Table 2.

Study characteristic and main findings

No	Year	Authors/ Country	Study objectives	Study design	Types of substance abuse	Result / findings Risk factors /Protective factors	Conclusion
1	2020	Dash et al. (USA)	To capture a time-sensitive report of the intersection of prescription opioid receipt and contextual risks for opioid misuse related to pain experience, mental health symptoms, and substance use at the adolescent and parental levels.	Cross-sectional	Opiod	Risk Factors 1) Pain catastrophe 2) Mother history of chronic pain (parents reported keeping opioids at home) and parent anxiety	Opioids at home as a risk factors for adolescent misuse
2	2020	Osborne et al. (USA)	To examine peer influence and parental guidance, in addition to peer and parental sources of alcohol, on patterns of prescription opioid use	Cross-sectional	Opiod	Risk factors 1) Close friend who used other substances 2) Alcoholic parents Protective Factors 1) Increased number of close friends	Increased number of close friends was a protective factor against prescription opioid
3	2020	Zuckermann et al.(Canada)	To investigate demographic and behavioral risk factors for non-medical use of prescription opioids.	Cross-sectional study	Opiod: oxycodone, fentanyl, other prescription pain relievers	Risk factors 1) lack of homework completion Protective Factors 1) School connectedness	School connectedness may lower the risk of non-medical use of prescription opioids, indicating that a school-based focus is justified.
4	2020	Spillane et al. (USA)	To examines the role of perceived availability and engagement in structured and unstructured activities on adolescent alcohol and marijuana use controlling for substance availability	Cross sectional	Marijuana	Risk Factors 1) Availability of unstructured activities	Perceived availability of and engagement in unstructured activities may present a risk, while perceived availability of and engagement in structured activities may serve as a protective factor for youth substance use
5	2020	Afifi et al.(Beirut)	To explore the association between bullying victimization and substance use in adolescents with low and high levels of religiosity.	Cross-sectional	Substance use	Risk Factors 1) Lower religiosity levels who had been bullied	Religiosity may be a potential moderator of the association between being bullied and substance use
6	2019	Marin S et al. (Iran)	To examine the relationship between optimistic explanatory style and cigarette smoking, hookah smoking, and illicit drug use among high school students in Sonqor county, Iran	Cross-sectional	Opium Cannabis Ecstasy Methamphetamine	Protective Factors 1) Optimism trait of an individual measured using Children Attributional Style Questionnaire (CASQ). 2) Higher scores of optimism protected students from using illicit drugs (Model 3: OR = 0.90, 95% CI: 0.85–0.95, P < 0.001). 3) Negative-stability and negative-globality domains of optimism were significantly higher among advanced-stage smokers and illicit drug users.	Optimism was found to be a protective factor against substance abuse.
7	2019	Schleimer et al. (Latin America: Chile, Uruguay, and Argentina)	1) To estimate associations between perceived availability and perceived risk of marijuana use and past-month marijuana use 2) To describe how these associations changed over time	Cross-sectional	Marijuana	Risk Factors 1) No/ Low perceived risk increase the odds of past-month marijuana use by 8.22 times compared to those who perceived moderate/great risk. 2) High perceived availability of drug: consistently associated with higher odds of past-month marijuana use. Protective Factors 1) Moderate/ High perceived risk of substance use. 2) Low perceived availability	Perceived risk and availability of marijuana are significant risk factors for adolescent marijuana use in the Southern Cone.
8	2019	Guttmannova et al. (USA)	To examine a set of marijuana-specific risk factors from multiple domains of development for marijuana use over the course of adolescence	Community Randomized-Controlled Trial	Marijuana	Risk Factors 1) Perception of lax community enforcement of marijuana laws regarding adolescent use 2) Low perception of harm 3) Rebelliousness traits 4) Parents with low education	A greater frequency of marijuana use was predicted among the identified risk factors.
9	2019	Doggett et al. (Canada)	To examine the association between various types of screen time sedentary behavior (STSBs) and cannabis use	Cross-sectional	Cannabis	Risk Factors 1) Total screen time sedentary behavior (internet use, messaging, playing video games, watching TV	STSB is a risk factor for the tendency for individuals to use substances as a coping mechanism.
