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Identifying Early Risk Factors for Addiction Later in Life: A Review of Prospective Longitudinal Studies
Angelica m morales , phd, scott a jones , phd, dakota kliamovich, gareth harman, bonnie j nagel , phd.
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Corresponding Author: Bonnie J. Nagel, Ph.D., Oregon Health & Science University, Departments of Psychiatry and Behavioral Neuroscience, 3181 SW Sam Jackson Park Road, MC: DC7P Portland, OR 97239, Phone: +1-503-494-4612, [email protected]
Issue date 2020 Mar.
Purpose of Review:
To review prospective longitudinal studies that have identified risk factors for the development of substance use disorders in adulthood from individual differences during childhood and adolescence.
Recent Findings:
Risk factors during childhood and adolescence that have been consistently linked to increased risk for addiction include externalizing and internalizing symptoms, early substance use, and environmental influences, such as parental behavior and exposure to traumatic experiences.
Since the etiology of substance use disorders is complex and likely is attributable to many causal pathways, systematic examination of the associations between risk factors will be necessary to understand the mixed findings in the existing literature, to determine which individuals should be targeted for prevention efforts, and to design interventions that address risk factors that are most likely to improve outcomes.
Keywords: substance use disorders, predictors, developmental, psychiatric, drug use
Introduction
Substance use disorders are associated with many personal and societal costs. For example, alcohol and tobacco use alone were linked to 568,000 preventable deaths in the US every year from 2006–2010 [ 1 , 2 ], and the financial costs of substance use (e.g. health care, crime) are estimated to be around $740 billion per year [ 1 , 3 – 7 ]. Furthermore, treatment for substance use disorders is challenging, with the majority of individuals requiring multiple interventions before achieving stable abstinence [ 8 , 9 ]. One strategy to reduce the negative consequences associated with substance use is to identify risk factors for the development of substance use disorders that can inform prevention efforts. Prospective longitudinal studies have the potential to provide important information about the complex pathways that lead to the development of substance use disorders; unlike cross-sectional studies they can use temporal information to disentangle causes from consequences and are less likely to be biased by temporal delay, as is the case in many retrospective studies relying on self-report.
Although many studies have examined factors that predict quantity of substance use, most people engage in some alcohol and drug use during their lifetime without developing a substance use disorder. For example, it is estimated that 86.4% of Americans drink alcohol in their lifetime, while 68.7% use tobacco products, and 46.9% use marijuana [ 10 ]. However, 30% of adults in the US will suffer from an alcohol use disorder in their lifetime [ 11 ], and the lifetime prevalence of nicotine and other drug use disorders is 27.9% and 9.9%, respectively [ 12 , 13 ]. These data suggest that there is considerable heterogeneity in the personal and environmental factors that impact the likelihood of developing addiction. While the negative consequences associated with substance use vary along a continuum, individuals with a substance use disorder, as opposed those who engage in substance use, are likely at highest risk of experiencing negative consequences. Therefore, this article reviews prospective longitudinal studies that assess individual differences in childhood and adolescence (< 18 years old) with the goal of predicting substance use disorders later in life (> 18 years old). Since meta-analysis improves the power of small or inconclusive studies, if available, we review meta-analyses of prospective longitudinal studies examining risk factors for substance use disorders instead of detailing individual findings. This review examines the evidence suggesting that personal and environmental factors such as psychopathology, personal substance use, parental and peer influence, socioeconomic status, negative life events, and neurobiology impact the likelihood of developing addiction (see Table 1 for a list of the articles included).
Potential Risk Factors During Childhood and Adolescence for Substance Use Disorders in Adulthood
Abbreviations: ↑ = increased risk for; AUD = alcohol use disorder; NUD = nicotine use disorder, CUD = cannabis use disorder, SUD = substance use disorder
denotes meta-analysis
Psychopathology
Psychiatric diagnoses.
Diagnosis of a mental health disorder early in life is one of the most extensively studied predictors of future substance use disorders in adulthood. A recent meta-analytic review found that childhood/adolescent diagnosis of attention-deficit/hyperactivity disorder (ADHD), conduct disorder (CD) or oppositional defiant disorder (ODD), and depression, were associated with an increased risk for adult addiction [ 14•• ]. In this study, ADHD and CD/ODD were associated with increased risk of alcohol, nicotine, other drug use and any substance use disorder, while depression was associated with an increased risk for alcohol, nicotine, and any substance use disorder [ 14 ]. While not significant in the meta-analysis by Groenman and colleagues [ 14 ], anxiety disorders in adolescence have also been associated with adult addiction, but findings are limited. One study found that social anxiety disorder in adolescence was associated with alcohol and cannabis dependence in adulthood [ 15 ], with a stronger effect in women than men [ 16 ]. Below, we review the evidence that externalizing and internalizing symptoms are also risk factors for addiction later in life.
Externalizing Behavior
Using parental and adolescent self-reports, studies have demonstrated that greater levels of externalizing behavior in childhood and adolescence are associated with increased risk for alcohol [ 17 ] and cannabis [ 18 , 19• , 20 ] use disorders, as well as symptoms nicotine use disorder [ 21 ] in adulthood. Furthermore, specific symptoms of CD in early adolescence, in the absence of a clinical diagnosis of CD or ODD, predicted alcohol dependence in young adult males [ 22 ], while greater ODD symptoms in childhood/early-adolescence predicted nicotine, cannabis, and cocaine abuse and/or dependence in young adulthood [ 23 ]. Similarly, in youth without an ADHD diagnosis, two studies have found that greater inattentive symptoms in childhood/early-adolescence predicted alcohol, nicotine, and cannabis abuse/dependence in young adulthood [ 23 , 24 ].
Several studies have also demonstrated associations with more specific externalizing behaviors and addiction in adulthood. Greater misbehavior at school, greater delinquency, deviant behavior, being sexually active, antisocial behavior, and lower perceived consequences of antisocial behavior are all associated with alcohol abuse and dependence in adulthood [ 24 – 27 ]. Similarly, delinquency and aggression in adolescence also predicted cannabis, nicotine, and other drug abuse/dependence in adulthood [ 24 ]. Additionally, novelty seeking in adolescence has also been shown to be predictive of alcohol, nicotine, cannabis, and other illicit substance use disorders in adulthood [ 28 , 29 ]. Lastly, studies using composite scores that include assessments of externalizing symptoms and cognitive functioning during adolescence have shown that neurobehavioral disinhibition is associated with increased risk for substance use disorders in adulthood [ 30 , 31 ].
Internalizing Symptoms
Similar to externalizing behaviors, internalizing symptoms during adolescence have been linked to greater likelihood of addiction in adulthood, but perhaps to a lesser extent. Internalizing and more specifically, depressive symptoms in adolescence have been linked to both alcohol dependence and nicotine dependence later in life [ 32 – 34 ] . The associations between depressive symptoms and future substance use disorders may be related to the presence of other risk factors, as depressive symptoms in adolescent males only predicted alcohol dependence in individuals with CD [ 22 ]. In contrast, some work suggests that internalizing behavior is inversely associated with cannabis use disorders in adulthood [ 19 ].
Personal Substance Use
Several studies have determined that alcohol and drug use before adulthood is a risk factor for the development of substance use disorders later in life. Research has been conducted to examine whether initiating alcohol use at various age-cutoff points is associated with heightened risk for addiction [ 35 ], with one study determining that initiating alcohol use before 11 increased risk for chronicity of adult alcohol dependence [ 36 ]. However, no evidence has been found that later cutoffs are associated with increased risk for alcohol dependence [ 35 , 36 ]. More recent work suggests that age of first intoxication is better predictor of risk for substance use disorder in adulthood, as unlike age of first drink [ 37 ], earlier age of first intoxication is a significant predictor of alcohol use disorder, nicotine, cannabis, and other illicit drug dependence, when controlling for other potential risk factors [ 38 ]. Beyond age of alcohol use initiation, frequency [ 24 ] and heaviness [ 35 , 36 ] of alcohol use during adolescence [ 25 – 27 , 32 , 39 ] has also been linked to increased risk for alcohol and other substance dependence during adulthood.
Although less well-studied than alcohol, similar effects have been observed with other drugs. For example, earlier onset of tobacco use and continued tobacco use during adolescence, were associated with higher risk of developing a cannabis [ 19 , 40 , 41 ], alcohol [ 32 ], and illicit drug use disorders [ 42 , 43 ] in young adulthood. Furthermore, frequency of marijuana use during adolescence was also associated with higher rates of adult alcohol [ 36 ] and cannabis dependence [ 41 ]. It has also been demonstrated that youth who experiment with or regularly use alcohol and/or drugs are at higher risk for developing other substance use disorders in young adulthood than those who abstain during this time of life [ 19 , 44 ].
Environmental Influences
Parental substance use and behavior.
The existing evidence suggests that having parents with a substance use disorder increases risk for personal addiction in adulthood [ 30 , 31 ]. More specifically, parental alcoholism during adolescence has been linked to alcohol and drug dependence in offspring in adulthood [ 35 , 45 – 47 ]. Similarly, Kosty and colleagues demonstrated that parental history of cannabis and other illicit drug disorder increased the risk of offspring cannabis use disorder. While having a parent that smoked cigarettes during adolescence was associated with greater risk of personal nicotine dependence in young adulthood, after controlling for internalizing and externalizing symptoms, only the association between maternal smoking and amount of personal cigarette use remained significant [ 33 ]. Furthermore, parental history of other illicit substance use disorders also increased personal risk for cannabis use disorder, but there was no significant association between presence of a parental alcohol use disorder and personal risk for cannabis use disorder. These effects are likely attributable to both genetic and environmental risk factors. It is estimated that 40–60% of the variability in risk for developing alcohol, nicotine or illicit substance use disorders is attributable to genetic factors and genome wide-association studies have been able to attribute some of that variability to specific genetic loci [ 48 ]. However, adoption studies suggest that the association between parental substance use disorders and personal risk for addiction is also attributable to environmental influences. For example, Nwelin and colleagues demonstrated that individuals with adoptive or step-parents with substance use disorders were also more likely to develop a substance abuse/dependence in adulthood [ 49 ], suggesting that these familial associations are not entirely genetic in nature.
There is also research suggesting that subclinical parental substance use and behavior can influence personal risk for addiction later in life. A recent meta-analysis of longitudinal studies examined which modifiable parenting factors measured in adolescence were associated with future alcohol misuse (including alcohol use disorders) in their children. The study determined that subclinical levels of parental alcohol use, favorable attitudes toward alcohol use, and parental provision of alcohol use were associated future alcohol misuse by their children [ 50•• ]. Furthermore, lack of parental involvement, monitoring, support and parent-child relationship quality were associated with increased risk for alcohol misuse later in life.
Peer Influences
Evidence from longitudinal studies suggests that socializing with peers that are engaging in alcohol and other drug use increases risk for substance disorders later in life [ 20 , 21 , 25 , 40 , 51 , 52 ], but the directionality of the relationships between peer affiliation and personal substance use remain unclear. For example, deviant peer affiliations in adolescence mediated the association between substance use in adolescence and substance dependence in young adulthood [ 52 ]. In contrast, another study found that the association between peer affiliations and future cannabis use disorder was mediated by increased cannabis use, but did not find evidence that cannabis use predicted affiliation with peers who used cannabis [ 20 ].
Socioeconomic Status
Studies linking economic disadvantage in childhood and adolescence to risk for adult substance use disorders have produced mixed results. While childhood economic disadvantage has been associated with increased risk for alcohol [ 53 ] and tobacco [ 21 , 53 ] dependence in adulthood, one study found that economic disadvantage during childhood was less likely to result in harmful drinking in adulthood in female participants [ 54 ]. Some studies have also failed to detect a significant association between socioeconomic status during childhood and/or adolescence and adult substance use disorders [ 22 , 32 , 40 ].
Negative or Traumatic Life Events
Most studies examining the association between negative and traumatic life events in childhood and adolescence and risk for developing addiction in adulthood have relied on retrospective reports [ 55 ]. Studies examining prospectively-substantiated childhood maltreatment demonstrated that any childhood maltreatment, physical abuse, emotional abuse, and neglect predicted cannabis dependence in young adulthood [ 19 , 56 ]. Given the evidence that retrospective self-reports of childhood maltreatment might be better predictors of substance use disorders than prospective substantiated-reports [ 57 , 58 ], it is worth noting that longitudinal studies beginning in childhood or adolescence have found associations between retrospective self-report of childhood adversity [ 55 ] or physical abuse [ 59 ] before the age of 18 and substance use disorders in adulthood.
Neurobiology
Compared to the wealth of literature using neurobiological assessments during adolescence to predict future patterns of substance use [for review, see 60 ], there have been few prospective longitudinal studies that investigate neural predictors of risk for substance use disorders. Further, in contrast to the cohort studies described previously, most longitudinal neuroimaging studies to date have sampled across a large age range at baseline and followed subjects for a relatively short time frame and are unable to risk factors that predict adult addiction. For example, the ratio of orbitofrontal cortex to amygdala volume during adolescence (ages 8–19) has been associated with substance use disorders several years later (ages 12–27) [ 61 ], and less orbitofrontal cortex volume at age 12 has been shown to predict diagnosis of a substance use disorder prior to age 18 [ 62 ]. Lastly, one study found that the amplitude of the P300 component of the event related-potential and postural sway (a marker of neurodevelopmental delay) during childhood, but not adolescence, predicted substance use disorders in adulthood [ 63 ]. Future studies in this domain are needed to isolate neurobiological predictors occurring specifically in childhood and adolescence (<18 years of age) that can be used to identify clinical diagnosis of a substance use disorder in adulthood (> 18 years of age).
