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. Author manuscript; available in PMC: 2022 Jul 1.
Published in final edited form as: J Clin Child Adolesc Psychol. 2020 Jul 27;50(4):498–509. doi: 10.1080/15374416.2020.1790379

Moderators of Substance Use Disorder Treatment for Adolescents

Rachel L Bachrach 1, Tammy Chung 2
PMCID: PMC7855225  NIHMSID: NIHMS1610847  PMID: 32716211

Abstract

Objective:

This brief review covers the current state of the literature on moderators of adolescent Substance Use Disorder (SUD) treatment. These moderators provide information on “for whom” a specific treatment may work best.

Method:

We used Google Scholar, PubMed, PsycInfo, and manual search of relevant reference lists to identify eligible peer-reviewed publications from January 2005 to December 2019.

Results:

We summarize 21 published studies (including meta-analyses, RCTs, and correlational work) testing moderators and/or predictors of adolescent SUD treatment outcomes. Conclusions are, thus, limited by the relatively small number of studies. Results suggest that, for adolescents with co-occurring externalizing pathology or those higher in SUD severity, more intensive treatment appears to be more effective. Other findings were often inconsistent (e.g., examining sex or race/ethnicity as a moderator) between studies, making it challenging to provide clear recommendations for personalizing SUD treatment choice.

Conclusions:

Future research may need to shift focus from exploring often unchangeable moderators (e.g., race/ethnicity) to factors that are potentially modifiable with treatment. Additionally, testing models that include mediators of treatment effects, that is, factors that help to explain “how” treatment works, along with moderators (moderated-mediation) may provide the most benefit in understanding both “for whom” and “how” to tailor SUD treatment to optimally meet an adolescent’s personal needs.

Adolescence is a time in which initiation of substance use most often occurs, and for some, progression into substance use disorder (SUD). Multiple treatments for adolescent SUD have been shown to be efficacious, including cognitive behavioral therapy (CBT), adolescent community reinforcement approach (A-CRA), family-based treatments (FBT), motivational enhancement therapy (MET), and the combination of CBT, MET, and various FBTs (Tanner-Smith, Wilson, & Lipsey, 2013). Upon admission to SUD treatment, certain characteristics may have a main effect on treatment outcome, that is, predict treatment response similarly across treatment groups. In contrast, moderators are associated with different levels of response across treatment conditions. These moderators of treatment effects can specify “for whom” a particular type of adolescent SUD treatment may work best (Black & Chung, 2014). Below, we provide a brief review regarding the current state of the literature on treatment moderators for SUD followed by future directions for the field.

Review of Moderators of SUD Treatment

Moderators of treatment indicate “for whom or under what conditions” treatment affects change in the outcome (Kraemer, 2016, p. 672) and have the potential to aid providers in choosing treatments based on, for example, baseline characteristics of patients (e.g., age). Identifying clinically significant moderators of SUD treatment can help tailor interventions (Litten et al., 2015), making them more personalized, relevant, and possibly increase motivation for changing one’s substance use (Hersh, Curry, & Becker, 2013; Winters, Lee, Botzet, Fahnhorst, & Nicholson, 2014). It is also possible that treatment personalization may enhance treatment efficacy directly, above and beyond client motivation level. In either case, discovering significant moderators of treatment would appear to be an important step towards improving adolescent substance use outcomes. As such, recent work reviewing evidence-based treatments for youth SUD stresses the importance of examining moderators (Hogue, Henderson, Becker, & Knight, 2018; Hogue, Henderson, Ozechowski, & Robbins, 2014) and notes that most studies examining moderators of SUD treatment only look at a patient’s demographic characteristics, which is also true of the adolescent treatment literature at large (Chorpita et al., 2011). Also true of the treatment literature generally, smaller sample size (and thus, limited power) often prohibits examining outcomes by subgroup (i.e., testing moderator effects). Thus, the limited number of studies examining moderators of youth SUD treatment has generated mixed results.

In order to provide an up-to-date review of this literature, we used Google Scholar, PubMed, and PsycInfo to search for peer-reviewed articles published over the last 15 years (January 2005 through December 2019) focused on testing moderators of adolescent SUD treatment. We also conducted manual searches of references lists to identify possibly relevant studies. We chose not to review studies that tested moderators of substance use prevention programs, as we were primarily interested in understanding moderators of SUD treatment. The studies reviewed below (see Table 1) cover the moderators of age, sex, race/ethnicity, SUD severity, co-occurring psychopathology, and personality and social factors (e.g., parent influence). Due to the small number of studies identified (k=18), we decided to also include three studies that either examined predictors of adolescent SUD treatment outcome (Brunelle et al., 2013) or moderators of adolescent SUD treatment for only participants in the intervention group (Hersh et al., 2013; Shelef, Diamond, Diamond, & Liddle, 2005; 21 total studies summarized in Table 1).

