Findings from a Longitudinal Study of Internet Gambling Behavior Sarah E. Nelson, Ph.D. Division on Addictions Cambridge Health Alliance, Harvard Medical

Findings from a Longitudinal Findings from a Longitudinal Study of Internet Gambling Study of Internet Gambling

BehaviorBehavior

Sarah E. Nelson, Ph.D.Sarah E. Nelson, Ph.D.

Division on AddictionsDivision on Addictions

Cambridge Health Alliance, Harvard Medical SchoolCambridge Health Alliance, Harvard Medical School

Presented at the Alberta Gaming Research Institute 2009 Banff Presented at the Alberta Gaming Research Institute 2009 Banff Conference on Internet GamblingConference on Internet Gambling

Actual Internet Actual Internet GamblingGambling

ObjectivesObjectives

Briefly review the knowledge base Briefly review the knowledge base about Internet gamblingabout Internet gambling

Examine the findings from two Examine the findings from two studies of Internet sports and casino studies of Internet sports and casino gambling behaviorgambling behavior

Examine the findings from two Examine the findings from two studies of attempts to intervene with studies of attempts to intervene with Internet gamblers who might be Internet gamblers who might be experiencing problemsexperiencing problems

The Division on Addictions The Division on Addictions Receives Support from:Receives Support from:

National Institutes of Health (NIDA, NIAAA)National Institutes of Health (NIDA, NIAAA) bwin Interactive Entertainment, AGbwin Interactive Entertainment, AG National Center for Responsible GamingNational Center for Responsible Gaming University of Nevada at Las VegasUniversity of Nevada at Las Vegas University of MichiganUniversity of Michigan Robert Wood Johnson FoundationRobert Wood Johnson Foundation Port Authority of Kansas CityPort Authority of Kansas City St. Francis HouseSt. Francis House Las Vegas Sands CorporationLas Vegas Sands Corporation Massachusetts Council on Compulsive Massachusetts Council on Compulsive

GamblingGambling

bwin Interactive Entertainment, AG bwin Interactive Entertainment, AG provided primary support for this provided primary support for this study. study.

Drs. Howard Shaffer, Richard LaBrie, Drs. Howard Shaffer, Richard LaBrie, and Debi LaPlante contributed to this and Debi LaPlante contributed to this presentation.presentation.

“Nothing leads the scientist so astray as a

premature truth.”

Pensées d’un Biologiste (1939; repr. in The Substance of Man, “A Biologist’s Thoughts,” ch. 7, 1962).

Jean Jean RostandRostand (French biologist, writer)(French biologist, writer)

Brief History of Internet Brief History of Internet Gambling ResearchGambling Research

Concerns about the InternetConcerns about the Internet

Facebook Addiction Disorder Facebook Addiction Disorder (FAD)(FAD)

1. The first thing is tolerance. This refers to the need for increasing amounts of time on 1. The first thing is tolerance. This refers to the need for increasing amounts of time on Facebook to achieve satisfaction and/or significantly diminished effect with continued Facebook to achieve satisfaction and/or significantly diminished effect with continued use of the same amount of time. They often have multiple Facebook windows opened at use of the same amount of time. They often have multiple Facebook windows opened at any one time. 3 is usually a sign and over 5 you're helpless. any one time. 3 is usually a sign and over 5 you're helpless.

2. After reduction of Facebook use or cessation, it causes distress or impairs social, 2. After reduction of Facebook use or cessation, it causes distress or impairs social, personal or occupational functioning such as wondering why your Vista is so fast and personal or occupational functioning such as wondering why your Vista is so fast and improved etc. These include anxiety; obsessive thinking about what is written on your improved etc. These include anxiety; obsessive thinking about what is written on your wall on Facebook etc. wall on Facebook etc.

3. Important social or recreational activities are greatly reduced and or migrated to 3. Important social or recreational activities are greatly reduced and or migrated to Facebook. Instead of sending an email you post a message on your friend’s page about Facebook. Instead of sending an email you post a message on your friend’s page about canceling a lunch appointment. You now stop answering your phone call from your Mom canceling a lunch appointment. You now stop answering your phone call from your Mom and insist she should contact you through Facebook chat. and insist she should contact you through Facebook chat.

4. This is getting serious if you start kissing your girlfriend's home page or a VRML virtual 4. This is getting serious if you start kissing your girlfriend's home page or a VRML virtual walk through a park is your idea of a date.walk through a park is your idea of a date.

5. Your bookmark takes 20 minutes just to scroll from top to bottom or 8 of 10 people in 5. Your bookmark takes 20 minutes just to scroll from top to bottom or 8 of 10 people in your friend's list you have no idea of who they are. your friend's list you have no idea of who they are.

6. When you meet people you start introducing yourself by following "see you in 6. When you meet people you start introducing yourself by following "see you in Facebook" or your dog has its own Facebook profile. You invite anyone you've met and Facebook" or your dog has its own Facebook profile. You invite anyone you've met and any notifications, messages and invites reward you with an unpredictable high, much any notifications, messages and invites reward you with an unpredictable high, much like gambling. like gambling.

http://blog.futurelab.net/2008/05/are_you_suffering_from_faceboo.html

Internet Disorders Internet Disorders Not Otherwise Specified…Not Otherwise Specified…

Youtube Addiction Disorder (YAD) Youtube Addiction Disorder (YAD) Google Search Addiction Disorder (GSAD) Google Search Addiction Disorder (GSAD) Widget Addiction Disorder (WAD) Widget Addiction Disorder (WAD) Twitter Addiction Disorder (TAD) Twitter Addiction Disorder (TAD) Blackberry Addiction Disorder (BAD)Blackberry Addiction Disorder (BAD)

