youth gambling and the internet: the good, the bad and the ugly jeffrey l. derevensky, ph.d....

Youth gambling and the Internet: The good, the bad and the ugly

Jeffrey L. Derevensky, Ph.D.

Professor, School/Applied Child Psychology

Professor, Psychiatry

McGill UniversityInternational Centre for Youth Gambling Problems and High-Risk

Behaviors

www.youthgambling.com

Alberta Gambling Research Institute Annual ConferenceMarch, 2009

Is gambling dangerous??

Internet gambling on anything

The appeal of the Internet…

Celebrity endorsements….

Prevalence Findings of Internet Wagering

• Vary considerably

• Dependent upon method & date of data collection

• Dependent upon population studied

• Difficulties collecting data have been articulated by Wood & Williams (2009)

Adolescent Internet use…

Internet Use Media Awareness Network, 2009

• In Canada, 99% of youth age 9-17 reported use of Internet, 94% have Internet access at home; 61% report having high speed access

• 37% report having their own Internet connections

• 89% of grade 4 school students play games on the Internet

• Where no household rules exist for Internet use, 74% report an adult was never present when the child was on the Internet

• 94% of students’ top 50 Internet sites include marketing material

• Large percentage of adolescents report observing Internet gambling pop-up messages & believe they were the target (Derevensky et al., 2008)

What we know about the Internet

• Access is widespread

• Access is inexpensive

• Internet is anonymous

• Internet is convenient

• Internet is entertaining

• Internet is used for many purposes

Two Internet gambling studies2004-2006

Gambling Severity by Age Group

N = 2292

Gambling Groups1

NonGambler(n = 745)

SocialGamblera

(n = 1333)

At-RiskGamblerb

(n = 139)

ProbablePathological

Gamblerc

(n = 75)

Age Group***

Under 18 years

n = 1242

35.5 51.0 8.9 4.6

18 and overn =

105029.0 66.5 2.8 1.7

Total 32.4 58.2 6.1 3.3

1Percentage. Gambling Groups are based on DSM-IV and DSM-IV-MR scores.aDSM-IV score (0-2); DSM-IV-MR-J score (0-1). bDSM-IV score (3-4); DSM-IV-MR-J score (2-3). cDSM-IV score ( ≥5); DSM-IV-MR-J score (≥4). ***p<.001.

Participation in Gambling in the Past 12 Months

0

10

20

30

40

50

lotteryscratch

cards /draws

sportsbetting

slotmachines

electronicgaming

machines

card games internetgambling

Type of Gambling

Per

cen

tag

e

male

female

Frequency of Play on Internet Gambling Games Without Money by Gender and Age

N = 2679

Frequency of Play

Never(%)

Occasionallya

(%)Regularlyb

(%)Dailyc

(%)

Gender**

Male n = 1162 59.0 33.6 4.9 2.5

Female n = 1517 62.0 32.0 4.9 1.1

Age***

12-13 years n = 166 53.6 34.4 7.8 4.2

14-15 years n = 475 56.0 36.4 5.5 2.1

16-17 years n = 786 56.6 36.0 5.5 1.9

18-20 years n = 973 62.9 31.7 4.6 0.8

21-24 years n = 235 74.9 21.7 2.1 1.3

> 25 years n = 44 88.7 6.8 0 4.5

Total 60.7 32.7 4.9 1.71Percentage. aLess than once a week. bOnce a week or more. cOnce a day or more. ***p<.001. **p<.05.

Frequency of Play on Internet Gambling Sites Without Moneyin the Past 12 Months by Gambling Severity

N = 2205

Internet Gambling Without Money1

Yes(n = 1082)

No(n = 1123)

Gambling Groups***

Non Gambler n = 726 33.9 66.1

Social Gambler n = 1278 56.6 43.4

At-Risk Gambler n = 129 74.4 25.6

Probable Pathological Gambler

n = 72 80.6 19.4

Total 49.1 50.9

1Percentage. ***p<.001.

Frequency of Play on Internet Gambling Sites With Moneyin the Past 12 Months by Gambling Severity

N = 2292

Internet Gambling With Money1

Yes(n = 183)

No(n = 2109)

Gambling Groups***

Non Gambler n = 745 0 100

Social Gambler n = 1333 9.5 90.5

At-Risk Gambler n = 139 21.6 78.4

Probable Pathological Gambler

n = 75 34.7 65.3

Total 8.0* 92.0

1Percentage *13.1% males; 4.6% females are gambling on Internet

Average Amount of Money Spent on Internet Gambling in the Last 12 Months by Gambling Severity

N=2291Amount of Money Spent

< $50 $50-$100 $100-$500 > $500

Gambling***Groups

Social Gambler

98.9 0.6 0.4 0.1

At-Risk Gambler

96.5 0 2.2 1.4

Probable Pathological Gambler

86.6 1.3 1.3 10.7

1Percentage.