Table 1.

Moderators and Predictors of Adolescent Substance Use Disorder Treatment: 2005–2019

Moderator/Predictor Study Treatment Conditions and Sample Size Sample Demographics Primary Outcome(s) Conclusions
Age (Moderator) Baldwin, Christian, Berkeljon, & Shadish, 2012 Meta-analysis (k = 24 studies) comparing: Family therapies (BSFT, FFT, MDFT, MST) to treatment-as-usual, an alternative therapy, or control group. Age: 11–19 Race/Ethnicity: Not reported Sex: Not reported -Delinquency, conduct problems, or substance use -Types of substances were not specified -Age not related to treatment outcome -Additionally, sample size, sex, race/ethnicity, timing of posttreatment assessments, presenting problem, and referral source did not moderate outcomes -Delinquency and substance use outcomes were combined for moderator analyses, so unable to judge whether findings are specific to substance use alone
Age (Moderator) Greenbaum et al., 2015 * Integrative data analysis from 5 RCTs comparing MDFT to another active treatment (N = 646) Age: 11–17 Race/Ethnicity: 51% Black, 35% Hispanic, 4% White Sex: 19% female -Substance use latent variable (composite of 4 indicators of use and consequences) -Exact breakdown of substances not specified, but authors state that sample at baseline was primarily cannabis users with a minority of participants using alcohol and other substances (mainly cocaine and anxiolytics) -Age not related to treatment outcome, possibly due to restricted range -See below for further findings on race/ethnicity and sex
Age (Moderator) Hendriks, van der Schee, & Blanken, 2012 * RCT comparing MDFT to CBT for cannabis use disorder (N = 109) Age: 13–18 Race/Ethnicity: 71.6% Dutch/western Europe (other ethnicities not reported) Sex: 20.2% female -Cannabis use quantity and frequency -Older adolescents (17–18 yrs old) benefited more from CBT while younger adolescents (13–16 yrs old) benefited more from MDFT -See below for further findings on co-occurring psychopathology
Age (Moderator) Slesnick & Prestopnik, 2009 RCT comparing home-based EBFT to office-based FFT or to service as usual through a homeless shelter (N = 119) Age: 12–17 Race/Ethnicity: 44% Hispanic, 29% White, 11% Native American, 5% Black, 11% other Sex: 55% female -Alcohol use and other substance use frequency, looked at separately -Alcohol use significantly decreased for both younger (12–15 yrs) and older (16–17 yrs) adolescents in EBFT. FFT only effective in older adolescents -Sex moderated treatment effects at p=.07; see article for details -Ethnicity and history of physical/sexual abuse did not moderate treatment effects
Race/Ethnicity (Moderator) Burrow-Sanchez, Minami, & Hops, 2015 RCT comparing standard CBT-G to a culturally accommodated CBT-G in Hispanic/Latino adolescents (N = 70) Age: 13–18 Race/Ethnicity: 100% Hispanic/Latino – 61.4% U.S. born, >74% of the parents born in Mexico Sex: 10% female -Substance use frequency (alcohol, cannabis, and other, excluding tobacco) as a composite variable -At baseline, majority substance was cannabis (~71% had a cannabis use disorder) -Outcomes were moderated by ethnic identity and familism; adolescents with lower ethnic identity and lower familism reduced use more in standard CBT-G than accommodated CBT-G; adolescent with higher ethnic identity and higher familism reduced use more in accommodated CBT-G than standard CBT-G
Race/Ethnicity (Moderator) Clair et al., 2014 RCT comparing MI to relaxation therapy for reducing alcohol and cannabis use in incarcerated adolescents (N = 147) Age: 14–19 Race/Ethnicity: 35% Hispanic, 33% White, 33% Black Sex: 14.3% female -Alcohol quantity and frequency on heavy drinking days and cannabis quantity and frequency -Hispanic adolescents who received MI decreased alcohol use (total number of drinks on heavy drinking days and percentage of heavy drinking days) compared to Hispanic adolescents who received relaxation therapy -Ethnicity did not moderate the effects of treatment on cannabis use
Race/Ethnicity (Moderator) Greenbaum et al., 2015 * Integrative data analysis from 5 RCTs comparing MDFT to another active treatment (N = 646) Age: 11–17 Race/Ethnicity: 51% Black, 35% Hispanic, 4% White Sex: 19% female -Substance use latent variable (composite of 4 indicators of use and consequences) -White and Black adolescents decreased substance use more in MDFT compared to White and Black adolescents in comparison treatments -Hispanic adolescents declined in substance use regardless of treatment condition