Speculation about Speculation about Internet GamblingInternet Gambling

Internet gambling is Internet gambling is prolific and growingprolific and growing– Growth increases Growth increases

exposureexposure Increased accessibility Increased accessibility

makes internet makes internet gambling more gambling more addictive than other addictive than other types of gamblingtypes of gambling

No standardized No standardized product safety product safety regulations to protect regulations to protect vulnerable populationsvulnerable populations

State of Knowledge: State of Knowledge: Internet GamblingInternet Gambling

Very little peer-reviewed and published Very little peer-reviewed and published empirical research empirical research

Theoretical propositions and opinion Theoretical propositions and opinion papers represent most of the papers represent most of the professional discussion surrounding professional discussion surrounding this topicthis topic

The available empirical findings are The available empirical findings are from studies that use variations of from studies that use variations of retrospective self-report methodology retrospective self-report methodology

Methods: ProceduresMethods: Procedures

Used Used PubMed & PsycINFOPubMed & PsycINFO databases to databases to identify the gambling literature that identify the gambling literature that includedincluded

– ““Internet” and “gambling”Internet” and “gambling” Three inclusion criteria for studies:Three inclusion criteria for studies:

– Published between Published between 1903 & 2007 1903 & 2007 in peer-in peer-review journalsreview journals

– HHave the word ave the word “gambling”“gambling” and and “Internet”“Internet” in in one of four citation fields: one of four citation fields: title, keyword, title, keyword, abstract, and textabstract, and text

– HHave some ave some relevancerelevance to the field of gambling to the field of gambling studiesstudies

3030 publications met these criteria publications met these criteria

We classified these We classified these 3030 into three publication into three publication groups:groups:

– CommentariesCommentaries - articles with no empirical - articles with no empirical datadata

– Self-report surveysSelf-report surveys - articles with empirical - articles with empirical data provided by participantsdata provided by participants

– Actual Internet gamblingActual Internet gambling - articles with - articles with data describing actual Internet Gambling data describing actual Internet Gambling

67%

33%

0%

Commentaries Self-Reports Actual Behavior

Internet Gambling PublicationsInternet Gambling Publications

0

1

2

3

4

5

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Commentaries Self-Reports Actual Behavior

"...self-report appears to have all but crowded "...self-report appears to have all but crowded out all other forms of behavior. Behavioral out all other forms of behavior. Behavioral

science today... mostly involves asking people science today... mostly involves asking people to report on their thoughts, feelings, memories, to report on their thoughts, feelings, memories,

and attitudes.... Direct observation of and attitudes.... Direct observation of meaningful behavior is apparently passe´" (p. meaningful behavior is apparently passe´" (p.

397).397).

Baumeister, R. F., Vohs, K. D., & Funder, D. C. (2007). Psychology Baumeister, R. F., Vohs, K. D., & Funder, D. C. (2007). Psychology as the science of self-reports and finger movements: whatever as the science of self-reports and finger movements: whatever happened to actual behavior? happened to actual behavior? Psychological Science, 2Psychological Science, 2(4), 396-(4), 396-

403.403.

SolutionsSolutions

Approaches need to go beyond Approaches need to go beyond retrospective self-report and include retrospective self-report and include objective measures, such as actual objective measures, such as actual Internet gambling behavior Internet gambling behavior

Using actual behavior avoids the Using actual behavior avoids the difficulties inherent in self-report (National difficulties inherent in self-report (National Research Council, 1999) as well as the Research Council, 1999) as well as the need to compress the information about need to compress the information about actual behavior occurring during long actual behavior occurring during long intervals into a few summary descriptions intervals into a few summary descriptions elicited by survey questionselicited by survey questions

Internet Gambling: Internet Gambling: Risk and Resource?Risk and Resource?

Internet Gambling provides unique Internet Gambling provides unique opportunities for the study of gambling opportunities for the study of gambling behavior and problems.behavior and problems.

Unlike land-based gambling, the very Unlike land-based gambling, the very technology that makes Internet technology that makes Internet gambling a potential risk allows for the gambling a potential risk allows for the study of actual real-time gambling study of actual real-time gambling behavior.behavior.

Responsible Gaming

BWIN Corporate

Social Responsibility

Database Research

Experimental Research

bwin / Division on Addictions bwin / Division on Addictions Research CollaborativeResearch Collaborative

BWin / DOA Collaborative: BWin / DOA Collaborative: ObjectivesObjectives

To address the dearth of scientific To address the dearth of scientific information on Internet gambling, bwin information on Internet gambling, bwin and the DOA have entered into a seminal and the DOA have entered into a seminal research collaboration relying substantially research collaboration relying substantially on data provided by bwin subscriber on data provided by bwin subscriber gaming activity. gaming activity.

The principal goal of this project is to The principal goal of this project is to empirically examine Internet gambling. empirically examine Internet gambling.

A second goal is to provide Bwin’s current A second goal is to provide Bwin’s current corporate social responsibility department corporate social responsibility department with evidence-based research, tools, and with evidence-based research, tools, and programs about problem gambling, so that programs about problem gambling, so that they can effectively protect the health of they can effectively protect the health of the general public as well as the industry. the general public as well as the industry.

