Depressive Symptomatology, Exposure to Violence, and ... - CiteSeerX

American Journal of Orthopsychiatry 2005, Vol. 75, No. 2, 262–274

Copyright 2005 by the Educational Publishing Foundation 0002-9432/05/$12.00 DOI: 10.1037/0002-9432.75.2.262

Depressive Symptomatology, Exposure to Violence, and the Role of Social Capital Among African American Adolescents Kevin M. Fitzpatrick, PhD

Bettina F. Piko, MD, PhD

University of Alabama at Birmingham

Szeged University

Darlene R. Wright, PhD

Mark LaGory, PhD

Samford University

University of Alabama at Birmingham

Focusing on the role of capital as both personal and social resources for adolescents, the authors examined depressive symptomatology among a sample of 10- to 18-year-old African American youths (N ⫽ 1,538). In addition to gender and age differences, adolescents exposed to threatening environments (school, neighborhood, home) reported more depressive symptoms. Social capital had a significant inverse relationship with adolescent depression; self-esteem and a social capital index were negatively related to depressive symptomatology. Furthermore, the interaction effects of gender with social capital, age with self-esteem, and age with grades were significant, indicating the presence of a buffering effect. These findings suggest the importance of interrelationships among violence exposure, capital, and well-being for adolescents.

Over the last several decades, we have witnessed a growing concentration of poverty and minority status in America’s inner cities—the ghettoization of poverty (Fitzpatrick & LaGory, 2000; Jargowsky, 1997; Wilson, 1987). This increasing isolation of the poor reflects a broader trend in society, described in Robert Putnam’s (2000) Bowling Alone. Putnam argued that this disconnectedness in American life has implications not only for communities but also for the physical and mental health of America’s residents. He believed that social connections are a critical form of personal and community capital affecting wellbeing. The absence of such connections may have dramatic significance for those already suffering Kevin M. Fitzpatrick, PhD, and Mark LaGory, PhD, Department of Sociology, University of Alabama at Birmingham; Bettina F. Piko, MD, PhD, Department of Psychiatry, Division of Medicine, Szeged University, Szeged, Hungary; Darlene R. Wright, PhD, Department of Sociology, Samford University. Darlene R. Wright is now at the Department of Sociology, Birmingham Southern University. We thank Chris Snead for her assistance at various stages of this project. In addition, we thank the Bessemer city school system and Mary Fitzpatrick, Safe and DrugFree Schools Coordinator, for making available the data used in this study. For reprints and correspondence: Kevin M. Fitzpatrick, PhD, Department of Sociology, University of Alabama, Birmingham, AL 35294-3350. E-mail: [email protected]

262

from the negative consequences of poverty and inner city spatial isolation. Youth, because of their limited mobility, may be particularly affected by the growing social and spatial isolation of the inner city. Research suggests that low-income and minority youth are at great risk for a wide range of problematic outcomes affecting their personal well-being (Aneshensel & Sucoff, 1996; Brooks-Gunn, Duncan, Klebanov, & Sealand, 1993; Compas, Connor, & Hinden, 1998; Ensminger & Juon, 1998; Fitzpatrick, 1993; Fitzpatrick & LaGory, 2000; Jessor, 1992; Kandel, 1998; Loeber, Farrington, Stouthamer-Loeber, & Van Kammen, 1998; M. D. Resnick et al., 1997). Putnam noted that wellbeing outcomes ranging from unhappiness and depression to suicide among youth may be a function of diminishing social capital (Putnam, 2000; Saguaro Seminar, 2000), a trend with special relevance for those living in the inner city because of its social isolation (Mitchell & LaGory, 2002). Among the most researched topics in the general literature on well-being is the subject of depression. Our understanding of adolescent depression, more so than other forms of adolescent psychopathology, has witnessed substantial revisions in the last decade (see Cicchetti & Toth, 1998, for a comprehensive review of depression research pertaining to youth). The literature has evolved from the belief that youth do not experience depression during adolescence to the realization that not only do they experience it, there is

DEPRESSION AND CAPITAL

a marked increase in depression between childhood and adolescence, with depression often co-occurring with other disorders (Compas et al., 1998; Glied & Pine, 2002). In fact, adolescent prevalence rates for depression closely approximate those of adults, indicating that, in many cases, adult depression may have its onset in adolescence. Although estimates vary, studies tend to report rates of depression in children between 1% and 3% and rates of 1% to 8% among adolescents (Anderson & McGee, 1994; Birmaher et al., 1996; Roberts, Lewinsohn, & Seeley, 1995; Satcher, 1999). Studies of depression for both youths and adults have documented a significant association between environmental hazards and risks (e.g., violence, poverty, social isolation) and depressive symptomatology (Birmaher et al., 1996; Deykin, Levy, & Wells, 1987; Fitzpatrick & LaGory, 2000; W. E. Hawkins, Hawkins, & Seeley, 1992; Kandel & Davies, 1986; Satcher, 1999). Although many of these studies have found a complicated set of causal relationships, as expected, participants who report greater exposure to environmental hazards report more mental health symptoms, are less socially competent, and have increased difficulty with social adaptation as they get older (Aneshensel & Sucoff, 1996). Independent of these negative circumstances, some youth are more resilient than others. This resiliency is fostered throughout development by a set of protective mechanisms, one of which is the individual’s social connections (Formoso, Gonzales, & Aiken, 2000). For youth, these connections, sometimes referred to as social capital, are embedded in several domains—family, school, peer group, and community. Since Durkheim’s (1897/1966) early work on suicide, the impact of social connections on mental well-being has been well documented (e.g., Lin, Dean, & Ensel, 1986; Putnam, 2000; Srole, Langer, Michael, Opler, & Thomas, 1962; Thoits, 1995). More specific to this research effort, studies have shown that children and adolescents benefited from these connections, whether through relationships with family, friends, or teachers (Dekovic, 1999; Fitzpatrick, 1997; Fitzpatrick & Boldizar, 1993; J. D. Hawkins, 1995; M. D. Resnick et al., 1997; Smith, Lizotte, Thornberry, & Krohn, 1995). However, no study, to our knowledge, has focused its exploration on the basic relationships among hazardous circumstances, social capital, and mental health among poor, minority youth. The intention of this article is to explore depressive symptomatology in a sample of African American

263

inner city youth, paying special attention to the following questions: (a) Does social capital really matter? Specifically, are bonding social ties important for well-being, and do they act as risk mediators or buffers in predicting depressive symptomatology among this sample of African American adolescents? (b) Do other personal forms of capital, so-called human capital (e.g., academic achievement, self-esteem), play a role in predicting depressive symptoms among adolescents? What hazardous circumstances and risks (e.g., exposure to violence) correlate with depression, and how are they related to social capital?

