Substance Use Prevention Programs

Several surveys provide information on adolescents' self-reported use of alcohol and illicit[¹] and licit[²] drugs in the United States.

Illicit and Licit Drug Use

The National Survey on Drug Use and Health (NSDUH), administered by the Substance Abuse and Mental Health Services Administration (SAMHSA), collects national- and state-level data annually from all 50 states and the District of Columbia. In 2020, more than 36,000 people ages 12 and older were surveyed, including 6,337 interviews conducted with youths ages 12 to 17. Among these youths, 13.8 percent reported use of any illicit drug in the past year (SAMHSA, 2021). The NSDUH also reports use of licit substances, such as tobacco products and cigarettes. The survey found that 8.2 percent of youths ages 12 to 17 drank alcohol in the past month and 1.4 percent smoked cigarettes in the past month (SAMHSA, 2021). In general, tobacco use has declined since its peak in the mid-1990s (SAMHSA, 2020; SAMHSA, 2021).

Another survey, Monitoring the Future (MTF), is administered annually to 8th, 10th, and 12th graders and asks questions about attitudes and behaviors related to drug use. Owing to the COVID–19 pandemic, data collection for the 2020 survey ended earlier than usual, resulting in a smaller-than-usual sample size (Johnston et al., 2021). The 2020 MTF surveyed approximately 11,821 students enrolled in 112 secondary schools, compared with the 2019 MTF, which surveyed 42,531 students from 396 secondary schools. Data from the study indicated that, in general, substance use has remained at or close to the historically low levels reported by adolescents in the past several years. Specifically, the results from the 2020 MTF showed the following trends in drug use: 

• Across all three grades, 30-day prevalence of cigarette use has fallen 85.0 percent since its peak in the mid-1990s. This decline slowed in 2020 among 8th and 10th graders; however, 12th graders showed a small increase in 30-day prevalence (although the increase was not statistically significant). Additionally, lifetime prevalence (or having used cigarettes on at least one occasion during one’s lifetime) increased for 8th and 12th graders by small, nonstatistically significant amounts in 2020. For eighth graders, lifetime prevalence increased for the second year in a row, from 10.0 percent to 11.5 percent. For 12th graders, lifetime prevalence increased for the first time since 1996, increasing by 1.7 percentage points to 24.0 percent in 2020.
• The rate of past-year use of illicit drugs (other than marijuana) has declined steadily in the past 5 years for 10th and 12th graders. Past-year use of illicit drugs other than marijuana has also decreased in previous years for eighth graders; however, a small nonstatistically significant increase was reported among the 2020 cohort.
• The past-year use of narcotics other than heroin (such as prescription opioids) is at 2.1 percent among 12th graders—decreasing by a small but nonstatistically significant 0.6 percentage points between 2019 and 2020.
• Annual prevalence for marijuana use has remained fairly steady for several years. In 2020, past-year use was reported to be 11.0 percent, 28.0 percent, and 35.0 percent in grades 8, 10, and 12, respectively. However, among students who use marijuana, daily consumption is on the rise. In 2019, daily marijuana prevalence increased statistically significantly among 8th and 10th graders, with a further increase in 2020 only among 12th graders. In 2020, all three grades were found to have daily marijuana levels that are at or near the highest level recorded since 1991.
• In 2020, adolescent vaping decreased across all grades. This follows the large, statistically significant increases in vaping between 2017 and 2019, when 30-day prevalence of vaping either marijuana or nicotine doubled or tripled in all grades. For example, among 12th graders, vaping marijuana rose from 4.9 percent in 2017 to 14.0 percent in 2019, and vaping nicotine rose from 11.0 percent to 25.5 percent across the same timeframe. However, in 2020, past-30-day prevalence for vaping nicotine and marijuana decreased by small, nonstatistically significant amounts among 10th and 12th graders. For eighth graders, the 30-day prevalence of any vaping and vaping nicotine held steady, whereas vaping marijuana increased by a small, nonstatistically significant amount. [Johnson et al., 2021] 

A third survey, the Youth Risk Behavior Surveillance System (YRBSS), covers various risk behaviors, including substance use. The survey is administered every 2 years to students in grades 9 to 12 and is representative of public and private school students from all 50 states and the District of Columbia. The 2019 YRBSS was completed by 13,872 students in 136 schools (Creamer et al., 2020). According to the most recent data available from 2019: 

• Six percent of students had smoked cigarettes or cigars or used smokeless tobacco on at least 1 day during the 30 days before the survey (Creamer et al., 2020). 
• About 37.0 percent of students had used marijuana at least once in their lifetime, with 21.7 percent reporting use within the last 30 days before the survey. There was nonstatistically significant change in reported marijuana use between 2017 and 2019 (Jones et al., 2020).
• About 50.0 percent of students had ever used an electronic vaping device, with 32.7 percent of students reporting they were current users of electronic vapor products (current use was defined as having vaped on at least 1 day in the past 30). This represents a statistically significant increase in electronic vaping from 2017, when 13.2 percent of students reported past-30-day electronic vapor use (Creamer et al., 2020).
• The YRBSS did not report any statistically significant changes in illicit drug use between the 2017 and 2019 surveys. About 1.8 percent of students reported use of heroin one or more times in their lifetime, and 1.6 percent of students had used a needle to inject any illegal drug into their body one or more times in their lifetime (Jones et al., 2020).

Alcohol Use

According the 2020 NSDUH, 8.2 percent of youths reported using alcohol in the past month. The NSDUH also reported on rates of binge alcohol use and heavy alcohol use.[³] Among the surveyed youths, 4.1 percent reported binge alcohol use, and 0.6 percent reported heavy alcohol use in the past month (SAMHSA, 2021).

According to the 2020 MTF, 38.3 percent of students reported consuming any alcohol in the previous 12 months (for all three grades combined). This is a statistically significant increase from 2019, when 35.9 percent of students reported having consumed alcohol in the past year. Similarly, there were statistically significant increases in lifetime, past-30-day, and daily alcohol consumption across all three grades. Further, binge drinking (defined on the MTF as having five or more drinks in a row in the past 2 weeks), which had been declining until 2018, saw a slight uptick across all three grades in both 2019 and 2020 (Johnston et al., 2021).

Finally, the 2019 YRBSS did not report on lifetime alcohol use. However, 2017 findings indicated that 60.4 percent of students had consumed alcohol at least once in their lifetime. In 2019, the YRBSS examined current alcohol use and binge-drinking behaviors. About 29.0 percent of students reported current alcohol use, defined as having had at least one drink of alcohol on at least 1 day during the past 30 before the survey. The prevalence of current alcohol use was fairly steady from 2017 (29.8 percent) to 2019 (29.2 percent). Additionally, nearly 14.0 percent of students reported binge drinking on at least 1 of the past 30 days. Among students reporting current alcohol use or current binge drinking, more than half (54.8 percent and 61.2 percent, respectively) reported that they engaged in these behaviors 1 to 2 days during the past month (Jones et al., 2020).

