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Journal of Studies on Alcohol and Drugs logoLink to Journal of Studies on Alcohol and Drugs
. 2023 Aug 29;84(4):560–569. doi: 10.15288/jsad.21-00392

Comparing the Efficacy of Mindfulness-Based Relapse Prevention Versus Relapse Prevention for Alcohol Use Disorder: A Randomized Control Trial

Carillon J Skrzynski a,,*, Hollis Karoly b, Jarrod M Ellingson c, Sarah L Hagerty a, Angela D Bryan a, Kent E Hutchison a,,c
PMCID: PMC10488314  PMID: 36971735

Abstract

Objective:

This study compared the efficacy of mindfulness-based relapse prevention (MBRP) with relapse prevention (RP) on reducing alcohol consumption. Secondary, exploratory aims assessed moderation of treatment effects by sex and cannabis use.

Method:

A total of 182 individuals (48.4% female; 21–60 years old) who reported drinking more than 14/21 drinks/week (for women and men, respectively) in the past 3 months but who wished to quit/reduce their drinking were recruited from Denver and Boulder, Colorado. Individuals were randomly assigned to 8 weeks of individual-based MBRP or RP treatment. Participants completed substance use assessments at baseline, halfway through and at the end of treatment, and 20 and 32 weeks after treatment. Primary outcomes were Alcohol Use Disorders Identification Test–consumption questions (AUDIT-C) scores, heavy drinking days (HDD), and drinks per drinking day (DDD).

Results:

Across treatments, drinking decreased over time (ps < .001), with a significant time-by-treatment interaction found for HDD (F = 3.50, p < .01). HDD initially decreased in both treatments but remained stable or increased after treatment for MBRP and RP participants, respectively. At follow-up, MBRP participants had significantly less HDD than RP participants. Sex did not moderate treatment effects (ps > .17), whereas cannabis use moderated treatment effects on DDD and HDD (F = 4.89, p < .001, and F = 4.30, p < .005, respectively). High cannabis use frequency was associated with continued posttreatment decreases in HDD/DDD for MBRP participants but increased HDD for RP participants. At low cannabis use frequency levels, HDD/DDD remained stable after treatment across groups.

Conclusions:

Drinking decreases were comparable across treatments, but HDD improvements diminished for RP participants after treatment. In addition, cannabis use moderated treatment efficacy for HDD/DDD.

More Than 14 million adults and 414,000 adolescents have an alcohol use disorder (AUD) (Substance Abuse and Mental Health Services Administration, 2019). Although treatment options are available, their success is often only moderate (e.g., Magill et al., 2019; Pierce et al., 2018). As such, continued research on treatment options and improvements remains a necessary avenue of investigation.

Mindfulness-based relapse prevention (MBRP) has shown promise in improving substance use outcomes including alcohol use. Large randomized controlled trials (RCTs) demonstrate that MBRP, versus relapse prevention (RP) or treatment as usual (TAU), results in less drug use among individuals with a range of substance use disorders (SUDs; Bowen et al., 2014; Witkiewitz et al., 2013, 2014). Although limited, research shows that MBRP has also resulted in improved treatment outcomes specifically for individuals with AUDs (e.g., Brown et al., 2020; von Hammerstein et al., 2019; Witkiewitz et al., 2019).