Unhealthy Places Inner city areas have been characterized as “islands of risk and despair” (Fitzpatrick & LaGory, 2000, p. 121); this is descriptive of disorganized communities in which social detachment, crime, physical hazards, and stress abound (Ross, 2000; Ross & Mirowsky, 2001; Ross, Mirowsky, & Pribesh, 2001; Wilson, 1996). Andrulis (1997) described the consequences of inner city residence as an “urban health penalty” (p. 2) in which persons living in high-minority, high-poverty neighborhoods share more in common with those in a third world country than they do with other residents of their own metropolitan area. This penalty—the intersection of poverty, unemployment, deteriorating housing, violence, poor nutrition, and a general erosion of service delivery— has created a deepening urban health crisis (Fitzpatrick & LaGory, 2000). One aspect of this crisis is the urban resident’s exposure to violence. Central city residents are twice as likely to be victims of violence and three times more likely to be murdered than those living in other parts of the metropolitan statistical area (Fingerhut & Kleinman, 1990; Reiss & Roth, 1993; U.S. Department of Health and Human Services, 1999). Because of youths’ immobility, immaturity, and dependence on others, they are truly more place bound and at the mercy of these hazardous circumstances. Because these youths are place bound, the risks attached to the local landscape, along with the youths’ ties to local actors and institutions, become crucial factors in shaping their overall well-being. Violence exposure has been linked to a wide range of mental health problems for youth, including anxiety, depression, suicide ideation, and posttraumatic stress disorder (e.g., Fitzpatrick, 1993; Fitzpatrick & Boldizar, 1993; Mazza & Reynolds, 1999; Rosenthal, 2000; Singer, Anglin, Song, & Lunghofer, 1995).

264

FITZPATRICK, PIKO, WRIGHT, AND LAGORY

Most of this work has found that increased violence exposure has a positive, additive effect on increased mental health symptom reporting. Whether the individual is a witness, a victim, or even a perpetrator, exposure continues to be a major predictor of mental health problems among youth, particularly those characterized as low income, minority, and urban. Even as some indicators of general violence have recently declined (Bureau of Justice Statistics, 2003), juvenile crime and violent victimization continue to be significant social problems (Fields & McNamara, 2003). In addition, studies on chronic exposure to violence indicate a rise in the reporting of violence in homes, schools, and communities by youth (Fitzpatrick & LaGory, 2000; Osofsky, 2001; Osofsky & Fenichel, 1999; U.S. Department of Justice, 2001). In the hazardous urban environment, few places represent a refuge. Unfortunately, the same domains that youth look to for protection often end up being places of risk and danger. Given the current literature regarding exposure to violence, we expect to find that, regardless of type, youth reporting more exposure to violence, either as a perpetrator or as a victim, are more likely to report more depressive symptoms than their counterparts (Knox, Funk, Elliot, & Bush, 2000; Vermeiren et al., 2003).

Personal Capital in Resource-Poor Environments Clearly, place matters for exposure to stressors such as violence. Nevertheless, not everyone residing in a hazardous place exhibits similar symptoms of distress. Families, friends, schools, churches, and service-based organizations all play an important role in lowering levels of stress, even in the face of high poverty, crime, and general community disorganization. This relationship is just as important for youth as it is for adults. Despite the significance of hazardous residential contexts for unfavorable outcomes among residents, some youth are more resistant or resilient to detrimental effects, whereas others are not. Why do children exposed to similar community, school, and family risk variables differentially experience and respond to those environments? Some children and adolescents living in high-risk communities are exposed to considerable environmental stressors yet manage to adapt and succeed. Even in resource-poor urban environments, youths may have assets on which they may draw for coping with stressful circumstances. These resources include a catalog of personal and social support mechanisms

that help to mediate or buffer the effects of stress on well-being (Brooks-Gunn, Duncan, & Aber, 1997; Dumont & Provost, 1999; Fitzpatrick, 1997; Garmezy, 1993; Werner, 1990). In the last decade, the public health literature has explored the issue of resiliency and assets within a risk and protective factors framework. The framework conceptualizes health behavior among youth as a function of both socially determined chances and individual choices, focusing on factors that either promote or discourage health-compromising behaviors; factors exist in multiple domains and operate both at the individual and at the contextual level (Fitzpatrick & LaGory, 2000; J. D. Hawkins, Catalano, & Miller, 1992; Rolf, Masten, Cichetti, Nuechterlein, & Weintraub, 1987). This approach provides considerable insight into what (risk) factors contribute to negative behavioral outcomes for youth and, perhaps more important, what (protective) factors help to mediate or buffer these negative circumstances to minimize the impact on children and adolescents. Although the concepts of risk and protection are theoretically useful, they have not been translated into specific social and psychological variables. In the mental health literature, two sets of resources have emerged as important in reducing negative effects on well-being—psychological and social resources (Ensel & Lin, 1991). Research on children’s mental health indicates that self-esteem is a significant psychological resource that is consistently recognized as lessening symptoms of anxiety and depression among adolescents (Bettschart, Nunez, Bolognini, & Plancherel, 1994; Dumont & Provost, 1999; Rosenbaum-Asarnow, Carlson, & Guthrie, 1987). Similarly, social support, social networks, and participation in various voluntary associations have been identified as critical social resources used by youth in coping with stressful events and circumstances. These two forms of resources (psychological and social) can be conceptualized as aspects of an individual’s personal capital—that is, resources regularly used by individuals to enhance well-being. Viewing assets from the perspective of capital provides fresh new insights into the analysis of mental health and the coping resources available to individuals. It further addresses some of the above-mentioned shortcomings of the risk and protective factors model developed in the public health literature. Although this perspective has a long history in sociology (Bourdieu, 1984; Burt, 1997; Coleman, 1990; Portes, 1998), in the last several years, Robert Putnam


(2000) has become its major proponent. Putnam’s (2000) work suggests that humans draw on various forms of capital in social settings to produce wellbeing, a perspective that has much value for the exploration of mental health in the urban community. He discussed three types of capital that may benefit well-being: (a) physical capital, that is, the income and wealth that improves the individual’s level of living; (b) human capital, the personal characteristics and experiences of an individual that enhance his or her productive behavior and overall well-being; and (c) social capital, the social ties and networks that help people get by or get ahead. From the capital perspective, psychological and social resources take on a broader meaning. Psychological resources can be viewed as an aspect of human capital (Becker, 1993; Putnam, 2000), the training, skills, talents, and personal orientation on which an individual draws in task-oriented situations. For youth, academic achievement and performance can be seen as a key aspect of human capital. Although grades have been cited as a risk factor in previous studies (e.g., J. D. Hawkins et al., 2000; G. Resnick & Burt, 1996), the present study argues, from a human capital perspective, that high academic achievement is a form of capital that promotes adaptive and productive capacity both now and in the future, thus reducing depressive symptomatology. In addition, self-esteem is a dimension of personality that orients the individual to the setting and affects his or her perception of performance. Youths who have a positive self-image are more likely to perform well in school and other social settings, and these successful social experiences are likely to promote mental well-being. Social resources are another form of capital—social capital. Social capital was described by Putnam (2000) as a critical resource for the promotion of individual and community well-being. Social networks and voluntary association memberships bond similar people together and bridge differences between heterogeneous people in the community. Of all the consequences of social capital, perhaps the most established is the case of health and well-being (Lin, Cook, & Burt, 2001; Putnam, 2000). We anticipate that the bonding social ties that youth depend on within their family, school, and community will have a significant inverse relationship with depressive symptomatology. By taking this perspective, we suggest that social connectedness is likely to yield benefits to the individual.

