دانلود مقاله ISI انگلیسی شماره 36785
عنوان فارسی مقاله

تاثیر خودکنترلی و اختلال محله ای بر روی قربانی زورگویی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
36785 2014 9 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
The Impact of Self Control and Neighborhood Disorder on Bullying Victimization
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Criminal Justice, Volume 42, Issue 4, July–August 2014, Pages 347–355

کلمات کلیدی
خودکنترلی - اختلال محله ای - قربانی زورگویی
پیش نمایش مقاله
پیش نمایش مقاله تاثیر خودکنترلی و اختلال محله ای بر روی قربانی زورگویی

چکیده انگلیسی

Abstract Purpose Whereas past research has examined the effect of individual-level and neighborhood-level predictors of bullying victimization separately, the current study examines their effects collectively. Methods Middle and high school students (n = 1972) in randomly selected classes within a Southeastern school district completed a battery of self-report measures. Levels of self-control (an individual-level factor) and neighborhood disorganization (a neighborhood-level factor) were regressed onto measures of the six-week prevalence of verbal, physical, and cyber bullying victimization.

مقدمه انگلیسی

Introduction Bullying has been identified as the persistent harassment (physical, verbal, emotional, or psychological) of one individual over another, accompanied by a power imbalance (Olweus, 1993). Research has documented that bullies use a variety of methods (i.e., physical, verbal, relational, and cyber) to victimize their peers (Hinduja and Patchin, 2008 and Wang et al., 2009). National studies documenting the prevalence of bullying suggest that approximately 30 percent of the youth in the U.S. population have experienced a bullying incident (Nansel et al., 2001). Despite sustained decreases in the nation's violent crime rates (Truman, Langton, & Planty, 2013), bullying and bully victimization among children and adolescents continues to capture the attention of the public and scholars alike (Committee on Injury, Violence, & Poison Prevention, 2009). Recent national public opinion data indicate that 74% of Americans believe that bullying is a “very serious” or “somewhat serious” problem (Public Agenda, 2010). Bullying and bully victimization have attracted the interest of researchers around the world (e.g., Arseneault et al., 2006, Bowes et al., 2009, Chui and Chan, 2013, Holt et al., 2013, Klomek et al., 2007, Klomek et al., 2008, Klomek et al., 2009, Olweus, 1993, Sourander et al., 2007a, Sourander et al., 2007b and Wong et al., 2014) who generally find that offenders and victims are at an elevated risk of experiencing adverse academic, legal, and mental health consequences (Arseneault et al., 2006, Copeland et al., 2013, Farrington and Ttofi, 2011, Gini and Pozzoli, 2013, Kaltiala-Heino et al., 1999, Klomek et al., 2007, Klomek et al., 2008, Klomek et al., 2009, Kumpulainen and Rasanen, 2000, Nansel et al., 2003, Sourander et al., 2000, Sourander et al., 2007a, Sourander et al., 2007b and van der Wal et al., 2003). Much of the literature targeting bully victimization has focused on individual-level risk factors of the victims, their peers, and educational institutions (Bowes et al., 2009, Cullen et al., 2008, Khoury-Kassabri et al., 2004, Shields and Cicchetti, 2001, Unnever and Cornell, 2003, Wolke et al., 2001 and Zimmerman et al., 2005). A limited body of research has examined neighborhood-level factors that may affect the risk of victimization. For instance, Bowes et al. (2009) have found that school, family, and neighborhood factors increase the odds of bullying and bully victimizations. Scholars have, however, given little consideration to how both individual-level and neighborhood-level factors affect the risk of victimization within the same statistical models. As a result, there is an underlying question as to whether the nature of bullying victimization is being driven by individual, situational, or contextual factors. This is a particularly salient question due to the various forms of bullying that may occur, whether physical, verbal or more recently via cyberspace (Holt et al., 2013, Lows and Espelage, 2013, Turner et al., 2013 and Wang et al., 2009). As a result, there is a need to identify the factors that contribute to the experience of bully victimization across on and off-line environments and any differences in the relationships between micro and macro-level factors. Criminological research has focused primarily on neighborhood level factors that increase the risk of victimization, particularly living in disorganized communities that increase proximity to motivated offenders, expose residents to larger opportunities to offend, and foster subcultures that support the use violence and intimidation (Anderson, 1999, Bowes et al., 2009, Fox et al., 2010, Lauritsen and Laub, 2007, Lauritsen et al., 1991, Lowenkamp et al., 2003, Sampson and Groves, 1989 and Stewart et al., 2006). Recently, however, Schreck (1999) developed an individual-level theory emphasizing the role that low self-control plays in increasing the risk of victimization. This theory combines routine activities and low self-control, and finds that youth with low self-control are more likely to engage in risky lifestyles and be exposed to criminal others thereby increasing the risk of victimization Piquero et al., 2005, Schreck, 1999, Schreck et al., 2006, Schreck et al., 2002, Stewart et al., 2004 and Bossler and Holt, 2010).