Overall Key Findings

Overall, results from the surveys showed that illicit drug use (other than marijuana) remains at the lowest point in 20 years, with a statistically significant reduction in opioid use between 2016 and 2017. Alcohol and marijuana remain the most commonly used substances among youth, and adolescent alcohol use may be on the rise. Two out of five 8th, 10th, and 12th graders reported use of alcohol in the past 12 months, whereas marijuana use trends have remained steady for 5 years, with annual prevalence estimates ranging from 13.2 to 24.6 percent (Johnson et al., 2021; NSDUH, 2020). Finally, while vaping among youths had increased dramatically between 2017 and 2019, recent survey results indicate that youths may be beginning to slow their use of electronic vapor products (Johnston et al., 2021). 

Substance Use by Race/Ethnicity

According to data from the 2019 MTF,[⁴] for several years white students had substantially higher rates of using any illicit drug than did Black students. However, in recent years, the differences have narrowed owing to increasing marijuana use among Black students and “some decline” among white students. The MTF also found that the rate of Hispanic student substance use generally falls between that of white students and Black students, though these rates can vary by specific substances and grades (Johnston, 2020). 

According to a detailed report on the complex subgroup differences and how they have changed over the years, across grades, Black students have the lowest levels of use for several licit and illicit drugs, including hallucinogens, synthetic marijuana, and all forms of prescription drugs used without a doctor’s orders. However, in recent years, heroin use among Black students in the 12th grade has been higher than among white students. Additionally, the 2018 annual prevalence of marijuana use was higher among 8th grade Black students, compared with white students, but no different for Black and white students in 10th and 12th grades (Johnston et al., 2019).

With regard to alcohol use, the MTF data showed that Black students had the lowest 30-day prevalence for alcohol use, heavy drinking, and self-reports of having been drunk during the prior month. Differences were largest among 12th grade students, with 24.0 percent of white youths reporting having been drunk, compared with 17.0 percent of Hispanic youths and 10.0 percent of Black youths (Johnston et al., 2019). Black students also had lower prevalence of past-month use of an electronic vapor product (19.7 percent), compared with white (38.3 percent) and Hispanic (31.2 percent) students, according to the YRBSS (Creamer et al., 2020). 

Overall, the results suggest that white students have the highest rate of alcohol use, whereas Black students have the lowest use rates for alcohol and nearly all other substances, except for heroin use among 12th graders and marijuana use among 8th graders. Rates of substance use among Hispanic students generally mirror the rates of white students; however, Hispanic youths have recently surpassed white youths in their rates of using illicit drugs such as synthetic marijuana and cocaine.

Substance Use by Gender and Sexual Orientation

Data from the 2018 MTF show that males tend to have higher rates of illicit drug use than females; however, gender differences have weakened over time. Specifically, the most recent data have shown few gender differences in marijuana use. In fact, there were no statistically significant gender differences among 12th graders, and 8th and 10th girls had slightly higher rates of marijuana use, compared with boys of the same age, however these differences were also not statistically significant (Johnston et al., 2020). 

Gender differences in regard to alcohol use have also decreased over time. In previous reports, males consistently reported higher 30-day and daily alcohol use rates than females. Yet in more-recent reports, there have been almost no gender differences in alcohol use among 8th and 10th graders. This finding has been consistent for 10th graders since 2002. Additionally, in the past few years, female students have reported higher 30-day prevalence of alcohol use (Johnston et al., 2020). 

Differences in rates of substance use across gender tend to emerge as students grow older. For example, in eighth grade, female students tend to report higher rates of use for some drugs, such as amphetamines. However, this difference disappears with age, with 9.6 percent of male students reporting lifetime prevalence of amphetamine use, compared with 7.3 percent of female students. Overall, substance use prevalence rates for males and females increase with age, but the increase is often more dramatic among males (Johnston et al., 2020). 

In addition, national surveys and other research have shown that gender minority youths (e.g., transgender, nonbinary) and sexual minority youths (e.g., gay, lesbian, bisexual, queer, or youth with same-sex attractions or behaviors) are at greater risk for substance misuse than cisgender or heterosexual youths (Mereish, 2019). For example, compared with heterosexual students or those who only had sexual contact with people of the opposite sex, the YRBSS found that sexual minority students were more likely to inject illegal drugs, misuse prescription opioids, and use select illicit drugs such as cocaine, heroin, methamphetamines, inhalants, hallucinogens, or ecstasy (CDC, 2020). And despite a general decrease in drug and alcohol use from 2005 to 2017, these declines were less evident for sexual minority youth, and in some cases, the disparities between sexual minority youth and heterosexual youth increased (Felt et al., 2020; Fish and Baams, 2018).

The reasons for the use of alcohol and other drugs by youth are grounded in numerous behavioral theories. These theories inform prevention programming by focusing on the possible factors that may lead to youth substance use. Two prevalent theories are social learning theory and social control theory.

The social learning theory offers a theoretical perspective on why youths engage (or don’t engage) in substance use. Social learning theory posits that people learn behaviors through observation of others and then model or imitate that behavior. People are more likely to imitate behavior if their observations are associated with positive experiences or rewards (Bandura, 1971). In this case, social learning can serve as either a risk or protective factor for substance use, depending on the context in which learning occurs. For example, youths can learn to avoid using alcohol and other drugs by emulating the prosocial behavior displayed by positive adult figures in their lives. Conversely, youths can be pressured into experimenting with substances by following the behavior shown by antisocial peers (Cleveland et al., 2010; Glasgow Erickson, Crosnoe, and Dornbusch, 2000).

The social development model, a part of the social learning theory, presupposes that children and adolescents learn behavior from the following four socializing units: 1) family, 2) school, 3) peers, and 4) community or religious institutions (Cleveland et al., 2012; Haggerty et al., 2007; Cleveland et al., 2010). This model includes both a social perspective and a developmental perspective. The social perspective looks at positive reinforcement; that is, youths who receive positive reinforcement from prosocial activities engage in prosocial activities (Cleveland et al., 2012), whereas youths who receive positive reinforcement from antisocial activities will engage in antisocial activities (Glasgow Erickson, Crosnoe, and Dornbusch, 2000). The developmental perspective focuses on the transitional periods from toddler to child to adolescent. These periods are shaped by changes experienced in one's social environment that influence behavioral changes over time. For example, behavioral changes often occur during the transition from middle to high school, a stressful period for many youths, as they try to fit in with other peer groups. 

Another theory, the social control theory, suggests that when an adolescent’s “conventional ties” are broken, the adolescent is more likely to commit delinquent acts (Vaughn et al., 2009; Church, Wharton, and Taylor, 2009; Glasgow Erickson, Crosnoe, and Dornbusch, 2000). Conventional ties include the bonds to 1) institutions (family or school), 2) beliefs (laws and normative standards), and 3) people (teachers, parents, peers). Family-based risk factors, such as parental substance use, contribute to the weakening of an adolescent’s social bonds (Glasgow Erickson, Crosnoe, and Dornbusch, 2000), and weak social bonds can influence the occurrence of future delinquency, including substance use. Thus, some prevention programs incorporate interactive components that involve both youths and their parents, to improve the family bond (Waldron and Turner, 2008; Liddle et al., 2009).

