FLAGS - European Association for the Study of Gambling

FLAGS (EGM)Preliminary Results of Phase IV:development of the FocaL AdultGambling ScreenTony Schellinck, Focal Research and Dalhousie UniversityTracy Schrans, President of Focal ResearchMichael Bliemel , Dalhousie UniversityHeather Schellinck, Dalhousie University8th European Conference on Gambling Studies and Policy Issues Sept 2010Research funded by Ontario Problem Gambling Research Centre – still under review© Focal Research1

Our VisionFLAGS (EGM) is the next generation ofmeasurement for adult gambling risk andharm specifically designed for public healthsurveillance. FLAGS moves beyondtraditional identification of problemgambling prevalence providing informationfor use in informing, monitoring andevaluating gambling related prevention,harm reduction, social policy and publichealth policy for youth.© Focal Research2

Our Purpose: Public Health Surveillance• According to the World Health Organization (WHO) Public HealthSurveillance is “the ongoing, systematic collection, analysis andinterpretation of health-related data essential to the planning,implementation, and evaluation of public health practice”• The primary goals of surveillance as defined by WHO are:– To serve as an early warning system - measure risk– Guide public health policy and strategies – Provide actionableinformation– Document the impact of an intervention or progress towards specifiedpublic health targets/goals – Be highly accurate and consistent– Understand and monitor the epidemiology of a condition in order to setpriorities and guide public health policy and strategies – be causallyrelated and detailed enough for policy development© Focal Research• http://www.who.int/immunization_monitoring/burden/routine_surveillance/en/index.html3

Why is FLAGS (EGM) needed?• Current screens are probably reasonably accurate in identifyingadults who are suffering more severely from the effects ofgambling. However, these instruments were not designed toidentify gamblers who may be at different risk levels or to providedetailed information to the decision maker. Moreover, the goal is touse surveillance to inform, monitor and evaluate it is equallyimportant to know ‘why’ a person is at risk especially if the goal isto help them.• FLAGS is designed to do just that. FLAGS also more accuratelyassigns adults to a problem gambling category as it has a largerinventory of consequences than other screens as well as a measureof persistence that helps to overcome the transient nature of adultbehaviour and properly define a problem gambler.• Because all of the constructs are multi-item measures that arereliable and valid, the FLAGS instrument allows for accuratecomparisons among jurisdictions of the prevalence of problemgambling and perhaps more importantly the extent to which theexisting adult populations are at risk of developing problemgambling.© Focal Research4

What is the FocaL Adult GamblingScreen (FLAGS)?• FLAGS (EGM) is a new survey instrument designed togather adult EGM gambling information in order to informsocial and public health policy.• ≈ 58 statements• Ten Constructs that provide indications of risk or problemgambling• A scoring system that allots people to one of five categoriesbased their being flagged on a combination of indicators• A reporting system - set of predesigned analyses that willprovide information necessary for decision makers– Validity and reliability checks of the constructs and theirrelationships in the setting it was administered– The prevalence and profiles of the each risk category© Focal Research5

FLAGS Five Levels of Player Risk for Machine GamblingRisk Level Label DescriptionLevel V Problem Gambler A Problem Gambler is a person who flagged as exhibiting bothNegative Consequences and Persistence.Level IVLevel IIILevel IIAdvanced RiskIntermediate RiskEarly RiskThose at Advanced Risk are not flagged as a problem gamblerbut have one or more indications on the five constructsranked highest in the hierarchy score: Impaired Control:Begin, Preoccupation: Obsessed, Risky Practices: Later,Negative Consequences and Persistence.Those at Intermediate Risk are not Problem or Advanced Riskgamblers, but have been flagged on one or more of theintermediate risk constructs: Impaired Control: Continue andRisky Practices: Earlier.Those at Early Risk have flagged on at least one of RiskyCognitions: Beliefs, Risky Cognitions: Motives orPreoccupation: Desire.Level I No RiskThose at No Risk do not flag on any of the risk indicatorsalthough it is possible that they answered yes to one or morestatements making up some of the constructs.Level 0 Non-gambler A Non-Gambler by definition is at no-risk because they are© Focal Researchnot involved in the activity over the last year.6

