"Neighborhood matters": assessment of neighborhood social processes.

Am J Community Psychol (2014) 54:187–204 DOI 10.1007/s10464-014-9681-z

ORIGINAL ARTICLE

‘‘Neighborhood Matters’’: Assessment of Neighborhood Social Processes David Henry • Deborah Gorman-Smith Michael Schoeny • Patrick Tolan

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Published online: 7 October 2014 Society for Community Research and Action 2014

Abstract Neighborhoods are important contexts for understanding development and behavior, but cost and difficulty have challenged attempts to develop measures of neighborhood social processes at the neighborhood level. This article reports the development, reliability, and validity of Neighborhood Matters, a collection of instruments assessing three aspects of neighborhood social processes, namely, norms (five subscales), informal social control (six subscales and total scale), social connection (two subscales), as well as individual scales for assessing neighborhood change, neighborhood resources, and neighborhood problems. Six hundred six residents of Chicago, chosen at random from 30 neighborhoods (defined by US Census tracts), completed the measures. Neighborhoods were selected randomly from pools that balanced poverty and predominant (African-American vs. Latino Hispanic) ethnicity. Within each neighborhood 20 individuals were selected at random, balanced by age (18–24 vs. 30?) and gender. Scaling and item analysis permitted reduction of the number of items in each scale. All subscales had individual-level internal consistency in excess of .7. Generalizability theory analysis using random effects regression models found significant shared variance at the Electronic supplementary material The online version of this article (doi:10.1007/s10464-014-9681-z) contains supplementary material, which is available to authorized users. D. Henry (&) University of Illinois at Chicago, Chicago, IL, USA e-mail: [email protected] D. Gorman-Smith M. Schoeny University of Chicago, Chicago, IL, USA P. Tolan University of Virginia, Charlottesville, VA, USA

neighborhood level for three norms subscales, four informal social control subscales, both social connection subscales, and the neighborhood change, resources and problems scales. Validity analyses found significant associations between neighborhood-level scores on multiple Neighborhood Matters scales and neighborhood levels of violent, property, and drug-related crime. Discussion focuses on potential applications of the Neighborhood Matters scales in community research. Keywords Neighborhoods Social processes Cohesion Norms Measurement Ecological assessment

Introduction There is considerable evidence that characteristics of neighborhoods have implications for youth health and development (Brooks-Gunn et al. 1993; Gorman-Smith et al. 1999, 2000; Leventhal and Brooks-Gunn 2000; Sampson 1997). A large body of research conducted over the last 20 years has demonstrated that neighborhood conditions are associated with a host of youth outcomes including youth violence (Chung and Steinberg 2006; Loeber and Wikstrom 1993), academic achievement (e.g., Dornbusch et al. 1991; Duncan 1994; Entwisle et al. 1994; Halpern-Felsher et al. 1997), social competence (Kupersmidt et al. 1995), and aggression (e.g., Lynam et al. 2000; Peeples and Loeber 1994). Much of this research has focused on structural characteristics of poor urban communities that might carry risk, such as concentrated poverty, racial segregation, low owner occupancy and high mobility and crime rates (Brooks-Gunn et al. 1997; Coulton et al. 1990). This research has clearly established that child development varies by these differences in residential

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ecology; i.e., that ‘‘neighborhoods matter.’’ In addition, work emanating from early sociological characterization of neighborhoods and social support studies has produced interest in and tests of how social relationships within neighborhoods might help explain differences in community rates of problems. For example, Sampson et al. (1997) measured how informal social control of behavior and felt connection to neighbors explained violence rate variations, noting that the composite of these, collective efficacy, could predict rates. While this study and others have spurred a resurgence in understanding how neighborhoods affect child development, the field has been limited by constraints in specificity, completeness, and clarity about scale reliability and validity for many constructs theorized as how neighborhoods affect child development. The present article focuses on an effort that builds from this rich theory and these important preceding efforts to report on a set of scales developed and validated to capture the multiple constructs invoked to explain neighborhood effects. The scholarship to date can be characterized as focusing on two distinct but related approaches to understanding neighborhoods as influences on youth violence. The first approach focuses on identifying and understanding neighborhood characteristics that relate to crime and violence occurring within a neighborhood to explain variations in violence rates between neighborhoods (Sampson 1997; Shaw and McKay 1942; Warner and Rountree 1997). The second approach has been to relate social and economic differences of communities to disparities in child development (Brooks-Gunn et al. 1993, 1997; Buu et al. 2009; Leventhal and Brooks-Gunn 2000; McLoyd 1990). This approach focuses on the relation of neighborhood characteristics to individual development. Although related, these two approaches remain relatively distinct and unconnected in both their conceptual basis and their analytic focus. Sociological theories of neighborhood effects are generally applied without careful consideration of how neighborhood conditions may interact with other developmental systems (family, school, peers) and with individual characteristics. Studies based in a developmental approach have generally oversimplified complex social processes, often reducing neighborhood processes to relative poverty or presumption of disorder. The development of measures of neighborhood social processes outlined here is intended to connect the knowledge base in each area by developing measures of neighborhood social processes that incorporate the most promising empirical findings and theoretical formulations from each into an approach that integrates a developmental perspective. Building from a developmental-ecological model (Bronfenbrenner 1979, 1986; Tolan et al. 1995) and the theoretical and empirical literature on community and neighborhood influences on youth development (Leventhal

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Am J Community Psychol (2014) 54:187–204

and Brooks-Gunn 2000; Sampson et al. 1997, 2002), the intent is to develop measures that capture important characteristics and social processes of neighborhoods to better understand direct effects on youth outcomes, particularly youth violence, but also indirect effects through or in interaction with other important socializing systems such as family, peer and schools. Developmental Ecology of Neighborhoods, Families, and Risk A developmental-ecological perspective on risk, protection and prevention informs the approach taken here. This perspective is closely aligned with Bronfenbrenner’s social ecological model of development (Bronfenbrenner 1979, 1988), a central tenet of which is that individual development is influenced by the ongoing qualities of the social settings in which the child lives or participates and the extent and nature of the interaction between these settings. In this model, child patterns and outcomes are influenced by microsystems in which the child develops including family functioning, peer relationships, schools, and neighborhoods, and these in-turn are nested within larger community differences and societal influences. While this approach notes that multiple systems of influence are important, family is considered the primary microsystem central to child development (Parke et al. 2004). Within this developmental-ecological model then, there may be differences in family functioning, strains on the family, or how parenting practices are utilized depending on neighborhood characteristics. For example, when neighborhood social connections are weak or absent, parents may be more anxious about controlling their children’s activities and assuring their safety likely to emphasize safety and be controlling with children. In addition, the effects of parenting practices or quality of family relationships may also vary when neighborhoods differ in social or structural characteristics (Furstenberg 1993; Gorman-Smith et al. 2000; Hoffart et al. 2002). Measurement Approaches Measurement of neighborhood social processes has been approached from individual-level and neighborhood level perspectives. In community psychology, the concept of psychological sense of community was first defined as individual ‘‘perception of similarity to others, an acknowledged interdependence with others, a willingness to maintain this interdependence by giving to or doing for others what one expects from them, and the feeling that one is part of a larger dependable and stable structure’’ (Sarason 1974, p. 157). Since its introduction, and despite some early work criticized as atheoretical and a ‘‘fuzzy community