Risk factors[⁵] consist of personal traits, characteristics of the environment, and conditions in the family, school, and community that are linked to a youth’s likelihood of engaging in delinquency and other problem behaviors such as substance use (Murray and Farrington, 2010). Numerous risk factors contribute to substance use among youth. These risk factors exist at the individual, family, peer group, school, and community domain levels. Much of the research concludes that risk and protective factors interact at multiple ecological levels to influence early substance use initiation (Bacio et al., 2015). Most of the research cited below concentrates on risk factors related to general alcohol and other drug use.

While some longitudinal studies have demonstrated how risk factors predict youths’ initiation of substance use, it is more often the case that research has been able to establish correlation, without definitive findings on causation. Some studies have concluded that many of the relationships between risk factors and substance use may be multidirectional (Winters et al., 2014; Hallfors et al., 2005; Skogen et al., 2014). Another aspect of research on risk factors that complicates findings is that relationships can be direct or indirect, factors can mediate or moderate other factors, factors can interact with one another, and substance use can be influenced by reciprocal multilayered systems (e.g., Bacio et al., 2015; Cooley–Strickland et al., 2009; Pardini, Lochman, and Wells, 2004; Sale et al., 2003; Voce and Anderson, 2020; Yoon, Snyder, and Yoon, 2020; Zapolski et al., 2019).

Individual

Individual risk factors vary among youths but stem from many origins such as genetics, early moral development, personality traits, temperament, and negative life events (Wong, Slotboom, and Bijleveld, 2010; Dick et al., 2013; Hodgins, Kratzer, and McNeil, 2001). Individual-level risk factors that may lead to substance use include antisocial behavior, delinquent beliefs, early onset of aggressive behavior, cognitive and neurological disorders, mental health disorders, prodrug attitudes, and violent victimization or exposure to violence (Fite, Schwartz, and Hendrickson, 2012; Swadi, 1999; Compton et al., 2005; O’Neill et al., 2011; Zapolski et al., 2019).

Antisocial behavior and aggression, commonly associated with delinquent behavior during adolescence, are considered major risk factors for initiation of substance use (Dryfoos, 1991; Hawkins, Catalano, and Miller, 1992; Compton et al., 2005). Numerous studies have found a significant relationship between antisocial behavior (such as lying, defiance, or becoming withdrawn) and substance use among youth (Adalbjarnardottir and Rafnsson, 2002; Armstrong and Costello, 2002; Hussong et al., 2004). Studies have found that aggression and conduct disorder during childhood may precede substance use (Harachi et al., 2006; Pardini, White, and Stouthamer–Loeber, 2007; Prinstein and La Greca, 2004). However, while the prevalence of both substance use and antisocial behavior increases during adolescence, aggression declines (Tremblay, 2010). Therefore, while the relationship between antisocial behavior and substance use has been established in research, the findings with regard to aggression and substance use are mixed.

Cognitive and neurological disorders associated with adolescent substance use most commonly include attention deficit hyperactivity disorder (ADHD), conduct disorder, and mood disorders (Swadi, 1999). For example, youths with ADHD are significantly more likely to misuse alcohol, tobacco, and illicit substances, compared with youths who do not have ADHD (Lee et al., 2011; Molina et al., 2007). ADHD is also associated with earlier initiation of substance use and an increased likelihood of using a variety of substances (Horner and Scheibe, 1997; Wilens et al., 2011). Research has shown that youths with ADHD tend to be impulsive and lack decisionmaking skills, leaving them more susceptible to initiation of substance use. Additionally, ADHD is associated with low levels of dopamine, which can be increased through use of several drugs, including cocaine, amphetamines, ecstasy, marijuana, and alcohol. Thus, youths who have ADHD may use substances for sensation-seeking or self-medicating purposes (Wilens et al., 2007).

Youths also may use substances to deal with unaddressed trauma or mental health problems (Garland, Pettus–Davis, and Howard, 2013; Mandavia et al., 2016). For example, adolescents who experience internalizing disorders, such as depression or anxiety, are at a higher risk for early initiation of alcohol or drug use and are more likely to develop substance use disorders (O’Neil, Conner, and Kendall, 2011; Marmorstein, 2009). However, early initiation of substance use also has been found to predict later development of mental health disorders, suggesting that, while a relationship exists between the two, causation cannot always be established or the relationship may be multidirectional (Winters et al., 2014; Hallfors et al., 2005; Skogen et al., 2014).

Finally, certain personality traits may predict initiation of substance use by youth, including fatalism and external locus of control (Bearinger and Blum, 1997; Lassi et al., 2019). For instance, a study of Hispanic youth in Los Angeles found that fatalism, a personality factor that comprises the belief that one’s destiny is out of their control, was associated with a higher risk of lifetime marijuana use and cigarette use (Soto et al., 2011).

Family

Factors at the family level are related to family structure, support, and functioning. Family risk factors related to substance use include lack of parental supervision, poor family attachment, family history of problem behaviors or criminality, parental substance use, marital status of parents, level of parental education and socioeconomic status, child perception that parents approve of their substance use, and child victimization and maltreatment (Development Services Group, 2015; Whitesell et al., 2013; Wong, Slotboom, and Bijleveld, 2010).

Family structure—specifically living in a one-parent household—may be associated with an increased likelihood of substance use initiation (Ewing et al., 2015; Barrett and Turner, 2006). One study found that living in a single-parent household was significantly associated with having been intoxicated at least once in a lifetime and having used cannabis at least once in a lifetime (Bränström, Sjöström, and Andréasson, 2008). Another study, using data from the MTF survey, found that children in mother-only families used more marijuana or amphetamines than children from dual-parent families (Hemovich and Crano, 2009). This study also found that drug use among daughters living with single fathers was greater than drug use of daughters living with single mothers, while gender of parent was not associated with sons’ usage.

However, other research has suggested that parenting style, rather than family structure, has a greater effect on youth substance use (Crawford and Novak, 2008). For example, one study of 400 youths found that having a poor relationship with parents was associated with the onset of both alcohol and marijuana use, and of binge drinking (Rusby et al., 2018). This same study also found that lower parental monitoring was associated with alcohol use, binge drinking, and marijuana use. Some studies find that both parenting style and family structure are independently related to substance misuse. A longitudinal study of Mexican American youths found that both those who experienced less overall parental monitoring and supervision and who came from single-parent homes were at risk for early substance use (Atherton et al., 2016).

Family history of problem behaviors, such as parental involvement in the criminal justice system and parental substance use, is a strong predictor of youth substance use (Lucenko et al., 2015; Shlafer, Poehlmann, and Donelan–McCall, 2012; Whitten et al., 2019). Youths who live with a parent or guardian who uses substances are at a higher risk for using substances themselves, even when controlling for peer influences or parenting styles (Biederman et al., 2000; Adalbjarnardottir and Hafsteinsson, 2001; Li, Pentz, and Chou, 2002; Mrug and McCay, 2013).

Siblings also have been found to be potential risk factors related to youth substance use. Research has found that youths who grew up with one or more older siblings are more likely to initiate substance use (Atherton et al., 2016). Researchers have presumed this is because younger siblings model their older siblings’ antisocial behavior and are more often exposed to older, deviant peer groups. They have found that having deviant, substance-using, or antisocial siblings is associated with initiation of alcohol, tobacco, and marijuana use, even after accounting for peer and parental substance use (Atherton et al., 2016; Low, Shortt, and Snyder, 2012; Whiteman, Jensen, and Maggs, 2013; Yurasek et al., 2019). However, studies that have accounted for the deviance of older siblings separately still found this influence on having an older sibling (Atherton et al., 2016).

