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Effect of positive and negative affective stimuli and beverage cues on measures of craving in non treatment-seeking alcoholics

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Abstract

Rationale

Laboratory paradigms are useful for investigating mechanisms of human alcohol cue reactivity in a highly controlled environment. A number of studies have examined the effects of beverage exposure or negative affective stimuli on cue reactivity independently, but only a few have reported on interaction effects between beverage cue and affective stimuli, and none have evaluated the effects of positive stimuli on beverage cue reactivity.

Objectives

To assess independent and interactive effects of both positive and negative affective stimuli and beverage cue on psychophysiological and subjective measures of reactivity in alcohol dependence.

Materials and methods

A total of 47 non-treatment-seeking paid volunteers with current alcohol dependence participated in a within-subjects trial where each was exposed to a standardized set of pleasant, neutral, or unpleasant visual stimuli followed by alcohol or water cues. Psychophysiological cue-reactivity measures were obtained during beverage presentation, and subjective reactivity measures were taken directly following beverage presentation.

Results

Mixed-effect models revealed a significant main effect of beverage and positive (but not negative) affective stimuli on subjective strength of craving and significant main effects of both positive and negative affective stimuli on ratings of emotionality. Despite the power to detect relatively small interaction effects, no significant interactions were observed between affect and beverage conditions on any reactivity measure.

Conclusions

A key finding of this study is that positive affective stimuli commonly associated with drinking situations can induce craving in the absence of alcohol cues. Main effects of beverage cue replicated results from previous studies. Beverage and affective cues showed no interaction effects.

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Notes

  1. The six possible permutations of positive (P), neutral (U), and negative (N) affective images were randomly but independently assigned to the first three and the last three exposures of a subject’s total sequence. Then, alcohol (A) or water (W) cues were assigned in random order to each distinct affective ordering. These procedures generated the final set of six orders, to which consecutive subjects were systematically (rotationally) assigned: (P/W,N/A,U/W–P/A,U/A,N/W), (N/A,U/A,P/W–N/W,P/A,U/W), (U/A,P/W,N/W–P/A,N/A,U/W), (P/A,U/W,N/A–U/A,P/W,N/W), (N/W,P/A,U/A–N/A,U/W,P/W), and (U/W,N/W,P/A–U/A,N/A-P/W). This approach thus takes account of the orderings of affective cues and the orderings of beverage cues but not all possible sequences of these orderings. Note that even if we had included all 6 × 6 = 36 possible sequences, with 47 subjects, we could not have had more than two observations per sequence, and balance would have been impossible (requiring multiples of 30 subjects).

  2. In an effort to minimize response burden and attendant fatigue, a subset of the full ACQ was substituted for the entire instrument. The four items selected were the highest loading on four factors in an analysis presented by Singleton et al. (1994). These items were not specifically validated as a subscale in that study, however.

  3. This somewhat shorter exposure time than employed in some studies (e.g., Monti et al. 1993a; Rubonis et al. 1994) was adopted in part to keep the entire protocol as brief as possible, an issue because of the repeated measures design. Pilot testing (not reported) had suggested that 90 s was a sufficient length of time for subjects to experience responses to presented beverages similar to what had been found with longer exposures, and subsequent results (reported below) suggest that this decision was reasonable.

  4. These difficulties were addressed in later versions of the software, so this was mainly a problem with cases collected early in the study. The subject pool was the same throughout, however, so this difficulty is not likely to have created outcome-related bias in the partially missing cases.

  5. Effect size calculations reported here reflect the difference in the predicted mean of the outcome variable Y for a dummy predictor = 1 versus 0. The denominator for this calculation is typically the standard deviation σ Y . In multilevel analyses, σ Y may be partitioned by level. But, in this study, it is of substantive interest to determine how much of the total variability in Y is generated by cue exposures, and this would imply that σ Y is the appropriate denominator.

  6. The study design produced this level of power to detect affect beverage cue interactions for two reasons: First, within-subject correlation of craving measures was modest (about 0.35) and second, because of random assignment, the interacting variables were stochastically independent. See McClelland and Judd (1993) for a full discussion.

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Acknowledgments

Funding for this project was provided by NIAAA, grant numbers R01AA012602 and R01AA014028 to BJM and the Pearson Center for Alcoholism and Addiction Research.

We are grateful to Dr. Brian Cutler for his assistance with data management and preliminary analyses for this project.

The experiments comply with the current laws of the country in which they were performed (USA).

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Authors and Affiliations

  1. The Pearson Center for Alcoholism and Addiction Research and Laboratory of Clinical Psychopharmacology, The Scripps Research Institute, 10550 North Torrey Pines Road, TPC-5, La Jolla, CA, 92037, USA

    Barbara J. Mason & Tobie Escher

  2. Oregon Research Institute, 1715 Franklin Blvd., Eugene, OR, 97403, USA

    John M. Light

  3. Tobacco Research and Intervention Program, Moffitt Cancer Center & Research Institute at the University of South Florida, 4115 East Fowler Avenue, Tampa, FL, 33617, USA

    David J. Drobes

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  1. Barbara J. Mason
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  2. John M. Light
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  3. Tobie Escher
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  4. David J. Drobes
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Correspondence to Barbara J. Mason.

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Mason, B.J., Light, J.M., Escher, T. et al. Effect of positive and negative affective stimuli and beverage cues on measures of craving in non treatment-seeking alcoholics. Psychopharmacology 200, 141–150 (2008). https://doi.org/10.1007/s00213-008-1192-x

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  • DOI: https://doi.org/10.1007/s00213-008-1192-x

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