psychology concept’’ (Pretty 1990, p. 60), a large body of theoretical and empirical literature has emerged. Exemplary is the work of Chavis et al. (1986) and McMillan and Chavis (1986), whose Sense of Community Index (Chavis et al. 2008) measures four aspects of psychological sense of community: (1) Membership (e.g., ‘‘I can trust people in this community’’), (2) Influence (e.g., ‘‘I care what other community members think of me’’), (3) Fulfillment of needs (e.g., ‘‘When I have a problem I can talk about it with members of this community’’), and (4) Shared emotional connection (e.g., ‘‘Members of this community care about each other.’’). Psychological sense of community is an individual-level construct. One study (Long and Perkins 2003) found some evidence for community-level differences in psychological sense of community, but did not find that items at the community level were structured according to the McMillan and Chavis (1986) dimensions. Approaching measurement of neighborhood social processes from a sociological perspective, Sampson et al. (1997) found that the relation of neighborhood structural characteristics (such as poverty) to crime was mediated by a construct they termed ‘‘collective efficacy,’’ defined as ‘‘willingness of local residents to intervene for the common good’’ (p. 919). The construct of neighborhood collective efficacy combines norms, informal social control, and social connection, reflecting the measures collected by the Project on Human Development in Chicago Neighborhoods (Sampson 2012). Like the studies on psychological sense of community, this work raises the question of dimensionality, i.e., the extent to which the components of collective efficacy are distinct at the neighborhood level. Strong neighborhood-level correlations would suggest that they represent a single underlying characteristic, but moderate correlations would raise the possibility of profiles that could be useful in assessment and planning intervention. For example, strong norms but weak informal social control would suggest a different community intervention approach than strong norms and informal social control with weak cohesion. Two major reviews of the neighborhood effects literature identified a substantial set of constructs representing neighborhood structural characteristics and social processes but both also noted little consistency in the way social processes were defined, theoretically related to structural characteristics and outcomes, or measured (Orlinski et al. 1994; Sampson et al. 2002). A third concern was confusing individual perceptions with representing characteristics of the neighborhood (cf., Trickett and WIlkinson 1979). The reviews were also consistent in calling for more robust theoretical influence on measures, more careful relating across constructs, and appropriate scaling and validation of measures. Also emphasized was the was need for both consideration of multiple aspects of neighborhood social process and the relation to structural

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characteristics within the same study to better understand the contributions of each to risk and to better inform intervention and prevention. Recent measurement development has broadened the constructs assessed. For example, Leykin et al. (2013) developed measures of community resiliency, i.e., the factors enabling communities to respond positively to disaster. Others have broadened the types of informants normally assessed. Smith et al. (2013) developed a collective efficacy measure to be used in after school programs. Recent investigations also have been more likely to use methods appropriate for assessing the effects of neighborhood social processes as neighborhood-level variables (e.g., O’Brien and Kauffman 2013). Key Constructs and Sources This article reports the development and evaluation of a set of scales representing distinct but interrelated constructs that comprise the critical neighborhood social processes likely to influence child development. Three broad areas have been identified in the literature as important processes of neighborhood social influence on risk that have the potential to inform prevention and intervention efforts. These are: (a) social norms; (b) informal social control; and (c) social support and social connection. Each of these constructs has meaning at both the individual and neighborhood levels of analysis, and has been empirically demonstrated to have value in explaining individual risk and behavior. Social Norms The power of social norms to influence behavior is one of the most enduring findings in the social and behavioral sciences (Deutsch and Gerard 1955; Roethlisberger and Dickson 1939; Sherif 1936; Thomas 1917). Social norms are shared beliefs about expected or acceptable behavior and attitudes. Investigations of normative influence on child development and risk have differentiated descriptive norms (Cialdini et al. 1991) or informational social influence (Deutsch and Gerard 1955), that involves people adjusting their behavior after observing the behavior of others (e.g., residents shovel snow off of their sidewalks because they see everyone in the neighborhood doing so) from prescribed or imposed behavioral control, through injunctive norms (Cialdini et al. 1991) or normative social influence (Deutsch and Gerard 1955). Injunctive norms are standards of acceptable behavior that are collectively enforced (e.g., residents ask a neighbor to clean up his/her yard due to having a shared belief one should keep your resident clean and neat). Both descriptive and injunctive

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norms are thought to produce conformity but differing in how coercive and conflict engendering they may be (Katz and Kahn 1978). When norms have been considered empirically, results suggest they can be influential aspects of social problems. For example, Massey and colleagues found that high concentration of neighbors who approve of deviant behavior makes it more likely that children will be socialized into violence or crime (Massey and Denton 1993; Massey et al. 1991). Similarly, using data from the Philadelphia Teen Study (PTS), Teitler (1996) found neighborhood-level adult norms for adolescent sexual initiation related to youth sexual behavior, although this effect was limited to primarily white neighborhoods and did not hold for primarily African-American neighborhoods. Analyzing data from the Los Angeles Family and Neighborhood Survey, Musick et al. (2008) found lower levels of youth smoking within neighborhoods with strong norms against youth substance use combined with high child-centered social control. Similarly, Aherna et al. (2009) reported that neighborhood norms about adolescent smoking moderated the effect of collective efficacy (defined as social cohesion among neighbors combined with willingness to intervene on behalf of the common good), with collective efficacy related to more smoking in neighborhoods with norms more accepting of smoking and related to less smoking in those neighborhoods with norms less accepting of adolescent smoking. These studies highlight the importance of distinguishing what is typical behavior (descriptive norms) from what is desired or expected behavior (injunctive norms) for participants in a neighborhood setting. In addition, other research has suggested the importance of the degree to which a setting fosters awareness about behavioral expectations (norm salience; Bettenhausen and Murnighan 1985; Cialdini et al. 1991; Henry et al. 2000b; Raven and Rubin 1976; Sherif 1936). Descriptive norms, injunctive norms, and norm salience provide the framework for our approach to measuring norms and assessing the reliability of measurement. Consistent with Katz and Kahn’s (1978) defining features of a system norm and the measurement approaches used in the existing literature about neighborhood norms, we (1) created items tapping beliefs about various aspects of neighborhood life that may impact child and adolescent development, including child management, child protection, adolescent behavior, crime, and neighborhood management; (2) assessed perceived neighborhood support for such beliefs (e.g., salience/informal social control related to neighborhood norms), and (3) calculated the statistical commonality (shared variance in a typical neighborhood) of such beliefs and perceptions, as well as the internal consistency of responses to items within individuals.