Other studies have indicated that youths who have experienced childhood maltreatment, abuse, and neglect are more than twice as likely to use substances and develop substance use problems, compared with youths who have not experienced maltreatment (Danielson, 2016; Lucenko et al., 2015; Proctor et al., 2017). Yet other research has shown that child maltreatment was not directly associated with adolescent substance use, but that deviant peer affiliation fully mediated this relationship (Yoon, Snyder, and Yoon, 2020).

Peers

Researchers have found that several peer-level risk factors influence youth substance use. These include friends who engage in delinquent behavior, gang membership, friends’ use of drugs, peer rewards for antisocial behavior, perception of peer substance-use norms,and quality of peer relationships.

Multiple studies have shown that association with deviant and substance-using peers is one of the main risk factors for youth substance use (Cattelino et al., 2014; Cleveland et al., 2008; Dick et al., 2013; Handren, Donaldson, and Crano, 2016; Tomé et al., 2012; Trucco et al., 2011). For example, a study of youth in Ohio that examined multiple risk factors for substance use found that peer delinquency was the strongest correlate, even when other relevant factors related to neighborhood, media, and family were controlled (Ferguson and Meehan, 2011). Specifically, research has shown that youths who are exposed to peers who use alcohol and other drugs (i.e., peer socialization) are more likely to begin using drugs themselves (Nalven, Spillane, and Schick, 2020; Odgers et al., 2008). In addition, gang membership has also been associated with substance use initiation (Gordon et al., 2004; Bjerregaard, 2010; Coffman, Melde, and Esbensen, 2015). Youths are particularly susceptible to peer influence during early and middle adolescence if they are 1) male, 2) exposed to peers who are slightly more deviant, and 3) in unstructured or unsupervised settings (Dishion, Dodge, and Lansford, 2008).

However, there also is evidence that youths who use drugs seek association (i.e., peer selection) with other substance-using youths (Burk et al., 2012; Fergusson and Horwood, 1999; Light et al., 2013; Osgood et al., 2013). Overall, there is growing support for the idea that a causal pathway between peers and substance use cannot be established. Youths select their friends based on similar behaviors and interests (i.e., selection); however, these behaviors and interests are influenced by their peers (i.e., socialization; Young and Rees, 2013). 

Despite findings on peer influence, other research has found that youths who use substances report fewer close social relationships, compared with youths who do not use substances (Power and Estaugh, 1990). A meta-analysis of 34 longitudinal studies (Fairbairn et al., 2018) found that youths with fewer secure attachments or close relationships engage in more substance use than youths with secure attachments. This suggests that a lack of peer relationships may also increase youths’ use of substances.

A related, peer-level risk factor is perception of peer substance-use norms, which may differ from actual peer substance behaviors (Bacio et al., 2015; Duan et al., 2009; Nalven, Spillane, and Schick, 2020; Wambeam et al., 2014). Some researchers suggest that an adolescent’s perception of what goes on in the environment may be more important than the actual reality of that environment (Bacio et al., 2015; Duan et al., 2009). A study of 8,000 students in Wyoming found that as a youth’s levels of misperception increase, substance use likelihood also increases (Wambeam et al., 2014). Another study of more than 500 low-income Black adolescents found that greater perceived risky peer norms correlated with the increased likelihood of substance use and that this risk factor was more influential than the protective effects of parental monitoring (Marotta and Voisin, 2017).

Other characteristics of peer groups have also been studied. For example, a longitudinal study that examined friendship networks found that other-sex friendships (i.e., girls who are friends with boys, and boys who are friends with girls) in early adolescence predicted a greater likelihood of alcohol use in late adolescence for both boys and girls and predicted a greater likelihood of drug use among girls, even after controlling for individual risk factors such as antisocial behaviors (Poulin, Denault, and Pedersen, 2011).

In addition, several studies have examined the potential risky effects of dating and romantic relationships on youth substance use (Aikins, Simon, and Prinstein, 2010; Longmore et al., 2008; Orpinas et al., 2013; Whitton et al., 2018). A study that examined dating trajectories from 6th through 12th grade found that students in middle school who dated more frequently were about twice as likely to report using drugs than youths who reported less dating frequency (Orpinas et al., 2013). In high school, youths who had dated more frequently in middle school and those who dated frequently throughout middle school and high school were 70.0 percent more likely to report using drugs than youths who had low levels of dating experience overall. Another study examining a sample of youth from the Toledo (OH) Adolescent Relationships Study found that the level of a romantic partner’s alcohol use was related to adolescent respondents’ self-reported alcohol use frequency and alcohol-related problems (Longmore et al., 2008). A study of sexual and gender minority youths found that, among bisexual youths, romantic involvement was associated with increased marijuana and other illicit drug use (Whitton et al., 2018).

School

School-level risk factors for substance use are related to school attendance, academic performance, and attachment and commitment to school (Arthur et al., 2015; Wong, Slotboom, and Bijleveld, 2010). For example, low levels of school attendance, or truancy, are related to earlier substance use initiation (Henry, Knight, and Thornberry, 2012). Other studies found that truancy was significantly associated with the onset and escalation of marijuana use among urban youth (Henry, Thornberry, and Huizinga, 2009; Henry and Thornberry, 2010).

As with other risk factors, the directional relationship between school-related factors and youth substance use initiation can be hard to establish in research. Poor school performance is one example where the directionality of the association is uncertain. Research has shown that initiation of substance use can hinder youths’ grades and engagement in school (Bugbee et al., 2019; Mandell et al., 2002; Meier et al., 2015; Patte, Qian, and Leatherdale, 2017). However, some research also suggests that youth who engage in substance using behaviors are more likely to have received lower grades in school before initiation (Hallfors et al., 2002; Nargiso, Ballard, and Skeer, 2015). This implies that the relationship between academic performance and substance use is complicated and directionality (i.e., whether substance use causes poor academic performance, or whether poor academic performance leads to substance use) is difficult to determine (Crosnoe, 2006; Cooley–Strickland et al., 2009). Further, other factors (such as socioeconomic status) may better explain the relationship between low academic performance and substance use initiation (Rogeberg, 2013).

Further, youths who have low levels of academic engagement or school connectedness, marked by poor relationships with peers or teachers, are also more likely to use alcohol or other drugs (Bachman et al., 2008; Bond et al., 2007; Henry, Thornberry, and Huizinga, 2009; Weatherson et al., 2018). For example, a 4-year study of some 33,000 students found that youths who report low levels of school connectedness showed higher levels of binge drinking, marijuana use, and cigarette smoking than students with high levels of school connectedness (Weatherson et al., 2018).