However, an under-investigated question is whether MBRP has enhanced efficacy for alcohol use relative to other active treatments. Only one study to date compared MBRP to another treatment (TAU) within individuals diagnosed with AUD, but found no outcome differences (Zgierska et al., 2019). However, RP treatment, which encompasses a similar treatment outline as MBRP but without the mindfulness component (i.e., cognitive-behavioral training excluding mindfulness meditation), may be a useful comparison. Given that the major difference between these treatments is the explicit inclusion of mindfulness techniques (e.g., urge surfing), comparing these programs can help isolate the unique contribution of mindfulness and, therefore, MBRP, in treating AUDs and alcohol misuse. In addition, although work exists comparing MBRP to RP in outpatient settings across SUDs, there is no research directly comparing these treatments in outpatient settings among individuals seeking alcohol treatment specifically or in the context of reducing harmful drinking (vs. abstinence). These gaps are important because individuals may be unmotivated to abstain entirely (e.g., Hodgins et al., 1997) and there are barriers to inpatient treatment. Indeed, two common obstacles to AUD treatment are fear of quitting drinking and shame/stigma (May & Nielsen, 2019), fears that may be heightened within inpatient programs. Thus, exploring the efficacy of MBRP versus RP in outpatient environments and among individuals whose goals are decreased drinking or total abstinence is an important research avenue.

Also important to understand is how treatment efficacy may differ depending on individual differences. One important characteristic relevant to AUD treatment is sex as a biological variable1 (hereafter referred to as “sex”). Research shows that sex is associated with alcohol consumption, with men drinking more often/greater amounts than women (e.g., Windle, 2016), but the extent to which sex influences alcohol treatment efficacy is equivocal. The literature has generally focused on gender versus sex or has not differentiated between them. However, there are well-established sex differences in metabolic/hormonal processes and anatomy, and differences in brain structure/function (McHugh et al., 2018), which may alter AUD progression and response to treatment. Despite this, studies assessing treatment differences present null or conflicting findings (i.e., better efficacy for men vs. women and vice versa) (Holzhauer et al., 2020). Similarly, research examining sex differences in mindfulness treatment has been mixed, but a few studies indicate that women prefer mindfulness-based treatments and may benefit more from them (Katz & Toner, 2013; Roos et al., 2019). We thus tentatively predict that women may respond better to MBRP than men, but existing findings make this uncertain.

Another important variable to consider in treatment is cannabis use. Cannabis use is relatively common among current drinkers (11.4%; Subbaraman & Kerr, 2015) and those who drink heavily specifically (34.4%; Crawford et al., 2021) and is related to greater alcohol quantity/frequency (e.g., Yurasek et al., 2017). However, like with sex, treatment efficacy research is mixed. For example, some studies show that cannabis use is associated with worse treatment outcomes (e.g., fewer days abstinent from alcohol; Subbaraman et al., 2019), whereas others show beneficial associations (e.g., reduced alcohol use, more days abstinent; Karoly et al., 2021; Metrik et al., 2011; Mikuriya, 2004). However, these findings are observational; thus, the nature/direction of the relationship between cannabis and alcohol treatment outcomes is unknown. In contrast, there is evidence from pre-clinical experimental work that cannabidiol, a main component of cannabis, can causally improve alcohol outcomes (e.g., Nona et al., 2019; Turna et al., 2019). In addition, research indicates that many individuals (e.g., medical cannabis users, patients with AUDs) use cannabis as a harm reduction tool for drinking via substitution (e.g., Lau et al., 2015; Mikuriya, 2004; Risso et al., 2020), although whether its effects accrue because of pharmacological or expectancy effects is unclear. Altogether, the data suggest the possibility that cannabis may have a beneficial influence on alcohol treatment. Further, a recent experimental study showed that mindfulness increased dose-dependently with Δ9-tetrahydrocannabinol, another main cannabis constituent (Murray & Srinivasa-Desikan, 2022). Thus, among those receiving MBRP treatment, more frequent cannabis use may be associated with greater drinking reductions. This may also be the case for RP treatment, although to a lesser extent. However, given conflicting findings and the lack of placebo-controlled experimental research and research on cannabis use in mindfulness treatment generally, this hypothesis is speculative.

Despite the uncertain nature of our hypotheses regarding sex and cannabis use, we believe these questions are crucial. With the National Institutes of Health mandate to explore sex in health research and the increasing availability of legal cannabis, investigating these factors and their relationship to alcohol treatment is important. For example, exploring how sex affects MBRP efficacy may lead to tailored treatment delivery/strategy options for women versus men. Similarly, knowing if/how cannabis relates to mindfulness treatment can address potential harms or benefits of use within treatment. Overall, these exploratory analyses may provide important directions for future hypothesis-driven research to concretely identify the impact of sex and cannabis on treatment outcomes.