Assessing the Playing Field: Assessing the Playing Field: Internet Sports GamblingInternet Sports Gambling

Present StudyPresent Study

Epidemiological description of Epidemiological description of characteristics of 40,499 sequentially characteristics of 40,499 sequentially subscribed Internet sports gamblerssubscribed Internet sports gamblers

Epidemiological description of the Epidemiological description of the gambling behavior of these Internet gambling behavior of these Internet gamblers over the course of 8 gamblers over the course of 8 monthsmonths

Epidemiological description of the Epidemiological description of the gambling behavior of empirically gambling behavior of empirically determined groups of the heavily determined groups of the heavily involved bettorsinvolved bettors

ParticipantsParticipants42,647 internet gamblers

925 did not bet w/ own money w/in month of study end

41,722 bet w/ own money w/in month of study end

40,499 sports bettors

1,223 non-sports bettors

15,705 fixed-odds only 780 live-action only24,014 fixed-odds and live-action

39,719 fixed-odds bettors 24,794 live-action bettors

MeasuresMeasures DemographicsDemographics

– AgeAge– GenderGender– Country of residence Country of residence

Types of betsTypes of bets– Fixed-oddsFixed-odds– Live-actionLive-action

Actual betting records (daily Actual betting records (daily aggregate) aggregate) – BetsBets– Value of betsValue of bets– WinningsWinnings

Types of BetsTypes of Bets Fixed-OddsFixed-Odds

– bets made on the outcomes of sporting events or games in bets made on the outcomes of sporting events or games in which the amount paid for a winning bet is set by the which the amount paid for a winning bet is set by the betting servicebetting service

– relatively slow-cycling betting propositions; the outcomes relatively slow-cycling betting propositions; the outcomes of a bet are generally not known for hours or even (in the of a bet are generally not known for hours or even (in the case of cricket matches) dayscase of cricket matches) days

Live-ActionLive-Action– bets made on propositions about outcomes within a bets made on propositions about outcomes within a

sporting event (e.g., which side will have the next corner sporting event (e.g., which side will have the next corner kick or whether the next tennis game in a match will be kick or whether the next tennis game in a match will be won at love by the server)won at love by the server)

– More rapidly cycling betting propositions; provides many, More rapidly cycling betting propositions; provides many, relatively quick-paced, betting propositions posed in real-relatively quick-paced, betting propositions posed in real-time during the progress of a sporting event time during the progress of a sporting event

Betting Behavior Betting Behavior (derived from daily aggregate (derived from daily aggregate

records)records) DurationDuration

– # of days from first to # of days from first to last eligible betlast eligible bet

FrequencyFrequency– % of days within % of days within

duration interval that duration interval that included a betincluded a bet

# of bets# of bets– Sum of daily Sum of daily

aggregatesaggregates Bets per dayBets per day

– # of bets / days on # of bets / days on which a bet was placedwhich a bet was placed

Euros per bet Euros per bet – Total wagered / # of Total wagered / # of

betsbets

Total wageredTotal wagered – Sum of daily Sum of daily

aggregatesaggregates Net lossNet loss

– Total wagered – Total wagered – Total winningsTotal winnings

Percent lostPercent lost– [Net loss / Total [Net loss / Total

wagered] * 100wagered] * 100

Cohort Characteristics: Cohort Characteristics: Gender and AgeGender and Age

Mean age = Mean age = 3131

0%5%

10%15%20%25%30%35%40%45%50%

<21 21-30 31-40 41-50 51-60 61+

91.6% male91.6% male

Cohort Characteristics: Cohort Characteristics: CountryCountry

2.3%2.3%

3.4%3.4%

4.9%4.9%

57.9%57.9%

5.7%5.7%

3.3%3.3%

5.7%5.7%

5.6%5.6%

1.4%1.4%

5.8%5.8%

85 countries85 countries

Gambling Behavior: Gambling Behavior: Type of GameType of Game

59%

2%

39%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Fixed Odds Only Fixed and Live Live Action Only

Gambling Behavior: Gambling Behavior: DurationDuration

28%

47%

10% 10%

7% 6%6% 5% 5% 5% 5% 6%

13% 11%

26%

11%

0%

10%

20%

30%

40%

50%

1-30 31-60 61-90 91-120 121-150 151-180 181-210 211-242

Days from First to Last Bet

Fixed OddsLive Action

M(SD), Median: Fixed-Odds 118(89), 116;M(SD), Median: Fixed-Odds 118(89), 116; Live-Action 79(83), 40Live-Action 79(83), 40

Gambling Behavior: Gambling Behavior: FrequencyFrequency

24%

26%

20%

17%

15%

11%11%

7%

9%

6%

4%3% 4%

3% 3% 2%

1%1%

7%

24%

0%

10%

20%

30%

0-10% 11-20% 21-30% 31-40% 41-50% 51-60% 61-70% 71-80% 81-90% 91-100%

% of Days w/ in Duration Including a Bet


M(SD), Median: Fixed-Odds 32%(27), 23%;M(SD), Median: Fixed-Odds 32%(27), 23%; Live-Action 42%(37), 27%Live-Action 42%(37), 27%

Gambling Behavior: Gambling Behavior: # of Bets# of Bets

23%

41%

50%

42%

13%8%

5% 3%3%

2%2% 1%

5% 4%

0%

10%

20%

30%

40%

50%

60%

<10 10-100 101-200 201-300 301-400 401-500 501+

# of Bets



Gambling Behavior: Gambling Behavior: Bets per DayBets per Day

10%

16%

30%

22%22%

17%

12%12%

7%8%

5% 6%

3%4%

2%

3%

2% 2% 1%2%

6%

8%

0%

5%

10%

15%

20%

25%

30%

35%

1 1.-2 2.-3 3.-4 4.-5 5.-6 6.-7 7.-8 8.-9 9.-10 10.+

Bets per Gambling Day


M(SD), Median: Fixed-Odds 4.1(7.7), 2.5;M(SD), Median: Fixed-Odds 4.1(7.7), 2.5; Live-Action 4.3(5.0), 2.8Live-Action 4.3(5.0), 2.8

