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. Author manuscript; available in PMC: 2022 Sep 1.
Published in final edited form as: Behav Ther. 2021 Feb 3;52(5):1198–1212. doi: 10.1016/j.beth.2021.01.007

Enhanced Brief Motivational Intervention for College Student Drinkers with ADHD: Goal Directed Activation as a Mechanism of Change

Lauren E Oddo a, Michael C Meinzer a,b, Alva Tang c, James G Murphy d, John M Vasko e, Carl W Lejuez f, Andrea Chronis-Tuscano a
PMCID: PMC8403236  NIHMSID: NIHMS1669732  PMID: 34452673

Abstract

College students with attention-deficit/hyperactivity disorder (ADHD) are at risk for alcohol-related problems and disorders relative to their typically developing peers. Despite risk, the optimal therapeutic approach for reducing problem alcohol use in students with ADHD, and mechanisms of change underlying treatment effects in this population, are largely unknown. The current study evaluated putative mechanisms of change in a randomized controlled trial of two harm reduction interventions for college student drinkers with ADHD (N = 113; 49% male): brief motivational intervention plus supportive counseling (BMI+SC) versus brief motivational intervention plus behavioral activation (BMI+BA). Results showed that participants in the BMI+BA condition engaged in more goal-directed activation and less avoidant behavior over the course of treatment compared to those in the BMI+SC condition, in turn predicting reductions in alcohol-related negative consequences. Effects were more robust 1-month following intervention, and diminished by 3-months. Sensitivity analyses revealed a significant indirect effect of treatment condition on alcohol-related negative consequence via reductions in avoidance over treatment. Post-hoc moderated mediations showed that BMI+BA engaged target mechanisms more robustly for students with more severe ADHD and depressive symptoms compared to BMI+SC. These findings support the application of BMI+BA intervention, particularly in targeting goal-directed activation and avoidance/rumination in at-risk student drinkers with ADHD.

Keywords: attention-deficit/hyperactivity disorder (ADHD), harmful alcohol use, brief motivational intervention, behavioral activation

Risky drinking in college is highly prevalent and confers risk for an array of negative consequences (Merrill & Carey, 2016). Alcohol-related problems and disorders arise, in part, from a pattern of aberrant reward-related decision-making wherein individuals are overly reinforced by their alcohol use relative to other activities (Bickel et al., 2014). Specifically, decisions to use alcohol are influenced by ongoing interactions among environmental-level factors (e.g., low availability of alternative rewards, social context supporting use) and person-level characteristics (e.g., tendency to discount delayed rewards), which enhance the reinforcing value of alcohol (Madden & Bickel, 2010).

ADHD in College: Person- and Environment-Level Risks

Many reward-related risk factors for alcohol-related problems and disorders nearly completely overlap with core dysfunctions of attention-deficit/hyperactivity disorder (ADHD), a neurodevelopmental disorder characterized by developmentally aberrant symptoms of inattention, hyperactivity, and impulsivity (APA, 2013). ADHD is considered a disorder of performance, with underlying deficits in executive function and self-regulation (Barkley, 1997). College success requires sustained self-regulated behavior in the context of easy access to alcohol and other substances, absent direct caregiver/teacher support and scaffolding (Merrill & Carey, 2016). In this context, students with ADHD experience more alcohol problems relative to their non-ADHD peers (Baker et al., 2012; Lee et al., 2011; Mesman, 2015). They show higher rates of alcohol use disorder and report more difficulties stopping drinking episodes, independent of average drinking levels (Rooney et al., 2012). Still, the optimal therapeutic approach for reducing alcohol problems in ADHD, and putative mechanisms of treatment effects, are largely unknown.

Brief Motivational Intervention

Brief motivational interventions (BMIs) aimed at reducing alcohol-related problems in college students unselected for ADHD are considered efficacious in the short term (Reid & Carey, 2015; Huh et al., 2015). The Brief Alcohol Screening and Intervention for College Students (BASICS) program is the prototypical BMI for college drinking, consisting of two in-person individual sessions: 1) assessment and identification of discussion topics and 2) self-monitoring of alcohol use and personalized feedback delivered via motivational interviewing (MI) style (Cronce & Larimer, 2011; Huh et al., 2015; Miller & Rollnick, 2012). Although BMIs have since been adapted in a variety of ways (i.e., group, peer delivery), these interventions generally share common principles, including the importance of delivering feedback on drinking patterns, sharing information about alcohol-related risks, and providing harm reduction strategies delivered in MI style (Ray et al., 2014). BMIs are designated as a Tier 1 prevention strategy by the National Institute on Alcohol Abuse and Alcoholism (i.e., demonstrated evidence of effectiveness; Cronce et al., 2018) and are popular programs in colleges nationwide.

Despite their popularity, the efficacy of BMIs are inconsistent across studies (Huh et al., 2015; Ray et al., 2014). In their meta-analysis of individual participant-level data of 17 randomized clinical trials evaluating BMIs, Huh and colleagues (2015) found that overall intervention effects were non-significant, with the exception of a small, statistically significant effect on alcohol problems in interventions with individual MI and personalized feedback. Indeed, many students continue to engage in problem alcohol use following BMIs (Carey et al., 2007). In particular, self-regulation deficits (i.e., a hallmark trait of ADHD) interfere with treatment efficacy and predict alcohol problems (Acuff et al., 2019; Ewing et al., 2009). Efforts to enhance the efficacy of BMIs, especially in the context of both person-level (i.e., ADHD) and environment-level (i.e., college) risks, are therefore necessary.