265

Method Data The sample consists of 1,538 African American middle and high school students from a single school district in central Alabama. The sample area for this study is a classic example of Jargowsky’s (1997) and Wilson’s (1987) descriptions of a high-poverty ghetto. The majority of the residents living in the school district are African American (60%); over one third (35%) are from families headed by a woman with children under the age of 18 years, and over one third are living below the poverty level (U.S. Bureau of the Census, 1993). Of the sampled students, approximately 49% were boys, and the median age of the sample was 14 years (ninth grade). The 2001–2002 average daily attendance for the middle and high schools in the system was 2,028 students. Students’ participation in the study was voluntary and yielded a response rate of approximately 76%. After institutional review board approval by the school, consent forms explaining the purpose of the health assessment were sent home by the school district office. If students chose not to participate, they were required to return the letter signed by a parent or guardian. In addition to those students who returned letters indicating that they were not to participate (less than 10%), the remaining students who did not participate likely consisted of youth who were absent, suspended, or no longer attending school in the system. Thus, it is possible that, if rates of participation had been higher, some of the problems reported in this article would actually have been higher as well. The data were collected during the spring of 2002. The survey instrument contained questions on sociodemographics, family structure, hazardous circumstances (exposure to violence), capital (human and social), students’ attitudes toward school, students’ assessments of their relationships with teachers and parents, and depressive symptomatology. The questionnaires were self-administered under close supervision by classroom teachers. Each teacher received training and a set of instructions outlining the procedure for survey administration, confidentiality, and the proper response to questions from students. The teachers read all instructions aloud and were available to students for questions. Students filled out the questionnaires during the class period and returned them in a sealed envelope. Students’ responses were completely confidential; the students were instructed not to put their name on the instruments, and no identifying marks or numbers were used

Measurement Depression. Depression was measured with a shortened version of the original 20-item Center for Epidemiological Studies for Depression (CES-D) Scale designed to index affective depressive symptoms (Radloff, 1977). The version used in the present study has eight items with individual responses to each item ranging from 0 (less than 1 day) to 3 (5 to 7 days; M ⫽ 5.1, SD ⫽ 5.2). The eight questions focus

266


mostly on the depressive affect domain of the CES-D. In addition to asking students whether they felt sad, lonely, or fearful, other questions asked students whether they had difficulty sleeping, trouble getting along with others, and so forth. The formal properties of the original CES-D have been amply demonstrated with very high coefficients of internal consistency when the scale is administered to adolescents (Allgood-Merten, Lewinsohn, & Hops, 1990; Avison & McAlpine, 1992; Garrison, Addy, Jackson, McKeown, & Waller, 1991; Prescott et al., 1998; M. D. Resnick et al., 1991; Roberts et al., 1995; Schoenbach, Kaplan, Wagner, Grimson, & Miller, 1983). Among our sample of students, the brief CES-D was reliable, with a Cronbach’s alpha of .85. We weighted the brief CES-D, for comparison purposes, by a factor of 2.5 (the number of original CES-D items divided by the number of brief version items; i.e., 20/8 ⫽ 2.5). This weighting provides a basis for comparison with other samples in which the full CES-D was used to assess adolescent depression. The new, weighted CES-D had a mean of 13.96 and a standard deviation of 12.65. Several caveats are necessary concerning the use of the brief CES-D. First, because the measure only assesses the frequency of symptoms, not the severity, we consider our sample of students to be on some continuum of depressive symptom reporting rather than in specific categories that correspond to degrees of clinical depression. Second, our measure is a self-reported assessment of feelings that students reported over a 2-week period. Thus, we are not in a position to report clinical diagnoses. In addition, we acknowledge the weakness of self-reported assessments generally in determining mental health status, particularly among adolescents. Finally, although the full CES-D was the most desirable to use in the current study, we were somewhat constrained by the length of the questionnaire and the single class period of approximately 45 min. Other studies facing time constraints have adopted brief versions of the CES-D and have had considerable success, yielding valid and reliable responses. It should be noted, though, that, in the majority of cases, those responses were from adult populations (e.g., Kohout, Berkman, Evans, & Cornoni-Huntley, 1993; Melchior & Huba, 1993; Mirowsky & Ross, 2001; Ross & Mirowsky, 1984). Sociodemographics. We control for two variables in the analysis. Both have been noted in previous depression research as important structural determinants of symptom reporting among adolescents. We included gender (1 ⫽ female) and age (years) in the multivariate analysis when we expected to see both girls and older youth reporting more depressive symptoms (Cicchetti & Toth, 1998; Fitzpatrick, 1993; Nolen-Hoeksema & Girgus, 1994). Hazardous circumstance (exposure to violence). Exposure to violence, either as a victim, as a witness, or as a perpetrator, has been linked to increased mental health symptom reporting among youth (Fitzpatrick, 1993, 1997; Fitzpatrick & Boldizar, 1993; Jenkins & Bell, 1994). For adolescents, exposure to violence is likely to take place in a variety of settings (family, school, and community), and,