نتیجه گیری انگلیسی

Results Table 1 summarizes the variables in this study. Participants ranged in age from 11 to 18 with a mean of 13.89 years. Slightly less than half of the students in the sample (48%) were male, and 27% of students identified their race as something other than “white.” Half of the sample had experienced an act of verbal bullying since the beginning of school (approximately 6 weeks earlier), compared to 28% who experienced physical bullying and 12% who experienced cyberbullying. Table 1. Summary of Study Variables (N = 1972) Variable M/% SD Min Max Age 13.89 1.92 11 18 Male 48% --- 0 1 Nonwhite 27% --- 0 1 Academic difficulty 2.48 1.17 1 5 Low self-control 15.95 3.25 6 24 Neighborhood disorder 9.61 3.53 7 21 Verbal bully victim 50% --- 0 1 Physical bully victim 28% --- 0 1 Cyberbully victim 12% --- 0 1 Table options Binary logistic regression models were used to assess the relationship between each form of bullying victimization and the set of covariates. Table 2 summarizes the logistic regression results for four models predicting the prevalence of verbal bullying since the beginning of school. In the first model, only demographic characteristics, academic success, and low self-control were used to predict victimization, with odds ratios and confidence intervals shown. In the second model, the control variables and neighborhood disorder were included. Model Three presents the demographic factors, self-control, and neighborhood disorder to control for each in a single model. In the final model, the remaining bullying victimization measures were included. Identical sets of regression models were used to predict physical bullying (Table 3) and cyberbullying (Table 4). Table 2. Logistic Regression Models Predicting Verbal Bullying Victimization Exp(β) (95% CI)a Model 1 Model 2 Model 3 Model 4 Age 0.94** (0.89-0.98) 0.93** (0.88-0.97) 0.93** (0.88-0.977) 0.96 (0.91-1.01) Male 0.89 (0.74-1.06) 0.87 (0.73-1.04) 0.88 (0.73-1.05) 0.82 (0.66-1.01) Nonwhite 0.75** (0.62-0.92) 0.63*** (0.51-0.76) 0.68*** (0.56-0.84) 0.71** (0.55-0.90) Academic difficulty 1.11* (1.02-1.20) 1.10* (1.01-1.19) 1.06 (0.98-1.15) 1.03 (0.93-1.14) Low self-control 1.04** (1.02-1.07) --- 1.03* (1.00-1.06) 1.02 (0.98-1.05) Neighborhood disorder --- 1.10*** (1.07-1.13) 1.09*** (1.06-1.12) 1.06*** (1.03-1.10) Cyberbully victim ---- --- --- 5.33*** (3.41-8.33) Physical bully victim ---- --- --- 14.66*** (10.75-20.00) Constant 1.09 0.96 0.62 0.40* Nagelkerke R2 0.02 0.05 0.05 0.37 Exp(B) indicates the factor by which the odds for bullying victimization change when the independent variable increases by 1 unit; *p < .05; **p < .01; ***p < .001; Model 1: − 2LL = 2703.022; χ2 (5) = 30.651***; Model 2: − 2LL = 2867.133; χ2 (5) = 89.585***; Model 3: − 2LL = 2693.959; χ2 (6) = 78.621***; Model 4: − 2LL = 2083.354; χ2 (8) = 650.320*** Table options Table 3. Logistic Regression Models Predicting Physical Bullying Victimization Exp(β) (95% CI)a Model 1 Model 2 Model 3 Model 4 Age 0.91** (0.87-0.96) 0.91*** (0.86-0.95) 0.91*** (0.86-0.96) 0.91** (0.85-0.97) Male 1.21 (0.99-1.49) 1.27** (1.05-1.55) 1.53* (1.01-1.53) 1.52** (1.20-1.93) Nonwhite 0.78* (0.62-0.98) 0.69*** (0.55-0.86) 0.71** (0.56-0.91) 0.80 (0.61-1.06) Academic difficulty 1.12* (1.03-1.23) 1.12** (1.03-1.22) 1.08 (0.99-1.18) 1.05 (0.95-1.17) Low self-control 1.05** (1.01-1.08) --- 1.03* (0.99-1.06) 1.02 (0.98-1.06) Neighborhood disorder ---- 1.09*** (1.07-1.12) 1.09*** (1.06-1.12) 1.04* (1.01-1.07) Cyberbully victim --- --- --- 2.83*** (2.04-3.92) Verbal bully victim ---- --- --- 14.71*** (10.78-20.07) Constant 0.47 0.01 0.27 0.07*** Naglekerke R2 0.02 0.05 0.05 0.39 Exp(B) indicates the factor by which the odds for bullying victimization change when the independent variable increases by 1 unit; *p < .05; **p < .01; ***p < .001; Model 1: − 2LL = 2287.137; χ2 (5) = 35.890***; Model 2: − 2LL = 2428.748; χ2 (5) = 82.479***; Model 3: − 2LL = 2283.063; χ2 (6) = 75.988***; Model 