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This randomized controlled trial evaluated the use of two brief intervention conditions for adolescents (aged 12–18 years) who have been identified in a school setting as abusing alcohol and other drugs. Adolescents and their parent (N = 315) were randomly assigned to receive either a 2-session adolescent only (BI-A), 2-session adolescent and additional parent session (BI-AP), or assessment only control condition (CON). Interventions were manually guided and delivered in a school setting by trained counselors. Adolescents and parents were assessed at intake and at 6 months following the completion of the intervention. Analyses of relative (change from intake to 6-months) and absolute (status at 6-months) outcome variables indicated that for the most part, adolescents in the BI-A and BI-AP conditions showed significantly more reductions in drug use behaviors compared to the CON group. Also, youth receiving the BI-AP condition showed significantly better outcomes compared to the BI-A group on several variables. Problem-solving skills and utilization of additional counseling services mediated outcome. The value of a school-based brief intervention for students is discussed.
Although there is now a range of treatment for adolescents involved alcohol and other drugs (see reviews by Lipsey, Tanner-Smith, & Wilson, 2010; Williams & Chang, 2000; Winters,1999; Winters, Botzet, Fahnhorst & Koskey, 2009), treatment services adolescents involved with drugs are more of the exception than the rule. Only about 10% of adolescents who need treatment for problematic drug use currently receive it (Substance Abuse and Mental Health Services Administration, 2005). Identification of adolescent drug abusers in settings such as pediatric clinics (Levy, Winters, & Knight, 2010), juvenile detention systems (Dembo & Gulledge, 2009) and school assistance programs (Winters, Leitten, Wagner & O’Leary Tevyaw, 2007) may help to address this service gap for such drug using youth.
A promising treatment option for drug-involved adolescents is the use of brief interventions (BIs). These strategies, typically between 1 to 4 sessions, can be a stand-alone approaches or part of ongoing care (Center for Substance Abuse Treatment, 1999). Applications of BIs for adolescents may include a motivational prelude to engagement and participation in more intensive treatment, a substitute for more extended treatment for persons seeking assistance but placed on waiting lists, and use in health care or other opportunistic settings to facilitate referrals for additional specialized treatment (Tait & Hulse, 2003).
BIs have received a great deal of theoretical and empirical attention in the literature and several reviews have been conducted (for adults, see meta-analysis by Hettema, Steele & Miller, 2005; for youth – including adolescents and college students – see reviews by Erickson, Gerstle, & Feldstein, 2005; Grenard, Ames, Pentz & Sussman, 2006; Tait & Hulse, 2003; and see meta-analysis of use of motivational interviewing with drug-involved adolescents, Jensen et al., 2011). In our synthesis of these reviews of BI studies pertaining to adolescents, we have identified these themes: 1) motivational interviewing techniques are a cornerstone of most brief intervention programs (Hettema et al., 2005); 2) BI’s are being studied in multiple settings (Erickson et al., 2005; Grenard et al., 2005); 3) the efficacy of BI’s can be described as yielding mixed results: in some studies the BI did not outperform a control or comparison condition and yet for others BI’s showed significant efficacy (Hettema et al., 2005; Tait & Hulse, 2003); 4) less reductions in alcohol use are observed compared to other drugs (Tait & Hulse, 2003); and 5) mediating or moderating elements common to those BI efficacious programs include one-to-one sessions, therapist fidelity to intervention components, and feedback on substance use compared to norms (Erickson et al., 2005). Regarding the latter issue, mechanisms of BIs is an area that is understudied in the adolescent literature. The adult BI literature suggests that motivation to change, self-efficacy and counselor empathy promote change (Burke, Arkowitz, & Menchola, 2003; Hettema et al., 2005), and we know from the general adolescent drug treatment literature that variables associated with change include peer drug use, parenting practices, and co-existing mental disorders (Deas & Thomas, 2001; Dennis, Godley, Diamond, Tims, Babor, et al., 2004; Winters et al., 2009). However, for the most part, the key mechanisms necessary for successful BIs with youth have not been fully identified.