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Informal Social Control Social control has been central in attention to neighborhood effects on crime and refers generally ‘‘to the capacity of a group to regulate its members according to desired principles’’ (Sampson et al. 1997, p. 918). Examples of informal social control include willingness of adults to manage child behaviors in the neighborhood, promoting pride in caring for private and public areas, and intervening when others are disturbing or disrupting public space. The critical characteristic is that rather than relying on formal control (e.g., the police), neighborhood residents take on responsibility for and authority to help regulate each other’s behavior collectively and informally. Perhaps the most influential study is the report of Sampson et al. (1997), who found that the relation of neighborhood structural characteristics to crime was mediated by collective efficacy, which as measured in that study, represents most fundamentally the construct of social control or ‘‘willingness of local residents to intervene for the common good’’ (p. 919). Emerging from factor analytic work, this measure assumes that levels of informal social control will be consistent across areas of neighborhood concern. That is, it assumes that neighborhoods with strong informal social control of crime in one area will be equally strong in all areas. The measures developed for this study make it possible to explore variability among neighborhoods in norms and informal social control. There has been little attention to variation in the forms and areas of informal social control that might occur among neighborhoods. In one neighborhood residents may act to control youth gathering and noise but tolerate great variation in parental harsh discipline of young children. Another neighborhood may enforce norms about use of public space but ignore management of private residences. The extent of informal social control may vary as a function of the developmental stages of neighborhood children and adolescents (e.g., regarding misbehaving children as each parent’s concern, but seeing misbehaving adolescents as a neighborhood problem). Moreover, informal social control enforces neighborhood norms, making it likely that the strength of informal social control in any particular area will reflect the strength of norms. Thus, we developed measures of informal social control that were consistent with the areas of neighborhood norms and related to potential neighborhood influences on child development (e.g., child welfare, parenting/child management, youth problem behaviors, academic achievement, and neighborhood management). Social Connection and Support A third aspect of neighborhood social influence is social connection and felt or expressed social support. Norms and


informal social control refer to the ways neighborhoods might regulate resident behavior, social connection and support express the extent of neighborliness experienced in a neighborhood. Deficits in social connection are an important element of social disorganization theories of crime and violence (Bursik and Grasmick 1993; Sampson and Groves 1989; Warner and Rountree 1997). Social connection and felt social support from neighbors are emphasized in framing of neighborhood effects as an expression of social capital (Coleman 1988), which may be defined broadly as resident contributions to and involvement in community, the extent and density of social connections, and support sought and received (Elliott et al. 1996; Rountree and Warner 1999). In the developmental literature, social support and connection are viewed as particularly important in highly stressed neighborhoods (McCord 1994). It has been argued that parents who are connected to others facing similar environmental and developmental challenges can better navigate typical daily hassles and better sustain functioning in the face of extraordinary challenges (Tolan and GormanSmith 1997). Empirical demonstrations have shown that social support and connection are each protective for adolescents in highly disadvantaged neighborhoods (Beyers et al. 2003; Wright et al. 2006). Similarly, interventions that focused on increasing support and connection among families residing in the same neighborhood have reduced child aggression and prevented later youth violence (Metropolitan Area Child Study Research Group 2002; The Multisite Violence Prevention Project 2009; Tolan et al. 2005). Social connection and support are not necessarily unambiguously positive in their effects. Some investigators have found a protective effect of low connection to others. For example, Brodsky (1996) found a protective effect of social isolation for African American youth in Washington DC neighborhoods. Similarly, Caughy et al. (2003) found a protective effect of low social connection on child mental health problems for families living in poor distressed communities. For families living in less distressed communities, the opposite relation was found. Higher risk for mental health problems were reported for families reporting low social connection who were living in less disadvantaged neighborhoods. Other research raises the question of the importance of the quality of social connections in minority urban neighborhoods. Warner and Rountree (1997) measured social ties within neighborhoods as the average proportion of persons within each neighborhood engaging in activities such as having meals, borrowing food or materials, or generally helping out. They found social ties related to decreased crime only in predominately white neighborhoods, with nonsignificant effects on crime in predominately minority

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neighborhoods. They hypothesized these differences might be related to the limited breadth of social networks within minority communities, limited ties to external institutions such as the police or, again, the norms held within the neighborhood. These same investigators found gender differences in the effects of social ties on crime, with strong social ties among women and not men related to decreased crime in their sample (Rountree and Warner 1999). In this study we gathered a predominantly minority sample stratified by community poverty levels. The results will contribute additional evidence related to the questions raised by these investigators. Focus on Urban Neighborhoods We focus here on neighborhood social processes within poor urban communities, specifically those in Chicago. These are communities with relatively high rates of social problems, including youth violence, academic failure, teen pregnancy and infant mortality (Butts and Travis 2002). Increased understanding of the role of neighborhood structural and social processes in such communities for understanding risk is critical to guiding prevention and intervention efforts. This article reports on the results of a project to develop and validate an inventory of measures of neighborhood social organization, including scales measuring norms, informal social control, and social connection. Additionally, the inventory contains measures that assess likely correlates of social processes such as neighborhood change, neighborhood problems and neighborhood resources. We address key questions raised in previous research, such as the question of how many dimensions are needed to characterize neighborhood measures, the internal consistency at the individual level, and the shared variance at the neighborhood level of analysis (Raudenbush and Sampson 1999). Finally, and consistent with previous studies of the effects of sense of community (e.g., Wilson-Doenges 2000) and collective efficacy (Sampson et al. 1997), we test the criterion-related validity of the scales by predicting neighborhood crime contemporaneous with collection of the neighborhood social process scales.

Method Participants Neighborhood Selection Neighborhoods were selected via stratified random sampling from pools of eligible census tracts within Chicago. Eligibility was based on the following criteria: (1)

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residential population predominantly ([50 %) Latino/Hispanic or African American; (2) more than 1,000 individuals living in the tract; (3) percent of households below poverty level must be between 20 and 45 %; and (4) tract crime rate of \150 aggravated assaults per 10,000 residents per year.1 Based on 2009 estimates of census and actual crime data, 155 (63 Latino, 92 African American) census tracts out of 866 in Chicago met these criteria. All eligible census tracts were divided into five strata based on poverty level (i.e., 20–25, 25–30, 30–35, 35–40, and 40–45 %), and within each poverty level stratum, six tracts were selected randomly (three Latino and three African American). Tracts were replaced by random selection if they (a) bordered other tracts already in the sample, or (b) contained significant geographic barriers within their boundaries (e.g., one selected tract was bisected by an expressway).

