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Mr Paul Marden and Ms Rosa Billi Manager and Senior Project Officer, Office of Gaming and Racing Research Presentation given at: The New Game: Emerging technology and responsible gamblingThis forum was hosted by the Victorian Government's Office of Gaming and Racing on 23 May 2011, as part of Responsible Gambling Awareness Week.
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Mr Paul Marden and Ms Rosa Billi
Office of Gaming and Racing Research
Victorian Longitudinal Study-overview and early outcomes
Rosa Billi and Paul Marden
Responsible Gambling Awareness Week
Melbourne (CD/11/170804)
23 May 2011
Presentation Overview
• Public Health Approach• Background• Methodology• Wave One • Wave Two results• Waves Three and Four• Qualitative component
What is a public health approach?• Public Health approach
– prevention, intervention, treatment– goal to reduce ‘disease’, premature death, disease-produced
discomfort and disability in the population
• Epidemiology – is a branch of medical science that deals with the study of the
causes, distribution, and control of disease in populations. Biostatistics is the application of statistics to a wide range of topics in biology.
• Cohort studies (i.e. longitudinal) prospective or retrospective– describes any designated group of persons who are followed or
traced over a period of time– from Latin cohors= warriors
What is a public health approach?
• Prevalence– the number of instances of a given disease or
condition (i.e. problem gambling) in a given population at a designated time
– usually expressed as a rate (0.7%)
• Incidence – The number of instances of illness or a condition,
commencing or developing, during a given period in a specified population
– ‘new cases’– usually expressed as a rate
Background
Major aims:Explore the causal pathways to, and from, problem gamblingInvestigate the incidence of cessation or remissionExplore risks and vulnerabilities
Key hypotheses guiding research: There are 13 hypotheses that are explored in this study. Some of
the key ones are: Gamblers move in and out of gambling risk categories. Problem gambling is transitory in nature Gamblers with moderate risk CPGI scores are considered at
greater risk to graduate to problem gambling
Background
Key hypotheses guiding research: Gamblers with moderate risk CPGI scores are considered
at greater risk to graduate to problem gambling Co morbidities are clustered together and associated with
problem gambling risk Electronic Gaming Machines (EGMs) and other
continuous forms of play are more likely to result in problem gambling development than non-continuous forms of play
There are many pathways to problem gambling Most people who become problem gamblers are young
and male
Background
Four waves
Wave Timing NOne July- Oct 2008 15000
Two Sept 2009-Jan 2010 5003
Three Oct 2010- Jan 2011 5620
Qualitative March –Sept 2011
Four Oct 2011-Jan 2012
Methodology
Wave One Epidemiology Baseline
• Vic adult population 18+
• Sample of 15,000
• Computer Assisted Telephone Interviewing – CATI, landline, all waves
• Gambler - anyone who had gambled once in the past 12 months (inc lotto)
• Non-gamblers also included - health, recreation, demographics questions
• A range of screens were used (a screen is not a diagnostic test, is usually administered by an investigator or agency and is not from a patient with a complaint)– PGSI (problem gambling)
– K10 (psychological distress)
– CAGE (alcoholism and alcohol use disorder)
Methodology
• PGSI– a nine question scored index, the validated Problem Gambling
Severity Index (from the Canadian Problem Gambling Index), which has been utilised by jurisdictions in Australia since 2001.
- Non problem: (score 0) will most probably not have experienced any adversity
- Low risk gamblers: (score 1-2) are likely not to have experienced any adversity
- Moderate risk gamblers: (score 3-7) may or may not have experienced adversity
- Problem gamblers (score 8–27) have experienced adversity
Methodology
Wave One- the following were asked:
PGSI Kessler 10Self reported health RecreationGambling Readiness to Change SmokingGambling participation CAGE screen for alcohol
abuseSocial capital Community connectednessLife Events Help Seeking BehaviourSubstance use, suicide, crime DietMoney management Gambling attitudesNODS CLiP2 lifetime risk Demographics
Methodology
Wave Two CATI• Core questions
Additional contextual questions-
– Global financial crisis
– Economic Stimulus Package
– Victorian bushfires
Wave Three CATI• Core questions
Additional contextual questions-
– Spring Racing carnival
– Major sporting events
– Linked jackpots
– First big win
Methodology-Qualitative
Qualitative
In-depth, face to face interviews, one-on-one
• Pool drawn from those who have consented to face to face or in depth interviews during W3 fieldwork
• To explore risk and protective factors which contribute to the movement in and out of PG
Methodology
Maintaining Contact
• communications/media • www.gamblingstudy.com.au• refresher phone calls• refresher emails• newsletter
Findings-Wave Two
Participation in W2 based on the PGSI status in W1
PGSI Risk segment
Agreed to participation
Wave 1(n)
ParticipatedWave 2
(n)
ParticipationRate
%
Non-gamblers 1493 1024 69%
Non-problem 5029 3569 71%
Low risk 423 274 65%
Moderate risk 150 96 64%
Problem gamblers
53 40 75%
Totals 7148 5003 70%
Findings-Wave Two
• Gender of the Wave Two sample (n=5003)
males, 1996
females, 3007
Findings-Wave Two
The four most popular gambling activities for all Wave Two participants were:
• buying tickets in raffles, sweeps and other
competitions, with nearly 64 per cent of the entire 5003 study population participating in this activity at least once in the last year
• playing Lotto, Powerball and Pools (62.1 per cent)• playing electronic gaming machines (28.5 per cent)• racing (horse, harness and greyhound) (27.2 per
cent).