This investigation extends the extant literature and our earlier pilot study (Winters & Leitten, 2007) in two significant ways. First, we employed larger sample sizes for each of the three groups [2-session adolescent-only condition (BI-A), 3-session adolescent and parent condition (BI-AP), and an assessment only control group (CON)] in order to improve the statistical power of our analyses. Second, the assessment battery included measures of the four hypothesized mediating factors targeted by the intervention: motivation to change, problem solving skills, parenting practices and utilization of community services. As with the pilot study, the BIs were administered within a student assistance program. Although challenges exist, in-school settings can provide an opportunistic and practical setting in which BIs for students can be implemented (Meyers et al., 2001; Wagner, Tubman, & Gil, 2004; Winters et al., 2007). Furthermore, the prevalence rate of mild-to-moderate drug involvement among students has been show to be substantially high. Estimates from Substance Abuse Mental Health Service Administration (2005) put the figure at approximately 25% among 12–18-year-olds (defined as the aggregate of these mutually exclusive groups: met criteria for at least one substance abuse disorder but did not meet criteria for any substance dependence disorder, occasional binge drinker, frequent binge drinker, and recent user of an illicit drug) (Winters et al., 2007).
Specifically, we hypothesize that 1) both intervention groups (BI-A and BI-AP) will reveal superior outcomes compared to the assessment-only (CON) group, 2) the BI-AP condition will show better outcomes compared to the BI-A condition, and 3) our hypothesized mediators will be associated with drug use behaviors measured at 6-months post-intervention. The prediction of superior outcomes for the BI-AP group is based on the logic that outcomes in this group are expected to be mediated by two factors that are addressed in the BI-AP curriculum (parenting practices and utilization of additional services) that are not expected to exert influence in the condition with no parent session (BI-A).
Participants were 315 students from an urban public school system who were identified by school officials (counselor or student assistant staff) as a possible drug user and who met study eligibility criteria. Most (n=283) met a DSM-IV (American Psychiatric Association, 1994) diagnostic criteria for an alcohol use disorder, cannabis use disorder, or both (see Table 1 for details). All of the 32 students who did not meet criteria for any substance use disorder reported either 1 or 2 dependence criteria for at least one substance (often referred to as diagnostic orphans; Chung, Martin, Armstrong & Labouvie, 2002). Fifty-two percent were male, 68% were white, 9.6% had received prior drug treatment, and the mean age was 16.3. Statistical tests on background characteristics, including all measures of drug use involvement and consequences, revealed no significant between–group differences (see Table 1).
To help establish subject eligibility for the study, we administered at baseline the Substance Use Disorder module of the ADI to assess DSM-IV criteria for abuse and dependence (Winters & Henly, 1993). This highly structured interview covers all abuse and dependence criteria for any substance used five or more times during the prior 12 months. We assessed current (prior year) diagnosis. There are extensive test-retest reliability and validity psychometric data on the ADI (Winters & Henly, 1993; Winters, Stinchfield, Fulkerson, & Henly, 1993). At follow-up, we assessed with the ADI prior 6 months presence of abuse and dependence symptoms for alcohol and cannabis.
The number of cannabis use days, other illicit drug use days, and alcohol use days were measured for the prior 90 days at intake and at the 6-months follow-up with the TLFB procedure (Sobell & Sobell, 1996). The TLFB has been shown to be reliable and valid with adolescents (Winters, 2003).
This 11-item self-report scale from the Personal Experience Inventory (Henly & Winters, 1988) focuses on negative consequences of alcohol and other drug involvement, including legal, health, motor vehicle, social and family (alpha = .92; test-retest = .87). Each item has a four-point response option (strongly disagree/disagree/agree/strongly agree); score range 11–44.
