Alcohol's Effects on Video Lottery Terminal (VLT) Play ... - Springer Link

Journal of Gambling Studies, Vol. 21, No. 3, Fall 2005 ( 2005) DOI: 10.1007/s10899-005-3101-0

Alcohol’s Effects on Video Lottery Terminal (VLT) Play Among Probable Pathological and Non-Pathological Gamblers Michael Ellery Sherry H. Stewart Pamela Loba Dalhousie University

This study tested whether alcohol increases behaviors associated with video lottery terminal (VLT) play, particularly among probable pathological gamblers. Forty-four regular VLT players were designated either probable pathological gamblers or nonpathological gamblers on the basis of scores on the South Oaks Gambling Screen (SOGS); [Lesieur & Blume (1997). American Journal of Psychiatry, 144, 1184–1188] Gamblers from each SOGS category were randomly assigned to either a moderately intoxicating alcohol dose or a control beverage condition (n = 11 per cell in the 2 · 2 between-subjects design). Following beverage consumption and absorption, participants played a video poker VLT game for up to 30 minutes. Four behaviors were measured: ‘‘power-bets’’ (doubling bet after viewing only two cards of the five-card poker hand); total money spent; mean bet magnitude; and number of minutes played. Alcohol increased time spent playing and rate of power-bets, particular among the probable pathological gamblers. Post hoc analyses revealed that alcohol also influenced the proportion of losing hands played––increasing them among the probable pathological gamblers while decreasing them among the non-pathological gamblers. Clinical and policy implications of the findings are discussed. KEY WORDS: alcohol; gambling; video lottery terminals (VLTs); experimental methodology; laboratory-based study; electronic gambling machines (EGMs); pathological gambling; alcohol use disorder; comorbidity.

Please address correspondence to Michael Ellery, Dalhousie Gambling Laboratory, Department of Psychology, Dalhousie University, Life Sciences Centre, 1355 Oxford Street, Halifax, Nova Scotia, Canada B3H 4J1. E-mail: [email protected].

299 1050-5350/05/0900-0299/0 2005 Springer Science+Business Media, Inc.

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The prevalence of alcohol misuse among gamblers, especially among people experiencing gambling problems, is high (CunninghamWilliams, Cottler, Compton, & Spitznagel, 1998; Ramirez, McCormick, Russo, & Taber, 1983; Smart & Ferris, 1996). In fact, estimates of comorbidity for alcohol use disorder and pathological gambling have approached 50%, reflecting an increased risk for having one disorder if the other disorder is present (Cunningham-Williams et al., 1998). More specifically, rates of alcohol use disorders are significantly higher among pathological gamblers (Daghestani, Elenz, & Crayton, 1996), and rates of pathological gambling are dramatically increased among people who misuse alcohol (e.g., Lesieur & Heineman, 1988; see also Grant, Kushner, & Kim, in press). However, the precise nature of this relationship remains unclear (see Adler & Goleman, 1969; Carlton & Manovitz, 1987). A number of studies have examined the effects of alcohol intake on gambling behavior. Steele (1986) conducted a meta-analysis of 34 controlled, empirical studies directly investigating alcohol’s effect on 12 types of social behavior, including gambling and risk-taking. This metaanalysis concluded that intoxicated participants tended to gamble more and take greater risks than their sober counterparts. For example, a recent experimental study of the effects of alcohol consumption on gambling behavior conducted by Kyngdon and Dickerson (1999), found that gamblers who had consumed a mildly intoxicating dose of alcohol (i.e., about 30 g pure alcohol) persisted for twice as many gaming trials and lost significantly more of their original stake than those assigned to a placebo beverage condition. However, individual studies have not always been conclusive in their findings regarding the nature and direction of the effects of alcohol intake on indices of gambling behavior. For example, in an early experimental study by Sjo¨berg (1969), although participants demonstrated an increase in willingness to gamble in response to a low dose of alcohol (i.e., BAC = 0.03%), they also demonstrated a decrease in willingness to gamble in response to a relatively higher dose of alcohol (i.e., BAC = 0.07%). As another example, Breslin, Sobell, Cappell, Vakili, and Poulos (1999) conducted a study with 108 social drinkers and found that a moderately intoxicating dose of alcohol, i.e., targeting a BAC of 0.08%, failed to influence social drinkers’ betting tendencies in a laboratory-based gambling task. The present study attempts to draw conclusions about the effects of alcohol on gambling behavior, improving on previous work in a

MICHAEL ELLERY, SHERRY H. STEWART, AND PAMELA LOBA

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number of ways. The first improvement pertains to alcohol doses. The early work of Sjo¨berg (1969) clearly demonstrated that the effects of alcohol on gambling behavior may vary as a function of alcohol dose. The dose found to increase participants’ willingness to gamble in the Sjo¨berg (1969) study was in fact very similar to the doses that gamblers report consuming while engaged in gambling behavior (Focal Research, 1998). Thus, we investigated the effects of a mildly intoxicating dose of alcohol on gambling behavior. Second, many previous studies have investigated the effects of alcohol on gambling behavior using university student samples (e.g., Kyngdon & Dickerson, 1999). Thus, in order to improve generalizability, we chose to study gamblers from the community. A third improvement is that most previous studies have examined the effects of alcohol on laboratory-based gambling tasks instead of ecologically valid gambling tasks drawn from real-world gambling situations, affecting the generalizability of the results to real-world gambling situations (e.g., Breslin, et al., 1999; Kyngdon & Dickerson, 1999; Sjo¨berg, 1969). For example, no previous study has examined the effects of alcohol on VLT play, which is surprising given that VLT gambling is the predominant form of gambling behavior among pathological gamblers seeking treatment (Morgan, Kofoed, Buchkoski, & Carr, 1996) and that gambling on machines (compared to other forms of gambling) is associated with a more rapid development of gambling problems (Breen & Zimmerman, 2002). Given that VLTs are restricted to premises serving alcohol in many jurisdictions (Focal Research, 1998), it is particularly important to understand the effects of alcohol consumption on VLT play. Because alcohol may differentially affect various aspects of gambling behavior, it becomes important to include several dependent measures in any study of alcohol’s effects on gambling behavior (e.g., Kyngdon & Dickerson, 1999). A final improvement upon previous research pertains to the lack of attention to the role of individual-difference factors. It is possible that some individuals may be more sensitive than others to the adverse effects of alcohol on gambling behavior. Breslin et al. (1999) investigated ‘‘sensation seeking’’ as one such potentially important individual difference factor but did not find sensation seekers to be any more susceptible than non-sensation seekers to alcohol effects on their betting tendencies in the laboratory-based gambling task. In contrast, in an unpublished study, Leiserson, Hoaken, and Pihl (2001) showed

