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Table 2 Study characteristic and main findings

From: Risk and protective factors of drug abuse among adolescents: a systematic review

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.