Community

Community-level risk factors are often associated with living in an area characterized by neighborhood disorganization (which is measured by residents’ perceptions of safety levels of crime), number of abandoned or decrepit buildings, frequency of publicly visible alcohol or drug use, accessibility of substances, poverty levels, and residential turnover rates (Crum, Lillie–Blanton, and Anthony, 1996; Hays, Hays, and Mulhall, 2003). Community type (urban versus rural) and laws related to substance availability can also affect levels of youth substance misuse (Gale et al., 2012; Miech et al., 2015; Warren, Smalley, and Barefoot, 2015).

Multiple studies have found that youths who report having greater access to alcohol, tobacco, and other drugs in the community are more likely to initiate substance use (Nargiso, Ballard, and Skeer, 2015; Stanley, Henry, and Swaim, 2011). Much of this research examines alcohol policies, laws, ordinances, and density of alcohol sales outlets (Chen, Gruenewald, and Remer, 2009; Paschall et al., 2012). A longitudinal study of youths in 50 California zip codes found that alcohol outlet density affected youth access to alcohol. The researchers concluded that high alcohol outlet density in a community enabled youth access to alcohol through several sources, such as direct purchase, shoulder tapping, family members, and underage acquaintances (Chen, Gruenewald, and Remer, 2009). State and local laws, ordinances, and policies can also influence youth substance use. A study of MTF data found that, after decriminalization of marijuana, youths in California had more positive attitudes toward marijuana and were 25.0 percent more likely to have used it in the past 30 days than youths in other states (Miech et al., 2015). Before decriminalization California youth did not show higher levels of marijuana prevalence or acceptance relative to their peers in other states.

Additionally, neighborhood disorganization and socioeconomic factors are significantly associated with substance use, even when controlling for individual- and family-level risk factors (Duncan, Duncan, and Strycker, 2002; Hadley–Ives et al., 2000; Jang and Johnson, 2001; Winstanley et al., 2008). For example, an analysis of data from the Seattle (WA) Social Development Project found that living in more socioeconomically disadvantaged neighborhoods was independently associated with increased smoking (Cambron et al., 2018).

Some researchers have also examined rural versus urban environments. One study that examined perceived ease of access to a variety of substances found that rural students reported higher levels of access to licit substances, while urban students reported higher levels of access to illicit substances (Warren, Smalley, and Barefoot, 2015). Another study found that adolescents in rural communities and in small urban communities had greater odds of past-year prescription opioid misuse than adolescents in large, urban environments (Monnat and Rigg, 2016). Another study of more than 18,000 youths from communities with populations of fewer than 50,000 people found that high school students living on farms were exposed to greater numbers of risk factors and had higher levels of substance use (and in some cases higher level of substance use initiation) than students who lived in towns (Rhew, Hawkins, and Oesterle, 2011). Finally, a study using data from the NSDUH found that rural youths started drinking at a younger age and also had higher rates of binge drinking than urban youths (Gale et al., 2012).

Protective factors[⁶] can help prevent initiation of substances among youth. These factors can be thought of as buffers that reduce the negative effect of adversity on child outcomes (Vanderbilt–Adriance and Shaw, 2008). Like risk factors, protective factors also exist on the individual, family, peer group, school, and community levels, and certain protective factors may exist on multiple levels. Interventions designed to prevent substance use initiation seek to reduce risk factors while enhancing the effectiveness of protective factors by incorporating components that are focused on developing factors such as strengthening family bonds, improving academic connectedness, or developing skills to handle life stressors (Development Services Group, 2015; Waldron and Turner, 2008).

Unfortunately, there has been less research conducted on protective factors, compared with the amount of research on risk factors on alcohol and drug use. In addition, researchers have found that risk factors are better at predicting youths' initiation of substance use than protective factors are at predicting youths’ not initiating substance use (Cleveland et al., 2008).

Individual

Individual-level protective factors include resiliency, social competence, problem-solving skills, intrapersonal psychological empowerment, and social skills. Youths who demonstrate high levels of these factors are less likely to engage in substance use, compared with youths who demonstrate low levels (Cleveland et al., 2008; Hinnant and Forman–Alberti, 2018; Lardier et al., 2020).

Ethnic, racial, and cultural identities and values can also protect youths against substance misuse, specifically for youths of color (Brook et al., 1998; Lardier et al., 2020; Zapolski, 2017). For example, one study found that higher ethnic identity was associated with lower past-month drug use for African American, Hispanic, and multiracial youth[⁷] (Zapolski, 2017).

Family

On the family level, research has shown that parental monitoring and good relationships between youths and their parents can improve child adjustment during important developmental phases and serve as a buffer to problem behaviors such as aggression and delinquency, which are associated with the initiation of substance use (Tilton–Weaver et al., 2013; Losel and Farrington, 2012; Reingle, Jennings, and Maldonado–Molina, 2011). 

Additional evidence shows that effective parental monitoring can reduce the influence of deviant peers on the initiation of alcohol, tobacco, and marijuana use (Van Ryzin, Fosco, and Dishion, 2012; Pesola et al., 2015). A study examining several protective factors among students in the Delaware School Survey found that quality of the relationship between child and parent is one of the strongest protective factors against alcohol and marijuana use in 8th and 11th grades (DeCamp and Smith, 2019). Studies in other states have found that parental attachment is a protective factor against prescription drug misuse (Park, Melander, and Sanchez, 2016). 

Family structure has also been examined as a protective factor. A study of youths who participated in the MTF survey found that children from two-parent families were less like to use inhalants, marijuana, and amphetamines than children from single-parent families (Hemovich and Crano, 2009). Another study of rural adolescents participating in the NSDUH found that living in a two–parent household was protective against nonmedical prescription drug use (Havens, Young, and Havens, 2011). Similarly, analysis of data from the Seattle Social Development Project found that adolescents living in two–parent households showed slower growth in alcohol use compared to adolescents living in other family structures (Cambron et al., 2018).

Peers

Exposure to prosocial peers may serve as a protective factor for substance use initiation. Several studies have found that prosocial peer association is significantly associated with decreased violence, substance use, and delinquency (Osgood et al. 2013; Padilla–Walker and Bean, 2009; Prinstein et al., 2001). However, the research on the relationship between prosocial peer association and youth substance use is limited; few studies have explored the influence of peers' positive behavior on increasing youths' prosocial behaviors and decreasing problem behaviors, such as initiation of substance use (Lee, Padilla–Walker, and Memmott–Elison, 2017).

Further, there is limited research available on the protective effects of dating/romantic relationships on substance use. For example, a longitudinal study of sexual and gender minority youths found that romantic involvement was associated with less drinking for the whole sample and associated with less illicit drug use among gay and lesbian participants (Whitton et al., 2018). However, this study also found that dating may promote drug use in those who identify as bisexual and may promote smoking among the whole sample.

School

On the school level, protective factors include positive school climate and attachment to school and teachers. Studies that have examined the relationship between school connectedness and substance use initiation have found that perceived teacher support has a protective effect on the initiation of smoking, alcohol, and marijuana (McNeely and Falci, 2004; Weatherson et al., 2018). An analysis of data from the COMPASS study (a prospective cohort study design to collect longitudinal data on a variety of behavioral outcomes from Canadian students in grades 9 to 12) included three forms of substance use behaviors, finding that school connectedness had the strongest protective effect on cigarette smoking, but also reduced likelihood of marijuana use and binge drinking (Weatherson et al., 2018). 