10	2017	Wilson et al. (USA)	To examine associations among levels of trait mindfulness and opioid use behaviors.	Cross sectional	Opioid	- Study using a convenience sample of 112 youth (ages 14–24) was recruited during an episode of inpatient detoxification and residential treatment for opioid use disorders. - Youth had difficulties in emotion regulation (m = 104.2; SD = 2.41) and low mindfulness (m = 19.1; SD = 0.59). Risk Factors 1) Difficulty in regulating emotions Protective Factors 1) High level of mindfulness	Majority of youth presenting with opioid use disorders have impairments in emotion regulation and deficits in trait mindfulness.
11	2017	Li et al. (Macau)	To identify culturally relevant predictors of synthetic drug use among adolescents in Macao.	Cross sectional	Ketamine Ecstasy/MDMA Methamphetamine Tranquilizers Hybrid synthetic drugs	- The rates of synthetic use among male adolescents were higher than those among female adolescents for lifetime use (1.79% vs. 1.04%), past-year use (1.29% vs. 0.70%), and past-month use (1.03% vs. 0.44%). - Synthetic drug use was the most prevalent among fifth and sixth graders at the elementary school level. Risk Factors 1) Peer usage 2) Recreational use of time 3) Attitudes towards synthetic drugs 4) Availability of synthetic drugs	The investigated risk factors contribute to adolescent drug abuse.
12	2017	Luk et al. (USA)	To examine both direct and indirect effects of multiple parenting dimensions on substance use behaviors across Asian-Pacific Islander (API) and European American youth.	Prospective Cohort	Marijuana	- Mother’s knowledge predicted fewer externalizing problems in Grade 8, which in turn predicted fewer substance use problems in Grades 9 and 12. - Father’s warmth predicted better academic achievement in Grade 8, which in turn predicted fewer substance use problems in Grades 9 and 12, as well as alcohol and marijuana dependence in Grade 12. Risk Factors 1) Mother’s psychological control Protective Factors 1) Father’s knowledge	Promoting father’s knowledge of adolescents’ whereabouts can reduce substance use risks among both European and API Americans.
13	2017	De Pedro et al. (USA)	This study aims to fill this gap in the literature and inform programs aimed at reducing substance use among LGB youth	Cross-sectional	Marijuana, inhalants, prescription pain medication, and other illegal drugs	Protective Factors 1) school connectedness and school adult support	The results indicate a need for substance use prevention programs that integrate school connectedness and adult support in school
14	2017	Dorard et al. (France)	To investigate alexithymia in young outpatient cannabis misusers to determine whether the levels of alexithymia and the state and traits of anxiety and depression predict cannabis misuse by adolescents	Case control	Cannabis	- Study done on 120 young patients with cannabis dependence or abuse (DSM-IV-TR criteria evaluated with the MINI) and seeking treatment in an addiction unit + another 110 healthy control subjects. - Used self-reports for measuring alexithymia (TAS-20;BVAQ-B), depression (BDI-13), and states and traits of anxiety (STAI). - 35.3% of cannabis users were alexithymia Risk Factors 1) Difficulty in identifying feelings Protective Factors 1) Difficulty in describing feelings	Lower rate of alexithymics than in previous reports among substance abusers but higher than those reported in the control
15	2017	Kobulsky (USA)	To examine the relations between child physical and sexual abuse and early substance use among youths investigated by child protective services	Cohort	Marijuana Inhalants Hard drugs NMPD	- Significant indirect effects of physical abuse severity on early substance use were found through externalizing behavior problems in girls, with a significantly stronger relation found only between externalizing problems and early substance use in girls. Risk Factors 1) Girls: Physical abuse severity, externalizing problems	Significant gender differences in the effect of early substance from physical abuse.
16	2017	Chuang et al. (USA)	To examine the potential relationship between two self-reported risk factors (impulsivity and the presence of one or more behavioral addictions) and tobacco, alcohol, and marijuana use—or susceptibility to use these drugs in the future among nonusers—in an adolescent population	Cross-sectional	Marijuana	- Adolescents who had either impulsivity alone or at least two behavioral addictions alone were more likely to have used tobacco, alcohol, or marijuana compared to individuals who had neither risk factor (OR = 2.50–4.13), and- Individuals who endorsed both impulsivity and three or more behavioral addictions were the most likely to have used these drugs (OR = 9.40–10.13) Risk Factors 1) High impulsivity combined with more than 3 behavioral addictions.	High impulsivity was related to behavioral addictions in adolescents, and a combination of these two factors increased risk for drug use
17	2016	Khoddam, et al. (USA)	To study whether the relationship of conduct problems and several internalizing disorders with future substance use is redundant, incremental, or interactive in adolescents.	Cross-sectional	Marijuana	Risk Factors 1) Conduct Problems (CPs) 2) Major depressive disorder Protective Factors 1) Social phobia	CPs are a risk factor for substance use, as well as the nuanced interplay of internalizing-externalizing problems in the developmental psychopathology of adolescent drug use vulnerability.
