دانلود مقاله ISI انگلیسی شماره 38592
عنوان فارسی مقاله

مسیر های طولی قربانی، استفاده از مواد مخدر و بزهکاری ها: یافته ها از سازمان ملی نوجوانان

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
38592 2011 8 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
Longitudinal pathways of victimization, substance use, and delinquency: Findings from the National Survey of Adolescents
منبع

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

Journal : Addictive Behaviors, Volume 36, Issue 7, July 2011, Pages 682–689

کلمات کلیدی
خشونت بین فردی - قربانی - مصرف مواد - بزهکاری - نوجوانان -
پیش نمایش مقاله
پیش نمایش مقاله مسیر های طولی قربانی، استفاده از مواد مخدر و بزهکاری ها: یافته ها از سازمان ملی نوجوانان

چکیده انگلیسی

Abstract Using a nationally representative sample of 3614 adolescents, age 12 to 17 years, this study examines longitudinal associations among interpersonal victimization (i.e., sexual abuse, physical abuse and/or assault, and witnessed community and domestic violence) and high risk behavior (i.e., alcohol use, drug use, and delinquent behavior). A bidirectional relationship was hypothesized between high risk behavior and victimization for the full sample. Descriptive results indicated that a high correlation between types of high risk behavior, with over 50% of adolescents having engaged in at least one type of high risk behavior by Wave 2 in the study. Results suggested strong links between victimization and high risk behaviors, whereas sequential order of the constructs across time was dependent on gender and type of victimization. Specifically, hypotheses concerning victimization and high risk behavior were fully supported with boys, but different patterns emerged in the data for girls.