Other factors, such as commitment to school (especially in youths in higher grades), participating in school activities, and high academic performance have also shown a protective effect against recent use of substances (Cleveland et al., 2008; DeCamp and Smith, 2019; Vidourek and King, 2010). The study examining several protective factors in a large sample of students in the Delaware School Survey found that school performance grades (defined as school grades) exhibited one of the strongest positive effects against past-month substance use (DeCamp and Smith, 2019).

Community

On the community level, protective factors include residence in a neighborhood with prosocial opportunities and resources and collective responsibility among neighbors. Youths who live in low-crime communities, where neighbors monitor one another's children, are less likely to have access to or engage in alcohol and substance use (Treno et al., 2007). A study of more than 18,000 youths in Nebraska found that youths who reported that there were fun and legal activities to do in their community were 18.0 percent less likely to have misused prescription drugs, compared with youths who did not have similar activities to engage in (Park, Melander, and Sanchez, 2016). Another study found that living in rural areas may be a protective factor for Black youths by lowering the risk of stress and negative affect (Gibbons et al., 2007). 

Community civic engagement can also serve as a protective factor for youth (Bartkowski and Xu, 2007; Lardier et al., 2020). For example, a study of students in a northeastern urban school district found that youths who participated more often in activities in their communities were less likely to have used illicit drugs in the previous month (Lardier et al., 2020).

Religiosity and Spirituality

Finally, several studies have examined religiosity/spirituality as protective factors (Bartkowski and Xu 2007; Ford and Hill, 2012; Hodge, Cardenas, and Montoya, 2001; Marsiglia et al., 2005; Salas–Wright et al., 2017; Vaughan et al., 2011; Vidourek and King, 2010). A meta-analysis of these studies identified several interesting patterns, including that religiosity/spirituality is multidimensional, involving various interconnected aspects at the individual, family, peer, and community levels (Hardy et al., 2019). Also, there are numerous complex and dynamic processes by which religiosity/spirituality relates to youth outcomes and both its public and private aspects can influence outcomes (Hardy et al., 2019).

Researchers have also found that using different definitions of religiosity/spirituality can result in different findings. For example, one study of more than 10,000 youths found that religious worship attendance was a statistically significant predictor of not using alcohol or marijuana in the past (DeCamp and Smith, 2019).  However, the same study found that identifying with a religion did not have the same protection. Another study found that religious affiliation had no significant effect on lifetime use of any of the studied substances, but that religious attendance was significantly related to lifetime marijuana and inhalant use, and that religious salience was significantly related to less use of cigarettes and marijuana (but there was no effect on alcohol or inhalant use) [Hodge, Marsiglia, and Nieri, 2011]. A meta-analysis found that both high religiosity and attending church often were protective factors for youth against consumption of alcohol (Kelly et al., 2015). Other studies suggest that religious social support may protect adolescents against risk for intergenerational substance use (Ohannessian et al., 2010; Peviani et al., 2020).

Substance use prevention programs seek to reduce the number of adolescents experimenting with, and potentially developing an addiction to, alcohol and illicit substances (Midford, 2009). The programs target various populations and age groups. Following are descriptions for several different types of prevention programs in terms of their target populations and various components. Specific examples of evidence-based programs from the Model Programs Guide are also provided.

School-Based Programs

Problem behaviors, such as alcohol or other drug use, often begin during the school-age years. Thus, many researchers contend that implementing prevention programs in a school setting increases the odds of averting problems associated with alcohol, tobacco, and other drug use (Botvin and Botvin, 1992; Perry et al., 1996; Tobler and Stratton, 1997). Most school-based prevention programs are universal and are designed for large audiences of students (Botvin and Griffin, 2007); however, some research suggests that curricula delivered in an interactive format with smaller groups of young people can also produce positive results (Tanner–Smith, Wilson, and Lipsey, 2013; Tripodi, et al., 2010; Tobler and Stratton, 1997).

The National Institute on Drug Abuse (NIDA, 2011) suggests that prevention programs should focus on key transition periods during adolescence, particularly the transition from middle school to high school, when youths are at high risk of experimenting with alcohol and other drugs. Classroom curricula give students the tools to recognize internal pressures (e.g., stress or anxiety) and external pressures (e.g., peer attitudes and advertising) that may influence their decision to use alcohol, tobacco, and other drugs, while also developing skills to resist these influences effectively (Sloboda et al., 2009).  

Many prevention programs have been implemented and evaluated in school settings across the country. One example, the LifeSkills Training (LST) program, is a classroom-based drug prevention program for upper elementary and middle school students. LST’s curriculum centers on the development of personal self-management skills, social skills, and drug-resistance skills. One study (Botvin et al., 1995) found that LST had numerous statistically significant effects on students who participated in the program, including the reduction of monthly cigarette use, problem drinking, and polydrug use (i.e., use of more than one drug at one time). However, there were no statistically significant differences on self-reported measures of marijuana use between students who participated and those who did not. Another study (Trudeau et al., 2003) found that the LST treatment group showed a statistically significant reduction in the growth of substance initiation, compared with the control group. 

However, not all classroom-based programs have had the desired effect on students. The original D.A.R.E. (Drug Abuse Resistance Education), in use from 1983 to 2009, had limited success in reducing youth substance use (Ennett et al., 1996). The core curriculum of D.A.R.E. consisted of 17 lessons, one given each week. The lessons were taught by police officers and covered topics such as drug use and misuse, resistance techniques, and drug use alternatives. In two studies, D.A.R.E. was found to have no statistically significant effects on students’ short- and long-term substance use, attitudes toward drugs, and self-esteem (Clayton, Cattarello, and Johnstone 1996; Ennett et al., 1994). 

Programs for Young Children

Research has also examined younger children and the link between the early presence of conduct disorder and future substance use (Shaw et al., 2006; Webster–Stratton. Reid, and Stoolmiller, 2008; Hopfer et al., 2013). Evidence suggests that programs implemented at earlier stages in a child’s life may be more effective in prevention efforts and behavior adjustments than programs implemented in later adolescent years, especially for high-risk populations (Park, 2008; Phillips, McDonald, and Kishbaugh, 2017; Webster–Stratton, Reid, and Hammond, 2004). Programs implemented in preschool and kindergarten classes are designed specifically to improve the social competence of children and establish skills for prevention. One aspect of prevention programs for younger children is the incorporation of both the family and the teacher/caregiver in program services. During this developmental period, children require proactive involvement and monitoring from parents, for a parent’s response to a child’s behavior is a predictor of future substance use (Shaw et al., 2006). Responses from teachers/caregivers to children’s behavior are also important during this time. As a result, many programs now include both motivational interviewing for parents and emotional and educational training for teachers (Shaw et al., 2006; Stormshak et al., 2021).

The Family–School Partnership Intervention to Reduce Risk of Substance Use is a preventive intervention designed to reduce first grade students' risk for later drug involvement by addressing students' poor achievement, aggressive and shy behavior, and concentration problems by improving teachers' and parents' teaching and behavior-management skills and parent–teacher communication. The findings from the studies  by Storr and colleagues (2002) and Furr–Holden and colleagues (2004) showed a statistically significant reduction in the risk of smoking initiation for students in the intervention group, compared with students in the control group. However, Furr–Holden and colleagues (2004) found no significant differences between the two groups in outcomes related to early alcohol or other drug use (including use of marijuana, inhalants, and other illegal drugs).

