Child Psychiatry & Human Development

, Volume 45, Issue 6, pp 736–745

The Role of Violence Exposure and Negative Affect in Understanding Child and Adolescent Aggression


    • Department of PsychologyDuksung Women’s University
  • Eunha Kim
    • Tennessee Valley Healthcare System, Alvin C. York VAMC
  • John Young
    • University of Mississippi
Original Article

DOI: 10.1007/s10578-014-0442-x

Cite this article as:
Ebesutani, C., Kim, E. & Young, J. Child Psychiatry Hum Dev (2014) 45: 736. doi:10.1007/s10578-014-0442-x


Aggressive behaviors in youth tend to be relatively stable across the lifespan and are associated with maladaptive functioning later in life. Researchers have recently identified that both violence exposure and negative affective experiences are related to the development of aggressive behaviors. Children exposed to violence also often experience negative affect (NA) in the form of anxiety and depression. Bringing these findings together, the current study used a clinical sample of youth (N = 199; ages 7–17 years) referred to a psychiatric residential treatment facility to examine the specific contributions of NA and exposure to violence on the development of aggressive behaviors in youth. Using structural equation modeling, both NA and recent exposure to violence significantly predicted aggressive behaviors. More importantly, negative affect partially mediated the relationship between exposure to violence and aggression. Implications of these findings from a clinical perspective and future directions for research on aggression are discussed.


AggressionNegative affectViolenceMediation


According to a national survey conducted in 2008, over 60 % of children reported exposure to violence within the past year [1]. Prior studies have also reported similarly high rates of violence exposure (e.g., 71 %; [2]). Despite decades of research and efforts to reduce incidence of this experience among youth, not only have rates of violence exposure remained high, but exposure to multiple types of violence has been found to be a common experience [3]. For example, Finkelhor et al. [1] found that having exposure to one type of violence increased risk for exposure to another type of violence two- to three-fold, depending on the type of violence.

Violence Exposure and Aggression in Youth

Research has identified a wide range of negative outcomes associated with exposure to violence, including emotional difficulties and aggression (e.g., [4]). Margolin et al. [5] discovered that violence between parent and youth significantly accounted for somatic complaints, delinquency, and acquired aggression. Likewise, domestic and physical violence has been linked to symptoms of anxiety, feelings of over-arousal, and delinquency. Exposure to community violence has also been linked to feelings of over-arousal [5]. Another study by Maikovich et al. [6] using a two-stage stratified sample design found that (a) witnessing violence in the home was associated with the development of internalizing symptoms, and (b) experiencing physical discipline was associated with the development of externalizing symptoms. Oravecz and colleagues also found that exposure to violence was significantly related to internalizing and externalizing symptoms in a sample of inner-city youth [7]. More recently, Margolin and colleagues assessed multiple domains of violence exposure (i.e., parent-to-youth aggression, marital physical aggression, community violence) and found that these domains of violence exposure were uniquely associated with negative outcomes such as anxiety, depression, somatic complaints, and aggression [5].

Of the aforementioned outcomes, acquisition of aggressive behavior is one area of particular concern due to its rise among school-aged children [8]. Bullying, for example, is a form of aggressive behavior and has been found to have negative effects on the victim’s mental health and well-being [9, 10] as well as associated with safety risks [11, 12]. Childhood victimization in general, such as exposure to abuse and neglect, has also been found to be associated with both later psychopathy [13] and an increased tendency towards violence [14]. Early displays of aggressive behavior have also been found to be stable across the lifespan, predicting risk for conduct disorder, antisocial behaviors, conflict with the legal system [15], high school incompletion, unemployment, and early pregnancy [16], among other negative life outcomes. Due to the negative sequelae associated with aggressive behaviors, researchers have attempted to identify the contributing factors leading to the acquisition of aggressive behaviors.