How was the FLAGS developed andtested?Built on earlier work, 1998 NS VLT study, 2000 Follow-up study, SAPGSdevelopment for the Victoria Gambling Research Panel (2004) and thequantitative testing phase for the Victoria Department of Justice (2006).Phase I – literature review of method bias in measures– funded by OPGRCPhase II – Literature review of Formative versus Reflective constructs – fundedby OPGRCPhase III – qualitative and preliminary quantitative research on 190 statementsand constructs that were eventually rejected (e.g., superstitions) with 63casino gamblers in Ontario – 2008 – funded by OPGRCPhase IV 2009 - 10 quantitative analysis of responses to 132 statements toformulate FLAGS (EGM) beta – 384 Ontario Casino Gamblers – Funded byOPGRCPhase V 2010 - Further quantitative refinement of instrument and testing onVLT gamblers – 500 VLT gamblers – funded by Nova Scotia GamblingFoundation – report due End of September 2010© Focal Research7

Preoccupation:DesireReflectiveImpairedControl:ContinueReflectiveFormative and ReflectiveConstructs: FLAGSImpairedControl: BeginReflectiveNegativeConsequencesFormativeRisky Practices:EarlierFormativeRisky Practices:LaterFormativeRiskyCognitions:MotivesFormativeRiskyCognitions:BeliefsFormativePreoccupation:ObsessionReflective© Focal ResearchPersistenceReflective8

Preoccupation:Desire0.1500.63817.20ImpairedControl:Continue0.4070.4848.14PLS Model of FLAGSCoefficients, t scores andconstruct variance explained0.3887.400.2053.920.55811.20Risky Practices:Earlier0.638ImpairedControl: Begin0.4230.2863.970.2914.180.3794.86Risky Practices:Later0.6190.4946.56NegativeConsequences0.633RiskyCognitions:Motives0.2430.4937.70RiskyCognitions:Beliefs0.0000.4526.520.1562.640.2624.620.2512.920.2383.44Preoccupation:Obsession0.364© Focal Research0.1973.760.2113.200.5699.21Persistence0.7189

Early RiskConstructsPreoccupation:DesireReflectiveImpairedControl:ContinueReflectiveIntermediateRiskConstructsRisk CategoryAssignment: FLAGSAdvanced Risk ConstructsImpairedControl: BeginReflectiveProblemGamblerNegativeConsequencesFormativeRisky Practices:EarlierFormativeRisky Practices:LaterFormativeRiskyCognitions:MotivesFormativeRiskyCognitions:BeliefsFormativePreoccupation:ObsessionReflective© Focal ResearchPersistenceReflective10

Median Hierarchy ranking of ConstructsMeasure developed based on Toce-Gerstein, et al. (2003)MedianHierarchyConstructsRankingRisky Cognitions: Beliefs 20Preoccupation: Desire 28Risky Practices: Earlier 45.5Impaired Control: Continue 59Risky Cognitions: Motives (Moneyand Depression)63.5Preoccupation: Obsessed 85Impaired Control: Begin 104Risky Practices: Later 103Persistence 103.5Negative Consequences 114© Focal ResearchEarly Risk ConstructsIntermediate RiskConstructsAdvanced RiskConstructsProblem GamblerConstructs11

Risk Profile by Risk CategoryConstructs All Gamblers No RiskEarlyRiskIntermediateRiskAdvancedRiskProblemGamblerPersistence 11.0% 0.0% 0.0% 0.0% 33.3% 100%Negative Consequences 9.9% 0.0% 0.0% 0.0% 22.2% 100%Preoccupation: Obsession 3.7% 0.0% 0.0% 0.0% 14.3% 41.4%Impaired Control: Begin 8.6% 0.0% 0.0% 0.0% 36.1% 65.5%Risky Practices: Later 12.8% 0.0% 0.0%% 0.0% 66.7% 82.8%Impaired Control:Continue23.5% 0.0% 0.0% 77.3% 69.4% 100.0%Risky Practices: Earlier 17.9% 0.0% 0.0% 47.7% 55.6% 89.7%Risky Cognitions: Motives 17.1% 0.0% 43.6% 20.5% 38.9% 82.8%Preoccupation: Desire 18.4% 0.0% 28.2% 45.5% 55.6% 62.1%Risky Cognitions: Beliefs 8.8% 0.0% 35.9% 4.5% 22.2% 31.0%© Focal Research12