The present study was implemented to compare MBRP versus RP in treating drinking via several aims. First, we compared treatment efficacy in an individually-delivered, outpatient, alcohol treatment context.2 Second, we explored whether treatment effects were moderated by sex and/or cannabis use. Individuals who wished to reduce their heavy drinking were randomly assigned to either 8 weeks of MBRP or RP treatment followed by two follow-up sessions (20 and 32 weeks after treatment). The main outcomes were average drinks per drinking day in the past month (i.e., drinks per drinking day; DDD), total days in the past month participants consumed at least 4/5 drinks per drinking occasion (for women/men, respectively) (i.e., heavy drinking days; HDD), and Alcohol Use Disorders Identification Test–consumption questions (i.e., AUDIT-C) scores. We hypothesized that MBRP participants would show lower AUDIT-C scores, DDD, and HDD than RP participants immediately after treatment and at follow-up (pre-registered hypothesis: https://clinicaltrials.gov/ct2/show/NCT02994043?term=NCT02994043&draw=2&rank=1). The investigation of treatment moderation by cannabis use and sex was exploratory and not pre-registered.

Method

Design

This study was a 2 (Treatment: MBRP vs. RP) × 5 (Time: Baseline, Weeks 4, 8, 20, 32) mixed factorial design in which treatment and time were between- and within-subjects factors, respectively. Individuals who met heavy drinking criteria and wished to quit/reduce their drinking were enrolled. Initially, an AUD diagnosis was required; however, because of procedure changes, diagnostic interviews were not conducted, and heavy drinking criteria were used instead. Study procedures and eligibility requirements are outlined below, and a participant flow diagram appears in Figure 1. The study and materials were approved by the University of Colorado Institutional Review Board. All participants provided written informed consent. Data collection occurred September 2016 through May 2021,3 ending when a sufficient sample size was reached. This was calculated as ~180 participants (~90 per treatment) via G*Power (Faul et al., 2007) based on a small effect size (f = .10), α = .05, and a correlation of .50 between repeated assessments.

Figure 1.

Figure 1.

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Participant flow diagram. MBRP = mindfulness-based relapse prevention; RP = relapse prevention; MRI = magnetic resonance imaging; LOC = loss of consciousness; BAC/ UA = blood alcohol concentration/urinalysis.

Participants

Recruitment. Recruitment included advertisements in mass media outlets, social media, and direct mailings within the Boulder/Denver area. Advertisements described the opportunity to earn up to $300 by participating in a study exploring mindfulness and biological mechanisms related to drinking.

Eligibility screening.4 Participants were screened via telephone and were eligible if they (a) were 21–60 years old; (b) were within 10 days of their last drink; (c) reported drinking more than 14/21 drinks/week with 2 or more heavy drinking days (≥4/5 drinks/occasion) during 4 consecutive weeks in the past 3 months for women and men, respectively; (d) had a breath alcohol level (BrAL) of 0 at screening (for consent); (e) were not currently taking any medications for psychiatric, substance use or mood disorders, and/or psychosis; (f) were not pregnant (if applicable; indicated by a pregnancy test at baseline); (g) tested negative for sedatives, opiates, cocaine, or amphetamine on urine drug screen at baseline; (h) did not meet criteria for a psychotic or bipolar disorder; (i) had a Clinical Institute Withdrawal Assessment score less than 8 (indicating no need for medical detox); and (j) wanted to reduce their drinking.

MBRP and RP interventions

Clinical psychology doctoral students and postdoctoral fellows implemented the interventions. Therapists received intensive training in motivational interviewing, MBRP, and RP by experts in these approaches via a 3-day (8 hours/day) workshop. Treatment manuals were reviewed (Bowen et al., 2021; Daley & Marlatt, 2006), and techniques were practiced with feedback given on their implementation. If new therapists came after the workshop, other training including online courses via American Psychological Association–accredited institutions was conducted. Eight additional training sessions were held after formal training by a supervising clinical psychology postdoctoral fellow.

