|Year : 2017 | Volume
| Issue : 2 | Page : 36-41
Alcohol abuse in Iranian adolescents: A mediational model of parental monitoring and affiliation with deviant peers
Sajad Aminimanesh1, Javad Khodadadi Sangdeh2, Khodabakhsh Ahmadi3, Alimohammad Nazari2, Mostafa Khanzade4
1 Department of Psychology, Shiraz Branch, Islamic Azad University, Shiraz, Iran
2 Department of Counseling, Faculty of Psychology and Educational Science, Kharazmi University, Tehran, Iran
3 Behavioral Sciences Research Center, Baqiatallah University of Medical Sciences, Tehran, Iran
4 Department of Psychology, Faculty of Psychology and Educational Science, Shahid Chamran University, Ahwaz, Iran
|Date of Web Publication||6-Oct-2017|
Department of Psychology, Shiraz Branch, Islamic Azad University, Shiraz
Source of Support: None, Conflict of Interest: None
Aims: This study aimed to determine the attitudes toward alcohol abuse among students in Tehran and to develop and test a model of the relationships among parental monitoring and affiliation with deviant peers as they predict youth alcohol abuse. Materials and Methods: In this cross-sectional study, 1266 adolescents were recruited from high schools in Tehran and three scales of alcohol abuse, parental monitoring, and adolescent affiliation with deviant peers were completed for them. Data were analyzed using independent sample t-test, Pearson correlation coefficient, and structural equations modeling. Results: The results of this study indicated that 7.4% of individuals had a positive attitude toward alcohol abuse. The percentage of positive attitude among males was nearly 2 times more than females. The study model was confirmed and explained 0.42 of attitudes toward alcohol abuse variance. Moreover, affiliation with deviant peers had a mediating role in the relationship between Parental Monitoring and attitude toward alcohol abuse. Conclusion: According to the results, parental monitoring and affiliation with deviant peers could explain the alcohol abuse among adolescents. Therefore, it is suggested to include these factors in prevention programs aimed at reducing alcohol abuse.
Keywords: Adolescence, alcohol abuse, deviant peers, parental monitoring
|How to cite this article:|
Aminimanesh S, Sangdeh JK, Ahmadi K, Nazari A, Khanzade M. Alcohol abuse in Iranian adolescents: A mediational model of parental monitoring and affiliation with deviant peers. Int Arch Health Sci 2017;4:36-41
|How to cite this URL:|
Aminimanesh S, Sangdeh JK, Ahmadi K, Nazari A, Khanzade M. Alcohol abuse in Iranian adolescents: A mediational model of parental monitoring and affiliation with deviant peers. Int Arch Health Sci [serial online] 2017 [cited 2019 Nov 16];4:36-41. Available from: http://www.iahs.kaums.ac.ir/text.asp?2017/4/2/36/216136
| Introduction|| |
Most of the researches that have been done on youth subject, suggest that risk-taking is part of the developmental features of adolescents. Since young people tend to be egocentric and misapprehend their behavior, the youth period is thought to be an important phase for starting high-risk behaviors  and these behaviors may end to unpleasant consequences.
Based on previous researches, rates of various high-risk behaviors such as smoking and alcohol use, substance abuse, physical aggression, risky driving, and unprotected sexual relationships  are increasing among adolescents. Moreover, children's participation in risky behaviors has become one of the most important sources of concern for parents.
After drug abuse, alcohol consumption has the most awful results for adolescents among other high-risk behaviors. It has been proved that people who initiate alcohol and drug use in adolescence will suffer the side effects on their somatic and mental health status in adulthood., Alcohol consumption in adolescence can cause some major problems such as road traffic deaths,, depressive disorders,, relational problems and poor performance at school, and also their engagement in other high-risk behaviors such as sexual risk taking, smoking, and cannabis use.