Gambling Behavior: Gambling Behavior: Euros per BetEuros per Bet

26%

31% 30%29%

22%

19%

8% 7%

4%4%

2% 2% 2% 2% 1%1%1%1% 1%1% 1%1%

4% 4%

0%

5%

10%

15%

20%

25%

30%

35%

0-2 2.-5 5.-10 10.-15 15.-20 20.-25 25.-30 30.-35 35.-40 40.-45 45.-50 50.+

Euros per Bet



Gambling Behavior: Gambling Behavior: Total WageredTotal Wagered

5%

20%

35%

39%

17%

11%9%

6%6%

3% 4%

2%

3%

2%2%

1%

2%

1%

2%

1%

1%

1%

6%4%

6%6%

1%3%

0%

5%

10%

15%

20%

25%

30%

35%

40%

0.-1

0

10.-1

00

100.-2

00

200.-3

00

300.-4

00

400.-5

00

500.-6

00

600.-7

00

700.-8

00

800.-9

00

900.-1

000

1000

.-200

0

2000

.-100

00

1000

0.+

Total Wagered


M(SD), Median: Fixed-Odds 729(3439), 148; Live-Action 1319(8592), 61M(SD), Median: Fixed-Odds 729(3439), 148; Live-Action 1319(8592), 61

Gambling Behavior: Gambling Behavior: Net LossNet Loss

16%

23%

27%

45%

19%

11%9%

5%7%3% 4%

2%3%

1% 2%1% 2%1%

7%4%

3%2% 2%2%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

<00-

25

25.-5

0

50.-7

5

75.-1

00

100.-1

25

125.-1

50

150.-1

75

175.-2

00

200.-5

00

500.-1

000

1000

.+

Total Wagered - Total Winnings



Gambling Behavior: Gambling Behavior: Percent LostPercent Lost

16%

22%

12%

17%

13%14%

11%10% 9%

7% 7%

5%5%

4% 4%

2% 3%2% 2% 1%

1% 0%

17%16%

0%

5%

10%

15%

20%

25%

<0

0-10

%

11-2

0%

21-3

0%

31-4

0%

41-5

0%

51-6

0%

61-7

0%

71-8

0%

81-9

0%

91-9

9%10

0%

(Net Loss / Total Wagered) * 100



Heavily Involved BettorsHeavily Involved Bettors

On 5 of 8 measures, 1% of the sample On 5 of 8 measures, 1% of the sample exhibited behavior that was exhibited behavior that was discontinuously highdiscontinuously high

e.g.:e.g.:Fixed Odds

0

5000

10000

15000

20000

25000

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

Percentile

Me

an

Tota

l Wa

ge

red

Heavily Involved BettorsHeavily Involved Bettors

We examined the betting behavior of: We examined the betting behavior of: – individuals who fell in the top 1% on total individuals who fell in the top 1% on total

wageredwagered– individuals who fell in the top 1% on net lossindividuals who fell in the top 1% on net loss– individuals who fell in the top 1% on # of betsindividuals who fell in the top 1% on # of bets

Fixed Odds Heavily Involved Fixed Odds Heavily Involved Bettors: Bettors: OverlapOverlap

45%

73%

36% 36%

8%8%

6% 6%

13% 13% 13%

43%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Top 1% Net Loss (NL) Top 1% Total Wagered (TW) Top 1% # of Bets (NoB)

NL Only TW Only NoB Only NL & TWNoB & NL TW & NoB All 3

Live Action Heavily Involved Live Action Heavily Involved Bettors: Bettors: OverlapOverlap

36%

52%

26% 26%

10%

10%

11% 11%

27% 27% 27%

37%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Top 1% Net Loss (NL) Top 1% Total Wagered (TW) Top 1% # of Bets (NoB)

NL Only TW Only NoB Only NL & TWNoB & NL TW & NoB All 3

Heavily Involved Bettors: Heavily Involved Bettors: Fixed OddsFixed Odds

Top 1% Net Loss Top 1% Net Loss (n=397)(n=397)

Top 1% Total Top 1% Total Wagered (n=397)Wagered (n=397)

Top 1% # of Bets Top 1% # of Bets (n=397)(n=397)

Mean (SD)Mean (SD) MediaMediann


Mean Mean (SD)(SD)

MediaMediann

DurationDuration 189 (57)189 (57) 215215 194 (53)194 (53) 217217 204 (43)204 (43) 220220

FrequencFrequencyy

45% (22)45% (22) 42%42% 51% (21)51% (21) 48%48% 57% (21)57% (21) 57%57%

# of Bets# of Bets 1545 (3241)1545 (3241) 423423 1438 1438 (3151)(3151)

423423 3497 3497 (3153)(3153)

23712371

Bets/DayBets/Day 18.0 (51.0)18.0 (51.0) 5.45.4 13.0 (27.2)13.0 (27.2) 4.74.7 37.3 (51.2)37.3 (51.2) 26.426.4

Euros/BetEuros/Bet 55 (94)55 (94) 2323 77 (96)77 (96) 4444 3 (5)3 (5) 11

Total Total WageredWagered

1503715037

(15709)(15709)1025910259 22891 22891

(23879)(23879)1678416784 8421 8421

(12898)(12898)41444144

Net LossNet Loss 3491 (2617)3491 (2617) 26452645 1838 1838 (4547)(4547)