Throughout the study, the clinical team met weekly for group supervision, during which clinical issues were discussed and adherence to manualized protocols was reinforced. Supervisors focused on maintaining therapist fidelity to treatments and preventing therapist drift during meetings via walking through patient–therapist conversations and noting any deviations from treatment plans. When deviations occurred, plans for correction moving forward were implemented.5 Further, therapists were encouraged to reach out to supervisors immediately when questions or concerns arose, and a licensed clinical psychologist was available for consultation during all sessions in case of timely clinical issues or emergencies.

Study procedures

Baseline session. After arriving at our laboratory at the University of Colorado Boulder, participants provided informed consent and completed a breath alcohol test. Any participant with a positive breath alcohol level (BrAL) or who reported drinking was rescheduled. If participants had a BrAL greater than .00% at a subsequent appointment, this session was “missed.”6

Participants then completed a urine toxicology screen followed by baseline questionnaires on demographics and substance use (see Measures). Following this, participants were assigned to MBRP or RP treatment based on a 1:1 ratio random assignment table generated before data collection by a study statistician.7

Treatment. Participants met with a trained therapist for 1-hour sessions one time per week in a private consultation room for a total of eight sessions across 2 months. Participants underwent breath alcohol analysis and completed their check-in survey before each session. At Weeks 4 and 8, participants completed a 30-day substance use assessment and self-report outcome measures (see Measures).

Follow-up assessments. Participants were scheduled to return to the lab for follow-up appointment sessions at Weeks 20 and 32. Participants again underwent breath alcohol analysis and completed the 30-day substance use assessment and self-report measures at these sessions.

Measures

Demographics questionnaire. Demographic information, including age and sex,8 was collected at baseline.

Substance use. The Timeline Followback (TLFB; Sobell et al., 1996) measured past-month alcohol use at each time point. Participants retrospectively reported total drinks consumed each day, which was used to calculate DDD and HDD. Cannabis use was also assessed per time point using the TLFB, and total number of days any cannabis was used (i.e., cannabis use frequency; hereafter referred to as CANN) was calculated.9

Hazardous alcohol use. The AUDIT-C measured hazardous drinking and includes the first three items from the original AUDIT, a well-validated 10-item questionnaire (Saunders et al., 1993). Items are summed, and higher scores indicate more hazardous drinking. Cronbach's alpha was low to acceptable across time points, ranging from .58 to .70, although lower alphas are not uncommon among scales with few items (Schmitt, 1996).

Dispositional mindfulness. The Five Facet Mindfulness Questionnaire–Short Form (FFMQ) is a 24-item self-report mindfulness measure adapted from the original 39-item FFMQ (Bohlmeijer et al., 2011). Items are averaged, and higher scores indicate more mindfulness. The baseline measurement was included in the study as a randomization check (i.e., analyses compared baseline scores across treatments to ensure no initial difference). Because of an oversight, 10 items were not administered at baseline; therefore, only 14 items were included in the final score.10 Reliability using the 14 items was excellent at all time points, with Cronbach's alpha ranging from .91 to .93.

Data analysis

Preliminary analyses were first conducted to ensure that randomization was successful. Analyses of variance and chi-square tests compared treatments on demographics (e.g., age), the main outcomes (i.e., AUDIT-C, DDD, HDD), CANN, and FFMQ at baseline. Main aims were tested with mixed-effects models for each outcome with time, treatment, and their interaction entered as predictors. Additional mixed-effects models were run to investigate moderation by sex and CANN by including these moderators and their twoand three-way interactions with treatment and time for each outcome. All models included random intercepts and slopes and used maximum likelihood estimation to account for missingness over time (see Figure 1 of CONSORT diagram documenting dropout numbers and reasons). All analyses were conducted using R (R Core Team, 2020), and all 182 participants were included.11