In general, the results of some epidemiologic studies have shown considerable rates of alcohol consumption in adolescents. The Center on Addiction and Substance Abuse in the United States reported that nearly three of four high school students in America have drunk alcohol. Moreover, 74% of American high school students in Fisher et al. survey  report having had a whole drink of alcohol and 43% report drinking within the past 30 days. Furthermore, previous researches have shown that 9.8% to 25.7% Iranian adolescents have used alcohol during their life time., Moreover, boys engage more than girls in high-risk behaviors such as drinking alcohol.,,, Considering these rates, it is vital to regard adolescents' alcohol abuse.
Older adolescents reported higher tendency for alcohol abuse., Studies showed that in mid adolescence, people tend to drink more for adaptation with risk factors of alcohol drinking. The theories that focus on dominant sociability have proved that principal resources such as family, school and peers play a major role in normal and abnormal behavior acquisition.
It has been proved that parental monitoring has the major role in preventing early development and maintenance of high-risk behaviors in children and adolescents.
Among family process variables, parental monitoring has been identified in the literature as one of the proximal determinants of early development and maintenance of antisocial and high-risk behaviors in children and adolescents.
Parental monitoring means that parents be aware of their child's friends and the places that he or she spends time. They also have to do behaviors involving attention to and tracking of the locations and activities of the adolescents. In researches, parental monitoring is usually defined as parents' knowledge or adolescents' perceptions of their parents' knowledge of the child's activities and friends. It has been well documented that poor parental monitoring is related to adolescents' alcohol risk taking.,,,
Young adulthood is a period in which the child develops a relationship with peers and enters social context and new activities. To fulfill intimacy needs, adolescents tend to spend their time out of the home with friends. Brendgen et al. considered parental monitoring as an important factor in adolescents' participation in high-risk behaviors and affiliation with deviant peers.
Affiliation with deviant peers means relationship with adolescents who are committing risky behaviors such as weapon carrying, offending others, and drug abuse. Considering social learning theory, affiliation with deviant peers can cause problem behaviors in adolescents. Recent research has shown that those adolescents who had a relationship with deviant peers tend to engage in a variety of alcohol risk behaviors.,,,,,
Those adolescents, who are monitored poorly, are more likely to participate in risky behaviors  and affiliate with deviant peers.
Problem behavior theory and other available models on high-risk behaviors suggest that peer affiliation mediates the relationship between parental monitoring and adolescent problem behaviors.
In other words, parental monitoring can cause high-risk behaviors through affiliation with deviant peers.,, However, previous studies failed to consider the effectiveness of parental monitoring and affiliation with deviant peers on alcohol abuse in adolescents. This study was aimed to determine the attitude toward alcohol consumption among students in Tehran and to develop and also to test a model of the relationships among parental monitoring and affiliation with deviant peers as they predict youth attitude toward alcohol use.
| Materials and Methods|| |
The study was a part of the Survey Project on Alcohol abuse and other high-risk behaviors among adolescents. A cross-sectional study was carried out among a sample of 1266 adolescents (737 girls and 529 boys), were recruited from high schools in Tehran, Iran. The Inclusion criteria were as followings: age limitation from 14 to 18 and residency in Tehran. Participants were selected through cluster sampling method. In the first step of sampling, Tehran was divided into 5 regions (north, west, center, east, and south). Then, some districts were randomly chosen from each of these regions. Subsequently, using the list of high schools located in these district, the sample was selected. All participants were informed about the goals of the survey and completed individually administered questionnaires with regular supervision to provide reliable and valid data. The following instrumentations were applied to collect data.
Alcohol abuse scale
The alcohol abuse scale (AAS) is a 4-item self-report scale which assesses the adolescents' attitudes to alcohol abuse. Because of cultural limitations, there was not any feasibility to assess alcohol use record directly. Zadeh-Mohammadi et al. confirmed the validity of the scale through exploratory factor analysis. Moreover, originally validated with college students, the AAS has acceptable internal consistency (α = 0.91; 43). In this study, the Cronbach's α of scale was. 83.
Parental monitoring scale
The parental monitoring scale is a 7-item self-report instrument that previously had achieved a Cronbach's α of. 81. Parental monitoring items included questions about adolescent's whereabouts, friends, and activities. The possible responses were “never/unimportant (0)” to “always/very important.” The validity of the Persian version has been confirmed by Alboukordi et al. For this study, Cronbach's α was. 70.