18	2016	Gabrielli et al. (USA)	To identify the relations between maltreatment and SU behavior in a population known for a significant risk of SU behaviour—youth in foster care.	Cross-sectional	Alcohol Marijuana Cocaine Stimulants LSD Tranquilizers Opiates PCP Sniffed gases/fumes Prescribed drugs	- 31% of participants reported past-year substance abuse. - Age of substance abuse onset was 11.08 years (Sd = 2.21 years) - Structural model with maltreatment predicting substance abuse severity demonstrated strong model fit with a significant path between maltreatment and substance abuse. Risk Factors 1) Maltreatment during stay in foster care.	Findings revealed a robust relationship between maltreatment, indicated by the severity and chronicity of experiences across types of maltreatment and substance use behavior severity.
19	2016	Traube et al. (USA)	1) To untangle two aspects of time in the growth process of polysubstance use: age or development and the length of time in the Child Welfare System (CWS). 2) To determine residential status as either a risk or protective factor	Cross-sectional	Alcohol Marijuana	- Analysis using longitudinal data from the National Survey of Child and Adolescent Well-Being (n = 1178). - Time- invariant characteristics of ethnicity and gender were not related to polysubstance use. - Increased proportions of the sample reporting the use of alcohol and marijuana (from 16 to 26% and from 9 to 18%, respectively). Risk Factors 1) Duration of stay in Child Welfare System (CWS)	Findings indicated that children who enter child welfare when they are older than age 15 are at increased risk of substance use, although those who enter the CWS at a young age may be at greater risk over time.
20	2016	Cecil et al. (UK)	1) To determine DNAm patterns at birth that are associated with adolescent substance use? 2) To identify DNAm markers that are associated with genetic and environmental influences	Cohort	Cannabis	- The sample comprised 244 youth (51% female) from the Avon Longitudinal Study of Parents and Children (ALSPAC). - At birth, epigenetic variation across a tightly interconnected genetic network (n = 65 loci; qo0.05) was associated with greater levels of substance use during adolescence, as well as an earlier age of onset among users. - Several of the identified loci were associated with known methylation quantitative trait loci. - Collectively, these 65 loci were also found to partially mediate the effect of prenatal maternal tobacco smoking on adolescent substance use. Risk Factors 1) Prenatal tobacco smoking	Tobacco exposure during pregnancy may increase the risk of future substance use.
21	2016	Ogunsola et al. (Nigeria)	To compare the prevalence of substance use among in-school adolescents in urban and rural areas of Osun State, Nigeria, and identified risk and protective factors.	Cross-sectional	Substances use	Risk Factors 1) Private school attendance 2) having friends who use substances 3) mother having had tertiary education Protective Factors 1) Parental disapproval of substance use	The risk and protective factors for adolescent substance use somewhat differ for rural and urban areas
22	2015	Miech et al. (USA)	To determine whether e-cigarette use is part of a pattern towards extensive substance use.	Cross-sectional	Marijuana Prescription drugs	- The distribution of e-cigarette use is consistent with the distribution of most other substances. - Youth who use e-cigarettes are, on average, highly likely to use other substances, as well. Risk Factors 1) E-cigarette smokers	Exposure to e-cigarettes within the past 30-days, increases the prevalence of marijuana use and prescription drug use among adolescents.
23	2018	El Kazdouh et al. (Morocco)	To explore and understand factors that protect or influence substance use in adolescents.	Focus Group Discussion (FGD) analysis via Thematic Analysis	Any illicit drug	Risk Factors 1) Perceived benefits of drug abuse 2) Perceived availability of drugs (cheaper price) 3) Lack of parental supervision 4) Peer pressure from those who do drugs Protective Factors 1) Strong belief in maintaining good health 2) Good family support in giving advice 3) Strong religious beliefs	There are many interplay factors that contribute to the risk of developing drug abuse problems and protecting adolescents from drug abuse. Key prevention activities need to be targeted at each level to ensure healthy behaviors among adolescents.