Findings-Wave Two
Amongst problem gamblers:• 95.6 per cent played electronic gaming machines in the
past year• nearly 78 per cent also played Lotto, Powerball and Pools.In the moderate and low risk segments the most popular
activity was:• playing Lotto, Powerball and Pools (84 per cent and 81.3
per cent respectively)In the non-problem risk segment, the most popular activity
was:• buying tickets in raffles, sweeps and other competitions
(74.9 per cent)
Findings-Wave Two
24.1 23.8
17.6
8.9
20.3
26.2
19.3
13.3
55.6
50
63
77.8
0
10
20
30
40
50
60
70
80
90
non problemgamblers
low risk gamblers moderate riskgamblers
problem gamblers
%
gamble in a group
gamble with one other
gamble alone
Gamblers within PGSI segments who gamble alone, with one other person or in groups
Findings-Wave Two
Self-reported depression and anxiety• Over a half (51 per cent) of problem
gamblers reported that they had depression whilst only 10.4 per cent of non-problem gamblers reported this condition. Similarly, nearly half (48.9 per cent) of problem gamblers reported anxiety disorders compared with 7.6 per cent of non-problem gamblers.
Findings-Wave Two
1.7 1.8 4.1
92.4
4.7 3.37.7
84.3
10.1 8.411.8
69.7
31.1
17.811.1
40
0
10
20
30
40
50
60
70
80
90
100
likely severe likely moderate likely mild likely w ell
%
non problem gamblers
low risk gamblers
moderate risk gamblers
problem gamblers
K10 psychological distress scale
Findings-Wave Two
Self-reported smoking• Participants in both waves were asked
questions regarding their smoking behaviour, as part of the health and wellbeing survey.
• Nearly 58 per cent of problem gamblers reported smoking in the past twelve months. In contrast, approximately 22 per cent of non-problem gamblers stated that they smoked in the past twelve months.
Findings-Wave Two
22.2
33.7 35.3
57.8
0
10
20
30
40
50
60
70
non problemgamblers
low riskgamblers
moderate riskgamblers
problemgamblers
%
Self reported smoking in past twelve months
Findings-Wave Two
Life Events• Problem gamblers reported higher rates of
several life events. • Nearly 43% of problem gamblers reported
the death of someone close to them. The average for all gamblers was 29%.
• Over one third of problem gamblers reported major changes to their financial situation compared to 20.2 % of non-problem gamblers
Findings-Wave Two
Social Capital• Approximately 85 per cent of gamblers
across all PGSI risk segments reported they could get help from friends and family if needed.
• similar to the Victorian adult population. The Victorian Population Health Survey 2008 - over 80 per cent of Victorian adults could get help from friends and family if needed.
Findings-Wave Two
Social capital• Less than 45 per cent of problem gamblers
reported that they could get help, if needed, from friends, family or neighbours.
• Less than 32 per cent of problem gamblers felt they were valued by society in comparison to nearly 70 per cent of all gamblers.
FindingsTransitions W1-W2
Wave Two
Completed 2009
NG NPG LR MR PGTOTALShiftedW1 to W2
NG 1024 464 526 24 9 1 560Wave One
NPG 3569 240 3131 169 24 5 438
LR 274 9 144 81 38 2 193
MR 96 3 20 26 39 8 57
PG 40 0 2 0 9 29 11
Total 5003 716 3823 300 119 45 1259
FindingsTransitions W1- W2
Stability and Change• 5.6 % of gamblers increased their risk segment
(This means they moved into the low risk, moderate risk or problem gambling categories)
• 4.3 % of gamblers decreased their risk status.
(This means they moved away from problem gambling, moderate risk or low risk categories)
* NG→NPG not included as risk (score = 0)
FindingsTransitions W1-W2
Incidence (new cases)
• 12 month incidence rate - 0.36%• Vic prevalence rate at wave one - 0.7%
Lifetime Incidence- NODS CLiP2
• 0.12% - (of 0.36%) new gamblers• 0.24% - (of 0.36%) previous history of
path/problem gambling (‘relapse’)
Trends and longitudinal studies
• You need more than one follow up (that is, wave two) to be definitive as to the factors which appear to be consistently associated with increasing or decreasing risk over time
• Trends will appear when wave three and four data are analysed.
• These trends will need to be identified using sophisticated statistical tools (not just logistic regression)
What were associated factors with wave two increasing risk?• Those who have poor general and
psychological health• Have smoked in the past year• Live in group households or one parent
families• Speak a language other than English at
home• Bet weekly on racing
BUT...we have to be careful jumping to conclusions…
• The measure for psychological distress ( Kessler 10) is associated with increasing AND decreasing risk levels between waves one and two.
• It is possible that this is a very dynamic factor in people’s lives.
• Will this be maintained in subsequent waves?
What about those who moved into problem gambling in wave two?• Strongest predictors of this movement are:
people who took up/played gaming machines and those who played keno.
• Other factors shown to be important are: poor general and psych health; those from one-parent families; people who have had a major illness or injury in past year; new marriage or other relationship partner.
What of those who moved in moderate risk category?
• Interestingly the factors that were associated with people who moved into the moderate risk category from lower risk groups were all gambling-related activities: Wagering Gaming machines Sports and events betting
If we group problem and moderate risk gamblers together ….• Between wave one and wave two,
those who moved into either category (controlling for age and gender) one variable was particularly strong .…divorce.
• Other factors associated with this increased risk were playing gaming machines, wagering and playing keno, clinical alcohol abuse
Factor associated with decreasing risk…
• No factors were found to be statistically significant for those moving out of problem gambling category. This will be explored in further analysis.
• Moving to lower risk categories from all groups (including MR and LR) is associated with death of someone close, a new partner, increasing arguments with someone close, health factors and substance abuse (smoking, alcohol)…
The End ...
• If only… more findings from the trend analysis will help us…stay tuned.
Thanks for listening,
Rosa and Paul