مقدمه انگلیسی

. Introduction Data from a variety of sources indicate a high prevalence of interpersonal violence victimization among adolescents, including sexual assault, physical assault/abuse, and witnessing domestic or community violence (Finkelhor et al., 2005, Finkelhor et al., 2009, Kilpatrick, Saunders and Smith, 2003 and Saunders, 2003), with gender differences in violence exposure consistently noted across studies. Male adolescents are more likely to experience physical assault and witnessed community violence, whereas females report higher rates of sexual abuse or assault (Finkelhor et al., 2005, Finkelhor et al., 2009, Kilpatrick, Ruggiero, et al., 2003, Kilpatrick, Saunders and Smith, 2003 and Stevens et al., 2005). A wealth of data suggests that victimization, in both sexes, is related to substance use and delinquent acts (hereto referred to as high risk behavior; e.g., Kilpatrick et al., 2000); however, the temporal relation is yet to be determined. Further, although gender differences are reported in the rates of various forms of interpersonal violence, as well as in engagement of high risk behaviors (e.g., Danielson et al., 2009), potential gender differences in the relations between victimization and high risk behaviors has not been studied, and therefore is the aim of the present study. 1.1. Victimization, substance use, and delinquent behavior Victimization has been linked to high risk behavior, such as increased substance use (Finkelhor et al., 2009, Kilpatrick et al., 2000 and Widom et al., 2006) and delinquency (Kingree, Phan, & Thompson, 2003;Stewart, Dennison, & Waterson, 2001). For example, studies indicate higher rates of alcohol use among adolescents with a victimization history (Hamburger et al., 2008 and Simpson and Miller, 2002), as well as strong associations between victimization and delinquency (Widom and Maxfield, 2001 and Dembo et al., 2007). Importantly, evidence suggests that high risk behaviors, such as alcohol and drug use problems and delinquency, tend to occur simultaneously (Dembo & Schmeidler, 2002). Researchers have found that 25% of adolescents detained for delinquent acts also reported alcohol use, 70% reported drug use, and 75% reported either alcohol or drug use (National Center on Addiction and Abuse Substance, 2002). Despite the reported high rates of co-occurrence of substance use and delinquency in youth with a victimization history, previous studies have examined these high risk behaviors in isolation. Studies have provided valuable information regarding the link between victimization and substance use – or victimization and delinquency – the frequent co-occurrence of multiple high risk behaviors in adolescents suggests the need for a combined investigation of these constructs. And further, less information is available on the temporal order of these constructs; whether paths between these constructs may be acting simultaneously or whether associations vary across different types of victimization. In other words: does victimization predict high risk behavior; does high risk behavior predict victimization; or are these relationships bidirectional? Two theoretical frameworks generate hypotheses to explain the temporal ordering of these relationships. First, coping theory proposes that adolescents engage in high risk behaviors to cope with increased negative affect resulting from exposure to victimization (Lazarus, 1993), similar to the self-medication hypothesis (Khantzian & Albanese, 2008) and negative reinforcement theory (Baker, Piper, McCarthy, Majeskie, & Fiore, 2004). In support of these theoretical frameworks, some researchers have found that adolescents who have experienced victimization were more likely to engage in high risk behavior than their non-victimized counterparts (Kilpatrick et al., 2000 and Widom et al., 2006). For example, in a longitudinal investigation of individuals from childhood into young adulthood, Widom et al. (2006) found that adolescents with histories of child abuse and neglect reported significantly more substance use in middle adulthood than their non-victimized counterparts. Similarly, other researchers have used the coping theory framework to describe behaviors in the context of victimization and high risk behavior (Macy, 2007). In contrast, findings from other studies have supported the opposite temporal sequencing relating to this link: that adolescents who have engaged in high risk behavior are more likely to experience victimization (Pedersen & Skrondal, 1996). According to life style and routine activities theories (Riley, 1987), lifestyle differences between teenagers may place some of them at increased risk for victimization. That is, adolescents who engage in high risk behavior may be more vulnerable to experiencing victimization due to the criminal and deviant lifestyles and greater exposure to potentially dangerous situations (Danielson, de Arellano, Ehrenreich et al., 2006). Although research has indicated that lifestyles involving violence or delinquent behavior increase risk of victimization (Riley, 1987 and Windle, 1994), violence is not a necessary factor; high risk behaviors including substance use may also heighten the risk for victimization (Rani & Thomas, 2000). In sum, according to coping theory, victimization is posited to precede high risk behavior; whereas the life style and routine activities theory propose that high risk behavior precedes victimization. While these theories contribute to understanding the relationship among constructs, researchers have not yet examined how they may be acting simultaneously in the expression of victimization and high risk behavior, or examined their contribution to different types of victimization. These are necessary components to further our understanding of the relationship between victimization and high risk behavior. Studies have indicated that there may be gender differences in the association between victimization and high risk behavior, with significant relationships more commonly found among girls than boys (Krischer and Sevecke, 2008 and Widom et al., 2006). A meta-analysis investigating the association between victimization and substance use found a significant link for girls, but not for boys among studies included in the review (Simpson & Miller, 2002). Similarly, several studies have reported significant relationships between victimization and delinquent behavior in girls, but not boys (Dixon et al., 2004 and Krischer and Sevecke, 2008). For example, when comparing delinquent boys and girls between 14 and 19 years of age, Krischer and Sevecke (2008) found that girls reported significantly higher rates of sexual and physical abuse than boys. However, researchers have yet to examine gender differences with regard to the temporal order between victimization and high risk behavior, or to specifically evaluate reasons for the higher associations among girls. In addition, no studies have utilized nationally representative samples, with data collected at multiple time points, to investigate these constructs simultaneously or to distinguish between different types of victimization. 1.2. Aims of the current study As indicated by this review of the extant literature, research is needed to inform understanding of the direction of the association between victimization and high risk behavior and the role of gender. The current study utilizes a nationally representative sample of adolescents (i.e., the 2005 National Survey of Adolescents [NSA-Replication]) to investigate the relationship between victimization and high risk behaviors over time. Based upon literature indicating that boys report higher rates of physical abuse and witnessing violence and girls report higher rates of sexual abuse (Finkelhor et al., 2005, Kilpatrick, Ruggiero, et al., 2003 and Kilpatrick, Saunders and Smith, 2003), these victimization variables were investigated separately within this study. Two hypotheses were proposed: (1) A bi-directional relationship would emerge between victimization and high risk behaviors, and (2) Gender differences would be found in the association between types of victimization and high risk behavior, such that physical abuse and witnessing violence would be related to high risk behavior in boys but not in girls, and sexual abuse would be related to high risk behavior in girls.

