference between our study and the Maimon and Browning (2010) study also using the PHDCN. Maimon and Browning detected a significant relationship between collective efficacy and unstructured socializing, whereas this relationship was not significant in Model 2 in Table 2. We attribute this disparity to sample and methodological differences. Specifically, we use data from the 9-, 12-, and 15-year-old cohorts, whereas Maimon and Browning used data only from the 9- and 12-year-old cohorts; and, we use a multiple imputation approach, whereas they used a listwise deletion approach. To control for heterogeneity in the propensity toward violence preceding the measurement of the covariates, we include a measure of prior violent behavior in Model 3. The results indicate that prior violence is positively and significantly associated with unstructured socializing (β = .12, p < .001). The inclusion of prior violence does not result in marked changes in the coefficient estimates for male and age, but it attenuates the significant coefficient for exposure to violent peers, which becomes non-significant. This finding represents another departure from the Maimon and Browning (2010) study, which detected a significant relationship between deviant peers and unstructured socializing. However, we note that prior violence accounts for the discrepancy with respect to deviant peers.

Linking Unstructured Socializing to Secondary Exposure to Community Violence Table 3 presents odds ratios (ORs; that is, exponentiated log-odds regression coefficients) and confidence intervals from the hierarchical item response model described above. To make the results interpretable for an average person in the sample, the independent variables (not previously standardized) were grand-mean centered (see Raudenbush & Bryk, 2002).



1819

Intercept Neighborhood variables Disadvantage Immigrant concentration Youth services Collective efficacy Demographic variables Male Age Race/ethnicitya Hispanic African American Immigrant statusb First Second Family factors Family structurec Two parents, non-biological One parent, non-biological One parent, biological Married parents Parental supervision Socioeconomic status

95% CI [0.37, 0.74] [1.05, 1.28] [0.99, 1.18] [0.86, 0.99] [0.95, 1.16] [1.11, 1.47] [1.02, 1.07] [1.44, 2.35] [1.60, 2.27] [0.50, 0.83] [0.61, 0.92]

[0.78, 1.12] [0.43, 1.02] [0.61, 1.07] [0.61, 0.92] [0.91, 1.03] [0.82, 0.98]

OR

0.53**

1.16** 1.08† 0.93* 1.05

1.28** 1.04**

1.84*** 1.91***

0.65** 0.75**

0.93 0.66† 0.81 0.75** 0.97 0.90*

Model 1

0.92 0.67† 0.81 0.76** 0.96 0.89**

0.66** 0.77*

1.94*** 2.00***

1.18* 1.00

1.17** 1.07 0.92* 1.04

0.51***

OR

95% CI

[0.77, 1.10] [0.44, 1.03] [0.62, 1.07] [0.62, 0.93] [0.90, 1.02] [0.81, 0.97]

[0.51, 0.86] [0.62, 0.95]

[1.51, 2.48] [1.68, 2.38]

[1.02, 1.35] [0.97, 1.02]

[1.06, 1.29] [0.98, 1.18] [0.86, 0.99] [0.94, 1.14]

[0.36, 0.72]

Model 2

0.92 0.78 0.81 0.79* 0.97 0.90*

0.73* 0.81*

1.78*** 1.81***

1.11 0.97

1.10† 1.07 0.95 1.02

0.32***

OR

95% CI

(continued)

[0.79, 1.09] [0.50, 1.22] [0.62, 1.05] [0.65, 0.97] [0.92, 1.04] [0.83, 0.98]

[0.58, 0.92] [0.66, 0.99]

[1.39, 2.29] [1.52, 2.16]

[0.97, 1.27] [0.97, 1.00]

[0.99, 1.21] [0.98, 1.16] [0.88, 1.02] [0.94, 1.11]

[0.22, 0.46]

Model 3

Table 3. Multilevel Item Response Model Regressing Secondary Exposure to Violence at Wave 3 on Unstructured Socializing at Wave 2 and Individual and Neighborhood Covariates at Wave 1 (N = 2,344 Persons, 80 Neighborhoods).

1820


1.01 1.07* 1.11** 1.29***

OR

Model 1

[0.94, 1.08] [1.01, 1.14] [1.04, 1.18] [1.21, 1.37]

95% CI 1.01 1.06* 1.10** 1.24*** 1.44***

OR

95% CI [0.94, 1.08] [1.01, 1.13] [1.04, 1.17] [1.18, 1.32] [1.34, 1.54]

Model 2

Note. OR = odds ratio; CI = confidence interval. aWhite = reference category. bThird generation or higher = reference category. cTwo parents, both biological = reference category; all models also control for “Other race;” significant findings are in bold. †p < .10. *p < .05. **p < .01. ***p < .001 (two-tailed tests).

Individual differences Verbal/reading ability Lack of self-control Violent peers Prior violence Unstructured socializing (Wave 2) Exposure to violence (Wave 2)

Table 3. (continued)

1.00 1.04 1.06† 1.16*** 1.29*** 1.24***

OR

95% CI [0.93, 1.07] [0.99, 1.10] [0.99, 1.13] [1.10, 1.23] [1.19, 1.39] [1.19, 1.28]

Model 3

Zimmerman et al.