Sample Selection and Recruitment To form the sample of neighborhood informants 20 participants within each of the 30 census tracts were recruited. The sample was stratified to ensure an equal number of male and female participants within each tract, as well as an even number of younger (age 18–24) and older (age 30?) adults. A random sample of USPS addresses in each of 30 census tracts was purchased from a third party vendor. Identification and recruitment of study participants followed several steps. A list of 20 random addresses was released in each census tract. Letters introducing the study were sent to each household prior to attempting in-person contact. When possible, recruiters called the household, and then visited each address individually. If someone was home, the recruitment team described the study and the survey. If the resident was receptive, the recruiters determined whether or not someone in the household fell into the assigned age group for invitation to participate in the study. Once identified, recruiters verified that the resident met eligibility requirements. As strata were filled, we limited inclusion to those in unfilled cells of crossed characteristics (age, gender). If eligible and interested, the recruiters obtained informed consent and when possible, the interview was conducted at the same time. If the resident was unwilling or unable to complete the interview immediately, the recruiters scheduled an interview time. Each home/housing unit was visited a minimum of three times at varying times of day (e.g., evening, weekend, morning). However, 1

In 2009, only one primarily Latino tract in Chicago had more than 150 aggravated assaults per 10,000 residents. In order to ensure congruence in crime rates between primarily Latino and primarily African American tracts, we decreased the maximum aggravated assault rate.

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if a house was clearly vacant, this was documented and additional visits were not required. Once all addresses from the initial list were exhausted (either through participation, refusal, inability to contact, or vacancy), a new list of 20 random addresses from the target neighborhood were released. This procedure was used in order to minimize the reliance on only the most conveniently available residents. Of those households that were determined to have a resident eligible for participation, 86.2 % completed the survey (606/703). Interview Procedures The interview included a pool of items representing neighborhood norms and informal social control, neighborhood support and social connection (cohesion and social resources), neighborhood change, and neighborhood resources and problems, and maps on which residents could indicate safe and unsafe areas in their neighborhoods. Interviewers administered the questions and recorded participant responses. Each interview took approximately 40 min to complete. Each participant was paid $25 for the interview. Measures All of the neighborhood social process scales with the number of items in each pool, and examples of content are reported in Table 1. Neighborhood Norms The item pool for neighborhood norms consisted of 44 items. Each item contained the stem, ‘‘People in this neighborhood believe that…’’ followed by the specific item content. Responses were on a five-point Likert-type scale on which one represented ‘‘Strongly Disagree’’ and five represented ‘‘Strongly Agree.’’ Additional codes were offered for ‘‘I don’t know’’ and ‘‘Refused.’’ Informal Social Control The total pool consisted of 62 items. For each item, the respondent was asked, ‘‘What would people in your neighborhood do if…’’ followed by the specific content of each item. Participants responded freely to each item and interviewers coded an answer ‘‘1’’ if the respondent indicated that, nothing would be done, ‘‘2’’ if the response suggested complaining to or discussing with other neighbors, ‘‘3’’ if the response suggested talking to someone who could do something about the problem (e.g., police, landlord, parents), and ‘‘4’’ for responses that suggested taking direct action, such as stepping in and talking directly to the

Am J Community Psychol (2014) 54:187–204 Table 1 Neighborhood matters item pools and content examples

Scale

193

Subscale

Neighborhood norms

# Items in pool

Example of item content

People in this neighborhood believe that… Child welfare

8

…adults should know who the neighborhood children and teenagers are

Child management

12

…adults should do something if a child is doing something dangerous, even if it is not their child

Adolescent behavior

11

…it is always wrong for teenagers to get into fist fights

Crime

7

…people should so something if a neighbor’s house is being vandalized

Neighborhood management

7

…people should keep their neighborhood looking nice

Informal social control

What would people in your neighborhood do if… Child welfare

8

… a child is left at home alone during the day?

Child management

12

… a child is throwing rocks at a someone’s pet?

Adolescent behavior

19

… teenagers are drinking alcohol?

Crime

10

… dog fighting is happening in the neighborhood?

Neighborhood management

5

… someone who lives in the neighborhood rarely or never shovels snow?

Neighborhood organization

7

… the public school closest to your home was going to be shut down or turned over?

Social cohesion

32

People in this neighborhood watch over each others’ property (homes) while they are away

Social resources

5

Does this neighborhood have a community policing program?

Neighborhood change

6

People in this neighborhood are more likely to try to fix problems in the neighborhood than they were a few years ago

Neighborhood resources

14

There are places to go shopping in this neighborhood

Neighborhood problems

13

Abandoned or boarded up homes are a problem in this neighborhood

Social connection

persons involved. As with Norms, codes were included for ‘‘I don’t know’’ and ‘‘Refused.’’ Social Support and Connection The extent of social connection in neighborhoods was assessed using a pool of 45 items, 32 of which tapped social cohesion. Consistent with theory emphasizing the importance of the setting-level means and structures that exist to organize resources (Seidman 2012; Tseng and Seidman 2007), the remaining items assessed the existence and use of neighborhood structures that might serve

to organize and promote social connection, such as community policing programs, block clubs, community meetings, community newspaper, organized youth activities, and block parties. Responses to the 32 cohesion items were coded on a five-point Likert-type scale ranging from ‘‘strongly disagree’’ to ‘‘strongly agree.’’ Responses to the social resources items were ‘‘yes’’ or ‘‘no’’ for the existence of each potential resource, followed by a three-point scale indicating whether none, some, or most community residents made use of the resource, contingent on a positive answer about the existence of the resource.

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Additional Neighborhood Measures Neighborhood Change Perceptions of change in the neighborhood over time were assessed by five items, with responses recorded on a fivepoint Likert-type scale as for Norms and Social Cohesion. Neighborhood Resources and Neighborhood Problems These scales were essentially checklists to which respondents indicated whether the item was or was not present in the neighborhood. Options were available for residents who said they did not know, or refused to answer.

Fig. 1 Bifactor model with three specific factors representing different content domains and one method factor

Archival Crime Records We collected archival records of crime for each census tract and the time period during data collection from the City of Chicago data portal. The data were collected from completed case reports of incidents to which the police responded. The data do not reflect all police responses, as not all responses generated a case report. The incidents were classified using crime classification codes derived from the Federal Bureau of Investigation’s (FBI) National Incident-Based Reporting System (NIBRS) Uniform Crime Reporting (UCR) Program (Arciaga et al. 2009). Data are updated daily, and up to 12 years of incident-level information is available. Filters allow for data to be retrieved at the census tract, beat, or community levels, or for a radius surrounding a specific address. For this study, we retrieved data for the 30 selected census tracts and within the data collection time frame. Data Analysis Approach Dimensionality The first question we addressed with each item pool that had multiple theoretical subscales was dimensionality, that is, the extent to which the responses to the items reflected our theorized subscale structure. With norms and informal social control we evaluated dimensionality using bifactor analysis. Bifactor models are a sub-class of confirmatory factor models that have proven to be useful in resolving questions of dimensionality because they are able to estimate the contribution of content and method sources of variation (Reise et al. 2007). Figure 1 illustrates a bifactor model with a single general factor and three specific factors. In a bifactor model each item is allowed to load on two factors. One is a general factor on which all items load. The other is one of some number of specific factors that are