نتیجه گیری انگلیسی

3. Results Descriptive statistics on high risk behaviors and types of victimization exposure (overall and by gender) are reported in Table 1. Study variables were highly related, with 31% of variables resulting in small effect sizes, 57% in medium effect sizes, and 12% in large effect sizes (Cohen, 1988). Further, effect sizes among high risk variables (range = 0.39 to 2.34) were medium (46%) to large (54%); effect sizes among victimization variables (range = 0.02 to 0.67) were small (39%) to medium (61%); and effect sizes between high risk and victimization variables (range = 0.02 to 0.69) were small (39%) to medium (61%). Substance use behaviors and delinquent behaviors were highly inter-related, so were considered in the same latent construct for further analyses. Table 1. Descriptive statistics. Overall (N = 3614) Girls (N = 1808) Boys (N = 1806) Wave 1 Wave 2 Wave 1 Wave 2 Wave 1 Wave 2 % Yes % Yes % Yes High risk behavior Alcohol use – 5 or more drinks 13.6 20.4 13.6 18.4 13.6 22.4 Alcohol use – gotten drunk 16.0 21.4 16.9 20.5 15.1 22.3 Drug use – Ever 18.6 16.6 19.4 15.8 17.9 17.4 Drug use – 4 or more occasions 11.7 10.4 11.1 8.9 12.2 11.8 Delinquency 20.1 8.6 13.4 5.9 26.9 11.2 Any one of the above 25.1 50.8 25.9 49.9 24.3 51.7 Victimization Sexual abuse 8.0 2.2 12.2 3.9 3.8 0.5 Physical abuse and assault 19.7 6.4 17.1 5.8 22.4 7.0 Witnessed community violence 39.2 19.4 37.7 18.5 40.6 20.4 Witnessed domestic violence 7.9 1.3 9.0 1.6 6.9 1.0 Note: Wave 1 includes prevalence of high risk behavior or victimization, while Wave 2 includes incidence of high risk behavior or victimization since the last interview (M = 15.29 months, SD = 4.58 months). Table options 3.1. Structural equation model in the full sample 3.1.1. Measurement model The baseline model for victimization provided a good fit to the sample data, χ2 (15, N = 3614) = 812.39, p < 0.001, NFI = 0.94, CFI = 0.94, SRMR = 0.05. Victimization at Wave 1 significantly predicted victimization at Wave 2 (β = 0.68, B = 22.76, p < 0.05) suggesting invariance of the construct over time. Similarly, the baseline model for high risk behavior provided an adequate fit, χ2 (29, N = 3614) = 4253.85, p < 0.001, NFI = 0.92, CFI = 0.92, SRMR = 0.08. High risk behavior at Wave 1 significantly predicted behavior at Wave 2 (β = 0.73, B = 43.88, p < 0.05). Finally, separate models were sequentially fit to test the invariance of factor loadings and stability coefficients across time in each construct. Results indicated a significant decline in fit for victimization, Δχ2 (8, N = 3614), p < 0.001, and high risk behavior, Δχ2 (10, N = 3614), p < 0.001; suggesting that factor loadings lacked invariance across time. 3.1.2. Cross-lag analyses The cross-lag model was fit to the sample data to examine the relation between victimization and high risk behavior (see Fig. 1). Results indicated that the model combining these constructs provided adequate fit to the hypothesized model, χ2 (122, N = 3614) = 8198.33, p < 0.001, NFI = 0.90, CFI = 0.91, SRMR = 0.10. Investigation of individual paths revealed that victimization at Wave 1 significantly predicted high risk behavior incidence at Wave 2 (β = 0.42, B = 16.47, p < 0.05), and risky behavior at Wave 1 significantly predicted victimization incidence at Wave 2 (β = 0.23, B = 9.30, p < 0.05). Additionally, paths from the victimization and high risk behavior latent constructs were investigated separately by time point. Results indicated that victimization and high risk behavior were significantly related at Wave 1 (β = 0.41, B = 19.32, p < 0.05), and also at Wave 2 (β = 0.57, B = 21.55, p < 0.05) assessment. 3.2. Gender differences Structural equation models were analyzed separately for boys (N = 1806) and girls (N = 1808) to investigate gender differences in the relation between victimization and high risk behavior. Sexual abuse was limited to investigation among girls, due to the low incidence (N = 6) of boys reporting new sexual victimization at Wave 2. Therefore, only physical abuse/assault, witnessed community violence, and witnessed domestic violence variables were included in the victimization latent construct. All procedures for analyzing the measurement model and cross-lag analyses followed that of the model in the full sample as described above. 