1821

Model 1 in Table 3 includes many of the known correlates of secondary exposure to community violence (see Buka et al., 2001), providing a baseline comparison with prior research. Regarding the contextual correlates of exposure to violence, the results indicate that the odds of being exposed to violence increase in neighborhoods with higher levels of concentrated disadvantage (OR = 1.16, p < .01) and lower levels of youth services (OR = 0.93, p < .05). These are the neighborhood factors most consistently associated with exposure to violence in prior research (see Gardner & BrooksGunn, 2009; Gibson et al., 2009; Zimmerman & Messner, 2013). Pertaining to the demographic variables, Model 1 shows that the odds of exposure to violence are higher for males (OR = 1.28, p < .01) and for older adolescents (OR = 1.04, p < .01), as compared with females and younger adolescents. In addition, the odds of exposure to violence are significantly higher for Hispanic (OR = 1.84, p < .001) and African American (OR = 1.91, p < .001) youths than for White youths, and for third generation (or higher) immigrants, as compared with first (OR = 0.65, p < .01) and second (OR = 0.75, p < .01) generation immigrants. The results also indicate that youths with married parents (OR = 0.75, p < .01) and those living in households with higher levels of socioeconomic status (OR = 0.90, p < .05) are less likely to be exposed to violence. These findings are generally consistent with research on the demographic and familial correlates of exposure to violence (Buka et al., 2001; Fitzpatrick & Boldizar, 1993; Gladstein et al., 1992; Gorman-Smith & Tolan, 1998; Miller et al., 1999; Richters & Martinez, 1993; Schubiner et al., 1993; Selner-O’Hagan et al., 1998; Singer, Anglin, Song, & Lunghofer, 1995). Model 1 further indicates that the odds of exposure to violence are higher for adolescents who lack self-control (OR = 1.07, p < .05) and who are exposed to violent peers (OR = 1.11, p < .01). Finally, the odds of violence exposure increase as prior violent offending increases (OR = 1.29, p < .001). Overall, the findings comport with previous research (e.g., Gardner & Brooks-Gunn, 2009; Gibson et al., 2009; Pratt & Cullen, 2000; Sampson et al., 1997; Warr, 2002; Zimmerman & Messner, 2013). We add our measure of unstructured socializing with peers to Model 2. The OR for “Unstructured Socializing” is 1.44 (p < .001), indicating that a one standard deviation increase in unstructured socializing is associated with a 44% (1.44 − 1) increase in the odds of secondary exposure to community violence. Next, we examine whether the relationships between the endogenous variables and exposure to violence operate indirectly through unstructured socializing. Specifically, we are interested in male, age, and prior violence, the three variables significantly associated with unstructured socializing (see Model 3 in Table 2).


1822

1.30


1.29

1.28

1.24

1.25 1.20

1.18

Without Unstructured Socializing

1.15

With Unstructured Socializing

1.10 1.04

1.05

1.00

1.00 Male

Age

Violence

Figure 1. Attenuation in odds ratios for male, age, and prior violence before and after unstructured socializing is accounted for, indicating that associations between exposure to violence and age, male, and prior violence operate, at least partly, through unstructured socializing.

Four criteria are commonly applied in the assessment of mediation (Baron & Kenny, 1986; Frazier, Tix, & Barron, 2004; James & Brett, 1984; Judd & Kenny, 1981). First, the independent variables must be significantly associated with the outcome. As discussed above, sex, age, and prior violence were significantly associated with exposure to violence (see Model 1 in Table 3). Second, the independent variables must be significantly associated with the mediator. As discussed earlier, sex, age, and prior violence were significantly associated with unstructured socializing (see Model 3 in Table 2). Third, the mediator must be significantly associated with the outcome. As discussed above, unstructured socializing was positively and significantly associated with exposure to violence (see Model 2 in Table 3). Finally, to establish complete mediation, or indirect-only mediation, the associations between the independent and dependent variables must not differ significantly from zero when controlling for the mediator. If the first three conditions are met, but the associations between the independent and dependent variables are non-zero when controlling for the mediator, partial mediation or complementary mediation is indicated (see MacKinnon, Fairchild, & Fritz, 2007; Preacher & Hayes, 2004, 2008; Zhao, Lynch, & Chen, 2010). Figure 1 shows the ORs between exposure to violence and male, age, and prior violence, split by whether unstructured socializing is accounted for. The figure indicates that the OR for “Male” is reduced by 36% from 1.28 (in Model 1 of Table 3) to 1.18 (in Model 2 of Table 3; note that the maximum


Zimmerman et al.

