Transcript Currie_Shawn_AGRI_Conference_2010.ppt

Canadian LowRisk Gambling Limits: New
Evidence and Limitations
Shawn R. Currie, Ph.D.
April 10, 2010
Gambling in Canada
Legal in all provinces
76% of Canadians have gambled in the last year (Cox et al., 2005)
Gambling venues and opportunities include:

87,000 electronic gaming machines (VLTs and slots)

33,000 lottery outlets

250 race tracks

60 permanent casinos

25,000 licenses to run temporary bingos, casinos, raffles
Large and growing unregulated gambling market in

Internet gambling

Private poker halls
What is Responsible Drinking?
Responsible
drinking is
Abstain
•
•
•
•
No more than 2 drinks
per day
1 non-drinking day per
week
Drink slowly, avoid
intoxication, wait an
hour between drinks
Alcohol
abuse
Don’t drink if driving,
operating equipment,
pregnant, others.
Consumption
Alcohol
dependence
What is Responsible Gambling?
No
gambling
Don’t gamble alone, for
money for basic needs,
with borrowed money,
chase loses, when
drinking.
Problem
gambling
Responsible gambling?
- Frequency?
- Amount?
- Time spent?
Level of participation/gambling intensity
Pathological
gambling
Source: Alberta Gambling Prevalence
Study (2002)
70
60
50
40
30
20
10
0
0.4
0.6
1
1.5
3
20
Average daily alcohol consumption and risk of all-cause mortality
1.5
Source: Babor et al. (2003)
1.4
1.3
Males 45 and over
1.2
1.1
1
0.9
0.8
g
11
0g
>
g
-1
10
70
-7
0
g
41
-4
0
g
31
-3
0
g
21
-2
0
11
0
-1
0g
0.7
in
er
s
0.2
Relative Risk
0.01 0.05 0.1
Ab
sta
Percent reporting two or more harms
Percent monthly income spent on gambling activities and harm
Using National Population
Health Data to Develop
Responsible Gambling Limits
Consequences of Gambling
(assessed by Canadian Problem Gambling Index)
Betting more than can afford to lose.
Gambling caused health problems, including stress/anxiety.
Gambling caused financial problems.
Borrowed money or sold anything to gamble.
Gambling caused interpersonal problems.
Others criticized your gambling.
Felt guilty about gambling.
Felt you might have a gambling problem.
Harms = Reporting 2 or more negative consequences.
CCHS-1.2
Dollars spent per year
Males
Females
Total
Proportion reporting two or more harms
40
30
20
10
0
0
-$
50
$5
1
-1
00
$1
01
-2
$2
51
50
-5
$5
01
00
>$
-1
00
0
10
0
0
N
Males
2472
1841
2101
1342
745
435
Females
3679
2153
1970
994
476
272
Total
6151
3994
4071
2336
1221
707
CCHS-1.2
Frequency by type of gambling
Percent reporting two or more harms
80
70
60
50
40
30
20
10
0
1-
5
tim
6es
/y
EGM in
ea
r
EGM out
11
tim
Ab
o
es
/ye
ar
Lottery
ut
2on
ce
/
m
on
t
3
tim
Ab
o
es
/m
on
h
Bingo
ut
th
Casino
2on
c
e/
we
e
k
6
tim
es
Da
ily
/w
ee
k
Instant win tickets
Comparison of CCHS-1.2 with AB, BC,
and ON data
Alberta
BC
1-5 times/year
Ontario
CCHS
6-11 times/year
About once/month
2-3 times/month
About once/week
2-6 times/week
Daily
0
10
20
30
40
Percent reporting two or more harms +/- 95% CI limit
Performance of optimal cut-points across surveys
AB
ONT
BC
CCHS-1.2
.77
.67
.63
.81
2 - 3X / month
2 - 3X / month
3 -5X / month
2 - 3X / month
92 / 57
61 / 67
65 / 57
88.3 / 59
.89
.75
.74
.81
$80 / month
$400 / year
$11 - $50 /month
$501-$1000 /
year
82 / 84
61 / 82
73 / 67
78 / 70
AUC
.91
.80
NA
.79
Optimal cut-off
3%
1%
1%
78 / 89
76 / 66
74 / 74
Frequency
AUC
Optimal cut-off