Examining the Complex Relationships Between Risk Factors for Addiction
Systematic inclusion of risk factors in prospective studies and careful evaluation of the relationships between risk factors is necessary for understanding heterogeneous findings in the existing literature and identifying the optimal targets for intervention. Existing studies suggest that different risk factors explain unique and overlapping variance in the risk for addiction. For example, Fergusson and colleagues determined that conduct and attentional problems during childhood and adolescence predicted alcohol, cannabis, nicotine, and other drug abuse/dependence in young adulthood using univariate models; however, only the effects of conduct problems remained significant when both predictors were modeled concurrently along with childhood adversity, socioeconomic status, family instability and conflict, parental substance use, childhood abuse, anxiety, and cognitive ability [ 64 ]. These findings suggest that conduct problems independently predict future substance use disorders; however, the association between inattention and future substance may be best explained by the correlations between inattention and conduct problems or other relevant personal and environmental risk factors. Although this is a single example, this pattern of results is pervasive in the literature, with many studies reporting significant effects in univariate analysis that are no longer significant when other personal and environmental risk factors are modeled simultaneously [e.g. 32 , 33 , 37 , 35 , 38 , 40 ]. To begin disentangling the complex relationships between variables, Kraemer and colleagues have proposed methodology for determining whether risk factors are working independently, have overlapping influence, or if one variable is only related to the outcome by proxy of another risk factor [ 65•• ]. In the existing literature, the examination of many variables at once, the heterogeneity of the variables selected for inclusion, and only reporting the effects associated with variables of interest, hampers our understanding of how different variables work together to influence outcomes. Working towards clarifying these relationships is important, because while proxy variables may be useful for identifying individuals who are at risk for addiction, interventions targeted at proxy risk factors are unlikely to improve outcomes.
Another important step in determining how risk factors work together, is to test for mediators that provide evidence for hypothesized relationships between chains of risk factors and for moderators that affect the relationship between other variables [ 65 ]. For example, it has been demonstrated that a latent variable of childhood socioeconomic disadvantage was a better predictor of cigarette use in young adulthood (another latent variable combining nicotine dependence and smoking frequency) than 5 observed variables (e.g. parental education, parental income) [ 21 ]. This association was mediated by educational achievement, conduct problems, and exposure to parental and peer smoking in adolescence. Given the temporal precedence of risk factors, these findings are consistent with the hypothesis that early economic disadvantage leads to factors in adolescence that promote risk for addiction in adulthood; however, it is important to note that tests of mediation tests do not prove causation. Furthermore, although the meta-analysis by Groenman and colleagues did not find evidence for an association between anxiety disorders in adolescence and adult addiction [ 14 ], one study found this association was moderated by sex, such that social anxiety disorder in adolescence predicted adult alcohol and cannabis dependence in women but not men [ 16 ]. Identification of moderators is important because they highlight which interventions might be appropriate for different individuals.
An alternative technique for examining the complicated relationships between risk factors involves the use of more data-driven statistical machine learning methods approaches that can use a large number of predictor variables and include higher order interactions between predictors in statistical models (e.g. random forest, support vector machine learning). Although to our knowledge, statistical machine learning has not been utilized to predict substance use disorders in adulthood from childhood and adolescent risk factors, these approaches have been used to predict binge drinking [ 66 ] and moderate/heavy alcohol use during adolescence [ 67 ]. In both studies, a variety of demographic, behavior, personality, cognitive, and neurobiological factors predicted alcohol use. Although these findings suggest that more complex models may improve our ability to predict addiction in adulthood, translating these findings into policy and preventions may prove to be challenging due to the highly dimensional nature of the results.
Developing indices of risk for substance use disorder that are easy to calculate and rely on a limited number of features may facilitate the translation of findings from prospective longitudinal studies for use in public health initiatives. For example, Meier and colleagues created a cumulative risk index by summing the presence of 9 childhood and adolescent risk factors: being male, lower family socioeconomic status, family history of substance use disorders, childhood conduct disorder and depression, early exposure to substances, and adolescent frequent alcohol, tobacco, and cannabis use [ 68 ]. The composite score predicted persistent substance use disorder in adulthood with 80% accuracy. They determined that 3% of adolescents without risk factors, 27% of adolescents with 3 risk factors, and 74% of adolescents with 6+ risk factors had persistent substance use disorder as adults. Similar work predicted cannabis use disorder in young adulthood using two composite scores thought to reflect transmissible and nontransmissible risk factors for substance use disorders derived from assessments obtained in boys during childhood [ 69 ]. Although promising due to their ease of use, careful examination of the variables included in composite scores is helpful for ensuring that important relationships between variables are not being obscured by aggregation of risk factors into composite scores. Lastly, across all approaches employed, replication in independent datasets is necessary to validate the veracity of findings.
Conclusions and Future Directions
Although progress has been made in identifying risk factors for addiction, the complicated relationships between risk factors are less well-understood and may hamper accurate identification of those at greatest risk and the creation of interventions targeted at the risk factors that have the greatest impact on risk for substance use disorders. This review highlights several risk factors that have been most consistently linked to higher risk for addiction, such as the presence of externalizing and internalizing symptoms, early substance use, and environmental influences including different aspects of the parent-child relationship and exposure to trauma. Further research to identify how these variables interact and to identify novel risk factors will be important for understanding the complexity of the various mechanisms that lead to the development of substance use disorders.
Since rates of illicit substance use are relatively lower, prospective longitudinal studies have predominately focused on predicting variable patterns alcohol, nicotine and/or marijuana use. To the extent that some risk factors for addiction are drug specific, larger longitudinal studies or recruitment of samples at higher risk for illicit drug use would aid in determining the factors that predict illicit substance use disorders. For example, a recent study determined that adolescents who experienced chronic pain were more likely to misuse opioids than adolescents without chronic pain [ 70 ]. With rates of opioid overdoses increasing 12.9-fold from 2007 to 2017 [ 71 ], more research is needed to determine which individuals are at greatest risk for opioid misuse and addiction.
While several large cohort studies exist for examining environmental and neurocognitive predictors of adult addiction, studies using neurobiological predictors have been limited. Large-scale prospective longitudinal studies, such as the Adolescent Brain Cognitive Development Study (ABCD), will provide an unprecedented opportunity to examine how cognitive, behavioral, and environmental risk factors for addiction are related to neurobiology and risk for addiction. For example, based on a review of the existing literature, it has been hypothesized that the relationship between internalizing symptoms and substance use is partially attributable to individual differences in the development of frontostriatal circuitry that predict the onset and escalation of depression, anxiety, and substance use [ 72 ]. Studies, like ABCD, should have an adequate sample size to examine this and many other hypotheses about the development of psychopathology, including addiction. Identifying biomarkers that predict increased risk of developing a substance use disorder could inform interventions that target and strengthen relevant circuitry.
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Conflict of Interest
The authors declare that they have no conflict of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
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** Of major importance
- 1. U.S. Department of Health and Human Services. The Health Consequences of Smoking-50 Years of Progress. A Report of the Surgeon General In: U.S. Department of Health and Human Services CfDCaP, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, editor. Atlanta: 2014. [ Google Scholar ]
- 2. Centers for Disease Control and Prevention. Alcohol-Attributable Deaths and Years of Potential Life Lost — 11 States, 2006–2010 In: CDC, editor. Atlanta, GA: 2014. [ Google Scholar ]
- 3. Xu X, Bishop EE, Kennedy SM, Simpson SA, Pechacek TF. Annual healthcare spending attributable to cigarette smoking: an update. Am J Prev Med. 2015;48(3):326–33. doi: 10.1016/j.amepre.2014.10.012. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 4. Centers for Disease Control and Prevention. Excessive Drinking is Draining the US Economy. 2016.
- 5. National Drug Intelligence Center. National Drug Threat Assessment. In: Do Justice, editor. Washington, DC: United States2011. [ Google Scholar ]
- 6. Birnbaum HG, White AG, Schiller M, Waldman T, Cleveland JM, Roland CL. Societal costs of prescription opioid abuse, dependence, and misuse in the United States. Pain Med. 2011;12(4):657–67. doi: 10.1111/j.1526-4637.2011.01075.x. [ DOI ] [ PubMed ] [ Google Scholar ]
- 7. Florence CS, Zhou C, Luo F, Xu L. The Economic Burden of Prescription Opioid Overdose, Abuse, and Dependence in the United States, 2013. Med Care. 2016;54(10):901–6. doi: 10.1097/MLR.0000000000000625. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 8. Dennis ML, Scott CK, Funk R, Foss MA. The duration and correlates of addiction and treatment careers. J Subst Abuse Treat. 2005;28 Suppl 1:S51–62. doi: 10.1016/j.jsat.2004.10.013. [ DOI ] [ PubMed ] [ Google Scholar ]
- 9. De Soto CB, O’Donnell WE, De Soto JL. Long-term recovery in alcoholics. Alcohol Clin Exp Res. 1989;13(5):693–7. [ DOI ] [ PubMed ] [ Google Scholar ]
- 10. Center for Behavioral Health Statistics and Quality. 2015 National Survey on Drug Use and Health. 2015.
- 11. Grant BF, Goldstein RB, Saha TD, Chou SP, Jung J, Zhang H et al. Epidemiology of DSM-5 Alcohol Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA Psychiatry. 2015;72(8):757–66. doi: 10.1001/jamapsychiatry.2015.0584. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 12. Grant BF, Saha TD, Ruan WJ, Goldstein RB, Chou SP, Jung J et al. Epidemiology of DSM-5 Drug Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions-III. JAMA Psychiatry. 2016;73(1):39–47. doi: 10.1001/jamapsychiatry.2015.2132. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 13. Chou SP, Goldstein RB, Smith SM, Huang B, Ruan WJ, Zhang H et al. The Epidemiology of DSM-5 Nicotine Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions-III. J Clin Psychiatry. 2016;77(10):1404–12. doi: 10.4088/JCP.15m10114. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 14. ••. Groenman AP, Janssen TW, Oosterlaan J. Childhood psychiatric disorders as risk factor for subsequent substance abuse: a meta-analysis. Journal of the American Academy of Child & Adolescent Psychiatry. 2017;56(7):556–69. [ DOI ] [ PubMed ] [ Google Scholar ]; A meta-analysis that examines the evidence that childhood/adolescent psychiatric disorders are risk factors for adult substance use disorders
- 15. Buckner JD, Schmidt NB, Lang AR, Small JW, Schlauch RC, Lewinsohn PM. Specificity of social anxiety disorder as a risk factor for alcohol and cannabis dependence. J Psychiatr Res. 2008;42(3):230–9. doi: 10.1016/j.jpsychires.2007.01.002. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 16. Buckner JD, Turner RJ. Social anxiety disorder as a risk factor for alcohol use disorders: a prospective examination of parental and peer influences. Drug Alcohol Depend. 2009;100(1–2):128–37. doi: 10.1016/j.drugalcdep.2008.09.018. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 17. Englund MM, Egeland B, Oliva EM, Collins WA. Childhood and adolescent predictors of heavy drinking and alcohol use disorders in early adulthood: a longitudinal developmental analysis. Addiction. 2008;103:23–35. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 18. Hayatbakhsh MR, McGee TR, Bor W, Najman JM, Jamrozik K, Mamun AA. Child and adolescent externalizing behavior and cannabis use disorders in early adulthood: an Australian prospective birth cohort study. Addict Behav. 2008;33(3):422–38. doi: 10.1016/j.addbeh.2007.10.004. [ DOI ] [ PubMed ] [ Google Scholar ]
- 19.•. Mills R, Kisely S, Alati R, Strathearn L, Najman JM. Child maltreatment and cannabis use in young adulthood: a birth cohort study. Addiction. 2017;112(3):494–501. doi: 10.1111/add.13634. [ DOI ] [ PubMed ] [ Google Scholar ]; Although the focus of this study is on childhood maltreatment, statistical analyses control for potential confounds and report the significance of especially important additional covariates (e.g. externalizing behavior and personal substance use).