Behavioral Activation to Enhance Brief Motivational Intervention

Although identification of harm reduction goals and self-monitoring of drinking that characterizes most standard BMI protocols may be necessary in reducing alcohol problems, this content is likely insufficient in translating goals to “real world” behavior for students with ADHD. Indeed, executing harm reduction strategies (i.e., counting drinks, setting limits), are in direct opposition of the chronic self-regulation and higher order executive control impairments of ADHD; these strategies require forethought, planning, and self-regulated decision-making in the context of immediately reinforcing stimuli (i.e., alcohol, friends). Therefore, BMIs for students with ADHD likely require adjunctive therapeutic components to support the execution of drinking goals. Behavioral activation treatment (BA; Lejuez, Hopko, & Hopko, 2001) adapted for ADHD is one plausible therapeutic component that may target these constructs. Originally designed as a parsimonious and time-bound treatment for depression, BA is proposed as a core element in behavioral treatment across many forms of psychopathology. A key aim of BA is to decrease avoidant behavior and increase engagement in goal-directed activities by using a repertoire of behavioral skills (e.g., calendar system; monitoring behavior) designed to facilitate adaptive sources of positive reinforcement from one’s environment (Trew, 2011).

BA content may be particularly useful in enhancing BMIs for problem alcohol use in ADHD, as it considers activation as a functional response alternative to avoidance of adaptive behaviors (Kanter et al., 2007). For example, drinking with friends the night before an exam may be arguably more pleasant in the short-term, but this behavior could function as escape from aversive schoolwork, which is a frequent source of distress and impairment in ADHD (LaCount et al., 2018), in turn resulting in negative outcomes in the longer-term. In BA for ADHD, the client would be encouraged to study for the exam instead of drinking with friends and pair this goal with the executive functioning supports necessary for follow-through, such as a calendar system with reminders to support active retrieval of goals and planning rewards following execution. Additionally, students identify “assists,” or trusted people (i.e., friends, family) in their lives who can support execution of goals outside of sessions. For example, a student setting a goal to leave a party at a predetermined time would identify a friend with whom to leave. Given the high rates of delay discounting, poor frustration tolerance, and avoidance of activities that require sustained mental effort characteristic of ADHD (Seymour et al., 2019; Winter et al., 2019), BA may activate a repertoire of approach behaviors that lead to engagement in adaptive and rewarding activities, paired with the organizational and planning supports (i.e., calendar system, monitoring) necessary for follow-through. Emerging research on BA treatment for depression, only, supports increases in goal-directed activation as a key mechanism of depression symptom reduction (e.g., Santos et al., 2019), yet there is no known research examining this construct as a mechanism in alcohol intervention for college student drinkers with ADHD.

There is preliminary support for targeting reward/reinforcement constructs in alcohol and substance use interventions using samples unselected for ADHD. Among non-treatment seeking young adult drinkers, low reward availability was significantly associated with alcohol-related problems, above and beyond depressive symptoms and drinking level (Joyner et al., 2016). Low levels of substance-free reward also predict poor BMI response (Murphy et al., 2005), and change in substance-free reward mediates change in drinking following a BMI (Murphy et al, 2019). In their life enhancement treatment for substance use, Daughters et al. (2018) targeted an index of rewarding and value-driven behaviors using BA in group substance use treatment, finding that individuals reported significantly fewer adverse consequences from substance use one year following treatment. Similarly, Murphy et al. (2019) showed that college students who received a single behavioral economic session aimed at increasing engagement in substance-free activities following a single BMI session reported significant reductions in alcohol use and related problems over a 16-month follow-up period relative to students assigned to a relaxation training session. In all, these findings support the importance of increasing access to adaptive sources of positive reinforcement (Cuijpers et al., 2007). They also show that these processes are, at least partially, independent of mood and overall drinking levels (Joyner et al., 2016).

The Current Study

Recognizing the core impairments of ADHD are related to execution of goals, students with ADHD likely need additional content over time to target core treatment mechanisms in alcohol intervention. The current study is a secondary data analysis from a randomized controlled trial (RCT; Meinzer et al., 2021) of two harm reduction alcohol interventions for college students with ADHD engaging in risky drinking: 1) BMI plus BA (i.e., BMI+BA) and 2) BMI plus supportive counseling (i.e., BMI+SC). Indeed, an essential step in evaluating the additive effects of BA in enhanced BMI on putative mechanisms of alcohol-related problems is including an active comparison condition. Supportive counseling (SC) has been used as the comparison condition in RCTs of BA to “control for” therapist contact (e.g., Daughters et al., 2018). SC involves client-lead sessions wherein individuals meet with an unconditionally supportive therapist engaging in nonspecific therapeutic skills (i.e., reflective listening, thought journaling) designed to guide toward self-directed exploration, insight, and action without organizational/executive function supports (Hill, 2009). Thus, the active comparison condition of BMI+SC allows for a rigorous evaluation of the relative contribution of the structured components of BA on putative mechanisms that mirror those theorized to underly alcohol-related problems. Ultimately, understanding how treatments instantiate change allows for the development of more targeted and parsimonious approaches. This line of scientific inquiry is especially important in ADHD, given risk of alcohol-related negative consequences, and that core features of the disorder predict poorer response to standard BMIs (Carey et al., 2007; Ewing et al., 2009).