1823

possible reduction, or 100%, would be from 1.28 to 1.00); the OR for age is reduced by 100% from 1.04 to 1.00 when unstructured socializing is accounted for; and the OR for prior violence is reduced by 17% from 1.29 to 1.24. However, only the association between age and exposure to violence is rendered non-significant. Moreover, statistical comparisons of the regression coefficients for age, male, and prior violence between models (see Clogg, Petkova, & Haritou, 1995; Paternoster, Brame, Mazerole, & Piquero, 1998) indicate that only the coefficient for age is significantly reduced when unstructured socializing is included as a covariate of exposure to violence (p < .01). In addition to assessing attenuation, we conducted formal tests of mediation using conservative Sobel tests (MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002; Sobel, 1982) as well as more recently advocated bootstrapping techniques with bias-corrected standard errors (Fritz, Taylor, & MacKinnon, 2012; Hayes & Scharkow, 2013; Preacher & Hayes, 2008). Results from both tests indicated that the associations between exposure to violence and male, age, and prior violence were significantly mediated by unstructured socializing (all ps < .001). Taken together, the results indicate that the relationship between age and exposure to violence is completely mediated by unstructured socializing (i.e., indirect-only mediation). However, the relationship between sex and exposure to violence and the relationship between prior violence and exposure to violence are partially mediated by unstructured socializing (i.e., complementary mediation). Note that, as expected, the coefficients of the covariates that were not significantly associated with unstructured socializing in Table 2 are largely unaffected by the inclusion of unstructured socializing in the model. The coefficients for concentrated disadvantage and youth services remain significant, as do the coefficients for immigrant status, parents’ marital status, household socioeconomic status, lack of self-control, and exposure to violent peers. In Model 3, we take advantage of the longitudinal nature of the PHDCN and control for an individual’s previous experiences with community violence. As expected, violence exposure at Wave 2 is significantly associated with violence exposure at Wave 3 (OR = 1.24, p < .001). In addition, controlling for prior violence exposure reduces the coefficients for many of the covariates in the model. However, the association between unstructured socializing and exposure to violence remains significant (OR = 1.29, p < .001).

Summary and Discussion This article proposed that a full understanding of the etiology of secondary exposure to violence, a particularly consequential and often common aspect Downloaded from jiv.sagepub.com at NORTH DAKOTA STATE UNIV LIB on May 23, 2015

1824


of youths’ lives, necessitates a situational component. Specifically, drawing upon prior research that has concentrated on criminal and delinquent offending (Maimon & Browning, 2010; Osgood & Anderson, 2004; Osgood et al., 1996), we argued that “unstructured socializing with peers in the absence of authority figures” represents a situational process that has implications for violence exposure. We posited that secondary violence exposure should be particularly prevalent when individuals spend more time with their friends, a known risk factor for delinquency; when individuals spend their time with friends in unstructured activities that increase the opportunity time for secondary violence exposure; and when individuals spend more time with friends in unsupervised activities outside of the purview of adults whose responsibility it is to exert social control in response to deviant behavior. Based on this reasoning, we anticipated that unstructured socializing would be positively associated with secondary violence exposure, net of the relationships with individual and contextual measures. We also hypothesized that unstructured socializing would mediate some of the relationships between secondary exposure to violence and the known correlates of violence exposure. The results provided strong support for our main assertions. An indicator of unstructured socializing was significantly associated with exposure to violence, net of an array of theoretically relevant covariates of violence exposure. Moreover, the relationships between exposure to violence and three of the most well-established correlates of violence exposure in the literature— age, male, and prior violence—were significantly mediated by unstructured socializing. The results indicated that relationship between age and exposure to violence was completely mediated by unstructured socializing. In addition, the relationship between sex and exposure to violence, and the relationship between prior violence and exposure to violence were partially mediated by unstructured socializing (i.e., complementary mediation). We were interested primarily in male, age, and prior violence because our analyses indicated that these variables were significantly associated with unstructured socializing. We note, however, that many of the known correlates of exposure to violence were unaffected when we accounted for unstructured socializing. Specifically, the coefficients for concentrated disadvantage and youth services remained significant after the inclusion of unstructured socializing, as did the coefficients for immigrant status, parents’ marital status, household socioeconomic status, lack of self-control, and exposure to violent peers. Yet, it is possible that our measure of unstructured socializing was narrow, and mediating effects not captured by unstructured socializing, as measured, were therefore absorbed in the direct effects of the independent variables. We suggest, like others (e.g., Maimon & Browning, 2010; Osgood et al., 1996),


Zimmerman et al.