4: − 2LL = 1698.448; χ2 (8) = 624.577*** Table options Table 4. Logistic Regression Models Predicting Cyberbullying Victimization Exp(β) (95% CI)a Model 1 Model 2 Model 3 Model 4 Age 1.05 (0.98-1.13) 1.06 (0.99-1.14) 1.05 (0.98-1.13) 1.11** (1.03-1.20) Male 0.68** (0.51-.091) 0.67** (0.51-0.88) 0.66** (0.50-0.88) 0.63** (0.46-0.85) Nonwhite 1.18 (0.87-1.60) 0.87 (0.64-1.18) 1.00 (0.73-1.37) 1.36 (0.97-1.89) Academic difficulty 1.17* (1.04-1.32) 1.15* (1.02-1.29) 1.12* (1.00-1.27) 1.09 (0.97-1.25) Low self-control 1.07** (1.02-1.11) --- 1.05* (1.00-1.09) 1.03 (0.99-1.08) Neighborhood disorder --- 1.11*** (1.07-1.14) 1.11*** (1.07.1.14) 1.08*** (1.04-1.12) Physical bully victim ---- --- --- 2.84*** (2.05-3.94) Verbal bully victim ---- --- --- 5.30*** (3.39-8.29) Constant 0.01*** 0.01*** 0.00*** 0.00*** Nagelkerke R2 0.02 0.05 0.06 0.23 Exp(B) indicates the factor by which the odds for bullying victimization change when the independent variable increases by 1 unit; *p < .05; **p < .01; ***p < .001; Model 1: − 2LL = 1404.835; χ2 (5) = 27.748***; Model 2: − 2LL = 1491.625; χ2 (5) = 58.581**; Model 3: − 2LL = 1397.892; χ2 (6) = 62.832***; Model 4: − 2LL = 1173.153; χ2 (8) = 259.430*** Table options The initial model (Model 1) for each form of bullying victimization demonstrates that youth with lower grades and lower self-control levels were significantly more likely to experience each form of bullying, net of demographic controls (odds ratios > 1.00). However, certain demographic factors were predictive of specific forms of bullying. Younger students and White students were more likely to experience verbal and physical bullying, while females were more likely to experience cyberbullying (odds ratios < 1.00). Similarly, the model for neighborhood disorder (Model 2) demonstrates that youth living in disorganized communities were more likely to experience victimization. The relationship is consistent across all forms of bullying, including cyberbullying. The demographic factors also remain consistent with one exception: Males are more likely to report physical bullying victimization when controlling for neighborhood disorder. The inclusion of both self-control and disorder (Model 3) illustrates that the relationship between self-control and victimization is mediated in part by the neighborhood conditions. Both of these items are significant across all forms of victimization, though self-control decreases in significance. In addition, academic difficulty becomes non-significant for both verbal and physical bullying victimization. All other demographic relationships remain consistent. The final model included measures for multiple forms of bullying victimization (Model 4). Academic performance and low self-control no longer remained significant in any model of bully victimization. At the same time, neighborhood disorder remained a positive and significant predictor of every type of victimization, suggesting that bullying victimization—regardless of form—is related in part to detrimental neighborhood conditions. Separate analyses (not shown) indicated that the influence of neighborhood conditions on victimization was independent of the particular school students attended. The relationships between control variables and victimization also change with the inclusion of multiple forms of bullying victimization. Age and academic difficulty become unrelated to verbal bullying; however, younger students and male students were more likely to experience physical bullying. Older students and female students were more likely to experience cyberbullying. White students continued to be more likely to experience verbal bullying, but were less likely to experience cyberbullying. Thus, these models demonstrated that bullying victimization was best predicted by the other forms of bullying, resulting in an approximate three-fold to fifteen-fold increase in the odds of victimization.

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