Adolescent affiliation with deviant peers scale
The adolescent affiliation with deviant peers (AADP) scale is an 8-item scale, used to ask adolescents for deviant behaviors committed by their peers, like drug and alcohol use, carrying knife or gun and physical fighting during the past 6 months. The possible responses were “none of them (0)” to “all of them (4).” The total response score was computed for each adolescent, with the higher score indicating more affiliation with deviant peers. The reliability and validity of the Persian version of the scale have been confirmed in Iran. In addition, the Cronbach's α of scale was. 82.
Attitude toward alcohol abuse was computed using descriptive analysis. Moreover, the latent variable analyses were performed using the structural equations modeling which compare a proposed hypothetical model with a set of actual data. The closeness of the hypothetical model to the empirical data was evaluated statistically and presented in [Figure 1].
|Figure 1: The investigated model for the mediating role of adolescent affiliation with deviant peers in the relationship between parental monitoring and alcohol abuse scale|
Click here to view
| Results|| |
Adolescents' attitude toward alcohol abuse
According to the AAS, 7.4% of all individuals were at high risk in terms of alcohol abuse. The percent of positive attitude among males was nearly 2 times more than the attitude among females (10.39% vs. 5.29%, χ2 = 23.570, P < 0.001).
Sociodemographic variables analysis
The participants were 529 male and 737 female adolescents. The participants mean and standard deviation (SD) of age were 16.07 and 1.04 years for males and 16.04 and 1.22 for females, respectively. All participants were high school students and 4.5% of them reported distress in the structure of their families. The results of independent sample t-test for study variables are shown in [Table 1]. These findings showed that males and females were significantly different in scores of AAS (P < 0.001), parental monitoring (P < 0.001), and affiliation with deviant peers (P < 0.001).
[Table 2] shows the mean and SD of study variables and their correlations. As the table shows, there is a positive and significant relationship between AAS and AADP while PM in negatively correlated with AAS and AADP.
|Table 2: Mean and standard deviation of the study's variables and their correlations (latent variables)|
Click here to view
To investigate the proposed model based on the mediating role of AADP in PM and AAS relationship, our findings confirmed the model. Considering the obtained error index, this model explains 42% of AAS variance.
Confirming the mediating role of AADP, the model goodness of fit was investigated using Chi-square test and adjusted goodness of fit index (AGFI). The AGFI equaled 0.98. The insignificant Chi-square showed model goodness of fit. [Table 3] shows all of the investigated goodness of fit indices (GFIs).
Schreiber et al. argue that the model has goodness of fit if and only if the indices of NFI, nonnormed fit index, comparative fit index, GFI, and AGFI exceed 95%, the root mean square residual index is near to zero and SRMR and root mean square error of approximation indices are smaller than 0.80% and 0.60%, respectively. Therefore, Considering Schreiber et al., the current model benefits from goodness of fit.
[Figure 1] shows the results of investigated structural equation model. Regarding this model, PM has a significant effect on AAS through AADP. The direct and indirect effectiveness of PM on AAS were −0.42 and −0.094, respectively. Moreover, AADP effectiveness on AAS was 0.21.
Finally, to investigate significant of the indirect effect of PM on AAS through AADP used bootstrapping method by macro. This result is shown in [Table 4].
As shown [Table 3], both of lower and upper bound in bootstrap results are negative. Therefore, these results show that indirect effect in this model is significant and then the relationship between PM and AAS mediate by AADP.
| Discussion|| |
The purpose of this study is to investigate the attitudes toward alcohol abuse among students and the role of parental monitoring and affiliation with deviant peers in predicting alcohol abuse. According to the findings of this research, 7.4% of the adolescents were at high risk in terms of alcohol abuse. This can be due to factors such as psychosocial characteristics of the adolescents  and peers' influences. Moreover, drug and alcohol abuse can be used by teenagers to cope with their stress. This study, which is consistent with Kelly et al., Kristjansson et al., and Mohammadkhani, also showed that alcohol abuse was more frequent among boys compared to the girls.,, Explaining the results, factors such as gender roles, different expectations from girls, and parents' extra monitoring  should be considered.