SOCRATES (Miller & Tonigan, 1996) is an experimental instrument designed to assess readiness for change in alcohol and other drug abusers. We used the 19-item version that was developed using the items that most strongly identify the instrument’s overall general factor. Each item has a two-point response option (true/false; score range 19–38).
To measure the problem solving goals of the intervention, the 25-item, single scale Problem Solving Inventory (PSI; Latimer, Winters, D’Zurilla, & Nichols, 2005) was administered. This questionnaire measures the ability to solve everyday problems, as well as coping with substance use relapse situations (alpha = .93; test-retest = .86).
The child version of the APQ (Shelton, Frick & Wooten, 1996) is a 42-item questionnaire that measures positive and negative parenting styles related to parenting practices to the child. The APQ contains 5 subscales, three of which we used in this study: parental monitoring, inconsistent discipline, and positive parenting (alphas, 54 - .83; Dadds, Maujean & Fraser, 2003; Essau, Sasagawa, & Frick, 2006).
The TSR is a structured interview that incorporates responses from the parent in order to record the adolescent’s participation in drug treatment or related mental health services. The TSR has high test-retest reliability for services received during the prior 6 months and one-year (all kappas greater than .80) (Winters & Stinchfield, 2000). This interview was administered at 6-months follow-up. For this study we scored the TSR as a dichotomous variable (0 = no additional services; 1 = additional services).
Over a 26-month period, students between the ages of 13 and 17 and who presented for a chemical health assessment at participating public school systems in the Twin Cities metro area were potentially eligible for inclusion in the research study. A chemical health assessment is conducted by a school’s counselor if the student is (a) caught using drugs during school, (b) caught with drugs on his or her possession, or (c) referred by a teacher due to concerns that the student was using drugs. If in the counselor’s judgment the student did not have a serious mental health problem, and if there was no need for the counselor to report the family to social services because of abuse or suicide, then a recommendation was made to the parents that their son or daughter receive a referral for an assessment by the research staff to determine study eligibility. Study eligibility required that the student (a) be between 13 and 18 years of age, (b) scored at or greater than a score of 26 (a cut point indicating at least a mild drug abuse problem) on a drug abuse screening questionnaire, the Personal Experience Screening Questionnaire (PESQ; Winters, 1992), (c) not currently receiving treatment in another drug treatment program (9 screened out due to receiving current drug treatment), (d) not report during the research assessment the presence of an acute psychiatric problem or medical condition (e.g., suicidal, mental retardation (no cases were screened out for this reason), and (e) agreed to participate along with the parent (26 students declined participation). The school does not provide any in-school intervention or treatment services; thus, our intervention was unique to the school system.
If the student met study inclusion criteria, and assent (student) and consent (parent) forms were signed, subjects were subsequently assigned to the study. During Phase I of the study, eligible students/parents were randomly assigned within school to one of the two active conditions (BI-A or BI-AP). Upon reaching the target number of participants in the two active conditions (n = 136, BI-A; n = 123, BI-AP), then we moved to a Phase II recruitment procedure whereby, schools offered to eligible students/parents an opportunity to participate in an assessment-only program. During this phase we had to cut short our recruitment period to accommodate the need to conduct the full compliment of outcome assessments within the grant period. Thus, we recruited 56 controls (CON). The rationale for the Phase I and Phase II recruitment procedure is that prior pilot work with the schools indicated a large decline rate by parents when faced with the possibility of being assigned to an assessment-only condition. As noted above, the youth background characteristics between the three groups did not differ. Also, we experienced very low participation refusal rates across the three groups (n = 3, 4, and 3, respectively).
Interventions and assessments pertaining to the student were typically conducted in the school at the end of the school day; the parent session (BI-AP) was typically conducted in the home. Three students in the BI-AP group completed just one of their adolescent session (although the parent session was completed in all of these cases), and two parents in the BI-AP group did not complete their single session (although the adolescent completed his/her sessions). These 5 cases were retained in the data analysis. The other BI-A and BI-AP cases completed their intervention sessions. At 6-months follow-up, there were 4 attrition cases (BI-A, 2 cases; BI-AP, 1 case; CON, 1 case).
