Abstract
Objective
The purpose of this study was to examine ecodevelopmental risk factors associated with alcohol uses, rule breaking and aggressive behaviors among Hispanic delinquent adolescents. Specifically, this study tests the effect of attitudes, family, peer, and school bonding on alcohol use, rule breaking and aggressive behaviors in Hispanic delinquent youth.
Methods
A sample of 235 heterogeneous Hispanic delinquent adolescents was recruited through referrals from the Miami-Dade County’s Department of Juvenile Services and from the Miami-Dade County Public School system. Logistic regression methods were utilized to examine the independent effect of each risk factor (attitudes, family, peer, school) and to determine the extent to which these factors are associated with alcohol use, rule breaking and aggressive behaviors.
Results
Family functioning was inversely and significantly related to past 90-day alcohol use in univariate regression (β = −.24, p = .035) but was not significant in multiple regression (β = −0.09, p = .556). Peer alcohol use (β = 2.02, p<0.001) and poor alcohol attitudes (β =0.59, p=0.006) were positively and significantly related to past 90-day alcohol use in the final model. Poor alcohol attitudes, family functioning, peer alcohol use, and school bonding were all significantly related to both rule breaking and aggressive behaviors in the final model.
Conclusions
Findings highlight the importance of identifying risk factors at multiple levels to prevent/reduce alcohol use, rule breaking and aggressive behaviors among Hispanic delinquent youth.
Keywords: Hispanic, adolescent, delinquency, alcohol, aggression, ecodevelopmental
INTRODUCTION
Underage drinking and delinquency among adolescents in the Unites States (U.S.) represent major public health problems [1]. Findings from the Youth Risk Behavior Surveillance indicate that 72.5% of adolescents report having had ever drank alcohol during their life and 41.8% report having had at least one drink of alcohol during the 30 days before the assessment [2]. Although all adolescents in the U.S. are affected by underage drinking, Hispanic adolescents are disproportionately affected. For example, findings from the Monitoring the Future study indicate that Hispanic 8th and 10th graders’ use of alcohol was higher than both Black and non-Hispanic white 8th and 10th graders’, respectively [3]. Furthermore, Hispanic adolescents are more likely to report having had drunk alcohol for the first time before 13 years of age (27.1%), when compared to both their Black (24.9%) and non-Hispanic white (18.1%) counterparts, respectively [2]. This is particularly troublesome given that underage drinking is associated with a myriad of social and behavioral adverse outcomes, including delinquency, aggressive and rule breaking behaviors [4–7].
Early onset of alcohol use in adolescents has been associated with a greater increase in delinquent behaviors, including rule breaking and aggressive behaviors [8, 9]. Given that Hispanic adolescents are more likely to report initiation of alcohol use at a younger age [2], combined with higher rates of alcohol use [3], Hispanics also experience significant disparities with respect to adverse alcohol outcomes when compared to their non-Hispanic white and Black counterparts [10, 11]. For example, Hispanics are more likely to experience negative social consequences including arguments and fights, and legal problems [10], relative to their non-Hispanic white and Black counterparts. In spite of these disparities, relatively little research has been conducted aimed at better understanding the etiology of problem behaviors, including alcohol use, rule breaking and aggressive behaviors, among Hispanic adolescents. Therefore, the purpose of this study was to evaluate individual, family, peer and school risk factors associated with alcohol use, rule breaking and aggressive behaviors in a sample of Hispanic delinquent youth.
Aggressive and rule breaking behaviors among adolescents in general, and Hispanic youth in particular, are a pressing concern. Findings from the Youth Risk Behavior Survey 2009 indicate that Hispanics (36.2%) had a considerably higher rate in engaging in a physical fight when compared to non-Hispanic whites (27.8%), and fell slightly below Blacks (41.1%). Hispanic adolescents (12%) were also at higher risk to be threatened with a weapon on school property, relative to both Black (11.2%) and non-Hispanic whites (7.8%). Targeting alcohol use is one mechanism by which to reduce aggressive behaviors among Hispanic adolescents [12].
Delinquent youth are at greater risk of engaging in alcohol use [13, 14], aggressive and rule breaking behaviors [15, 16], relative to their non-delinquent adolescent counterparts. Hispanic delinquent adolescents, in particular, are at increased risk of engaging in these behaviors, when compared to Black and non-Hispanic white delinquent youth. Hispanic delinquent youth, for example, report higher rates of alcohol use when compared to Blacks, as well as higher rates of aggressive behaviors [15] relative to both Black and non-Hispanic whites. Given these disparities, there remains a need to develop and expand on theoretical models aimed at better understanding the etiology of problem behaviors among Hispanic delinquent youth.