1825

that future research refine and broaden measures of unstructured socializing to better reflect the routine activities and types of guardianship that are relevant for all youths. While these possibilities represent fruitful areas for future research, we should first focus on practical issues related to the implications of unstructured socializing for exposure to violence. For example, our results indicated that the relationships between violence exposure and sex, age, and prior offending operated, at least in part, through unstructured socializing. Most notably, accounting for the relationship between exposure to violence and unstructured socializing completely mediated the relationship between age and exposure to violence. Given that the PHDCN did not go beyond the official boundaries of the city of Chicago into a wider region (Sampson et al., 1997), care must be taken in generalizing these results. Nonetheless, these results indicate the need for caution when considering the causal significance of demographic characteristics in explaining violence exposure (see Kaufman & Cooper, 2001; Sampson et al., 2005). Demographic characteristics may, in part, be significantly correlated with secondary violence exposure because they are disproportionately distributed across theoretically relevant factors that are, in turn, related to exposure to community violence. Our findings also contribute to a growing body of research finding support for the relationship between unstructured socializing with peers and risky behavior among youths. Recent research has found positive associations between unstructured socializing and general delinquency, substance use, and dangerous driving (see Haynie & Osgood, 2005; Osgood & Anderson, 2004; Osgood et al., 1996). But, this is the first study, to our knowledge, that has examined the relationship between unstructured socializing with peers and exposure to violence. We conclude by highlighting the research implications of incorporating situational mechanisms into the study of exposure to violence. Such an approach expands the focus of attention beyond individual and neighborhood background factors to include opportunities presented by patterns of everyday activities. Understanding how everyday activities encourage or protect youths from risky situations can aid in prevention efforts aimed at limiting youth exposure to violence. Ultimately, the etiology of secondary exposure to community violence and its prevention necessitate a comprehensive analysis of variation in individual, community, and situational processes. 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.


1826


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

Notes 1. The discussion of data and methods draws upon author reference Zimmerman and Messner (2013). 2. In sensitivity analysis, we re-estimated models controlling for a more extensive array of individual (family size, parental warmth, parental lack of hostility, years at residence, and preference for older peers) and contextual (residential stability, neighborhood violence, intergenerational closure, and reciprocated exchange) control variables. These variables were generally unassociated with both unstructured socializing and exposure to violence, and the results were substantively unchanged with their inclusion. 3. The standard hierarchical linear model (HLM) is appropriate, given that unstructured socializing is continuous and approximately normally distributed. Nonetheless, we investigated the validity of the normality assumption by examining the distribution of the Level 1 residuals and the Level 2 random effects. The Level 1 residuals were normally distributed, and the distributions of the Level 2 random effects had a multivariate normal distribution, lending credence to our modeling strategy.

References Achenbach, T. M. (1991). Manual for the youth self-report and 1991 profile. Burlington: Department of Psychiatry, University of Vermont. Agnew, R., & Peterson, D. M. (1989). Leisure and delinquency. Social Problems, 36, 332-350. Allison, P. D. (2002). Missing data. Thousand Oaks, CA: Sage. Anderson, A. L. (2013). Adolescent time use, companionship, and the relationship with development. In C. Gibson & M. Krohn (Eds.), Handbook of life-course criminology (pp. 111-128). New York, NY: Springer. Bagwell, C. L., & Schmidt, M. E. (2011). Friendships in childhood and adolescence (The Guilford Series on Social and Emotional Development). New York, NY: Guilford Press. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182. Bell, C. C., & Jenkins, E. J. (1993). Community violence and children on Chicago’s south side. Psychiatry, 56, 46-54. Berndt, T. J. (1986). Children’s comments about their friendships. In M. Perlmutter (Ed.), Cognitive perspectives on children’s social and behavioral development: The Minnesota symposia on child psychology (Vol. 18, pp. 189-211). Hillsdale, NJ: Lawrence Erlbaum.


Zimmerman et al.

1827

Bingenheimer, J. B., Brennan, R. T., & Earls, F. J. (2005). Firearm violence exposure and serious violent behavior. Science, 308, 1323-1326. Boxer, P., Morris, A. S., Terranova, A. M., Kithakye, M., Savoy, S. C., & McFaul, A. F. (2008). Coping with exposure to violence: Relations to emotional symptoms and aggression in three urban samples. Journal of Child and Family Studies, 17, 881-893. Buka, S. L., Stichick, T. L., Birdthistle, I., & Earls, F. J. (2001). Youth exposure to violence: Prevalence, risks, and consequences. American Journal of Orthopsychiatry, 71, 298-310. Buss, A. H., & Plomin, R. (1975). A temperament theory of personality development. New York, NY: John Wiley & Sons. Cairns, R. B., & Cairns, B. D. (1995). Lifelines and risks: Pathways of youth in our time. New York, NY: Cambridge University Press. Caldwell, B., & Bradley, R. (1984). Home observation for measurement of the environment. Little Rock: University of Arkansas at Little Rock. Ceballo, R., Dahl, T. A., Aretakis, M. T., & Ramirez, C. (2001). Inner-city children’s exposure to community violence: How much do parents know? Journal of Marriage and Family, 63, 927-940. Clogg, C. C., Petkova, E., & Haritou, A. (1995). Statistical methods for comparing regression coefficients between models. American Journal of Sociology, 100, 1261-1293. Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44, 588-608. Corsaro, W. A., & Eder, D. (1990). Children’s peer cultures. Annual Review of Sociology, 16, 197-220. Csikszentmihalyi, M., & Larson, R. (1984). Being adolescent: Conflict and growth in the teenage years. New York, NY: Basic Books. Dishion, T. J., Andrews, D. W., & Crosby, L. (1995). Antisocial boys and their friends in early adolescence: Relationship characteristics, quality, and interactional process. Child Development, 66, 139-151. Dodge, K., Bates, J., & Petit, G. (1990). Mechanisms in the cycle of violence. Science, 250, 1678-1683. Eunice Kennedy Shriver National Institute of Child Health and Human Development. (2002). Workshop on children exposed to violence: Current status, gaps, and research priorities. Washington, DC: U.S. Government Printing Office. Felson, M. (2003). The process of co-offending. Crime Prevention Studies, 16, 149167. Finkelhor, D., Turner, H., Ormrod, R., & Hamby, S. L. (2009a). Children’s exposure to violence: A Comprehensive National Survey (Bulletin). Washington, DC: U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention. Finkelhor, D., Turner, H., Ormrod, R., & Hamby, S. L. (2009b). Violence, abuse, and crime exposure in a national sample of children and youth. Pediatrics, 124, 1411-1423.


