the road less travelled… a longitudinal studyquestion 1 the onset of high risk gambling •scoring...

The road less travelled… a longitudinal study

Rosa Billi,

Manager, Research

European Association of Gambling Studies

Helsinki, Finland, September 2014

Where is Victoria?

Victorian Gambling Study

http://www.google.com.au/url?url=http://www.whitehat.com.au/melbourne/Attractions/Trams.asp&rct=j&frm=1&q=&esrc=s&sa=U&ei=vXn6U9KJJM3d8AWf2YLgBg&ved=0CBoQ9QEwAg&sig2=5OkQwoJQKOOCu3RcTGPpxg&usg=AFQjCNH9cD99pNjj5ElnBq40msY-1ac9ew

http://www.google.com.au/url?url=http://www.smh.com.au/news/environment/koalas-may-be-extinct-in-seven-years/2007/04/11/1175971155875.html&rct=j&frm=1&q=&esrc=s&sa=U&ei=H3r6U_3JLIrt8AXGvoKwBQ&ved=0CBgQ9QEwAQ&sig2=xCIgg75mGqIXmZJT9vdo-g&usg=AFQjCNHBxo3JHiTLyX4WHIM--OTtAv1R2A

http://www.google.com.au/url?url=http://animals.nationalgeographic.com/animals/mammals/platypus/&rct=j&frm=1&q=&esrc=s&sa=U&ei=UHr6U4vDNoXf8AX0o4E4&ved=0CBYQ9QEwAA&sig2=lxzvdrv4_qHhiK00Qp3Rww&usg=AFQjCNFsMQPcLhRc4t5wksDbGxoTJItbUw

Presentation Overview

Background

Study design

Findings

Challenges

The future

Acknowledgements

The road more travelled....

•Most gambling epidemiology studies are cross sectional and/or retrospective

•Assess current participation and problems (prevalence)

•Give an indication of past participation and problems

•Provide information on distribution and potential risk/protective factors

•Additional information, e.g. help-seeking

•Frequently methodologically compromised

•Limitations - temporal sequence, causal inference, risk/protective factors for problem onset and progression

•Prevalence study 'replications' provide estimates of change over time (snapshots at population level)

Travelling the road…

A wider variety of research methods, including longitudinal studies…. would broaden our base of knowledge about gambling and problem gambling…

Abbott and Volberg (1996)

The road less travelled…moving from distribution to determinants in the study of gambling epidemiology.

Shaffer et al (2004)

The hope that this road will become ‘more’ travelled and in the process help shift the focus of gambling studies from gambling distribution to gambling determinants.

Abbott and Clarke (2007)

Early journeys along the road

Early longitudinal studies - shortcomings:

•Usually Clinical populations

•Short time spans

•Mix of 'add-ons' and stand alone studies

•Mostly small/moderate samples not representative of general population

•Various methodological problems including high attrition

•Psychological focus

Volberg (2010) el-Guebaly et. al (2008)

Prospective (longitudinal) important:

•Relatively little knowledge re people who report problems at a particular point in time (prevalence) and whether these will resolve over time- stability of condition

•Provides insights into incidence or the number of new cases that develop over time

Delfabbfro (2013)

Background

Objectives to explore:

• Risks and vulnerabilities related to changes in gambling status

• Incidence

• Movements in and out of PGSI states

Eleven hypotheses (including)

• Gamblers move in and out of PGSI states

• Problem gambling is transitory in nature

• Co morbidities are clustered together

• Chasing wins to cover losses is the biggest predictor of problem gambling

• Contextual factors contribute to problem gambling

• EGMs and other continuous forms of play are more likely to result in problem

gambling than non continuous forms of play

• Gamblers with moderately high PGSI scores are more likely to transition to

problem gambling.

Design

Cross Sectional (W1)

15,000 RDD CATI survey

70/20/10

representative of Vic population

Prospective cohort or longitudinal (W2, W3, W4)

annual follow up x 3

Qualitative component

face to face interviews (n=44)

Design

Map of Victorian Government Regional Boundaries 2008

Wave One July 2008 - October 2008

Wave Two September 2009 - January 2010

Wave Three September 2010 - January 2011

Qualitative May 2011 - August 2011

Wave Four October 2011 - January 2012

Data collection periods

Sample

•Gambling participation in 12 activities:

– informal private betting; electronic gaming machines (EGMs); table games (e.g,

blackjack, roulette, poker); horse or harness racing or greyhounds; sports and event results; Lotto, Powerball or the Pools; Keno; scratch tickets; bingo; telephone or SMS competitions; raffles, sweeps and other competitions; and speculative stock investments.