The Child–Parent Center Program (Chicago, Ill.) is a family- and school-based program intended for preschool and kindergarten students and their families. The goal of the program is to provide comprehensive educational and family support services. The findings of the study by Reynolds and Ou (2011) indicated that participants were less likely to report substance misuse at age 24, compared with control group participants. This difference was statistically significant.

Family-Based Programs

Family-based programs focus on parental influence, parenting skills, and family cohesion as major factors in substance abuse prevention (Abbey et al., 2000; Cleveland, Feinberg, and Greenberg, 2010; Cleveland, Feinberg, and Jones, 2012). Prevention programs seek to provide information to both parents and children about alcohol and drugs and encourage parents to clarify their views about substance use with their children (Cleveland, Feinberg, and Greenberg, 2010; Cleveland, Feinberg, and Jones, 2012). During the developmental period from childhood to adolescence, research has shown that parental influence makes a large impact on youth behaviors. Therefore, supportive, motivated parents can greatly affect prevention efforts (Haggerty et al., 2007; Cleveland et al., 2010; Shaw et al., 2006). Family-based programs are designed to prepare parents and children for the changes they will experience during this developmental phase and offer tools to assist youth in resisting drugs and alcohol. Factors such as family functioning, communication, involvement, and supervision are fundamentally important to many programs for adolescents (Riesch et al., 2012). 

Numerous family-based prevention programs have shown effectiveness in improving family functioning and reducing youth substance use. For example, the Positive Family Support (PFS) program is a multilevel, family-centered intervention targeting children at risk for problem behaviors or substance use, and their families. Designed to address family dynamics related to the risk of adolescent problem behavior, the program is delivered to parents and their children in a middle-school setting. In a study (Connell et al., 2007) that examined PFS's effect on substance use and antisocial behavior in students ages 11 to 17, the intervention group reported a statistically significant decrease in the use of tobacco, alcohol, and marijuana, compared with the control group. A study by Dishion and colleagues (2002) also found that students in PFS had a statistically significant lower rate of substance use, compared with control group students. 

Another example of a family-based program is Guiding Good Choices (GGC). This program is designed for families of middle school–age children, aims to promote healthy, protective parent–child interactions, and reduces children’s risk for early substance use. A 2009 study conducted by Spoth and colleagues found that participation in GGC was associated with a statistically significant reduction in alcohol-related problems and the frequency of cigarette use 10 years later, compared with control group participants. However, there was no statistically significant impact found on the frequency of drunkenness or illicit drug use.

Programs for High-Risk Families

Another type of prevention program focuses on high-risk families or families that need additional one-on-one assistance, therapy, or skills enhancement. High-risk families include single-parent homes, early/first-time mothers, and parents with a history of substance abuse (Hemovich and Crano, 2009). According to NIDA (2011), prevention programs should be tailored to address specific characteristics of particular populations to improve program effectiveness. For example, research has shown that urban communities with low socioeconomic status and strong acceptance of drug use have benefited from more focused, community prevention efforts (Cleveland, Feinberg, and Jones, 2012). At-risk adolescents who have parents with a history of substance abuse or limited concern for their children’s behavior benefit from programs that incorporate interactive family components (Hemovich and Crano, 2009).

Nurse–Family Partnership (NFP), designed for high-risk families, focuses specifically on first-time mothers and children from birth to 3 years old, who are at risk for conduct problems and possible later substance use. The program provides low-income, first-time mothers of any age with home-visitation services from public health nurses. The nurses work intensively with the mothers to improve maternal, prenatal, and early childhood health and well-being, with the goal of helping at-risk families achieve long-term improvements in their lives. Several studies (Eckenrode et al., 2000; Kitzman, 2010; Olds et al., 2004) examining NFP found statistically significant positive impacts on the targeted populations. For example, a 12-year, follow-up study found that children in the NFP program were statistically significantly less likely to have used cigarettes, alcohol, or marijuana, compared with children in the control group (Kitzman et al., 2010).      

Another program, the Strengthening Families Program for Parents and Youth 10–14, targets families who use substances. This program is designed to reduce substance use and behavior problems during adolescence through improved skills in nurturing and child management by parents and improved interpersonal and personal competencies among youths. One study (Spoth et al., 2004) found that youths who participated in the program had statistically significantly slower growth in substance use at the 6-year follow-up, compared with youths who did not participate. However, there was no statistically significant impact on lifetime marijuana use or on delaying the growth of tobacco use. Another study (Spoth, Randall, and Shin, 2008) found that youths who participated in the program had statistically significant reductions in substance-related risk at the sixth-grade level.  

Culturally Specific or Culturally Adapted Programs

Several substance use prevention programs are designed or culturally adapted for specific groups within the youth population. Culturally specific or culturally adapted interventions are designed to engage youths and families of color who do not feel represented by mainstream programs and who thus may not benefit from or even participate in the intervention (Dillman Carpentier et al., 2007; Harachi, Catalano, and Hawkins, 1997; Marek, Brock, and Sullivan, 2006). Culturally adapted programs adjust existing programs for a specific ethnic group. Adaptions may include surface-level revisions, such as alterations to language used during the program, either through complete translation or subtle changes to the vernacular phrases used throughout the intervention (Wang–Schweig et al., 2014). Deeper, structural changes to a program may also be necessary for cultural adaptation, such as modifying or adding new intervention components. Unlike adapted programs, culturally specific programs are initially designed for a specific ethnic group. Whether culturally specific or culturally adapted, however, an intervention should be suitable for the target population’s worldview, norms, beliefs, and values (Wang–Schweig et al., 2014). 

Strong African American Families (SAAF) is a program for high-risk, rural, Black families. The SAAF program is designed to help youths and their families cope with life stressors such as discrimination. The program concentrates on enhancing racial pride and family bonding through parental training and family therapy, thereby strengthening the attachment between parent and child (Brody et al., 2002). A study by Brody and colleagues (2006) found that SAAF youths showed a growth rate in alcohol use that was 17.4 percent lower than that of the comparison group, a statistically significant difference. SAAF youths also reported statistically significant reductions in levels of alcohol use initiation, compared with the control group. 

Familias Unidas, a prevention program for immigrant and first-generation Hispanic families, is designed to improve family functioning and reduce drug use and risky sexual behavior in youth. The program works to help parents understand U.S. culture and the strains of the acculturation process on their children, while also maintaining the importance of their Hispanic culture. It seeks to build supportive relationships among Hispanic immigrant parents, to integrate them into the greater community and reduce feelings of social isolation. A study (Pantin et al., 2009) found, at the 30-month follow-up, treatment group youths who participated in the program reported lower substance use, compared with the control group—a statistically significant finding. 