Mediating Pathways

One of the robust findings in the literature is that exposure to violence is related to the acquisition of aggressive behaviors in youth [17]. Researchers have also found that chronic exposure to violence tends to lead to externalizing behaviors, such as aggression [18]. The specific pathways through which aggressive behaviors are acquired however remain unclear [19]. Social learning theory, modeling principles, and coercion theory provide some insight into how exposure to violence can lead to aggressive behavior in youth. According to these theories, behavior is learned within social contexts and maintained via rewarding and punishing consequences [20, 21]. More specifically, these theories would posit that exposure to violence (a) provides an opportunity for the child to learn via modeling of aggressive acts, which leads to (b) obtaining desired outcomes (e.g., escaping a negative/stressful situation) through use of these aggressive behaviors learned through modeling. Studies have found that young children, for example, do learn aggressive acts via modeling [22].

Other researchers have sought to identify intervening variables and mediators to explain the relationship between exposure to violence and aggressive behaviors in youth. For example, Bradshaw and colleagues found that social information processing—which involves perception biases of social situations, others’ intentions, situational factors—mediated the relationship between exposure to violence and aggressive behaviors in school settings [23]. One mechanism through which aggressive behaviors develop may be that some children with anxiety, for example, are biased in their interpretation of social cues, which may result in impulsive and aggressive behaviors within contexts that are viewed as potentially dangerous [24]. Guerra et al. also found that the relationship between exposure to violence and aggressive behavior among children ages 9–12 years old was mediated by social cognition (i.e., the belief that aggression is appropriate; [22]). Research also exists that suggests that difficulties in emotion regulation in the context of violence exposure may be associated with the development of aggressive behaviors [25].

Negative Affect as a Mediating Pathway

As a search for meaningful mediators continues (in the relationship between exposure to violence and aggressive behaviors in youth), one promising variable is the experience of negative affect (NA). Previous studies have found that violence exposure is linked with experiences of NA, such as anxiety and depression. For example, exposure to community violence has been associated with depressive symptoms [26] and other internalizing symptoms (e.g., [27]). In a study of children with mothers who were depressed, Boyd et al. found that community violence exposure was associated with less anxiety induced avoidance behaviors but more physical symptoms of anxiety (e.g., muscle tension; [28]). In the same study, younger children who viewed themselves as socially skilled engaged in more avoidance behaviors related to anxiety following exposure to violence [28]. Loney et al. [29] also found that NA is related to aggressive behaviors in youth. Despite studies suggesting that exposure to violence, NA, and aggressive behaviors are somehow interrelated, no studies have yet specifically examined whether NA serves as a mediator in the relationship between exposure to violence and aggressive behaviors in youth. Identifying NA as a significant mediator in this relationship would help broadened our understanding of the various pathways through which violence exposure leads to aggressive behaviors.

The Present Study

The present study, we thus sought to investigate the role of emotional vulnerability in the development aggressive behaviors by looking at the role of negative affectivity in the relationship between violence exposure and aggression. According to Clark and Watson [30], NA includes negative mood states such as anger, contempt, disgust, guilt, fear, and nervousness. We predicted to find a significant relationship between exposure to violence and aggressive behaviors (consistent with previous findings; e.g., [17]). We also expected to find a significant relationship between negative affect and aggressive behaviors in our sample of residential youth. Lastly, we expected to find that negative affect would significantly mediate the relationship between exposure to violence and aggressive behaviors.



Data were collected from sequential admissions to a residential facility in a large metropolitan area in the Southeastern United States as part of a standardized assessment procedure that occurs within several days of admission to the facility (see [31] for full description). Instruments examined in the current study (indicated below) were a subset of the broader battery of assessments conducted. Data were collected by predoctoral clinical psychology interns as a part of routine clinical care. All youth and their parents and/or guardians consented to complete the measures upon admission into the facility. Youth were also given the opportunity to revoke assent verbally prior to administration of the materials. The youth were instructed to complete the forms on their own, in a group format. The interns were available to answer questions during the administration; when necessary, they verbally administered the questionnaires to youth who had difficulty reading. All youth were provided with (tangible) rewards (e.g., candy, time spent outsides) as incentives for participation.