Results

Table 1 shows descriptive statistics and significance tests confirming that there were no baseline differences between treatments. On average, participants were equally split by sex, middle-aged, predominantly White, and of relatively high socioeconomic status. Participants scored an average of 8.01 (SD = 2.24) on the AUDIT-C, which is significantly higher than the alcohol misuse cutoff of 3 and 4 for women and men, respectively (Bradley et al., 2007). Participants consumed an average of 5.44 drinks per drinking day with an average of 12.17 days being heavy drinking days in the past month, and 45.05% were cannabis users (i.e., used ≥1 day in the past month at baseline).

Table 1.

Descriptive statistics and analysis of variance/chi-square results from preliminary results

graphic file with name jsad.21-00392tbl1.jpg

Variable MBRP (n = 90) % RP (n = 92) % Everyone (n = 182) % F/χ 2 p
Sex 0.80 .37
 Female 44.4% 52.2% 48.4%
 Male 55.6% 47.8% 51.6%
Race 6.58 .25
 White 94.4% 91.3% 92.9%
 American Indian/Alaska Native 4.4% 1.1% 2.8%
 Asian 0.0% 1.1% 0.6%
 Black/African American 0.0% 1.1% 0.6%
 Native Hawaiian/Pacific Islander 0.0% 1.1% 0.6%
 Mixed race/other 1.1% 4.4% 2.8%
Employment 1.34 .86
 Full time 78.9% 73.9% 76.4%
 Part time 12.2% 15.2% 13.7%
 Unemployed 4.4% 6.5% 5.5%
 Full-time student 2.2% 1.1% 1.7%
 Homemaker/stay-at-home parent 2.2% 3.3% 2.8%
M (SD) M (SD) M (SD)
Age 44.10 (10.03) 44.26 (10.29) 44.18 (10.14) 0.01 .92
AUDIT-C 8.13 (2.22) 7.89 (2.26) 8.01 (2.24) 0.53 .47
CANN 6.53 (10.44) 5.29 (8.61) 5.91 (9.56) 0.77 .38
DDD 5.56 (3.64) 5.33 (3.20) 5.44 (3.41) 0.21 .65
FFMQ 3.47 (0.55) 3.41 (0.58) 3.44 (0.56) 0.32 .57
HDD 12.61 (10.31) 11.74(10.48) 12.17 (10.38) 0.32 .57
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Notes: AUDIT-C = Alcohol Use Disorders Identification Test–consumption questions; CANN = cannabis use frequency; DDD = drinks per drinking day; FFMQ = Five-factor mindfulness questionnaire; HDD = heavy drinking days.

Table 2 shows results from the main mixed-effects models. There were no main effects of treatment, but there was a main effect of time for all measures showing improved outcomes over time (Figure 2). There were no time-by-treatment interactions for AUDIT-C or DDD, but there was for HDD; HDD decreased until treatment end for both MBRP and RP participants but from then to study end, HDD stabilized among MBRP participants and increased for RP participants (seen in Figure 2, panel A). This was confirmed with simple effects analyses (see Supplemental Material Table 2) using the emmeans package in R (Russell, 2021). (Supplemental material appears as an online-only addendum to this article on the journal's website.) At the end of the study, MBRP participants had significantly lower HDD than RP participants (~3 days; see Supplemental Material Table 3).12

Table 2.

Time, treatment, and time by treatment interaction mixed effects models

graphic file with name jsad.21-00392tbl2.jpg

Variable F p
AUDIT-C
 Time 39.28 <.001
 Treatment 0.08 .77
 Time x Treatment 0.94 .44
DDD
 Time 18.79 <.001
 Treatment 0.07 .79
 Time x Treatment 0.88 .48
HDD
 Time 21.15 <.001
 Treatment 0.11 .74
 Time x Treatment 3.50 <.01
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Notes: AUDIT-C = Alcohol Use Disorders Identification Test–consumption questions; DDD = drinks per drinking day; HDD = heavy drinking days.