- 20. Defoe IN, Khurana A, Betancourt LM, Hurt H, Romer D. Disentangling longitudinal relations between youth cannabis use, peer cannabis use, and conduct problems: developmental cascading links to cannabis use disorder. Addiction. 2019;114(3):485–93. doi: 10.1111/add.14456. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 21. Fergusson DM, Horwood LJ, Boden JM, Jenkin G. Childhood social disadvantage and smoking in adulthood: results of a 25-year longitudinal study. Addiction. 2007;102(3):475–82. doi: 10.1111/j.1360-0443.2006.01729.x. [ DOI ] [ PubMed ] [ Google Scholar ]
- 22. Pardini D, White HR, Stouthamer-Loeber M. Early adolescent psychopathology as a predictor of alcohol use disorders by young adulthood. Drug Alcohol Depend. 2007;88 Suppl 1:S38–49. doi: 10.1016/j.drugalcdep.2006.12.014. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 23. Pingault JB, Cote SM, Galera C, Genolini C, Falissard B, Vitaro F et al. Childhood trajectories of inattention, hyperactivity and oppositional behaviors and prediction of substance abuse/dependence: a 15-year longitudinal population-based study. Mol Psychiatry. 2013;18(7):806–12. doi: 10.1038/mp.2012.87. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 24. Hayatbakhsh MR, Najman JM, Jamrozik K, Al Mamun A, Bor W, Alati R. Adolescent problem behaviours predicting DSM-IV diagnoses of multiple substance use disorder. Findings of a prospective birth cohort study. Soc Psychiatry Psychiatr Epidemiol. 2008;43(5):356–63. doi: 10.1007/s00127-008-0325-1. [ DOI ] [ PubMed ] [ Google Scholar ]
- 25. Guo J, Hawkins JD, Hill KG, Abbott RD. Childhood and adolescent predictors of alcohol abuse and dependence in young adulthood. J Stud Alcohol. 2001;62(6):754–62. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 26. D’Amico EJ, Ellickson PL, Collins RL, Martino S, Klein DJ. Processes linking adolescent problems to substance-use problems in late young adulthood. J Stud Alcohol. 2005;66(6):766–75. [ DOI ] [ PubMed ] [ Google Scholar ]
- 27. Bonomo YA, Bowes G, Coffey C, Carlin JB, Patton GC. Teenage drinking and the onset of alcohol dependence: a cohort study over seven years. Addiction. 2004;99(12):1520–8. doi: 10.1111/j.1360-0443.2004.00846.x. [ DOI ] [ PubMed ] [ Google Scholar ]
- 28. Foulds JA, Boden JM, Newton-Howes GM, Mulder RT, Horwood LJ. The role of novelty seeking as a predictor of substance use disorder outcomes in early adulthood. Addiction. 2017;112(9):1629–37. doi: 10.1111/add.13838. [ DOI ] [ PubMed ] [ Google Scholar ]
- 29. Palmer RH, Knopik VS, Rhee SH, Hopfer CJ, Corley RC, Young SE et al. Prospective effects of adolescent indicators of behavioral disinhibition on DSM-IV alcohol, tobacco, and illicit drug dependence in young adulthood. Addict Behav. 2013;38(9):2415–21. doi: 10.1016/j.addbeh.2013.03.021. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 30. Mezzich AC, Tarter RE, Kirisci L, Feske U, Day BS, Gao Z. Reciprocal influence of parent discipline and child’s behavior on risk for substance use disorder: a nine-year prospective study. Am J Drug Alcohol Abuse. 2007;33(6):851–67. doi: 10.1080/00952990701653842. [ DOI ] [ PubMed ] [ Google Scholar ]
- 31. Tarter RE, Kirisci L, Habeych M, Reynolds M, Vanyukov M. Neurobehavior disinhibition in childhood predisposes boys to substance use disorder by young adulthood: direct and mediated etiologic pathways. Drug Alcohol Depend. 2004;73(2):121–32. [ DOI ] [ PubMed ] [ Google Scholar ]
- 32. Huurre T, Lintonen T, Kaprio J, Pelkonen M, Marttunen M, Aro H. Adolescent risk factors for excessive alcohol use at age 32 years. A 16-year prospective follow-up study. Soc Psychiatry Psychiatr Epidemiol. 2010;45(1):125–34. doi: 10.1007/s00127-009-0048-y. [ DOI ] [ PubMed ] [ Google Scholar ]
- 33. Jester JM, Glass JM, Bohnert KM, Nigg JT, Wong MM, Zucker RA. Child and adolescent predictors of smoking involvement in emerging adulthood. Health Psychol. 2019;38(2):133–42. doi: 10.1037/hea0000703. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 34. Bardone AM, Moffitt TE, Caspi A, Dickson N, Stanton WR, Silva PA. Adult physical health outcomes of adolescent girls with conduct disorder, depression, and anxiety. J Am Acad Child Adolesc Psychiatry. 1998;37(6):594–601. doi: 10.1097/00004583-199806000-00009. [ DOI ] [ PubMed ] [ Google Scholar ]
- 35. Newton-Howes G, Boden JM. Relation between age of first drinking and mental health and alcohol and drug disorders in adulthood: evidence from a 35-year cohort study. Addiction. 2016;111(4):637–44. doi: 10.1111/add.13230. [ DOI ] [ PubMed ] [ Google Scholar ]
- 36. King KM, Chassin L. A prospective study of the effects of age of initiation of alcohol and drug use on young adult substance dependence. J Stud Alcohol Drugs. 2007;68(2):256–65. [ DOI ] [ PubMed ] [ Google Scholar ]
- 37. Guttmannova K, Bailey JA, Hill KG, Lee JO, Hawkins JD, Woods ML et al. Sensitive periods for adolescent alcohol use initiation: predicting the lifetime occurrence and chronicity of alcohol problems in adulthood. J Stud Alcohol Drugs. 2011;72(2):221–31. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 38. Newton-Howes G, Cook S, Martin G, Foulds JA, Boden JM. Comparison of age of first drink and age of first intoxication as predictors of substance use and mental health problems in adulthood. Drug Alcohol Depend. 2019;194:238–43. doi: 10.1016/j.drugalcdep.2018.10.012. [ DOI ] [ PubMed ] [ Google Scholar ]
- 39. Guo J, Collins LM, Hill KG, Hawkins JD. Developmental pathways to alcohol abuse and dependence in young adulthood. J Stud Alcohol. 2000;61(6):799–808. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 40. Prince van Leeuwen A, Creemers HE, Verhulst FC, Vollebergh WA, Ormel J, van Oort F et al. Legal substance use and the development of a DSM-IV cannabis use disorder during adolescence: the TRAILS study. Addiction. 2014;109(2):303–11. doi: 10.1111/add.12346. [ DOI ] [ PubMed ] [ Google Scholar ]
- 41. Swift W, Coffey C, Carlin JB, Degenhardt L, Patton GC. Adolescent cannabis users at 24 years: trajectories to regular weekly use and dependence in young adulthood. Addiction. 2008;103(8):1361–70. doi: 10.1111/j.1360-0443.2008.02246.x. [ DOI ] [ PubMed ] [ Google Scholar ]
- 42. Brook JS, Balka EB, Ning Y, Brook DW. Trajectories of cigarette smoking among African Americans and Puerto Ricans from adolescence to young adulthood: associations with dependence on alcohol and illegal drugs. Am J Addict. 2007;16(3):195–201. doi: 10.1080/10550490701375244. [ DOI ] [ PubMed ] [ Google Scholar ]
- 43. Strong C, Juon HS, Ensminger ME. Effect of Adolescent Cigarette Smoking on Adulthood Substance Use and Abuse: The Mediating Role of Educational Attainment. Subst Use Misuse. 2016;51(2):141–54. doi: 10.3109/10826084.2015.1073323. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 44. Gil AG, Wagner EF, Tubman JG. Associations between early-adolescent substance use and subsequent young-adult substance use disorders and psychiatric disorders among a multiethnic male sample in South Florida. Am J Public Health. 2004;94(9):1603–9. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 45. Knop J, Penick EC, Nickel EJ, Mednick SA, Jensen P, Manzardo AM et al. Paternal alcoholism predicts the occurrence but not the remission of alcoholic drinking: a 40-year follow-up. Acta Psychiatr Scand. 2007;116(5):386–93. doi: 10.1111/j.1600-0447.2007.01015.x. [ DOI ] [ PubMed ] [ Google Scholar ]
- 46. Kosty DB, Farmer RF, Seeley JR, Gau JM, Duncan SC, Lewinsohn PM. Parental transmission of risk for cannabis use disorders to offspring. Addiction. 2015;110(7):1110–7. doi: 10.1111/add.12914. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 47. Chassin L, Pitts SC, DeLucia C, Todd M. A longitudinal study of children of alcoholics: predicting young adult substance use disorders, anxiety, and depression. J Abnorm Psychol. 1999;108(1):106–19. [ DOI ] [ PubMed ] [ Google Scholar ]
- 48. Hancock DB, Markunas CA, Bierut LJ, Johnson EO. Human Genetics of Addiction: New Insights and Future Directions. Curr Psychiatry Rep. 2018;20(2):8. doi: 10.1007/s11920-018-0873-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 49. Newlin DB, Miles DR, van den Bree MB, Gupman AE, Pickens RW. Environmental transmission of DSM-IV substance use disdorders in adoptive and step families. Alcohol Clin Exp Res. 2000;24(12):1785–94. [ PubMed ] [ Google Scholar ]
- 50. ••. Yap MBH, Cheong TWK, Zaravinos-Tsakos F, Lubman DI, Jorm AF. Modifiable parenting factors associated with adolescent alcohol misuse: a systematic review and meta-analysis of longitudinal studies. Addiction. 2017;112(7):1142–62. doi: 10.1111/add.13785. [ DOI ] [ PubMed ] [ Google Scholar ]; This meta-analysis aggregates findings from studies examining how parenting behaviors influence alcohol-related problems in adulthood.
- 51. Gil AG, Vega WA, Turner RJ. Early and mid-adolescence risk factors for later substance abuse by African Americans and European Americans. Public Health Rep. 2002;117 Suppl 1:S15–29. [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 52. Van Ryzin MJ, Dishion TJ. Adolescent deviant peer clustering as an amplifying mechanism underlying the progression from early substance use to late adolescent dependence. J Child Psychol Psychiatry. 2014;55(10):1153–61. doi: 10.1111/jcpp.12211. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 53. Poulton R, Caspi A, Milne BJ, Thomson WM, Taylor A, Sears MR et al. Association between children’s experience of socioeconomic disadvantage and adult health: a life-course study. Lancet. 2002;360(9346):1640–5. doi: 10.1016/S0140-6736(02)11602-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 54. Maggs JL, Patrick ME, Feinstein L. Childhood and adolescent predictors of alcohol use and problems in adolescence and adulthood in the National Child Development Study. Addiction. 2008;103 Suppl 1:7–22. doi: 10.1111/j.1360-0443.2008.02173.x. [ DOI ] [ PubMed ] [ Google Scholar ]
- 55. LeTendre ML, Reed MB. The Effect of Adverse Childhood Experience on Clinical Diagnosis of a Substance Use Disorder: Results of a Nationally Representative Study. Subst Use Misuse. 2017;52(6):689–97. doi: 10.1080/10826084.2016.1253746. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 56. Abajobir AA, Najman JM, Williams G, Strathearn L, Clavarino A, Kisely S. Substantiated childhood maltreatment and young adulthood cannabis use disorders: A pre-birth cohort study. Psychiatry Res. 2017;256:21–31. doi: 10.1016/j.psychres.2017.06.017. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 57. Newbury JB, Arseneault L, Moffitt TE, Caspi A, Danese A, Baldwin JR et al. Measuring childhood maltreatment to predict early-adult psychopathology: Comparison of prospective informant-reports and retrospective self-reports. J Psychiatr Res. 2018;96:57–64. doi: 10.1016/j.jpsychires.2017.09.020. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 58. Widom CS, Weiler BL, Cottler LB. Childhood victimization and drug abuse: a comparison of prospective and retrospective findings. J Consult Clin Psychol. 1999;67(6):867–80. [ DOI ] [ PubMed ] [ Google Scholar ]
- 59. Silverman AB, Reinherz HZ, Giaconia RM. The long-term sequelae of child and adolescent abuse: a longitudinal community study. Child Abuse Negl. 1996;20(8):709–23. [ DOI ] [ PubMed ] [ Google Scholar ]
- 60. Squeglia LM, Gray KM. Alcohol and Drug Use and the Developing Brain. Curr Psychiatry Rep. 2016;18(5):46. doi: 10.1007/s11920-016-0689-y. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 61. O’Brien JW, Hill SY. Neural predictors of substance use disorders in Young adulthood. Psychiatry research Neuroimaging. 2017;268:22–6. doi: 10.1016/j.pscychresns.2017.08.006. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 62. Cheetham A, Allen NB, Whittle S, Simmons J, Yucel M, Lubman DI. Orbitofrontal Cortex Volume and Effortful Control as Prospective Risk Factors for Substance Use Disorder in Adolescence. Eur Addict Res. 2017;23(1):37–44. doi: 10.1159/000452159. [ DOI ] [ PubMed ] [ Google Scholar ]
- 63. Hill SY, Steinhauer SR, Locke-Wellman J, Ulrich R. Childhood risk factors for young adult substance dependence outcome in offspring from multiplex alcohol dependence families: a prospective study. Biol Psychiatry. 2009;66(8):750–7. doi: 10.1016/j.biopsych.2009.05.030. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 64. Fergusson DM, Horwood LJ, Ridder EM. Conduct and attentional problems in childhood and adolescence and later substance use, abuse and dependence: results of a 25-year longitudinal study. Drug Alcohol Depend. 2007;88 Suppl 1:S14–26. doi: 10.1016/j.drugalcdep.2006.12.011. [ DOI ] [ PubMed ] [ Google Scholar ]
- 65. ••. Kraemer HC, Stice E, Kazdin A, Offord D, Kupfer D. How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. Am J Psychiatry. 2001;158(6):848–56. doi: 10.1176/appi.ajp.158.6.848. [ DOI ] [ PubMed ] [ Google Scholar ]; This paper proposes a method for systematically evaluating relationships between risk factors and classifying them into different categories to help identify individuals at high-risk for developing psychiatric disorders and in need of preventative interventions.
- 66. Whelan R, Watts R, Orr CA, Althoff RR, Artiges E, Banaschewski T et al. Neuropsychosocial profiles of current and future adolescent alcohol misusers. Nature. 2014;512(7513):185–9. doi: 10.1038/nature13402. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 67. Squeglia LM, Ball TM, Jacobus J, Brumback T, McKenna BS, Nguyen-Louie TT et al. Neural Predictors of Initiating Alcohol Use During Adolescence. Am J Psychiatry. 2017;174(2):172–85. doi: 10.1176/appi.ajp.2016.15121587. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 68. Meier MH, Hall W, Caspi A, Belsky DW, Cerda M, Harrington HL et al. Which adolescents develop persistent substance dependence in adulthood? Using population-representative longitudinal data to inform universal risk assessment. Psychol Med. 2016;46(4):877–89. doi: 10.1017/S0033291715002482. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 69. Kirisci L, Tarter R, Mezzich A, Ridenour T, Reynolds M, Vanyukov M. Prediction of cannabis use disorder between boyhood and young adulthood: clarifying the phenotype and environtype. Am J Addict. 2009;18(1):36–47. doi: 10.1080/10550490802408829. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 70. Groenewald CB, Law EF, Fisher E, Beals-Erickson SE, Palermo TM. Associations Between Adolescent Chronic Pain and Prescription Opioid Misuse in Adulthood. J Pain. 2019;20(1):28–37. doi: 10.1016/j.jpain.2018.07.007. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 71. Centers for Disease Control and Prevention, National Center for Health Statistics. Multiple Casues of Death 1999–2017 on CDC WONDER Online Database.
- 72. Jones SA, Morales AM, Lavine JB, Nagel BJ. Convergent neurobiological predictors of emergent psychopathology during adolescence. Birth Defects Res. 2017;109(20):1613–22. doi: 10.1002/bdr2.1176. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
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A Review Study of Substance Abuse Status in High School Students, Isfahan, Iran
Mah monir nahvizadeh, shohreh akhavan, leila qaraat, nahid geramian, ziba farajzadegan, kamal heidari.
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Correspondence to: Dr. Shohreh Akhavan, Provincial Health Center, Isfahan University of Medical Sciences, Isfahan, Iran, E-mail: [email protected]
Received 2014 Jun 20; Accepted 2014 Nov 8.