We explored engagement in a repertoire of goal-directed behaviors designed to increase adaptive sources of positive reinforcement and reduce avoidant behaviors (i.e., the treatment mechanism, hereon referred to as goal-directed “activation”; Santos et al., 2019) as a mechanism of change explaining the direct and indirect effects of condition on alcohol-relate negative consequences. We hypothesized that students in BMI+BA would evidence more goal-directed activation over the course of treatment relative to students in BMI+SC. In turn, we hypothesized that more goal-directed activation would predict fewer alcohol-related negative consequences 1 month following intervention (i.e., the most proximal study outcome timepoint). We also examine sustained effects at 3 months following intervention. In sensitivity analyses, we examined sub-domains of goal-directed activation to isolate possible drivers of treatment effects. Finally, we conducted exploratory post-hoc moderated mediation analyses to evaluate individual differences in baseline ADHD and depression symptom severity on treatment mechanisms and response, and the degree to which BMI+BA engaged the target mechanisms more robustly for individuals with more severe baseline presentation versus BMI+SC.

Method

Participants and Procedures

Participants (N=113; 49% male) in this study took part in an RCT comparing the efficacy of BMI+BA (n=55; 47.3% male) versus BMI+SC (n=58; 51.7% male) in reducing alcohol-related negative consequences among college student drinkers diagnosed with ADHD (Meinzer et al., 2021). The study consort diagram is illustrated in Figure 1. The average age of participants was 19.87 years (SD=1.44; 67.3% under 21). Demographic characteristics of the sample are presented in Table 1.

Figure 1.

Figure 1.

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CONSORT Diagram

Table 1.

Means, standard deviations, and correlations between key study variables

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.
1. S1 BADS 1.00
2. S2 BADS 0.84** 1.00
3. S3 BADS 0.82** 0.83** 1.00
4. S4 BADS 0.76** 0.75** 0.84** 1.00
5. Condition 0.01 0.06 0.09 0.07 1.00
6. BYAACQ-30 1-mo −0.38** −0.30** −0.29* −0.41** 0.10 1.00
7. BYAACQ-30 3-mo −0.43** −0.38** −0.35** −0.42** 0.11 0.50** 1.00
8. Sex (Male) −0.02 −0.03 0.12 0.06 0.05 −0.13 −0.23* 1.00
9. BL BDI −0.69 −0.63 −0.57** −0.62** 0.11 0.26* 0.32** 0.11 1.00
10. BL ACDS −0.28** −0.24* −0.27** −0.30** <0.01 −0.03 0.20 0.21* 0.25** 1.00
11. BL DDQ −0.10 −0.03 −0.11 −0.05 0.14 0.15 0.43** −0.31** −0.01 −0.06 1.00
M (SD) 97.94
(23.21)		 99.92
(21.86)		 102.40
(23.49)		 105.98
(22.40)		 0.50
(0.50)		 4.48
(3.80)		 5.32
(5.12)		 1.50
(0.50)		 13.42
(11.08)		 12.00
(3.13)		 15.00
(9.76)
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Notes. BADS = Behavioral Activation for Depression Scale; BYAACQ-30 = Brief Young Adult Alcohol Consequences Questionnaire, 30 Days; BDI = Beck Depression Inventory; ACDS = Adult ADHD Clinical Diagnostic Scale; DDQ = Daily Drinking Questionnaire; S1 = Session 1; S2 = Session 2; S3 = Session 3; S4 = Session 4. Condition = BMI+SC (coded as 0), BMI+BA (coded as 1)

*

p <0.05

**

p <0.01

Students were recruited through flyers, campus listservs, referrals from campus health services, and an online university survey pool at a large, public, Mid-Atlantic university. Interested students completed a telephone screen and were invited for a baseline assessment if they endorsed 3 or more ADHD symptoms on the Barkley Adult ADHD Rating Scale (BAARS; Barkley, 2011) and a score on the Alcohol Use Disorders Identification Test (AUDIT; Saunders et al., 1993) of 7 or greater for males or 5 of greater for females (Demartini & Carey, 2012).

Students who were eligible per the phone screen completed a baseline assessment, where they were administered background interviews, the Adult ADHD Clinical Diagnostic Scale (ACDS; Kessler et al., 2010), and modules of the Structured Clinical Interview of DSM-5 (SCID; First, Williams, Karg, & Spitzer, 2016). Participants also completed a battery of questionnaires, including self-report of ADHD symptoms and impairment via the BAARS and Barkley Functional Impairment Scale (BFIS; Barkley, 2011b). With consent from participants (n = 70), parent-report of current and childhood ADHD symptoms and impairment using the BAARS and BFIS was obtained for the purpose of ADHD diagnosis. Rigorously trained and supervised research staff administered diagnostic interviews, and each case was reviewed with an expert panel including 2 clinical psychologists. Final diagnoses were made based on expert consensus from the interviews, self- and parent-reports, which were synthesized using the “or rule” to arrive at a diagnosis of ADHD (Shemmassian & Lee, 2012).1 All procedures received IRB approval.

Students were eligible if they met the study inclusion criteria: (1) met DSM-5 diagnostic criteria for ADHD, (2) had elevated levels of problem drinking based on an AUDIT cut-off score, (3) lived independent of parents, and (4) were not currently participating (or were willing to suspend) psychotherapy for ADHD or substance abuse that would interfere with the study. All study participants were allowed to remain on a stable dose of prescribed psychiatric medication.