Figure 2.

Figure 2.

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Alcohol Use Disorders Identification Test–consumption questions (AUDIT-C), drinks per drinking day (DDD), and heavy drinking days (HDD) across time by treatment. RP = Relapse prevention; MBRP = mindfulness-based relapse prevention. Notes: T1 = Baseline; T2 = Week 4 (halfway through treatment); T3 = Week 8 (immediately after treatment); T4 = Week 20 (first follow-up assessment); T5 = Week 32 (second follow-up assessment).

Table 3 shows results from the moderation mixed-effects models, including sex and CANN as covariates. Across outcomes, there was no significant moderation by sex (ps > .17), but there was a main effect; men had greater AUDIT-C scores, DDD, and HDD compared with women across time (Supplemental Materials Table 4). In contrast, CANN models resulted in significant three-way interactions for HDD and DDD, but only a main effect of CANN for AUDIT-C; greater CANN was associated with greater AUDIT-C scores. To explore the interactions, we graphed changes in HDD and DDD at different CANN levels (i.e., high, low, and average based on holding CANN at 1 SD above, below, and at the mean, respectively) across time for each treatment (Figure 3). Across treatments and CANN levels, HDD/DDD decreased from baseline to treatment end. However, at high CANN levels, HDD/DDD continued decreasing among MBRP participants, but DDD remained stable, and HDD increased for RP participants. At average levels, DDD remained stable after treatment for both groups as did HDD in the MBRP treatment, but HDD increased in the RP treatment. At low CANN levels, HDD/ DDD remained stable after treatment in both groups. Findings were confirmed with simple effects analyses (Supplemental Material Table 5).

Table 3.

Results from the mixed effects models with moderation of sex and cannabis use AUDIT-C DDD HDD

graphic file with name jsad.21-00392tbl3.jpg

Predictors AUDIT-C DDD HDD
F p F p F p
Time 39.90 <.001 18.62 <.001 18.37 <.001
Sex 25.04 <.001 14.87 <.001 54.04 <.001
CANN 3.21 .07 3.84 .05 3.88 .05
Treatment 0.00 .98 0.05 .83 0.96 .33
Time × Sex 0.33 .86 0.80 .52 0.88 .47
Time × Treatment 0.94 .44 1.01 .40 3.40 <.01
Sex × Treatment 0.10 .75 0.00 .97 1.86 .17
Time × Treatment × Sex 0.85 .49 0.70 .59 0.97 .42
Time 39.83 <.001 19.24 <.001 18.66 <.001
Sex 23.93 <.001 14.54 <.001 53.11 <.001
CANN 4.32 .04 3.86 <.05 3.62 .06
Treatment 0.18 .68 0.02 .88 0.02 .88
Time × CANN 0.44 .78 4.06 <.01 0.61 .65
Time × Treatment 0.86 .49 1.05 .38 3.49 <.01
CANN × Treatment 0.12 .73 1.85 .17 0.11 .74
Time × Treatment × CANN 1.40 .23 4.89 <.001 4.30 <.005
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Notes: AUDIT-C = Alcohol Use Disorders Identification Test–consumption questions; DDD = drinks per drinking day; HDD = heavy drinking days; CANN = cannabis use frequency.

Figure 3.

Figure 3.

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Drinks per drinking day (DDD) and heavy drinking days (HDD) over time by treatment across cannabis use frequency (CANN). Notes: T1 = Baseline; T2 = Week 4 (halfway through treatment); T3 = Week 8 (immediately after treatment); T4 = Week 20 (first follow-up assessment); T5 = Week 32 (second follow-up assessment).