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that individuals scoring above the clinical cutoff on a measure of gambling problems (i.e., the South Oaks Gambling Screen, SOGS; Lesieur & Blume, 1987) increased their gambling behavior during a lab-based gambling task relative to those scoring below the SOGS cutoff, suggesting that problem gambler status may be one potentially important individual difference variable in this area. The present study improves upon the previous work by directly observing, experimentally, the effects of a mildly intoxicating dose of alcohol on various indices of risk-taking on an ecologically valid gambling task (i.e., a real-world VLT game) among communityrecruited regular gamblers sub-divided into probable pathological and non-pathological gambler groups. In this study, we used a 2 (beverage condition: alcohol vs. control) · 2 (gambler group: probable pathological vs. non-pathological) between-subjects design to test the following hypotheses. We expected that administration of a mildly intoxicating dose of alcohol, relative to control beverage administration, would lead to increases among regular gamblers on the following four aspects of VLT play: overall average bet magnitude, overall money spent on VLT play, overall time spent playing, and rate of power-bets (i.e., the number of times per minute an initial bet is doubled after viewing only the first two cards of the five-card poker hand). We expected gambler status to moderate these effects of alcohol on VLT play such that the effects of alcohol vs. control beverage on the dependent measures would be of greater magnitude among those participants classified as probable pathological gamblers, relative to those classified as non-pathological gamblers. METHOD Participants Forty-four participants were recruited from the community via printed advertising (i.e., notices posted at places where VLTs are played, and advertisements in local community newspapers), as well as via public television community bulletin boards. Participants were screened by telephone, at which time they were told about the nature of the study and the tasks they would be asked to complete. At the time of telephone contact, the participants were screened for the following exclusion criteria: (1) inability to speak/read English, (2) age of


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minority, (3) inexperience with VLT play (i.e., VLTs played less than once per month), (4) currently attempting to abstain from gambling, (5) medical contraindications to alcohol consumption, including use of certain medications (i.e., amphetamines, analgesics/narcotics, antianginal preparations, antibiotics, anticoagulants, anticonvulsants, antidepressants, antidiabetic drugs, antihistamines, antihypertensive drugs, barbiturates, diuretics, penicillin, sedative-hypnotics, major and minor tranquilizers) or presence of certain medical conditions (i.e., peripheral vascular disorder, hypertension, gastrointestinal disorder, neurological disorder, pulmonary disease, cardiac disease, arterial disease, diabetes, seizure disorder, liver disease), (6) allergy to the orange juice mix, (7) possible pregnancy, (8) possible drinking problems as determined by a score of five or more on the Brief Michigan Alcoholism Screening Test (B-MAST; Pokorny, Miller, & Kaplan, 1972). Demographics Demographic variables were analyzed in set of 2 · 2 (SOGS category · beverage condition) ANOVAs (i.e., Age, Total Years of Schooling, and Income) or Chi-square analysis in the case of the two dichotomous demographic variables (i.e., gender and marital status: coded as either living with a partner or not living with a partner) in order to ensure comparability of the four groups. For the set of 2 · 2 ANOVAs on the continuous demographic variables, the only significant effect revealed was a main effect of SOGS category on age, where probable pathological gamblers were significantly older than nonpathological gamblers (F1,40 = 6.17, p < .05). For the dichotomous demographic variables, no differences existed among the four groups, i.e., between probable pathological gamblers in the alcohol condition, non-pathological gamblers in the alcohol condition, probable pathological gamblers in the control condition, and non-pathological gamblers in the control condition, in terms of Gender (v2 = 0.42, n.s.) or Marital Status (v2 = 2.97, n.s.). Table 1 displays means (and SDs) for the demographic variables as a function of SOGS category and beverage condition. Measures For the purposes of telephone screening, we developed a standard telephone script, incorporating the scorable items from the SOGS

(n = 7) (n = 7) (9.00) (2.36) (1.63)

Drink alcohol during VLT play % Yes 64%

64%

31.73 14.30a 2.36

Smoke during VLT play % Yes

Age Years of schooling Income (1–7 scale)

28.73 14.89b 4.11b

55%

91%

36%

64%

M

(13.78) (1.90) (2.03)

(n = 6)

(n = 10)

(n = 4)

(n = 7)

SD

39.64 14.73 3.45

73%

82%

11%b

73%

M

SD

(12.87) (2.94) (1.75)

(n = 8)

(n = 9)

(n = 1)

(n = 8)

n = 11

Control

38.09 13.70a 3.45

64%

91%

27%

73%

M

SD

(9.75) (2.91) (1.75)

(n = 7)

(n = 10)

(n = 3)

(n = 8)

n = 11

Alcohol

Probable pathological gamblers

Note: N = 44 except where indicated via superscript (some participants did not provide complete data); aCell n = 10; bCell n = 9.