An experienced research assistant, who was blind to treatment condition, completed the intake and 6-months follow-up interviews. Assessments occurred in person. The student was administered the ADI, TLFB, PCS, PSQ SOCRATES and APQ at intake and 6-months follow-up and the TSR at 6-months follow-up. The parent was administered a parent version of the ADI and APQ at intake and 6-months follow-up and the TSR at 6-months follow-up. Students and parents were paid via Target store cards $20 after the intake assessment and $40 after completing the 6-month fallow-up.
The adolescent and parent brief intervention sessions was developed from existing adolescent and young adult programs organized around motivational interviewing and self-change programs (Breslin, Li, Sdao-Jarvie, Tupker, & Ittig-Deland, 2002; Miller & Rollnick, 1991; Monti, Colby, Barnett, Spirito, Rohsenow, et al., 1999). A first version of the intervention was field tested with six students at the participating schools and feedback from the therapist and clients were used to refine the manual (Winters & Leitten, 2001). A subsequent pilot study (Winters & Leitten, 2007) led to additional refinements to the manual.
Each brief intervention consists of 60-minute individual sessions delivered with a therapist using a motivational interviewing (MI) style. Sessions 1 and 2, separated by 7–10 days, are identical for the BI-A and BI-AP conditions. Session 1 focuses on eliciting information about the students’ alcohol and other drug use and related consequences, assessing their willingness to change (Prochaska, DiClemente, & Norcross, 1992), examining the pros and cons of their use via the decisional balance exercise (Miller & Rollnick, 1991), and discussing what goals for change the student would like to select and pursue. Consistent with a MI approach, students are allowed to negotiate goals with the counselor, although drug abstinence is encouraged. Session 2 focuses on the students’ progress in achieving the goals, identifying high risk situations associated with drug use triggers, discussing strategies to deal with social pressures to use drugs, assessing again willingness to change, and negotiating long-term goals. The third session (for BI-AP) involves delivering the same MI interviewing style to the primary parent or guardian. The focus of this session was informed by an integrative behavioral and family therapy approach (Liddle & Hogue, 2001; Waldron, 1997), and addresses these topics: their son or daughter’s substance use problem; parent monitoring and supervision to promote progress towards their child’s intervention goals; and healthy drug use behaviors and attitudes by the parent.
During program development we considered including a component to the brief intervention that involved challenging the client’s perceived norms regarding adolescent drug use. Whereas this element has shown to be an important feature of effective brief interventions for college student problem drinkers (Larimer & Cronce, 2002), its use in BIs for adolescent drug-abusers has been questioned (Levy, Winters, & Knight, 2010). In addition, many of consultants to the project advised against using this component. Thus, we chose to not include this content in the intervention.
Assignment of cases for both the BI-A and BI-AP conditions were equally divided between two therapists. Both therapists have experience in delivering structured treatment to substance abusers in a school setting. We employed a “crossed” design (i.e., the therapists administered both treatments), as recommended by Crits-Christoph and Mintz (1991). Treatment integrity was monitored through regular supervision meetings with the senior author (KCW) and audio tape reviews of all sessions by research assistants in order to complete session adherence checklists. The adherence data indicated that the therapists covered 98% of the key components of the intervention sessions.
First, relative and absolute outcomes were analyzed in terms of several drug use outcome variables (number of alcohol and cannabis use days; count of alcohol/cannabis abuse and dependence symptoms; and drug use consequences). Next we conducted the mediation analyses examine the effects of the mediators on the relationship between treatment condition and drug use outcome. Finally, we examined if moderator variables were related to outcome.