Race/Ethnicity (Moderator) Huey & Polo, 2008 Review aiming to identify effective treatment on various outcomes, including substance use, for racial/ethnic minority adolescents from years 1960–2006 (k = 3 SUD treatment studies met criteria) Age: 11–17 Race/Ethnicity: 50–60% Black, 1–42% Hispanic, 3–47% White Sex: 24–27% female -Substance use indicated by variety of measures -Substances measured: cannabis, alcohol, and/or cocaine -MDFT was the only probably efficacious treatment for reducing substance use in racial/ethnic minority adolescents -MST met criteria for possibly efficacious for reducing substance use in Black adolescents
Race/Ethnicity (Moderator) Smith, Tabb, Fisher, & Cleeland, 2014 Integrative data analysis from 37 SAMHSA-funded outpatient treatment sites implementing A-CRA to compare Black adolescents receiving refusal skills training (n=214), Black adolescents who did not receive refusal skills training (n=212), and White adolescents that received refusal skills training (n= 214); N = 640 Age: Range not reported; M=16.3 (SD =1.75) Race/Ethnicity: 67% Black; 33% White Sex: 17% female -Substance use (composite frequency variable and variable indicating abstinence) -Exact breakdown of substances used not specified -Exposure to refusal skills did not predict better substance use outcomes for Black adolescents compared to White adolescents or Black adolescents who did not receive refusal skills
Race/Ethnicity (Moderator) Waldron & Turner (2008) Meta-analysis (k=17 studies; 1998–2007) on RCTs for treating outpatient adolescent substance use, including CBT, MET, A-CRA, and family therapies (N = 2,307) Age: 11–19 Race/Ethnicity: 45% White, 25% Hispanic, 25% Black, and 5% other Sex: 25% female -Substance use -Range of substances included as outcomes -Some studies suggest that family-based treatment may be more efficacious than CBT for Hispanic adolescents
Sex (Moderator) Greenbaum et al., 2015 * Integrative data analysis from 5 RCTs comparing MDFT to another active treatment (N = 646) Age: 11–17 Race/Ethnicity: 51% Black, 35% Hispanic, 4% White Sex: 19% female -Substance use latent variable (composite of 4 indicators of use and consequences) -Male adolescents decreased substance use more in MDFT compared to male adolescents in comparison treatments -Female adolescents declined in substance use regardless of treatment condition
Sex (Moderator) Winters, Lee, Botzet, Fahnhorst, & Nicholson, 2014 RCT comparing: (1) a 2-session MI-based brief intervention, (2) a 2-session MI-based brief intervention + Parent session, and (3) an assessment only control for adolescents with SUD (N = 284) Age: 13–17 Race/Ethnicity: 71.8% White, 11.3% Black, 6.3% Hispanic, 4.9% Native American, 3.2% Asian, 2.5% other Sex: 50.4% female -Substance use -Range of outcomes (e.g., abstinence, SUD criteria met, frequency of use) and types of substances (alcohol, cannabis, other drugs) included as outcomes -Sex did not moderate treatment outcomes -Age, race, and baseline drug use severity also did not moderate treatment outcomes
Substance use severity, psychological problems, and delinquency (Predictors) Brunelle et al., 2013 Longitudinal study assessing 3- and 6-month SUD treatment outcomes from adolescents seeking treatment at inpatient (n=102) and outpatient (n=97) addiction treatment centers in Quebec (N = 199) Age: 13–18 Race/Ethnicity: Not reported (all participants had to be French-speaking) Sex: 40.7% female -Substance use trajectories, excluding alcohol use -Composite variable representing severity of substance use and related problems; cannabis and methamphetamine most commonly used substances at baseline -Adolescents with higher severity of substance use at baseline showed greater improvement after treatment than those with lower baseline severity -Greater delinquent behavior (number of arrests) is associated with fewer substance use improvements after treatment -Severity of psychological problems (e.g., depression, anxiety) did not influence substance use treatment outcome
Cannabis use severity, recruitment method, psychosocial functioning, and cannabis use disorder symptoms (Moderators) de Gee, Verdurmen, Bransen, de Johnge, & Schippers, 2014 RCT comparing a 2 session MET intervention to a control information session for adolescents who use cannabis (N = 119) Age: 14–21 Race/Ethnicity: Approx. 79% Dutch, 10–14% Western Europe non-Dutch, 7–11% Non-Western European Sex: 26% female -Cannabis use, represented by quantity and frequency (average weekly number of joints) -Heavier cannabis users in the intervention group had a greater reduction in cannabis use than heavier users in the control group -Recruitment method, psychosocial functioning and symptoms of cannabis use disorder at baseline did not moderate treatment outcomes