The sample included 199 children and adolescents ages 7–17 years old (mean = 13.89; SD = 2.05) who were admitted to a psychiatric residential treatment facility in Mississippi. Use of a clinical sample allowed us to conduct analyses on a sample characterized by high levels of the variables of interest (i.e., exposure to violence, negative affect, aggression). All assessment measures referenced below were completed as part of a psychometrically-supported assessment battery administered to all youth residents at intake [31]. Youth with at least 90 % completed data were included in the study, allowing for the inclusion of the majority of participants and their data (i.e., more than 90 % of all 219 possible participants), while excluding those with too many missing items (cf. [32]). Of the 217 total youth assessed at the facility, 18 youth had less than 90 % complete data and were thus excluded from the study. The remaining 199 children and adolescents (who had less than 10 % missing data) comprised our final sample. Only six participants (3 %) had one missing item on the aggression questionnaire; the remaining 193 (97 %) of the sample had no missing items. Demographics of the final sample were as follows: 53.3 % female; 59.8 % African American; 32.7 % Caucasian; 31.7 % from single-parent homes; 38.7 % not residing with either parent when not in the residential facility (due to being a ward of the state or cared for by another relative). Table 1 includes other demographic background information. Boys and girls did not differ significantly on any of the main study variables, including recent exposure to violent (as measured by the LES Recent Events scale), aggression (as measured by the BPAQ-SF total score), or negative affect (as measured by the PANAS-C NA scale).
Table 1

Participant demographics and test variables




LES recent (mean [SD])

PANAS-C NA (mean [SD])

BPAQ-SF (mean [SD])






31.12 (22.81)

38.34 (9.20)

28.73 (11.17)




34.17 (25.28)

40.43 (9.34)

31.09 (12.71)






30.79 (27.59)

39.20 (9.03)

26.91 (11.14)

 Black/African American



34.01 (21.79)

39.53 (9.74)

31.44 (12.35)




5.00 (n/a)

29.00 (n/a)

30.00 (n/a)




9.00 (n/a)

30.00 (n/a)

14.00 (n/a)




32.90 (24.22)

39.44 (9.36)

29.97 (12.10)

People in home


 Two to three



38.30 (28.98)

37.64 (9.91)

30.64 (12.61)

 Four to five



29.06 (21.16)

40.04 (9.62)

30.25 (12.80)

 Six to seven



32.27 (23.90)

41.24 (6.24)

28.45 (10.36)

 Eight to nine



32.27 (31.42)

42.68 (9.76)

31.67 (15.01)

 More than 10



12.00 (7.78)

41.80 (11.82)

30.40 (15.65)

Biological parents at home





34.12 (27.06)

44.79 (12.49)

33.32 (12.85)

 Mom only



34.55 (25.98)

38.79 (9.30)

29.11 (13.38)

 Dad only



26.58 (32.38)

36.17 (6.90)

21.21 (8.47)




32.47 (24.81)

39.76 (9.11)

32.00 (11.79)

Stepparents at home





32.88 (30.39)

42.21 (8.65)

30.56 (13.84)




24.11 (33.90)

39.16 (9.57)

26.95 (12.80)

 No stepparents



33.97 (24.06)

39.19 (9.73)

30.65 (12.34)

LES Recent = items assessing recent exposure to violence on the Life Events Scale; PANAS-C NA = Negative Affect Scale of the Positive Affect and Negative Affect Schedule for Children; BPAQ-SF = Buss Perry Aggression Questionnaire—Short Form


Life Events Scale

The Life Events Scale (LES) is a 36-item self-report measure assessing recent (e.g., “within the past year”) and lifetime (e.g., “while growing up”) frequency of witnessing or being the target of physical or sexual violence in multiple contexts including the home, school, and neighborhood [33]. Given the high correlations between recent and lifetime exposure to violence (e.g., victimization, r = .72; observation, r = .70), only recent exposure to violence was used in the current analyses. Items assessing recent exposure to violence are rated on a six-point Likert-type scale ranging from 0 (“never”) to 5 (“almost every day”) and assessed for experiences “in the past year.” Example items include “Saw someone else get slapped/hit/punched” and “Been threatened.” Previous examinations of the reliability of LES subscales demonstrated psychometric support for the instrument, with alpha reliability coefficients ranging from .68 to .87 for items related to recent exposure and .66 to .80 for items assessing lifetime exposure [33]. Reliability estimates for the LES scale scores as utilized in the current study were also high, with alpha reliability coefficients of .94 for items related to recent violence exposure and .91 for items assessing lifetime exposure (i.e., prior to the last year).