•Gambling behaviour using the Problem Gambling Screening Index (PGSI):

– Nine-item index with scores from 0 to 27

– Non-gambler, non-problem gambler (PGSI=0), low-risk gambler (PGSI=1-2), moderate-risk gambler (PGSI=3-7), problem gambler (PGSI=8-27)

•Lifetime risk of gambling using NORC DSM-IV Screen for Gambling Problems – Control, Lying and Preoccupation (NODS-CLiP2) scale:

– Lifetime non-problem gambler (NODS=0); lifetime at-risk gambler (NODS=1,2);

lifetime problem gambler (NODS=3-4); lifetime pathological gambler (NODS≥5)

Gambling participation questions

PGSI and NODS CLiP2

PGSI

•Measures past year risk

•Non gambler 0

•Non problem gambler 0

•Low risk gambler 1-2

•Moderate risk gambler 3-7

•Problem gambler 8+

NODS CLiP2 •Measures lifetime risk

•Lifetime non problem 0

•Lifetime at risk1-2

•Lifetime problem gambler 3-4

•Lifetime pathological gambler 5+

Health and wellbeing questions

Core non-gambling questions W1 W2 W3 W4

•Health, K10, readiness to change, life events, recreation, smoking CAGE etc

Additional contextual questions for specific waves

•Global Financial Crises (W2)

•Economic Stimulus Package (W2)

•Vic Bushfires (W2)

•Linked Jackpots (W3)

•Major sporting events (W3)

•Additional social capital (W4)

•Trauma and hardship (W1 and W4)

•Loneliness (W4)

Some findings

Prevalence (total stock)

Vic prevalence rate from wave one - 0.7%

Incidence (new cases)

12 month incidence rate

0.36% (95% CI 0.21% - 0.57%)

NODS CLiP2

0.12% (CI – 0.03% - 0.25%) - (of 0.36%) new problem gamblers

0.24% (CI 0.13% - 0.41%) - (of 0.36%) previous history of path/problem gambling ‘relapse’

Co-morbidities

Co-morbidity:

•a condition (or disorder) existing simultaneously but independently with another condition in a person, or

•a condition (or disorder) in a person that causes, is caused by, or is otherwise related to another condition in the same person.

Valderas et al. (2009)

Shaffer and Korn (2002) believe that the complex relationships between co-morbid disorders include the possibilities that:

– both disorders are independent of each other

– one disorder protects against the other

– one disorder causes the other

– both disorders share the same cause or are components of a more complex set of symptoms

Co-morbidities

Co-morbidities (from various cross sectional studies) and problem gamblers:

•Depression: 37-71%

•Anxiety disorders: 41-60%

•Severe psychological distress: 25-30%

•Personality disorders: 61% (US)

•Nicotine dependence: 47-64%

•Alcohol abuse & dependence: 48-72%

•Drug dependence: 38% (US)

•Suicide ideation: 9-27%

•In Victoria more likely to report poor health, lung conditions, obesity and a disability affecting everyday life (wave one).

Kessler et al. (2008) Petry et al. (2005) Productivity Commission (1999) Thomas & Jackson (2008) Dept of Justice (2009)

Co-morbidities

conditions

0%

10%

20%

30%

40%

50%

60%

70%

current

smokers

sign of

alcohol abuse

obesity anxiety depression troubles w ith

w ork

increased

arguments

w ith

someone

close

unable to get

help w hen

needed

non-problem gamblers low risk gamblers moderate risk gamblers problem gamblers

Source: Victorian Gambling Study, 2008 (Sample =15,000, w eighted)

Co-morbidities

number of co-occurring conditions

0%

10%

20%

30%

40%

50%

60%

70%

0 1 2 3 4 >=5

non-problem gamblers low risk gamblers moderate risk gamblers problem gamblers

Source: Victorian Gambling Study, 2008 (Sample =15,000, w eighted)

Co-morbidities

Yeah I’ve been, I’ve had mental problems since I was little, for social phobia and growing up I was anorexic for ten years, so I didn’t go to school, I was hospitalised my whole teenage adolescence and the children’s but yeah, it was just always depression, obsessive compulsive disorder and ahm, borderline personality disorder, so….

female—qualitative study, Victorian Gambling Study,

I had the accident, I feel like, I can’t do a lot and just you know you get a bit depressed, do you know what I mean?

male—qualitative study, Victorian Gambling Study

But that’s what happens. You get depressed, you go and blow your money and then you’re depressed because you’ve blown your money. So work that out.

male—qualitative study, Victorian Gambling Study

Psychological distress

Alcohol abuse

Life event triggers

Co-morbidities

Chicken or egg?

Little research that clarifies how the onset of problem gambling relates temporally to the onset of other disorders.