Alcohol use severity (Moderator) Gmel, Venzin, Marmet, Danko, & Labhart, 2012 Cluster (by school) quasi-RCT comparing a 2-session MI-based group intervention to assessment-only controls for adolescents with unhealthy alcohol use (N = 668) Age: 16–18 Race/Ethnicity: Not reported (took place in the Swiss section of Zurich) Sex: Approx. 52.7% female -Alcohol binge frequency, typical alcohol quantity, and maximum alcohol quantity -Adolescents with moderate unhealthy alcohol use in the intervention reduced drinking compared to the control group, although results only neared significance (p=.06) -Adolescents with the highest unhealthy alcohol use in the intervention groups showed iatrogenic effects compared to controls
Substance use severity and psychiatric comorbidities (Moderators) Henderson, Dakof, Greenbaum, & Liddle, 2010 A secondary analysis of 2 RCTs comparing outpatient MDFT to CBT (Study 1; N = 224) or MDFT to treatment as usual in a juvenile detention facility (Study 2; N = 154) to examine heterogeneity in substance use treatment response Study 1 Age: 12–17.5 Race/Ethnicity: 72% Black, 18% White, 10% Hispanic/Latino Sex: 19% female Study 2 Age: 13–17 Race/Ethnicity: 61% Black, 22% Hispanic/Latino, 17% White Sex: 17% female -Latent trajectory classes of substance use frequency and problem severity post-treatment -Types of substances not reported -In both studies, two latent substance use severity classes were found – low and high severity -In both studies, MDFT was more effective than comparison treatments for adolescents with higher substance use severity and psychiatric comorbidities, specifically higher substance use problem severity (Study 1) and higher substance use frequency (Study 2)
Psychiatric comorbidities (Moderators) Hendriks, van der Schee, & Blanken, 2012 * RCT comparing MDFT to CBT for cannabis use disorder (N = 109) Age: 13–18 Race/Ethnicity: 71.6% Dutch/western Europe (other ethnicities not reported) Sex: 20.2% female -Cannabis use quantity and frequency -Adolescents with conduct disorder, oppositional defiant disorder, or internalizing problems reduced cannabis use more after MDFT than CBT -Adolescents without psychiatric comorbidities showed better cannabis outcomes after CBT than MDFT
Depression and conduct disorder (Moderators within intervention arm) Hersh, Curry, & Becker, 2013 A secondary analysis of intervention data aiming to test a brief, evidence-based treatment (5 session MET+CBT) for adolescents with alcohol and/or cannabis use disorder (N = 90) Age: 13–21 Race/Ethnicity: 75.6% White, 8.9% Black, 14.4% multiracial, 1.1% Hispanic/Latino Sex: 23.8% female -Substance use frequency and related problems -Types of substances assessed include alcohol, cannabis, crack/cocaine and heroin/opioid use -Greater conduct disorder severity was associated with higher substance use frequency post-treatment in adolescents with lower levels of depression compared to those with higher levels of depression
Depression (Moderator) Hersh, Curry, & Kaminer, 2014 Review summarizing the effects of comorbid depression on adolescent SUD treatment outcomes through March 2014 (k = 13 studies) Age: 12–21 Race/Ethnicity: Most studies had majority White participants; see Hersh et al. for breakdown Sex: Except for one study, all had less than 50% female -Substance use -Most common substance use outcome was alcohol (11 studies) followed by multiple substances including alcohol (8 studies) -Findings were equivocal, indicating depression may have no effect on adolescent SUD treatment (6 results), negatively affect SUD treatment (5 results), or positively affect SUD treatment (7 results) -Concluded that methodological differences between studies (e.g., treatment setting, treatment type, treatment duration, measurement methods, demographics) may account for mixed findings
Disruptive behavior disorder (DBD; Oppositional Defiant Disorder and/or Conduct Disorder) (Moderator) Ryan, Stanger, Thostenson, Whitmore, & Budney, 2013 Secondary data analysis of RCT comparing MET/CBT + Parent Management Training + CM (intervention condition) to MET/CBT + Parent Drug Education (attention control) for adolescent cannabis users (N = 68) Age: 12–18 Race/Ethnicity: 89.7% White; other ethnicities not reported Sex: 17.6% female -Cannabis use frequency and abstinence -Adolescents with a DBD in the MET/CBT + Parent Management Training + CM showed a significantly greater reduction in cannabis frequency than adolescents with a DBD in the attentional control