Prevention science has highlighted the importance of taking an ecological approach to better understand the social determinants of problem behaviors in adolescents, including alcohol use, rule breaking and aggressive behaviors [17, 18]. The ecodevelopmental framework [17] in particular is helpful in conceptualizing integrated developmental risk processes operating in the lives of adolescents [17, 19, 20]. The ecodevelopmental framework [17] draws from Bronfenbrenner’s socioecological theory [21] and affirms that social domains in which the adolescent is embedded in both influence and are influenced by the adolescent in a developmental context. These systemic and developmental processes occur on various levels which include macrosystems (e.g., culture and social norms), exosystems (e.g., parent support systems), mesosystems (e.g., family-peer systems) and microsystems (e.g., individual, family). Thus, adolescent problem behaviors, including delinquency and alcohol use, are influenced by a multiplicity of factors, some of which are proximal to the adolescent, whereas others are more distal. From this perspective, the complexity of alcohol use, rule breaking and aggressive behaviors, requires that it be understood as multi-level (e.g., individual, family, peer, school) phenomena, with multiple and interrelated factors and processes contributing to their development. Although several studies have investigated factors associated with alcohol use, rule breaking and aggressive behaviors in Hispanic youth, few studies have examined risk factors at multiple levels in Hispanic delinquent adolescents [12]. Furthermore, although all Hispanic delinquent adolescents are at increased risk of engaging in alcohol use, aggressive and rule breaking behaviors, equally important is to better ascertain gender differences within this population particularly because female and male Hispanic adolescents differ in socialization processes. In fact, some research has highlighted the ways in which gender moderates the effect of family and peers on problem behaviors in adolescents [22, 23]. For example, research has found that relative to males, parental monitoring has a greater influence on aggressive behaviors in females [22]. Furthermore, research has demonstrated that families of substance abusing girls show lower levels of family cohesion and higher levels of family conflict, relative to families of substance abusing boys [24]. However, these studies did not consist of Hispanic delinquent samples or a very small sample (i.e., 8%; [24]) and therefore are not generalizable to Hispanic delinquent adolescents. Thus, there remains the need to determine whether and the extent to which the role of ecodevelopmental factors on Hispanic delinquent youth vary by gender.
PURPOSE OF THE STUDY
The present study represents a secondary analysis of a larger study aimed at evaluating the efficacy of a family-based preventive intervention on an indicated sample of Hispanic delinquent youth. The purpose of the present study was to examine ecodevelopmental risk factors associated with alcohol use, rule breaking and aggressive behaviors in an indicated sample of Hispanic delinquent adolescents. Specifically, this study tests the effects of attitudes, family, peer, and school bonding on alcohol use, rule breaking and aggressive behaviors in Hispanic delinquent youth.
METHODS
Participant Recruitment
Participants were recruited from September 2009 to February 2010 through referrals from both Miami-Dade County’s Department of Juvenile Services and from the Miami-Dade County Public School system. To be eligible for this study, adolescents had to: (a) be of Hispanic origin, (b) be between the ages of 12 – 17 years, (c) have plans to remain a resident of South Florida during the study period, and (d) be identified as a delinquent youth. For the purposes of this study, delinquency was defined as having been arrested or as having committed at least one “Level III Behavior Problem,” described by Miami-Dade County Public Schools as assault/threat against a non-staff member, breaking and entering/burglary, fighting (serious), hazing, possession or use of alcohol and/or controlled substances, possession of simulated weapons, trespassing, and vandalism. Of the 446 potential participants, 53 (39%) had intentions to move out of the area during the study period, 50 (36.8%) adolescents did not identify as delinquent, 25 (18.4%) adolescents were not between the ages of 12 and 17 years, and 8 (5.9%) were not Hispanic. Therefore, 310 potential participants met the study’s eligibility criteria. Of the 310 eligible participants, 68 did not participate of which 30 (44.1%) refused to participate, 12 (17.6%) had health complications and did not participate, and 26 (38.2%) had work schedule conflicts which prevented them from participating. Therefore, 242 youth and their primary caregivers agreed to participate, signed informed consent and assent forms, and completed the baseline assessment. This study was approved by the University of Miami’s Institutional Review Board.
Participants
A total of 235 Hispanic adolescents with a mean age of 14.7 years (SD=1.39) were included in the analysis (Seven participants were missing data and were not included in the present study). A total of 152 (65%) boys and 83 (35%) girls participated in the present study. The majority of adolescents were born in the United States (64%) and immigrant adolescents were predominantly from Cuba (25%) and Honduras (16%). Sixty-seven percent of adolescents reported having resided in the United States for over 10 years, 23% reported living in the United States between 3 and 10 years, and 10% less than 3 years. The majority (60%) of participants came from families with a total yearly income of less than $20,000.
Data Collection
Adolescents completed survey assessments via laptop computers using the audio-CASI system in her/his preferred language (i.e., English or Spanish) [25]. The content of each questionnaire item along with the response choices were read to adolescents through a set of headphones connected to the laptop computer. Adolescents indicated her/his response using the keyboard or mouse. Participants were compensated $60 for completing the assessment.