Discussion

Participants in both the MBRP and RP treatment had improved alcohol outcomes. This is not surprising because both treatments are empirically supported treatments for maladaptive alcohol use (e.g., Carroll, 1996; Zgierska, 2019). However, contrary to hypotheses, there were no significant treatment differences for AUDIT-C scores or DDD. This is surprising because MBRP was superior to RP in reducing alcohol outcomes in prior studies (Bowen et al., 2014; Witkiewitz et al., 2013, 2014). However, this research included individuals who used multiple substances rather than alcohol specifically, which may explain the discrepancies. In addition, a previous study comparing MBRP to TAU in individuals diagnosed with AUD found that treatments led to comparable improvements (Zgierska, 2019), which parallels our findings.

In contrast, HDD did differ between treatments. For both treatments, HDD decreased until end of treatment but remained stable versus increased after treatment for MBRP and RP participants, respectively. At the end of the study, there was a small but significant difference of 3 more HDD among RP versus MBRP participants. We speculate that more frequent consumption of large quantities of alcohol is influenced by mindfulness training to a greater extent than the average number of drinks consumed on any particular day. That is, mindfulness training, compared with techniques instilled by RP therapy, may help individuals reduce the number of days they drink heavily, but not their drinking frequency or amount generally. Regardless, that the MBRP group seemed superior on at least one outcome compared with the RP group is meaningful and points to the advantages of mindfulness training in alcohol treatment.

Exploratory analyses showed that sex did not moderate treatment effects, although men consumed more alcohol overall than women (e.g., Wilsnack et al., 2000; Windle, 2016). Although CANN did not moderate treatment effectiveness as assessed by theAUDIT-C, there was a main effect; greater frequency of cannabis use was associated with higher AUDIT-C scores. In addition, CANN significantly moderated treatment effects on DDD and HDD. Higher CANN was associated with continued decreases in HDD and DDD for MBRP participants but increases in HDD for RP participants after treatment. At low CANN, HDD/DDD remained stable across treatments. Thus, it appears that concurrent, frequent cannabis use may influence treatment efficacy, although given the exploratory nature of these analyses and the fact that cannabis use was not experimentally manipulated, a causal relationship cannot be inferred. More research is needed to experimentally test such a relationship as well as ensure replicability. However, if further work continues to show such a pattern, it may behoove clinicians to assess cannabis use and incorporate strategies to address polysubstance use within RP treatment settings.

As with all research, there are limitations to the current study. The majority of participants were White and non-Hispanic/Latinx, and of relatively high socioeconomic status, which could compromise generalizability. Further work is needed with more diverse populations. This is especially important considering racial disparities in consumption and treatment; for example, Black and Hispanic populations may have increased substance use risk in later life compared with White populations (Gardner et al., 2020) but also face more obstacles to treatment (Matsuzaka & Knapp, 2020). In addition, we excluded individuals who were taking medications for psychiatric disorders and/or tested positive for illicit substances. This likely further restricts generalizability and may have had an impact on sex-specific interactions given the high rate of comorbid substance use among individuals diagnosed with AUD and women. Future studies should include individuals with multiple diagnoses. Of further note, the study recruited from and was conducted in the Denver/ Boulder area, which has a generally accepting norm concerning mindfulness practice, and may not be true of other regions. Related, the study advertised mindfulness treatment, which may have influenced recruitment and findings; among RP participants, 33 had prior mindfulness experience, and 11 had been practicing for 1 or more years. Replicating this work using more neutral advertising and excluding for prior mindfulness experience is indicated. Another limitation is the possibility that we were underpowered to test for three-way interactions. Again, replication and further investigation is crucial. A final limitation is that sex was based on self-reported gender. Although 99.47% of Colorado adults are cisgender (Herman et al., 2017), assuming that gender reflects sex may not be accurate for the whole sample. Further studies assessing gender and sex separately are indicated to explore sex differences in response to treatment.