Substance use severity, ADHD severity, court-mandated to treatment, and conduct disorder comorbidity (Moderators) Tamm et al., 2013 Secondary data analysis of RCT comparing methylphenidate to placebo in adolescents with both ADHD and a non-tobacco SUD all receiving CBT for SUD (N = 299) Age: 13–18 Race/Ethnicity: 61% White, 23% Black, 14% multiracial/other, 1% American Indian/Alaska Native, and 1% Asian, with 15% also identifying as Hispanic/Latino Sex: 21% female -Number of negative urine samples and substance use frequency, defined as achieving a 50% reduction in substance use days from baseline to end of treatment -At baseline, most met criteria for DSM-IV cannabis dependence (66.9%) or abuse (26.4%), and/or for alcohol dependence (28.1%) or abuse (28.1%); <10% met for other SUDs (sedatives, cocaine, amphetamine, and hallucinogens) -ADHD symptom change -Adolescents with comorbid conduct disorder who received methylphenidate were more likely to achieve a 50% reduction in substance use frequency than those with comorbid conduct disorder receiving placebo -Substance use severity, ADHD severity, and court-mandated referral did not moderate treating outcomes
Multiple variables tested (e.g., age, sex, race/ethnicity, internalizing pathology) but moderators of interest were substance use severity and externalizing pathology severity (Moderators) van der Pol et al., 2017 Meta-analysis of RCTs through 2016 looking at the effectiveness of MDFT versus other evidence-based therapies in reducing adolescents’ substance use, delinquency, externalizing/internalizing psychopathology, and family malfunctioning in adolescents with SUD and comorbid behavior problems (k = 19 studies; N = 1,488 participants) Age: Full range not reported; Mean ages ranged from 13.7–17.0 Race/Ethnicity: 28–100% ethnic minority Sex: 7–33% females -Substance use frequency (majority of studies [18] assessed substance use as primary outcome) -Majority of adolescents used cannabis at baseline, followed by alcohol -Also looked at delinquency, externalizing symptoms, internalizing symptoms, and family functioning outcomes -Adolescents with severe substance use and disruptive behavior disorder at baseline benefited more from MDFT than adolescents with less severe conditions -Sex, age, socioeconomic status, and ethnic background did not moderate effectiveness of MDFT
Decision-making style (defined as adaptive or maladaptive problem solving) (Moderators) Piehler & Winters, 2017 RCT comparing a 2-session MI-based brief intervention to a 2-session MI-based brief intervention + Parent session for adolescents with unhealthy alcohol and/or cannabis use (N = 259) Age: 13–18 Race/Ethnicity: 69.5% White, 12% Black, 8.1% Native American, 4.2% Hispanic/Latino, 3.1% Asian, 3.1% other Sex: 47.1% female -Alcohol use latent variable (indicators were alcohol use frequency and DSM-IV disorder symptoms) -Cannabis use latent variable (indicators were cannabis use frequency and DSM-IV disorder symptoms) -Adolescents with a more maladaptive decision-making style (e.g., more impulsive, careless) reported better alcohol outcomes if they were in the 2 session + Parent intervention compared to the adolescent-only intervention -Adolescents with a less maladaptive decision-making style showed equivalent alcohol outcomes in both intervention conditions -Decision-making style did not interact with intervention condition when predicting cannabis outcomes
Parent-therapist alliance (Moderator within intervention arm) Shelef et al., 2005 A secondary data analysis from an RCT looking only at adolescents with current cannabis use who received MDFT (N = 65); did not compare results to another treatment or control condition Age: 13–18 Race/Ethnicity: 47% Black, 47% White, 6% not reported Sex: 15% female Note: Demographics are based on the original full sample (N=100); authors did not report separate demographics for final analyzed sample (N=65) -Cannabis use frequency -Problems related to substance use -Adolescent-therapist alliance predicted less substance use problems posttreatment when parent-therapist alliance was moderate or high
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Note. Studies included are those that conducted work with intervention data for adolescents with a substance use disorder or referred for treatment due to problems with substance use. Prevention studies were not reviewed/included. ADHD = attention-deficit/hyperactivity disorder; A-CRA = adolescent community reinforcement approach; BSFT = brief strategic family therapy; CBT = cognitive-behavioral therapy; CBT-G = group cognitive-behavioral therapy; CM = contingency management; EBFT = ecological-based family therapy; FFT = functional family therapy; MDFT = multidimensional family therapy; MET = motivational enhancement therapy; MI = motivational interviewing; RCT = randomized clinical trial; SUD = substance use disorder.