(n = 1)

10%a

Marital status % Living with a partner

(n = 7)

64%

SD

n = 11

n = 11

Gender % Male

M

Alcohol

Control

Non-pathological gamblers

Table 1 Means (and SDs) for the Demographic Variables and Self-Report Addictive Behaviors as Functions of Gambler Status (Probable Pathological vs. Non-Pathological Gambler) and Beverage Condition Alcohol vs. Control

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(Lesieur & Blume, 1987) in order to appropriately assign the participant to a condition within the 2 · 2. design. Problem gamblers were over-recruited (i.e., actively sought as potential participants on the basis of the results of telephone screening) in order to equate the n in each cell of the 2 · 2 (beverage condition · SOGS category) between-subjects design. Otherwise, assignment to one of the two beverage conditions was random. Demographic Questionnaire We used an author-compiled questionnaire to obtain information on the participants’ age, gender, education level (years of schooling), and annual income (on 7-point scale with anchors from 1 = ‘‘up to $10,000’’ to 7 = ‘‘more than $60,000’’ CDN per annum) (see Stewart, Collins, Blackburn, Ellery, & Klein, 2005). This measure did not query about race because the regular gamblers presenting for gambling studies at our laboratory are almost exclusively White. Addictive Behaviors Measure We used an author-compiled measure to assess certain addictive behaviors: smoking status (smoker, non-smoker), whether or not and how much the participant consumes alcohol while playing VLTs, and history of VLT use (i.e., frequency of VLT play per week, average amount spent playing VLTs, number of years playing VLTs) (see Stewart et al., 2005). The SOGS (Lesieur & Blume, 1987) The SOGS is a 16-item self-report questionnaire that asks respondents to describe their lifetime gambling habits. Eleven items are scored, and SOGS scores P 5 are used to identify ‘‘probable pathological gamblers’’ (Lesieur & Blume, 1987). The content of the SOGS (Lesieur & Blume, 1987) was derived from Gamblers Anonymous’ 20 questions and from DSM-III (APA, 1980) criteria, and from problem gambling counselors at the South Oaks Hospital in Amityville, NY. Internal consistency was estimated at a = .97, and test–retest reliability after 30 days was estimated at r = .71, revealing the SOGS to be a reliable instrument (Lesieur & Blume, 1987). The SOGS also appears to be a sensitive and specific instrument, making few errors in the classification of individuals as probable pathological and nonpathological gamblers relative to the DSM-III-R (APA, 1987) as the

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gold standard (Lesieur & Blume, 1987). False positive rates range from .7% to 1.4%, and false negatives range from .0% to 3.4% in three populations: Gamblers Anonymous members, university students, and hospital employees (Lesieur & Blume, 1987). Visual Analogue Scale of Subjective Intoxication (VAS; Kushner et al., 1996) We used a VAS to quantify the participants’ post beverage consumption experiences of feeling alcohol-intoxicated or drunk. Participants are asked to place a mark on a 100 mm line to rate how intoxicated they feel, with anchors of 0 = ‘‘not at all’’ and 100 = ‘‘extremely so’’. Distance (in mm) was measured from the 0 anchor to the participants’ mark to determine the VAS score. Apparatus We assessed BACs, in mg alcohol/dl blood, using the Alco-Sensor III, a hand-held breathalyser manufactured by Intoximeters, Inc. Two VLTs were used that are identical to those found in licensed premises throughout the Canadian province of Nova Scotia. The VLTs differed from those typically found in bars in that only two types of gambling games were available on each machine, i.e., a video poker game and a spinning reels game. For the purpose of ensuring relatively similar gambling experiences across participants in the laboratory, they were only permitted to play the one experimenter-selected game of the two available on each machine. We chose the video poker game, irrespective of which machine they selected, because it contains the interesting feature of ‘‘power-betting’’ (i.e., a button that allows the player to double his or her initial bet after viewing only the first two cards of the five card poker hand). Notably, there exists a ceiling for the powerbet function on this video poker game such that wagers that are more than half of the maximum allowable are not effectively doubled, but are increased only to the maximum bet size allowed. Procedure When the eligible participant arrived at the lab, it was verbally verified that he or she had fasted for 4 hours prior to the session, as he/she had been instructed during the telephone screening interview. Upon provision of written informed consent, the participant was asked to complete the questionnaire package that included the demographic


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items and the SOGS (Lesieur & Blume, 1987). With these complete, the participant was informed of his or her assignment to either the alcohol or control beverage condition. We used control beverages in this study, rather than placebo beverages, to better approximate naturalistic conditions (i.e., in everyday life people are generally aware of whether or not they are consuming alcohol) and as a first step in examining the effects of alcohol on VLT play regardless of whether these effects are pharmacologically and/or cognitively mediated. The participant was then compensated with $30.00 CDN (which was to be used as their bankroll during VLT play), weighed, and had a baseline blood alcohol concentration (BAC) measure taken with the AlcoSensor III. The purpose of this BAC reading was to verify the participant’s compliance with the instruction given during the telephone screening that he or she remain abstinent from alcohol for 24 hours prior to the study. If the BAC screen was negative, then the participant was led into a room containing two VLTs, which had been decorated to approximate a licensed establishment as much as possible (see Stewart, Blackburn, & Klein, 2000 for a more detailed description of the ‘barlab’ in the Dalhousie Gambling Laboratory). The participant relaxed in the bar-lab for 10 minutes, while the experimenter left to mix the drinks. This period allowed for participants to become accustomed to the bar-lab environment. We mixed the alcoholic beverages according to a formula described in MacDonald, Baker, Stewart, and Skinner (2000) in order to target a BAC of 0.06%. The alcohol dose for males was 1.55 ml 50% USP units of alcohol per kg body weight, mixed 1:4 parts alcohol to orange juice. The alcohol dose for females was 1.29 ml 50% USP units of alcohol per kg body weight, mixed 1:4 parts alcohol to orange juice. Control beverages contained mix- (orange-juice-) only, equated for volume with the alcoholic beverages. Depending on the body weight of the individual, the volume of liquid was usually equal to three or four glasses, or three or four standard drinks per person. After 10 minutes had elapsed, the experimenter returned to the bar-lab to administer the beverages. We allowed the participant 5 minutes to consume each glass of beverage (usually four drinks depending on total volume), and an equal number of minutes to absorb the contents, irrespective of assignment to the alcohol or control beverage condition. After absorption, a BAC reading (i.e., pre-play) was taken and a Subjective Intoxication Visual Analog Scale (VAS) was administered. At that time, the participant was invited to play the video poker VLT game