Buss–Perry Aggression Questionnaire: Short Form

The Buss–Perry Aggression Questionnaire—Short Form (BPAQ-SF) is a 12-item self-report measure assessing aggressive behaviors across four domains (i.e., physical, verbal, anger, hostility) [34]. Participants respond on a five-point Likert-type scale ranging from “very unlike me” to “very like me.” Item examples include “Given enough provocation, I may hit another person” and “I have threatened people I know.” The BPAQ-SF scores have evidenced strong psychometric support across a number of previous studies [34, 35], with reliabilities ranging from .62 to .77 [35]. We used the total aggression score in the present study. The reliability estimate of the total score in the current sample was .90.

Positive Affect and Negative Affect Schedule for Children (PANAS-C)

The PANAS-C is a 27-item, self-report measure assessing youth experiences of positive and negative affect [36]. Respondents are asked to rate various affective-related items with the time scale being within the past few weeks. It is important to note, however, that positive and negative affect have been found to be relatively stable constructs [37], and so these scores may be used as markers for general temperament extending far beyond just the ‘past few weeks.’ Adjectives of mood states are rated on a five-point Likert-type scale from 1 (“very slightly or not at all”) to 5 (“extremely”), yielding two scale scores corresponding to Negative Affect (15 items) and Positive Affect (12 items). The PANAS-C has demonstrated good convergent and divergent validity with symptoms of anxiety and depression as well as strong internal consistency coefficients (αNA = .92; αPA = .89; [36] ). Ebesutani and colleagues also recently found that the NA total score should continue to be used and interpreted as the preferred index of general negative affectivity across both children and adolescents, despite the emergence of NA:Fear and NA:Distress group factors in adolescence [31]. The PANAS-C NA scale was thus used in the current study as the criterion measure for negative affectivity across all youth in our sample. Internal consistency of the NA scale scores in the present study was .90, meeting the benchmark for acceptable reliability for scale scores used in clinical samples [38].

Data Preparation

Missing data levels were low for all measures included in the study. Specifically, of the 199 youth included in the study, 193 (97 %) had no missing BPAQ-SF data and the remaining 6 youth (3 %) had only one missing item. Among the 199 included youth, 177 youth had available PANAS-C data. Of these, 176 youth had at least 90 % completed PANAS-C data and were thus included in analyses. Specifically, 158 youth had no missing PANAS-C items, 17 youth had one missing item, and one youth had two missing items. There were also 156 youth with available LES data. Of these, 152 youths had at least 90 % completed data and were thus included in analyses. Specifically, 136 youth had no missing LES items, 12 youth had one missing item, and four youth had two missing items. We then imputed missing data using the missing value analysis (MVA) module of SPSS 15.0 (SPSS 2006), which examines missing data patterns and imputes missing values through a maximum likelihood method based on expectation maximization algorithms [39]. The SPSS MVA imputation method requires that data be missing completely at random (MCAR) to ensure that biases are not introduced into the dataset following imputation. We thus conducted Little’s MCAR test available in SPSS to test for MCAR across the various measures with missing data. A nonsignificant Chi square value indicates that the data are MCAR [40]. Results revealed that the BPAQ data were missing completely at random (χ2 = 56.81, df = 55, p = .408); and the PANAS-C data were missing completely at random (χ2 = 233.80, df = 257, p = .848). The LES Recent data however did not meet criteria for missing completely at random (χ2 = 474.85, df = 272, p < .001). Because of this, we examined for differences between those with and without missing LES Recent data. Those with (n = 15) and those without (n = 140) missing LES Recent data did not differ with respect to age [t(152) = .08, p = .936], or gender proportions [i.e., the gender proportion difference of .079 was not significantly greater than zero (CI99 % = −.0196 to .1776)]. This thus provides support that little to no bias was introduced due to missing data.

Data Analytic Approach

We conducted structural equation modeling (SEM) using Mplus version 4.21 [41] to examine relationships between our variables. Our initial inclination to control for variables—such as types of violence—was precluded by Miller and Chapman’s [42] criticisms against statistical “control” of variables in studies that do not use random assignment to groups. Despite the use of sophisticated statistical methods for “control,” Miller and Chapman [42] argued that it is not possible to statistically control for confounding variables, despite often being seen in the literature; instead such efforts to “control” for variables lead to relatively meaningless and often misleading results and flawed conclusions.