This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background:
As the first experience of substance abuse often starts in adolescence, and studies have shown that drug use is mainly related to cigarette and alcohol consumption, an initial exploration of substance abuse prevalence, including cigarette and alcohol, seems to be the first step in preventing and controlling drug consumption. This study aimed to explore studies on drug use among high school students by investigating articles published in the past decade in Iran.
In this study, the databases inside the country were used to access articles related to substance abuse by students during 2001–2011, among which 7 articles on 14–19 years old high school students were studied.
The seven studied articles showed that the highest drug use prevalence pertained to cigarette and hookah, followed by alcohol, opium, ecstasy, hashish and heroin. Opium and heroin use in Kerman city were, respectively, about 4 and 5 times of their use in other studied cities.
Conclusions:
Drug use is relatively high in the adolescent and effective group of the society, which requires particular attention and prompt and immediate intervention.
Keywords: Addiction, Iranian student, prevalence, substance abuse
INTRODUCTION
Substance abuse is a common phenomenon in the world and has invaded the human society as the most important social damage.[ 1 , 2 ] Substance abuse is a nonadaptive model of drug use, which results in adverse problems and consequences, and includes a set of cognitive, behavioral, and psychological symptoms.[ 3 ]
Iran also, due to its specific human and geographic features, has a relatively high degree of contamination.[ 4 ] The World Health Organization's report in 2005 shows that there are about 200 million opiate addicts in the world, reporting the highest prevalence in Iran and the most frequency in the 25–35 year-age group.[ 5 ] The onset of drug use is often rooted in adolescence, and studies show that substance abuse is often related to cigarette and alcohol consumption in adolescence.[ 6 ] Results of studies indicate that age, being male, high-risk behavirs, and the existence of a cigarette smoker in the family or among friends, the experience of substance abuse, inclination and positive thoughts about smoking have relationship with adolescent cigarette smoking.[ 7 ] Studies also confirm that the chance of becoming a cigarette smoker among males and females is almost equal (11.2%); however, the prevalence of regular alcohol consumption in males (22.4%) is slightly higher than in females (19.3%).[ 8 ]
Few studies have been conducted in Iran on adolescents’ patterns of substance abuse, producing various data on the prevalence and the type of consumed drugs, but there is currently no known specific pattern of substance abuse in this age group; therefore, this review study has studied drug consumption prevalence in the student population of the country by collecting various data.
This article is a narrative review focusing on studies conducted in Iran. In this research, all articles related to substance abuse and its patterns among high school students, which were conducted in Iran and published in domestic and international journals, were investigated. The articles were acquired from academic medical journals, research periodicals and the Scholar Google, Magiran, Irandoc, and Medlib. The search keywords included prevalence, substance abuse, Iranian student, and addiction.
This study explored articles in the past 10 years (2001–2011) about Iranian high school students. The full texts of the articles were often accessible in the scientific information database and magiran websites, but the full text of the article about Gilan Province was obtained after contacting the journal's office. Correspondence was made with the author of the article about Mahriz city to obtain the article as it was not published in the Toloee Behdasht journal.
These articles provide information about the consumed drug type, its prevalence in terms of the sex and age, and the experience of at-least-once consumption in the adolescent's life. Some articles had only pointed to drug consumption, which was also included in this research. Some had attended to substance abuse in general terms without distinguishing different kinds of drugs, and in some articles only psychoactive drug use, was mentioned.
The cases, in which the sample volume was not sufficient, or were not in the studied age groups, were excluded from the study. Due to different categorizations in these articles regarding the long-term prevalence of substance abuse or the experience of at-least-once consumption, in this study the shared aspect of these articles, that is, the experience of at-least-once use was adopted. Some articles had addressed the students’ predisposing factors for drug abuse, in addition to drug use prevalence, which were not included in this study for being scattered.
An initial search into the data bases yielded 11 articles, two of which were related to years before the study time frame (1997 and 1998). Furthermore, two articles were ignored, one because of its different age group (a lower age) and the other because it had addressed a particular district in Tehran with a small sample size. These results are based on 7 articles. All studies were about the 14–19 years old group, and only three studies had distinguished between the sexes. All 7 studies considered in this article were cross-sectional.
The prevalence of drug consumption in the studied cities
A study was conducted in 2003 on 500 students, from 142 high schools and vocational schools in Zahedan City, using a multi-stage cluster sampling method. In total, from the total of 259 females and 216 males who completed the questionnaire, the following results were obtained. 0.4% of the females and 2.3% of the males would usually smoke cigarette. The first experience of smoking was most often seen at the age of 14 (26.2%). The prevalence of other drugs was not studied in this research.[ 9 ] A study was conducted in 2009 on 610 students of Kerman's Male Pre-university Centers, in which the prevalence of each drug was reported, but the total consumption prevalence was not mentioned.[ 10 ]
A study in Gilan Province in 2004–2009 on 1927 high school students, including 46% females and 54% males, showed that the percentage of at-least-once use, including and excluding cigarette, was 23.7 and 12.8, respectively.[ 11 ]
A study in Karaj city in 2009–2010 on 447 high school students, including 239 females and 208 males, showed that 57% had at-least-once experience of drug use, including cigarette, of this number 56.1% were male and 43.9% were female.[ 12 ]
A study in Nazarabad city in 2007 on 400 3 rd year high school students, including 204 females and 196 males with the mean age of 17.3, showed that drug use prevalence, including and excluding cigarette, was 24.5% and 11.1%, respectively.[ 13 ] A study was performed in Lahijan city in 2004 on 2328 high school students, including 42.2% females and 57.8% males.[ 14 ] A descriptive study was conducted in 2008 on a 285-member sample of male high school students.[ 15 ]
The consumption prevalence for each drug type in different cities
A research on Kerman's Male Pre-university students yielded the following results. The consumption prevalence of hookah was 15.5%, sedatives (without medical prescription) 40.7%, alcohol 37.7%, cigarette 34.6%, strong analgesics 10.2%, nas 9.7%, opium 8.7%, hashish 6.7%, ecstasy 6.6%, and heroin 4.9%.
Consumption prevalence for each drug type in Gilan: The prevalence was 20% for cigarette, 10.5% for alcohol, 2.4% for opium, 1.2% for ecstasy, 2% for hashish, and 0.3% for heroin. In Karaj city, the consumption prevalence was 53% for hookah, 24.8% for cigarette, 13.6% for alcohol, 2% for ecstasy, 2% for opium, 1.1% for hashish, 0.4% for crystal, and 0.2% for heroin.
In Nazarabad City, the consumption prevalence was found to be 23.1% for cigarette, 2% for opium, 1% for amphetamines and ecstasy, 0.5% for heroin, 0.3% for hashish and cocaine. The male and female drug consumption was 69.7% and 36.2%, respectively, representing a significant statistical difference ( P < 0.05).
A study in Lahijan City showed that the consumption prevalence was 14.9% for cigarette, 2.4% for ecstasy, 4.1% for other drug types (with the highest rate of consumption for opium and hashish). In the Mahriz city of Yazd, the consumption prevalence among the male 3 rd year high school students in 2008 was reported 6.8% for alcohol and 3% for psychoactive substances [ Table 1 ].
The comparison of the prevalence of at-least-once drug use for each drug type in each studied region[ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]
Drug consumption prevalence for each sex
A study in Zahedan also reported that at-least-once drug use prevalence was 1.6% and 8%, respectively, among females and males; and at-least-once cigarette smoking prevalence was 7.8% and 25.2%, respectively, for females with the mean age of 15.8 and males with the mean age of 16.
In Gilan, drug use, excluding cigarette, was reported 19.1% and 5.3%, respectively, for males and females, representing a significant statistical difference ( P < 0.05). Furthermore, cigarette and drug use prevalence was 31.3% and 14.8% in males and females, respectively, showing that this rate was significantly higher in males ( P < 0.05). Cigarette use prevalence was 25.9% and 3%, respectively, for male and female students. Alcohol consumption was 16.6% and 3.4% for males and females, respectively. Opium consumption was 3.3% and 1.5% among males and females, respectively, which was a significant statistical difference (…). Drug consumption, excluding cigarette, was 19.1% and 5.3%, respectively, for males and females, pointing to a statistically significant difference ( P < 0.05). Ecstasy use prevalence was reported 3% and 1.1%, respectively, for males and females, pointing to a statistically significant difference ( P < 0.00081); 0.5% of males and 0.1% of females were heroin consumers, lacking any significant statistical difference ( P > 0.05). In Karaj city, drug consumption prevalence was studied for each sex and drug type [ Table 2 ].
The comparison of the prevalence of at-least-once drug consumption for each sex in each studied region
Drug consumption prevalence based on the age distribution in the studied populations
As the study conducted on students with the mean age of 16 in Zahedan showed that the highest incidence of the first experience of cigarette smoking belonged to the age of 14. A study in Kerman on students with the mean age of 17.9 about the age at the first experience yielded the following results for each drug type: 14 for cigarette, 14.6 for alcohol, 13.9 for hookah, 13.1 for sedatives, 15.3 for analgesics, 17 for ecstasy, 16.7 for hashish, 16.7 for heroin, 16.7 for opium, and 15.3 for naswar.
A study in Gilan indicated that drug and cigarette consumption had significantly increased in males aged 19 and above (88.9% of males aged 19 and above) ( P < 0.05). According to a study in Nazarabad, the highest drug use onset was at the age of 15–16. The students’ mean age in the Karaj study was 16.9.
Exploring the MFT performed in the USA on the 10 th graders showed that drug use had increased from 11% to 34% during 1992–1996. In 1998, 12.10% of the 8 th year and 12.5% of the 10 th graders and 25.611 th % had experienced illegal drug use in the previous month.[ 16 ] It was shown that hashish, followed by opium and alcohol, is the most commonly used illicit drug.[ 17 ] The immediate necessity of planning for reducing the consumption of these drugs among students, and consequently among university students, has become increasingly important.
Investigating addictive drugs prevalence among university students showed the prevalence in the following order: Hookah (74.5%), cigarette (67.5%), opium (6.1%), alcohol (13.5%), psychoactive pills (5.26%), hashish and heroin. Entertainment constitutes the tendency for drug consumption in most cases (47.4%).[ 18 ] Results of a meta-analysis showed that 7% of Iranian adolescents regularly smoke, and 27% had experienced smoking. The increased cigarette use prevalence among Iranian adolescents is a major public health concern.[ 19 ] Paying attention to healthy recreations for adolescents and the youth has become increasingly important and needs planning for discouraging drug use. The cross-sectional prevalence of drug use in 1997 among American 12–17 years old adolescents was reported 11.4%, which was close to drug use prevalence, excluding cigarette.[ 16 ]
Another study showed that 56% of male and 42% of female university students were drug users, which accords with the present research with regard to the higher number of the males.[ 20 ] Since, the addiction problem is an old problem in other countries, it might be better to use the solutions practiced by them to speed up our reaction in cases which adhere to our culture and customs.
At-least-once alcohol use prevalence among the 8 th year American students in 2005 and 2006 was 27% and 20%, respectively, increasing to 88% among the 12 th year students.[ 20 ] The history of hashish consumption among the 8 th , the 10 th , and the 12 th year students was 10%, 23%, and 36%, respectively, representing a remarkable difference with our country's students.[ 20 ] About 0.5% of the 8 th year and 10% of the 12 th year students consumed cocaine, and the consumption of amphetamines by the 12 th year students was 1.5%,[ 20 ] being almost close to the consumption rate of Iranian students. The open consumption of hashish is common in France by almost one-third of the population (nearly 30%), compared with the average rate of 19% in European countries; also the consumption of ecstasy and cocaine has increased over 2000–2005, although it is 4% but yet remarkable.[ 21 ]
A study on students’ knowledge of narcotics in Rafsanjan and Yazd cities showed that 5.6% of Yazdian and 10% of Rafsanjanian students had at least one addicted person in their families. Also, 2.23% of the Yazdian and 7% of the Rafsanjanian students held that narcotics could also be useful.[ 22 ] The important issue here is the existence of an addicted relative and his or her leadership role in this regard; therefore, this point suggests the further importance of the sensitivity of this age group with regard to their dependence on narcotics.
It is noteworthy that Kerman City, compared to other studied cities, has received higher rates of drug use, such that opium and heroin consumption in this city has been, respectively, almost 4 and 5 times that of other cities. These statistics also hold true clearly with regard to ecstasy and alcohol consumption, each being almost 3 times that of Karaj and Gilan. Hashish consumption in the pre-university stage in this city is also higher than in other cities, which might be related to easier drug access in Kerman.
In the cities, in which sex-distinct studies were conducted, drug consumption by males had been, with no exception, far higher than by the females, which is, almost 4 times except for hookah and then cigarette. Of course, it is not possible to judge firmly about drug use general prevalence as a result of the few studies in this field; however, the important point is the relatively high drug use among the adolescent and effective group of the society, which deserves particular attention for education and intervention in this group. It has been observed that adolescent and young crystal users, compared to nonusers, show clinical symptoms, have less control and affection in their families, with excitable, aggressive and anxious personalities, and low accountability;[ 23 ] on the other hand, behavioral problems and friend influence are among the strongest risk factors of drug consumption among adolescent consumers.
Nevertheless, it is not clear to what extent the adolescent can manage the effect of behavioral problems and peer group interaction for refusing invitations for drug consumption.[ 24 ] It has been stated that using software programs would assist in the prevention and increasing the youth's skills for reducing drug use.[ 25 ] It has been shown that adolescent inclination to and consumption of drugs decrease significantly in the 1 st year of educational intervention.[ 26 ] On the other hand, studies indicate that there is a relationship between the borderline personality disorder and the extent of drug abuse.[ 27 ]
Therefore, prevention programs for harm reduction, treatment and consultation as the main objective of the intervention structure should apply to consumers.[ 28 ] Also, emphasis should be laid upon the relationship between schools and parental care as important protective factors for adolescents’ health.[ 29 ] Adolescence is a growth period which is associated with a relatively high rate of drug use and its related disorders. Accordingly, recent progress in evaluating drug abuse among adolescents would continue for information sharing in the field of clinical and research services.[ 30 ] Therefore, attention to this group through coherent planning for damage prevention would still remain in priority.