1828


Fitzpatrick, K. M., & Boldizar, J. P. (1993). The prevalence and consequences of exposure to violence among African-American youth. Journal of the American Academy of Child & Adolescent Psychiatry, 32, 424-430. Fitzpatrick, K. M., Piko, B. F., Wright, D. R., & LaGory, M. (2005). Depressive symptomatology, exposure to violence, and the role of social capital among African American adolescents. American Journal of Orthopsychiatry, 75, 262-274. Fowler, P. J., Tompsett, C. J., Braciszewski, J. M., Jacques-Tiura, A. J., & Baltes, B. B. (2009). Community violence: A meta-analysis on the effect of exposure and mental health outcomes of children and adolescents. Development and Psychopathology, 21, 227-259. Frazier, P. A., Tix, A. P., & Barron, K. E. (2004). Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology, 51, 115-134. Fritz, M. S., Taylor, A. B., & MacKinnon, D. P. (2012). Explanation of two anomalous results in statistical mediation analysis. Multivariate Behavioral Research, 47, 61-87. Gardner, M., & Brooks-Gunn, J. (2009). Adolescents’ exposure to community violence: Are neighborhood youth organizations protective? Journal of Community Psychology, 37, 505-525. Gibson, C. L., Morris, S. Z., & Beaver, K. M. (2009). Secondary exposure to violence during childhood and adolescence: Does neighborhood context matter? Justice Quarterly, 26, 30-57. Giordano, P. C. (2003). Relationships in adolescence. Annual Review of Sociology, 29, 257-281. Gladstein, J., Rusonis, E. S., & Heald, F. P. (1992). A comparison of inner-city and upper-middle class youths’ exposure to violence. Journal of Adolescent Health, 13, 275-280. Gold, M. (1970). Delinquent behavior in an American city. Belmont, CA: Brooks/ Cole. Gorman-Smith, D., Henry, D. B., & Tolan, P. H. (2004). Exposure to community violence and violence perpetration: The protective effects of family functioning. Journal of Child Clinical & Adolescent Psychology, 33, 439-449. Gorman-Smith, D., & Tolan, P. (1998). The role of exposure to community violence and developmental problems among inner-city youth. Development and Psychopathology, 10, 101-116. Gottfredson, M. R. (1981). On the etiology of criminal victimization. Journal of Criminal Law and Criminology, 72, 711-726. Hammack, P. L., Richards, M. H., Luo, Z., Edlynn, E. S., & Roy, K. (2004). Social support factors as moderators of community violence exposure among inner-city African American young adolescents. Journal of Clinical Child & Adolescent Psychology, 33, 450-462. Hansell, S. (1981). Ego development and peer friendship networks. Sociology of Education, 54, 51-63. Hartup, W. W. (1993). Adolescents and their friends. New Directions for Child and Adolescent Development, 60, 3-22.


Zimmerman et al.

