New digital technologies, computer games and gambling among youth

Dr Daniel King The University of Adelaide

Dr Daniel King (University of Adelaide) Dr Paul Delfabbro (University of Adelaide) Dr Mark Griffiths (Nottingham Trent University) Digital technologies, computer games, & gambling among youth

Outline of presentation
Definition of Internet/digital forms of gambling
Status of the Internet gambling industry
Gambling-like experiences in adolescence
Trends in technology-based gaming
Empirical research: Prevalence and usage data
Links to problem gambling
Convergence of gambling: Implications for youth
Discussion/conclusions

Definitions of Internet gambling
Very broadly, there is a need to distinguish between different forms of Internet gambling
Internet gambling: Online-only gaming activities, including casinos.
Internet-facilitated gambling : People using network technology to place bets on land-based activities (e.g., Betfair) or sign up accounts that charge up cards for use on slot-machines (e.g., in Sweden, Norway)

Definitions (continued)
It is also possible to differentiate between:
Online wagering : Racing, sports, events
Online gaming : casino games, virtual EGMs
Lottery products : keno, lottery draws

Australia’s policy environment
Interactive Gambling Act 2001
This allows online wagering (sports, race, event betting via the internet)
BUT prohibits online gaming services to be provided to Australians.
The Productivity Commission argues that Australians are spending money on overseas sites (lost revenue) + and that these sites may not have the same levels of probity and regulation as land-based gambling in Australia

Scale of Internet gambling
In 2008, it was estimated that annual Internet revenue would reach around $25billion by 2010.
In January 2008, there were over 2000 Internet gambling sites in operation. Currently, over 3000.
Estimates suggest that Australians are spending at least $700m per annum on online casino games and poker (Productivity Commission, 2010).
Poker is particularly popular due to growing TV promotion of the activity, film and TV references.

Scale (cont.)
Productivity Commission (2010)
Very large increase in the number of active player accounts
Casino : 2004 (n = 324,900) to 2008 (n = 703,300)
Poker : 2004 (n = 131,300) to 2008 (n = 363,100)
Expenditure :
Online poker: $249 million
Online casinos: $541 million

Prevalence of Internet gambling
The rates are quite low
In Canada, Williams and Wood (2009) found that only 2.1% of people gamble on the net (past 12 months)
In Australia, only 1-2% report gambling on the Internet in surveys, but the PC estimates the true rate to be 4.3% based on active player accounts (i.e., online gaming)
May be under-reported in surveys due to sampling error or a reluctance to admit to illegal activity

Prevalence vs. Active Account Data
Some studies have also looked at actual Internet gambling statistics, i.e., objective data of expenditure
LeBrie et al. (2008) formed a link with industry providers and tracked 4222 accounts over 2 years
Most people spend very small amounts (people lose only around AUS$10 per session of gambling)
Only 5% of bettors gambled regularly and lost a median of around AUS$70

Demographics
Best data from Canada (Wood & Williams, 2009)
Over 80% of internet gamblers are male
Tend to be younger
More likely to be single
Slightly higher levels of education and income
Higher rates of substance use, but lower rates of physical and mental disability

Prevalence of online gambling among youth
Byrne (2004) - Over the past year, almost one in twenty (4.6%) of the participants had gambled online with their own money. (N=2,087)
Griffiths & Wood (2007) – 8% of young people aged 12 to 15 years reported they had played a lottery game on the Internet in past year. (N=8,017)
Ipsos MORI (2009) - 1% of 11-15 year olds reported gambling on the Internet for money in the seven days prior to the survey (N=8,598)
Brunelle, Gendron et al (2009)- 8% of 14-18 year olds had gambled on the Internet in the previous 12 months. (N=1,876)
Olason et al. (2009a) - 20% of 16-18 year olds had gambled on the Internet, and just under 4% were regular Internet gamblers (N=1,513)
Olason et al. (2009b) - 24% of 13-18 year olds had gambled on the Internet, and just over 4% were regular Internet gamblers. (N=1,537)
Welte et al. (2009) - 2% of 14-21 year old respondents reported gambling online in the past year. (N=2,274)

Social responsibility and online gambling
Smeaton and Griffiths (2004) study of 30 online gambling sites:
Credit limit (90%)
Age verification (66%)
Initial age check (50%)
Instant exit (37%)
No direct access to bank account (33%)
No encouragement to keep gambling (17%)
Credit check (13%)
Link to gambling help (13%)
Self-exclusion (3%)

How is net-based gambling different? Is it riskier?
More isolated : Do not need to interact with others
Always accessible : no restrictions by hours and there are thousands of choices
Cashless: One gambles with credit or e-money so that real money is not visible during play
Anonymous: Staff cannot see who is gambling
Faster : Allows rapid bets on all forms of gambling. This reduces the differences between different forms of gambling. All become more continuous

Links with Problem gambling
PG rates have been found to be higher in Internet gambling populations
Wood, Griffiths and Parke (2007) sampled online poker players in UK and found 18% met DSM-IV criteria
Delfabbro et al. (2007) found that 10% of young ( < 18 years) pathological gamblers had tried internet gambling

Links with PG (cont.)
Wood and Williams (2009) found (in a telephone survey in Canada) that 17.1% of net gamblers had moderate to severe problems vs. 4.1% of non-internet gamblers
An online sample: 16.6% vs. 5.7% (moderate to severe problems as based on the Canadian Problem Gambling Index)
But only 11% identified the Internet as a source of their problems