CONCLUSIONS
Source of Support: Nil
Conflict of Interest: None declared.
- 1. Poor RA. Tehran: Salaman; 2004. A guide for prevention and treatment of substance abuse; p. 13. 23-4, 32, 17, 53, 143, 51-4. [ Google Scholar ]
- 2. Siam SH. Drug abuse prevalence in male students of different universities in Rashtin 2005. Tabibe Shargh. 2006;8:279–84. [ Google Scholar ]
- 3. Madadi A, Nogani F. Tehran: Jameanegar; 2004. The Text Book of Addiction and Substance Abuse; p. 10. [ Google Scholar ]
- 4. Jahangiri B. Tehran: Arjmand; 2002. A guide for cognition and treatment of addiction in Iran; p. 8. [ Google Scholar ]
- 5. Abasi A, Taziki S, Moradi A. Drug abuse pattern based on demographic factors in self-introducing addicts in Gorgan province, the scientific. J Gorgan Univ Med Sci. 2005;8:22–7. [ Google Scholar ]
- 6. Farhadinasab A, Allahverdipour H, Bashirian S, Mahjoub H. Lifetime pattern of substance abuse, parental support, religiosity, and locus of control in adolescent and young male users. Iranian Journal of Public Health. 2008;37:88–95. [ Google Scholar ]
- 7. Mohammadpoorasl A, Nedjat S, Fakhari A, Yazdani K, Rahimi Foroushani A, Fotouhi A. Smoking stages in an Iranian adolescent population. Acta Med Iran. 2012;50:746–54. [ PubMed ] [ Google Scholar ]
- 8. Simantov E, Schoen C, Klein JD. Health-compromising behaviors: Why do adolescents smoke or drink? identifying underlying risk and protective factors. Arch Pediatr Adolesc Med. 2000;154:1025–33. doi: 10.1001/archpedi.154.10.1025. [ DOI ] [ PubMed ] [ Google Scholar ]
- 9. Najafi K, Fekeri F, Mohseni R, Zarabo H, Nazefei F, Fagheirpour M, Shirazi M. Cigarette and drug consumption prevalence among high school students in Zahedan. Tabibe Sharq 6th Year. 2003:59–65. [ Google Scholar ]
- 10. Ziaaaldini H, Sharifi A, Nakhaee N, Ziaaaldini A. A. Theat-least-once narcotics consumption prevalence among male pre-university students in Kerman city. J Addict Health Summer Autumn 2nd Year. 2009:103–110. [ Google Scholar ]
- 11. Najafi K, Fekeri F, Mohseni R, Zarabi H, Nazefei F, Fagheirpour M, Sirazi M. Investigating drug consumption prevalence in high school students in Gilan province in the 2004-5 academic year. Gilans J Med Sci. 2006;16:67–79. [ Google Scholar ]
- 12. Alaee Kharaiam R, Kadivar P, Mohammad Khani SH, Sarami GH, Alaee Kharaiam S. The extent of cigarette, hookah, alcoholic breavegaes, narcotics and stimulants among high school students. J Subst Abuse Addict Stud 5th Year. 2010:99–114. [ Google Scholar ]
- 13. Ghavidel N, Samadi M, Khoram Beiz AH, Asasi A, Feizi AR, Ahmadi R, et al. Investigating drugs consumption prevalence (Cigarette, Narcotics, Alcohol, Psychoactive Drugs) and its related factors among the Third year high school students in Nazarabad city between February 2008 until July 2009. Razi J Med Sci. 2012;19:28–26. [ Google Scholar ]
- 14. Amiri M, Rezazadeh Z, Sadeghi S, Baneh FK. Ecstasy consumption prevalence among high school students in Lahijan city in 2004. Iran's Epidemiology, winter. 2004;1:47–52. [ Google Scholar ]
- 15. Zohreh K, Poran H, Meitham K, Bagher MM. Investigating alcoholic and psychoactive substances among male high school students in the Mahriz city of Yazd in 2008. J Toloee Behdasht Paeez and Zemestan. 2008;8:33. [ Google Scholar ]
- 16. Drug Abuse: Origins & Interventions. In: Glantz MD, Hartel CR, editors; Mohammadi M, Nejat MR, Parsa N, Ghorbani M, Mirzaei A, Namati F, Najarian F, Naziri G, translators. Tehran: Research Center of Iran Drug Control Headquarters; 2002. [ Google Scholar ]
- 17. Rahimi Movaqar A, Elaheh SY, Masuood Y. A review of drug consumption status among the country's university students. Pazhohesh Q 5th Year. 2005;5:104–8. [ Google Scholar ]
- 18. Jurgaitiene D, Zaborskis A, Sumskas L. Prevalence of drug use among students of vocational schools in Klaipeda city, Lithuania, in 2004-2006. Medicina (Kaunas) 2009;45:291–301. [ PubMed ] [ Google Scholar ]
- 19. Nazarzadeh M, Bidel Z, Ayubi E, Bahrami A, Jafari F, Mohammadpoorasl A, et al. Smoking status in Iranian male adolescents: A cross-sectional study and a meta-analysis. Addict Behav. 2013;38:2214–8. doi: 10.1016/j.addbeh.2013.01.018. [ DOI ] [ PubMed ] [ Google Scholar ]
- 20. Sadock BJ, Sadock VA. 10th ed. Vol. 5. Philadelphia: Lippincott Williams & Wilkins; 2007. Kaplan and Sadock's synapsisi of psychiatry: behavioral sciences/clinical psychiatry; pp. 1294–5. [ Google Scholar ]
- 21. Beck F, Legleye S. Sociology and epidemiology of consumption of psychoactive substances in adolescents. Encephale. 2009;35(Suppl 6):S190–201. doi: 10.1016/S0013-7006(09)73470-0. [ DOI ] [ PubMed ] [ Google Scholar ]
- 22. Yasini Ardekani SM, Zahra PM, Ahmadieyh MH. Investigating the extent of male high school students awareness of narcotics in Yazd and Rafsanjan cities. Yazds Third Public Congr Hazard Behav. 2012;8:27. [ Google Scholar ]
- 23. Zadeh SH. The comparison of clinical, family, personality, and training factors in ice consumers/non-consumers. J Subst Abuse Addict Stud 7th Year. 2012:53–72. [ Google Scholar ]
- 24. Glaser B, Shelton KH, van den Bree MB. The moderating role of close friends in the relationship between conduct problems and adolescent substance use. J Adolesc Health. 2010;47:35–42. doi: 10.1016/j.jadohealth.2009.12.022. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 25. Schinke SP, Schwinn TM, Fang L. Longitudinal outcomes of an alcohol abuse prevention program for urban adolescents. J Adolesc Health. 2010;46:451–7. doi: 10.1016/j.jadohealth.2009.11.208. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 26. Tebes JK, Feinn R, Vanderploeg JJ, Chinman MJ, Shepard J, Brabham T, et al. Impact of a positive youth development program in urban after-school settings on the prevention of adolescent substance use. J Adolesc Health. 2007;41:239–47. doi: 10.1016/j.jadohealth.2007.02.016. [ DOI ] [ PubMed ] [ Google Scholar ]
- 27. Sansone RA, Watts DA, Wiederman MW. Borderline personality symptomatology and legal charges related to drugs. Int J Psychiatry Clin Pract. 2014;18:150–2. doi: 10.3109/13651501.2013.847107. [ DOI ] [ PubMed ] [ Google Scholar ]
- 28. Eskandarieh S, Nikfarjam A, Tarjoman T, Nasehi A, Jafari F, Saberi-Zafarghandi MB. Descriptive Aspects of Injection Drug Users in Iran's National Harm Reduction Program by Methadone Maintenance treatment. Iran J Public Health. 2013;42:588–93. [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 29. Phuong TB, Huong NT, Tien TQ, Chi HK, Dunne MP. Factors associated with health risk behavior among school children in urban Vietnam. Glob Health Action. 2013;6:1–9. doi: 10.3402/gha.v6i0.18876. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
- 30. Winters KC. Advances in the science of adolescent drug involvement: Implications for assessment and diagnosis - Experience from the United States. Curr Opin Psychiatry. 2013;26:318–24. doi: 10.1097/YCO.0b013e328361e814. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
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Risk and protective factors of drug abuse among adolescents: a systematic review
- Azmawati Mohammed Nawi 1 ,
- Rozmi Ismail 2 ,
- Fauziah Ibrahim 2 ,
- Mohd Rohaizat Hassan 1 ,
- Mohd Rizal Abdul Manaf 1 ,
- Noh Amit 3 ,
- Norhayati Ibrahim 3 &
- Nurul Shafini Shafurdin 2
BMC Public Health volume 21 , Article number: 2088 ( 2021 ) Cite this article
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Drug abuse is detrimental, and excessive drug usage is a worldwide problem. Drug usage typically begins during adolescence. Factors for drug abuse include a variety of protective and risk factors. Hence, this systematic review aimed to determine the risk and protective factors of drug abuse among adolescents worldwide.
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was adopted for the review which utilized three main journal databases, namely PubMed, EBSCOhost, and Web of Science. Tobacco addiction and alcohol abuse were excluded in this review. Retrieved citations were screened, and the data were extracted based on strict inclusion and exclusion criteria. Inclusion criteria include the article being full text, published from the year 2016 until 2020 and provided via open access resource or subscribed to by the institution. Quality assessment was done using Mixed Methods Appraisal Tools (MMAT) version 2018 to assess the methodological quality of the included studies. Given the heterogeneity of the included studies, a descriptive synthesis of the included studies was undertaken.
Out of 425 articles identified, 22 quantitative articles and one qualitative article were included in the final review. Both the risk and protective factors obtained were categorized into three main domains: individual, family, and community factors. The individual risk factors identified were traits of high impulsivity; rebelliousness; emotional regulation impairment, low religious, pain catastrophic, homework completeness, total screen time and alexithymia; the experience of maltreatment or a negative upbringing; having psychiatric disorders such as conduct problems and major depressive disorder; previous e-cigarette exposure; behavioral addiction; low-perceived risk; high-perceived drug accessibility; and high-attitude to use synthetic drugs. The familial risk factors were prenatal maternal smoking; poor maternal psychological control; low parental education; negligence; poor supervision; uncontrolled pocket money; and the presence of substance-using family members. One community risk factor reported was having peers who abuse drugs. The protective factors determined were individual traits of optimism; a high level of mindfulness; having social phobia; having strong beliefs against substance abuse; the desire to maintain one’s health; high paternal awareness of drug abuse; school connectedness; structured activity and having strong religious beliefs.
The outcomes of this review suggest a complex interaction between a multitude of factors influencing adolescent drug abuse. Therefore, successful adolescent drug abuse prevention programs will require extensive work at all levels of domains.
Peer Review reports
Introduction
Drug abuse is a global problem; 5.6% of the global population aged 15–64 years used drugs at least once during 2016 [ 1 ]. The usage of drugs among younger people has been shown to be higher than that among older people for most drugs. Drug abuse is also on the rise in many ASEAN (Association of Southeast Asian Nations) countries, especially among young males between 15 and 30 years of age. The increased burden due to drug abuse among adolescents and young adults was shown by the Global Burden of Disease (GBD) study in 2013 [ 2 ]. About 14% of the total health burden in young men is caused by alcohol and drug abuse. Younger people are also more likely to die from substance use disorders [ 3 ], and cannabis is the drug of choice among such users [ 4 ].
Adolescents are the group of people most prone to addiction [ 5 ]. The critical age of initiation of drug use begins during the adolescent period, and the maximum usage of drugs occurs among young people aged 18–25 years old [ 1 ]. During this period, adolescents have a strong inclination toward experimentation, curiosity, susceptibility to peer pressure, rebellion against authority, and poor self-worth, which makes such individuals vulnerable to drug abuse [ 2 ]. During adolescence, the basic development process generally involves changing relations between the individual and the multiple levels of the context within which the young person is accustomed. Variation in the substance and timing of these relations promotes diversity in adolescence and represents sources of risk or protective factors across this life period [ 6 ]. All these factors are crucial to helping young people develop their full potential and attain the best health in the transition to adulthood. Abusing drugs impairs the successful transition to adulthood by impairing the development of critical thinking and the learning of crucial cognitive skills [ 7 ]. Adolescents who abuse drugs are also reported to have higher rates of physical and mental illness and reduced overall health and well-being [ 8 ].
The absence of protective factors and the presence of risk factors predispose adolescents to drug abuse. Some of the risk factors are the presence of early mental and behavioral health problems, peer pressure, poorly equipped schools, poverty, poor parental supervision and relationships, a poor family structure, a lack of opportunities, isolation, gender, and accessibility to drugs [ 9 ]. The protective factors include high self-esteem, religiosity, grit, peer factors, self-control, parental monitoring, academic competence, anti-drug use policies, and strong neighborhood attachment [ 10 , 11 , 12 , 13 , 14 , 15 ].
The majority of previous systematic reviews done worldwide on drug usage focused on the mental, psychological, or social consequences of substance abuse [ 16 , 17 , 18 ], while some focused only on risk and protective factors for the non-medical use of prescription drugs among youths [ 19 ]. A few studies focused only on the risk factors of single drug usage among adolescents [ 20 ]. Therefore, the development of the current systematic review is based on the main research question: What is the current risk and protective factors among adolescent on the involvement with drug abuse? To the best of our knowledge, there is limited evidence from systematic reviews that explores the risk and protective factors among the adolescent population involved in drug abuse. Especially among developing countries, such as those in South East Asia, such research on the risk and protective factors for drug abuse is scarce. Furthermore, this review will shed light on the recent trends of risk and protective factors and provide insight into the main focus factors for prevention and control activities program. Additionally, this review will provide information on how these risk and protective factors change throughout various developmental stages. Therefore, the objective of this systematic review was to determine the risk and protective factors of drug abuse among adolescents worldwide. This paper thus fills in the gaps of previous studies and adds to the existing body of knowledge. In addition, this review may benefit certain parties in developing countries like Malaysia, where the national response to drugs is developing in terms of harm reduction, prison sentences, drug treatments, law enforcement responses, and civil society participation.