Measures
Demographics
Adolescents completed a demographics form on which they provided information including her/his age, gender, ethnic background, country of birth, and number of years lived in the United States.
Alcohol Attitudes
Alcohol attitudes was measured using one item from the CSAP [26], “Getting drunk every now and then fits with the kind of life I want to lead.” Responses ranged from 0= “Disagree a lot” to 4=“Agree a lot”.
Alcohol Use
Alcohol use was measured using one item, “On how many occasions (if any) have you had alcohol to drink - more than just a few sips in the past 3 months?”. Responses ranged from 1=“0 occasions” to 7=“40+ occasions”. Because 67.2% of participants reported no alcohol use in the past 90 days, this variable was treated as a binary variable and coded 0=“no” and 1=“yes”.
Rule Breaking Behavior
Rule breaking behavior was assessed using 15 items (α = .86) from the subscale of the Youth Self Report [YSR; 27]. For example, participants were asked, “I break rules at school, home or elsewhere.” Responses ranged from 0=“Not true” to 2=“Very true or Often true.” A total score of these 15 items were created for rule breaking behavior.
Aggressive Behavior
Aggressive behavior was assessed using 17 items (α =.86) from the Aggressive Behavior subscale of the Youth Self Report [YSR; 27]. Adolescents were asked, for example, “I get in many fights.” Responses ranged from 0=“Not true” to 2=“Very true or Often true.” A total score of these 17 items were created for aggressive behavior.
Family Functioning
Family functioning was assessed using adolescent reports of five indicators: parental involvement, positive parenting, family communication, parent-adolescent communication and parental monitoring over peers. Parental involvement and positive parenting were assessed using the corresponding subscales from the Parenting Practices Scale [28]. Parental involvement was measured with 17 items (α = .86). Adolescents were asked, for example, how often have parents talked with them about what they had actually done during the day? Positive parenting was measured with 9 items (α = .81). For example, adolescents were asked, how often have parents given them a wink or a smile when they have done something their parents like or approve of. All Items were rated on a 4 point Likert scale from 0= “never” to 3= “often”. Family communication (3 items, α = .72) was assessed using the corresponding subscale from the Family Relations Scale [29]. For example, adolescents were asked to what extent the family knows what he/she means when he/she says something [29]. Adolescents responded on a 4 point Likert scale ranging from 1 = “Not at all true” to 4 = “Almost always or always true”. Parent-adolescent communication (20 items, α = .84) was assessed using the Parent-Adolescent Communication Scale [30]. For example, adolescents were asked to what extent they can discuss beliefs with their mother without feeling restrained. Adolescents responded on a 5 point Likert scale ranging from 1 = “Strongly Disagree” to 5 = “Strongly Agree”. The Parent Relationship with Peer Group Scale [31] was used to obtain adolescent reports (6 items, α = .80) of parental monitoring attempts to actively supervise their adolescents and know their adolescents’ friends. For all five family functioning indicators, higher scores on the subscale represent higher family functioning on each indicator.
Peer Alcohol Use
Perceived peer alcohol use (1 item, α = .80) was measured using an adapted substance use item from the Monitoring the Future Survey [3]. The substance use item was adapted by replacing “have you” with “how many of your friends have”. Adolescents were asked, “How many of your friends have been high or drunk from drinking alcoholic beverages in their lifetime.” Response choices ranged from 1= “none of them” to 4= “all of them”. This variable was treated as a binary variable and coded 0=”no to perceived peer alcohol use” and 1= “yes to perceived peer alcohol use”.
School Bonding
Adolescent reports of school bonding were gathered using the school bonding subscale (8 items, α = .86) from the People in My Life [32] measure. The school bonding measure assesses the extent to which the adolescent enjoys school and feels connected to classmates and teachers and was reverse coded so that higher scores would reflect less bonding to school. For example, adolescents were asked, “Most mornings I look forward to going to school”. Responses ranged from 1= “Almost never or never true” to 4= “Almost always or always true”. A total score from these 8 items were created.
Analytic Strategy
A descriptive statistics analysis was conducted on both the outcome and predictor variables. The data analytic strategy then proceeded in three steps. First, a measurement model was estimated to ascertain the feasibility of collapsing multiple indicators of family functioning into a single latent variable (all other variables were measured using observed variables). This was done by conducting confirmatory factor analyses (CFA). The fit of the model was evaluated primarily in terms of factor loadings, the comparative fit index (CFI), which compares the hypothesized model to a null model with no paths or latent variables; and the root mean square error of approximation (RMSEA), which estimates the extent to which the covariance matrix specified in the model deviates from the covariance matrix observed in the data. CFI values of .95 or greater and RMSEA values of .06 or less are indicative of good model fit [33]. The family functioning latent variable was used in subsequent regression analyses.