1829

Hayes, A. F., & Scharkow, M. (2013). The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological Science. Advance online publication. doi:10.1177/0956797613480187 Haynie, D. L., & Osgood, D. W. (2005). Reconsidering peers and delinquency: How do peers matter? Social Forces, 84, 1109-1130. Hill, H. M., & Jones, L. P. (1997). Children’s and parents’ perceptions of children’s exposure to violence in urban neighborhoods. Journal of the National Medical Association, 89, 270-276. Hindelang, M. J., Gottfredson, M. R., & Garofalo, J. (1978). Victims of personal crime: An empirical foundation for a theory of personal victimization. Cambridge, MA: Ballinger. Howard, D. E., Cross, S. I., Li, X., & Huang, W. (1999). Parent-youth concordance regarding exposure to violence: Relationship to youth psychosocial functioning. Journal of Adolescent Health, 25, 396-406. James, L. R., & Brett, J. M. (1984). Mediators, moderators and tests for mediation. Journal of Applied Psychology, 69, 307-321. Johnston, C. A., Steele, R. G., Herrera, E. A., & Phipps, S. (2003). Parent and child reporting of negative life events: Discrepancy and agreement across pediatric samples. Journal of Pediatric Psychology, 28, 579-588. Judd, C. M., & Kenny, D. A. (1981). Process analysis: Estimating mediation in treatment evaluations. Evaluation Review, 5, 602-619. Kaufman, J. S., & Cooper, R. S. (2001). Commentary: Considerations for use of racial/ ethnic classification in etiologic research. American Journal of Epidemiology, 154, 291-298. Kennedy, A. C. (2008). An ecological approach to examining cumulative exposure to violence among urban, African American adolescents. Child & Adolescent Social Work Journal, 25, 25-41. Kindlon, D. J., Wright, B. D., Raudenbush, S. W., & Earls, F. J. (1996). The measurement of children’s exposure to violence: A Rasch analysis. International Journal of Methods in Psychiatric Research, 6, 187-194. Kliewer, W., Lepore, S. J., Oskin, D., & Johnson, P. D. (1998). The role of social and cognitive processes in children’s adjustment to community violence. Journal of Consulting and Clinical Psychology, 66, 199-209. Kuo, M., Mohler, B., Raudenbush, S. W., & Earls, F. J. (2000). Assessing exposure to violence using multiple informants: Application of hierarchical linear model. Journal of Child Psychology and Psychiatry, 41, 1049-1056. Larson, R. W., Richards, M. H., Moneta, G., Holmbeck, G., & Duckett, E. (1996). Changes in adolescents’ daily interactions with their families from ages 10 to 18: Disengagement and transformation. Developmental Psychology, 32, 744-754. Lauritsen, J. L., Laub, J. H., & Sampson, R. J. (1992). Conventional and delinquent activities: Implications for the prevention of violent victimization among adolescents. Violence and Victims, 7, 91-108. Leventhal, T., Selner, P., O’Hagan, M., Brooks-Gunn, J., Bingenheimer, J., & Earls, F. (2004). The homelife interview for the project on human development in


1830


Chicago neighborhoods: Assessment of parenting and home environment for 3-15 year olds. Parenting: Science and Practice, 4, 211-241. Lewis, T., Thompson, R., Kotch, J. B., Proctor, L. J., Litrownik, A. J., English, D. J., . . .Dubowitz, H. (2012). Parent-youth discordance about youth-witnessed violence: Associations with trauma symptoms and service use in an at-risk sample. Child Abuse & Neglect, 36, 790-797. Listenbee, R. L. Jr., Torre, J., Gregory Boyle, S. J., Cooper, S. W., Deer, S., Durfee, D. T., . . .Taguba, A. (2012). Report of the attorney general’s national task force on children exposed to violence. Washington, DC: U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention. Luther, S. S., & Goldstein, A. (2004). Children’s exposure to community violence: Implications for understanding risk and resilience. Journal of Clinical Child & Adolescent Psychology, 33, 499-505. Lynch, M. (2003). Consequences of children’s exposure to community violence. Clinical Child and Family Psychology Review, 6, 265-274. Lynch, M., & Cicchetti, D. (2002). Links between community violence and the family system: Evidence from children’s feelings of relatedness and perceptions of parent behavior. Family Process, 41, 519-532. MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation analysis. Annual Review of Psychology, 58, 593-614. MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test the significance of the mediated effect. Psychological Methods, 7, 83-104. Maimon, D., & Browning, C. R. (2010). Unstructured socializing, collective efficacy, and violent behavior among urban youth. Criminology, 48, 443-474. Margolin, G., & Gordis, E. B. (2000). The effects of family and community violence on children. Annual Review of Psychology, 51, 445-479. Martin, S. L., Gordon, T. E., & Kupersmidt, J. B. (1995). Survey of exposure to violence among the children of migrant and seasonal farm workers. Public Health Reports, 110, 268-276. McCart, M. R., Smith, D. W., Saunders, B. E., Kilpatrick, D. G., Resnick, H. S., & Ruggiero, K. J. (2007). Do urban adolescents become desensitized to community violence? Data from a national survey. American Journal of Orthopsychiatry, 77, 434-442. Miller, L. S., Wasserman, G. A., Neugebauer, R., Gorman-Smith, D., & Kamboukos, D. (1999). Witnessed community violence and antisocial behavior in high-risk, urban boys. Journal of Clinical Child Psychology, 28, 2-11. Mohler, B., Kuo, M., Kindlon, D., Buka, S., & Earls, F. (1999, April 15). Developmental variation of reliability and validity of instrument of exposure to violence. Presented at the biennial meetings of the Society for Research in Child Development, Albuquerque, NM. Morenoff, J. D., & Sampson, R. J. (1997). Violent crime and the spatial dynamics of neighborhood transition: Chicago, 1970-1990. Social Forces, 76, 31-64.


Zimmerman et al.