although the effects are mixed, the literature has generally found that adolescents with greater violence exposure report more mental health symptomatology. This symptomatology ranges from anxiety to depression and posttraumatic stress disorder (Fitzpatrick, 1993; Fitzpatrick & Boldizar, 1993; Mazza & Reynolds, 1999; Nelson-Hinton, Roberts, & Snyder, 1996). For the current study, we examine two forms of violence exposure. The first one is a scale composed of three ordinal variables assessing direct involvement with violence as a perpetrator. The variables include whether and how often the student carries a weapon, whether and how often he or she has been in a fight in the last 30 days, and whether and how often he or she bullied other students in the last 30 days. The scale has a range of 0 (none) to 2 (more than 5; M ⫽ 1.6, SD ⫽ 1.5). The index was moderately reliable, with a Cronbach’s alpha of .62. A second violence exposure variable tapped aspects of adolescents’ victimization and their feelings about safety and threats in school, home, and their community. The scale is composed of five ordinal variables that ask students whether they have been victims of parental physical abuse or sexual victimization, whether they have been threatened or bullied by someone in the last 30 days at school, and whether they feel that their school and community environments are unsafe. The index has a range of 0 (never) to 2 (most of the time; M ⫽ 2.7, SD ⫽ 2.4). The index was reliable, with a Cronbach’s alpha of .68. In both cases, we expect that increased reporting of exposure to violence will be related to increased levels of depressive symptom reporting. Human capital. Human capital involves the personal resources (capacity, knowledge, and demeanor) that persons bring to bear in task-oriented situations. In exploring the link between human capital and depression, we examine self-esteem. We measured self-esteem using Rosenberg’s (1965, 1979) 10-item Self-Esteem Scale. These 10 items ask students questions pertaining to how they perceive themselves. Answers range from 1 ⫽ strongly agree to 4 ⫽ strongly disagree. Higher scores indicate greater self-esteem among the students (M ⫽ 32.1, SD ⫽ 5.1). The self-esteem variable in this sample of students was reliable, with a Cronbach’s alpha of .76. A second human capital variable used in the analysis was the subjective reporting by students of the grades “they mostly get in school,” ranging from 1 ⫽ mostly Ds and Fs to 7 ⫽ mostly As. Academic performance has been noted as an indicator of a personal resource—important in the development of resiliency and coping strategies, particularly in the face of hazardous environments. Social capital. In addition to inner resources and capacities that constitute human capital, capital is also a product of social relationships that occur at the family, school, and community levels (Coleman, 1990; Lin et al., 2001; Portes, 1998; Putnam, 2000). These supportive relationships act as critical assets fostering competence, promoting successful development, and building resiliency in youth. Forms of social capital, in part, are expected to mediate or buffer negative effects of hazardous environments and, despite

DEPRESSION AND CAPITAL exposure to debilitating circumstances, help individuals to adapt and succeed (Mitchell & LaGory, 2002). These multilevel factors should mediate or buffer exposure to violence and, through either individual or structural means, promote positive development among children and adolescents. In the current study, we examine forms of social capital in the family, school, and church community. We created a multidimensional index of social capital that combines six ordinal level variables. One is how often the family shares an evening meal together, with categories ranging from 0 ⫽ never to 4 ⫽ all of the time. This variable continues to be recognized as a critical indicator of connectedness within the family unit, and, even where parental presence is limited, many youth view a time set aside to share a meal as extremely important. A second variable is how often during the week an adult is present when the student comes home from school, with categories ranging again from 0 ⫽ never to 4 ⫽ all of the time. Another family domain variable is how often the adolescent talks to his or her parents about personal problems, with categories ranging from 0 ⫽ never to 4 ⫽ all of the time. Another set of variables used to create the social capital index are at the school level. Youth spend a great deal of time in their school, and that community institution can be a crucial link to the general success they experience during this critical phase of development. In particular, students who are able to identify someone in the school who cares for them or pays attention to them may be less at risk to experience negative health outcomes. We used a variable that asked the student, “Is there someone at school who cares about you and what happens to you?” Besides selfreporting of attitudes about school and teachers, students were asked how often they talked to their teachers about their personal problems. A final variable that we used to create the social capital index is how often students attend church or religious functions. Again, the ordinal variable has four categories, ranging from 0 ⫽ never attend to 4 ⫽ attend all the time (every week). The analyses focus primarily on the cross-sectional relationships among sociodemographics, exposure to violence, capital (human and social), and depressive symptomatology. Although we know that cross-sectional data limit our ability to formally test causal hypotheses, they nevertheless provide an important assessment of the interrelationships among these factors and their association with depressive symptoms among African American middle and senior high school students. Such data also limit our ability to analyze more complex interrelationships among the variables in the model, such as the interplay between human and social capital (i.e., academic performance and self-esteem, on the one hand, and social relationships, on the other). Additionally, we note that several independent variables used in the regression analyses are not interval-level variables but rather combinations of ordinal-level variables. Thus, we exercise some caution in the interpretation of the findings in light of this limitation. Finally, the data for the analysis are based on youths’ subjective accounts. Although we cannot assess the importance of this subjective reporting, there is

267

growing evidence that self-report measures of adolescent behaviors are reliable and valid (Brener, Collins, Kann, Warren, & Williams, 1995).

Results Table 1 presents the descriptive statistics and Pearson correlations for sociodemographic, exposure to violence, and capital (human and social) variables. The mean CES-D for this group of African American adolescents was 13.49. This average is higher than is typically reported in general adolescent population studies (e.g., Birmaher et al., 1996; Lewinsohn, Hops, Roberts, Seeley, & Andrews, 1993) as well as some studies of depression among African American youth (Doerfler, Felner, Rowlison, Raley, & Evans, 1988; Roberts, Roberts, & Chen, 1997; Siegel, Aneshensel, Taub, Cantwell, & Driscoll, 1998). Given the already stressful circumstances to which these youth find themselves exposed, it is not surprising that their symptom levels were elevated. The correlations provide important preliminary information regarding the interrelationships among violence exposure, capital, and well-being in youth. Both exposure variables were significantly ( p ⬍ .01) related to CES-D scores, which suggests that greater exposure to violence and violent circumstances is associated with increased depressive symptom reporting. Clearly, self-esteem had a strong correlation with depressive symptomatology; the social capital index also had a significant negative association with CES-D symptoms. All these relationships were significant at the .01 level. Likewise, the hazardous circumstances and exposure to violence variables consistently had inverse, in some cases significant, relationships with the capital variables. Youth who reported more exposure to violence had lower grades and self-esteem, and youth with lower capital also reported more exposure to violence, either as a perpetrator or as a victim. Table 2 presents a series of regressions examining the effects of sociodemographic, exposure to violence, and capital (human and social) variables on depressive symptom reporting among this sample of African American adolescents. Blocks of variables were entered in succession; the intention is to examine not only the independent effects of each of the variables but also the significance of groups of variables and the role they play in predicting depressive symptomatology. In addition, we are interested in whether capital (both human and social) plays a mediating or buffering role, thus, by either mecha-

Variable

CES-D Gender Age Sexual victimization Parental assault Threatened Fights Self-esteem Grades Dinner with parents Intact family Sports team School cares Gang member Friends in gangs

1

— .172** .236** .128** .243** .260** .117** ⫺.354** ⫺.127** ⫺.126** ⫺.076** ⫺.005 ⫺.085** .012 .032 12.68 13.06

— .021 ⫺.081** ⫺.014 ⫺.060** ⫺.171** .050* .155** ⫺.064* ⫺.032 ⫺.149** .142** ⫺.236** ⫺.208** 0.52 0.50

2

— .082** .011 ⫺.104** ⫺.061** .161** ⫺.198** ⫺.230** ⫺.052* ⫺.092** ⫺.007 .108** .171** 13.98 2.34

3

— .218** .173** .142** ⫺.135** ⫺.087** ⫺.053 ⫺.029 .061* ⫺.013 .171** .181** 0.47 0.98

4

— .227** .125** ⫺.195** ⫺.048* ⫺.110** ⫺.034 .024 .019 .100** .127** 0.42 0.82

5

— .295** ⫺.196** ⫺.059** ⫺.037 ⫺.038 .036 ⫺.074** .125** .114** 0.96 1.32

6

Note. N ⫽ 1,538. CES-D ⫽ Center for Epidemiological Studies Depression Scale. * p ⬍ .05, one-tailed. ** p ⬍ .01, one tailed.