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for up to 30 minutes. The VLTs used in our laboratory allow for printouts of the last 40 gambling events played on each machine. We reasoned that collecting such information at 5 minute intervals over the course of play would achieve a suitable balance between accessing as much of this information from the machines as possible while minimizing disruptions to participants’ naturalistic course of play. The participant was thus informed that he or she would be interrupted briefly every 5 minutes so that a printout could be obtained from the VLT. These printouts provided data on the total amount of money gambled (i.e., from the final printout) and overall mean bet magnitude over the course of play (i.e., averaged across all printouts obtained). Participants also provided another BAC measure at the interruption 15 minutes into play and again 30 minutes following the onset of play (i.e., mid-play and post-play). The participant was also observed during play in order for the experimenter to record the number of times the participant touched the on-screen ‘‘power-bet’’ key. Touching the on-screen button is sufficient to activate the powerbet function. The experimenter stood behind the participant, out of his or her view, but within clear viewing distance of the VLT controls. All interactions with each participant (including power-bet observations) were conducted by one of two experimenters (ME or PL). Inter-Rater Reliability for Observer Ratings of Power-Bets Because observer ratings of VLT power-bets are a novel index of gambling activity, we felt it important to first demonstrate adequate psychometric properties of this measure. In particular, since this is an observer-rated measure, it is crucial to ensure good inter-rater reliability. Moreover, one experimenter was not blind to the SOGS status (probable pathological or non-pathological gambler) or beverage status (alcohol or control beverage) of the participants, and was present for every session of testing. Thus it is also important to establish sufficient interrater reliability among raters which included those who were blind to their condition, to mitigate the concern that experimenter awareness of their condition might have had an effect on participants’ behavior. In other research conducted in the Dalhousie Gambling Laboratory where one rater was blind and the other was not, the two raters in the present study (i.e., ME and PL) made independent observations of 15 participants’ use of the power-bet


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feature. A Pearson correlation coefficient generated from the two observers revealed perfect inter-rater reliability (r = 1.00, p < .01) and there was no significant difference between raters in the mean number of powerbets observed. Although two observers were used for a subset of participants in the present experiment, only one of the two was ever present to make observations for any given participant. Fan and Chen (2000) have demonstrated that ‘‘score reliability when only one rater is used for scoring is lower than the score reliability for which two raters are used’’ (p. 532). Thus, in order to generalize the estimation of interrater reliability to our entire sample, we corrected the Pearson correlation coefficient generated from the two observers to reflect the use of a single observer to obtain the data for each participant in this experiment. Using the formula for correction suggested by Fan and Chen (2000), our reliability coefficient remains 1.00, indicating excellent reliability, despite the fact that one observer was blind to the participants’ SOGS status and one was not. Irrespective of whether participants opted to play for the full half hour, they were required to remain for 30 minutes after the onset of the VLT play period. The amount of time (in minutes) participants spent playing the VLT was recorded. At the end of the half-hour, any winnings were paid out, and, if the participant was in the control beverage condition, he or she was permitted to leave the gambling lab. If he or she had been assigned to the alcohol condition, the participant was required to remain in the gambling lab until BAC reached 0.04%, at which point he or she was sent home via pre-paid taxi. Alcohol condition participants were allowed to watch movies in the VLT room until they were sober enough to leave. RESULTS Transformations The distributions of all variables examined using analyses of variance (ANOVAs) had skew values that were within acceptable limits, i.e., they had sufficiently normal distributions as to not violate ANOVA assumptions. One exception was the years playing VLTs variable, which showed marked positive skew. This variable was therefore transformed using a square-root transformation. After transformation, skew values fell within acceptable limits. Rate of Power-Betting (per minute) was