Second, regression analyses with the family functioning latent variable and the other predictors were conducted to examine the relations between these factors and the three outcome variables (alcohol use, aggression, rule breaking behavior). Specifically, we ran multiple regressions with ecodevelopmental domains and attitudes entered sequentially (family, peer, school, individual). Thus we estimated a model with four steps to test the effects of each predictor variable on each outcome variable (alcohol, aggression, rule breaking behavior). First, we examined the effect of family functioning on past 90 day alcohol use in a univariate regression model. Second, we evaluated the effect of peer alcohol use, controlling for family functioning, on past 90 day alcohol use. Next, we examined the joint effect of family functioning, peer alcohol use and school bonding on past 90 day alcohol use. Finally, we evaluated all predictor variables on past 90 day alcohol use. The same analytic strategy was conducted to evaluate both the rule breaking and aggressive behavior outcomes. All analyses were conducted using Mplus version 6.11 [34].
RESULTS
A descriptive statistics analysis indicated that 32.8% of adolescents reported past 90 day alcohol use. The mean score of rule breaking behavior was 6.98 (SD=5.47) and aggressive behavior 8.56 (SD=6.34), respectively (Table 1).
Table 1.
Variable | Mean or % | Standard Deviation | Minimum | Maximum |
---|---|---|---|---|
Past 90 Day Alcohol Use | 32.8% | |||
Rule Breaking Behavior | 6.98 | 5.47 | 0 | 29 |
Aggressive Behavior | 8.56 | 6.34 | 0 | 33 |
Positive Parenting | 17.18 | 5.54 | 2 | 27 |
Parental Involvement | 36.85 | 7.49 | 17 | 52 |
Peer Monitoring | 12.62 | 4.73 | 5 | 26 |
Parent-Adolescent Communication | 64.53 | 14.25 | 24 | 100 |
Family Communication | 7.80 | 2.17 | 3 | 12 |
Peer Alcohol Use | 57.8% | |||
School Bonding | 19.67 | 5.59 | 8 | 32 |
Alcohol Attitudes | 1.58 | .80 | 1 | 4 |
Measurement Models
Family Functioning
A confirmatory factor analysis indicated that all five indicators of family functioning loaded significantly onto a single latent construct. The standardized factor loadings were .64, .81, .71, .67 and .52 for positive parenting, parent involvement, parent-adolescent communication, family communication and parental monitoring over peers, respectively. The model fit indices also suggested a good fit (X2=1.24, df=4, p=0.87; CFI=0.999 and RMSEA<0.001).
Regression Analyses
Alcohol use
Family functioning was inversely and significantly related to past 90-day alcohol use in the univariate model (β = −.24, p = .035). After entering peer alcohol use in the model, family functioning became non-significant (β = −0.22, p=0.10.), whereas peer alcohol use was significantly related to alcohol use (β =2.21, p<0.001). Peer alcohol use remained significant (β = 2.16, p <0.001) after controlling for both family functioning and school bonding. Both family functioning (β = −.15, p=0.297) and school bonding (β = −0.05, p=0.149) were non-significant in this model. Finally, poor alcohol attitudes (β = 0.59, p=0.006) and peer alcohol use (β = 2.02, p<0.001) were positively and significantly related to past 90-day alcohol use, while school bonding (β = −.04, p = .247) and family functioning (β = −0.09, p = .556) remained non-significant (Table 2).
Table 2.
Alcohol Use in the Past 90 Days | Rule Breaking Behaviors | Aggressive Behaviors | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Model | Model | Model | ||||||||||
1 | 2 | 3 | 4 | 1 | 2 | 3 | 4 | 1 | 2 | 3 | 4 | |
Family Functioning | −0.24* | −0.22 | −0.15 | −0.09 | −1.41* | −1.28* | −0.99* | −0.77* | −1.76* | −1.59* | −1.24* | −1.08* |
Peer Alcohol Use | 2.21* | 2.16* | 2.02* | 3.07* | 2.85* | 2.05* | 2.67* | 2.39* | 1.87* | |||
School Bonding | −0.05 | −0.04 | −0.19* | −0.16* | −0.23* | −0.21* | ||||||
Alcohol Attitudes | 0.59* | 2.32* | 1.52* |
Note: Alcohol use: Model X2=106.9, df=43, p<0.001.
Rule breaking behaviors: Model X2=94.8, df=43, p<0.001, R2=0.30.
Aggressive behaviors: Model X2=92.6, df=43, p<0.001, R2=0.25.
p<0.05.
All models adjusted for adolescent’s age, gender, nativity status, and family income.
Rule breaking behavior
Family functioning was inversely and significantly related to rule breaking behavior in the univariate model (β = − 1.41, p <0.001). After entering peer alcohol use in the model, both family functioning (β = −1.28, p<0.001) and peer alcohol use (β =3.07, p<0.001) were significantly related to rule breaking behaviors. Once school bonding was entered in the model, family functioning (β = −0.99, p <0.001), peer alcohol use (β =2.85, p<.001), and school bonding (β = −0.19, p=0.004) were significantly related to rule breaking behaviors. Finally, poor alcohol attitudes (β = 2.32, p<0.001), family functioning (β = −0.77, p=0.003), peer alcohol use (β = 2.05, p=0.002), and school bonding (β = −0.16, p = 0.011) were significantly related to rule breaking behaviors. The final model accounted for 30% of the variance (Model X2=94.8, df=43, p<0.001, R2=0.30).