Sensitivity/specificity
Dollars spent
AUC
Optimal cut-off
Sensitivity/specificity
Percent gross income
Sensitivity/specificity
AUC = area under ROC curve, Swets (1988) guidelines
0.5 – 0.7 = ‘low accuracy’
0.7 – 0.9 = ‘moderate accuracy’
> 0.9 = ‘high accuracy’
Soliciting Expert Opinion
Survey Goals:
(1)
(2)
Obtain opinions from 171 gambling experts
(researchers, clinicians, policy makers) on the
need for low-risk limits
Assess the face validity of CCHS-1.2 derived
limits
Face Validity of Proposed Limits
Proportion of responses
25
20
15
10
5
0
Very
2
conservative
3
4 Just right 6
Frequency: 2-3 times/month
7
8
9 Very liberal
Dollars spent: $500 - $1000CAN/year
Percent income: 1% gross income
Source: Currie, S. R., Hodgins, D. C., Wang, J. el-Guebaly, N., & Wynne, H. (2008). In pursuit of empirically
derived low-risk gambling limits. International Gambling Studies, 8, 207-227.
Limitations of the Method
Insufficient data to develop game-specific lowrisk limits
Reliability of gambler’s self-reported expenditure
in phone surveys is questionable
Lack of agreement on definition of harm in
context of gambling
Retrospective accounts of gambling harm and
expenditure
Analysis of Low-Risk Gambling Limits in the
Leisure, Lifestyle, Lifecycle Project
Investigators:
Nady el-Guebaly, MD
David Hodgins, PhD
Garry Smith, PhD
Rob Williams, PhD
Don Schopflocher, PhD
Rob Wood, PhD
Method
Starting in 2006, longitudinal cohort study of over 1800 adolescents and adults living
in rural and urban Alberta
Individuals in five age cohorts range from 13 to 65 years being followed for five years
The sample includes persons randomly selected from the general population and
persons considered at-risk for problem gambling based on certain criteria.
Data collection every 14 months.
Leisure, Lifestyle, Lifecycle Project: Demographics at
Time 1
Variable
Total Adult Completes (N=1372)
N
%
315
341
403
313
23.0
24.9
29.4
22.8
Gender Male
Female
602
770
43.9
56.1
Location Calgary
Edmonton
Grande Prairie
Lethbridge
577
405
170
220
42.1
29.5
12.4
16.0
Age
18-20
23-25
43-45
63-65
Leisure, Lifestyle, Lifecycle Project: Description of
Longitudinal Sample (N=809)
Inclusion criteria:
• Adults (>17 years)
• Participated in Time 1 and 2
Exclusion criteria:
• No gambling at Time 1 and 2
Variable
N
% (weighted)
146
182
283
198
26
27
32
15
Gender Male
Female
348
461
50
50
Employ PT or FT
Unemployed
587
222
75
25
Smokers
Good-excellent physical health
Good-Excellent mental health
185
638
737
19
78
91
Age
Health
18-20
23-25
43-45
63-65
Gambling above the Risk Limits at
Time 1 & Time 2 (~18 months)
Time 1
Time 2
Low risk
gambling
limit
N
%
(weighted)
N
%
(weighted)
> 1% income
137
12%
237
23%
140.71*
> $500/year
87
7.5%
193
18%
74.94*
> 2-3
times/month
168
17%
226
21%
88.65*
Any risk
factor
237
23%
368
36%
136.04*
* p < .0001
Chisquare
Gambling above the Risk Limits at
Time 1 & Time 2
Time 1
Time 2
40
35
Percentage
30
25
20
15
10
5
0
> 1% income
> $500/year
> 2-3 times/month
Any low-risk limit
Cross-Sectional Data Time 1
Low risk
gambling
limit
Weighted proportion
gambling over limit
who report harm
Weighted proportion
gambling under limit
who report harm
Odds
ratio
Chi-square
(weighted)
> 1% income
31%
6%
7.3
65.09*
> $500/year
43%
6%
11.7
94.71*
> 2-3
times/month
29%
4%
8.6
85.77*
* p < .0001