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calculated by dividing the overall number of power-bets observed for the session by minutes played. Self-Report Addictive Behaviors Self-report addictive behavior variables were examined in a 2 · 2 (SOGS category · beverage condition) MANOVA (i.e., years playing VLTs (square root transformed, as described above), Frequency of VLT Play (per week), Frequency of Drinking Occasions (per week)) or Chi-square analysis in the case of the dichotomous variables (i.e., Smoking During VLT Play; Drinking During VLT Play). The 2 · 2 MANOVA revealed a significant overall multivariate effect of SOGS category on the set of continuous addictive behavior variables (F3,38 = 6.25, p < .005). Follow-up 2 · 2 (SOGS category · beverage condition) univariate ANOVAs showed that the overall effect was reflective of the significant effect of SOGS category on transformed years playing VLTs (F1,40 = 6.79, p < .05) and on Frequency of VLT Play (F1,40 = 9.29, p < .005). Probable pathological gamblers had been playing VLTs for more time than non-pathological gamblers (untransformed means (and SDs) = 8.25 (5.53) vs. 5.20 (2.50) years, respectively). Probable pathological gamblers also currently played VLTs more often on a weekly basis than non-pathological gamblers (means (and SDs) = 2.65 (1.21) vs. 1.61 (1.16) gambling occasions per week, respectively). These relationships are theoretically expected, and provide some evidence for the construct validity of the SOGS categorization. A significant univariate effect of SOGS category on frequency of drinking occasions was also revealed (F1,40 = 4.65, p < .05) with probable pathological gamblers reporting drinking more frequently than non-pathological gamblers (means (and SDs) = 2.30 (1.62) vs. 1.40 drinking occasions per week (1.00), respectively). With respect to the dichotomous addictive behavior measures, no differences among the four groups were found for Drinking During VLT Play (v2 = 3.67, n.s.) or for Smoking During VLT Play (v2 = 0.79, n.s.) (see Table 1). Intoxication Levels A 2 · 2 (SOGS category · beverage condition) ANOVA was conducted on the VAS ratings of subjective intoxication on the 100 mm line. As expected, a main effect for beverage condition was


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observed (F1,40 = 63.97, p < .001). Those who consumed alcohol felt more intoxicated relative to those who consumed the control beverage (means (and SDs) = 39.68 mm (20.54 mm) vs. 2.07 mm (6.76 mm)). Scores in the control beverage condition ranged from .00 mm (which was the modal score, at a frequency count of 18) to a single score of 30.00 mm. The remaining three score VAS scores were .50, 3.00, and 12.00 mm. Scores other than zero in the control beverage condition could be explained in a couple of ways. Either they had difficulty understanding how the VAS measure was to be used, and indicated some level of subjective intoxication (despite BACs of .000) or they may have thought they were being administered alcohol, given the bar-lab setting. No other significant effects were observed. Objective intoxication in the control condition (as assessed with BAC) did not deviate from .000% at any of the three post-drinking testing times (pre-play, mid-play, or post-play). Means (and SDs) for the BAC readings in the alcohol condition were 0.052% (0.019%), 0.057% (0.013%), and 0.049% (0.010%) at pre-play, mid-play, and post-play, respectively. Thus, we accurately targeted a BAC of .06 at mid-play. Hypothesis Testing: Effects of Alcohol on Gambling Behaviors A 2 · 2 (SOGS category · beverage condition) MANOVA was conducted on the four dependent measures of VLT play: Overall Money Spent Playing VLT, Overall Mean Bet Magnitude, Overall Time Spent Playing VLT,1 and Rate of Power-Betting. Hypothesis 1: Beverage Effects An overall multivariate effect of beverage condition was detected, as hypothesized (F4,37 = 2.89, p < .05). Univariate analyses revealed that this effect was due to the significant effect of beverage condition in increasing Overall Time Spent Playing VLT (F1,40 = 6.04, p < .05) (see Figure 1) and the marginal effect of beverage condition in increasing Rate of Power-Betting (F1,40 = 3.81, p < .06) (see Figure 2). Hypothesis 2: Effect of the Interaction of SOGS Category and Beverage Condition The hypothesized multivariate SOGS category by beverage condition interaction on the dependent measures was also statistically

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Mean Minutes Spent Playing VLT

Figure 1 Mean time spent playing VLT (in minutes) as a function of gambler status (probable pathological gambler vs. non-pathological gambler) and beverage condition (alcohol vs. control). Notes: error bars represent standard errors. NPG = non-pathological gamblers; PPG = probable pathological gamblers 30.00

Control Alcohol

29.00

28.00

27.00

26.00

25.00

24.00

NPG

PPG

SOGS Classification

significant (F4,37 = 2.86, p < .05). While the univariate interactions were not significant, our a priori prediction of this interaction, and the patterns of group means for these dependent measures justified a further exploration of the multivariate interaction (Winer, 1971). Thus, simple effects analyses were used to examine the effects of beverage condition on each of the dependent variables in the probable pathological gambler and non-pathological gambler groups separately. A significant simple effect of beverage condition among probable pathological gamblers on Overall Time Spent Playing VLTs (F1,20 = 5.36, p < .05) was observed as well as a marginally significant simple effect of beverage condition on Rate of Power-Betting (F1,20 = 3.32, p < .09). In both cases, alcohol was associated with increases in these behaviors relative to the control beverage (see Figures 1 and 2). No such significant simple effects of beverage condition were observed on either of these two indices among the non-pathological gamblers (see Figures 1 and 2). For the other two indices (total amount of money spent and overall mean


313

Figure 2 Mean rate of powerbetting (per minute) as a function of gambler status (probable pathological gambler vs. non-pathological gambler) and beverage condition (alcohol vs. control). Notes: error bars represent standard errors. NPG = non-pathological gamblers; PPG = probable pathological gamblers

Rate of Power betting

1.50

Control Alc ohol 1.00

0.50

0.00

NPG

PPG

SOGS Classification bet magnitude), no simple effects of beverage condition were observed for either the probable pathological gamblers or the non-pathological gamblers. Means (and SDs) for the total amount of money spent were: $15.27 ($9.18) and $20.30 ($6.23) for the probable pathological gamblers in the no alcohol and alcohol conditions, respectively, and $12.64 ($8.03) and $15.64 ($12.30), for the non-pathological gamblers in the no alcohol and alcohol conditions, respectively. Means (and SDs) for overall mean bet magnitude were: $0.55 ($0.35) and $0.55 ($0.28) for the probable pathological gamblers in the no alcohol and alcohol conditions, respectively, and $0.37 ($0.18) and $0.55 ($0.32) for the nonpathological gamblers in the no alcohol and alcohol conditions, respectively.2 Post Hoc Analyses Probable pathological gamblers in the alcohol condition appeared to be powerbetting more frequently, and playing for greater periods of

