The WAGER Vol. 9(13) – In the Mood for a Relapse?

Understanding the predictors of relapse is an important first step towards developing relapse prevention strategies. Whereas past studies have examined the predictors of relapse for substance abusers, few studies have characterized the experience for those with a gambling disorder. This week’s WAGER reports on a study by Hodgins and el-Guebaly (2004) that investigated the precipitants of relapse in a cohort of intemperate gamblers.

Hodgins and el-Guebaly recruited 101 research participants through media announcements. Inclusion criteria included a lifetime South Oak Gambling Screen (Lesieur & Blume, 1987) score greater than 4, a self-perceived gambling problem, having quit gambling within the past month, and a goal of abstinence from gambling. A quarter of the participants reported current treatment involvement and half reported past treatment involvement.

The researchers initially assessed the participants with a structured interview that included demographics, DSM-IV pathological gambling criteria, mood and substance abuse diagnoses, and gambling goal1. Follow-up interviews occurred at 3, 6 and 12 months to assess relapse, the main reasons for relapse, and the participant’s mood before the relapse. The researchers defined relapse as
“any gambling that violated their personal goal after a period of two weeks of abstinence.” In addition, half of the participants were randomly assigned to be contacted weekly and questioned about their current mood and gambling behaviors.

Of the 80 participants successfully followed for 12 months, 92% experienced a relapse. Optimism about winning was the most frequently reported precipitant of relapse for both genders (Table 1). Overall, however, significant gender differences emerged (X2 (7, N=244) = 22.6, p < .002). After cognitions about winning, men were more likely to cite the need to make money as a precipitant of relapse, whereas women were more likely to report they began gambling again to deal with negative emotions or situations. However, the authors found preceding moods were similar across genders. When questioned about their mood prior to relapsing, 70% of participants reported that they were thinking about finances. Participants were equally likely to report feelings of frustration (53%) and feelings of happiness (49%) prior to relapse. Likewise, active moods (45%) were as likely to be reported as tired, bored moods (44%).
Table 1. Main Reason for Relapse by Gender (Hodgins & el-Guebaly, 2004)

In this study, the participants provided the data. Self-report is subject to several limitations. Self-report can be misleading because participants often lack insight into their own behavior and might not be aware of the most important reasons for relapse. Self-report is also vulnerable to recall bias. The researchers used a  prospective design so they could compare information given in the weekly phone call prior to a relapse to the information reported later in the follow-up interview about the same relapse. They found no evidence in this study of a recall bias in reporting.

Prior to relapse, participants reported a wide range of moods with no dominant pattern. Further, men and women attributed their relapses to different causes. This suggests that there is not a one-size-fits-all model of gambling relapse. For men, the self-perceived driving force behind relapse appears to be financial need and a belief that this can be met through gambling returns; cognitive-behavioral treatment might counter this misconception. Alternatively, women often self-reported gambling in response to negative emotions or situations, suggesting they might be using gambling as an escape from other problems. Thus, women might have a greater need for treatment aimed at recognizing and resolving other life problems and/or mood disorders. Finally, Hodgins and el-Guebaly showed that both positive and negative affect states can precede gambling relapse behaviors. This is consistent with prior findings in the field of substance abuse: for drug users, the most important influences on relapse are negative affective states followed by urges and temptations and positive affect states (e.g., Marlatt & Gordon, 1985).

Comments on this article can be addressed to Rachel Kidman.

Notes

1 The specific measures used in the initial and follow-up interviews included the SOGS (Lesieur & Blume, 1987), the Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961), the Life Events Questionnaire (Vuchinich, Tucker, & Harllee, 1986), a modified version of  the Mood Adjectives Checklist (Larsen & Diener, 1992; Russell, 1980), and a modified Relapse Experience Interview (Hodgins, el-Guebaly, & Armstrong, 1995).

References

Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 561-571.

Hodgins, D., & el-Guebaly, N. (2004). Retrospective and Prospective Reports of Precipitants to Relapse in Pathological Gambling. Journal of Consulting & Clinical Psychology, 72(1), 72-80.

Hodgins, D., el-Guebaly, N., & Armstrong, S. (1995). Prospective and retrospective reports of mood states before relapse to substance abuse. Journal of Consulting & Clinical Psychology, 63, 400-407.

Larsen, R. J., & Diener, E. (1992). Promises and problems with the circumplex model of emotion. In M. S. Clark (Ed.), Emotion review of personality and social psychology. Newbury Park, CA: Sage.

Lesieur, H. R., & Blume, S. B. (1987). The South Oaks gambling screen (SOGS): A new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144(9), 1184-1188.
Marlatt, G. A., & Gordon, J. (Eds.). (1985). Relapse prevention. New York: Guilford.

Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161-1178.

Vuchinich, R. E., Tucker, J. A., & Harllee, L. M. (1986). Individual differences in the reliability of alcoholics’ report  of drinking. Paper presented at the 94th Annual Convention of the American Psychological Association, Washington, DC.