Aggressive behavior
Family functioning was significantly related to aggressive behaviors in the univariate model (β = −1.76, p <0.001). After entering peer alcohol use, family functioning (β = −1.59, p<0.001) and peer alcohol use (β =2.67, p=.001) were significantly related to aggressive behaviors. Once school bonding was entered in the model, family functioning (β = −1.24, p <0.001), peer alcohol use (β = 2.39, p=0.002), and school bonding (β = −0.23, p=0.002) were significantly related to aggressive behaviors. Finally, poor alcohol attitudes (β = 1.52, p=0.001), family functioning (β = −1.08, p=0.001), peer alcohol use (β = 1.87, p=0.016), and school bonding (β = −0.21, p = 0.003) were significantly related to aggressive behaviors. The final model accounted for 25% of the variance (Model X2=92.6, df=43, p<0.001, R2=0.25).
Post hoc Analysis
A post hoc analysis was conducted to examine whether and the extent to which the effect of each predictor variable on each outcome varied by gender. The interaction terms were created by ‘multiplying gender with the family functioning latent variable and the observed predictors (peer alcohol use, school bonding and alcohol use attitudes). The interaction with the family functioning latent variable was created using Mplus, which can define an interaction between a continuous latent variable (i.e., family functioning) and an observed variable (i.e., gender). If a significant interaction was observed, which suggests the effect of predictor on outcome vary by gender, we further conducted multiple group regression analysis by gender. In multiple group analysis, the path coefficients from predictor to outcome were freely estimated across gender if the interaction was significant, whereas for those predictors whose interaction was not significant, regression path coefficients were constrained to be equal.
We observed a significant family functioning by gender interaction when predicting aggressive behavior (β = −1.32, p=0.034) (Table 3). Multi-group regression analyses found family functioning was a significant predictor of aggressive behaviors for girls (β = −1.76, p= 0.001), but not for boys (β = −0.57, p= 0.121) (Fig. 1). The alcohol attitudes by gender interaction was significant when predicting rule-breaking behaviors (β =1.93, p= 0.022). We found alcohol attitudes was a stronger predictor of rule-breaking behaviors for girls (β =3.74, p<0.001) than for boys (β =1.79, p<0.001)1 (Fig. 2).
Table 3.
Rule Breaking Behaviors | Aggressive Behaviors | |||
---|---|---|---|---|
Boys | Girls | Boys | Girls | |
Family Functioning | −0.78* | −0.78* | −0.57 | −1.76* |
Peer Alcohol Use | 1.88* | 1.88* | 2.06* | 2.06* |
School Bonding | −0.16* | −0.16* | −0.23* | −0.23* |
Alcohol Attitudes | 1.79* | 3.74* | 1.51* | 1.51* |
Note: Some path coefficients were constrained to be equal across gender because no significant interactions by gender were found.
p<0.05.
All models adjusted for adolescent’s age, nativity status, and family income.
DISCUSSION
The purpose of this study was to examine the role of attitudes, family, peer and school risk factors on alcohol use, rule breaking and aggressive behaviors among Hispanic delinquent youth. In addition, we sought to examine whether and the extent to which gender moderated any such effects. To date, few studies have examined factors associated with alcohol use, rule breaking and aggressive behaviors among Hispanic delinquent youth from an ecodevelopmental framework [17].
Findings from the present study identified ecodevelopmental [17, 19, 35] risk factors operating in the lives of Hispanic delinquent youth. One interesting finding from the present study is that family functioning was a significant predictor of past 90 day alcohol use in univariate analysis, however was non-significant in multivariate analysis. There are two possible explanations for this. It is possible that family functioning could mediate the effects of peer alcohol use on past 90 day alcohol use [36]. Thus, future research could test the mediation effects of family functioning on past 90 day alcohol use. In addition, it is also possible that there is a shared variance between both family functioning and peer alcohol use. Multivariate analysis suggest that poor alcohol attitudes and peer alcohol use were significant predictors of past 90-day alcohol use among Hispanic delinquent adolescents. These findings confirm previous research indicating that both peer alcohol use [37] and negative attitudes [38] towards alcohol are risk factors for alcohol use among Hispanic adolescents. These findings also extend previous findings in that a dearth of research exists which examine these risk factors in a sample of Hispanic delinquent youth [39].