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. M SD

8

9

10

11

12

13

14

15

— ⫺.074** — ⫺.138** .165** — ⫺.013 .047* .043* — ⫺.021 .047* .079** .056* — .081** ⫺.028 ⫺.050* .089** .026 — ⫺.055* .151** .126** .051* .002 .020 — .225** .060* ⫺.160** ⫺.023 ⫺.043* .083** ⫺.050* — .207** ⫺.056* ⫺.138** ⫺.074** ⫺.074** .065* ⫺.044* .396** — 1.55 16.47 4.17 2.51 1.58 0.71 0.86 0.11 0.38 1.45 3.29 1.61 1.26 1.02 1.04 0.35 0.31 0.49

7

Table 1 Descriptive Statistics and Correlations for Sociodemographics, Exposure to Violence, Social Capital, and Depressive Symptomatology

268 FITZPATRICK, PIKO, WRIGHT, AND LAGORY


269

Table 2 Ordinary Least Squares (Unstandardized/Standardized Coefficients) Regression Models Predicting Depressive Symptomatology Among African American Adolescents Model 1 Variable Sociodemographics Gender (female ⫽ 1) Age Exposure to violence Violence perpetrator Violence victim Capital (human and social) Self-esteem Grades Social capital index Interactions Gender ⫻ Social Capital Index Age ⫻ Self-Esteem Age ⫻ Grades Constant R2

Model 2

Model 3

Model 4

B

␤

B

␤

2.25** 0.38*

.091 .066

4.63** 0.31

.125 .054

3.33** 0.41*

.134 .070

8.19** 1.55**

.330 .270

0.00 1.79**

.001 .336

0.01 1.45**

.006 .272

0.01 1.44**

.011 .271

⫺0.71** 0.21 ⫺0.18*

⫺.284 .030 ⫺.070

0.28 ⫺3.35** 0.01

.111 ⫺.245 .005

7.38 .02

3.11 .12a

␤

B

7.39 .20a

B

␤

⫺0.38** ⫺.225 ⫺0.01** ⫺.585 0.26** .490 8.37 a .23

Note. N ⫽ 1,538. a 2 R change is based on a hierarchical F test of significance ( p ⬍ .001). * p ⬍ .05, one-tailed. ** p ⬍ .01, one-tailed.

nism, reducing the negative effects of exposure to violence on the reporting of depressive symptoms. The sociodemographic variables were entered first. As expected, gender was significant ( p ⬍ .01); girls reported more symptoms than boys. Age was also significant, in that older adolescents reported more symptoms. The second block of variables involved exposure to violence. When we controlled for gender and age, the block of exposure variables was significant, increasing the explained variation in depressive symptomatology by more than 10%. The victim exposure variable was significant at the .01 level. Both variables operated in the expected positive direction, with increased frequency of exposure increasing depressive symptomatology. Nevertheless, the perpetrator variable (weapon carrying, fighting, and bullying) did not have a significant impact on depressive symptomatology. Human and social capital variables were added in a third block. Both exposure variables remain unchanged. Self-esteem had a significant and large inverse relationship with depressive symptom reporting; youth with higher self-esteem reported fewer depression symptoms. The relationship between the social capital index and depression was in the expected inverse direction and significant ( p ⬍ .05); students who scored higher on the social capital index reported lower levels of depressive symptoms. Twenty percent of the variation in adolescent self-

reported depressive symptoms was accounted for by the sociodemographic, exposure to violence, and social capital variables. Each successive block of variables was significant and increased the explained variation in the overall model. In addition, an inspection of the regression coefficients and their change or lack of change in subsequent equations suggested no evidence to support a mediation hypothesis. Because human and social capital variables remained significant, it was important to test a buffering hypothesis. Thus, the final part of the analysis involves an examination of interaction effects between the major structural variables (gender and age) and the human and social capital variables. A fourth and final block of variables included three interaction terms. We tested for the significance of all possible interaction terms, using an F test criterion (⌬R2), and included the Gender ⫻ Social Capital, Age ⫻ SelfEsteem, and Age ⫻ Grades interactions in this fourth block. Entering the block of interaction effects slightly increased the explained variation in depressive symptom reporting. When these interaction terms were included, the additive effects of the capital variables became less significant. These results suggest that capital could play the role of a buffering agent for particular segments of youth. For example, whereas girls generally report higher depressive symptoms, those with high levels of social capital report fewer symptoms. Similarly, although age tends

270


to be directly related to depression, older adolescents experiencing high levels of capital report fewer symptoms. Finally, whereas grades are inversely related to depression, age interacts with grades such that younger persons with lower grades are particularly affected, reporting a greater number of depressive symptoms.

Discussion The major focus of this article has been to examine the applicability of a capital perspective for understanding the well-being of African American middle and high school students in an inner city community. Using a sample of 1,538 mostly low-income, African American students, the model does a reasonable job in predicting depressive symptomatology. The results underscore important aspects of the hazards faced by inner city youth and the resources available to them. Although the resources examined in this article are primarily relational, they nevertheless highlight the importance of social connectedness for adolescent well-being. As expected, there are significant sociodemographic differences in symptom self-reporting among adolescents. The higher levels of depression for adolescent girls may be due, in part, to their greater emotional maturity. They are not only more aware of their emotions but also more likely to discuss their feelings with others. The link between gender and depression, coupled with the finding that older adolescents tend to report more symptoms, has important implications for the design of interventions. Keeping youth insulated from the negative effects of hazardous circumstances is a daunting task for both parents and teachers in the inner city (Weist, Freedman, Paskewitz, Proescher, & Flaherty, 1995). The inner city is clearly an unhealthy place for the young, yielding a distinct health penalty. Nevertheless, these results suggest important forms of capital (human and social) that can be leveled at these risks. From an individual perspective, self-esteem is unquestionably a critical asset that adolescents can draw on in attempting to navigate these risky circumstances (Dumont & Provost, 1999). It is surprising that grades did not exhibit an independent effect, although they did interact with age to influence depressive symptom reporting. Our research suggests that human capital matters and is a critical resource that youth can effectively use in managing the hazards of inner city life. In addition, social capital makes a critical contribution to the quality of life for poor, minority youth.