This systematic review was conducted using three databases, PubMed, EBSCOhost, and Web of Science, considering the easy access and wide coverage of reliable journals, focusing on the risk and protective factors of drug abuse among adolescents from 2016 until December 2020. The search was limited to the last 5 years to focus only on the most recent findings related to risk and protective factors. The search strategy employed was performed in accordance with the Preferred Reporting Items for a Systematic Review and Meta-analysis (PRISMA) checklist.
A preliminary search was conducted to identify appropriate keywords and determine whether this review was feasible. Subsequently, the related keywords were searched using online thesauruses, online dictionaries, and online encyclopedias. These keywords were verified and validated by an academic professor at the National University of Malaysia. The keywords used as shown in Table 1 .
Selection criteria
The systematic review process for searching the articles was carried out via the steps shown in Fig. 1 . Firstly, screening was done to remove duplicate articles from the selected search engines. A total of 240 articles were removed in this stage. Titles and abstracts were screened based on the relevancy of the titles to the inclusion and exclusion criteria and the objectives. The inclusion criteria were full text original articles, open access articles or articles subscribed to by the institution, observation and intervention study design and English language articles. The exclusion criteria in this search were (a) case study articles, (b) systematic and narrative review paper articles, (c) non-adolescent-based analyses, (d) non-English articles, and (e) articles focusing on smoking (nicotine) and alcohol-related issues only. A total of 130 articles were excluded after title and abstract screening, leaving 55 articles to be assessed for eligibility. The full text of each article was obtained, and each full article was checked thoroughly to determine if it would fulfil the inclusion criteria and objectives of this study. Each of the authors compared their list of potentially relevant articles and discussed their selections until a final agreement was obtained. A total of 22 articles were accepted to be included in this review. Most of the excluded articles were excluded because the population was not of the target age range—i.e., featuring subjects with an age > 18 years, a cohort born in 1965–1975, or undergraduate college students; the subject matter was not related to the study objective—i.e., assessing the effects on premature mortality, violent behavior, psychiatric illness, individual traits, and personality; type of article such as narrative review and neuropsychiatry review; and because of our inability to obtain the full article—e.g., forthcoming work in 2021. One qualitative article was added to explain the domain related to risk and the protective factors among the adolescents.
PRISMA flow diagram showing the selection of studies on risk and protective factors for drug abuse among adolescents.2.2. Operational Definition
Drug-related substances in this context refer to narcotics, opioids, psychoactive substances, amphetamines, cannabis, ecstasy, heroin, cocaine, hallucinogens, depressants, and stimulants. Drugs of abuse can be either off-label drugs or drugs that are medically prescribed. The two most commonly abused substances not included in this review are nicotine (tobacco) and alcohol. Accordingly, e-cigarettes and nicotine vape were also not included. Further, “adolescence” in this study refers to members of the population aged between 10 to 18 years [ 21 ].
Data extraction tool
All researchers independently extracted information for each article into an Excel spreadsheet. The data were then customized based on their (a) number; (b) year; (c) author and country; (d) titles; (e) study design; (f) type of substance abuse; (g) results—risks and protective factors; and (h) conclusions. A second reviewer crossed-checked the articles assigned to them and provided comments in the table.
Quality assessment tool
By using the Mixed Method Assessment Tool (MMAT version 2018), all articles were critically appraised for their quality by two independent reviewers. This tool has been shown to be useful in systematic reviews encompassing different study designs [ 22 ]. Articles were only selected if both reviewers agreed upon the articles’ quality. Any disagreement between the assigned reviewers was managed by employing a third independent reviewer. All included studies received a rating of “yes” for the questions in the respective domains of the MMAT checklists. Therefore, none of the articles were removed from this review due to poor quality. The Cohen’s kappa (agreement) between the two reviewers was 0.77, indicating moderate agreement [ 23 ].
The initial search found 425 studies for review, but after removing duplicates and applying the criteria listed above, we narrowed the pool to 22 articles, all of which are quantitative in their study design. The studies include three prospective cohort studies [ 24 , 25 , 26 ], one community trial [ 27 ], one case-control study [ 28 ], and nine cross-sectional studies [ 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. After careful discussion, all reviewer panels agreed to add one qualitative study [ 46 ] to help provide reasoning for the quantitative results. The selected qualitative paper was chosen because it discussed almost all domains on the risk and protective factors found in this review.
A summary of all 23 articles is listed in Table 2 . A majority of the studies (13 articles) were from the United States of America (USA) [ 25 , 26 , 27 , 29 , 30 , 31 , 34 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ], three studies were from the Asia region [ 32 , 33 , 38 ], four studies were from Europe [ 24 , 28 , 40 , 44 ], and one study was from Latin America [ 35 ], Africa [ 43 ] and Mediterranean [ 45 ]. The number of sample participants varied widely between the studies, ranging from 70 samples (minimum) to 700,178 samples (maximum), while the qualitative paper utilized a total of 100 interviewees. There were a wide range of drugs assessed in the quantitative articles, with marijuana being mentioned in 11 studies, cannabis in five studies, and opioid (six studies). There was also large heterogeneity in terms of the study design, type of drug abused, measurements of outcomes, and analysis techniques used. Therefore, the data were presented descriptively.
After thorough discussion and evaluation, all the findings (both risk and protective factors) from the review were categorized into three main domains: individual factors, family factors, and community factors. The conceptual framework is summarized in Fig. 2 .
Conceptual framework of risk and protective factors related to adolescent drug abuse
DOMAIN: individual factor
Risk factors.
Almost all the articles highlighted significant findings of individual risk factors for adolescent drug abuse. Therefore, our findings for this domain were further broken down into five more sub-domains consisting of personal/individual traits, significant negative growth exposure, personal psychiatric diagnosis, previous substance history, comorbidity and an individual’s attitude and perception.
Personal/individual traits
Chuang et al. [ 29 ] found that adolescents with high impulsivity traits had a significant positive association with drug addiction. This study also showed that the impulsivity trait alone was an independent risk factor that increased the odds between two to four times for using any drug compared to the non-impulsive group. Another longitudinal study by Guttmannova et al. showed that rebellious traits are positively associated with marijuana drug abuse [ 27 ]. The authors argued that measures of rebelliousness are a good proxy for a youth’s propensity to engage in risky behavior. Nevertheless, Wilson et al. [ 37 ], in a study involving 112 youths undergoing detoxification treatment for opioid abuse, found that a majority of the affected respondents had difficulty in regulating their emotions. The authors found that those with emotional regulation impairment traits became opioid dependent at an earlier age. Apart from that, a case-control study among outpatient youths found that adolescents involved in cannabis abuse had significant alexithymia traits compared to the control population [ 28 ]. Those adolescents scored high in the dimension of Difficulty in Identifying Emotion (DIF), which is one of the key definitions of diagnosing alexithymia. Overall, the adjusted Odds Ratio for DIF in cannabis abuse was 1.11 (95% CI, 1.03–1.20).
Significant negative growth exposure
A history of maltreatment in the past was also shown to have a positive association with adolescent drug abuse. A study found that a history of physical abuse in the past is associated with adolescent drug abuse through a Path Analysis, despite evidence being limited to the female gender [ 25 ]. However, evidence from another study focusing at foster care concluded that any type of maltreatment might result in a prevalence as high as 85.7% for the lifetime use of cannabis and as high as 31.7% for the prevalence of cannabis use within the last 3-months [ 30 ]. The study also found significant latent variables that accounted for drug abuse outcomes, which were chronic physical maltreatment (factor loading of 0.858) and chronic psychological maltreatment (factor loading of 0.825), with an r 2 of 73.6 and 68.1%, respectively. Another study shed light on those living in child welfare service (CWS) [ 35 ]. It was observed through longitudinal measurements that proportions of marijuana usage increased from 9 to 18% after 36 months in CWS. Hence, there is evidence of the possibility of a negative upbringing at such shelters.
Personal psychiatric diagnosis
The robust studies conducted in the USA have deduced that adolescents diagnosed with a conduct problem (CP) have a positive association with marijuana abuse (OR = 1.75 [1.56, 1.96], p < 0.0001). Furthermore, those with a diagnosis of Major Depressive Disorder (MDD) showed a significant positive association with marijuana abuse.
Previous substance and addiction history
Another study found that exposure to e-cigarettes within the past 30 days is related to an increase in the prevalence of marijuana use and prescription drug use by at least four times in the 8th and 10th grades and by at least three times in the 12th grade [ 34 ]. An association between other behavioral addictions and the development of drug abuse was also studied [ 29 ]. Using a 12-item index to assess potential addictive behaviors [ 39 ], significant associations between drug abuse and the groups with two behavioral addictions (OR = 3.19, 95% CI 1.25,9.77) and three behavioral addictions (OR = 3.46, 95% CI 1.25,9.58) were reported.
Comorbidity
The paper by Dash et al. (2020) highlight adolescent with a disease who needs routine medical pain treatment have higher risk of opioid misuse [ 38 ]. The adolescents who have disorder symptoms may have a risk for opioid misuse despite for the pain intensity.
Individual’s attitudes and perceptions
In a study conducted in three Latin America countries (Argentina, Chile, and Uruguay), it was shown that adolescents with low or no perceived risk of taking marijuana had a higher risk of abuse (OR = 8.22 times, 95% CI 7.56, 10.30) [ 35 ]. This finding is in line with another study that investigated 2002 adolescents and concluded that perceiving the drug as harmless was an independent risk factor that could prospectively predict future marijuana abuse [ 27 ]. Moreover, some youth interviewed perceived that they gained benefits from substance use [ 38 ]. The focus group discussion summarized that the youth felt positive personal motivation and could escape from a negative state by taking drugs. Apart from that, adolescents who had high-perceived availability of drugs in their neighborhoods were more likely to increase their usage of marijuana over time (OR = 11.00, 95% CI 9.11, 13.27) [ 35 ]. A cheap price of the substance and the availability of drug dealers around schools were factors for youth accessibility [ 38 ]. Perceived drug accessibility has also been linked with the authorities’ enforcement programs. The youth perception of a lax community enforcement of laws regarding drug use at all-time points predicted an increase in marijuana use in the subsequent assessment period [ 27 ]. Besides perception, a study examining the attitudes towards synthetic drugs based on 8076 probabilistic samples of Macau students found that the odds of the lifetime use of marijuana was almost three times higher among those with a strong attitude towards the use of synthetic drugs [ 32 ]. In addition, total screen time among the adolescent increase the likelihood of frequent cannabis use. Those who reported daily cannabis use have a mean of 12.56 h of total screen time, compared to a mean of 6.93 h among those who reported no cannabis use. Adolescent with more time on internet use, messaging, playing video games and watching TV/movies were significantly associated with more frequent cannabis use [ 44 ].
Protective factors
Individual traits.
Some individual traits have been determined to protect adolescents from developing drug abuse habits. A study by Marin et al. found that youth with an optimistic trait were less likely to become drug dependent [ 33 ]. In this study involving 1104 Iranian students, it was concluded that a higher optimism score (measured using the Children Attributional Style Questionnaire, CASQ) was a protective factor against illicit drug use (OR = 0.90, 95% CI: 0.85–0.95). Another study found that high levels of mindfulness, measured using the 25-item Child Acceptance and Mindfulness Measure, CAMM, lead to a slower progression toward injectable drug abuse among youth with opioid addiction (1.67 years, p = .041) [ 37 ]. In addition, the social phobia trait was found to have a negative association with marijuana use (OR = 0.87, 95% CI 0.77–0.97), as suggested [ 31 ].
According to El Kazdouh et al., individuals with a strong belief against substance use and those with a strong desire to maintain their health were more likely to be protected from involvement in drug abuse [ 46 ].
DOMAIN: family factors
The biological factors underlying drug abuse in adolescents have been reported in several studies. Epigenetic studies are considered important, as they can provide a good outline of the potential pre-natal factors that can be targeted at an earlier stage. Expecting mothers who smoke tobacco and alcohol have an indirect link with adolescent substance abuse in later life [ 24 , 39 ]. Moreover, the dynamic relationship between parents and their children may have some profound effects on the child’s growth. Luk et al. examined the mediator effects between parenting style and substance abuse and found the maternal psychological control dimension to be a significant variable [ 26 ]. The mother’s psychological control was two times higher in influencing her children to be involved in substance abuse compared to the other dimension. Conversely, an indirect risk factor towards youth drug abuse was elaborated in a study in which low parental educational level predicted a greater risk of future drug abuse by reducing the youth’s perception of harm [ 27 , 43 ]. Negligence from a parental perspective could also contribute to this problem. According to El Kazdouh et al. [ 46 ], a lack of parental supervision, uncontrolled pocket money spending among children, and the presence of substance-using family members were the most common negligence factors.
While the maternal factors above were shown to be risk factors, the opposite effect was seen when the paternal figure equipped himself with sufficient knowledge. A study found that fathers with good information and awareness were more likely to protect their adolescent children from drug abuse [ 26 ]. El Kazdouh et al. noted that support and advice could be some of the protective factors in this area [ 46 ].
DOMAIN: community factors
- Risk factor
A study in 2017 showed a positive association between adolescent drug abuse and peers who abuse drugs [ 32 , 39 ]. It was estimated that the odds of becoming a lifetime marijuana user was significantly increased by a factor of 2.5 ( p < 0.001) among peer groups who were taking synthetic drugs. This factor served as peer pressure for youth, who subconsciously had desire to be like the others [ 38 ]. The impact of availability and engagement in structured and unstructured activities also play a role in marijuana use. The findings from Spillane (2000) found that the availability of unstructured activities was associated with increased likelihood of marijuana use [ 42 ].
- Protective factor
Strong religious beliefs integrated into society serve as a crucial protective factor that can prevent adolescents from engaging in drug abuse [ 38 , 45 ]. In addition, the school connectedness and adult support also play a major contribution in the drug use [ 40 ].
The goal of this review was to identify and classify the risks and protective factors that lead adolescents to drug abuse across the three important domains of the individual, family, and community. No findings conflicted with each other, as each of them had their own arguments and justifications. The findings from our review showed that individual factors were the most commonly highlighted. These factors include individual traits, significant negative growth exposure, personal psychiatric diagnosis, previous substance and addiction history, and an individual’s attitude and perception as risk factors.