Methodological Challenges
It is difficult to obtain useful prevalence figures from population surveys because of the low base-rate of the behaviour
Online surveys are likely to be over-estimates because the population are already gamblers
Online samples are more likely to be younger and male- both demographic factors are associated with higher gambling rates and a higher risk of problem gambling

Gambling via SNSs (Facebook) and mobile apps

Gambling themes/content in computer games

Structural similarities of gambling & gaming  = rare or atypical  = common Gambling machines Computer games Onscreen display of score   Sound and graphics   Audiovisual rewards   Competitive elements   Skill-based elements   Require response to predictable visual stimuli   Rapid span of play   Random elements   Scripted ‘near miss’ event   Entrapment   No endpoint  

Gambling-like experiences among youth
North American studies have reported that anywhere between 25% to 50% of teenagers have played 'free play' games via online gambling sites (Derevensky & Gupta, 2007; McBride & Derevensky, 2009; Poulin & Elliot, 2007).
Griffiths and Wood (2007) - Of the 8% who had gambled online, a quarter said they had played free instant win games (24%)
Ipsos MORI (2009) - Just over 25% of adolescents had played in ‘money- free mode’ in the week preceding the survey, with opportunities on the social networking sites four or five times more popular than those presented on real gambling sites.
Brunelle et al. (2009) report 35% of youth (49% males; 21% females) had played on the ‘free play’/’demo’ mode on gambling sites.
Byrne (2004) - More individuals under the age of 18 years than 18 to 24 years played ‘free play’ games on Internet gambling sites

OFLC ratings of gambling content in computer games

OFLC classification of gambling content
Online gambling games and applications (e.g., via SNSs) are not reviewed by the OFLC Board (reason: material considered “inherently unreviewable”)
Since 2000: Over 100 computer games with gambling content/themes reviewed by OFLC
70 games rated PG (Parental guidance), the remainder are classified ‘G’ (General audience)
However, drug use (legalised and illicit drugs) with in-game incentive carries a restricted classification rating
Computer games with high impact content (e.g., violence, sex) and gambling carry no consumer advice regarding gambling content

Research on gambling and video game play
Gupta and Derevensky (1996) study of 104 children aged 9 to 14 years
Children who regularly play video games exhibit a “false sense of confidence and security” and take greater risks and gamble larger amounts when playing a game of blackjack.
Wood, Gupta, Derevensky, and Griffiths (2004) study of 996 adolescents aged 10 to 17 years
Small but significant correlation was found between the number of hours spent playing video games and the severity of problem gambling
Delfabbro, King, Lambos, and Puglies (2009) survey of 2,669 adolescents aged 13 to 17 years
Video game playing was unlikely to be a significant risk factor for pathological gambling in adolescence

Summary: Gambling and gambling-like experiences Type of gambling Gambling activities Availability Gambling with money
Casino websites:
Poker
Blackjack
Other wagering:
Sports betting
Racing and other events
Over 3,000 online gambling sites worldwide Gambling without money
Gambling applications (“apps”):
Smartphones
Social networking sites
-‘Free play’ online casinos
iPhone apps: 400 casino, 250 poker, 30 slots, and 42 sports Facebook apps: 350 poker, 120 casino betting, 80 slot machines, and 20 sports betting Gambling-like experiences Video games with gambling themes and content Online shopping or auction sites Over 100 video games rated ‘G’ or ‘PG’ that contain gambling

Technological trends
Greater familiarity with, and use of, digital technology among youth (“digital natives”)
Growth in mobile gaming sector
Increase in technological advertising and marketing of gambling online
Greater use of behavioural tracking data
Increase in gambling via SNSs
Convergence/integration of gambling technologies (devices; networks; content)
Emergence of non-financial problem gambling
Online gambling help services

Implications of new gambling media for young people
Greater accessibility and familiarity of gambling
24hr access to gambling activities
More visible, attractive, and ubiquitous
Normalisation of the activity
More difficult to self-exclude
Involvement in gambling at earlier age
Fewer restrictions on first gambling experience
Potential for non-supervised gambling activity
Early development of gambling beliefs/strategies
Exposure to factually incorrect or misleading information

Implications (cont.)
Greater likelihood of experiencing a ‘big win’
Online sites engineer early big wins in ‘free play’ sections
Lack of financial element may create dissociation between actions and consequences
Gambling within skill-based domains like computer games
May be other rewards of non-financial gambling (e.g., social, excitement, relief of boredom)
A way of coping for youth
Gambling as an accessible escape or ‘safety’ behaviour
Characteristics of the online environment
Asocial/Anonymous
Disinhibiting

Implications (cont.)
Peer-to-peer influences
Internet enables social dynamics of gambling (approval, competition, knowledge-sharing, etc.)
Mere presence effects
Opportunity for interaction with older, experienced gamblers
Parental beliefs
Family entertainment: “Cocooning” effects
Increase parental transmission of attitudes
Lack of consumer advice
Protective factor: Earlier detection? Controlled gambling?

Summary
Prevalence of Internet gambling appears to be low but increasing
Research needed on youth gambling and new technologies:
Demographics and motivations
Psychosocial factors associated with Internet gambling
Influence of gambling-like experiences
Possible links to problem gambling
Research in the Australian context
Australian policy environment offers few protections
Convergence of gambling and digital technologies may pose unique psychological risks for young people

New digital technologies, computer games and gambling among youth

by Victorian Responsible Gambling Foundation

Accessibility

Categories

Upload Details

Usage Rights

Statistics