In our mediation model, we used the 12 BPAQ-SF items as indicators of latent “aggression,” the 15 PANAS-C NA items as indicators of latent “negative affectivity,” and the 24 LES-Recent Violent Events items as indicators of latent “recent exposure to violent events.” We created items parcels for each of the three constructs using the same procedures described by Chorpita so that the overall SEM model had three (item parcel) indicators identifying each factor [43]. We utilized this strategy given that item parceling (a) improves the distribution properties of each indicator, and (b) minimizes the contribution of measurement effects to model fit (cf. [43]).

We followed Anderson and Gerbing’s [44] recommended two-step approach for the mediational analyses in the present study. First, we used confirmatory factor analysis (CFA) to identify the best-fitting measurement model of our data related to NA, aggression and exposure to negative life events. As recommended by Byrne [45], we fixed the variances of each of the latent factors to 1.00 to identify the factors in the measurement model and to establish a metric for the latent constructs. We used the MLM estimator and evaluated model fit using fit indices via widely published cut-offs for interpretation of good model fit, including the Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Standardized Root Mean Square Residual (SRMR), and the Root Mean Square Error of Approximation (RMSEA). CFI and TLI values of .90 or greater [46] and more recently, values of .95 or greater [47], have been deemed cut-offs for good model fit. RMSEA values of .08 or lower [48] also suggest good model fit. SRMR values less than or equal to .05 also suggest good model fit, and values between .05 and .10 suggest acceptable fit [49]. All parameters reported are indicated as completely standardized solutions.

We also conducted a combination of tests to examine the mediated effect in an SEM framework. First, we examined the presence of a mediating variable effect via Baron and Kenny’s causal link approach which requires the following conditions to be met: (1) the independent variable (exposure to violent events) significantly predicts the dependent variable (aggressive behaviors), (2) the independent variable (exposure to violent events) significantly predicts the hypothesized mediating variable (NA); (3) the hypothesized mediating variable (NA) significantly predicts the dependent variable (aggression) while controlling for the independent variable (exposure to violent events); (4) full mediation is supported if the relationship between the independent variable (exposure to violent events) and the outcome variable (aggression) changes from significant to non-significant once accounting for the hypothesized mediating variable (NA), and (5) partial mediation is supported if the relationship between the independent variable (exposure to violent events) and the outcome variable (aggression) significantly drops, yet remains significant after accounting for the hypothesized mediating variable (NA). All parameters were estimated using SEM [50].

In addition to examining these steps, we used the “indirect” command in Mplus and employed the bias-corrected bootstrapping method in SEM with 5,000 resampling iterations and generated asymmetric confident intervals of the mediated effect—akin to the sobel test in a regression framework—given that this is a recommended approach when testing mediation effects [51].


Negative Affect, Exposure to Violence and Aggression

Measurement Model

As outlined above, the first step in data analysis was to examine the fit of our measurement model for the latent constructs of interest (i.e., NA, historical exposure to violence, recent exposure to violence, and aggression). Figure 1 depicts our measurement model for this analysis, which was associated with good model fit (i.e., CFI = .98, TLI = .97, RMSEA = .08, SRMR = .05). All factor loadings between indicators and latent factors were also high and significant.
Fig. 1

Measurement model of latent aggression, negative affect, and exposure to violence. LES = Life Events Scale; NA = negative affect as assessed by the Positive Affect and Negative Affect Schedule for Children; Agg = aggression as assessed by the Buss–Perry Aggression Questionnaire—Short Form

Exposure to Violence and NA

We then regressed latent negative affectivity (NA) on latent exposure to violence. The path coefficient between exposure to violence and NA in this structural model was significant (γ = .21, z = 2.04, p < .05).