Outcomes were analyzed based on number of alcohol use days (TLFB), number of cannabis use days (TLFB), number of alcohol abuse and dependence symptoms (ADI), number of cannabis abuse and dependence symptoms (ADI), and score on the drug use consequences scale (PCS).
A repeated measures analysis of variance (Group × Time) with intake PESQ score as a covariate indicated significant Group × Time interactions on all of drug involvement variables (range of F (2), 3.2 – 28.6; all p’s < .05). The effect sizes (eta squared) ranged from .02 – .17. The ordering of group means for the 6-month outcome scores revealed two trends. First, both intervention groups (BI-AP and BI-A) revealed better outcomes compared to the CON group (Student-Newman-Keuls (SNK) post-hoc tests, p < .05) on five outcome variables (alcohol use days, cannabis use days, alcohol abuse symptoms, alcohol dependence symptoms, and PCS). Second, the BI-AP showed significantly better outcomes (p < .05) than the BI-A and CON groups on three variables (cannabis use days, cannabis abuse symptoms, and cannabis dependence symptoms). To summarize, at least one of the target condition (BI-A or BI-AP) was associated with better results than the CON group for each drug involvement variable, and the BI-AP group emerged as the best-performing group.
The next set of analyses examined the abstinence variables at 6-months (drug use abstinence, prior 90 days; absence of abuse/dependence symptoms, prior 6 months) (see Table 3). Significant chi-square results were obtained on all measures (range X2 (df=2), 7.6–10.6, all p levels < .05; range d, 1.8 – 2.1), except for percent absence of cannabis dependence symptoms (p = .06). The percentages of most outcome measures showed the following trend: BI-AP < BI-A < CON (see Table 3). Percentages range from 26% to 85%.
Mediation analyses were conducted to test the effects of mediators on the relationship between treatment condition and drug use outcome. The mediation variables were motivation to change (source youth, measured at 6-month outcome), problem solving (source youth, measured at 6-month outcome), parenting practices (source youth, measured at 6-month outcome); and additional services (source parent, composite measured at 6-month outcome). The outcome variable was the non-weighted sum of the prior 90 days of alcohol and cannabis use days reported at the 6-month follow-up. Given that the sample size is not large enough to conduct multiple meditational analyses we chose this outcome measure given that the distribution of this composite closely approximates a normal distribution for the study groups, and reduction of alcohol and cannabis use was a primary focus of change for the intervention. Table 4 provides a summary of the variables involved in the mediation analysis.
According to Baron and Kenny (1986), to meet criteria for mediation, a) predictor variable (treatment condition) must be significantly associated with criterion variable (alcohol and cannabis use outcome) ; b) predictor variable (treatment condition) must be significantly associated with the mediator variable (e.g., change in motivation); c) the mediator variable must have a significant effect on the criterion variable (drug use outcome); and d) the association between the predictor and the criterion variables should be zero (complete mediation) or the strength of association becomes reduced (partial mediation) when the mediator variable are controlled for in the analysis.
Zero-order Pearson’s correlations among the predictor, mediator and criterion variables for each model are presented in Table 5. As shown, treatment condition (predictor) was significantly related to drug use days and the mediator in all 4 models (steps a and b). Finally the mediator variables were significantly related to the criterion variable for models 1 and 3 (step c). In short, models 1 and 3 met the criteria described by Baron and Kenny (1986) as appropriate for further analysis for mediation.
Summary of the results from the mediation analyses are presented in Table 6 (step d). The magnitude of the effect of the mediator is shown via the contrast of betas before and after controlling the mediator, and also via the percent effect accounted for by the mediator, and Sobel tests are also presented. Sobel test examines whether the indirect effect of the predictor on the criterion variable via the mediator is significantly different from zero. In model 1, the results indicated that there was some evidence for partial mediation of problem solving between the treatment condition (BI-A, BI-AP vs. CON) and drug use days. The mediating effect of problem solving accounted for approximately 12% of the total effect of treatment condition to drug use days. In model 3, additional services provided evidence for mediation. This indicated that the relationship between treatment condition (BI-AP vs. BI-A & CON) and drug use days was mediated by usage of additional treatment services. The mediating effect of additional services accounted for approximately 32% of the total effect of treatment condition to the outcome variable.