Despite these limitations, this study provides important contributions to the AUD treatment literature. Across both treatments, alcohol consumption was reduced, providing continued support for their use in treating AUDs. Findings also indicate that cannabis use moderates alcohol treatment efficacy because there were lasting reductions within MBRP versus RP treatment with greater use. Although findings are exploratory and results should be interpreted cautiously, they are important and novel given the prevalence of co-occurring cannabis and alcohol use, and the rise in legal cannabis availability.

Acknowledgments

The authors acknowledge Erin Moe, Nicholas Gonyea, and Sasha Zabelski for their contributions in the recruitment of participants and collection of the data. We also thank the participants who volunteered their time to this research.

Footnotes

This work was supported by National Institutes of Health (NIH) Grant R01AA024632 (to Kent E. Hutchison).The content is solely the responsibility of the authors and does not represent the opinion of NIH, and they played no role in the study design; the collection, analysis, and interpretation of data; or the art. Clinicaltrials.gov registration number/pre-registration link: NCT02994043/ https://clinicaltrials.gov/ct2/show/NCT02994043?term=NCT02994043&draw=2&rank=1

1

Per the National Institutes of Health terminology, we use the phrase “sex as a biological variable” rather than “sex assigned at birth.”

2

All eight sessions were done in an individual rather than a group context, primarily for the logistical advantage of using a one-onone approach among outpatient treatment seekers. That is, unlike inpatient environments where patients are housed together at a single facility, it is difficult to schedule outpatient participant groups for multiple sessions given differing schedules. Using an individual-based treatment plan overcomes this scheduling challenge. This methodology is also informative because it tests the generalizability of the MBRP and RP treatments to the individual-level setting.

3

Because of the COVID-19 pandemic, which required a facility shutdown, 26 participants received at least one therapy session over Telehealth, an online portal. Because the pandemic may have affected some individuals’ drinking patterns, a variable indicating whether individuals received any Telehealth sessions versus those who received all sessions in person was created, and models were re-run including this variable. All study findings remained the same.

4

Medications for and/or meeting criteria for psychotic or bipolar disorders as well as illicit substance use (excluding cannabis use, which is recreationally legal and very common in Colorado) were included as exclusion criteria given their potential as confounds for treatment. Additionally, the larger project included a functional magnetic resonance imaging scan, which precludes pregnancy and is why this was also an exclusion criterion.

5

For a subset of participants (N = 53), there was also a fidelity checklist completed by the therapist after each therapy session to ensure that the components necessary to cover within each session were completed. On average, 97.33% of the necessary content was completed across sessions.

6

Missed sessions were monitored by the study team and discussed between the participant and their respective therapist.

7

Random assignment was not segmented based on other variables (e.g., sex).

8

Sex was based on a single item querying gender, with the options of female and male. Although gender and sex are distinct constructs, in the context of the current study, we assume that reported gender reflects participant sex because the majority of adults living in Colorado are cisgender (99.47%; Herman et al., 2017). However, we note this as a limitation in the discussion section.

9

Type (flower vs. edible) and amount (g/day for flower use [amount of edible use was not assessed]) of cannabis use was also measured, and information on these data can be found in Table 1 of supplemental materials.

10

The 14 items included items from each of the 5 subscales; observing: 4 items, describing: 3 items, acting with awareness: 2 items, nonjudging: 3 items, and nonreactivity: 2 items.

11

In all analyses, time was coded categorically, and cannabis use frequency was centered such that means from each time point were subtracted from each individual's use at that time point. However, we re-ran all analyses to include time as both a linear and a quadratic numerical variable, and model findings remained the same.

12

Although it was not an aim of the study, we also tested differences in days abstinent across treatments via the wilcox.test function from the stats package in R. Although there was no difference at any time during treatment (ps > .09), there was a significant difference at the first follow-up (W = 1,359.50, p = .04), with more days abstinent observed in the MBRP vs. RP treatment (M = 20.66 and 16.95, SD = 8.58 and 10.17, respectively) as well as at the last follow-up (W = 865.5, p < .001; M = 20.43 and 14.08, SD = 8.76 and 8.93, respectively).

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