Interventions

Participants were randomized to BMI+ BA or BMI+SC. Both interventions spanned 5 sessions over 7 weeks, with sessions 1 through 4 conducted in person (60 minutes) and session 5 delivered via abbreviated telephone check-in (15-20 minutes). BMI+BA included 1 session of ADHD psychoeducation and personalized feedback delivered in MI style, 1 session of alcohol-focused BMI (including personalized alcohol feedback and goal setting), and 2 sessions of BA intervention adapted for ADHD. Finally, participants completed 1 telephone check-in, which was designed for brief BA content review and support. BMI+SC consisted of 1 session of ADHD psychoeducation and personalized feedback delivered in MI style, 1 session of alcohol-focused BMI (including personalized alcohol feedback and goal setting), and 2 sessions of SC, with a final telephone session for check-in (Hill, 2014). Unlike the BMI+BA, BMI+SC did not include cognitive-behavioral skills to address problem areas (e.g., Reynolds et al., 2011). Instead, therapists engaged in reflective listening and nondirective support of student’s self-identified topics.2

A more comprehensive description of the interventions and main findings can be found in (Meinzer et al., 2021). In brief, both interventions emphasized harm-reduction and the primary outcome was alcohol-related negative consequences (R34AA022133). Results from the main study (Meinzer et al., 2021) showed that students in both active treatment conditions reported significant reductions in alcohol-related negative consequences and alcohol use following treatment. Baseline depressive symptoms moderated treatment effects, such that individuals with more severe depressive symptoms evidenced fewer alcohol-related negative consequences in BMI+BA relative to BMI+SC.

Measures

Demographics.

Given prior research suggesting important variations in alcohol problems based on biological sex (Salvatore et al., 2017), students reported their demographic information at the baseline study visit. Sex was dichotomized to represent (1) male and (0) female.

Adult ADHD Clinical Diagnostic Scale (ACDS; Kessler et al., 2010).

The ACDS is a clinician-administered semi-structured interview used in the current study to assess the presence of ADHD symptoms during the past 6 months (current) and in childhood (before the age of 12).

Barkley Adult ADHD Self-Report Scale (BAARS; Barkley, 2011).

The BAARS is a self-and parent-report measure assessing the 18 DSM-5 symptoms of ADHD on a 4-point Likert scale. Higher scores indicate more ADHD symptoms. Three versions of the BAARS were used to support ADHD diagnosis: self-report of current symptoms, parent-report of current symptoms, parent-report of childhood symptoms. We used parent report (when available) to obtain a fuller picture of the student’s ADHD history and current functioning for diagnostic purposes (Sibley et al., 2012). The BAARS has shown adequate internal consistency (αs = .80 - .90; Barkley, 2011).

Behavioral Activation for Depression Scale (BADS; Kanter et al., 2006).

The BADS is a 25-item questionnaire measuring change in participants’ goal-directed activation, defined as engagement in approach behaviors that increase the likelihood of response contingent reinforcement from the environment. Participants completed the BADS weekly during each treatment session3, with a latent variable computed in the current analyses to reflect total goal-directed activation across treatment. On the BADS, all items are rated using a 7-point Likert scale (0 = “Not at all”; 6 = “Completely”). A higher total score on the BADS indicates greater goal-directed activation. The BADS includes four subscales (Kanter et al., 2006): avoidance/rumination (i.e., representing avoidance of negative aversive states and engagement in rumination rather than active problem solving), activation (i.e., representing overall engagement in activating activities), work/school impairment (i.e., representing consequences of inactivity in work and school), and social impairment (i.e., representing social isolation). The subscales assess a broad activation repertoire across domains of functioning. The BADS has been shown as both valid and reliable and has been used in undergraduate samples (Kanter et al., 2007). In this sample, baseline BADS scores were lower (i.e., more severe) than reports from published studies of non-clinical college student samples (e.g., Kanter et al., 2007). Internal consistency was α=.83.

Beck Depression Inventory (BDI; Beck, Brown, & Steer, 1996).

The BDI is a 21-item self-report measure of depressive symptoms in the past 2-weeks, used in the current study as a covariate. Participants rate each symptom on a 4-point Likert scale. The BDI has strong psychometric properties (Storch et al., 2004). The internal consistency in the current study was α=.92.

Alcohol Use Disorder Identification Test (AUDIT; Saunders et al., 1993).

The AUDIT is a 10-item brief self-report of risky drinking, used in this study to assess eligibility on the phone screen. Test-retest reliability is satisfactory in a general population sample (intra-class correlation coefficient = 0.84; Park et al., 2008). The internal consistency in this sample was α=.80.

Daily Drinking Questionnaire (DDQ; Collins, Parks, & Marlatt, 1985).

The DDQ is a self-report measure of weekly drinks consumed in a typical month. Participants list the average number of drinks consumed over the number of hours for each day. For our analyses, we used the total number of weekly drinks as a covariate in all analyses. Weekly drinking has been shown to be a reliable indicator of drinking-related problems (Borsari, Neal, Collins, & Carey, 2001).

Brief Young Adult Alcohol Consequences Questionnaire – Past 30 Days (BYAACQ-30; Kahler et al., 2008).