Our results are similar to those of Brendgen, Vitaro, and Bukowski, Paschall et al., and Meldrum et al. as they showed that affiliation with deviant peers could predict the high-risk behaviors. Consistent with previous research, spending time with deviant peers has a direct effect on both high-risk behaviors and parental monitoring., The results also support the idea that relationship with deviant peers is as an important factor in the development of high-risk behaviors in adolescents as it was suggested in the social learning theory.
This study showed that parental monitoring was a major factor in adolescents' alcohol abuse directly and also through affiliation with deviant peers. Previous research suggested that parental monitoring is an important deterrent of alcohol abuse,,, hence, this study supported this prediction. Consistent with Brendgen et al., parental monitoring could indirectly predict affiliation with deviant peers. Dishion et al. demonstrated that lacking parental monitoring can foster adolescents' affiliation with deviants by providing children with the opportunity to meet with them. In sum, we found that parental monitoring and affiliation with deviant peers were significant predictors of attitude toward alcohol abuse; furthermore, parental monitoring indirectly influences attitudes through affiliation with deviants.
Regarding the results of the present study, the theoretical model proposed by Paschal et al. is confirmed. In line with the previous research, it can be concluded that parental monitoring effectiveness on alcohol abuse is mediated through affiliation with peers.,,
Limitations of this study are worthy of discussion. Considering cultural limitations, we investigate alcohol consumption indirectly, which can affect the results of this study. Another limitation of this study is that measurement of research variables was based on participants' self-report, and there was no independent method for testing the validity of their responses. Furthermore, this study was carried out in Tehran, and its result should be generalized with caution. Future studies would probably benefit from using interview and observational research data to help researchers understand the connections of adolescent alcohol abuse and its connected variables in greater depth.
| Conclusion|| |
Generally speaking, results of this study show that parental monitoring and affiliation with deviant peers had largely explained the attitude toward alcohol abuse among adolescents. Therefore, prevention efforts aimed at reducing risky alcohol drinking should be composed of these factors. In fact, the results suggested that prevention efforts beginning earlier (i.e., at the start of high school) may be warranted.
This research was supported by the Behavioral Sciences Research Center, Baqiatallah University of Medical Sciences. The authors would like to thank the participating students as well as the research assistants for assisting with data collection.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Kloep M, Güney N, Cok F, Simsek OF. Motives for risk-taking in adolescence: A cross-cultural study. J Adolesc 2009;32:135-51.
Boyer TW. The development of risk-taking: A multi-perspective review. Dev Rev 2006;26:291-345.
Carr-Gregg MR, Enderby KC, Grover SR. Risk-taking behaviour of young women in Australia: Screening for health-risk behaviours. Med J Aust 2003;178:601-4.
Engels RC, Scholte RH, van Lieshout CF, de Kemp R, Overbeek G. Peer group reputation and smoking and alcohol consumption in early adolescence. Addict Behav 2006;31:440-9.
Nargiso JE, Becker SJ, Wolff JC, Uhl KM, Simon V, Spirito A, et al.
Psychological, peer, and family influences on smoking among an adolescent psychiatric sample. J Subst Abuse Treat 2012;42:310-8.
Fallu JS, Janosz M, Brière FN, Descheneaux A, Vitaro F, Tremblay RE, et al.
Preventing disruptive boys from becoming heavy substance users during adolescence: A longitudinal study of familial and peer-related protective factors. Addict Behav 2010;35:1074-82.
Tomas Dols S, Alvarez González FJ, Llorens Aleixandre N, Vidal-Infer A, Torrijo Rodrigo MJ, Valderrama-Zurián JC. Predictors of driving after alcohol and drug use among adolescents in Valencia (Spain). Accid Anal Prev 2010;42:2024-9.
Dittus PJ, Jaccard J. Adolescents' perceptions of maternal disapproval of sex: Relationship to sexual outcomes. J Adolesc Health 2000;26:268-78.
Rai AA, Stanton B, Wu Y, Li X, Galbraith J, Cottrell L, et al.