Negative Affectivity as a Mediating Variable

Because exposure to violence (i.e., the IV) was significantly related to aggression (i.e., the DV) and also to NA (i.e., the proposed mediating variable), we then conducted multiple tests to examine whether NA significantly mediated the relationship between exposure to violence and aggression. The structural model for these analyses (including all parameter estimates) appears in Fig. 2. The measurement model evidenced good overall model fit (i.e., CFI = .98, TLI = .97, RMSEA = .08, SRMR = .05). All statistical tests converged supporting the notion that NA (partially) mediated the relationship between exposure to violence and aggression. First, Baron and Kenny’s causal link test supported mediation, given that (a) exposure to violence (i.e., the IV) significantly predicted aggression (i.e., the DV); (b) exposure to violence significantly predicted NA (the proposed mediator); (c) the hypothesized mediating variable (NA) significantly predicted aggression while controlling for exposure to violence (γ = .34, z = 4.06, p < .05; see Fig. 2); and (d) the relationship between exposure to violence and aggression dropped when accounting for NA (suggesting partial mediation, due to the path from recent exposure to violence to aggression remaining significant after including the hypothesized mediator in the model) [50]. Further, the bias-corrected bootstrapped confidence interval of the mediated effect of NA did not include zero (CI(95 %) = .004–.079), providing additional support that the temperamental trait of NA accounts for a significant portion of the relationship between exposure to violence and aggression. Together, these convergent results suggest that NA is a significant partial mediator of the relationship between recent exposure to violence and aggression.
Fig. 2

Structural model of negative affect as a mediator of exposure to violence and aggression. LES = Life Events Scale; NA = negative affect as assessed by the Positive Affect and Negative Affect Schedule for Children; Agg = aggression as assessed by the Buss–Perry Aggression Questionnaire—Short Form


The findings of the current study suggest that violence exposure is a significant predictor of current aggressive behavior. This is consistent with previous findings showing that violence exposure negatively influences behavior (e.g., [52, 53]). The present findings also provided support for the significant role of NA in the prediction of aggressive behaviors, thus corroborating previous studies on the role of trait affectivity in maladaptive behaviors such as aggression (e.g., [29]). This finding further bolsters the association that has been noted to exist between negative affective correlates and aggressive behaviors. Research has demonstrated that state-induced anger is a negative emotion associated with greater left (than right) prefrontal cortex activation and the motivation to approach [54, 55] and offensive aggression in animals (i.e., attack without escape tendencies) [56]. These findings have also been found in humans, linking negative affect related states, such as anger, with aggression [57].

Likewise, exposure to violence was a significant predictor of negative affect as corroborated by previous studies and etiological conceptualizations [58]. Depressive symptoms, for example, have been found to be associated with violent victimization [59] and acute experiences of violence in the community [18]. Physically abusive punishment and experiences of physical assault have also been associated with symptoms of posttraumatic stress disorder [60], providing support for the role of violence exposure in experiences associated with negative affect.

To examine the interrelationships among these variables, the current study went beyond the methods employed by previous studies by simultaneously relating all variables in a single mediational model. Conclusions based on these analyses indicated that the relationship between exposure to violence and aggressive behaviors was significantly mediated (partially) by NA. This suggests that the experience of exposure to violent events may not be sufficient to completely explain aggressive behaviors; rather, violence exposure appears to confer its risk via subsequent and intermediate negative affective emotional experiences. Consistent with this notion, Boyd and colleagues found that low levels of anxiety in an aggressive group of boys served to protect them from future exposure to violence [61]. Negative affectivity thus appears to be an important and highly relevant client characteristic to consider, evaluate and monitor with respect to risk and protective factors following violence exposure. This is particularly relevant in the context of violent neighborhoods where children are often kept home in efforts to protect them from future re-exposure to violence in the community [62]. Although such efforts can be helpful (due to keeping children safe from violence re-exposure), doing so also has the potential to affect the youth’s negative affect experience. Specifically, keeping children protected in their homes also simultaneously restricts a child’s activities and contact with (prosocial) peers—which are believed to have positive effect on one’s NA-related affective experiences [19, 59]. This illustrates the complicated relationship between violence exposure and the development of aggressive behaviors and the intermediate processes that may be important to consider in order to prevent the development of aggressive behaviors. Finding ways to simultaneously protect youth from violence re-exposure and also minimize negative affective experiences following exposure to violence will be important for future directions in this line of research. Identifying NA as a relevant and significant mediator in this relationship also has implications related to identification and prevention efforts. Specifically, youth exposed to violence with already known levels of high NA may be in need of further assessment; interventions may also need to be initiated early in the process to prevent the development and acquisition of aggressive behaviors in such youth.