The BYAACQ-30 is a 24-item self-report measure designed to assess negative consequences of drinking in the past 30 days. The BYAACQ-30 was selected as the primary study outcome given the emphasis on harm reduction, not abstinence, in the interventions. Students completed the BYAACQ-30 1 and 3 months following the last treatment session. It is effective at discriminating severity of alcohol-related negative consequences (Kahler et al., 2005). Internal consistency of BYAACQ-30 in the present sample was α=.87.

Data Analytic Approach

In preliminary data analyses, we first used confirmatory factor analysis (CFA) to define a latent construct, capturing overall improvement in goal-directed activation across treatment (measured using the BADS total score). This approach maximized information from repeated assessments and ensured the robustness and validity of this latent construct. Subsequent to defining the latent variable for BADS across treatment, we tested our hypotheses by adding predictors (i.e., treatment condition) and outcome (i.e., alcohol-related negative consequences) in the main analyses. These structural equation models were performed in R using the “Lavaan” package (Rosseel, 2012). Model fit was evaluated based on these indices: χ2 goodness of fit, Comparative Fit Index (CFI; Bentler, 1990), Standardized Root Mean Square Residual (SRMR), and Root Mean Square Error of Approximation (RMSEA; Steiger, 1990). Conventional thresholds of these model fit indices indicate that CFI of .90 are acceptable (Schweizer, 2010) and .95 (Hu & Bentler, 1999) indicate good fit. SRMR values less than 0.08 are generally considered a good fit (Hu & Bentler, 1999). RMSEA values below .08 are considered acceptable (MacCallum et al., 1996) and values below .06 suggest good fit (Hu & Bentler, 1999).

Overall increase in goal-directed activation across treatments was measured as a latent construct with four indicators (i.e., total scores from the BADS scale for each of the active treatment sessions). A residual covariance between the last two treatment sessions was included to account for the increased dosage of (or more intensive) BA in the final two sessions. BADS scores across the four sessions were significantly and positively correlated with each other, r’s= 0.75-0.84, p’s < 0.01 (Table 1) and CFA of the measurement model revealed good fit (RMSEA < 0.001, SRMR = 0.003, CFI = 1.00); Factor loadings for BADS were above 0.40, range = 0.81-0.92, p’s < .01, (Supplemental Table S1). The BADS subscales also fit the data well: avoidance/rumination (RMSEA < 0.001, SRMR = 0.005, CFI = 1.00), activation (RMSEA = 0.077, SRMR = 0.01, CFI = 1.00), work/school impairment (RMSEA < 0.001, SRMR = 0.004, CFI = 1.00), and social impairment (RMSEA = 0.077, SRMR = 0.015, CFI = 0.99).

Successive multiple-group CFAs further tested measurement invariance across treatment groups (Vandenberg & Lance, 2000). We tested (1) configural invariance, with the same parameters specified in both treatment groups as the only invariance constraint; (2) metric invariance, which added equality constraints to factor loadings; and (3) scalar invariance, which added equality constraints to each indicators’ intercept. To determine measurement invariance, we examined changes in CFI (ΔCFI) and χ2 difference (Δχ2) values. Decreases in CFI values (≥ .01) and significant Δχ2 indicate a lack of invariance across groups (Cheung & Rensvold, 2002). Results in Supplemental Table S1 show invariance across both conditions. The same factor structure was representative in conditions, the factor loadings were comparable across groups, and individuals with the same score on the latent construct had the same score on observed variables.

We next evaluated the direct effect of condition on the primary study outcome: alcohol-related negative consequences (i.e., the BYAACQ-30). Second, we examined the effect of treatment condition (BMI+SC versus BMI+BA) on the proposed treatment mechanism variable: goal-directed activation (i.e., latent variable of total BADS). Third, we evaluated the effect of goal-directed activation (i.e., total BADS score) on alcohol-related negative consequences (i.e., BYAACQ-30). Full information maximum likelihood (FIML) estimation methods were used in all models. FIML reduces potential bias in parameter estimates due to missing data and uses all available data (Enders & Bandalos, 2001). To determine statistical significance of indirect effects, we used Monte Carlo simulation derived confidence intervals (CIs) (Tofighi & MacKinnon, 2016) in an interactive online tool with 20,000 repetitions (Preacher, Rucker, & Hayes, 2007; Preacher & Selig, 2012). Monte Carlo CIs were chosen to retain FIML estimation in R.

To determine which specific domain(s) of goal-directed activation induced changes in alcohol-related negative consequences, we repeated the mediation analyses with each of the four BADS subscales (i.e., avoidance/rumination, activation, work/school impairment, and social impairment). We first ensured the robustness and validity of the latent constructs of each subdomain of BADS (see Supplemental Table S1), then we added predictors and outcomes into the mediation models to evaluate exploratory indirect effects. Finally, post-hoc analyses evaluated individual differences on the target mechanisms and treatment response. We evaluated the conditional effects of baseline ADHD symptom severity (i.e., total symptom count on the ACDS) and depression symptom severity (i.e., total score on the BDI) on goal-directed activation and subdomains across treatment, and the degree to which BMI+BA engaged target mechanisms more robustly for individuals with more severe baseline presentation versus BMI+SC. We conducted a series of exploratory moderation analyses on each significant pathway, with statistically significant moderated paths included in a moderated mediation model to ensure parsimonious models.