314


time, without spending more money overall. One possible explanation for this is that, perhaps due to the effect of alcohol in encouraging ‘‘favourable’’ risk-taking (i.e., promoting greater skill at the game), they may have been winning more frequently and/or losing less frequently. In order to explore this possibility, a set of 2 · 2 (SOGS category · beverage condition) univariate ANOVAs were conducted on the following two variables: Proportion of Total Hands Won and Proportion of Total Hands Lost, as recorded on the VLT printouts obtained for the last 40 events over each successive 5 minute interval of play. For the purposes of calculating these variables, gaming events that resulted in neither gain nor loss were scored as ‘‘breaking even’’. Thus, Proportion of Total Hands Won is not simply the inverse of the Proportion of Hands Lost. There were no significant effects in the ANOVA for Proportion of Total Hands Won. However, there was a significant SOGS category by beverage condition interaction for Proportion of Total Hands Lost (F1,40 = 6.02, p < .05).3 A simple effects analysis of this interaction revealed a marginally significant simple effect of beverage condition among the probable pathological gamblers with alcohol actually increasing the proportion of total hands lost relative to the control beverage (means (and SDs) = 58.88 (4.15) vs. 54.85 (6.49), respectively; F1,20 = 3.00, p < .10). A marginally significant simple effect of beverage condition in the opposite direction was observed among non-pathological gamblers such that alcohol tended to decrease the proportion of total hands lost relative to the control beverage (means (and SDs) = 55.76 (3.76) vs. 59.13 (5.14), respectively; F1,20 = 3.08, p < .10). Additional simple effects analyses of SOGS category at each level of beverage condition were also conducted. There was no significant simple effect of SOGS category in the control beverage condition, but a marginally significant simple effect of SOGS category was obtained in the alcohol condition (F1,20 = 3.42, p = .08) with probable pathological gamblers showing a larger proportion of total hands lost relative to the non-pathological gamblers. In summary, no evidence was obtained to suggest that probable pathological gamblers in the alcohol condition were winning more hands. However, we did obtain evidence that probable pathological gamblers in the alcohol condition tended to lose more hands.


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DISCUSSION This study found that consumption of alcohol affected some, but not all, of the VLT play variables, with alcohol being associated with a more ‘‘risky’’ style of play. Specifically, relative to a control beverage, alcohol consumption significantly increased time spent playing VLTs and tended to also increase rate of power-betting. In contrast, alcohol failed to significantly increase the other two behaviors, namely mean bet magnitude and overall money spent. The effect of alcohol in prolonging play is consistent with the results of Kyngdon and Dickerson (1999). However, in terms of overall money spent (which is a net figure of wins and losses at the end of the session), we failed to replicate their finding that alcohol consumption results in greater monetary losses. In the present study, we reasoned that one potential explanation for the prior inconsistencies regarding the effects of alcohol on gambling was that previous research had not attended fully to individual difference factors (see Breslin et al., 1999). Specifically, some people may be more susceptible to the effects of alcohol in increasing certain gambling behaviors during VLT play. In the present study, we examined gambler status (probable pathological vs. nonpathological gambler according to SOGS criteria) as one potentially important individual difference variable. Consistent with hypotheses, the effects of alcohol consumption on some of the dependent measures were greater among probable pathological gamblers compared to non-pathological gamblers. In fact, these effects of alcohol on the amount of time spent playing and on rate of powerbetting were statistically significant only among the probable pathological gamblers. Thus, it appears that probable pathological gamblers are particularly sensitive to the effects of alcohol in increasing their persistence at play, and in causing them to make potentially risky bets during play. Post hoc analyses further revealed that alcohol increased the proportion of hands lost only among the probable pathological gamblers. This pattern of findings is consistent with the unpublished findings of Leiserson et al. (2001) showing that intoxicated subjects scoring above the SOGS cutoff for probable pathological gambling borrowed more money and chased more losses on a computerized Blackjack game. There are several models that have been proposed to explain the high rate of co-occurrence of gambling and alcohol use disorders (see Stewart & Kushner, 2003). One potential explanation is that alcohol

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use disorder causes pathological gambling. This is thought to occur as a result of heavy drinking’s effects in increasing the likelihood of gambling as well as influencing the kinds of gambling behaviors that result in problems, such as increased length of play and greater risktaking. The present pattern of findings wherein alcohol increased some aspects of potentially problematic gambling behavior is generally consistent with this causal model. However, sensitivity to the effects of alcohol was only observed in the present study among those who had already developed gambling problems (i.e., those scoring high on the SOGS). The results create problems for this causal explanation, as, presumably, those who are at increased risk for gambling problems would also show sensitivity to these alcohol effects (see Stewart & Kushner, 2003). To better test this model, one would need to compare the responses to alcohol among three groups of regular gamblers: pathological gamblers, those ‘‘at risk’’ for pathological gambling, and those not likely to develop gambling problems. One would need to show that susceptibility to alcohol’s effects on gambling behavior were shared by those in the pathological gambler and ‘‘at risk’’ groups relative to the low risk group. The present findings are more consistent with a model wherein alcohol problems maintain or exacerbate existing gambling problems via the effects of alcohol on certain gambling behaviors, such as persistence at gambling, or playing more losing hands (which might result in chasing losses). It is notable, for instance, that while alcohol did not increase overall money spent playing during VLT play, there was a tendency for probable pathological gamblers who consumed alcohol to persist at play. Clearly, more time spent playing a gambling machine whose payout percentage is less than 100% puts people at risk for losing more money. Thus, playing longer in a real-world setting, where no 30 minute time limit is enforced, corresponds to greater exposure to the risk of not being paid representative odds and may result in greater monetary losses among probable pathological gamblers who consume alcohol during VLT play. As noted by Blaszczynski, Sharpe, and Walker (2001), longer gambling play can also result in problems due to more time spent away from family and other productive activities. While the differences reported in this study amount to real-world differences in terms of only minutes of play, the fact that we allowed a maximal play period of only 30 minutes placed an artificial ceiling on the amount of time that intoxicated probable pathological gamblers were able to play.