Sharing a meal with one’s family, talking with one’s parents about one’s personal problems, and having one’s parents around generally are significant forms of social capital (Formoso et al., 2000); the more supportive the parental environment was, the fewer depressive symptoms participants experienced. What is important about this finding is that it provides parents with a very direct and manageable strategy for improving their child’s well-being—they must make themselves available. Although this can be challenging, particularly in a low-income environment in which both parents are working, only one parent is present, or one parent is working multiple jobs, it highlights an important aspect of parenting and its role in predicting negative outcomes among adolescents. This availability may be particularly difficult to achieve for the working poor, who may have to put in long hours to support the family economically (Ackerman, D’Eramo, Umylny, Schultz, & Izard, 2001). The school variables that are part of this index are also important; just as other studies have shown (e.g., M. D. Resnick et al., 1997), these aspects (levels) of a youth’s environment are significant for determining adaptation and developmental outcomes. School and other institutions play a vital role in helping youth develop resiliency while protecting them from negative environments. To this end, feeling connected to school and community is an important aspect of successful maturation (Jessor, 1993). In addition to providing structure and control, schools and communities protect resident youth by helping them feel connected, building their self-esteem, and giving them a role to play in their own development. Thus, maintaining relationships with people at school and having someone there the youth can rely on or who cares about them can be crucial to youth at this age as they navigate an often hazardous, risk-filled environment. It is notable that the blocked regression indicates the absence of a mediating role for both human and social capital. Capital, in both forms, matters for the quality of life of inner city youth. Its contribution, however, is not as a mediator of risky circumstances. This suggests that although capital can inoculate youth from hazardous environments, the inoculation reduces symptoms without eliminating all of the negative health consequences of the presenting condition. Our research indicates support for a buffering hypothesis similar to that found by Wheaton (1983, 1985), suggesting that protective factors (social support) work selectively in reducing negative behavioral outcomes. In particular, social capital does not


seem to be as effective for boys in reducing the negative consequences of inner city residence. Likewise, the consequences of limited human capital (poor grades) for younger adolescents are intensified. Given the previously mentioned limitations of the current research, further research is necessary to more fully understand the relationships between various forms of capital and mental health among inner city, minority youth. The measurement of the capital variables, both human and social, also requires further development. More comprehensive social capital measures for the three relational domains should be explored. In addition, an examination of well-being outcomes other than depressive symptomatology may provide a more comprehensive understanding of the dynamics of mental and physical health among inner city youth. Given the cross-sectional nature of the data, further research is necessary to establish the causal relationships among hazard, capital, and mental distress. In addition, it may be useful to consider the possibility of respecification of the causal relationships (i.e., reverse causal sequencing in the case of exposure to hazards and capital). The implications of our findings are significant in several ways. To date, few studies have examined the applicability of an assets-based framework to psychosocial outcomes, particularly depressive symptomatology among low-income, African American adolescents. Although we have not made a definitive test of the framework, our analysis provides important insight into the relationship among hazards, capital, and well-being for adolescents. These data show that significant mental health differences exist between boys and girls; those who are connected to family, peers, and school versus those who are disconnected; and those with higher self-esteem and grades versus those with lower levels of human capital. Finally, although we know that depression is a diagnosable and treatable disease, it is often undetected among adolescents. Because of a reluctance to report symptoms or to formally seek care, youth remain a difficult population to treat. Still, more training for parents, teachers, clinicians, and community workers in the recognition of signs and symptoms of depression will allow for the development of more effective clinical and nonclinical strategies to address the issues and treatment of symptoms of depression.

References Ackerman, B. P., D’Eramo, K. S., Umylny, L., Schultz, D., & Izard, C. E. (2001). Family structure and the external-

271

izing behavior of children from economically disadvantaged families. Journal of Family Psychology, 15, 288 – 301. Allgood-Merton, B., Lewinsohn, P. M., & Hops, H. (1990). Sex differences and adolescent depression. Journal of Abnormal Psychology, 99, 55– 63. Anderson, J. C., & McGee, R. (1994). Co-morbidity of depression in children and adolescents. In W. M. Reynolds & H. F. Johnston (Eds.), Handbook of depression in children and adolescents (pp. 581– 601). New York: Plenum Press. Andrulis, D. P. (1997). The urban health penalty: New dimensions and directions in inner-city health care (American College of Physicians Position Paper No. 1). Washington, DC: National Public Health and Hospital Institute. Aneshensel, C. S., & Sucoff, C. A. (1996). The neighborhood context of adolescent mental health. Journal of Health and Social Behavior, 37, 293–310. Avison, W. R., & McAlpine, D. (1992). Gender differences in symptoms of depression among adolescents. Journal of Health and Social Behavior, 33, 77–96. Becker, G. S. (1993). Human capital (3rd ed.). Chicago: University of Chicago Press. Bettschart, W., Nunez, R., Bolognini, M., & Plancherel, B. (1994). L’estime de soi a la pre-adolescence: Une etude longitudinale [Regard of oneself as a pre-adolescent: A longitudinal study]. Nervure, 7, 23–25. Birmaher, B., Ryan, N. D., Williamson, D. E., Brent, D. A., Kaufman, J., Dahl, R. E., et al. (1996). Childhood and adolescent depression: A review of the past 10 years, Part I. Journal of the American Academy of Child and Adolescent Psychiatry, 35, 1427–1439. Bourdieu, P. (1984). Distinction (Richard Nice, Trans.). Cambridge, MA: Harvard University Press. Brener, N. D., Collins, J. L., Kann, L., Warren, C. W., & Williams, B. I. (1995). Reliability of the Youth Risk Behavior Survey Questionnaire. American Journal of Epidemiology, 141, 575–580. Brooks-Gunn, J., Duncan, G. J., & Aber, J. L. (1997). Neighborhood poverty (Vols. 1 and 2). New York: Russell Sage Foundation. Brooks-Gunn, J., Duncan, G. J., Klebanov, P. K., & Sealand, N. (1993). Do neighborhoods influence child and adolescent development? American Journal of Sociology, 99, 353–395. Bureau of Justice Statistics. (2003). Criminal victimization, 2002. Washington, DC: U.S. Department of Justice. Burt, R. S. (1997). The contingent value of social capital. Administrative Science Quarterly, 42, 339 –365. Cicchetti, D., & Toth, S. L. (1998). The development of depression in children and adolescents. American Psychologist, 53, 221–241. Coleman, J. (1990). Foundations of sociological theory. Cambridge, MA: Harvard University Press. Compas, B. E., Connor, J. K., & Hinden, B. R. (1998). New perspectives on depression during adolescence. In R. Jessor (Ed.), New perspectives on adolescent risk behav-