Most Money Wagered in One Internet Gambling Session by Gender and Age

Amount of Money Wagered

< $50 $50-$100 $100-$500 > $500

Gender***

Males 96.8 0.9 1.2 1.0

Females 99.6 0.1 0.3 0

Age

12-13 years 98.1 0.6 1.2 0

14-15 years 97.2 0.8 0.6 1.2

16-17 years 98.3 0.3 1.0 0.4

18-20 years 98.5 0.5 0.6 0.3

21-24 years 100.0 0 0 0

> 25 years 100.0 0 0 0

1Percentage.

Most Money Wagered in One Internet Gambling Sessionby Gambling Severity

Amount of Money Wagered

< $50 $50-$100 $100-$500 > $500

Gambling***Groups

Social Gambler

99.0 0.4 0.5 0.2

At-Risk Gambler

93.5 2.2 2.2 2.2

Probable Pathological Gambler

85.3 2.7 4.0 8.0

1Percentage.

Most Money Won in One Internet Gambling Sessionby Gender and Age

Amount of Money Won

< $50 $50-$100 $100-$500 > $500

Gender***

Males 96.1 0.9 0.9 2.2

Females 98.9 0.5 0.3 0.3

Age

12-13 years 96.9 1.2 0 1.8

14-15 years 96.7 1.1 0.4 1.9

16-17 years 97.6 0.5 0.5 1.4

18-20 years 97.7 0.7 0.9 0.6

21-24 years 100.0 0 0 0

> 25 years 100.0 0 0 0

1Percentage.

Most Money Won in One Internet Gambling Session by Gambling Severity

Amount of Money Won

< $50$50-$100

$100-$500

> $500

Gambling***Groups

Social Gambler

98.4 0.2 0.8 0.6

At-Risk Gambler

92.1 4.3 0 3.6

Probable Pathological Gambler

77.3 5.3 4.0 13.3

1Percentage.

Most Money Lost in One Internet Gambling Session by Gender and Age

Amount of Money Lost

< $50 $50-$100 $100-$500 > $500

Gender***

Males 96.8 0.9 1.0 1.2

Females 99.5 0.3 0.2 0.1

Age

12-13 years 98.7 0 0 1.2

14-15 years 96.7 1.1 0.4 1.9

16-17 years 98.7 0.4 0.5 0.4

18-20 years 98.3 0.6 0.9 0.1

21-24 years 100.0 0 0 0

> 25 years 99.0 1.0 0 0

1Percentage.

Most Money Lost in One Internet Gambling Session by Gambling Group

Amount of Money Lost

< $50 $50-$100 $100-$500 > $500

Gambling***Groups

Social Gambler

99.0 0.6 0.5 0.1

At-Risk Gambler

95.1 0 2.9 2.1

Probable Pathological Gambler

81.3 5.3 4.0 9.3

1Percentage.

Age of Onset for Internet Gambling Without Moneyby Gambling Severity

1Percentage. Gambling Groups are based on DSM-IV and DSM-IV-MR scores.aDSM-IV score (0-2); DSM-IV-MR-J score (0-1). bDSM-IV score (3-4); DSM-IV-MR-J score (2-3). cDSM-IV score ( ≥5); DSM-IV-MR-J score (≥4). ***p<.001.

Gambling Groups1

SocialGamblera

(n = 1333)

At-RiskGamblerb

(n = 138)

ProbablePathological

Gamblerc

(n = 72)

Age***

Under 10 years 4.4 13.1 16.9

10-11 years 8.8 10.9 16.9

12-13 years 15.2 19.0 25.4

14-15 years 17.2 15.3 15.5

16-17 years 9.1 7.3 2.8

Over 18 years 2.8 0.7 2.8

Age of Onset for Internet Gambling With Moneyby Gambling Severity

Gambling Groups1

SocialGamblera

(n = 1333)

At-RiskGamblerb

(n = 138)

ProbablePathological

Gamblerc

(n = 72)

Age***

Under 10 years n = 13 0.5 3.6 1.4

10-11 years n = 8 0.5 0.7 7.2

12-13 years n = 30 1.0 7.2 5.6

14-15 years n = 52 2.6 5.8 11.1

16-17 years n = 29 1.7 2.9 4.2

Over 18 years n = 26 1.9 0.7 0

1Percentage. Gambling Groups are based on DSM-IV and DSM-IV-MR scores.aDSM-IV score (0-2); DSM-IV-MR-J score (0-1). bDSM-IV score (3-4); DSM-IV-MR-J score (2-3). cDSM-IV score ( ≥5); DSM-IV-MR-J score (≥4). ***p<.001.