In all analyses, we controlled for pre-intervention levels of alcohol-related negative consequences and goal-directed activation. Baseline levels of total weekly alcohol consumption, depressive symptoms, and biological sex were included as a-priori covariates in the current study. Baseline drinking levels were included due to main outcome findings (Meinzer et al., 2021) showing significant mean differences between BMI+BA and BMI+SC on baseline drinking quantity (p <.005): participants in BMI+BA reported drinking significantly more at baseline than those in BMI+SC. Baseline depressive symptoms were included as a covariate consistent with others (i.e., Joyner et al., 2016). Prior research shows variations in alcohol problems, drinking, and depression based on sex (Boggiano & Barrett, 1991; Salvatore et al., 2017), so we included sex as a control variable. Covariances were included among predictors.

Results

Descriptive statistics and bivariate associations for key study variables are presented in Table 1, and mediation results and model fit statistics are presented in Figure 2, and Table 2. All models fit the data well (e.g., CFI ≥ 0.95, RMSEA < 0.08). As seen in Figure 2 and Table 2 for the main analyses, we found no direct effect of treatment condition on alcohol-related negative consequences following intervention, consistent with (Meinzer et al., 2021). Participants in both conditions evidenced significant reductions in alcohol-related negative consequences following intervention. Examination of each pathway revealed a significant effect of condition on the latent factor of BADS total across sessions (b = 7.07, SE = 3.03, p = 0.02), such that participants in BMI+BA evidenced more total goal-directed activation on the BADS across treatment compared to those in BMI+SC. We also found a significant effect of the latent factor of BADS total across sessions on alcohol-related negative consequences at 1-month (b = −0.06, SE = 0.03, p = 0.03) but not 3-month (b = −0.05, SE = 0.03, p = 0.09) follow-up. Participants who evidenced more goal-directed activation across treatment experienced fewer alcohol-related negative consequences 1-month following treatment. Follow-up analyses on the indirect effect of condition on alcohol-related negative consequences via total goal-directed activation were non-significant at both 1-month (b = −0.40, SE = 0.26, 95% CI [−1.03, 0.004]) and 3-month (b = −0.40, SE = 0.26, 95% CI [−0.92, 0.06]) follow-up.

Figure 2.

Figure 2.

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Results from mediation analyses using (1) BADS total score (2) and BADS avoidance/rumination subscale.

Table 2.

Summary of results from BADS total score model

Mediation Mediation
1 Month Follow-up 3 Month Follow-up
b SE B b SE B
Effects on BADS (Across Treatment)
  Condition (BMI+BA) 6.73* 3.08 0.16 6.74* 3.07 0.16
  BYAACQ-30 (Baseline) −0.79* 0.40 −0.17 −0.79* 0.04 −0.17
  BDI (Baseline) −1.29** 0.15 −0.67 −1.29** 0.15 −0.67
  DDQ (Baseline) −0.10 0.18 −0.03 −0.09 0.18 −0.03
  Gender 1.06 3.16 0.03 1.03 3.16 0.02
Effects on BYAACQ-30
  Condition (BMI+BA) 0.65 0.77 0.08 0.62 0.83 0.06
  BADS (Across Treatment) −0.06* 0.03 −0.31 −0.05 0.03 −0.20
  BYAACQ-30 (Baseline) 0.33** 0.11 0.40 0.54** 0.11 0.50
  BDI (Baseline) −0.05 0.05 −0.13 −0.02 0.05 −0.05
  DDQ (Baseline) 0.01 0.05 −0.01 0.11* 0.05 0.22
  Gender −0.72 0.76 −0.09 −1.09 0.82 −0.11
Model Fit
  χ2 χ2(21) = 28.00, p = .12 χ2(21) = 27.64, p = .15
  CFI 0.99 0.99
  RMSEA 0.05 0.05
  SRMR 0.04 0.04
  R2 BYAACQ-30 0.30 0.53
  R2 Activation 0.56 0.56
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Notes. BADS = Behavioral Activation for Depression Scale; BYAACQ-30 = Brief Young Adult Alcohol Consequences Questionnaire; BDI = Beck Depression Inventory; DDQ = Daily Drinking Questionnaire

*

p <0.05

**

p <0.01

As shown in Figure 2, sensitivity analyses of subdomains of the BADS supported a significant effect of condition on avoidance/rumination (b = −2.97, SE = 1.21, p = 0.01). Participants receiving the BMI+BA intervention evidenced less avoidance/rumination across treatment compared to those in BMI+SC. In turn, participants who reported fewer avoidance/rumination across treatment experienced fewer alcohol-related negative consequences at 1-month follow-up (b = 0.18, SE = 0.07, p = 0.02). This effect was approaching statistical significance at 3-month follow-up (b = 0.14, SE = 0.08, p = 0.06). A significant indirect effect of condition on alcohol-related negative consequences by reductions in avoidance/rumination was observed at 1-month follow-up (b = −0.53, SE = 0.30, 95% CI [−1.27, −0.03]) but not at 3-month follow-up (b = −0.42, SE = 0.29, 95% CI [−1.11, 0.03]). No other sub-domains were significant mediators.