Exploratory analysis added gender, age and race, baseline drug use severity (abuse diagnosis only or at least one dependence diagnosis) and therapist (2) in turn as independent variables to the above outcome analyses. No significant interactions with the two active treatment conditions were found on any of the outcome measures.
This study adds to the growing research on the use of brief interventions for adolescents. Adolescents experiencing mild to moderate drug abuse received either a two or three session school-based intervention and were assessed for drug use outcomes at six months follow-up. There are three major findings from the study: (1) both active conditions showed significant absolute and relative improvements across the range of outcomes compared to the assessment-only group; (2) the group that included a parent session (BI-AP) exhibited greater and more consistent intervention effects compared to the condition in which only the adolescent client received services (BI-A); and (3) support for the mediating effects for problem solving (BI-A and BI-AP) and use of additional services post-intervention (BI-AP) were found.
Consistent with other evaluations of brief interventions for adolescents (e.g., Grenard et al., 2006), the present study supports the view that this approach is an appropriate solution for mild-to-moderate drug abusing adolescents. In this light, brief interventions are increasing in viability as an effective treatment solution within the range of services for youth with problems associated with drug involvement. The current study showed that either brief intervention condition was associated with significant improvement in all of our drug use outcome variables, which included number of cannabis using days, number of alcohol using days, and number of drug-related consequences. Furthermore, the additional one session with the parent was associated with enhanced outcome effects compared to those youth who received just the two adolescent sessions. Only one outcome variable, alcohol abstinence prior 90 days, showed better outcome for the BI-A group compared to the BI-AP group. Nonetheless, our finding of better outcomes with the adolescent-parent condition is consistent with a large drug abuse treatment literature showing relatively better outcomes when parents are involved in the therapy compared to therapy involving only the adolescent (see Lipsey, Tanner-Smith, & Wilson, 2010; Rowe, 2010). Whereas these outcome findings are encouraging, it is important to note that abstinence prevalence rates of drug use were not particularly high across the two active conditions (range, 47% – 63%). Our study is remindful that expectations of the effects of BIs need to be realistic. Also, we found favorable outcomes for the assessment only control group. This finding provides a reminder that assessment only conditions can build empathy and may activate incentives for behavior change even in the absence of any direct instructions about behavior change (Borkovec & Sibrava, 2005). Also, there was no association observed between baseline drug involvement severity and intervention outcome, which suggests that a BI may have applicability to a range of youth varying in terms drug problem severity.
`The examination of mediation effects extends previous adolescent brief intervention research. Although statistically significant, the mediation effects sizes are modest in size, particularly when you compare their effect sizes to the findings associated with the absolute outcome data, where we found the largest effect sizes (Table 3). Thus, one can surmise that other factors were influencing outcome. Also, the mediators and the outcomes were assessed at the same observation point, which may have diminished the ability to observe a greater impact of the mediators on outcome. Nonetheless, the mediation results showed that reported improvement in problem solving skills was associated with reductions in drug use behavior in both active intervention groups (BI-A and BI-AP). It is relevant to consider the specific mechanism from the BI experience that influenced improvement in problem solving. The intervention may have increased the motivation to employ these skills, rather than increase these actual skills in the adolescents.
The second session of BI particularly focused on skills associated with coping and addressed triggers of drug use. This focus on skill-building may have been instrumental in achieving the mediating effect of problem solving on outcome. Better use of coping and related psychosocial functioning skills (e.g., focus on problem situation; generate several behavioral options, seek social supports) has been shown to be related to recovery among youth receiving intensive treatment for a substance dependence disorder (Brown, Meyers, Mott & Vik, 1994). The present study suggests that even a relatively minimal focus on coping strategies has benefit. For youth in the BI-AP group, positive outcome was associated with utilization by the teenager in post-BI services. These services were identified primarily as use of local community mental health and school counseling resources. It appears that the additional parent session in the BI-AP condition was an important element in activating the influence of additional services in reducing the adolescent’s drug use behaviors.
