Preparing for the future: Emerging forms of gambling and new technologies Jeffrey L. Derevensky, Ph.D. James McGill Professor, School/Applied Child Psychology Professor, Psychiatry McGill University Research Director, Florida Council on Compulsive Gambling www.youthgambling.com National Council of Legislators from Gaming States Denver, June, 2017

The normalization of gambling/gaming Transition to Jeff

Chocolate poker chips for kids Poker chips for adults

Arcades

Safety 1st Jack Potty Training Seat

Gambling (gaming) has become glamorized

Ryan Reiss, age 23, wins $8.36 million in 2013 WSP recent college grad

The new face of youth gambling

Youth involvement in addictive behaviors

Involvement in addictive behaviors Total use Weekly use Gr 7 Gr 9 Gr 11 Gr 7 Gr 9 Gr 11 Alcohol 36.8% 62.2% 79.8% 7.4% 14.0% 20.2% Drugs 3.5% 13.4% 26.5% 2.7% 2.1% 9.0% Cigarettes 18.2% 34.5% 48.4% 7.0% 16.1% 31.4% Gambling 79.1% 78.9% 83.4% 30.4% 37.4% 37.1%

Prevalence of problem gambling 1-2% of adults 4-6% of adolescents

Emerging Forms of Gambling: Concerns?

Circa 1920’s Slot Machine

Slot Machine 2013

Skill-Based Slots

Guitar Warrior

Texas Tea Pinball

The millennials Transition to Jeff

Internet gambling

Are Internet gamblers more likely to have problems? Wood & Williams (2007) - Sample of on-line adult gamblers Non-problem gamblers: 34% At-risk gamblers: 24% Moderate problem gamblers: 23% Severe problem gamblers: 20% 2/3 of those respondents gambling on the Internet are likely to have problems 2001 = upwards of 1400 different online gambling sites Recent research suggest I-gamblers, compared to non-I gamblers, are more likely to be suffering from a gambling problem and are at greater risk of developing one (Azmier, 2000; Hammer, 2001) Unclear whether I-gambling leads to problems, or problem gamblers are led to Internet Experience may facilitate emergence of gambling problem: convenience, ease of accessibility, immersive, anonymous Visual, aural, tactile qualities of interface may accelerate passage of time; easy access from home may lead to playing more often; psychological value of electronic cash – may result in greater than normal gambling losses To what extent do I-gamblers show tendency for problem gambling (CPGI)? What are correlates and predictors of problem gambling among I-gamblers? N=1920, 56% men, avg age=34 (range=18-84), 87% from U.S. Internet users as well as gamblers: email, chat, IM, banking, shopping Gambling mean=5 hours/week Predictors of problem gambling status: time spent gambling, East Asian, South Asian, African ancestry, preference for non-Internet gambling (maybe problem gamblers go to Internet as one more place to gamble), male gender They suggest the rate of problem gambling among Internet gamblers may be 10x higher than the rate among the general population

Mobile wagering

Social casino gambling

Minneapolis Airport

Social Casino Gamers There are currently 170 million social casino gamers, well over triple the number of online gamblers (Morgan Stanley, 2012). The Morgan Stanley Blue Paper (Morgan Stanley, 2012) highlighted the importance of trying to migrate social casino gamblers to become online gamblers,"

U.K. Gambling Commission (2015) The boundaries between social gaming and commercial gambling have become increasingly blurred and are of concern for young people as a result of: the growth in use of social media for social gaming and gambling an increasing convergence between the products of traditional gambling and social gaming businesses significant investment  by companies developing new products or ways of marketing existing products

Expansion of sports wagering

Sports Wagering in the U.S. Recent poll: 65% of fans support regulated sports wagering (AGA, 2016) A Nov 1, 2016 Fairleigh Dickinson University Public Mind poll found 48% support changing federal law to make sports wagering legal throughout U.S. (39% opposed) Among those in favor 45% are already doing it; 39% view increased state revenues Among those opposed 55% are concerned about increased gambling addiction; 22% concerned about organized crime; 16% concerned about the integrity of the game

Prevalence of Sports Wagering by Gender among Adolescents Ages 12 to 18 in Wood County, Ohio (n=5183)   Gender Daily About once a week About once a month Less than once a month Total Bet money on sports teams (pro, college, or amateur) Female Male .3 1.8 3.0 1.4 5.4 5.0 9.8 7% 20% Bet money on fantasy sports or games (with an entry fee) 1.9 .1 2.6 .2 2.7 1.7 4.9 2.3% 12.1% Bet or wager on daily fantasy sports (FanDuel or DraftKings, etc.) 2.2 2.3 .9 2.4 1.4% 8.7%

Participation in Fantasy Sports by Gambling Severity (2012)   Male Female Social Gamblers At-Risk/PPG Free Fantasy Leagues 52.2% 65.4% 8.5% 44.4% Fee-Based Fantasy Leagues 18.4% 48.1% 1.8% 25.0% Marchica & Derevensky (2015)

Parental perceptions: Serious Youth Issues

Harm minimization: Some approaches School-based education prevention initiatives Limit setting and use of smart card technology Responsible gambling centers within casinos Algorithms to identify high risk players Normative feedback and messaging Advertising standards

mentor Early Risk Detection Harm Minimization Player Communication Self-Assessment

Tailored Recommendation The right recommendation for the right player at the right point of time

PRESENTATION RIGHTS RESERVED. COPYRIGHT BETBUDDY LTD. YEAR 2017. Assessment Interpretation Interaction Evaluation 1. Assessment 2. Interpretation Based on research, operators build an evidence base using player data and apply quantitative and qualitative methods to classify players on a continuum of risk Transparent RG models enable solutions to be independently tested by experts and regulators and enable operators to understand each player’s risk profile PRESENTATION RIGHTS RESERVED. COPYRIGHT BETBUDDY LTD. YEAR 2017.

3. Interaction 4. Evaluation Assessment Interpretation Interaction Evaluation 3. Interaction 4. Evaluation Message Type General, Personal, Normative, etc. Messaging Channel Email, Telephone, SMS, In-Game, etc. Messaging Strategy Single, Multiple, Ad-hoc, Regular, etc. Marketing Strategy Promote RG marketing to high risk, etc. Data shows RG Interactions resulted in 24% of regular players, who exhibited some risk, significantly moderating behaviours The RG data insights generated can be used to drive targeted responsible gambling interactions with the customer base to help players to make informed choices Operators have the opportunity to develop trials to assess optimal player interaction approaches via continuous experimentation and testing PRESENTATION RIGHTS RESERVED. COPYRIGHT BETBUDDY LTD. YEAR 2017.