Within the individual factor domain, nine articles were found to contribute to the subdomain of personal/ individual traits [ 27 , 28 , 29 , 37 , 38 , 39 , 40 , 43 , 44 ]. Despite the heterogeneity of the study designs and the substances under investigation, all of the papers found statistically significant results for the possible risk factors of adolescent drug abuse. The traits of high impulsivity, rebelliousness, difficulty in regulating emotions, and alexithymia can be considered negative characteristic traits. These adolescents suffer from the inability to self-regulate their emotions, so they tend to externalize their behaviors as a way to avoid or suppress the negative feelings that they are experiencing [ 41 , 47 , 48 ]. On the other hand, engaging in such behaviors could plausibly provide a greater sense of positive emotions and make them feel good [ 49 ]. Apart from that, evidence from a neurophysiological point of view also suggests that the compulsive drive toward drug use is complemented by deficits in impulse control and decision making (impulsive trait) [ 50 ]. A person’s ability in self-control will seriously impaired with continuous drug use and will lead to the hallmark of addiction [ 51 ].
On the other hand, there are articles that reported some individual traits to be protective for adolescents from engaging in drug abuse. Youth with the optimistic trait, a high level of mindfulness, and social phobia were less likely to become drug dependent [ 31 , 33 , 37 ]. All of these articles used different psychometric instruments to classify each individual trait and were mutually exclusive. Therefore, each trait measured the chance of engaging in drug abuse on its own and did not reflect the chance at the end of the spectrum. These findings show that individual traits can be either protective or risk factors for the drugs used among adolescents. Therefore, any adolescent with negative personality traits should be monitored closely by providing health education, motivation, counselling, and emotional support since it can be concluded that negative personality traits are correlated with high risk behaviours such as drug abuse [ 52 ].
Our study also found that a history of maltreatment has a positive association with adolescent drug abuse. Those adolescents with episodes of maltreatment were considered to have negative growth exposure, as their childhoods were negatively affected by traumatic events. Some significant associations were found between maltreatment and adolescent drug abuse, although the former factor was limited to the female gender [ 25 , 30 , 36 ]. One possible reason for the contrasting results between genders is the different sample populations, which only covered child welfare centers [ 36 ] and foster care [ 30 ]. Regardless of the place, maltreatment can happen anywhere depending on the presence of the perpetrators. To date, evidence that concretely links maltreatment and substance abuse remains limited. However, a plausible explanation for this link could be the indirect effects of posttraumatic stress (i.e., a history of maltreatment) leading to substance use [ 53 , 54 ]. These findings highlight the importance of continuous monitoring and follow-ups with adolescents who have a history of maltreatment and who have ever attended a welfare center.
Addiction sometimes leads to another addiction, as described by the findings of several studies [ 29 , 34 ]. An initial study focused on the effects of e-cigarettes in the development of other substance abuse disorders, particularly those related to marijuana, alcohol, and commonly prescribed medications [ 34 ]. The authors found that the use of e-cigarettes can lead to more severe substance addiction [ 55 ], possibly through normalization of the behavior. On the other hand, Chuang et al.’s extensive study in 2017 analyzed the combined effects of either multiple addictions alone or a combination of multiple addictions together with the impulsivity trait [ 29 ]. The outcomes reported were intriguing and provide the opportunity for targeted intervention. The synergistic effects of impulsiveness and three other substance addictions (marijuana, tobacco, and alcohol) substantially increased the likelihood for drug abuse from 3.46 (95%CI 1.25, 9.58) to 10.13 (95% CI 3.95, 25.95). Therefore, proper rehabilitation is an important strategy to ensure that one addiction will not lead to another addiction.
The likelihood for drug abuse increases as the population perceives little or no harmful risks associated with the drugs. On the opposite side of the coin, a greater perceived risk remains a protective factor for marijuana abuse [ 56 ]. However, another study noted that a stronger determinant for adolescent drug abuse was the perceived availability of the drug [ 35 , 57 ]. Looking at the bigger picture, both perceptions corroborate each other and may inform drug use. Another study, on the other hand, reported that there was a decreasing trend of perceived drug risk in conjunction with the increasing usage of drugs [ 58 ]. As more people do drugs, youth may inevitably perceive those drugs as an acceptable norm without any harmful consequences [ 59 ].
In addition, the total spent for screen time also contribute to drug abuse among adolescent [ 43 ]. This scenario has been proven by many researchers on the effect of screen time on the mental health [ 60 ] that leads to the substance use among the adolescent due to the ubiquity of pro-substance use content on the internet. Adolescent with comorbidity who needs medical pain management by opioids also tend to misuse in future. A qualitative exploration on the perspectives among general practitioners concerning the risk of opioid misuse in people with pain, showed pain management by opioids is a default treatment and misuse is not a main problem for the them [ 61 ]. A careful decision on the use of opioids as a pain management should be consider among the adolescents and their understanding is needed.
Within the family factor domain, family structures were found to have both positive and negative associations with drug abuse among adolescents. As described in one study, paternal knowledge was consistently found to be a protective factor against substance abuse [ 26 ]. With sufficient knowledge, the father can serve as the guardian of his family to monitor and protect his children from negative influences [ 62 ]. The work by Luk et al. also reported a positive association of maternal psychological association towards drug abuse (IRR 2.41, p < 0.05) [ 26 ]. The authors also observed the same effect of paternal psychological control, although it was statistically insignificant. This construct relates to parenting style, and the authors argued that parenting style might have a profound effect on the outcomes under study. While an earlier literature review [ 63 ] also reported such a relationship, a recent study showed a lesser impact [ 64 ] with regards to neglectful parenting styles leading to poorer substance abuse outcomes. Nevertheless, it was highlighted in another study that the adolescents’ perception of a neglectful parenting style increased their odds (OR 2.14, p = 0.012) of developing alcohol abuse, not the parenting style itself [ 65 ]. Altogether, families play vital roles in adolescents’ risk for engaging in substance abuse [ 66 ]. Therefore, any intervention to impede the initiation of substance use or curb existing substance use among adolescents needs to include parents—especially improving parent–child communication and ensuring that parents monitor their children’s activities.
Finally, the community also contributes to drug abuse among adolescents. As shown by Li et al. [ 32 ] and El Kazdouh et al. [ 46 ], peers exert a certain influence on other teenagers by making them subconsciously want to fit into the group. Peer selection and peer socialization processes might explain why peer pressure serves as a risk factor for drug-abuse among adolescents [ 67 ]. Another study reported that strong religious beliefs integrated into society play a crucial role in preventing adolescents from engaging in drug abuse [ 46 ]. Most religions devalue any actions that can cause harmful health effects, such as substance abuse [ 68 ]. Hence, spiritual beliefs may help protect adolescents. This theme has been well established in many studies [ 60 , 69 , 70 , 71 , 72 ] and, therefore, could be implemented by religious societies as part of interventions to curb the issue of adolescent drug abuse. The connection with school and structured activity did reduce the risk as a study in USA found exposure to media anti-drug messages had an indirect negative effect on substances abuse through school-related activity and social activity [ 73 ]. The school activity should highlight on the importance of developmental perspective when designing and offering school-based prevention programs [75].
Limitations
We adopted a review approach that synthesized existing evidence on the risk and protective factors of adolescents engaging in drug abuse. Although this systematic review builds on the conclusion of a rigorous review of studies in different settings, there are some potential limitations to this work. We may have missed some other important factors, as we only included English articles, and article extraction was only done from the three search engines mentioned. Nonetheless, this review focused on worldwide drug abuse studies, rather than the broader context of substance abuse including alcohol and cigarettes, thereby making this paper more focused.
Conclusions
This review has addressed some recent knowledge related to the individual, familial, and community risk and preventive factors for adolescent drug use. We suggest that more attention should be given to individual factors since most findings were discussed in relation to such factors. With the increasing trend of drug abuse, it will be critical to focus research specifically on this area. Localized studies, especially those related to demographic factors, may be more effective in generating results that are specific to particular areas and thus may be more useful in generating and assessing local control and prevention efforts. Interventions using different theory-based psychotherapies and a recognition of the unique developmental milestones specific to adolescents are among examples that can be used. Relevant holistic approaches should be strengthened not only by relevant government agencies but also by the private sector and non-governmental organizations by promoting protective factors while reducing risk factors in programs involving adolescents from primary school up to adulthood to prevent and control drug abuse. Finally, legal legislation and enforcement against drug abuse should be engaged with regularly as part of our commitment to combat this public health burden.
Data availability and materials
All data generated or analysed during this study are included in this published article.
Nation, U. World Drug Report 2018 (United Nations publication, Sales No. E.18X.XI.9. United Nation publication). 2018. Retrieved from https://www.unodc.org/wdr2018
Google Scholar
Degenhardt L, Stockings E, Patton G, Hall WD, Lynskey M. The increasing global health priority of substance use in young people. Lancet Psychiatry. 2016;3(3):251–64. https://doi.org/10.1016/S2215-0366(15)00508-8 Elsevier Ltd.
Article PubMed Google Scholar
Ritchie H, Roser M. Drug Use - Our World in Data: Global Change Data Lab; 2019. https://ourworldindata.org/drug-use [10 June 2020]
Holm S, Sandberg S, Kolind T, Hesse M. The importance of cannabis culture in young adult cannabis use. J Subst Abus. 2014;19(3):251–6.
Luikinga SJ, Kim JH, Perry CJ. Developmental perspectives on methamphetamine abuse: exploring adolescent vulnerabilities on brain and behavior. Progress Neuro Psychopharmacol Biol Psychiatry. 2018;87(Pt A):78–84. https://doi.org/10.1016/j.pnpbp.2017.11.010 Elsevier Inc.
Article CAS Google Scholar
Ismail R, Ghazalli MN, Ibrahim N. Not all developmental assets can predict negative mental health outcomes of disadvantaged youth: a case of suburban Kuala Lumpur. Mediterr J Soc Sci. 2015;6(1):452–9. https://doi.org/10.5901/mjss.2015.v6n5s1p452 .
Article Google Scholar
Crews F, He J, Hodge C. Adolescent cortical development: a critical period of vulnerability for addiction. Pharmacol Biochem Behav. 2007;86(2):189–99. https://doi.org/10.1016/j.pbb.2006.12.001 .
Article CAS PubMed Google Scholar
Schulte MT, Hser YI. Substance use and associated health conditions throughout the lifespan. Public Health Rev. 2013;35(2). https://doi.org/10.1007/bf03391702 Technosdar Ltd.
Somani, S.; Meghani S. Substance Abuse among Youth: A Harsh Reality 2016. doi: https://doi.org/10.4172/2165-7548.1000330 , 6, 4.
Book Google Scholar
Drabble L, Trocki KF, Klinger JL. Religiosity as a protective factor for hazardous drinking and drug use among sexual minority and heterosexual women: findings from the National Alcohol Survey. Drug Alcohol Depend. 2016;161:127–34. https://doi.org/10.1016/j.drugalcdep.2016.01.022 .
Article PubMed PubMed Central Google Scholar
Goliath V, Pretorius B. Peer risk and protective factors in adolescence: Implications for drug use prevention. Soc Work. 2016;52(1):113–29. https://doi.org/10.15270/52-1-482 .
Guerrero LR, Dudovitz R, Chung PJ, Dosanjh KK, Wong MD. Grit: a potential protective factor against substance use and other risk behaviors among Latino adolescents. Acad Pediatr. 2016;16(3):275–81. https://doi.org/10.1016/j.acap.2015.12.016 .
National Institutes on Drug Abuse. What are risk factors and protective factors? National Institute on Drug Abuse (NIDA); 2003. Retrieved from https://www.drugabuse.gov/publications/preventing-drug-use-among-children-adolescents/chapter-1-risk-factors-protective-factors/what-are-risk-factors
Nguyen NN, Newhill CE. The role of religiosity as a protective factor against marijuana use among African American, White, Asian, and Hispanic adolescents. J Subst Abus. 2016;21(5):547–52. https://doi.org/10.3109/14659891.2015.1093558 .
Schinke S, Schwinn T, Hopkins J, Wahlstrom L. Drug abuse risk and protective factors among Hispanic adolescents. Prev Med Rep. 2016;3:185–8. https://doi.org/10.1016/j.pmedr.2016.01.012 .
Macleod J, Oakes R, Copello A, Crome PI, Egger PM, Hickman M, et al. Psychological and social sequelae of cannabis and other illicit drug use by young people: a systematic review of longitudinal, general population studies. Lancet. 2004;363(9421):1579–88. https://doi.org/10.1016/S0140-6736(04)16200-4 .
Moore TH, Zammit S, Lingford-Hughes A, Barnes TR, Jones PB, Burke M, et al. Cannabis use and risk of psychotic or affective mental health outcomes: a systematic review. Lancet. 2007;370(9584):319–28. https://doi.org/10.1016/S0140-6736(07)61162-3 .
Semple DM, McIntosh AM, Lawrie SM. Cannabis as a risk factor for psychosis: systematic review. J Psychopharmacol. 2005;19(2):187–94. https://doi.org/10.1177/0269881105049040 .
Nargiso JE, Ballard EL, Skeer MR. A systematic review of risk and protective factors associated with nonmedical use of prescription drugs among youth in the united states: A social ecological perspective. J Stud Alcohol Drugs. 2015;76(1):5–20. https://doi.org/10.15288/jsad.2015.76.5 .
Guxensa M, Nebot M, Ariza C, Ochoa D. Factors associated with the onset of cannabis use: a systematic review of cohort studies. Gac Sanit. 2007;21(3):252–60. https://doi.org/10.1157/13106811 .
Susan MS, Peter SA, Dakshitha W, George CP. The age of adolescence. Lancet Child Adolesc Health. 2018;2(Issue 3):223–8. https://doi.org/10.1016/S2352-4642(18)30022-1 .
Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The mixed methods appraisal tool (MMAT) version 2018 for information professionals and researchers. Educ Inf. 2018;34(4):285–91. https://doi.org/10.3233/EFI-180221 .