Another important observation from this study is that at each sequential step, poor alcohol attitudes, peer alcohol use, family functioning and school bonding were all significant predictors of both rule-breaking and aggressive behaviors. These findings confirm previous research indicating that problem behaviors, including rule breaking and aggressive behaviors, may best be understood in the context of multiple and interrelated ecological determinants [19, 40]. These findings suggest the need for the development of interventions aimed at targeting multiple domains operating in the lives of Hispanic delinquent youth to further prevent/reduce problem behaviors [41]. Future research should explore additional risk factors (e.g., parental mental health) located in ecological domains (e.g., family) in the lives of Hispanic delinquent adolescents [39].
Previous research has indicated that family functioning is a stronger predictor for alcohol use in girls but not among boys [42]. In post hoc analyses, however, we did not find a significant interaction between family functioning and gender when predicting past 90 day alcohol use (i.e., p=.056). In addition, previous studies indicate that the effect of family functioning on aggressive behaviors is universal across gender [43]. These studies are limited, however, in that the samples consisted of non-delinquent and non-Hispanic adolescents. In addition, post hoc analysis indicated that family functioning was a significant protective factor for girls, but not for boys. One possible explanation for this finding is that family functioning may be more central and salient in the lives of Hispanic girls, whereas Hispanic boys may be more influenced by other systems (e.g., peer). Further research is needed to better ascertain gender differences in relation to family functioning and alcohol use and aggressive behaviors among Hispanic delinquent youth.
LIMITATIONS AND CONCLUSIONS
It is also important to note the limitations of this study. First, this study used a cross sectional design. Longitudinal studies are needed to further examine ecodevelopmental risk factors on alcohol use, aggression and rule breaking behaviors. Second, all measures collected were self report. This may be of particular concern with respect to perceived peer alcohol use as participants may over report behaviors, particularly among those youth who report alcohol use [44]. A third limitation of the study is failure to include peer violence as a potential confounding variable. A growing body of literature has demonstrated the effects of peer violence on adolescent problem behaviors, including alcohol use [45]. Future studies, therefore, should include peer violence as a potential confounding variable. Finally, given that this sample consisted of Hispanic delinquent youth, the findings from this study may not generalize to the Hispanic youth general population.
Nonetheless, the study findings identify ecodevelopmental risk factors associated with alcohol use, rule breaking and aggressive behaviors in a sample of Hispanic delinquent youth, an understudied population in prevention research. Thus, the present study provides possible targets for interventions to prevent/reduce alcohol use, rule breaking and aggressive behaviors among Hispanic delinquent adolescents.
Acknowledgments
This grant was supported by National Institute on Drug Abuse grants # R01 DA025894 and #3R01DA025192-02S1 awarded to Guillermo Prado.
Footnotes
Family functioning measurement model was first tested for measurement invariance between boys and girls. The results suggested measurement invariance across gender with respect to factor loadings and the intercepts (Δχ2(8)= 2.67, p=.95).
This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
CONFLICT OF INTEREST
None declared.
References
- 1.National Institute on Alcohol Abuse and Alcoholism [NIAAA] Statistical snapshot of underage drinking. 2011 March;:230. [Date of Access: [2011 Mar 23] [cited 2010]; Available from: http://www.niaaa.nih.gov/AboutNIAAA/NIAAASponsoredPrograms/Documents/StatisticalSnapshotofUNderageDrinking.pdf.
- 2.Centers for Disease Control and Prevention [CDC-P] MMWR CDC Surveill Summ. Vol. 59. 2010. Youth risk behavior surveillance — United States, 2009; pp. SS–5. [PubMed] [Google Scholar]
- 3.Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the future-national survey results on drug use, 1975–2009 Volume I: Secondary school students. Bethesda, MD: Department of Health, and Human Services; 2010. [Google Scholar]
- 4.Walton MA, Cunningham RM, Goldstein AL, et al. Rates and correlates of violent behaviors among adolescents treated in an urban emergency department. J Adolesc Health. 2009;45(1):77–83. doi: 10.1016/j.jadohealth.2008.12.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Spoth R, Greenberg M, Turrisi R. Preventive interventions addressing underage drinking: state of the evidence and steps toward public health impact. Pediatrics. 2008;121:S311–36. doi: 10.1542/peds.2007-2243E. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Komro KA, Toomey TL. Strategies to prevent underage drinking. Alcohol Res Health. 2002;26(1):5. [PMC free article] [PubMed] [Google Scholar]