3.2.1. Boys For boys, the baseline measurement model for victimization provided good fit to the sample data, χ2 (5, N = 1806) = 165.69, p < 0.001, NFI = 0.98, CFI = 0.98, SRMR = 0.09. As with the overall model, victimization at Wave 1 significantly predicted victimization incidence at Wave 2 (β = 0.65, B = 19.17, p < 0.05) for the boys, suggesting invariance of the construct over time. The baseline model for high risk behavior provided adequate fit for the sample of boys, χ2 (29, N = 1806) = 2350.70, p < 0.001, NFI = 0.92, CFI = 0.92, SRMR = 0.21. Further, high risk behavior at Wave 1 significantly predicted high risk behavior incidence at Wave 2 (β = 0.77, B = 33.06, p < 0.05). Results of the cross-lag model analyses provided adequate fit to the sample of boys, χ2 (92, N = 1806) = 4773.74, p < 0.001, NFI = 0.89, CFI = 0.89, SRMR = 0.23. As Fig. 2 shows, examination of individual paths revealed that victimization at Wave 1 significantly predicted high risk behavior at Wave 2 (β = 0.03, B = 1.55, p < 0.05), and high risk behavior at Wave 1 significantly predicted victimization at Wave 2 (β = 0.07, B = 2.96, p < 0.05). Finally, the paths between high risk behavior and victimization were significant at Wave 1 (β = 0.71, B = 23.06, p < 0.05), and at Wave 2 (β = 0.28, B = 9.66, p < 0.05). Boys – physical abuse/assault, witnessed community violence, and witnessed ... Fig. 2. Boys – physical abuse/assault, witnessed community violence, and witnessed domestic violence. Figure options 3.2.2. Girls The baseline measurement model for victimization (i.e., physical abuse/assault, witnessed community violence, and witnessed domestic violence) provided adequate fit to the sample of girls, χ2 (5, N = 1808) = 505.58, p < 0.001, NFI = 0.94, CFI = 0.94, SRMR = 0.06. Further, victimization at Wave 1 significantly predicted victimization incidence at Wave 2 (β = 0.68, B = 12.42, p < 0.05), suggesting invariance of the construct over time. For girls, the baseline model for high risk behavior provided good fit to the data, χ2 (29, N = 1808) = 2343.91, p < 0.001, NFI = 0.90, CFI = 0.90, SRMR = 0.08. High risk behavior at Wave 1 significantly predicted high risk behavior at Wave 2 (β = 0.67, B = 19.72, p < 0.05). Results of the cross-lag model did not provide an adequate fit to the sample of girls, χ2 (92, N = 1808) = 2385.98, p < 0.001, NFI = 0.85, CFI = 0.86, SRMR = 0.12. The individual paths of this model could not be interpreted, as the overall cross-lag model did not provide adequate fit to the data. 3.3. Sexual abuse in girls Additional analyses were conducted to examine paths of sexual abuse in girls. Procedures followed those of the overall abuse model, although the victimization latent construct consisted of sexual abuse only. A baseline measurement model for sexual abuse could not be conducted, due to lack of degrees of freedom. Sexual abuse at Wave 1 significantly predicted sexual abuse at Wave 2 (β = 0.50, B = 33.47, p < 0.05). The baseline model for high risk behavior provided a good fit to the sample data, χ2 (29, N = 1808) = 2343.91, p < 0.001, NFI = 0.90, CFI = 0.90, SRMR = 0.08, although high risk behavior at Wave 1 did not significantly predict high risk behavior incidence at Wave 2 (β = 0.80, B = 11.29, n.s.). Results of the cross-lag model investigating sexual abuse provided a good fit to the sample of girls, χ2 (46, N = 1808) = 5753.42, p < 0.001, NFI = 0.99, CFI = 0.99, SRMR = 0.08. As shown in Fig. 3, the individual path from sexual abuse at Wave 1 to high risk behavior at Wave 2 was significant (β = 0.47, B = 16.68, p < 0.05), although high risk behavior at Wave 1 did not significantly predict sexual abuse at Wave 2 (β = 0.22, B = 3.09, n.s.). Finally, high risk behavior and sexual abuse were not significantly related to one another at Wave 1 (β = 0.46, B = 7.65, n.s.), but were significantly related at Wave 2 (β = 0.42, B = 11.24, p < 0.05). Girls – sexual abuse. Fig. 3. Girls – sexual abuse.

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