*

Indicates study reported in table more than once because it assessed multiple moderators of interest

Age.

Behaviors during early versus later adolescence may be differentially affected by ongoing brain development, and peer and parent influences (Gardner & Steinberg, 2005; Giedd et al., 2015), all of which play roles in the development of youth SUD. Thus, several studies have investigated whether age moderates adolescent SUD treatment effects. However, findings have been mixed and are limited based on a small number of studies. First, in a study comparing a CBT-based intervention versus FBT (multi-dimensional family therapy; MDFT) for youth cannabis use (Hendriks, van der Schee, & Blanken, 2012), the authors found that older (aged 17–18), relative to younger (aged 13–16), adolescents showed greater reductions in cannabis use when participating in a CBT-based intervention versus MDFT. Conversely, younger adolescents showed greater reductions in cannabis use in MDFT versus CBT (Hendriks et al., 2012). These results are consistent with previous work examining age as a moderator of SUD treatment (Kaminer, Burleson, Goldberger, 2002), and suggest that older adolescents may be more developmentally ready to use cognitive skills to decrease their substance use whereas younger adolescents may benefit more from a holistic intervention that incorporates involvement from family, parents, and the community.

Second, Slesnick and Prestopnik (2009) found that older adolescents (aged 16–17) receiving Functional Family Therapy (FFT) delivered in an office setting reduced their alcohol use more than younger adolescents (aged 12–15) receiving office-based FFT. Similar to Hendriks et al. (2012), the authors hypothesized that older adolescents may have had the cognitive ability to respond more positively to the office-based FFT, as this treatment tended to be very cognitively-focused. In addition, the researchers found that adolescents (regardless of age) assigned to the comparison treatment – a home-based Ecological-Based Family Therapy (EBFT) intervention – showed similar reductions in alcohol use (Slesnick & Prestopnik, 2009). However, meta-analysis and integrative work looking at family therapy for adolescent SUD outcomes has not found age to be related to treatment outcome (Greenbaum et al., 2015), but has combined SUD outcomes with other outcomes (e.g., delinquency; Baldwin, Christian, Berkeljon, & Shadish, 2012), making conclusions difficult to draw. Due to the limited number of studies and conflicting findings, strong conclusions for SUD treatment choice based on developmental stage or adolescent’s age are lacking. Thus, further research is needed, particularly to determine the extent to which age, relative to other developmental indicators (e.g., school grade, pubertal maturation, cognitive development), is a critical factor in influencing treatment response.

Sex.

Sex differences regarding treatment needs (e.g., experiences of sexual trauma, intimate partner violence) and outcomes have long been recognized (American Psychologist Practice Guidelines, 2007), yet few studies have examined sex as a moderator of treatment effects (Mak, Law, Alvidrez, & Perez-Stable, 2007). This is also true for adolescent SUD treatment research. Although recent research did not find sex differences in the prevalence of adolescent SUD (Grucza et al., 2018), adolescent males (vs females) are more likely to be admitted to SUD treatment, which contributes to the limited statistical power to test sex as a moderator in adolescent SUD treatment studies. To circumvent this issue, a recent study integrated data from five randomized clinical trials (RCTs) testing the effectiveness of MDFT compared to other effective treatments (individual CBT, residential treatment, and adolescent group treatment) to assess whether sex and/or race/ethnicity (see below) moderated adolescent substance use treatment outcomes (Greenbaum et al., 2015). The pooled analysis, which included 124 females and 522 males, found that MDFT was effective for both males and females, but was more effective than comparison treatments for males only (Cohen’s d = 1.17; large effect). Unlike males, females seemed to benefit from either MDFT or comparison treatments. Nevertheless, the authors caution against drawing firm conclusions regarding these findings until results are replicated. Other recent adolescent substance use treatment research with the power to test sex as a moderator (Winters et al., 2014) did not find significant interactions with treatment outcome. Winters and colleagues conducted an RCT comparing a 2-session MI-based brief intervention versus a 2-session MI-based brief intervention + parent session or an assessment only control improved SUD outcomes for adolescents (N = 284; 50% female). The authors did not find that sex moderated results (see Table 1), but that adolescents improved in both treatment conditions compared to the assessment only controls. Thus, the current empirical literature does not provide definitive conclusions regarding sex as a moderator of treatment effects for adolescent SUD.

Race/ethnicity.

Similar to the problems with both age and sex as moderators, the generalizability of results from treatment outcome studies to racial/ethnic minority youth may be limited due to lack of diversity in racial/ethnic representation, and thus low power to test moderation effects (Hall, 2001). In 2008, Huey and Polo reviewed the literature testing the effectiveness of evidence-based treatments for racial/ethnic minority youth and found no “well-established” SUD treatment for racial/ethnic minority youth. However, they did review research which found that MDFT was “probably efficacious” for Hispanic/Latinos, Haitian, and Jamaican youth with SUD and that another FBT, multisystemic therapy (MST), was “possibly efficacious” for Black youth with SUD (Huey & Polo, 2008). Around the same time, Waldron and Turner (2008) completed a meta-analysis, examining the effectiveness of treatments for adolescent SUD. They concluded, similarly, that some research suggested that FBTs may be more efficacious for Hispanic youth than CBT. They also found that group-based treatment may not work as well for Hispanic youth compared with White and Black adolescents. However, recent research has found that ethnic identity may moderate findings for Hispanic adolescents receiving group treatment. Burrow-Sanchez, Minami, and Hops (2015) conducted an RCT to compare a culturally-tailored CBT-group versus standard CBT-group for Hispanic adolescents with SUD. They found that Hispanic adolescents with a strong ethnic identity improved more in the culturally-tailored CBT group than Hispanic adolescents with weaker endorsement of ethnic identity. Thus, group treatment may be effective for Hispanic youth, but self-reported strength of ethnic identity may be important constructs to consider in choosing the type of group treatment for an adolescent with a SUD.