- 7.Eklund JM, af Klinteberg B. Alcohol use and patterns of delinquent behaviour in male and female adolescents. Alcohol Alcohol. 2009;44(6):607–14. doi: 10.1093/alcalc/agn107. [DOI] [PubMed] [Google Scholar]
- 8.Peleg-Oren N, Saint-Jean G, Cardenas GA, Tammara H, Pierre C. Drinking alcohol before age 13 and negative outcomes in late adolescence. Alcohol Clin Exp Res. 2009;33(11):1966–72. doi: 10.1111/j.1530-0277.2009.01035.x. [DOI] [PubMed] [Google Scholar]
- 9.French MT, Maclean JC. Underage alcohol use, delinquency, and criminal activity. Health Econ. 2006;15(12):1261–81. doi: 10.1002/hec.1126. [DOI] [PubMed] [Google Scholar]
- 10.Mulia N, Ye Y, Greenfield TK, Zemore SE. Disparities in alcohol-related problems among white, black, and Hispanic Americans. Alcohol Clin Exp Res. 2009;33(4):654–62. doi: 10.1111/j.1530-0277.2008.00880.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Caetano R. Alcohol-related health disparities and treatment-related epidemiological findings among whites, blacks, and Hispanics in the United States. Alcohol Clin Exp Res. 2003;27(8):1337–9. doi: 10.1097/01.ALC.0000080342.05229.86. [DOI] [PubMed] [Google Scholar]
- 12.Maldonado-Molina M, Jennings W, Komro K. Effects of alcohol on trajectories of physical aggression among urban youth: an application of latent trajectory modeling. J Youth Adolesc. 2010;39(9):1012–26. doi: 10.1007/s10964-009-9484-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Romero EG, Teplin LA, McClelland GM, Abram KM, Welty LJ, Washburn JJ. A longitudinal study of the prevalence, development, and persistence of HIV/sexually transmitted infection risk behaviors in delinquent youth: implications for health care in the community. Pediatrics. 2007;119(5):e1126–41. doi: 10.1542/peds.2006-0128. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.D’Amico EJ, Edelen MO, Miles JNV, Morral AR. The longitudinal association between substance use and delinquency among high-risk youth. Drug Alcohol Depend. 2008;93(1–2):85–92. doi: 10.1016/j.drugalcdep.2007.09.006. [DOI] [PubMed] [Google Scholar]
- 15.Vazsonyi AT, Chen P. Entry risk into the juvenile justice system: African American, American Indian, Asian American, European American, and Hispanic children and adolescents. J Child Psychol Psychiatr. 2010;51(6):668–78. doi: 10.1111/j.1469-7610.2010.02231.x. [DOI] [PubMed] [Google Scholar]
- 16.Lynne-Landsman S, Graber J, Nichols T, Botvin G. Is sensation seeking a stable trait or does it change over time? J Youth Adolesc. 2011;40(1):48–58. doi: 10.1007/s10964-010-9529-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Szapocznik J, Coatsworth JD. An ecodevelopmental framework for organizing the influences on drug abuse: a developmental model of risk and protection. Drug abuse: origins & interventions. In: Glantz MD, Hartel CR, editors. Am Psychol Assoc. 1999. pp. 331–66. [Google Scholar]
- 18.Hawkins JD, Catalano RF, Miller JY. Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychol Bull. 1992;112(1):64–105. doi: 10.1037/0033-2909.112.1.64. [DOI] [PubMed] [Google Scholar]
- 19.Prado G, Shi H, Maldonado-Molina M, et al. An empirical test of ecodevelopmental theory in predicting hiv risk behaviors among hispanic youth. Health Educ Behav. 2010;37(1):97–114. doi: 10.1177/1090198109349218. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Pantin H, Coatsworth JD, Feaster DJ, et al. Familias Unidas: The efficacy of an intervention to promote parental investment in Hispanic immigrant families. Prev Sci. 2003;4(3):189–201. doi: 10.1023/a:1024601906942. [DOI] [PubMed] [Google Scholar]
- 21.Bronfenbrenner U. Ecology of the family as a context for human development: Research perspectives. Dev Psychol. 1986;22(6):723–42. [Google Scholar]
- 22.Griffin KW, Botvin GJ, Scheier LM, Diaz T, Miller NL. Parenting practices as predictors of substance use, delinquency, and aggression among urban minority youth: Moderating effects of family structure and gender. Psychol Addict Behav. 2000;14(2):174–84. doi: 10.1037//0893-164x.14.2.174. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.van Lier PA, Vitaro F, Wanner B, Vuijk P, Crijnen AA. Gender differences in developmental links among antisocial behavior, friends’ antisocial behavior, and peer rejection in childhood: results from two cultures. Child Dev. 2005;76(4):841–55. doi: 10.1111/j.1467-8624.2005.00881.x. [DOI] [PubMed] [Google Scholar]
- 24.Dakof GA. Understanding gender differences in adolescent drug abuse: issues of comorbidity and family functioning. J Psychoactive Drugs. 2000;32(1):25–32. doi: 10.1080/02791072.2000.10400209. [DOI] [PubMed] [Google Scholar]