1831

Newcomb, A. F., & Bagwell, C. L. (1995). Children’s friendship relations: A metaanalytic review. Psychological Bulletin, 117, 306-347. O’Keefe, M. (1997). Adolescents’ exposure to community and school violence: Prevalence and behavioral correlates. Journal of Adolescent Health, 20, 368-376. Osgood, D. W., & Anderson, A. L. (2004). Unstructured socializing and rates of delinquency. Criminology, 42, 519-549. Osgood, D. W., Wilson, J., O’Mally, P., Bachman, J., & Johnston, L. (1996). Routine activities and individual deviant behavior. American Sociological Review, 61, 635-655. Osofsky, J. (1995). The effects of exposure to violence on young children. American Psychologist, 50, 782-788. Ozer, E. J., Richards, M. H., & Kliewer, W. (2004). Introduction to the special section on protective factors in the relation between community violence exposure and adjustment in youth. Journal of Clinical Child & Adolescent Psychology, 33, 434-438. Paternoster, R., Brame, R., Mazerole, P., & Piquero, A. (1998). Using the correct statistical test for the equality of regression coefficients. Criminology, 36, 859-866. Piquero, A. R., & Hickman, M. (2003). Extending Tittle’s control balance theory to account for victimization. Criminal Justice and Behavior, 30, 282-301. Pratt, T. C., & Cullen, F. T. (2000). The empirical status of Gottfredson and Hirschi’s general theory of crime: A meta-analysis. Criminology, 38, 931-964. Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36, 717-731. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879-891. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). London, England: Sage. Raudenbush, S. W., Johnson, C., & Sampson, R. J. (2003). A multivariate, multilevel Rasch model with application to self-reported criminal behavior. Sociological Methodology, 33, 169-211. Raudenbush, S. W., & Sampson, R. J. (1999). Ecometrics: Toward a science of assessing ecological settings, with application to the systematic social observation of neighborhoods. Sociological Methodology, 29, 1-41. Regnerus, M. D. (2002). Friends’ influence on adolescent theft and minor delinquency: A developmental test of peer-reported effects. Social Science Research, 31, 681-705. Reiss, A. J. Jr. (1986). Co-offender influences on criminal careers. In A. Blumstein, J. Cohen, J. Roth, & C. Visher (Eds.), Criminal careers and career criminals (pp. 121-160). Washington, DC: National Academy Press. Richards, M. H., Crowe, P. A., Larson, R., & Swarr, A. (1998). Developmental patterns and gender differences in the experience of peer companionship during adolescence. Child Development, 69, 154-163. Richters, J. E., & Martinez, P. (1993). The NIMH community violence project: I. Children as victims of and witnesses to violence. Psychiatry, 56, 7-21. Downloaded from jiv.sagepub.com at NORTH DAKOTA STATE UNIV LIB on May 23, 2015

1832


Rosario, M., Salizinger, S., Feldman, R. S., & Ng-Mak, D. S. (2008). Intervening processes between youths’ exposure to community violence and internalizing symptoms over time: The roles of social support and coping. American Journal of Community Psychology, 41, 34-62. Royston, P. (2005). Multiple imputation of missing values: Update. The Stata Journal, 5, 1-14. Rubin, K. H., Bukowski, W. M., & Laursen, B. (2009). Handbook of peer interactions, relationships, and groups. New York, NY: Guilford Press. Sampson, R. J., Morenoff, J. D., & Raudenbush, S. W. (2005). Social anatomy of racial and ethnic disparities in violence. American Journal of Public Health, 95, 224-232. Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277, 918-924. Schreck, C. J., Stewart, E. A., & Fisher, B. S. (2006). Self-control, victimization, and their influence on risky activities and delinquent friends: A longitudinal analysis using panel data. Journal of Quantitative Criminology, 22, 319-340. Schreck, C. J., Wright, R. A., & Miller, J. M. (2002). A study of individual and situational antecedents of violent victimization. Justice Quarterly, 19, 159-180. Schubiner, H., Scott, R., & Tzelepis, A. (1993). Exposure to violence among innercity youth. Journal of Adolescent Health, 14, 214-219. Schwab-Stone, M. E., Koposov, R., Vermeiren, R., & Ruchkin, V. (2012). Crosscultural findings on community exposure to violence and internalizing psychopathology: Comparing adolescents in the United States, Russia and Belgium. Child Psychiatry & Human Development, 44, 516-524. Selner-O’Hagan, M. B., Kindlon, D. J., Buka, S. L., Raudenbush, S. W., & Earls, F. J. (1998). Assessing exposure to violence in urban youth. Journal of Child Psychology and Psychiatry, 39, 215-224. Singer, M. I., Anglin, T. M., Song, L. Y., & Lunghofer, L. (1995). Adolescents’ exposure to violence and associated symptoms of psychological trauma. The Journal of American Medical Association, 273, 477-482. Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In S. Leinhardt (Ed.), Sociological methodology (pp. 290-312). Washington, DC: American Sociological Association. Stein, B. D., Jaycox, L. H., Kataoka, S., Rhodes, H. J., & Vestal, K. D. (2003). Prevalence of child and adolescent exposure to community violence. Clinical Child and Family Psychology Review, 6, 247-263. Steinberg, L. (1990). Autonomy, conflict, and harmony in the family relationship. In S. Feldman & G. R. Elliott (Eds.), At the threshold: The developing adolescent (pp. 255-276). Cambridge, MA: Harvard University Press. Stewart, E. A., Elifson, K., & Sterk, C. (2004). Integrating the general theory of crime into an explanation of violent victimization among female offenders. Justice Quarterly, 21, 159-182. Sullivan, H. S. (1953). The interpersonal theory of psychiatry. New York, NY: W. W. Norton. Sullivan, T. N., Kung, E. M., & Farrell, A. D. (2004). Relation between witnessing violence and drug use initiation among rural adolescents: Parental monitoring Downloaded from jiv.sagepub.com at NORTH DAKOTA STATE UNIV LIB on May 23, 2015

Zimmerman et al.