272


ior (pp. 319 –362). Cambridge, England: Cambridge University Press. Dekovic, M. (1999). Risk and protective factors in the development of problem behavior during adolescence. Journal of Youth and Adolescence, 28, 667– 685. Deykin, E. Y., Levy, J. C., & Wells, V. (1987). Adolescent depression, alcohol and drug abuse. American Journal of Public Health, 77, 178 –182. Doerfler, L. A., Felner, R. A., Rowlison, R. T., Raley, P. A., & Evans, E. (1988). Depression in children and adolescents: A comparative analysis of the utility and construct validity of two assessment measures. Journal of Consulting and Clinical Psychology, 56, 769 –772. Dumont, M., & Provost, M. A. (1999). Resilience in adolescents: Protective role of social support, coping strategies, self-esteem, and social activities on experience of stress and depression. Journal of Youth and Adolescence, 28, 343–363. Durkheim, E. (1966). Suicide. New York: Free Press. (Original work published 1897) Ensel, W., & Lin, N. (1991). The life-stress paradigm and psychological distress. Journal of Health and Social Behavior, 32, 321–341. Ensminger, M. E., & Juon, H. (1998). Transition to adulthood among high-risk youth. In R. Jessor (Ed.), New perspectives on adolescent risk behavior (pp. 365–391). Cambridge, England: Cambridge University Press. Fields, S. A., & McNamara, J. R. (2003). The prevention of child and adolescent violence: A review. Aggression and Violent Behavior, 8, 61–91. Fingerhut, L. A., & Kleinman, J. C. (1990). International and interstate comparisons of homicide among young males. Journal of the American Medical Association, 263, 3292–3295. Fitzpatrick, K. M. (1993). Exposure to violence and presence of depression among low-income, African-American youth. Journal of Consulting and Clinical Psychology, 61, 528 –531. Fitzpatrick, K. M. (1997). Fighting among America’s youth: A risk and protective factors approach. Journal of Health and Social Behavior, 38, 131–148. 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 and Adolescent Psychiatry, 32, 424 – 430. Fitzpatrick, K. M., & LaGory, M. (2000). Unhealthy places: The ecology of risk in the urban landscape. New York: Routledge Formoso, D., Gonzales, N. A., & Aiken, L. S. (2000). Family conflict and children’s internalizing and externalizing behavior: Protective factors. American Journal of Community Psychology, 28, 175–199. Garmezy, N. (1993). Children in poverty: Resilience despite risk. Psychiatry, 56, 1127–1136. Garrison, C. Z., Addy, C. L., Jackson, K. L., McKeown, R. L., & Waller, J. L. (1991). The CES-D as a screen for depression and other psychiatric disorders in adolescents.

Journal of the American Academy of Child and Adolescent Psychiatry, 30, 636 – 641. Glied, S., & Pine, D. S. (2002). Consequences and correlates of adolescent depression. Archives of Pediatrics and Adolescent Medicine, 156, 1009 –1014. Hawkins, J. D. (1995). Controlling crime before it happens: A risk-focused prevention. National Institute of Justice Journal, 229, 8 –10. Hawkins, J. D., Catalano, R., & Miller, J. (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychological Bulletin, 112, 64 –105. Hawkins, J. D., Herrenkohl, T. I., Farrington, D. P., Brewer, D., Catalano, R. F., Harachi, T. W., & Cothern, L. (2000). Predictors of youth violence. Washington DC: Office of Juvenile Justice and Delinquency Prevention, Office of Justice Programs, U.S. Department of Justice. Hawkins, W. E., Hawkins, M. J., & Seeley, J. (1992). Stress, health-related behavior and quality of life on depressive symptomatology in a sample of adolescents. Psychological Reports, 71, 183–186. Jargowsky, P. A. (1997). Poverty and place: Ghettos, barrios, and the American city. New York: Russell Sage Foundation. Jenkins, E. E., & Bell, C. C. (1994). Violence among inner city high school students and posttraumatic stress disorder. In S. Friedman (Ed.), Anxiety disorders in African Americans (pp. 76 – 88). New York: Springer. Jessor, R. (1992). Risk behavior in adolescence: A psychosocial framework for understanding and action. In J. Stevenson (Ed.), Adolescents at risk: Medical and social perspectives (pp. 19 –34). Boulder, CO: Westview Press. Jessor, R. (1993). Successful adolescent development among youth in high-risk settings. American Psychologist, 48, 117–126. Kandel, D. (1998). Persistent themes and new perspectives on adolescent substance abuse: A lifespan perspective. In R. Jessor (Ed.), New perspectives on adolescent risk behavior (pp. 43– 89). Cambridge, England: Cambridge University Press. Kandel, D., & Davies, M. (1986). Adult sequelae of adolescent depressive symptoms. Archives of General Psychiatry, 43, 255–262. Knox, M., Funk, J., Elliot, R., & Bush, E. (2000). Gender differences in adolescents’ possible selves. Youth and Society, 31, 287–309. Kohout, F. J., Berkman, L. F., Evans, D. A., & CornoniHuntley, J. (1993). Two shorter forms of the CES-D depression symptoms index. Journal of Aging and Health, 5, 179 –193. Lewinsohn, P. M., Hops, H., Roberts, R. E., Seeley, J. R., & Andrews, J. A. (1993). Adolescent psychopathology: I. Prevalence and incidence of depression and other DSM– III–R disorders in high school students. Journal of Abnormal Psychology, 102, 133–144. Lin, N., Cook, K., & Burt, R. (2001). Social capital: Theory and research. New York: Aldine de Gruyter.

DEPRESSION AND CAPITAL Lin, N., Dean, A., & Ensel, W. (1986). Social support, life events, and depression. New York: Academic Press. Loeber, R., Farrington, D. P., Stouthamer-Loeber, M., & Van Kammen, W. B. (1998). Multiple risk factors for multiproblem boys: Co-occurrence of delinquency, substance abuse, attention deficit, conduct problems, physical aggression, covert behavior, depressed mood, and shy/withdrawn behavior. In R. Jessor (Ed.), New perspectives on adolescent risk behavior (pp. 90 –149). Cambridge, England: Cambridge University Press. Mazza, J. J., & Reynolds, W. M. (1999). Exposure to violence in young inner-city adolescents: Relationships with suicidal ideation, depression, and PTSD symptomatology. Journal of Abnormal Child Psychology, 27, 203–213. Melchior, L. A., & Huba, G. J. (1993). A short depression index for women. Education and Psychological Measurement, 53, 1117–1126. Mirowsky, J., & Ross, C. E. (2001). Age and the effect of economic hardship on depression. Journal of Health and Social Behavior, 42, 132–150. Mitchell, C. U., & LaGory, M. (2002). Social capital and mental distress in an impoverished community. City and Community, 1, 199 –222. Nelson-Hinton, M. D., Roberts, M. C., & Snyder, C. R. (1996). Early adolescents exposed to violence: Hope and vulnerability to victimization. American Journal of Orthopsychiatry, 66, 346 –353. Nolen-Hoeksema, S., & Girgus, J. S. (1994). The emergence of gender differences in depression during adolescence. Psychological Bulletin, 115, 424 – 443. Osofsky, J. (2001). Addressing youth victimization. Washington, DC: Office of Juvenile Justice and Prevention, U.S. Department of Justice. Osofsky, J. D., & Fenichel, E. (1999). Infants and violence: Building community strengths. Washington, DC: Zero to Three and National Center for Infants, Toddlers, and Families. Portes, A. (1998). Social capital: Its origins and applications in modern sociology. Annual Review of Sociology, 24, 1–24. Prescott, C. A., McArdle, J. J., Hishinuma, E. S., Johnson, R. C., Miyamoto, R. H., Andrade, N. N., et al. (1998). Prediction of major depression and dysthymia from CES-D scores among ethnic minority adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 37, 495–503. Putnam, R. (2000). Bowling alone: The collapse and revival of American community. New York: Simon & Schuster. Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385– 401. Reiss, A., & Roth, J. (1993). Understanding and preventing violence. Washington, DC: National Academy Press. Resnick, G., & Burt, M. R. (1996). Youth at risk: Definitions and implications for service delivery. American Journal of Orthopsychiatry, 66, 172–188.

