Elsevier

Drug and Alcohol Dependence

Volume 155, 1 October 2015, Pages 293-297
Drug and Alcohol Dependence

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Integrating alcohol response feedback in a brief intervention for young adult heavy drinkers who smoke: A pilot study

https://doi.org/10.1016/j.drugalcdep.2015.08.017Get rights and content

Highlights

  • Current alcohol brief intervention (BI) is modestly effective at reducing drinking.

  • Feedback on alcohol response phenotype is not currently included in standard BI.

  • This pilot study examined the utility of adding alcohol response feedback to BI.

  • Including this information improved drinking and smoking outcomes in young adults.

  • Future research should refine this approach to enhance BI outcomes.

Abstract

Background

More effective approaches are needed to enhance drinking and other health behavior (e.g., smoking) outcomes of alcohol brief intervention (BI). Young adult heavy drinkers often engage in other health risk behaviors and show sensitivity to alcohol's stimulating and rewarding effects, which predicts future alcohol-related problems. However, standard alcohol BIs do not address these issues. The current pilot study tested the utility of including feedback on alcohol response phenotype to improve BI outcomes among young adult heavy drinkers who smoke (HDS).

Methods

Thirty-three young adult (M ± SD age = 23.8 ± 2.1 years) HDS (8.7 ± 4.3 binge episodes/month; 23.6 ± 6.3 smoking days/month) were randomly assigned to standard alcohol BI (BI-S; n = 11), standard alcohol BI with personalized alcohol response feedback (BI-ARF; n = 10), or a health behavior attention control BI (AC; n = 11). Alcohol responses (stimulation, sedation, reward, and smoking urge) for the BI-ARF were recorded during a separate alcohol challenge session (.8 g/kg). Outcomes were past-month drinking and smoking behavior assessed at 1- and 6-months post-intervention.

Results

At 6-month follow-up, the BI-ARF produced significant reductions in binge drinking, alcohol-smoking co-use, drinking quantity and frequency, and smoking frequency, but not maximum drinks per occasion, relative to baseline. Overall, the BI-ARF produced larger reductions in drinking/smoking behaviors at follow-up than did the BI-S or AC.

Conclusions

Including personalized feedback on alcohol response phenotype may improve BI outcomes for young adult HDS. Additional research is warranted to enhance and refine this approach in a broader sample.

Introduction

In the United States, rates of binge drinking (i.e., consuming ≥5 drinks in an occasion for men or ≥4 for women) are highest among young adults age 18–29 years, placing this subgroup at increased risk for negative alcohol-related consequences including sexual misconduct, accidents, injury, and premature death (Abbey et al., 2001, Schoenborn et al., 2013). As young adults may not be interested in or appropriate for more intensive alcohol treatments, brief interventions (BIs) have been developed as time-limited (2–4 sessions) and cost-effective early interventions designed to mitigate future hazardous drinking and related consequences. Standard alcohol BIs, such as the Brief Alcohol Screening and Intervention for College Students protocol (BASICS; Dimeff et al., 1999), feature several main elements including comparison of one's drinking to age-matched norms, feedback on alcohol harm and consequences, and education on practical techniques for drinking reduction. BASICS and other related alcohol BIs are modestly effective at reducing overall alcohol consumption compared to no treatment, alcohol education, or brief advice (ds = .18–.43; Vasilaki et al., 2006) with similar effects for binge drinking (d = .25; Carey et al., 2006).

Given these relatively modest effect sizes, efforts are underway to improve and expand upon the scope of alcohol BI to reduce binge drinking and other risky health behaviors in young adults. These initiatives include providing additional educational materials, enhancing alternative non-drinking behaviors, and promoting other health behaviors, such as sleep quality and duration (Fucito et al., 2014, Murphy et al., 2012). Of note, smoking is not included in traditional alcohol BI despite data showing that approximately 50% of young adult heavy-drinkers also smoke (Weitzman and Chen, 2005), most often during drinking episodes (McKee et al., 2004). In laboratory-based studies, we have shown that heightened alcohol stimulation and reward in young binge drinkers prospectively predicted future alcohol-related problems in early middle adulthood (King et al., 2011, King et al., 2014). We and other investigators have also shown that alcohol acutely increases smoking urge (King and Epstein, 2005, Sayette et al., 2005), which may perpetuate comorbid use of these substances and increase health risks such as cancer, pulmonary, and cardiovascular disease (Negri et al., 1993, Pelucchi et al., 2006, Prabhu et al., 2014). However, feedback on smoking urge or alcohol response phenotype is not included in BASICS or other standard alcohol BIs. The potential importance of including alcohol response into BI has been recently highlighted by Schuckit and colleagues in their work showing that college students assessed for low sensitivity to alcohol's intoxicating and impairing effects, compared with those students with high sensitivity to these alcohol effects, demonstrated lower maximum drinks per occasion after viewing a video-based educational prevention module geared to this response type (Schuckit et al., 2015). Given the prospective role of alcohol responses to future drinking problems, measuring and providing feedback on one's response phenotype may improve outcomes of alcohol BI in young adults with hazardous drinking and smoking.

In sum, there is a need to enhance and improve outcomes with standard alcohol BI by incorporating novel intervention elements, and to reach drinkers who engage in other high-risk behaviors, such as smoking. In the present pilot study, we randomized non treatment-seeking young adult heavy (binge) drinkers who smoke (HDS) to one of three BI conditions: a standard alcohol BI, a standard alcohol BI with personalized feedback on alcohol response, and an attention control group. We hypothesized that adding personalized feedback on alcohol responses would produce greater reductions in drinking quantity, frequency, binge drinking, and alcohol-smoking co-use at 1- and 6-months after the intervention compared with the other two conditions.

Section snippets

Participants

Young adult heavy drinkers who smoke (HDS) were recruited from online advertisements. Screening included online questionnaires assessing demographics and general health history, as well as the Alcohol Use Disorders Identification Test (Babor et al., 2001), Fagerström Test for Nicotine Dependence (Heatherton et al., 1991), and the Online Timeline Follow-back (O-TLFB; Rueger et al., 2012) for past month alcohol and cigarette use. Inclusion criteria were age between 21 and 29 years, having no

Results

The groups did not differ on demographic and baseline characteristics (Table 1). Results from the alcohol laboratory session showed a mean peak breath alcohol concentration (BrAC) of .086 ± .013 SD g/210 L. For the BI-ARF group, during the ascending limb of the BrAC (baseline to peak), the majority of participants (90%) showed an increase in BAES stimulation, which was higher than sedation, and showed alcohol rewarding effects (80%) indicative of liking and wanting above neutral, positive effects.

Discussion

The results of this pilot study were promising for enhancing outcomes with standard alcohol BI in young adult HDS by incorporating targeted, personalized feedback about alcohol response phenotype and its implications into the intervention. Six months after this intervention (BI-ARF), binge drinking rates decreased by 64%, drinking-smoking co-use by 39%, drinking smoking frequency by 32%, and smoking frequency by 39%, compared to lesser reductions produced by either the standard BI (BI-S) or the

Role of funding source

This research was funded by National Institute on Alcohol Abuse and Alcoholism (NIAAA) R01-AA013746 (AK) and the University of Chicago Psychiatry Research Fund.

Conflict of interest statement

None.

Contributors

Drs. Fridberg and King conceived of the study design and drafted the manuscript. Dr. Cao provided input on statistical analysis and data presentation. All authors approved the final manuscript.

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