1833

and family support as protective factors. Journal of Clinical Child & Adolescent Psychology, 33, 488-498. Terr, L. C. (1990). Too scared to cry: Psychic trauma in childhood. New York, NY: Harper & Row. Warr, M. (2002). Companions in crime: The social aspects of criminal conduct. New York, NY: Cambridge University Press. Wechsler, D. (1979). Wechsler Intelligence Scale for Children–Revised. New York, NY: Psychological Corporation. Weerman, F. M., Bernasco, W., Bruinsma, G. J. N., & Pauwels, L. J. R. (2013). When is spending time with peers related to delinquency? The importance of where, what, and with whom. Crime & Delinquency. Advance online publication. doi:10.1177/0011128713478129 Wikström, P.-O. H., & Loeber, R. (2000). Do disadvantaged neighborhoods cause well-adjusted children to become adolescent delinquents? A study of male juvenile serious offending, individual risk and protective factors, and neighborhood context. Criminology, 38, 1109-1142. Wilkinson, G. S. (1993). WRAT-3: Wide-Range Achievement Test Administration manual. Wilmington, DE: Wide-Range. Wilson, W. C., & Rosenthal, B. S. (2003). The relationship between exposure to community violence and psychological distress among adolescents: A meta-analysis. Violence and Victims, 18, 335-352. Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of Consumer Research, 37, 197-206. Zimmerman, G. M., & Messner, S. F. (2013). Individual, family background, and contextual explanations of racial and ethnic disparities in youths’ exposure to violence. American Journal of Public Health, 103, 435-442. Zinzow, H. M., Ruggiero, K. J., Resnick, H. S., Hanson, R., Smith, D., Saunders, B., & Kilpatrick, D. G. (2009). Prevalence and mental health correlates of witnessed parental and community violence in a national sample of adolescents. Journal of Child Psychology and Psychiatry, 50, 441-450.

Author Biographies Gregory M. Zimmerman is an assistant professor of criminology and criminal justice at Northeastern University. His research is focused on the interrelationships among individual and contextual causes of criminal offending. Steven F. Messner is a distinguished teaching professor of sociology at the University at Albany, State University of New York. His research focuses primarily on the relationship between social organization and crime, with a particular emphasis on criminal homicide. He also studies the spatial patterning of violent crime, crime in China, and the situational dynamics of violence. Carter Rees is an assistant professor of criminology and criminal justice at Arizona State University. His work applies the theoretical and statistical concepts of social network analysis to the longitudinal study of delinquency.


The covariates of parent and youth reporting differences on youth secondary exposure to community violence.

Incorporating exposure-response modeling into the assessment of QTc interval: A potential alternative to the thorough QT study.

Incorporating culture into the study of affect and health.

Coping styles moderate the relationships between exposure to community violence and work-related outcomes.

A simplified framework for incorporating health into community development initiatives.

Incorporating a research study into undergraduate clinical.

EXPOSURE TO DOMESTIC VIOLENCE AND CHILDHOOD EMOTIONAL ABUSE: Childhood Domestic Violence Exposure among a Community Sample of Adult Perpetrators: What Mediates the Connection?

Assessing Adult Exposure to Community Violence: A Review of Definitions and Measures.

"Community vital signs": incorporating geocoded social determinants into electronic records to promote patient and population health.

Profiles of Community Violence Exposure Among African American Youth: An Examination of Desensitization to Violence Using Latent Class Analysis.

Exposure to community violence and social maladjustment among urban African American youth.

Testing pathways linking exposure to community violence and sexual behaviors among African American youth.

Effects of witnessing or exposure to community violence on mental health of Iraqi men.

Empirical versus Etiological Approaches in Oriental Medical Research.

Patterns of teen exposure to a community-based violence prevention project.

Effects of Exposure to Domestic Physical Violence on Children's Behavior: A Chinese Community-based Sample.

Double disadvantage: the influence of childhood maltreatment and community violence exposure on adolescent mental health.

The Violence Prevention Community Meeting: A Multi-Site Study.

Socioemotional Adjustment as a Mediator of the Association between Exposure to Community Violence and Academic Performance in Low-Income Adolescents.

partners: a new pathway to secondary trauma and relationship violence?

Examining the Pathologic Adaptation Model of Community Violence Exposure in Male Adolescents of Color.

Socializing a Plastic Surgeon.

Empirical calibrated radiocarbon sampler: a tool for incorporating radiocarbon-date and calibration error into Bayesian phylogenetic analyses of ancient DNA.

Secondary alexithymia: an empirical validation.