15441544 1261 1261 (2232)(2232)

740740

% Lost% Lost 35 (22)35 (22) 2929 10 (16)10 (16) 99 19 (17)19 (17) 1818

Heavily Involved Bettors: Heavily Involved Bettors: Live ActionLive Action

Top 1% Net Loss Top 1% Net Loss (n=247)(n=247)

Top 1% Total Top 1% Total Wagered (n=247)Wagered (n=247)

Top 1% # of Bets Top 1% # of Bets (n=247)(n=247)



Mean Mean (SD)(SD)

MediaMediann

DurationDuration 189 (53)189 (53) 213213 188 (50)188 (50) 209209 206 (34)206 (34) 217217

FrequencFrequencyy

50% (23)50% (23) 49%49% 57% (21)57% (21) 56%56% 64% (18)64% (18) 65%65%

# of Bets# of Bets 1767 (2678)1767 (2678) 973973 1700 1700 (2315)(2315)

10341034 2938 2938 (2451)(2451)

21502150

Bets/DayBets/Day 16.1 (16.5)16.1 (16.5) 11.311.3 14.6 (13.9)14.6 (13.9) 10.710.7 23.0 (15.7)23.0 (15.7) 18.518.5

Euros/BetEuros/Bet 59 (63)59 (63) 3434 81 (79)81 (79) 5353 15 (26)15 (26) 66

Total Total WageredWagered

4795447954

(56687)(56687)2914429144 64740 64740

(53046)(53046)4411144111 36115 36115

(54215)(54215)1574315743

Net LossNet Loss 4189 (3062)4189 (3062) 30523052 2642 2642 (4270)(4270)

19731973 2159 2159 (3115)(3115)

11111111

% Lost% Lost 15 (12)15 (12) 1212 14 (7)14 (7) 44 9 (7)9 (7) 77

Longitudinal CohortLongitudinal Cohort

Median Behaviors – Fixed OddsMedian Behaviors – Fixed Odds

Total Sample and Most Involved LosersTotal Sample and Most Involved Losers

MeasureMeasure Total (39,719) Total (39,719) Top B&L* (144)Top B&L* (144)

Duration Duration 116 (of 244)116 (of 244) 219 (of 244)219 (of 244)

FrequencyFrequency 23%23% 50%50%

Bets/dayBets/day 2.52.5 77

Euros/betEuros/bet 44 4242

Total WageredTotal Wagered 148148 21,80721,807

Net LossNet Loss 3333 3,9143,914

% Lost% Lost 29%29% 18%18%

Sum of Stakes by Month Sum of Stakes by Month (Total (Total Sample)Sample)

0.00

1000000.00

2000000.00

3000000.00

4000000.00

5000000.00

6000000.00

7000000.00

8000000.00

9000000.00

10000000.00

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Months

Su

m o

f S

take

s (F

ull

Sam

ple

)

STAKE fixed odds STAKE live action

Sum of Stakes By Day Sum of Stakes By Day (Most (Most involved)involved)

0

10000

20000

30000

40000

50000

60000

70000

80000

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88

Days

Su

m o

f S

take

s (1

% F

O-S

)

STAKE fixed odds STAKE live action

CaveatCaveat

We don’t know how much disposable We don’t know how much disposable income these betters had availableincome these betters had available

Therefore, it is not possible to Therefore, it is not possible to calibrate the social harm these calibrate the social harm these losses might have causedlosses might have caused

Despite the caveat about discretionary funds, the results do suggest problem

gambling is not as common among Internet sports bettors as the

speculations and the consequent conventional wisdom suggested.

ConclusionConclusion

Inside the Virtual Casino: Inside the Virtual Casino: Internet Casino GamblingInternet Casino Gambling

Sports Betters RevisitedSports Betters Revisited

Most people play moderatelyMost people play moderately– 1% of the sample played differently 1% of the sample played differently

from the rest, making a median of 4.7 from the rest, making a median of 4.7 bets every other daybets every other day

Most people’s play adapted, following the Most people’s play adapted, following the prototypical public health adaptation prototypical public health adaptation curvescurves– 1% of the sample did not adapt1% of the sample did not adapt

Casino Play HypothesesCasino Play Hypotheses

Individuals betting in virtual casinos will Individuals betting in virtual casinos will exhibit riskier behaviors than observed exhibit riskier behaviors than observed among Internet sports bettors and poker among Internet sports bettors and poker players. players. – Example: more excessive loss patterns or time Example: more excessive loss patterns or time

spent gamblingspent gambling Moderate and consistent gambling among Moderate and consistent gambling among

the majority of the population the majority of the population A small minority (i.e. 5% or less) will A small minority (i.e. 5% or less) will

exhibit excessive gambling behavior.exhibit excessive gambling behavior.

Internet Casino GamblersInternet Casino Gamblers

Ever played Casino Games (n = 8,472) Ever played Casino Games (n = 8,472)

20% of Longitudinal Sample20% of Longitudinal Sample– Excluded (n = 4,250)Excluded (n = 4,250)

Gambled 3 or fewer times (4,225)Gambled 3 or fewer times (4,225) Gambled with promotional funds (10)Gambled with promotional funds (10) Gambling began less than one month Gambling began less than one month

before the end to the study (15) before the end to the study (15) – Final sample (n = 4,222)Final sample (n = 4,222)

DemographicsDemographics Average age = 30Average age = 30• 93% male93% male• Spread out across 46 countriesSpread out across 46 countries• Only 1 gender difference:Only 1 gender difference:

– Women place more bets per day than Women place more bets per day than men men

•MMwomenwomen = 141, SD = 206 = 141, SD = 206

•MMmenmen = 114, SD = 191 = 114, SD = 191

•P<0.05P<0.05

Gambling behavior of Gambling behavior of internet casino gamblersinternet casino gamblers

Casino vs Sports Casino vs Sports GamblingGambling

Even though casino spending was higher than spending on other types of Even though casino spending was higher than spending on other types of games, the cohort of casino bettors played less frequently than the sports games, the cohort of casino bettors played less frequently than the sports bettors.bettors.