Finally, post-hoc analyses showed that BMI+BA engaged the target mechanisms more robustly for individuals with more severe baseline presentation versus BMI+SC. Relative to BMI+SC, individuals with more baseline ADHD symptoms in BMI+BA experienced more goal-directed activation (b = 8.39, SE = 3.72, p = 0.02, B = 0.18, R2 = 0.57) and greater reductions in avoidance/rumination (b = −3.48, SE = 1.42, p = 0.01, B = −0.19, R2 = 0.57). An exploratory moderated mediation showed that higher baseline ADHD symptoms significantly moderated the indirect effect of BMI+BA on alcohol-related negative consequences at 1-month follow up via avoidance/rumination, but not goal-directed activation (b = −0.50, SE = 0.30, 95% CI [−1.22, - 0.02], R2mediator = 0.60, R2outcome = 0.32). Similarly, higher levels of baseline depression symptoms in BMI+BA was related to more goal-directed activation (b = 7.71, SE = 3.55, p = 0.03, B = 0.17, R2 = 0.57) and greater reductions in avoidance/rumination (b = −3.21, SE = 1.35, p = 0.02, B = −0.19, R2 = 0.58) compared to BMI+SC. In turn, baseline depressive symptoms moderated the indirect effect of avoidance/rumination, but not goal-directed activation, on the relation between BMI+BA and alcohol-related negative consequences 1-month following intervention (b = −0.35, SE = 0.22, 95% CI [−0.88, −0.004], R2mediator = 0.58, R2outcome = 0.29).

Discussion

The conceptual overlap between ADHD and reward-related risk factors for alcohol-related problems and disorders has meaningful implications for understanding treatment mechanisms, particularly during the high-risk developmental period of college. The current study sought to evaluate the effect of BMI+BA versus BMI+SC on a broad goal-directed index of activation over the course of intervention and, in turn, the effect of goal-directed activation on change in alcohol-related negative consequences. Sensitivity analyses by specific domains of goal-directed activation related to avoidance/rumination, work, school, and social domains were also examined to evaluate possible drivers of treatment effects. Finally, post-hoc moderated mediation analyses evaluated the degree to which BMI+BA engaged these target mechanisms more robustly for individuals with more severe ADHD and depression symptoms versus BMI+SC. Overall, findings support the application of BMI+BA in targeting goal-directed activation among high-risk drinkers with ADHD, and especially those with more severe baseline symptomology.

Results showed that students receiving BMI+BA evidenced significantly more goal-directed activation over treatment relative to BMI+SC. BMI+BA incorporates daily activity and mood monitoring to facilitate active thinking in “real world” behaviors and consequences, with the goal to replace maladaptive behaviors with valued and goal-oriented alternatives. These preliminary findings are particularly robust considering the active comparison condition. That is, even though the participants in BMI+SC received BMI and the addition of non-specific clinical helping skills that facilitate self-directed introspection and action, participants in BMI+BA still reported an increase in goal-directed activation over and above this rigorous comparison.

Perhaps the more structured approach to identifying and scheduling activities across a broad range of life areas in BMI+BA was necessary in promoting goal-directed activation over the course of treatment for heavy drinking college students with ADHD. This possibility aligns with research showing atypical responses to reinforcement that are both pervasive and fundamental in ADHD (Kessler et al., 2010). Relative to their typically developing peers, youth with ADHD perform less well under partial (instead of full) reinforcement contingencies, and require clear structure and support in goal and task execution (Johansen et al., 2009; Luman et al., 2005). BMI+BA contains several therapeutic elements, each designed to increase the use of behavioral skills necessary to approach adaptive and feasible sources of response contingent positive reinforcement. For example, BA involves scheduling goal-directed activities in a calendar system, and incorporates reminders to facilitate follow-through. This content is in contrast to BMI+SC, which used daily journaling to mirror the activity monitoring in BMI+BA (Meinzer et al., 2021). Perhaps the monitoring and organizational and scheduling supports of BMI+BA were especially important in guiding adaptive resource allocation for students with ADHD, given their difficulties with organization, delaying gratification, sustained effort, and follow-through.

Expanding upon this effect, and consistent with study hypotheses, results showed that more goal-directed activation over treatments significantly predicted fewer alcohol-related negative consequences 1 month following intervention, although effects diminished over time (i.e., at 3-month follow-up). Indeed, individuals who misuse alcohol and other drugs tend to organize their behavior around access and consumption (MacKillop, 2016). Perhaps increasing resource allocation to valued and goal-directed activities supplanted time spent surrounding alcohol use with adaptive alternatives (Murphy et al. 2019).

Although the indirect effect of goal-directed activation was not supported in the mediation model, sensitivity analyses showed a significant indirect effect of condition on alcohol-related negative consequences via reductions in avoidance/rumination. Students in BMI+BA evidenced less avoidance/rumination over treatment relative to those in BMI+SC; less avoidance/rumination, in turn, predicted fewer alcohol-related negative consequences at 1-month follow-up. Notably, treatment effects faded over time (i.e., at 3-month follow-up) but were approaching significance. These findings suggest that reductions in avoidant/ruminative behaviors in part lead to reductions in alcohol-related negative consequences resulting from BMI+BA, and that avoidance/rumination may be a relatively more robust mechanism than broad goal-directed activation.

There are several possible explanations for these findings, each warranting substantial empirical attention and replication. Rumination (i.e., the process of thinking perseveratively about one’s feelings and problems without resolution or adaptive change) and avoidance (i.e., refraining from certain behaviors and activities) are considered complementary cognitive and behavioral phenomena leading to the inability to recognize and repair dysfunctional patterns of behavior (Bjornsson et al., 2010; Moulds et al., 2007). Individuals with ADHD display maladaptive coping (i.e., employing more procrastination/avoidance and ruminative strategies), perhaps due to well-documented difficulties with emotion regulation, frustration tolerance, and executive function (Anastopoulos et al., 2011; Barkley & Fischer, 2010; Seymour et al., 2019). Indeed, research has shown that ruminative responses predict depression in adults with ADHD (Oddo et al., 2016) and that negative automatic thoughts are significantly associated with ADHD, even after accounting for the confounding role of depression (Mitchell et al., 2013). Given that several symptoms of ADHD capture cognitive-behavioral avoidance, and that individuals with ADHD experience high rates of cross-domain impairment and self-regulatory failures, reductions in avoidance and rumination may be especially powerful ingredients of adaptive behavior change in this population. This possibility aligns with research showing behavioral approaches alone can modify maladaptive cognitions, without targeting them directly in treatment (Kanter et al., 2010).