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generally constrained to be orthogonal, but may be correlated. The interpretation of the general and specific factors varies by the measurement issue being addressed. For example, when applied to data where a single rater provides ratings on multiple subscales, the general factor can be interpreted as a method factor and the specific factors as content factors. However, in situations where multiple measurement methods are used to assess a single underlying construct (e.g., Campbell and Fiske 1959), the general factor can be interpreted as the content factor and the specific factors will model variation attributable to the different methods used. The bifactor models for norms and informal social control in this study had multiple specific factors representing the subscales under each construct and a single general factor representing the common variance shared by all items. Our bifactor models employed the complex sample feature in Mplus to account for clustering of observations within neighborhoods. For item pools that were intended to measure a single underlying dimension, we used multi-level exploratory factor analysis (EFA) through MPlus (Mutheń and Mutheń 2007) that specified a single factor at the census tract level, leaving the correlation structure at the individual level unspecified. Figure 2 illustrates such a model. Multilevel EFA in Mplus permitted us to compare the fit of single-factor and multifactorial solutions without having to propose specific multidimensional structures, as would have been the case with a bifactor model or a multilevel CFA. The bifactor and multilevel EFA analyses also permitted us to evaluate the intraclass correlation of each item at the tract level as well as the extent to which the item loaded significantly on its intended factor. Both pieces of information were important in selecting items for retention in the final scales.


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where s00 = the variance component for census tracts within strata, r2 is the residual variance, and njk is the number of individuals in an average tract. We used the Wald Z test provided by SAS PROC MIXED for the neighborhood variance component as a test of the significance of the neighborhood-level shared variance. Validity

Fig. 2 Multilevel exploratory factor analysis illustration with the factor model on the neighborhood level and unspecified correlation structure at the individual level

Reliability Once items were selected for retention, the second question addressed in analysis was the reliability of the scales at the individual and tract levels. At the individual level we calculated Cronbach’s alpha for each scale, except for the scales that were checklists where there was no expectation of internal consistency. Tract-level reliability is the proportion of the total variance in the scale that is shared within neighborhoods. Assessment of tract-level reliability in this study was more complex than assessment of individual-level internal consistency. Because of the stratified sampling of both census tracts and individuals within tracts, we employed a generalizability theory method (G-theory; Cronbach 1963) to identify the proportion of variance attributable to the neighborhoods. We obtained the variance components using mixed models through SAS PROC MIXED (SAS Institute Inc. 2004). In a manner similar to the ‘‘ecometric’’ models of Raudenbush and Sampson (1999), we predicted an individual’s response on each item from dummy codes representing the number of items less one, the gender and age stratum from which the individual was sampled, and the interaction between gender and age, with random intercepts for neighborhood poverty and ethnicity strata and for census tract nested within neighborhood strata. We then used the variance components to assess the average shared variance in a typical tract according to Raudenbush and Bryk’s (2002, pp. 50–51, 79) formula for Level 2 reliability, which is identical to Shrout and Fleiss’ (1979) second formula for the intraclass correlation, ICC2: s00 k0jk ¼ 2 ; s00 þ nrjk

Evidence for construct validity of the scales comes from the confirmatory factor analyses of scale structure, and from correlations among the scales and subscales. Evidence for criterion-related validity was gathered by regressing police reports of neighborhood violent crime, property crime, and drug crime (aggregated to the census tract level and collected from daily reports during the same time frame as the neighborhood data collection), controlling for the population and poverty stratum of the census tract.

Results A table of means, standard deviations and correlations for all variables used in this study may be found in the online appendices, along with a document containing the final items and scales and a third table. In what follows, for each scale and subscale we report assessment of dimensionality and item selection, reliability, and validity. Table 2 reports reliability and validity statistics for all scales and subscales. Norms Dimensionality and Item Selection The item pool for the norms measure comprised 45 items assessing perceived neighborhood norms in the areas of child welfare, child management, youth behavior, crime, and citizen responsibility. We conducted bifactor confirmatory factor analysis in Mplus (Mutheń and Mutheń 2007) that adjusted for clustering of items within neighborhoods. Each item was allowed to load on one of the five specific factors as well as on a general factor. Twelve items related to adolescent behavior either did not load significantly on their intended content factors or did not have substantial agreement within census tracts (i.e., interclass correlation \.02). Removing these items improved the fit of the solution. The final model, specifying the five theoretical subscales and treating the response scale as ordinal, resulted in good fit to the data, v2(423, N = 572) = 852.9, p \ .01, CFI = .94, RMSEA = .04, RMR = .04.

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Table 2 Individual and neighborhood reliability and validity, N = 30 neighborhoods Scale

Subscale

Final number of items

Individual internal consistency

Shared proportion of variance in an average neighborhood

Association with Police crime reports, controlling for population and neighborhood poverty

Estimate

p

Violent crime

Property crime

Drug crime

-.06

Norms Child welfare

6

.78

.08

.1448

-.01

-.12

10

.73

.33

.0005

.21

.16

Adolescent behavior

4

.90

.04

.2565

-.27?

-.29*

-.26

Crime

6

.81

.18

.0089

.03

.09

-.04

Citizen responsibility

5

.82

.35

.0061

.01

.10

-.05

Child welfare

8

.81

.28

.0017

-.34*

-.31*

Child management

.18

Informal social control Child management

11

.88

.22

.0087

-.39**

-.26

?

-.18 -.30?

Adolescent behavior

4

.83

.27

.0148

-.47**

-.26

-.41*

Crime

6

.87

.26

.0067

-.58**

-.43**

-.52**

Citizen responsibility

5

.81

.13

.0917

-.09

Neighborhood organization

7

.74

.14

.0456

-.31?

-.17

.06

-.18 -.36*

General factor

47

.95

.18

.0016

-.47**

-.31*

-.41*

Social cohesion

32

.92

.20

.0026

-.32*

-.23

-.32*

?

Neighborhood social connection Social resources

5 5

N/A .77

.50 .49

.0044 .005

.29 -.54**

.15 -.43**

.25 -.39**

Neighborhood resources

9

N/A

.34

.0007

.22

.13

.18

Neighborhood problems

7

N/A

.59

.0002

.22

.13

.19

Perceived neighborhood change

Validity coefficients are standardized weights from regressions of police reports of neighborhood crime on each neighborhood (sub)scale controlling for neighborhood population and poverty level ?

p \ .10, * p \ .05, ** p \ .01

Reliability As can be seen in Table 2, the individual-level internal consistencies of the norms subscales were all above .7. At the neighborhood level, generalizability theory analysis incorporating the study design revealed that only three of the five neighborhood norms subscales had significant shared variance at the neighborhood level: Norms for Child Management, Norms for Crime, and Norms for Neighborhood Management. The neighborhood-level shared variance of norms for child welfare and norms for adolescent behavior did not differ significantly from zero and were of small magnitude (.08 and .04 respectively). Validity Appendix 3 in the supplemental material reports the means, standard deviations, and correlations among the norms