More recent work related to individual (e.g., Clair et al., 2013) and family therapy for adolescent SUDs has additionally found evidence for some moderating role of race/ethnicity. As discussed above, Greenbaum et al. (2015) integrated data from multiple RCTs comparing MDFT with individual CBT, residential treatment, and adolescent group treatment to assess the potential role of sex and race/ethnicity as moderators of adolescent SUD treatment outcome. Regarding race/ethnicity, the authors reported that SUD outcomes did not differ for Hispanic youth receiving MDFT versus a comparison treatment (n=225; Cohen’s d = 0.19) indicating that they improved on substance use frequency and consequences in all treatment conditions. However, MDFT was found to be more effective than comparison treatments for Black (n=329; Cohen’s d = 1.95) and White youth (n=92; Cohen’s d = 1.75; Greenbaum et al., 2015). In contrast to these findings, other research indicates that evidence-based family treatment is equally effective across racial/ethnic groups, particularly when there is a racial/ethnic match between therapist and adolescent (Henggeler & Sheidow, 2012). Likewise, recent work comparing A-CRA with and without refusal skill training for adolescent SUD did not find that treatment outcomes were moderated by race/ethnicity (Smith, Tabb, Fisher, & Cleeland, 2014). Heterogeneity within racial/ethnic subgroups further complicates the interpretation of race/ethnicity as a moderator of treatment response and may contribute to mixed findings across studies. This issue was discussed in Burrow-Sanchez et al. (2015), which is why the authors deemed tailoring SUD treatment based on level of race/ethnic identity more fruitful than simply treating all Hispanic participants homogenously. Work attempting to improve SUD care for adolescents based on race/ethnicity should, thus, consider the heterogenous aspects within one’s race/ethnicity as opposed to only between group differences.

Co-occurring psychopathology and symptom severity.

The role of co-occurring psychopathology and symptom severity in moderating SUD treatment outcomes emphasizes the importance of addressing individual needs and patient-centered care. Thus, research attempting to uncover the interaction of these variables is essential, but may depend on the co-occurring disorder and treatment modality. Importantly, there does seem to be converging evidence that more intensive treatments (e.g., FBTs, individual CBT plus medication) are more effective at reducing substance use in youth with a co-occurring disruptive behavior disorder (e.g., conduct disorder, ADHD; Henderson, Dakof, Greenbaum, & Liddle, 2010; Hendriks et al., 2012; Ryan, Stanger, Thostenson, Whitmore, & Budney, 2013; Tamm et al., 2013; Tripodi, Bender, Litschge, & Vaughn, 2010). For example, a recent meta-analysis looking at whether MDFT improved outcomes for adolescents with co-occurring SUD and a disruptive behavior disorder found that youth higher in severity (in both SUD and disruptive behavior) improved more after MDFT than youth lower in severity (van der Pol et al., 2017). It is possible that higher pretreatment SUD severity and co-occurring psychopathology predict greater improvement post-treatment because there is more potential room for improvement (e.g., Brunelle et al., 2013; de Gee, Verdurmen, Bransen, de Johnge, & Schippers, 2014; Hogue, Henderson, & Schmidt, 2017). However, some evidence suggests that treatment modalities that are less intense (e.g., 1–2 sessions of a brief motivational intervention) have shown null findings for youth higher in substance use severity (e.g., Gmel, Venzin, Marmet, Danko, & Labhart, 2012) suggesting that therapy dosage (length of treatment) and/or modality (e.g., family v. group) plays a key role in whether more severe adolescents improve.

In contrast to co-occurring disruptive behavior disorders, co-occurring depression appears to be equivocally associated with SUD treatment outcomes (Hersh et al., 2013; Hersh, Curry, & Kaminer, 2014). For example, Hersh et al. (2014) reviewed the literature to elucidate the effect of co-occurring depression on SUD treatment outcomes and did not find that depression affected outcomes in a consistent manner. They concluded that methodological differences between studies (e.g., timeframe for measuring depression, depression categorized as dichotomous or continuous, type of SUD outcome assessed) most likely explain why co-occurring depression inconsistently affects SUD treatment outcomes.

Individual differences and social context.

Last, limited research has looked at individual differences (e.g., personality) and social context (e.g., parent involvement) to assess whether these might moderate response to SUD treatment. For example, Piehler and Winters (2017) found that adolescents with a more maladaptive decision-making style (e.g., more impulsive, careless) reduced their alcohol use more than youth with a less maladaptive decision-making style after a brief MI-based substance use intervention with parental involvement. In terms of social context, Shelef and colleagues (2005) looked at whether the parent-therapist alliance during MDFT treatment for adolescent SUD improved SUD outcome. The authors found that the adolescent-therapist alliance predicted less substance use problems posttreatment when the parent-therapist alliance was moderate or high. Results from both studies point to the importance of engaging parents in adolescent SUD treatment, although sample size was low in the Shelef et al. study (N=65), indicating that findings should be interpreted with caution. Unfortunately, even though peers and parents play a critical role in influencing adolescent substance use trajectories, there are a dearth of recent studies assessing peer or parent influences as moderators of adolescent SUD treatment. Instead, researchers have examined these variables in the context of adolescents seeking treatment for a variety of problems (not just SUD; e.g., Boxer, 2011) or as mediators of treatment (particularly parenting practices), theorizing that treatment may change how parents interact with the adolescent, which in turn affects change in SUD outcomes (e.g., Henderson, Rowe, Dakof, Hawes, & Liddle, 2009; Schmidt, Liddle, & Dakof,1996; Winters et al., 2014).