Question 1 • The relationship between onset (new cases) of high risk

(MR/PG) gambling behaviour and co morbidities

Question 2 • The relationship between onset (new cases) of co morbidities

and high risk (MR/PG) gambling behaviour

Co-morbidities

The onset of co-morbidities

Question 2

The significant variables were:

• being male (OR=2.0, CI 1.3-3.0, p=0.002)

• age (OR= 1.02, CI 1.00-1.03, p=0.008)

• disability (OR=2.1, CI 1.9-4.0, p=0.028), and

• PGSI problem gambling risk category (OR=4.2, CI 0.9-18.9, p= 0.061).

Co-morbidities

Question 1

The onset of high risk gambling

•Scoring as an ‘at-risk lifetime gambler’ (NODS CLiP2) was significantly associated with new onset of high risk gambling behaviour during the study period (OR=6.3, p=0.007, CI 1.7-23.9).

•Any health condition (OR=2.7, p=0.027, CI 1.1-6.7)

•Current smoker (OR=2.7, p=0.035, CI 1.1-6.8)

Further analysis on any health condition…

•Participants with anxiety were x 4 more likely to develop MRPG (OR=4.0 p=0.036, CI 1.1-14.6) [adjusted for NODS and smoking]

Transitions

PGSI Risk Group Transitions

Wave Four risk groups from Waves One, Two and Three

For example, problem gamblers and their risk group in previous waves

0

10

20

30

40

50

60

70

80

90

100

2008 2009 2010 2011 2008 2009 2010 2011 2008 2009 2010 2011 2008 2009 2010 2011

ZR LRG MRG PG

Zero risk Low Risk Gamblers Moderate Risk Gamblers Problem Gamblers



Wave One risk groups thro Waves Two, Three and Four

For example, problem gamblers and their risk group in subsequent waves

Transitions

•MR greatest probability of transitioning to PG - 11%

•Most PG are likely to remain PG, regardless of gender - 71%

•19% of PG likely to decrease to MR, and

•Probability that PG will cease gambling is close to zero - <1%.

Markov chain to predict the probabilities of transitioning in and out of gambling risk states.

Lifetime gambling risk compared to

PGSI category across the four waves

Frequency of EGM use

W1 to W3

Person time

Wave One July 2008 - October 2008 What is person years?

The time at risk for all persons in a population

Each year a participant contributes to a study

= one person year

In our study 3686 participants completed all four waves

= 14,744 person years

Person time

Wave One July 2008 - October 2008 Most problem gamblers (71%) were likely to remain problem gamblers from one year to the next Approximately 22% of problem gamblers were likely to decrease to moderate risk The probability that problem gamblers were likely to cease gambling was close to zero (0.1%) Moderate risk (9%) had the greatest probability of becoming problem gamblers Non gamblers or non problem gamblers had a very low probability of becoming problem gamblers (0.1%)

Stability probability

CPGSI Category Overall Stability

n % %

NG 2,148 14.57 48.86%

NPG 11,225 76.13 82.51%

LR 896 6.08 35.67%

MR 345 2.34 43.34%

PG 130 0.88 59.09%

Total 14,744 100

Challenges and learnings

•Ambitious project

•Multi supplier model (international, national)

•(Baseline + additional) funding

•Time - lack thereof (govt dept)

•Analysis, analysis, analysis (for example, response rate with priorities)

•Definitional changes

•Measurement (PGSI anchors, definitional changes etc)

Challenges and learnings

•Attrition (endeavour to counteract)

•Awareness of mortality (loss of research staff)

•Collaboration- international

•‘doh’ moments - what should have been asked

•Familiarity

•Spreading the word

•Replication

Where to from here?

Short cohort follow up survey in 2015-2016? (another world first) - report changes over 7-8 years?

Short, sharp three-monthly follow up of participants to see short term transitions?

Examine remaining hypotheses

Secondary analyses currently underway

Use findings for targeted prevention (e.g. MR to PG)

Collaboration with Sweden & New Zealand & USA (article in press) & data pooling

Fact sheets underway

Peer reviewed articles (methods paper submitted)

Delivery of findings via presentations

(Caution: findings need to be confirmed via other studies)

Research team

• Max Abbott

• Rosa Billi

• Sarah Hare

• Damien Jolley

• Penny Marshall

• Paul Marden

• Jan McMillen

• Elmer Villanueva

• Rachel Volberg

• Christine Stone

We would like to acknowledge and

remember Damien Jolley

http://www.google.com/url?url=http://cva.stanford.edu/people/davidbbs/photos/nature/slides/IMG_2624%2520beatufiul%2520white%2520flower%2520pretty%2520dark%2520green%2520background%2520good.html&rct=j&frm=1&q=&esrc=s&sa=U&ei=70DfU5r4FNTo8AXR64LQAw&ved=0CBYQ9QEwAA&usg=AFQjCNH3zvWtRdHHC7xWPZbNEvWUZP1r5g

the road less travelled… a longitudinal studyquestion 1 the onset of high risk gambling •scoring...

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