Findings from the addiction literature also support the role of rumination and avoidance in negative outcomes. For example, in their sample of college students, Bravo et al. (2017) found that problem-focused rumination was associated with drinking to cope motives and alcohol-related problems. Others have shown that rumination predicts drinking status following brief cognitive-behavioral therapy for alcohol abuse, independent of depression and initial levels of alcohol use (Caselli et al., 2010). In light of the current findings, it is possible that BMI+BA included skills and strategies to supplant rumination/avoidance behaviors with appropriate goal-directed action and coping strategies, in turn leading to reductions in alcohol negative consequences.

Finally, post-hoc exploratory moderated mediation analyses suggest that BMI+BA intervention engaged the target mechanisms more robustly for students with more severe baseline ADHD and depression symptoms versus BMI+SC. As stated, the core content of BMI+BA includes targeted behavioral skills and strategies to support executive function, self-regulation, and approach behaviors. Although largely speculative given the post-hoc nature of these findings, perhaps individuals with more severe presentations require the explicit structure and support of BMI+BA to increase goal-directed activation and reduce avoidance/rumination. Future research on these findings is necessary to determine “for whom” more intensive intervention is warranted.

Limitations & Future Directions

The present findings should be interpreted in the context of study limitations. The current study represents secondary data analyses from a treatment development study with a relatively small sample and a rigorous control condition. Replication of this mediation effect in a larger, fully powered RCT is critical. We also did not collect data on other possible mechanisms of behavior change in BMI+BA versus BMI+SC. Indeed, there were no direct effects of treatment condition on outcomes (i.e., participants in both conditions reported fewer alcohol-related negative consequences; Meinzer et al., 2021), suggesting that BMI+SC may be operating via other mechanisms (i.e., many roads to Rome). It is possible that the SC component, particularly following BMI, was not entirely inert. Although including an already established treatment is the most stringent comparison (Chambless & Hollon, 1998), future studies with a delayed treatment condition in addition to the active comparison condition would provide additional information about natural change in these mechanisms over time. It is also notable that effects diminished over time (i.e., 3-month follow-up). Considering that ADHD is a chronic disorder characterized by performance deficits in self-regulation and executive function, it may be that additional follow-up booster sessions are necessary to sustain treatment effects in the long-term. Future research should balance efforts to meet the unique needs of this population with implementation realities (i.e., limited staffing at university counseling centers).

It is critical to evaluate additional mechanisms that may explain the significant effect of BMI+SC on alcohol problems. Future studies should examine the role of motivation to change, alcohol motives, protective behavioral strategies, self-regulation, social network drinking, and coping behaviors to evaluate a broader array of mechanisms of change tapping into the BMI component, alone. Additionally, though a notable strength of current study is incorporating weekly reports of goal-directed activation and sub-domains over the course of treatment, finer-grained measures of daily and momentary decision-making, alcohol consumption, and social-emotional experiences are needed to better understand the temporal unfolding of mechanisms.

Conclusion

The current study tested mechanisms of change in novel harm reduction interventions for college drinkers with ADHD, using an active comparison condition with the established intervention for college drinkers (i.e., BMI). Students in BMI+BA engaged in significantly more goal-directed activation over treatment relative to those in BMI+SC. The addition of a BA component to BMIs seems particularly important in increasing goal-directed activation and decreasing avoidance in college student drinkers with ADHD to reduce negative consequences from heavy drinking (particularly for those with higher baseline ADHD or depression severity), and provides further support for activity engagement/avoidance as a key mechanism of change in brief alcohol interventions (Murphy et al., 2019).

Supplementary Material

1

Highlights.

Key features of ADHD predict poorer outcomes in standard alcohol intervention

Behavioral Activation treatment increases goal-directed behavior and reduces avoidance

Behavioral Activation treatment targets mechanisms underlying alcohol-related problems

Acknowledgments

This project was funded by a grant from NIAAA R34AA022133 awarded to Andrea Chronis-Tuscano. During the preparation of this manuscript, Lauren Oddo received funding by a grant from NIAAA F31AA027937. The authors declare that they have no conflicts of interest.

Footnotes

1

Of the 70 participants with parent report, 2.86% (n = 2) required parental report to meet ADHD diagnostic criteria. 97.15% met criteria based on self-report alone. 75.2% (n = 85) reported a previous diagnosis of ADHD.

2

Twenty percent of all sessions (n = 90) were randomly selected to be coded by independent evaluators. Within BMI+BA and BMI+SC, 98.9% and 100% of the main points were covered across sessions, respectively. Therapists delivered the content with fidelity and used BA in the BMI+BA condition only (Meinzer et al., 2021).

3

Participants completed the BADS on a laptop computer alone at each of the sessions, without the therapist present. Additionally, therapists did not see participants’ reports or discuss answers throughout the intervention.

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