Hitting the Jackpot: The Influence of Monetary Payout on Gambling Lena C. Quilty, Ph.D., C.Psych. Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health Department of Psychiatry University of Toronto

Co-authors Daniela LoboMartin Zack Centre for Addiction & Mental Health; University of Toronto Alexander Blaszczynski Courtney Crewe-Brown University of Sydney

Disclosure of Potential Conflict of Interest n The current work was supported by operating funds from Gambling Research Exchange Ontario n In the past 5 years, I have received funding from: u National Institutes of Health u Canadian Institutes of Health Research u American Psychiatric Association u Ontario Mental Health Foundation u Canadian Consortium for Gambling Research u Gambling Research Exchange Ontario u Ontario Lottery & Gaming

Background n Theoretical models emphasize reinforcement in development & maintenance of problem gambling, e.g. u Behavioural models u Decision-making theory n Cognitive neuroscience research has linked magnitude of monetary outcomes to distinct neural events u Neural responses to monetary outcomes are the result of outcome valence and magnitude (Goyer et al., 2008; Kreussel et al., 2012; Wu & Zhou, 2009) u Valence and magnitude governed by distinct neural mechanisms (Gu et al., 2011)

Background n Monetary payout is the primary motivation for recreational and problem gambling u Maximum jackpot size as form of prevention? u Promote view of gambling as form of entertainment rather than source of income?

Background n Crewe-Brown, Blaszczynski, & Russell (2013) n 171 undergraduate students n Asked to estimate gambling expenditure, frequency, & duration to win jackpots of increasing amounts u Endorsed increased gambling with increased jackpots u Gambling debt and gender moderated link: F Males and females endorsed similar bets under conditions of no debt and low jackpot sizes F Males tended to endorse higher bets than females when debt levels were high

Background n Crewe-Brown, Blaszczynski, & Russell (2013)

Objectives n Replication and extension of Crewe-Brown et al. n 1) To investigate link between self-reported wagering and jackpot size in adults with wide range of gambling frequency and associated harms n 2) To investigate moderating role of gender, gambling debt, and other risk factors for problem gambling

Methods n Participants: u 187 adults u 101 males, 85 females, 1 other, 1 did not disclose u Average age years (SD=13.88) F Range 18 to 68 years u Average gambling frequency 9.3 x/month F Ranged 0 to 60 x/month u Approximately 50% (n=93) PGSI ≥ 8

Methods n Participants:

Methods n Participants:

Methods n Participants:

Methods n Participants:

Methods Contacts (N=195) 65% Completed Survey (N=127) n Advertisements: n Hospital Research Registry: Contacts (N=95) 42% Completed Survey (N=40)

Methods n Measures: n Vignettes (Crewe-Brown et al., 2013): u Self-reported willingness to wager for a series of hypothetical jackpots of increasing amounts u “Please indicate how much you would be willing to bet on an electronic gaming machine for the chance to win a prize of $500” u EGM – expenditure & duration F high frequency, more probable, smaller jackpot Lottery – expenditure & # games played F low frequency, less probable, larger jackpot

Methods n Measures: n Vignettes (Crewe-Brown et al., 2013): u Ten jackpot sizes F EGM jackpots ranged from $100 to $200,000+ F Lottery jackpots ranged from $100 to $10,000,000 u 3 levels of gambling debt F Low, medium, and high

Methods n Measures: u Problem Gambling Severity Index (Ferris & Wynne, 2001) u Gambling Motives Questionnaire (Stewart & Zack, 2008) F Enhancement, coping, & social motives u UPPS-P Impulsive Behavior Scale-P (Lynam et al., 2007) F Negative and positive urgency; F (Lack of) premeditation and perseverance; F Sensation seeking, u Positive and Negative Affect Schedule (Watson & Clark, 1988)

Results n F=54.16, p<.01, partial  2 =.24

Results n F=72.30, p<.01, partial  2 =.29

Results n F=26.39, p<.01, partial  2 =.14

Results n F=55.71, p<.01, partial  2 =.25

Results n Self-reported gambling increased as a function of magnitude of reinforcement u Money wagered increased with jackpot size u Duration of EGM play increased with jackpot size u Number of lottery games played increased with jackpot size n Effect sizes large n Results consistent even when taking problem gambling severity as assessed by the PGSI into account (all ps <.05)

Results n F=3.98, p<.01, partial  2 =.03

Results n F=5.71, p<.01, partial  2 =.03

Results n F=3.57, p=.03, partial  2 =.03

Results n F=2.95, p<.01, partial  2 =.02

Results n Self-reported gambling increased as a function of magnitude of reinforcement and decreased as a function of magnitude of debt u Main effects across all outcomes, w/ large effect sizes Jackpot × debt size interaction for money wagered (EGM & lottery) and lottery games played u Impact of debt most pronounced at high jackpot sizes Jackpot × gender interaction for duration of EGM play u Females endorsed longer durations at high jackpot sizes u Small effect size

Results n Self-reported gambling association with jackpot size not moderated by: u Gambling motivations u Impulsivity u Affect n EGM expenditures increased with coping motives (F=5.97, p=.02) and positive urgency (F=5.16, p=.02) n Lottery expenditures and games increased with social motives (F=6.11, p=.01; F=4.53, p=.04) n Results replicated with and without covariates

Conclusions n Jackpot size may significantly impact gambling across qualitatively different gambling products, and across gamblers with different risk factors u Increased gambling in response to increased jackpots u Across games with different probability of winning and nature of game play n Debt moderated these outcomes: gambling decreased with increased debt, particularly at elevated prize levels

Conclusions n Online self-report design u Replication of earlier research u Recruitment of large N in efficient, economical design u Established delay-discounting tasks similar (Madden & Bickel, 2010) F Self-report comparable to behavior (Odum, 2011) n Possible influence of expectations or task demands n Somatic marker hypothesis: vulnerability factors may only moderate if somatic signal for risk or reward u i.e., an in vivo manipulation; see Bechara et al., 2000

Implications n Robust association between gambling frequency, duration, and expenditures and gambling-related harms u Accruing evidence for association between gambling outcomes and jackpot size n Gambling expenditures, duration, and frequency endorsed above suggested cut-offs for harmful or problem gambling (e.g., Quilty et al., 2014) n Restriction of jackpots may be viable form of prevention

Acknowledgements n CAMH Research Services & Quilty Clinical Research Lab: u Susan Dickens u Natalia Potapova u Suzie Woldemariame u Gloria Leo u Daniela Avila Murati u Heba Shamsi u Rebecca Persaud u Premika Premachandiran

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