273

Resnick, M. D., Bearman, P. S., Blum, R. W., Bauman, K. E., Harris, K. M., Jones, J., et al. (1991). Screening for adolescent depression: A comparison of depression scales. Journal of the American Academy of Child and Adolescent Psychiatry, 30, 58 – 66. Resnick, M. D., Bearman, P. S., Blum, R. W., Bauman, K. E., Harris, K. M., Jones, J., et al. (1997). Protecting adolescents from harm: Findings from the National Longitudinal Study of Adolescent Health. Journal of the American Medical Association, 278, 823– 832. Roberts, R. E., Lewinsohn, P. M., & Seeley, J. R. (1995). Symptoms of DSM–III–R major depression in adolescence: Evidence from an epidemiological survey. Journal of the American Academy of Child and Adolescent Psychiatry, 34, 1608 –1617. Roberts, R. E., Roberts, C. R., & Chen, Y. R. (1997). Ethnocultural differences in prevalence of adolescent depression. American Journal of Community Psychology, 25, 95–110. Rolf, J., Masten, A., Cichetti, D., Nuechterlein, K., & Weintraub, S. (1987). Primary prevention of psychopathology: Vol. 3. Social competence in children. Hanover, NH: University Press of New England. Rosenbaum-Asarnow, J., Carlson, G. A., & Guthrie, D. (1987). Coping strategies, self-perception, hopelessness, and perceived family environments in depressed and suicidal children. Journal of Consulting and Clinical Psychiatry, 55, 361–366. Rosenberg, M. (1965). Society and the adolescent selfimage. Princeton, NJ: Princeton University: Press. Rosenberg, M. (1979). Conceiving the self. New York: Basic Books. Rosenthal, B. S. (2000). Exposure to community violence in adolescence: Trauma symptoms. Adolescence, 138, 271– 284. Ross, C. E. (2000). Neighborhood disadvantage and adult depression. Journal of Health and Social Behavior, 41, 177–187. Ross, C. E., & Mirowsky, J. (1984). Components of depressed mood in married men and women: The Center for Epidemiologic Studies’ depression scale. American Journal of Epidemiology, 119, 997–1004. Ross, C., & Mirowsky, J. (2001). Neighborhood disadvantage, disorder and health. Journal of Health and Social Behavior, 42, 258 –276. Ross, C., Mirowsky, J., & Pribesh, S. (2001). Powerlessness and the amplification of threat: Neighborhood disadvantage, disorder, and mistrust. American Sociological Review, 66, 568 –591. Saguaro Seminar. (2000). Better together: Report by the Saguaro Seminar on civic engagement in America. Cambridge, MA: John F. Kennedy School of Government, Harvard University. Satcher, D. (1999). Mental health: A report of the surgeon general. Washington, DC: U.S. Government Printing Office. Schoenbach, V., Kaplan, B. H., Wagner, E. H., Grimson, R. C., & Miller, F. T. (1983). Prevalence of self-reported

274


depressive symptoms in young adolescents. American Journal of Public Health, 73, 1281–1287. Siegel, J. M., Aneshensel, C. S., Taub, B., Cantwell, D. P., & Driscoll, A. K. (1998). Adolescent depressed mood in a multiethnic sample. Journal of Youth and Adolescence, 27, 413– 427. Singer, M. I., Anglin, T. M., Song, Y. L., & Lunghofer, L. (1995). Adolescents’ exposure to violence and associated symptoms of psychological trauma. Journal of the American Medical Association, 273, 477– 482. Smith, C., Lizotte, A., Thornberry, T., & Krohn, M. (1995). Resilient youth: Identifying factors that prevent high-risk youth from engaging in delinquency and drug use. In J. Hagan (Ed.), Current perspectives on aging and the lifecycle (Vol. 4, pp. 217–247). Greenwich, CT: JAI Press. Srole, L., Langer, T. S., Michael, S. T., Opler, M. K., & Thomas, A. (1962). Mental health in the metropolis: The Midtown Manhattan Study. New York: McGraw-Hill. Thoits, P. (1995). Stress, coping, and social support processes: Where are we? What next? Journal of Health and Social Behavior, 36, 53–79. U.S. Bureau of the Census. (1993). 1990 Census of Population and Housing, population and housing characteristics for census tracts and blocks, Birmingham, AL MSA. Washington, DC: U.S. Government Printing Office. U.S. Department of Health and Human Services. (1999). Health, United States 1999. Washington DC: U.S. Government Printing Office. U.S. Department of Justice. (2001). Addressing youth victimization: Action plan update. Washington, DC: Office

of Juvenile Justice and Delinquency Prevention, U.S. Department of Justice. Vermeiren, R., Schwab-Stone, M., Ruchkin, V. V., King, R. A., Van Heeringen, C., & Deboutte, D. (2003). Suicidal behavior and violence in male adolescents: A school-based study. Journal of the American Academy of Child and Adolescent Psychiatry, 42, 41– 48. Weist, M. D., Freedman, A. H., Paskewitz, D. A., Proescher, E. J., & Flaherty, L. T. (1995). Urban youth under stress: Empirical identification of protective factors. Journal of Youth and Adolescence, 24, 705–721. Werner, E. E. (1990). Protective factors and individual resilience. In S. J. Meisels & J. P. Shonkoff (Eds.), Handbook of early childhood intervention (pp. 97–116). New York: Cambridge University Press. Wheaton, B. (1983). Stress, personal coping resources, and psychiatric symptoms: An investigation of interactive models. Journal of Health and Social Behavior, 24, 208 – 229. Wheaton, B. (1985). Models for the stress-buffering functions of coping resources. Journal of Health and Social Behavior, 26, 352–364. Wilson, W. J. (1987). The truly disadvantaged: The inner city, the underclass, and public policy. Chicago: University of Chicago Press. Wilson, W. J. (1996). When work disappears: The world of the new urban poor. New York: Vintage Press.

Received June 18, 2003 Accepted February 10, 2004 䡲