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There are several potential mechanisms whereby alcohol might lead to increases in gambling behavior during VLT play among the probable pathological gamblers. The first set of mechanisms pertains to alcohol’s effects on various cognitive processes. Understanding how alcohol influences willingness to gamble (or any other behavior associated with gambling) requires an understanding of some of the cognitive effects of alcohol consumption (Breslin et al., 1999). One line of research has studied the effects of alcohol on behavioral control (Vogel-Sprott, Easdon, Fillmore, Finn, & Justus, 2001), examining measures such as response inhibition (Easdon & Vogel-Sprott, 2000; Fillmore & Vogel-Sprott, 2000), response flexibility (Easdon & VogelSprott, 2000), and intentional behavior (Fillmore, Vogel-Sprott, & Gavrilescu, 1999). This research has demonstrated reductions in each of these in response to moderate doses of alcohol. Alcohol-induced changes in any of these cognitive functions might mediate the observed effects of alcohol on the gambling indices in the present study. For example, alcohol’s impairment of behavioral control might be responsible for its effect of increasing persistence at play and the disinhibiting effects of alcohol might be responsible for its effect of increasing rates of powerbetting. It would be interesting for future research to determine if probable pathological gamblers are more sensitive to alcohol’s effects on behavioral control, response inhibition, or related cognitive functions using established cognitive tasks. Another cognitive mechanism to account for the effect of alcohol only among probable pathological gamblers involves the effects of alcohol on executive functions (e.g., planning and organization), commonly thought to be localized to the prefrontal cortex. At moderately intoxicating doses, alcohol has a measurable adverse effect on executive cognitive functioning (Peterson, Finn, & Pihl, 1992; Peterson, Rothfleisch, Zelazo, & Pihl, 1990). Perhaps probable pathological gamblers are more susceptible to the effects of alcohol on executive functioning. This would translate into difficulties with gaming strategies during VLT play, leading to more hands being lost. Indeed, previous research suggests that probable pathological gamblers show subtle deficits in executive, frontally mediated cognitive processes relative to non-addicted controls (Rugle & Melamed, 1993). Thus, probable pathological gamblers may be more sensitive to the effects of alcohol on gambling behavior due to alcohol’s disruptive effects on an already compromised prefrontal cortical system. In this study, although

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alcohol increased powerbetting and resulted in a greater proportion of hands lost among probable pathological gamblers, it did not result in their spending a greater amount of money by the end of the play period. Moreover, probable pathological gamblers in the alcohol condition were able to play for a significantly greater amount of time without spending significantly more money overall. As mentioned earlier, if participants had been afforded a longer period in which to play (i.e., greater than 30 minutes), the increased risk taking and greater proportion of hands played that were losing hands might have translated into greater overall money spent among probable pathological gamblers drinking alcohol. An affective-cognitive model to explain behavior during gambling has been proposed (Nygren, 1998) that may also be relevant to explaining the effects of alcohol among probable pathological gamblers. Nygren (1998) found evidence that the framing of a gambling task (emphasizing either potential gains or potential losses) acts as an mood inducer wherein positive affect results in more risk-seeking behavior, but only in a low-risk gambling situation. Previous research has shown that alcohol intoxication is associated with increases in positive affect (e.g., Conrod, Peterson, & Pihl, 2001). Thus, alcohol consumption may affect gambling behavior in the present study, by way of its effects in increasing positive mood. Alcohol might cause a greater increase in positive mood in probable pathological gamblers vs. nonpathological gamblers or pathological gamblers may show a stronger effect of positive mood on increased risk-taking. In turn, the positive mood might lead pathological gamblers to persist longer at play or to seek greater risks through behaviors such as increased power betting, resulting in more hands being lost. It was interesting to note that not all VLT players showed adverse effects of alcohol on the proportion of poker hands lost. In fact, nonpathological gamblers displayed a response to alcohol opposite to that observed among the probable pathological gamblers, with alcohol resulting in marginally fewer hands lost relative to the control beverage. Perhaps alcohol consumption led to increases in favorable risk-taking behavior in this group, resulting in fewer losing hands. However, this effect did not translate into a decrease in overall spending by the end of the play session nor did it result in an increase in proportion of hands won. Nonetheless, this finding does underscore the importance of


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considering individual difference factors such as problem gambler status when investigating the effects of alcohol on gambling behavior. Several potential limitations of the study should be acknowledged. First, because we were using a real-world gambling task, the indices of risk-taking defined here are not necessarily generalizable to forms of gambling outside of VLT play. Another potential limitation involves the method of collecting data for one of the dependent risk-taking measures. Previous research has demonstrated that problem gamblers focus intensely upon VLT play (Diskin & Hodgins, 2001). Because participants in our study were interrupted every 5 minutes by the researchers in order to obtain printouts from the machines (to assess mean bet magnitude over the course of play as well as to tabulate number of winning and losing hands), ecological validity may have been compromised. It is possible that if participants were allowed focus on play as they do in the real world, without interruption, stronger effects may have emerged. Future studies might also consider extending VLT sessions longer than 30 minutes in order to better approximate in vivo VLT play. A self-report study of VLT players showed that problem gamblers played for sessions of more than 3 hours on average (Focal Research, 1998). Extension of the length of the VLT play session might allow for a better examination of the effects of alcohol on total money spent relative to the short play period examined in the present study. Another limitation to this study corresponds to the use of a control beverage, where participants knew whether or not they were receiving alcohol, as they would in a real-world drinking situation. Since the present study did not control for expectancy factors in the control beverage condition, future studies would do well to control for these by using a placebo condition where participants are unaware of the beverage condition to which they have been assigned. It is also possible that this study was subject to the Rosenthal effect, i.e., that the participants behaved in ways they thought the experimenters expected (Rosenthal, 1966). Because one of the experimenters, who was present for every testing session, was not blind to the SOGS status or beverage condition of the participants, subtle cues may have been supplied to the participants to influence their gambling behavior, e.g., encouraging probable pathological gamblers in the alcohol condition to take more risks. Our analysis of the effects of tester blindness on the power-bet observations revealed no evidence of demand