The observation that casino game bettors incur larger losses at each The observation that casino game bettors incur larger losses at each gambling session compared to sports bettors is consistent with our gambling session compared to sports bettors is consistent with our hypothesis that casino-type games offer an additional risk for players.hypothesis that casino-type games offer an additional risk for players.

0

1

2

3

4

5

6

7

Live action

Fixed-odds

Casino games

Cos

t pe

r da

y (€

)

0

1

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3

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6

7

Live action

Fixed-odds

Casino

Pla

y pe

r m

onth

Frequency of play for each game typeFrequency of play for each game typeCost of play for each game typeCost of play for each game type

ImplicationsImplications

Few people play internet casino Few people play internet casino gamesgames– 18% of bwin subscribers played, half of 18% of bwin subscribers played, half of

whom never played more than three whom never played more than three days.days.

The typical daily cost of casino The typical daily cost of casino gambling is considerably larger than gambling is considerably larger than the sports betting costs of this the sports betting costs of this cohort.cohort.

Total stakes wagered on casino Total stakes wagered on casino gamesgames

Gambling behavior of extreme 5 Gambling behavior of extreme 5 and 95% subgroups of casino and 95% subgroups of casino

bettorsbettors

Cost of Casino GamblingCost of Casino Gambling

The top 5% of casino gamers lost The top 5% of casino gamers lost a significantly smaller percent of a significantly smaller percent of their total wagers compared to their total wagers compared to the rest of the casino gamblers the rest of the casino gamblers (t = 21.0, ndf = 871, P < 0.001).(t = 21.0, ndf = 871, P < 0.001).

LimitationsLimitations

Casino gambling might not have Casino gambling might not have been so popular because bwin is been so popular because bwin is primarily a sports betting primarily a sports betting service.service.

Females are underrepresented, Females are underrepresented, although their betting behavior although their betting behavior did not differ much from that of did not differ much from that of males.males.

Responsible Gambling Efforts Responsible Gambling Efforts in the Virtual Worldin the Virtual World

Unique Opportunities for Unique Opportunities for InterventionIntervention

Tracking software for early Tracking software for early identification of people who are at-identification of people who are at-risk for developing problemsrisk for developing problems

Limit-settingLimit-setting– TimeTime– LossesLosses– DepositsDeposits

Pop-up messaging and email by Pop-up messaging and email by request or by designrequest or by design

Corporate Social Corporate Social ResponsibilityResponsibility

Corporate Deposit LimitsCorporate Deposit Limits Self-limitation of DepositsSelf-limitation of Deposits

Deposit LimitsDeposit Limits

bwin Interactive Entertainment, AG bwin Interactive Entertainment, AG imposes corporate deposit limits on its imposes corporate deposit limits on its subscribers and allows subscribers to set subscribers and allows subscribers to set specific deposit limits, if they are lower specific deposit limits, if they are lower than the corporate limitsthan the corporate limits

Subscribers who try to deposit more than Subscribers who try to deposit more than the allowed amount receive from bwin a the allowed amount receive from bwin a notification message about the attempt to notification message about the attempt to exceed the deposit limit and bwin rejects exceed the deposit limit and bwin rejects the attempted depositthe attempted deposit

Broda, LaPlante, Nelson, LaBrie, Bosworth, & Shaffer, 2008

ExpectationsExpectations

Users who receive a notification Users who receive a notification constitute a group of extremely constitute a group of extremely engaged gamblersengaged gamblers– Excessively large betting, high loss or Excessively large betting, high loss or

high frequency of gamblinghigh frequency of gambling Receiving a notification acts as a Receiving a notification acts as a

warning signwarning sign– Gambling behavior would attenuate Gambling behavior would attenuate

after such notificationafter such notification

Sample DescriptionSample Description

160 (0.3%; 5 women) of the sample 160 (0.3%; 5 women) of the sample received at least one notification received at least one notification (Exceeders)(Exceeders)

Exceeders received between 1 and 267 Exceeders received between 1 and 267 notifications (M=14 notifications)notifications (M=14 notifications)

Gambling Behavior Before & Gambling Behavior Before & After NotificationAfter Notification

After receiving notification:After receiving notification:– Exceeders did not reduce their number Exceeders did not reduce their number

of active betting days of active betting days – Exceeders patterns of losses did not Exceeders patterns of losses did not

changechange– Exceeders increased their average size Exceeders increased their average size

of betof bet– Exceeders decreased the average Exceeders decreased the average

number of bets per active betting daynumber of bets per active betting dayExceeders made fewer, larger bets per active betting day after notification

SummarySummary In general, the mere existence of deposit In general, the mere existence of deposit

limits might serve as a harm reduction limits might serve as a harm reduction devicedevice

Exceeding established limits can serve as Exceeding established limits can serve as an indicator for heavy betting behavior an indicator for heavy betting behavior and large overall lossesand large overall losses