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subscales. Overall the average tract had scores on the norms scales that approached the ‘‘Agree’’ point on the scale. At the tract level, most correlations were moderate in magnitude, the exception being the correlation between norms for neighborhood management and norms about crime (r = .82, p \ .01). Four correlations were not significant at the tract level of analysis. They were the correlation between norms for child welfare and norms about crime, the correlation between norms for child welfare and norms for neighborhood management, the correlation between norms for child management and norms about crime, and the correlation between norms for child management and norms for neighborhood management. At the individual level of analysis, all correlations were significant and moderate in magnitude (r \ .6). As can be seen in Table 2, models predicting neighborhood crime levels from each neighborhood norms subscale, controlling for population and poverty stratum


found norms about adolescent behavior correlated significantly with police reports of neighborhood property crime (r = -.29, p \ .05) and marginally with police reports of neighborhood violent crime (r = -.27, p \ .10). Informal Social Control Dimensionality and Item Selection The item pool for the measure of informal social control comprised 62 items assessing perceived informal social control in the areas of child welfare, child management, youth behavior, crime, neighborhood management, citizen responsibility, and neighborhood organization. Bifactor confirmatory factor analysis adjusted for clustering of items within tracts and treated the response scale as an ordinal scale with the lowest level of informal social control being ‘‘do nothing’’ and the highest level being ‘‘take direct action.’’ Each item was allowed to load on one of the seven specific factors as well as on a general factor. Fifteen items either did not load significantly on their intended specific factors or did not have substantial agreement within census tracts. Removing these items improved the fit of the solution. The final model was a reasonable fit to the data, v2(972, N = 572) = 1,898.58, p \ .01, CFI = .89, RMSEA = .04, RMR = .04. Although the CFI was below a desirable level of .9, the RMSEA and RMR were both below .05. For Informal Social Control we retained the general factor as well as the specific factors. We did that because several items on the Adolescent Behavior and Crime subscales of the Informal Social Control scale loaded strongly on the general factor but weakly on their specific factors. Items with the same content had loaded significantly on the Adolescent Behavior and Crime content factors of the Neighborhood Norms Scale, thus, in the interest of consistent content between norms and enforcement of norms we retained these items in the Informal Social Control scales. Reliability The individual-level internal consistencies of the informal social control subscales were above .8 with one exception, namely Informal Social Control regarding Neighborhood Organization, whose individual-level internal consistency was still acceptable at .74 (Table 2). G-theory analyses revealed that the shared variance at the neighborhood level was significant for all subscales except for Citizen Responsibility, as well as for the General Informal Social Control Factor. Validity Appendix 3 in the supplemental material reports the descriptive statistics and correlations among the Informal

197

Social Control subscales. Scores on Informal Social Control tended to be between ‘‘Talk about the problem’’ and ‘‘Talk to someone who can do something about the problem’’ anchors. At the neighborhood level, all correlations were significant with four exceptions: The correlation between Child Welfare and Neighborhood Management (r = .37, ns), between Child Management and Neighborhood Management (r = .42, ns), between Child Welfare and Neighborhood Organization (r = .45, ns), and the correlation between Neighborhood Organization and Neighborhood Management (r = .33, ns). At the individual level of analysis, all correlations were significant. Results of regressions of neighborhood crime on the Informal Social Control general scale and subscales are reported in Table 2. Only the subscales for Citizen Responsibility and Neighborhood Organization did not significantly predict neighborhood violent crime levels. As can be seen in Table 2, all of the significant regression coefficients were in the expected direction, indicating that higher levels of neighborhood informal social control were associated with lower levels of neighborhood violent crime. On property crime, significant associations were found for the Child Welfare and Crime subscales and for the General Informal Social Control scale. These all were in a negative direction, as with the effects on neighborhood violent crime. On drug crime, significant associations were observed for the General Informal Social Control Scale, and for the Adolescent Behavior, Crime, and Neighborhood Organization subscales. As with violent crime and property crime, these coefficients were in a negative direction. Social Connection Dimensionality and Item Selection The 44 items of the neighborhood social connection scale consisted of two different types of items; 32 Likert-type scale items assessed Neighborhood Social Cohesion and six sets of two items each assessed Neighborhood Social Resources. Two questions were asked regarding each social resource (e.g., block club): (a) Did the resource exist in the neighborhood, and (b) to what extent were neighbors involved in the resource. If the resource did not exist, involvement was coded zero, making the involvement items suitable for further analysis. Multilevel EFA of the 32 items assessing social cohesion, with the factor structure specified at the tract level, returned a single-factor solution that fit the data very well, v2(464, N = 508) = 222.76, ns, CFI = 1.0, RMSEA = .00, RMR = .00. However, this analysis found very few item loadings to be significantly different than zero, indicating that any factor structure was probably at the individual level. A confirmatory factor analysis with the factor structure specified at the

123

198

individual level but accounting for clustering at the tract level fit better than a model with the factor structure at the tract level (DBIC = 5,303.41). Moreover, when the factor structure was specified at the individual level, all items had significant loadings on a single factor. For the six involvement in social resources items, multilevel EFA found that one item (community meetings) did not load and did not have significant reliability at the tract level, but all other items loaded significantly on a single factor. The fit of the multilevel EFA with a single factor at the tract level and an unconstrained variance–covariance matrix at the individual level was nearly perfect, v2(9, N = 403) = 8.72, ns, CFI = 1.0, RMSEA = .00, RMR = .00. Reliability The individual-level internal consistencies of the Social Cohesion Scale was .92, as can be seen in Table 2. Surprisingly, given the results of the dimensionality analyses, G-theory analysis revealed that the shared variance at the neighborhood level was significant (ICC2 = .20). We did not compute individual internal consistency of the Social Resources subscale, reasoning that internal consistency would not be expected from a checklist of items about which there is no expectation of a consistent response. G-theory analysis showed that reliability at the tract level was high (ICC2 = .50), as can be seen in Table 2.


point Likert-type response scale with 1 = strongly disagree and 5 = strongly agree was used. Multi-level EFA found that a model with a single factor at the tract level of analysis was a perfect fit to the data, v2(5, N = 545) = 2.85, ns, CFI = 1.0, RMSEA = .00, RMR = .09. Two items with low intraclass correlations and loadings were removed, and one item was reversed so that positive scores would indicate neighborhood change in a positive direction. Reliability The internal consistency of the Neighborhood Change scale was .77, and the G-Theory analysis found an ICC2 of .47 (p = .005), indicating high neighborhood-level reliability. Validity The Neighborhood Change scale had strong associations with all official measures of crime. Because the scale was scored so that higher scores indicate more positive neighborhood change, the negative regression coefficients with violent crime (b = -.54, p \ .001), property crime (b = -.43, p \ .01), and drug crime (b = -.39, p \ .05) all indicated that higher crime levels were associated with perceptions of negative neighborhood changes.