Interestingly, we did not observe a mediating effect of parenting behaviors on outcome, despite the emphasis in the parent session on improving parenting monitoring and supportive behaviors. Many family-based studies have identified parenting practices as a key active ingredient of change (e.g., Henderson, Rowe, Dakof, Hawes, & Liddle, 2009). Perhaps the single parent session in the BI-AP condition does not offer sufficient dosage to impact parenting enough to emerge as an intervening variable. Another possibility is that younger adolescents’ behaviors may be more influenced by parental monitoring than the somewhat older group in this study. Younger adolescents are likely to be more dependent on their parents when it comes to peer affiliations, involvement in recreational activities, and school connectedness, for example, and thus parental monitoring may have a greater impact on their behavior (Henderson et al., 2009). A fruitful area of additional research might be to explore if parenting practices have a differential mediating effect based on the age of the adolescent. Nonetheless, it appears that the discussion with parents about referral needs and possible interest in seeking more services was influential in eliciting more services sought by these families. This finding points to both the importance of parents in the rehabilitation of drug-abusing adolescents, as well as reinforcing that a role of BIs in the behavior change process is to activate more help-seeking behaviors among its participants. Thus, a possible beneficial mechanism of change with the BI-AP condition may be that it promotes additional help-seeking behavior, and such experiences reinforce the adolescent’s intervention goals.
There are implementation issues to consider when conducting BI’s in a school setting. On the positive side, in-school interventions may promote the program’s external validity given that many of the targets for behavior change may be related to the student’s school experiences (Wagner, Swensen, & Hughes, 2000). However, the implementation of any clinical-based service in schools may face practical and systemic challenges, such as concerns that doing so will label the school as having many students with serious drug problems, and the strain on school resources in the likelihood that additional training for school counselors would be needed in order to address several clinical issues (e.g., when to refer for additional drug treatment; dealing with co-existing mental or behavioral problems) (Winters et al., 2007). An interesting area for further research is to explore challenges and solutions to the transportability of BI’s in school settings.
Several limitations of the study should be noted. The study’s generalizability needs to be considered in the context that the sample sizes are not large, and our adolescent and parent participants are predominately white, middle class and suburban. Because the intervention was conducted in a school setting and after a student had been identified by the school as having a drug problem, our findings might not apply in other settings with different referral conditions. Our follow-up was only 6-months and thus we do not know if brief counseling can sustain significant long-term outcomes. Another limitation to consider is that the number of sessions between groups was not equated. Whereas youth in the two active conditions (BI-A and BI-AP) received equal number of adolescent sessions (2) across two weeks, there was an additional parent session one-week later for cases assigned to the BI-AP group. Also, students were not randomized to one of the three conditions in identical contexts. The assessment only control group was recruited later than the two intervention groups. It is relevant to note that the recruitment rates across all three groups were similar.
Finally, other variables not measured in the study could have affected outcome (e.g., personality traits), and our outcome data were based on self-report. Regarding this latter issue, one cannot rule out that our self-report data may reflect inaccuracies, despite studies that support the validity of adolescent drug abuse self-report (Maisto, Connors & Allen, 1995). These study design weaknesses are noted in the context that as a relatively new treatment shows early indications of efficacy, more rigorous and controlled studies need to be conducted (National Institute on Drug Abuse, 1995).
This study was supported by grants DA017492, AA14866, K02-DA15347, and P50-DA027841 from the National Institute on Health.
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Sincere appreciation is expressed to research staff Jessie Breyer and Jocelyn McClelland, and to the staff of school districts in the Twin Cities metropolitan area for their assistance with project implementation.