Discovering the Causes of Problem Gambling: Overcoming Methodological Challenges Donald Schopflocher, PhD Associate Professor, School of Public Health,

Discovering the Causes of Problem Gambling: Overcoming Methodological Challenges

Donald Schopflocher, PhDAssociate Professor,

School of Public Health, University of Alberta

Preliminaries

• Datasets– LLLP 3 (of 4) waves, Alberta, initial N= 1808– QERI 4 (of 5) waves, SE Ontario, initial N= 4121 – ‘07-’08 CCHS cross section, Ont., Quebec, Sask. N=81427

• Analyses are exploratory – Sketch out some research questions– Examine some methods especially for

• Causal analysis• Longitudinal (panel) data

• Analyses (so far) focus upon gambling as measured by the CPGI

Focus Questions

• Are there enough Problem Gamblers to study by survey methods?

• Is Problem Gambling a category, or part of a continuum?

• What causes changes in gambling?

Focus Methods

• Latent Variable and Structural Equation Models • Fixed Effects Regression Methods• Multivariate Visualization Techniques

CCHS 2007-2008Quebec, Ontario, SaskatchewanN=81427

CPGI Problem Score

0 5 10 15 20 25

Num

ber

0.1

1

10

100

1000

10000

100000

Non Problem Gambler 40.5%Low Risk Gambler 1.7.%Moderate Risk Gambler 0.9%Problem Gambler 0.3%Not a Current Gambler 53.4%

Question 1: Are there enough Problem Gamblers to study?

CCHS 2007-2008Quebec, Ontario, SaskatchewanN=81427

CPGI Problem Score

0 5 10 15 20 25

Num

ber

0

5000

10000

15000

20000

25000

30000

35000

Non Problem Gambler 40.5%Low Risk Gambler 1.7.%Moderate Risk Gambler 0.9%Problem Gambler 0.3%Not a Current Gambler 53.4%

LLLP

QERI

Wave 1 Recruitment: CPGI categories

Loss to Followup LLLP Wave 1 to Wave 2 QERI Wave 1 to Wave 4 by CPGI Problem Score Wave 1

CPGI Problem Score

NON-PROBLEM GAM

BLER

LOW RISK GAM

BLER

MODERATE RISK GAM

BLER

PROBLEM GAM

BLER

Odd

s of

Los

s to

Fol

low

up

0.5

1.0

1.5

2.0

2.5

3.0

LLLPQERI

QERI CPGI Problem Score Trajectories

Wave

1 2 3 4

CP

GI

Sco

re

0

5

10

15

20

8

35

7

5

1312

35

2152

Question 2: Is Problem Gambling a category, or part of a continuum?

QERI Waves 1-4

QERI Waves 1-4

Further indications that gambling and problem gambling may be stable characteristics on a continuum:

• QERI Intraclass Correlations (proportion of o/a variance between individuals)– Gambling Activities 0.78– Gambling Frequency 0.76– Ln (Gambling Expenditures) 0.71– CPGI Problem Score 0.77

• QERI Autocorrelations in change scores – Lag 1 Change in Gambling Activities -0.176– Lag 1 Change in Gambling Frequency -0.254– Lag 1 Change in Ln (Gambling Expenditures) -0.279– Lag 1 Change in CPGI Problem Score -0.212

Question 3a: What causes gambling ?

• Traits

Question 3a: What causes gambling ? Mental disorders implicated?

CCHS Discriminant Function Analysis of CPGI Risk Groups

Discriminant Function 1

-0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8

Dis

crim

inan

t F

unct

ion

2

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

NGNEVER

NRG

LRGMRGPG

+

PHlthMHlth

AlC

IncEd

PHlthMHlth

SMK

ALC

GVar

DEPR

ANX

happy

stress

CCHS Discriminant Function Analysis of CPGI Risk Groups

Discriminant Function 1

-0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8

Dis

crim

inan

t F

unct

ion

2

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

NGNEVER

.