Conclusions and Future Directions

Based on the emerging research on moderators of adolescent SUD treatment outcome in the past 15 years, there are mixed findings for most of the moderators examined, due, in part, to differences across studies in sample demographic characteristics and substance use outcomes measured (e.g., type of substance, single substance vs. multiple substances, frequency of use vs. symptom severity). However, one relatively consistent finding is that for adolescents with co-occurring SUD and externalizing disorders, greater duration and intensity of treatment, particularly family-based treatment, results in better outcomes. Youth with co-occurring psychopathology, or a dual diagnosis, constitute an important majority subgroup of adolescents in addictions treatment, with specific treatment needs, and who seem to benefit from intensive and integrated (behavioral and pharmacological) intervention (Hulvershorn, Quinn, & Scott, 2015). Dually-diagnosed youth also highlight the importance of considering transdiagnostic targets for intervention, such as improving cognitive control and emotion regulation, which are involved in both SUD and some types of co-occurring psychopathology (e.g., conduct problems, depression). Additionally, it appears that older adolescents may benefit more from cognitively-based interventions (e.g., identifying and challenging irrational thoughts) than younger adolescents.

This review highlights several areas for future research with regard to tailoring adolescent SUD treatment for specific subgroups to increase effectiveness. Specifically, in moving beyond investigating moderators that are immutable and based on heterogeneous demographic characteristics (e.g., age), future work should examine modifiable moderators (e.g., executive cognitive functioning; social network influences), which could be addressed during treatment to help improve outcomes. In addition, although baseline characteristics can be used to match adolescents to a given treatment (e.g., Henderson et al., 2010; Hendriks et al., 2012), moderators (e.g., co-occurring psychopathology) can inform treatment content that meets a specific subgroup’s needs (e.g., Piehler & Winters, 2017). Furthermore, moderators can help guide adjustments to treatment based on progress from session-to-session (e.g., using Sequential Multiple Assignment Randomized Trials (SMART); see Pfammatter et al., 2019). Future research also is needed to better understand the mechanisms (i.e., mediators) that explain how SUD treatments produce better outcomes for specific subgroups (see Peihler & Winters, 2017). Testing these moderated-mediation models can simultaneously help us understand “for whom” and “how” a specific intervention had an effect, and may ultimately provide personalized treatment for adolescents with a SUD.

An important conceptual model to guide future research on moderators of treatment outcome is the Addictions Neuroclinical Assessment (ANA; Kwako, Momenan, Litten, Koob, & Goldman, 2016). The ANA proposes three domains: executive function, incentive salience (e.g., reward processing), and negative emotionality, which are linked to specific phases in the addiction cycle (e.g., binge-intoxication; withdrawal-negative affect; preoccupation-anticipation). Multi-modal (e.g., DNA, neuroimaging), systematic assessment of ANA domains covers multiple levels of analysis, from genes to brain circuitry to behavior, including assessment of social and environmental influences (Kwako et al., 2016). While the ANA provides a heuristic framework specific to addictions, it is still undergoing validation (Voon et al., 2020), and was developed for use with adults. Ideally, an evidence- and measurement-based care model for youth SUD treatment would, like the ANA, assess multiple dimensions (e.g., co-occurring mental and physical health conditions, family and peer environment) over time (Hickie et al., 2019). Further, real-time assessment, enabled by technology, could facilitate personalized care, permitting a pro-active, rather than reactive approach to treatment (e.g., checking in after a lapse rather than seeing a patient on re-admission to treatment; Hickie et al., 2019). These future directions for research and conceptual models hold promise for moving the field closer to personalized treatment for adolescent SUD.

Funding details and acknowledgments:

This work was supported in part by the Department of Veterans Affairs Office of Academic Affiliations, Advanced Fellowship Program in Addiction Treatment, Advanced Fellowship Program in Mental Illness Research, Education and Clinical Center; the National Institute on Alcohol Abuse and Alcoholism under Grant R01AA023650; and the National Institute on Drug Abuse under Grants R01DA012237 and R20DA043181. The opinions expressed in this work are those of the authors and do not necessarily reflect those of the funders, institutions, the Department of Veterans Affairs, or the United States Government.

Footnotes

Declarations of interest: None

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