- 25.Turner CF, Ku L, Rogers SM, Lindberg LD, Pleck JH, Sonenstein FL. Adolescent sexual behavior, drug use, and violence: increased reporting with computer survey technology. Science. 1998;280(5365):867–73. doi: 10.1126/science.280.5365.867. [DOI] [PubMed] [Google Scholar]
- 26.Sambrano S, Springer JF, Hermann J. Informing the next generation of prevention programs: CSAP’s cross-site evaluation of the 1994–1995 high-risk youth grantees. J Community Psychol. 1997;25(5):375–95. [Google Scholar]
- 27.Achenbach TM, Dumenci L, Rescorla LA. Ten-year comparisons of problems and competencies for national samples of youth: self, parent, and teacher reports. J Emot Behav Disord. 2002;10(4):194–203. [Google Scholar]
- 28.Gorman-Smith D, Tolan PH, Zelli A, Huesmann LR. The relation of family functioning to violence among inner-city minority youths. J Fam Psychol. 1996;10(2):115–29. [Google Scholar]
- 29.Tolan PH, Gorman-Smith D, Huesmann LR, Zelli A. Assessment of family relationship characteristics: a measure to explain risk for antisocial behavior and depression among urban youth. Psychol Assess. 1997;9(3):212–23. [Google Scholar]
- 30.Barnes HL, Olson DH. Parent--Adolescent communication and the circumplex model. Child Dev. 1985;56(2):438–47. [Google Scholar]
- 31.Pantin H. Scale of parent relationship with peers. University of Miami; 1996. (unpublished manuscript) [Google Scholar]
- 32.Cook E, Greenberg M, Kusche C. The relations between emotional understanding, intellectual functioning, and disruptive behavior problems in elementary-school-aged children. J Abnorm Child Psychol. 1994;22(2):205–19. doi: 10.1007/BF02167900. [DOI] [PubMed] [Google Scholar]
- 33.Byrne BM. Structural equation modeling with AMOS, EQS, and LISREL: comparative approaches to testing for the factorial validity of a measuring instrument. Int J Test. 2001;1(1):55–86. [Google Scholar]
- 34.Muthen LK, Muthen BO. Mplus: Statistical analysiswith latent variables: User’s guide. Los Angelos: Authors; 1998–2010. [Google Scholar]
- 35.Pantin H, Schwartz SJ, Sullivan S, Prado G, Szapocznik J. Ecodevelopmental HIV prevention programs for Hispanic adolescents. Am J Orthopsychiatry. 2004;74(4):545–58. doi: 10.1037/0002-9432.74.4.545. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–82. doi: 10.1037//0022-3514.51.6.1173. [DOI] [PubMed] [Google Scholar]
- 37.Lopez B, Schwartz SJ, Prado G, et al. Correlates of early alcohol and drug use in hispanic adolescents: examining the role of ADHD with comorbid conduct disorder. Family, School, and Peers. J Clin Child Adolesc Psychol. 2008;37(4):820–32. doi: 10.1080/15374410802359676. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Kam J, Matsunaga M, Hecht M, Ndiaye K. Extending the theory of planned behavior to predict alcohol, tobacco, and marijuana use among youth of mexican heritage. Prev Sci. 2009;10(1):41–53. doi: 10.1007/s11121-008-0110-0. [DOI] [PubMed] [Google Scholar]
- 39.Jennings W, Maldonado-Molina M, Piquero A, Canino G. Parental suicidality as a risk factor for delinquency among Hispanic youth. J Youth Adolesc. 2010;39(3):315–25. doi: 10.1007/s10964-009-9439-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Ferguson CJ, San Miguel C, Hartley RD. A multivariate analysis of youth violence and aggression: the influence of family, peers, depression, and media violence. J Pediatr. 2009;155(6):904–8.e3. doi: 10.1016/j.jpeds.2009.06.021. [DOI] [PubMed] [Google Scholar]
- 41.Santisteban DA, Coatsworth JD, Perez-Vidal A, et al. Efficacy of brief strategic family therapy in modifying Hispanic adolescent behavior problems and substance use. J Fam Psychol. 2003;17(1):121–33. doi: 10.1037/0893-3200.17.1.121. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Yeh M-Y, Chiang IC, Huang S-Y. Gender differences in predictors of drinking behavior in adolescents. Addict Behav. 2006;31(10):1929–38. doi: 10.1016/j.addbeh.2005.12.019. [DOI] [PubMed] [Google Scholar]
- 43.Eichelsheim VI, Buist KL, Dekovic M, et al. Associations among the parent-adolescent relationship, aggression and delinquency in different ethnic groups: a replication across two Dutch samples. Soc Psychiatry Psychiatr Epidemiol. 2010;45(3):293–300. doi: 10.1007/s00127-009-0071-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Ennett ST, Bauman KE, Foshee VA, Pemberton M, Hicks KA. Parent-Child communication about adolescent tobacco and alcohol use: what do parents say and does it affect youth behavior? J Marriage Fam. 2001;63(1):48–62. [Google Scholar]
- 45.Swahn MH, Bossarte RM, Sullivent EE. Age of alcohol use initiation, suicidal behavior, and peer and dating violence victimization and perpetration among high-risk, seventh-grade adolescents. Pediatrics. 2008;121(2):297–305. doi: 10.1542/peds.2006-2348. [DOI] [PubMed] [Google Scholar]