In these noted ways, finding mediators of the relationship between violence exposure and aggressive behavior is important for research and clinical application. Given the partial mediation results found in the current study, however, other intervening variables also need to be identified in future work. According to Patterson’s model, aggressive behaviors may more likely be exhibited by children who have learned to interact coercively and are associated with peers that promote aggressive behaviors when approached with violent situations [21]. This pathway should thus be examined in future studies as an important link between violence exposure and the development of aggressive youth behavior. Research also supports the role of maternal depression as another important factor in the relationship between community violence and behavioral problems in adolescents [63]. In future work that seeks to identify other mediators of this relationship between violence exposure and the acquisition of aggressive behaviors, it may also be helpful to consider the related set of findings that boys are at greater risk for violence exposure (e.g., [64] ), as are African Americans compared to other races [65]. Identifying and combining these various potential mediators and intervening pathways would greatly enhance our understanding of how and when aggressive behaviors develop in children and adolescents—and how to prevent them.

Limitations and Future Recommendations

The current study is not without limitations. First, the cross-sectional nature of the present data limits our ability to make direct causal inferences and claims about the directionality of effects. Although our findings suggest that exposure to violence lead to increased aggressive behaviors, it is possible that aggressive behavior increases one’s likelihood to be exposed to violent experiences. Future studies would do well to examine this issue more close via longitudinal designs. The current study was also conducted in a residential setting that derives most of its population from rural areas with high poverty rates and low SES. As previous research suggests, these youth are representative of the population for whom the study of aggression may provide the most pragmatic implications for children’s mental health. Nonetheless, more studies should be conducted on more diverse samples to increase the generalizability of the present findings to other regions of US and abroad. As cited in the literature on aggression, we do not yet have strong evidence pertaining to the effects of different forms of violence exposure (e.g., setting differences, observation of violence vs. target of violence, differences in perpetrators of violence) on the development of various negative outcomes [3]. Studies that aim to delineate the psychological effects of sexual abuse in childhood, for example, report significant elevations on all scales measuring the psychological symptoms of traumatic events (e.g., anxious arousal, depression, dissociation) as well as associations among the aforementioned symptoms and abuse at a later age, higher number of incidence of abuse, having multiple abusers, and being upset during the incident [66]. It is important to note that many of these studies have used statistical methods in attempts to “control” for confounding variables. The use of such statistical methods however is associated with flaws that are not insignificant and limit our ability to draw accurate inferences from the results (see [42] for a detailed discussion). To overcome such limitations, future studies may seek to identify and include only youth who have been exposed to single violence exposure types, and compare the effects of different violence exposure types across youth. Future efforts of this nature will be useful to extend our knowledge of the generalized sequelae of violence exposure on psychological functioning.


Aggressive behavior in youth is a serious problem that is in need of attention to better understand its contributing risk factors and pathways to development. Through better understanding the various components and developmental pathways of aggression, we may be better able to understand, identify, and prevent the onset of aggressive acts in youth. The present study represents a small step towards advancing our understanding of aggression and its precursors in this area—particularly the ways in which exposure to violence may confer risk for later aggressive acts. We used a clinical sample of youth (N = 199), ages 7–17 years, referred to a psychiatric residential treatment facility to identify pathways through which exposure to violence leads to the development of aggressive behaviors in youth. We hypothesized that one’s experience of negative affect following exposure to violence contributes significantly to the development of aggressive behaviors in youth. Using structural equation modeling, we found support for this notion. Specifically, negative affect significantly mediated the relationship between violence exposure and aggressive behaviors in youth. This finding was also found across both children and adolescents. Indeed, more research is needed to substantiate this finding, particularly using research designs involving longitudinal designs and longitudinal data modeling. Nonetheless, the present findings support a line of research that has important implications related to the identification, prevention and treatment of this national problem of aggression. We hope that continued research in this area leads to further unraveling of this complicated relationship between aggression, one’s experiences/learning history, environment, and biological vulnerabilities, so that we can do a better job at thwarting the development, maintenance, and worsening of aggressive acts in youth.

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© Springer Science+Business Media New York 2014