Types of Internet Gambling Activities by Gambling Group

0

2

4

6

8

10

12

14

Roulette Blackjack SportsBetting

Slotmachines

Cards Maj Jong StockMarket

Games

Fre

qu

ency

%

Social Gambler

At-Risk Gambler

Probable Pathological

Follow-up study (McBride & Derevensky, 2007)

• Montreal high-school students: N = 1113

• Canadian and U.S. college and university students: N = 1273

• On-line gaming newsletter link: N = 546

Past year gambling

0

10

20

30

40

50

60

70

80

90

100

Fre

qu

en

cy

%

Male Female

High School

College/University

Internet Sample 18-24

Internet Sample 25+

Past-Year Gambling Frequencies

0

10

20

30

40

50

60

70

80

Fre

qu

en

cy

%

Never Lessthan

once amonth

Monthly Weekly

High School

College/University

Internet Sample 18-24

Internet Sample 25+

Use of “Demo/Practice” Sites

0

10

20

30

40

50

60

70

80

90

Fre

qu

en

cy %

Male Female

High School

College/University

Internet Sample

“Demo/Practice” Site Frequency

0

10

20

30

40

50

60

Fre

qu

en

cy

%

Never Less thanonce amonth

Monthly Weekly Daily

High School

College/University

Internet Sample

“Demo/Practice” Activities

0

10

20

30

40

50

60

70

80

90

Fre

qu

en

cy %

Roulette Blackjack Dice Sportsbetting

Slotmachines

Cards Maj Jong Keno

High School

College/University

Internet Sample

Gambling for Money on Internet

0

10

20

30

40

50

60

Fre

qu

en

cy

%

Male Female

High School

College/University

Internet Sample

Gambling for Money on Internet Frequency

010

2030

40

5060

70

8090

100

Fre

qu

en

cy

%

never less thanonce amonth

monthly weekly

High School

College/University

Internet Sample

Internet Sample Online Gambling Activities

0

10

20

30

40

50

60

70

80

Fre

qu

en

cy

%

Roulette Blackjack Baccarat Dice Keno Sportsbetting

HorseRacing

Slots Cards StockMarket

Gambling Severity by Sample

0

10

20

30

40

50

60

70

80

Fre

qu

en

cy

%

Non-gambler Social gambler Problem gambler

High School

College/University

Internet Sample

Internet Sample of Problem Gamblers

0

10

20

30

40

50

60

70

80

90

Fre

qu

en

cy

%

Male Female 18-24 25+

Have gambled formoney

Have used"demo/practice" sites

Reasons Youth Gamble on Internet

0

10

20

30

40

50

60

70

80

90

100

Gamediversity

High speedplay

Bonuses Competition Convenience Privacy Anonymity Don't need toleave house

Good odds Fair/reliablepayouts

24-houraccessibility

Internet sample 18-24

Reasons Youth Don’t Gamble on Internet

0

5

10

15

20

25

30

35

40

45

50

Fre

qu

en

cy

%

Need a creditcard

Worried aboutfraud

Bets might berigged

Lack ofambience

Unsure ofcollectingwinnings

Easier to hideproblems

Don't want togive personal

info

How Youth Are Paying

0

5

10

15

20

25

30

35

40

45

Fre

qu

ency

%

Personalcredit card

Family creditcard (with

permission)

Family creditcard (withoutpermission)

Debitcard/ATM

Personalcheque

Wire/banktransfer

Facts & Concerns

Internet Gambling• Provides a form of entertainment• Enhances levels of excitement and arousal• Provides an opportunity to win money• Younger generation of teens very attracted to Internet

gambling sights• Practice sights are exceedingly popular amongst

problem gamblers-age of onset is before 13• Adolescents are gambling on the net, occasionally• Over 10% of problem gamblers spent over $500 on

Internet gambling• Sites are widely advertised

Internet Gambling

• Offers free games and trial (practice) sites• Incorporates video-game technology• Reward and loyalty programs• Initial deposit bonuses• Bettor’s Insurance• Graphics add to the excitement of the game• Perceived elements of skill• Convenience and ease of access• Allows individuals to lie about their age• Allows underage youth to gamble on prohibited

activities• Reinforcement schedules are quick

Gambling for money on the Internet

• 9% of high school students have gambled for money on the Internet– 13% of males, 6% of females

• 6% of College and University students have gambled for money on the Internet– 11% of males, 3% of females

• 42% of the Internet sample have gambled for money on the Internet– 53% of males, 20% of females– 70% at least weekly

Conclusions

• Playing on Internet gambling sites without money is a common practice amongst adolescents and young adults

• At-Risk and PPGs play on Internet with and without money more often than non-gamblers and social gamblers

• Internet wagers for money increases with severity of gambling problems

• Most money won and lost increases by gambling severity

• Gambling sites permitting playing without money have been shown to– have differential payout rates

– represent breeding ground for future players

• Much Internet wagering incorporates videogame technology

• Recent studies suggest young male adults are more likely to engage in Internet gambling

….. a fourth wave of gambling

• significant expansion of Internet gambling

• greater government regulation, ownership

& taxation

• likely see new innovative harm minimizationefforts including technological advances (e.g. Techlink & biometric devices)

• more gambling problems emerging

• more research and hopefully collaborativeresearch efforts

• potential for future problems amongst youth remains high

• use of gambling blocking software may be advisable

• regulated, grey market, dark grey/black market sites

• young adults highest risk group

• we will see other forms of Internet wagering including mobile gambling, interactive t.v.

• gambling has become normalized

• sensitizing parents