McHugh ML. Interrater reliability: The kappa statistic. Biochem Med. 2012;22(3):276–82. https://doi.org/10.11613/bm.2012.031 .
Cecil CAM, Walton E, Smith RG, Viding E, McCrory EJ, Relton CL, et al. DNA methylation and substance-use risk: a prospective, genome-wide study spanning gestation to adolescence. Transl Psychiatry. 2016;6(12):e976. https://doi.org/10.1038/tp.2016.247 Nature Publishing Group.
Article CAS PubMed PubMed Central Google Scholar
Kobulsky JM. Gender differences in pathways from physical and sexual abuse to early substance use. Child Youth Serv Rev. 2017;83:25–32. https://doi.org/10.1016/j.childyouth.2017.10.027 .
Luk JW, King KM, McCarty CA, McCauley E, Stoep A. Prospective effects of parenting on substance use and problems across Asian/Pacific islander and European American youth: Tests of moderated mediation. J Stud Alcohol Drugs. 2017;78(4):521–30. https://doi.org/10.15288/jsad.2017.78.521 .
Guttmannova K, Skinner ML, Oesterle S, White HR, Catalano RF, Hawkins JD. The interplay between marijuana-specific risk factors and marijuana use over the course of adolescence. Prev Sci. 2019;20(2):235–45. https://doi.org/10.1007/s11121-018-0882-9 .
Dorard G, Bungener C, Phan O, Edel Y, Corcos M, Berthoz S. Is alexithymia related to cannabis use disorder? Results from a case-control study in outpatient adolescent cannabis abusers. J Psychosom Res. 2017;95:74–80. https://doi.org/10.1016/j.jpsychores.2017.02.012 .
Chuang CWI, Sussman S, Stone MD, Pang RD, Chou CP, Leventhal AM, et al. Impulsivity and history of behavioral addictions are associated with drug use in adolescents. Addict Behav. 2017;74:41–7. https://doi.org/10.1016/j.addbeh.2017.05.021 .
Gabrielli J, Jackson Y, Brown S. Associations between maltreatment history and severity of substance use behavior in youth in Foster Care. Child Maltreat. 2016;21(4):298–307. https://doi.org/10.1177/1077559516669443 .
Khoddam R, Jackson NJ, Leventhal AM. Internalizing symptoms and conduct problems: redundant, incremental, or interactive risk factors for adolescent substance use during the first year of high school? Drug Alcohol Depend. 2016;169:48–55. https://doi.org/10.1016/j.drugalcdep.2016.10.007 .
Li SD, Zhang X, Tang W, Xia Y. Predictors and implications of synthetic drug use among adolescents in the gambling Capital of China. SAGE Open. 2017;7(4):215824401773303. https://doi.org/10.1177/2158244017733031 .
Marin S, Heshmatian E, Nadrian H, Fakhari A, Mohammadpoorasl A. Associations between optimism, tobacco smoking and substance abuse among Iranian high school students. Health Promot Perspect. 2019;9(4):279–84. https://doi.org/10.15171/hpp.2019.38 .
Miech RA, O’Malley PM, Johnston LD, Patrick ME. E-cigarettes and the drug use patterns of adolescents. Nicotine Tob Res. 2015;18(5):654–9. https://doi.org/10.1093/ntr/ntv217 .
Schleimer JP, Rivera-Aguirre AE, Castillo-Carniglia A, Laqueur HS, Rudolph KE, Suárez H, et al. Investigating how perceived risk and availability of marijuana relate to marijuana use among adolescents in Argentina, Chile, and Uruguay over time. Drug Alcohol Depend. 2019;201:115–26. https://doi.org/10.1016/j.drugalcdep.2019.03.029 .
Traube DE, Yarnell LM, Schrager SM. Differences in polysubstance use among youth in the child welfare system: toward a better understanding of the highest-risk teens. Child Abuse Negl. 2016;52:146–57. https://doi.org/10.1016/j.chiabu.2015.11.020 .
Wilson JD, Vo H, Matson P, Adger H, Barnett G, Fishman M. Trait mindfulness and progression to injection use in youth with opioid addiction. Subst Use Misuse. 2017;52(11):1486–93. https://doi.org/10.1080/10826084.2017.1289225 .
Dash GF, Feldstein Ewing SW, Murphy C, Hudson KA, Wilson AC. Contextual risk among adolescents receiving opioid prescriptions for acute pain in pediatric ambulatory care settings. Addict Behav. 2020;104:106314. https://doi.org/10.1016/j.addbeh.2020.106314 Epub 2020 Jan 11. PMID: 31962289; PMCID: PMC7024039.
Osborne V, Serdarevic M, Striley CW, Nixon SJ, Winterstein AG, Cottler LB. Age of first use of prescription opioids and prescription opioid non-medical use among older adolescents. Substance Use Misuse. 2020;55(14):2420–7. https://doi.org/10.1080/10826084.2020.1823420 .
Zuckermann AME, Qian W, Battista K, Jiang Y, de Groh M, Leatherdale ST. Factors influencing the non-medical use of prescription opioids among youth: results from the COMPASS study. J Subst Abus. 2020;25(5):507–14. https://doi.org/10.1080/14659891.2020.1736669 .
De Pedro KT, Esqueda MC, Gilreath TD. School protective factors and substance use among lesbian, gay, and bisexual adolescents in California public schools. LGBT Health. 2017;4(3):210–6. https://doi.org/10.1089/lgbt.2016.0132 .
Spillane NS, Schick MR, Kirk-Provencher KT, Hill DC, Wyatt J, Jackson KM. Structured and unstructured activities and alcohol and marijuana use in middle school: the role of availability and engagement. Substance Use Misuse. 2020;55(11):1765–73. https://doi.org/10.1080/10826084.2020.1762652 .
Ogunsola OO, Fatusi AO. Risk and protective factors for adolescent substance use: a comparative study of secondary school students in rural and urban areas of Osun state, Nigeria. Int J Adolesc Med Health. 2016;29(3). https://doi.org/10.1515/ijamh-2015-0096 .
Doggett A, Qian W, Godin K, De Groh M, Leatherdale ST. Examining the association between exposure to various screen time sedentary behaviours and cannabis use among youth in the COMPASS study. SSM Population Health. 2019;9:100487. https://doi.org/10.1016/j.ssmph.2019.100487 .
Afifi RA, El Asmar K, Bteddini D, Assi M, Yassin N, Bitar S, et al. Bullying victimization and use of substances in high school: does religiosity moderate the association? J Relig Health. 2020;59(1):334–50. https://doi.org/10.1007/s10943-019-00789-8 .
El Kazdouh H, El-Ammari A, Bouftini S, El Fakir S, El Achhab Y. Adolescents, parents and teachers’ perceptions of risk and protective factors of substance use in Moroccan adolescents: a qualitative study. Substance Abuse Treat Prevent Policy. 2018;13(1):–31. https://doi.org/10.1186/s13011-018-0169-y .
Sussman S, Lisha N, Griffiths M. Prevalence of the addictions: a problem of the majority or the minority? Eval Health Prof. 2011;34(1):3–56. https://doi.org/10.1177/0163278710380124 .
Aldao A, Nolen-Hoeksema S, Schweizer S. Emotion-regulation strategies across psychopathology: a meta-analytic review. Clin Psychol Rev. 2010;30(2):217–37. https://doi.org/10.1016/j.cpr.2009.11.004 .
Ricketts T, Macaskill A. Gambling as emotion management: developing a grounded theory of problem gambling. Addict Res Theory. 2003;11(6):383–400. https://doi.org/10.1080/1606635031000062074 .
Williams AD, Grisham JR. Impulsivity, emotion regulation, and mindful attentional focus in compulsive buying. Cogn Ther Res. 2012;36(5):451–7. https://doi.org/10.1007/s10608-011-9384-9 .
National Institutes on Drug Abuse. Drugs, brains, and behavior the science of addiction national institute on drug abuse (nida). 2014. Retrieved from https://www.drugabuse.gov/sites/default/files/soa_2014.pdf
Hokm Abadi ME, Bakhti M, Nazemi M, Sedighi S, Mirzadeh Toroghi E. The relationship between personality traits and drug type among substance abuse. J Res Health. 2018;8(6):531–40.
Longman-Mills S, Haye W, Hamilton H, Brands B, Wright MGM, Cumsille F, et al. Psychological maltreatment and its relationship with substance abuse among university students in Kingston, Jamaica, vol. 24. Florianopolis: Texto Contexto Enferm; 2015. p. 63–8.
Rosenkranz SE, Muller RT, Henderson JL. The role of complex PTSD in mediating childhood maltreatment and substance abuse severity among youth seeking substance abuse treatment. Psychol Trauma Theory Res Pract Policy. 2014;6(1):25–33. https://doi.org/10.1037/a0031920 .
Krishnan-Sarin S, Morean M, Kong G, et al. E-Cigarettes and “dripping” among high-school youth. Pediatrics. 2017;139(3). https://doi.org/10.1542/peds.2016-3224 .
Adinoff B. Neurobiologic processes in drug reward and addiction. Harvard review of psychiatry. NIH Public Access. 2004;12(6):305–20. https://doi.org/10.1080/10673220490910844 .
Kandel D, Kandel E. The gateway hypothesis of substance abuse: developmental, biological and societal perspectives. Acta Paediatrica. 2014;104(2):130–7.
Dempsey RC, McAlaney J, Helmer SM, Pischke CR, Akvardar Y, Bewick BM, et al. Normative perceptions of Cannabis use among European University students: associations of perceived peer use and peer attitudes with personal use and attitudes. J Stud Alcohol Drugs. 2016;77(5):740–8.
Cioffredi L, Kamon J, Turner W. Effects of depression, anxiety and screen use on adolescent substance use. Prevent Med Rep. 2021;22:101362. https://doi.org/10.1016/j.pmedr.2021.101362 .
Luckett T, NewtonJohn T, Phillips J, et al. Risk of opioid misuse in people with cancer and pain and related clinical considerations:a qualitative study of the perspectives of Australian general practitioners. BMJ Open. 2020;10(2):e034363. https://doi.org/10.1136/bmjopen-2019-034363 .
Lipari RN. Trends in Adolescent Substance Use and Perception of Risk from Substance Use. The CBHSQ Report. Substance Abuse Mental Health Serv Admin. 2013; Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/27656743 .
Muchiri BW, dos Santos MML. Family management risk and protective factors for adolescent substance use in South Africa. Substance Abuse. 2018;13(1):24. https://doi.org/10.1186/s13011-018-0163-4 .
Becoña E, Martínez Ú, Calafat A, Juan M, Fernández-Hermida JR, Secades-Villa R. Parental styles and drug use: a review. In: Drugs: Education, Prevention and Policy: Taylor & Francis; 2012. https://doi.org/10.3109/09687637.2011.631060 .
Berge J, Sundel K, Ojehagen A, Hakansson A. Role of parenting styles in adolescent substance use: results from a Swedish longitudinal cohort study. BMJ Open. 2016;6(1):e008979. https://doi.org/10.1136/bmjopen-2015-008979 .
Opara I, Lardier DT, Reid RJ, Garcia-Reid P. “It all starts with the parents”: a qualitative study on protective factors for drug-use prevention among black and Hispanic girls. Affilia J Women Soc Work. 2019;34(2):199–218. https://doi.org/10.1177/0886109918822543 .
Martínez-Loredo V, Fernández-Artamendi S, Weidberg S, Pericot I, López-Núñez C, Fernández-Hermida J, et al. Parenting styles and alcohol use among adolescents: a longitudinal study. Eur J Invest Health Psychol Educ. 2016;6(1):27–36. https://doi.org/10.1989/ejihpe.v6i1.146 .
Baharudin MN, Mohamad M, Karim F. Drug-abuse inmates maqasid shariah quality of lifw: a conceotual paper. Hum Soc Sci Rev. 2020;8(3):1285–94. https://doi.org/10.18510/hssr.2020.83131 .
Henneberger AK, Mushonga DR, Preston AM. Peer influence and adolescent substance use: a systematic review of dynamic social network research. Adolesc Res Rev. 2020;6(1):57–73. https://doi.org/10.1007/s40894-019-00130-0 Springer.
Gomes FC, de Andrade AG, Izbicki R, Almeida AM, de Oliveira LG. Religion as a protective factor against drug use among Brazilian university students: a national survey. Rev Bras Psiquiatr. 2013;35(1):29–37. https://doi.org/10.1016/j.rbp.2012.05.010 .
Kulis S, Hodge DR, Ayers SL, Brown EF, Marsiglia FF. Spirituality and religion: intertwined protective factors for substance use among urban American Indian youth. Am J Drug Alcohol Abuse. 2012;38(5):444–9. https://doi.org/10.3109/00952990.2012.670338 .
Miller L, Davies M, Greenwald S. Religiosity and substance use and abuse among adolescents in the national comorbidity survey. J Am Acad Child Adolesc Psychiatry. 2000;39(9):1190–7. https://doi.org/10.1097/00004583-200009000-00020 .
Moon SS, Rao U. Social activity, school-related activity, and anti-substance use media messages on adolescent tobacco and alcohol use. J Hum Behav Soc Environ. 2011;21(5):475–89. https://doi.org/10.1080/10911359.2011.566456 .
Simone A. Onrust, Roy Otten, Jeroen Lammers, Filip smit, school-based programmes to reduce and prevent substance use in different age groups: what works for whom? Systematic review and meta-regression analysis. Clin Psychol Rev. 2016;44:45–59. https://doi.org/10.1016/j.cpr.2015.11.002 .
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The authors acknowledge The Ministry of Higher Education Malaysia and The Universiti Kebangsaan Malaysia, (UKM) for funding this study under the Long-Term Research Grant Scheme-(LGRS/1/2019/UKM-UKM/2/1). We also thank the team for their commitment and tireless efforts in ensuring that manuscript was well executed.
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Nawi, A.M., Ismail, R., Ibrahim, F. et al. Risk and protective factors of drug abuse among adolescents: a systematic review. BMC Public Health 21 , 2088 (2021). https://doi.org/10.1186/s12889-021-11906-2
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