..PG

+

PHlthMHlth

AlC

IncEd

PHlthMHlth

SMK

ALC

GVar

DEPR

ANX

happy

stress

Biplot: Variables composing Canonical Variates, Axes representing High Frequency Gamblers with and without Problem Gambling status

Loadings on Canonical Variate1

-0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6

Loa

ding

s on

Ca

noni

cal V

aria

te 2

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

GambFreq

DSMProb

Smoker

single

Religiosity

Excitement

Impulsive

Antisocial

Depression

Anxiety

1st age gamb

Child Trauma

IQ

Gamb Fallacies

older

Drugs

Alcohol

OCD

male

Gamb-Friends

Gamb-ParentsGamb-Sibs

Gamb-Young

+

High Frequency Problem Gamblers

High Frequency Non Problem Gamblers

Infrequent/Non Problem Gamblers

LLLP Wave 1

Aside: Maybe Gambling behaviour and Gambling Problems are dissociated.

QERI Waves 1-4

• Note that if we accept the dissociation of gambling behaviour from gambling problems there can now be path models of this type:

Question 3b: What causes gambling ?

• What causes CHANGES to gambling behaviour &/or gambling problems ?

OR• What’s time got to do with it?

• Total model

Yit = B1TXit + B2TZi + eit

where i indexes persons

t indexes occasions

Problem:– Persons will generally be more similar to themselves than to

random others

ReviewRegression Analysis of Longitudinal Panel Data

• Between Model

Problem-Ignores change

Yi = B0B + B1BXi + B2BZi + ei

Traits related to Trait Gambling and Trait Gambling Problems

Weights

-0.25 -0.20 -0.15 -0.10 -0.05 0.00 0.05 0.10 0.15

age

male

Neuroticism

Extraversion

Agreeableness

Conscienciousness

Openness

Gambling ProblemsGambling Behaviour

+-QERI Waves 1-4

• Within Model (Fixed Effects)

yit = B0W + B1Wxit + AiDi + eit

uses Ai as a single person specific coefficient to

stand in for the effects of all variables constant over time, measured or unmeasured.

Weights for Fixed Effect Regression of CPGI Total Problems

weights

-0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Marital

Social Support

Family

Community

Stressful Events

Stress

PTSD

Depression

Mania

Anxiety

Panic Attacks

OCD

Schizophrenia

Substance Abuse

Gambling

Trait (Between)State (Within)

+-QERI Waves 1-4

Weights for Fixed Effect Regression of Gambling Behaviour

Weights

-0.10 -0.05 0.00 0.05 0.10 0.15 0.20

Marital

Social Support

Family

Community

Stressful Events

Stress

PTSD

Depression

Mania

Anxiety

Panic Attacks

OCD

Schizophrenia

Substance Abuse

- +

Trait (Between)State (Within)

QERI Waves 1-4

Coefficient

-0.04 -0.02 0.00 0.02 0.04 0.06

dropped out of school had serious conflicts or difficulties with spouse

borrowed a significant amount of money (e.g., morhad serious conflicts with neighbor(s)

suffered a significant financial losshad a significant change in work hours

had serious conflict(s) with coworkerdeveloped a serious mental illness

received serious threats or harassmenthad serious conflicts with ex-spouse

suffered a serious injury as a result of an accidhad serious conflicts with close friend(s)

had serious conflicts with family member(s)

declared bankruptcy

had a new addition to the family through birth orwas a victim of some other crime

started schoolreceived an important promotion

death of important family pet moved to new location/house

was laid offwas disciplined at work

suffered a significant loss or damage of property had a significant financial improvement

suffered a significant business loss or failuredeveloped a serious physical illness

QERI Waves 1-4

Some tentative conclusions

• ‘Gambling behaviour’ is largely a stable characteristic• ‘Having gambling problems’ is largely a stable characteristic • The two are dissociated, but related (here as elsewhere

behaviour ‘causes’ problems).• Personality traits are differentially related to gambling

behaviour and having gambling problems.• Changes in mental health and in stressful life events are

related to changes in gambling behaviour and gambling problems

• Relationships in general are quite small

• Random Effects Model (Multilevel Models)

Yit = B0R + B1RXit + B2RZi + Vi + eit

Assumes a specific distribution for V. A critical assumption is that V and E are

independent of X and Z

Appendix: An Alternative to Fixed Effect Regression