Relative influences of perceived parental monitoring and perceived peer involvement on adolescent risk behaviors: An analysis of six cross-sectional data sets. J Adolesc Health 2003;33:108-18.
Fraga S, Sousa S, Ramos E, Dias S, Barros H. Alcohol use among 13-year-old adolescents: Associated factors and perceptions. Public Health 2011;125:448-56.
Koposov RA, Ruchkin VV, Eisemann M, Sidorov PI. Alcohol abuse in Russian delinquent adolescents. Associations with comorbid psychopathology, personality and parenting. Eur Child Adolesc Psychiatry 2005;14:254-61.
Schinke SP, Schwinn TM, Fang L. Longitudinal outcomes of an alcohol abuse prevention program for urban adolescents. J Adolesc Health 2010;46:451-7.
Zhang X, Yao H, Hu G, Cui M, Gu Y, Xiang H, et al.
Basic characteristics of road traffic deaths in China. Iran J Public Health 2013;42:7-15.
Clark DB, De Bellis MD, Lynch KG, Cornelius JR, Martin CS. Physical and sexual abuse, depression and alcohol use disorders in adolescents: Onsets and outcomes. Drug Alcohol Depend 2003;69:51-60.
Mattisson C, Bogren M, Horstmann V, Tambs K, Munk-Jörgensen P, Nettelbladt P. Risk factors for depressive disorders in the Lundby cohort – A 50 year prospective clinical follow-up. J Affect Disord 2009;113:203-15.
Santelli JS, Robin L, Brener ND, Lowry R. Timing of alcohol and other drug use and sexual risk behaviors among unmarried adolescents and young adults. Fam Plann Perspect 2001;33:200-5.
Mohammadpoorasl A, Nedjat S, Fakhari A, Yazdani K, Foroushani AR, Fotouhi A, et al.
Substance abuse in high school students in association with socio-demographic variables in Northwest of Iran. Iran J Public Health 2012;41:40-6.
Terzic Supic Z, Santric Milicevic M, Sbutega I, Vasic V. The importance of family relations for cannabis users: The case of Serbian adolescents. Iran J Public Health 2013;42:249-60.
The National Center on Addiction and Substance Abuse (CASA) at Columbia University. CASA analysis of the Youth Risk Behavior Survey (YRBS). Atlanta: U.S. Department of Health and Human Services, National Center for Chronic Disease Prevention and Health Promotion; 2011.
Fisher LB, Miles IW, Austin SB, Camargo CA Jr., Colditz GA. Predictors of initiation of alcohol use among US adolescents: Findings from a prospective cohort study. Arch Pediatr Adolesc Med 2007;161:959-66.
Mohammadkhani S. Prevalence of cigarette smoking, alcohol drinking and illegal drugs use among Iranian adolescents. J Kerman Univ Med Sci 2012;19:32-48.
Hamdieh M, Motalebi N, Asheri H, Boroujerdi A. Prevalence of alcohol and drug abuse in young people, 15-35 year old, living in Tehran, Iran. Res Med 2008;32:315-9.
Kristjansson AL, Sigfusdottir ID, James JE, Allegrante JP, Helgason AR. Perceived parental reactions and peer respect as predictors of adolescent cigarette smoking and alcohol use. Addict Behav 2010;35:256-9.
Kelly AB, Chan GC, Toumbourou JW, O'Flaherty M, Homel R, Patton GC, et al.
Very young adolescents and alcohol: Evidence of a unique susceptibility to peer alcohol use. Addict Behav 2012;37:414-9.
Lopez WD, Krueger PM, Walters ST. High-risk drug use and sexual behaviors among out-of-treatment drug users: An aging and life course perspective. Addict Behav 2010;35:432-7.
Melchior M, Chastang JF, Goldberg P, Fombonne E. High prevalence rates of tobacco, alcohol and drug use in adolescents and young adults in France: Results from the GAZEL Youth study. Addict Behav 2008;33:122-33.
Villanti A, Boulay M, Juon HS. Peer, parent and media influences on adolescent smoking by developmental stage. Addict Behav 2011;36:133-6.