Validity Neighborhood Resources The correlation between Social Cohesion and Social Resources was effectively zero (r = -.03, ns). As can be seen in Table 2, regression found that Neighborhood Social Cohesion was significantly associated with neighborhood levels of violent crime and drug-related crime. These coefficients were negative (b = -.32, p \ .05 for both), indicating that neighborhoods with higher levels of social cohesion had lower levels of crime. Neighborhood Social Resources did not correlate significantly with any measure of crime, but there was a marginal and positive correlation with violent crime (b = .29, p = .07), suggesting that higher crime neighborhoods tended to have more social resources. The coefficient between Neighborhood Social Cohesion and Neighborhood Social Resources was significant and positive at the individual level (b = .27, p \ .001) but non-significant at the tract level of analysis (r = -.03, p = .87). Perceived Neighborhood Change Dimensionality and Item Selection The Neighborhood Change item pool consisted of six items believed to represent a single underlying construct. A five-

123

Dimensionality and Item Selection The 15-item pool for Neighborhood Resources was subjected to multilevel EFA with the factor structure specified at the tract level. We were guided in item selection by the item intraclass correlations from this analysis, which located six items with ICC1 values below .05. These items were dropped from the final scale. The resulting model fit the data nearly perfectly, v2(65, N = 446) = 58.32, ns, CFI = 1.0, RMSEA = .00, RMR = .00.

Reliability Although there are neighborhoods with generally higher or lower levels of resources, there is no reason to expect that having one resource makes it more probable that a neighborhood will have another. Thus we did not calculate individual level internal consistency on the neighborhood resources scale, but relied on the estimate of shared variance in the neighborhood to index reliability. The G-Theory analysis showed the ICC2 to be .34 (p \ .01).


Validity The associations between the Neighborhood Resources scale and police reports of crime were all nonsignificant. Neighborhood Problems Dimensionality and Item Selection Like the Neighborhood Resources scale the Neighborhood Problems scale is a checklist. As with the Neighborhood Resources scale we conducted a multilevel EFA but relied on the item intraclass correlations to guide selection of the final item set. A solution with a single factor at the tract level and unspecified factor structure at the individual level fit the data nearly perfectly, v2(65, N = 526) = 69.14, ns, CFI = 1.00, RMSEA = .00, RMR = .00. This analysis found six items with low agreement at the tract level. These were removed to produce the final scale. Reliability As with Neighborhood Resources, we relied on agreement among persons in the neighborhood to index reliability, rather than agreement among items within individuals. The ICC2 for Neighborhood Problems was .59 (p \ .001). Validity Controlling for neighborhood population and poverty levels, none of the associations between the Neighborhood Problems scale and police reports of crime were significant, although all were positive in direction.

Discussion Based on a developmental-ecological theory of human growth and development, this study aimed to test a battery of measures of neighborhood-level social processes, including neighborhood cohesion, social resources, norms, and informal social control with a sample of randomlyselected informants from 30 neighborhoods selected in such a manner that balanced levels of poverty and ethnicity. The evidence gathered supports the internal consistency of virtually all of the Neighborhood Matters scales at the individual level, and the reliability of most of the scales as indicators of neighborhood level phenomena. Our results compare quite favorably to other assessments of level-2 reliability where social processes are concerned. For example, Cooke and Rousseau (1988), in a study of organizational culture, found that between 6 and 13 % of the variance in their scales was shared at the organizational

199

level. Moreover, many of the scales that demonstrated significant neighborhood-level reliability also had significant associations with neighborhood crime. Analyses testing the dimensional structure of the measures generally supported their theorized structure. In the cases of neighborhood norms and neighborhood informal social control, however, we expected items referencing adolescent misbehavior to load with items about child management. Surprisingly, our neighborhood informants did not respond similarly to these two groups of items. This led us to construct new scales for norms and informal social control related to adolescent behavior. In constructing and testing the scales in this study we followed criteria similar to those suggested by Katz and Kahn (1978) in their discussion of norms in organizations. First, there must be individual attitudes or beliefs about the process at the neighborhood level, and second, there must be statistical commonality of such beliefs among neighborhood residents. This second requirement can only be met if there is similarity of such attitudes or beliefs within neighborhoods and diversity of average attitudes or beliefs among neighborhoods. This second criterion will be impossible to achieve if there is not enough variation in individual scores to permit clustering by neighborhood, as might be the case with highly socially desirable beliefs or attitudes. This second criterion appears not to have been met in the case of the Norms about Child Welfare subscale in this study. At the individual level, this subscale had a relatively high mean and small standard deviation, which might suggest that there was insufficient individual-level variability to permit there to be much clustering by neighborhood. This was not the case for the other scale that did not have significant neighborhood-level variation, namely Norms about Adolescent Behavior. This subscale had a relatively large standard deviation at the individual level. It appears that the absence of neighborhood clustering of Norms about Adolescent Behavior may have been due to absence of agreement within neighborhoods. Social Processes at Individual and Neighborhood Levels Community psychology research has clearly demonstrated that both individual sense of community (Davidson and Cotter 1991) and shared sense of community (Battistich and Hom 1997) are associated with individual outcomes. This provokes the question of the meaning of neighborhood-level effects, particularly when individual reports are aggregated to produce neighborhood-level measures, a widely-used practice in organizational and community research (Chan 1998). Relevant to this question is work on norms at the setting level of analysis,

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200

which at the individual level operate as normative beliefs about appropriate behavior (Huesmann and Guerra 1997), but at the setting level operate through processes involving gain or loss of status or approval among peers (Henry et al. 2004; Henry and Chan 2010). Future research will be required to explore neighborhood-level processes that may be involved in the influence of other variables assessed in this study. Research on Youth Violence As was noted in the introduction, our purpose in developing the Neighborhood Matters scales was to permit investigation of neighborhood effects on youth violence. Each of the subscales was chosen because of a demonstrated or hypothesized relation to youth violence or a predictor of youth violence (e.g., parental monitoring) in the literature. In order to facilitate research on the effects of neighborhood social processes on youth violence, the parent study included collection of a developmental sample of 20 youth from two age groups in each neighborhood, resulting in samples of 300 early school-age and 300 high school youth from 30 neighborhoods balanced on poverty and ethnicity. Youth in these samples and their parents were administered measures of psychopathology, school functioning, positive development, family relationships, social competence, and parenting practices, as well as the neighborhood matters scales. The existence of this sample will permit investigation of the complex interrelationships between neighborhood social processes, family variables, and individual characteristics. Beyond the parent study of the current sample, the supplemental material to this article make the scales easily available to community researchers who wish to administer them. It will be important to address the question of the minimum number of neighborhood respondents needed to produce valid estimates of neighborhood social processes, i.e., as the number of respondents per neighborhood is reduced, at what point does the neighborhood-level reliability of each scale deteriorate? However, this study suggests that, with 20 respondents per neighborhood, valid assessment of social processes related to youth violence may be obtained. The neighborhood matters scales will also be useful to assess contextual mediation and moderation of intervention effects. The question of assessing the appropriateness of potential intervention contexts has received little research attention, despite studies that have found such contextual differences in intervention effects (e.g., Metropolitan Area Child Study Research Group 2002). The Neighborhood Matters scales make it possible to conduct prospective assessment of neighborhood social processes during intervention planning to permit assessment of the potential moderating role of neighborhood characteristics. Contextual factors have been found to moderate both the