Notification systems for exceeding deposit Notification systems for exceeding deposit limits do not completely curtail betting limits do not completely curtail betting behavior, but are associated with changes behavior, but are associated with changes in betting strategyin betting strategy– Moving away from smaller more frequent bets Moving away from smaller more frequent bets

to larger more infrequent betsto larger more infrequent bets

General Comment on General Comment on Notification SystemsNotification Systems

Apparent need to re-think the use of notification Apparent need to re-think the use of notification systems as harm reduction devices for those at-systems as harm reduction devices for those at-risk for excessive patterns of bettingrisk for excessive patterns of betting

Similar limitations for other such systems:Similar limitations for other such systems:– People who were given feedback that BAC exceeded People who were given feedback that BAC exceeded

legal limits have been subsequently observed to drivelegal limits have been subsequently observed to drive– Drivers who receive speed tickets are at increased risk Drivers who receive speed tickets are at increased risk

of receiving subsequent speeding ticketsof receiving subsequent speeding tickets– Smokers who receive biomedical feedback do not Smokers who receive biomedical feedback do not

initiate appreciable changes toward quitting smokinginitiate appreciable changes toward quitting smoking

Self-limitation of DepositsSelf-limitation of Deposits

bwin Interactive Entertainment, AG bwin Interactive Entertainment, AG allows subscribers to self-impose allows subscribers to self-impose deposit limits that are lower than deposit limits that are lower than those defined by corporate policythose defined by corporate policy

Attempts to exceed self-imposed Attempts to exceed self-imposed deposit limits are blocked by the deposit limits are blocked by the company software systemcompany software system

Nelson, LaPlante, Peller, Schumann, LaBrie, & Shaffer, in press

ExpectationsExpectations

Participating in the self-limitation Participating in the self-limitation system could be an indicator of system could be an indicator of potential disordered gamblingpotential disordered gambling

Users who self-limit constitute a Users who self-limit constitute a group of extremely engaged group of extremely engaged gamblersgamblers

Self-limitation will promote healthier Self-limitation will promote healthier gambling behaviorgambling behavior– Decreased stakes, bets, and frequency Decreased stakes, bets, and frequency

of bettingof betting

Sample DescriptionSample Description

567 (1.2%) of the sample 567 (1.2%) of the sample participated in the self-limitation participated in the self-limitation system (Limiters)system (Limiters)– 7% of these individuals placed these 7% of these individuals placed these

limits before they made their first betlimits before they made their first bet– 11% ceased betting completely after 11% ceased betting completely after

they self-imposed limitsthey self-imposed limits

Limiters versus Others: Limiters versus Others: Pre-limit ComparisonsPre-limit Comparisons

Limiters played a greater diversity of Limiters played a greater diversity of gambling gamesgambling games

Limiters bet on more days within their Limiters bet on more days within their active betting periodactive betting period

Limiters placed more bets per dayLimiters placed more bets per day Limiters wagered less money per betLimiters wagered less money per bet Limiters and others did not differ in terms Limiters and others did not differ in terms

of:of:– Total wagered, net loss, percent lostTotal wagered, net loss, percent lost

Results: Games PlayedResults: Games Played

0%

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30%

40%

50%

60%

70%

80%

90%

100%

Per

cent

Pla

yin

g

Fixed Odds Live Action Casino Supertoto Softgames Lottery Flash Poker

Rest of Sample SLs

Gambling Behavior Before & Gambling Behavior Before & After Self-LimitationAfter Self-Limitation

Limiters behavior’ after imposing limits generally Limiters behavior’ after imposing limits generally moved in the direction of fewer betsmoved in the direction of fewer bets

For example, for fixed odds betting, limiters:For example, for fixed odds betting, limiters:

ActiveBettingDays

BetsPerDay

AmountWagered

Results: Self Limiter Pre-Post Results: Self Limiter Pre-Post Behavior Behavior

(Fixed Odds & Live Action Combined; (Fixed Odds & Live Action Combined; n=477)n=477)

Pre-limitPre-limit % active days bet:% active days bet:

– 33.0 (SD: 29.5)*33.0 (SD: 29.5)* Bets per day: Bets per day:

– 7.1 (SD: 6.9)*7.1 (SD: 6.9)* Net loss/stakes: Net loss/stakes:

– .23 (SD: .35).23 (SD: .35) Average bet size: Average bet size:

– €€7.0 (SD: €12.0)*7.0 (SD: €12.0)*

Post-limitPost-limit % active days bet: % active days bet:

– 29.5 (SD: 26.2)*29.5 (SD: 26.2)* Bets per day: Bets per day:

– 6.2 (SD: 7.1)*6.2 (SD: 7.1)* Net loss/stakes: Net loss/stakes:

– .24 (SD: .48).24 (SD: .48) Average bet size: Average bet size:

– €€8.3 (SD: €14.8)*8.3 (SD: €14.8)*

SummarySummary

Limiters were more active bettors Limiters were more active bettors than othersthan others– Place more bets, bet on more days Place more bets, bet on more days

during active period, bet on greater during active period, bet on greater diversity of productsdiversity of products

If self-limitation is a sign of disordered If self-limitation is a sign of disordered gambling, gambling, involvementinvolvement might be as might be as important to indicating gambling-important to indicating gambling-related problems as related problems as expendituresexpenditures

General LimitationsGeneral Limitations

Limiting resources Limiting resources are only helpful if are only helpful if people can access people can access them easilythem easily


Interventions will Interventions will only work if the only work if the message gets message gets through to the through to the targettarget


Real behavior measures provide an Real behavior measures provide an unbiased assessment of actual Internet unbiased assessment of actual Internet gambling, but cannot be used to gambling, but cannot be used to determine rates of gambling-related determine rates of gambling-related problemsproblems