Singer MI, Flannery DJ, Guo S, Miller D, Leibbrandt S. Exposure to violence, parental monitoring, and television viewing as contributors to children's psychological trauma. J Community Psychol 2004;32:489-504.
Romero AJ, Ruiz M. Does familism lead to increased parental monitoring? Protective factors for coping with risky behaviors. J Child Fam Stud 2007;16:143-54.
Fröjd S, Kaltiala-Heino R, Rimpelä M. The association of parental monitoring and family structure with diverse maladjustment outcomes in middle adolescent boys and girls. Nord J Psychiatry 2007;61:296-303.
Beck KH, Boyle JR, Boekeloo BO. Parental monitoring and adolescent alcohol risk in a clinic population. Am J Health Behav 2003;27:108-15.
Chaplin TM, Sinha R, Simmons JA, Healy SM, Mayes LC, Hommer RE, et al.
Parent-adolescent conflict interactions and adolescent alcohol use. Addict Behav 2012;37:605-12.
Freisthler B, Byrnes HF, Gruenewald PJ. Alcohol outlet density, parental monitoring, and adolescent deviance: A multilevel analysis. Child Youth Serv Rev 2009;31:325-30.
Trucco EM, Colder CR, Wieczorek WF. Vulnerability to peer influence: A moderated mediation study of early adolescent alcohol use initiation. Addict Behav 2011;36:729-36.
Engels RC, Ter-Bogt T. Influences of risk behaviors on the quality of peer relations in adolescence. J Youth Adolesc 2001;30:675-95.
Brendgen M, Vitaro F, Bukowski WM. Stability and variability of adolescents' affiliation with delinquent friends: Predictors and consequences. Soc Dev 2000;9:205-25.
Paschall MJ, Ringwalt CL, Flewelling RL. Effects of parenting, father absence, and affiliation with delinquent peers on delinquent behavior among African-American male adolescents. Adolescence 2003;38:15-34.
Meldrum RC, Young JT, Weerman FM. Reconsidering the effect of self-control and delinquent peers: Implications of measurement for theoretical significance. J Res Crime Delinquency 2009;46:353-76.
Fite PJ, Colder CR, O'Connor RM. Childhood behavior problems and peer selection and socialization: Risk for adolescent alcohol use. Addict Behav 2006;31:1454-9.
Nash SG, McQueen A, Bray JH. Pathways to adolescent alcohol use: Family environment, peer influence, and parental expectations. J Adolesc Health 2005;37:19-28.
Westling E, Andrews JA, Hampson SE, Peterson M. Pubertal timing and substance use: The effects of gender, parental monitoring and deviant peers. J Adolesc Health 2008;42:555-63.
Brandt D. Delinquency, Development, and Social Policy. 1st
ed. Connecticut: Yale University Press; 2006.
Zadeh-Mohammadi A, Ahmadabadi Z, Panaghi L, Heidari M. Validity and reliability of iranian youth risk-taking scale. J Psychol 2011;15:129-46.
Alboukordi S, Nazari AM, Nouri R, Khodadadi J. Predictive factors for juvenile delinquency: The role of family structure, parental monitoring and delinquent peers. Int J Criminol Sociol Theory 2012;5:770-7.
Schreiber JB, Stage FK, King J, Nora A, Barlow EA. Reporting structural equation modeling and confirmatory factor analysis results: A review. J Educ Res 2006;99:323-37.
Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods 2008;40:879-91.
Valencia LS, Cromer BA. Sexual activity and other high-risk behaviors in adolescents with chronic illness: A review. J Pediatr Adolesc Gynecol 2000;13:53-64.
Eaton NR, Krueger RF, Johnson W, McGue M, Iacono WG. Parental monitoring, personality, and delinquency: Further support for a reconceptualization of monitoring. J Res Pers 2009;43:49-59.
Dishion TJ, Capaldi DM, Spracklen KM, Li F. Peer ecology of male adolescent drug use. Dev Psychopathol 1995;7:803-24.
[Table 1], [Table 2], [Table 3], [Table 4]