Several culturally specific prevention programs designed for Native Americans focus on providing participants with skills to help resist pressures toward substance abuse—within the Native American community specifically, and within U.S. society in general. Additionally, content is designed to promote holistic concepts of health present in Native American culture, as these values run counter to substance abuse (Schinke et al., 1988). One example, the Cherokee Talking Circle (CTC), was designed specifically to prevent and reduce substance abuse among youths who are members of the United Keetoowah Band of Cherokee Indians. A study by Lowe and colleagues (2012) found that youths who participated in CTC showed statistically significant reductions on measures of substance problems and symptom severity, compared with youths who participated in other nonculturally specific, substance abuse education programs.

Mentoring Programs

Mentoring programs[⁸] may be school based or community based and serve youths living in high-poverty neighborhoods, youths whose parents are incarcerated, youths in foster care, and other at-risk youths (Ahrens et al., 2008; Britner et al., 2006; Goode and Smith, 2005). Mentoring programs provide a youth with positive adult or older peer contact. This mentor–mentee relationship can help reduce risk factors that may lead to the initiation of alcohol or other drug use (e.g., early antisocial behavior, poor parental supervision/monitoring, association with delinquent peers) by enhancing protective factors (e.g., perception of social support from a trusted adult, healthy beliefs and clear standards, positive expectations for the future). 

Across three meta-analyses that examined the impact of mentoring programs on substance use, the findings were mixed. Thomas, Lorenzetti, and Spragins (2011) found that mentoring programs resulted in a statistically significant positive impact on adolescents' substance use. However, DuBois and colleagues (2011) and Tolan and colleagues (2008) did not find a statistically significant effect of mentoring on substance use. 

One example of a mentoring program is the Big Brother or Big Sister (BBBS) Community-Based Mentoring (CBM) Program. The program involves one-to-one mentoring between a Big Brother or Big Sister (the mentor or adult) and a Little Brother or Little Sister (the mentee or youth). Mentors and youths participate in various activities such as going to the movies, attending a sports event, going to a restaurant, reading books, going on a hike, visiting museums, or simply hanging out and talking with one another. These activities are intended to enhance communication skills, develop relationship skills, and support positive decisionmaking (Grossman and Garry, 1997). Results from one study (Tierney, Grossman, and Resch, 2000) found that youths who participated in the CBM program showed a statistically significant reduction in initiation of drug and alcohol use and antisocial behavior, compared with control group youths. 

Another example, Across Ages, is a mentoring program designed to delay or reduce substance use in at-risk middle school youth. The program pairs adult volunteers (55 and older) with students (10 to 13 years old) to create a special bonding relationship. The project also uses community service activities, provides a classroom-based life skills curriculum, and offers parent-training workshops. The mentors help youths develop the awareness, self-confidence, and skills they need to abstain from drug use and overcome other obstacles. Participation in Across Ages was found to have a statistically significant effect on youths’ reactions to situations involving drug use; however, the program did not statistically significantly affect youths' frequency of substance use (LoSciuto et al., 1996).  

Mass Media Campaigns

Mass media campaigns are a common way of delivering preventive health messages to the general population, particularly to individuals who may be difficult to access through traditional approaches (Wakefield, Loken, and Hornik, 2010). Campaigns can be implemented and disseminated through several different media, including television commercials, radio broadcasts, newspaper or magazine advertisements, billboard posters, brochures or posters on buses and subways, and the Internet. Exposure to a campaign is generally passive, meaning people happen to see the message during routine viewing of media, such as television or magazines. Media campaigns may be part of a larger information or social marketing program, or they may be standalone interventions. The duration of campaigns may vary (Wakefield, Loken, and Hornik, 2010).

One meta-analysis (Ferri et al., 2013) examined the effectiveness of mass media campaigns that are designed to prevent or reduce the use of or intention to use illicit drugs among youth. Notably, the review did not include mass media campaigns that concentrated on alcohol or licit drugs. The researchers analyzed the results of five randomized controlled trials and found no significant effects of media campaigns on illicit drug use. Although youths exposed to antidrug media campaigns tended to, on average, use fewer illicit drugs, compared with youths not exposed to media campaigns, the differences between the groups were not statistically significant. The researchers also found, based on results from four randomized controlled trials, that mass media campaigns had no significant effects on intentions not to use, intentions to reduce use, and intentions to stop use of illicit drugs. Despite their findings, the study authors recommended further evaluation studies of mass media campaigns (Ferri et al., 2013). 

Although research has shown that prevention programs can prevent or reduce youths' use of substances, there are still many limitations to prevention efforts. One challenge is in identifying and overcoming the barriers to program fidelity (Midford, 2009). For instance, with regard to family-based programs, many studies focus on the parents and adolescents who choose to be involved in those programs. There are few studies, however, that analyze the factors that lead to participation or the decision not to participate, and even fewer that recommend specific alternatives to increase participation (Midford, 2009; Midford et al., 2012; Lee et al., 2016).

In addition, programs are designed to focus on "substance use prevention," yet program evaluations often do not measure the actual substance use among adolescents. Rather, program evaluators identify and measure behaviors, attitudes, and perceptions related to substance use (Loxley et al., 2004; Lee et al., 2016). Therefore, it is difficult to determine whether prevention programs specifically affect a youth's actual use of drugs and alcohol.

Finally, further research is required to understand long-term implications of prevention programs. Often, program evaluation research concentrates on measuring outcomes in the short term. Few studies examine the effects of prevention programs in the long term (Shaw et al., 2006). There is a need to understand whether prevention skills will continue through both the transition to high school and the transition to college, as these are periods of development when youths are at greatest risk for experimenting with drugs and alcohol (Lee et al., 2010; Nguyen et al., 2011; Shaw et al., 2006).

Federal and local governments make large investments every year in substance use prevention programs. Although youths' self-reported use of alcohol and other drugs has generally declined over the last few years (Johnston et al., 2021), current research still demonstrates a need for prevention programs (CDC, 2018). 

Although rates of substance use remain high, with as many as 25.0 percent of 12- to 17-year-olds reporting ever having used an illicit drug in their lifetime (SAMHSA, 2018), overall rates are at historically low levels. Although much research has been done to examine the specific risk factors that influence whether youths will initiate substance use, less has been done to explore the protective factors that may buffer youths against choosing to use drugs or alcohol. Many prevention programs—designed for general audiences of youth, or of more at-risk youths and families—attempt to target certain risk factors, to prevent or reduce the use of substances (Trudeau et al., 2003; Brody et al., 2006; Connell et al., 2007; Spoth, Randall, and Shin, 2008; Kitzman et al., 2010). 

While there have been several studies conducted to look at the impact of alcohol and drug prevention programs, future research could overcome some of the current limitations, including measurement of the effect on youths’ actual substance use (rather than only skills, knowledge, or attitudes related to substance use) or evaluations that have longer follow-up periods. Finally, despite use rates leveling off in 2020, vaping remains popular among adolescents (Johnson et al., 2021). Future studies could explore whether current prevention programs influence youths’ decisions to vape or programs should add additional components to address this relatively new drug.

Suggested Reference: Development Services Group, Inc. 2022. "Substance Use Prevention Programs." Literature review. Washington, DC: Office of Juvenile Justice and Delinquency Prevention. https://ojjdp.ojp.gov/model-programs-guide/literature-reviews/substance-use-prevention-programs

Prepared by Development Services Group, Inc., under Contract Number: 47QRAA20D002V.