Change in Risk Category between
Time 1 & Time 2
N = 809 Gamblers
n = 400
Low risk at
T1 & T2
(59%)
n = 175
Low risk (T1) to
High risk (T2)
(19%)
n = 50
High risk (T1) to
Low risk (T2)
(6%)
Low risk = gambling below all risk limits
High risk = exceeds at least one low risk limit
n = 184
High risk at
T1 & T2
(16%)
Game preferences at Time 1 & Time 2
(all gamblers)
Time 1
Time 2
60
Percentage
50
40
30
20
10
0
VLTs or Slots
Casino games
Raffle
Instant win
Bingo
Game preferences at Time 1 & Time 2
(gamblers shifting from low risk to high risk)
Time 1
Time 2
p < .01
80
70
p < .0001
60
Percentage
p < .0001
50
40
p < .001
30
20
10
0
VLTs or Slots
Casino games
Raffle
Instant win
Game preferences at Time 2
(gamblers who were low risk at Time 1)
Below all low-risk limits at Time 2
Exceeds at least one low-risk limit at Time 2
p < .05
80
70
p < .001
60
Percentage
p < .0001
50
40
p = NS
30
20
10
0
VLTs or Slots
Casino games
Raffle
Instant win
Gamblers who shift from low risk to high risk
on frequency of gambling
Time 2
Χ2 = 3.21, p = .07
Harm
Time 1
Low risk
High Risk
N = 22 (17%)
> 2-3 times/mo
N= 129
No harm
(23%)
N = 107 (83%)
< 2-3 times/mo
N= 637
(83%)
Harm
Low Risk
N = 55 (9%)
< 2-3 times/mo
N= 507
No harm
(77%)
N = 452 (90%)
Gamblers who shift from low risk to high risk
on percent of income
Time 2
Χ2 = 22.15, p < .0001
Harm
Time 1
Low risk
High Risk
N = 31 (23%)
> 1% income
N= 136
No harm
(37%)
N = 105 (77%)
< 1% income
N= 635
Harm
Low Risk
N = 42 (8%)
< 1% income
N=499
No harm
(63%)
N = 457 (92%)
Gamblers who shift from low risk to high risk
on dollars spent
Time 2
Χ2 = 13.53, p < .001
Harm
Time 1
Low risk
High Risk
N = 31 (22%)
> $500/yr
N= 137
No harm
(15%)
N = 106 (78%)
< $500/yr
N = 722
Harm
Low Risk
N = 59 (9%)
< $500/yr
N=585
No harm
(85%)
N = 526 (91%)
Gamblers who shift from low risk to high risk
on any low risk limit
Time 2
Χ2 = 12.52, p < .001
Harm
Time 1
Low risk
High Risk
N = 31 (18%)
on at least one limit
N= 175
No harm
(25%)
N = 144 (82%)
on all limits
N = 549
Harm
Low risk
N = 26 (7%)
on all limits
N=374
No harm
(75%)
N = 348 (93%)
Impact of Changing Risk Category on DSM
Symptoms of Pathological Gambling
CIDI-Gambling Time 2
(Mean symptom count)
T-value
Signif
1.51
4.81 **
<.0001
.09
1.31 *
NS
Harm
No harm
Differ
Low risk to high
risk (n = 175)
1.65 (0.43)
0.13 (0.05)
Low risk to low
risk (n = 374)
0.19 (0.19)
0.07 (0.03)
Change from
Time 1 to 2
Gamblers who shift from high risk to low risk
on any low risk limit
Time 2
Χ2 = 3.41, p = 0.16
Harm
Time 1
High risk
High Risk
N =59 (31%)
on at least one limit
N= 184
No harm
(73%)
N = 125 (69%)
on at least one limit
N = 234
Harm
Low risk
N = 10 (19%)
on all limits
N=50
No harm
(28%)
N = 40 (81%)
Conclusions
Cross-sectional data:
The risk curve method appears to be valid for identifying low risk
gambling limits
Limitations of current population data dictate that disseminating
actual limits to public would be premature at this point
Longitudinal data:
Large number of people shift to higher risk gambling and begin to
experience more harm
Change from low-risk to high risk gambling based on exceeding the
quantitative
limits
is associated with:
- increased
harm
-
preference for higher risk forms of gambling (EGMs, casino gambling,
instant win tickets)
-
more symptoms of pathological gambling.