Healthy changes in gambling behavior Healthy changes in gambling behavior for our sample do not preclude for our sample do not preclude unhealthy changes in gambling unhealthy changes in gambling behavior, or other behavior, on other behavior, or other behavior, on other websites or activitieswebsites or activities

Concluding ThoughtsConcluding Thoughts The Internet provides some unique The Internet provides some unique

opportunities for harm reduction opportunities for harm reduction devices that might be executed with devices that might be executed with some successsome success

Internet gambling is likely to continue Internet gambling is likely to continue to grow during the next decades, and to grow during the next decades, and empirical examination is necessary to empirical examination is necessary to the development of safe and effective the development of safe and effective responsible gaming intervention effortsresponsible gaming intervention efforts

ReferencesReferences LaBrie, R. A., LaPlante, D. A., Nelson, S. E., Schumann, A., & LaBrie, R. A., LaPlante, D. A., Nelson, S. E., Schumann, A., &

Shaffer, H. J. (2007). Shaffer, H. J. (2007). Assessing the playing field: A prospective longitudinal study of IAssessing the playing field: A prospective longitudinal study of Internet sports gambling behaviornternet sports gambling behavior. . Journal of Gambling Studies, Journal of Gambling Studies, 23, 347-362.23, 347-362.

LaBrie R.A., Kaplan, S.A., LaPlante, D.A., Nelson, S.E., and LaBrie R.A., Kaplan, S.A., LaPlante, D.A., Nelson, S.E., and Shaffer, H.J. (2008). Shaffer, H.J. (2008). Inside the virtual casino: A prospective longitudinal study of actInside the virtual casino: A prospective longitudinal study of actual Internet casino gamblingual Internet casino gambling. . European Journal of Public HealthEuropean Journal of Public Health, 18(4), 410-416. , 18(4), 410-416.

LaPlante, D.A., Schumann, A., LaBrie, R.A., & Shaffer, H.J. LaPlante, D.A., Schumann, A., LaBrie, R.A., & Shaffer, H.J. (2008). (2008). Population trends in Internet sports gamblingPopulation trends in Internet sports gambling. . Computers in Human BehaviorComputers in Human Behavior, 24, 2399-2414. , 24, 2399-2414.

Broda, A., LaPlante, D. A., Nelson, S. E., LaBrie, R. A., Bosworth, Broda, A., LaPlante, D. A., Nelson, S. E., LaBrie, R. A., Bosworth, L. B. & Shaffer, H. J. (2008). L. B. & Shaffer, H. J. (2008). Virtual harm reduction efforts for Internet gambling: Effects of Virtual harm reduction efforts for Internet gambling: Effects of deposit limits on actual Internet sports gambling behaviordeposit limits on actual Internet sports gambling behavior. . Harm Reduction JournalHarm Reduction Journal, 5, 27. , 5, 27.

Nelson, S. E., LaPlante, D. A., Peller, A. J., Schumann, A., LaBrie, Nelson, S. E., LaPlante, D. A., Peller, A. J., Schumann, A., LaBrie, R. A., & Shaffer, H. J. (2008). R. A., & Shaffer, H. J. (2008). Real limits in the virtual world: Self-limiting behavior of InternetReal limits in the virtual world: Self-limiting behavior of Internet gamblers gamblers. . Journal of Gambling StudiesJournal of Gambling Studies, 24(4), 463-477. , 24(4), 463-477.

Available Resources & Available Resources & LinksLinks

www.divisiononaddictions.orgwww.divisiononaddictions.org

www.basisonline.orgwww.basisonline.org

www.thetransparencyproject.orgwww.thetransparencyproject.org

[email protected]@hms.harvard.edu

www.divisiononaddictions.orgwww.divisiononaddictions.org

www.basisonline.orgwww.basisonline.org

www.thetransparencyproject.orgwww.thetransparencyproject.org

[email protected]@hms.harvard.edu

First ever public data repository for First ever public data repository for privately-funded datasets, such as privately-funded datasets, such as industry-funded dataindustry-funded data

Addictive behavior datasets (e.g., Addictive behavior datasets (e.g., alcohol, drugs, gambling, excessive alcohol, drugs, gambling, excessive shopping, etc.)shopping, etc.)

The Transparency Project website http://www.thetransparencyproject.org

Scientific information often is locked away with Scientific information often is locked away with limited accessibilitylimited accessibility

There is a need to facilitate greater access to There is a need to facilitate greater access to privately-funded databasesprivately-funded databases

A venue through which researchers can make A venue through which researchers can make public their private data is neededpublic their private data is needed

The Transparency ProjectDivision on Addictions, The Cambridge Health Alliance

a teaching affiliate of Harvard Medical School

Promote transparency for privately-funded Promote transparency for privately-funded science and better access to scientific informationscience and better access to scientific information

Collect and archive high quality addiction-related Collect and archive high quality addiction-related privately-funded data from around the worldprivately-funded data from around the world

Make data available to scientists to advance the Make data available to scientists to advance the available empirical evidence and knowledge base available empirical evidence and knowledge base about addictionabout addiction

Alleviate the burdens caused by addictive Alleviate the burdens caused by addictive behaviorsbehaviors

The Transparency ProjectDivision on Addictions, The Cambridge Health Alliance

a teaching affiliate of Harvard Medical School

Documents

Findings from a Longitudinal Study of Internet Gambling Behavior Sarah E. Nelson, Ph.D. Division on Addictions Cambridge Health Alliance, Harvard Medical