123


implementation and the outcomes of preventive interventions (Dymnicki 2014; Gregory et al. 2007). Research on Developmental Ecological Theory Developmental ecological theory suggests that characteristics of the environments within which the child is nested, and the interactions among those environments, have effects on child development. An often unspoken yet prevalent opinion is that since environments are mediated by individual sense perceptions, little is gained by attempting to measure characteristics of environments as environments over what can be know by collecting individual perceptions. Some studies have challenged this notion, having produced findings that characteristics of school environments predict behavior over and above what can be predicted by perceptions of the same environmental characteristics (Henry et al. 2011b), and that individual perceptions incorrectly estimate group attitudes toward violence (Henry et al. 2013) and peer drug and alcohol use (Henry et al. 2011b). The cost and difficulty of assessing environmental characteristics may prolong the substitution of perceptions for environmental measures, but research based on developmental ecological theory cannot occur without measures such as those developed in this study. Questions these measures make possible to address include questions about the stability of and relations among different neighborhood social processes. For example, the magnitude and direction of effects of neighborhood norms on crime suggest direct effects consistent with the effects of norms on youth behavior (Henry et al. 2000a, 2004, 2011a). However, as Cialdini et al. (1991) and Barker (1968) have suggested, making norms salient or enforcing them is an important component of normative influence. This study assessed norms and informal social control separately, allowing future research into the relation between normative beliefs and informal social control. The Neighborhood Matters scales also make it possible to investigate the relation between the social processes of communities and psychological sense of community. As was noted earlier, psychological sense of community is an individual-level construct whereas the social processes assessed in this study were conceptualized and developed as neighborhood-level constructs. This is one of few studies to test models in which the factor structure of a measure was specified at the neighborhood level as well as to assess the neighborhood-level reliability of an individual-level scale. In most instances, measures with significant shared variance at the neighborhood level also had strong factor structures at the neighborhood level. An exception was social cohesion, whose factor structure was strong at the individual level, but not at the neighborhood level. This result is consistent with the theory behind psychological sense of community, that


is, that it is an individual-level construct that might be shared within a neighborhood. The results of other scales that had strong factor structures at the neighborhood level (such as neighborhood social resources) are more consistent with the concept of collective efficacy, which is a neighborhood-level construct in which individuals participate. This present study lays the groundwork for studies of the effects of neighborhood social processes on behavior of individual parents and children. Limitations The Neighborhood Matters inventory was designed to assess some of the social processes that may be operating in urban neighborhoods, with particular attention to those processes likely to affect the functioning of families and the growth and development of children. It was tested in a sample of 30 urban neighborhoods, selected specifically to be comprised primarily of residents of minority ethnicity and varying proportions of residents living below the poverty level. Thus, we make no claim of validity for this inventory for measurement outside of an urban context, in neighborhoods of majority ethnicity, neighborhoods of extreme wealth or of extreme poverty. Future measurement studies will be required to assess the eco-metric characteristics of the Neighborhood Matters scales in other contexts. In this cross-sectional study it was not possible to determine the extent to which the neighborhood social processes contributed to neighborhood crime, or vice versa. It is equally possible that higher crime neighborhoods tend to organize block clubs and neighborhood watches as it is that such neighborhood organizations will contribute to changes in crime levels. Differences in the directions of effects, however, might be expected. Neighborhoods with higher crime that produce neighborhood organization could result in positively signed regression coefficients, whereas the opposite effect could result in negatively signed coefficients. Most of the signs of the effects on neighborhood crime were negative, which is the direction that would be expected if informal social control, in particular, were having an effect on neighborhood crime. However, it is equally possible that neighborhoods with high crime weaken neighborhood social processes, as residents eschew opportunities for neighborhood integration and organization out of fear. Future longitudinal research will be needed to understand the directionality of the relations between social processes at the neighborhood level and neighborhood crime.

Conclusion Neighborhood social processes are true latent variables. As with other extra-individual constructs such as climate or

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culture (Moos 1973), they are usually not made manifest and cannot be directly assessed, requiring their characteristics to be inferred from individual indicators or from observations. Accordingly they are difficult and expensive to measure, often requiring multiple settings and multiple individuals within each setting. These requirements, no doubt, have been partially responsible for the relative paucity of such measures and the continuing embryonic state of the field of setting-level measurement (Henry, in press). Yet there is evidence that setting-level measures add value above and beyond individual perceptions for understanding individual behavior, and that such measures affect family functioning (Gorman-Smith et al. 2000; Tolan et al. 2003). We offer the Neighborhood Matters inventory in the belief that continued efforts at setting-level measurement are worthwhile pursuits for the fields of community psychology and child development alike. Acknowledgments This research was supported by Grant number UO1CE00167 from the Centers for Disease Control and Prevention to the second author. The authors gratefully acknowledge the contributions of Franklin Gay, MPH and Molly Coeling, MPH, who recruited participants and conducted the interviews.

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Neighborhood health centers: an assessment.

Neighborhood linguistic diversity predicts infants' social learning.

[Successful aging in social environment and neighborhood].

Rural Neighborhood Walkability: Implications for Assessment.

Neighborhood social capital and achieved mobility of older adults.

Adolescent neighborhood quality predicts adult dACC response to social exclusion.

Why the Neighborhood Social Environment Is Critical in Obesity Prevention.

Individual, Social, and Neighborhood Associations With Sitting Time Among Veterans.

Assessment of neighborhood context in a nationally representative study.

Twenty Years of Neighborhood Effect Research: An Assessment.

Living environment matters: relationships between neighborhood characteristics and health of the residents in a Dutch municipality.

Neighborhood: A Conceptual Analysis.

[Neighborhood Systematic Social Observation; The Case of Chile and its Perspectives for Social Work.]

Neighborhood Income Matters: Disparities in Community Recreation Facilities, Amenities, and Programs.

Associations of Neighborhood Safety and Neighborhood Support with Overweight and Obesity in US Children and Adolescents.

Putting Activism in Its Place: The Neighborhood Context of Participation in Neighborhood-Focused Activism.

Travel beyond the home neighborhood for delinquent behaviors: moderation of home neighborhood influences.

Subpopulation differences in the association between neighborhood urban form and neighborhood-based physical activity.

Neighborhood socioeconomic deprivation, perceived neighborhood factors, and cortisol responses to induced stress among healthy adults.

Socioeconomic status, neighborhood characteristics, and walking within the neighborhood among older Hong Kong Chinese.

Does neighborhood collective efficacy for families change over time? The Boston Neighborhood Survey.

Neighborhood food environment and obesity in community-dwelling older adults: individual and neighborhood effects.

Birds of a Feather: Social Bases of Neighborhood Formation in Newark, New Jersey, 1880.

Effect of neighborhood stigma on economic transactions.