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characteristics; however, this analysis was conducted on data from another study (Stewart & Ellery, 2001). Due to these latter limitations, we cannot fully rule out possible roles played by alcohol expectancy or demand characteristics in these results. The design of the ‘bar-lab’ within which this study was conducted has its strengths and weaknesses. Although designed with ecological validity in mind (by approximating bar conditions in the lab), it falls short in several respects, e.g., participants were unable to smoke in the VLT room (Stewart et al., 2000). Because participants played on commercially available VLTs, this study has the advantage of increased generalizability of the findings to the situations where gamblers actually play the machines in the ‘‘real world’’. However, use of these commercially available VLTs meant that we could not manipulate the VLT payout algorithm, and thus we were unable to manipulate wins/ losses in order to examine potential interactions between such gambling events (see Delfabbro & Winefield, 1999) and beverage condition and/or gambler status on the risk-taking indices. Moreover, the ecological validity of the protocol may have contributed to the ability of the participants to guess the object of the study, possibly contributing to a Rosenthal effect. Thus, while the bar-lab is valuable for its ecological strengths, it is not without limitations in terms of experimental control. The results of the present study have some potentially important policy and treatment implications. With respect to policy, the findings imply that jurisdictions interested in harm reduction should question the practice of making VLTs available in licensed premises or in making alcoholic beverages freely available to casino patrons. With respect to treatment, alcohol problems and problematic gambling are frequently regarded as separate clinical issues. However, our results show that alcohol intake might indirectly exacerbate gambling problems among pathological gamblers by increasing the kinds of gambling behavior that could lead to problems. For example, alcohol increases the time probable pathological gamblers spend engaged in gambling behavior, which can take time away from social, academic, or occupational functioning (cf. Blaszczynski et al., 2001). Alcohol also increased risk-taking during play and increased the proportion of hands lost by probable pathological gamblers which, over time, might contribute to their chasing losses (Breen & Zuckerman, 1999). Perhaps


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interventions with pathological gamblers should address alcohol use as a component of treatment.

ACKNOWLEDGMENTS This study was funded by a grant to the second author from the Nova Scotia Gaming Foundation (NSGF), Nova Scotia Department of Health, and was conducted at the Dalhousie Gambling Laboratory, Department of Psychology, Dalhousie University. This study was conducted by the first author in partial fulfillment of requirements for the Doctoral degree in Clinical Psychology at Dalhousie University. Mr. Ellery’s doctoral studies are generously supported by the Killam Trust Fund in the form of an Honourary Izaak Walton Killam Memorial Fellowship as well as by the Social Sciences and Humanities Research Council (SSHRC) of Canada in the form of a Doctoral Fellowship and the Ontario Problem Gambling Research Center (OPGRC) in the form of a Doctoral Fellowship. Dr. Stewart is supported through an Investigator Award from the Canadian Institutes of Health Research. The results of this study were presented at a Symposium on ‘‘Recent Research on Alcohol Abuse and Gambling Relations’’, chaired by Dr. S. H. Stewart and Dr. Matt G. Kushner at the Annual Meeting of the Research Society on Alcoholism, San Francisco, USA, June–July 2002.

NOTES 1. Of the five participants who spent their entire bankroll during play, two played for the entire half hour, one played for 28 minutes, one for 26 minutes, and one for 23 minutes, suggesting that when play was terminated by participants before the full 30 minutes had elapsed, it was unlikely to have been due to a depletion of funds. 2. Since there were significant SOGS category effects on age and frequency of alcohol use, a pair of 2 · 2 (SOGS category · beverage condition) MANCOVAs was conducted on the four dependent measures of risk-taking with age and alcohol use as covariates, respectively. In both analyses, the multivariate effect of beverage condition persisted (Fs 4,36 = 2.78 and 2.84, ps < .05, respectively) and the multivariate beverage condition · SOGS category interaction also persisted (Fs4,37 = 2.80 and 2.76, ps < .05, respectively). The pattern of covariate-adjusted means was identical to those reported in the initial MANOVA. These covariance analyses determined that the observed effects with the risk-taking dependent measures were not secondary to gambler group differences in age or in frequency of alcohol use. 3. Since there were significant SOGS category effects on age and frequency of alcohol use, pairs of 2 · 2 (SOGS category · beverage condition) ANCOVAs were conducted on Proportions of Total Hands Won and Lost with age and alcohol use as covariates. In these analyses, the uni-

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variate beverage condition · SOGS category interaction persisted for Proportion of Total Hands Lost (Fs1,39 = 5.90 and 5.90, ps < .05, respectively). The pattern of covariate-adjusted means was identical to those reported in the initial ANOVA. These covariance analyses determined that the observed effects on Proportion of Total Hands Lost were not secondary to gambler group differences in age or in frequency of alcohol use.

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