Risk Profile by Risk CategoryConstructs All Gamblers No RiskEarlyRiskIntermediateRiskAdvancedRiskProblemGamblerPersistence 11.0% 0.0% 0.0% 0.0% 33.3% 100%Negative Consequences 9.9% 0.0% 0.0% 0.0% 22.2% 100%Preoccupation: Obsession 3.7% 0.0% 0.0% 0.0% 14.3% 41.4%Impaired Control: Begin 8.6% 0.0% 0.0% 0.0% 36.1% 65.5%Risky Practices: Later 12.8% 0.0% 0.0%% 0.0% 66.7% 82.8%Impaired Control:Continue23.5% 0.0% 0.0% 77.3% 69.4% 100.0%Risky Practices: Earlier 17.9% 0.0% 0.0% 47.7% 55.6% 89.7%Risky Cognitions: Motives 17.1% 0.0% 43.6% 20.5% 38.9% 82.8%Preoccupation: Desire 18.4% 0.0% 28.2% 45.5% 55.6% 62.1%Risky Cognitions: Beliefs 8.8% 0.0% 35.9% 4.5% 22.2% 31.0%© Focal Research13

PGSI CategoriesComparison to PGSIFLAGS CategoriesNo RiskEarlyRiskInter-mediateRiskAdvancedRiskProblemGamblerTotalNo Risk 47.1% 6.4% 0.8% 0.5% 0.0% 54.8%Low Risk 11.2% 2.4% 4.3% 1.1% 0.3% 19.3%MediumRisk2.1% 1.6% 6.7% 7.2% 2.7% 20.3%ProblemGambler0.0% 0.0% 0.0% 0.8% 4.8% 5.6%Total 60.4% 10.4% 11.8% 9.6% 7.8% 100.0%Overall the FLAGS categories correlation with the PGSI categories (Spearman=0.730).Risk category only correlation is 0.644 (n= 345).If it is assumed that the FLAGS Intermediate and Advanced Risk segments areroughly equivalent to the PGSI Moderate Risk there was 68.2% agreement .For those classified at some level of risk (excluding Problem Gambler) by eitherinstrument the two instruments agreed on only 39.9% of the cases .14

What are the next steps? FLAGS• Focal has completed a survey of 500 regularVLT gamblers in Nova Scotia for the NovaScotia Gambling Foundation. These data haveprovided further testing of the FLAGSinstruments on a different population and adifferent form of EGM gambling.• The general report should be released by theend of this month.• A detailed report focus on FLAGS will follow.© Focal Research15

Cut-Offs Chosen for IndicatorsBased on ROC AnalysisConstructNumber ofStatementsCut-OffChosenNumberStatementsTestedFLAGS IIPersistence 4 2 4Negative Consequences 14 3 14Preoccupation: Obsession 2 2 5Impaired Control: Begin 3 2 4Risky Practices: Later 6 2 7Risky Practices: Earlier 6 3 6Impaired Control: Continue 5 3 5Preoccupation: Desire 4 3 4Risky Cognitions: Motives 4 2 4Risky Cognitions: Beliefs 5 3 6Total 53 59© Focal Research16

Impaired Control BeginComp. 2LoadingFrequencyHier.RankCorrwithPGSIImpaired Control ContinueComp. 1LoadingFrequencyHier.RankCorrwithPGSIConstruct and StatementsI often spend more money gambling than I intended.Even when I intend to spend a few dollars gambling,I often end up spending much more.I sometimes gamble with money that I can’t reallyafford to lose.Once I have started gambling on the slots I find itvery hard to stop.I often spend more time gambling than I intend to.0.86 24.3% 62 0.630.85 25.9% 55 0.630.78 21.4% 65 0.70.74 24.1% 59 0.64.71 24.1% 56 0.60Construct and StatementsI have tried to cut back on my slots play with littlesuccess.I have tried unsuccessfully to stop or reduce mygambling on the slots.There have been times I have gambled despite mydesire not to.© Focal Research0.87 9.1% 104 0.680.85 8.0% 109 0.620.74 15.0% 76 0.6117

PreoccupationDesirePreoccupation:ObsessedImpaired Control:ContinueImpaired Control:BeginPersistenceRisky Cognitions:BeliefsRisky Cognitions:MotivesRisky Practices:EarlierRisky Practices:LaterNegativeConsequencesDiscriminant Validity among Reflective Constructs: Gefen and Straub (2005)compared the correlations between the individual items and the PLS calculatedconstruct scores as listed with the individual items. Min 0.10 diff needed.ConstructsStatementsIC-cont1 0.57 0.41 0.87 0.49 0.55 0.29 0.44 0.69 0.53 0.49IC-cont2 0.50 0.46 0.83 0.55 0.57 0.33 0.46 0.63 0.52 0.50IC-cont3 0.53 0.43 0.79 0.53 0.51 0.30 0.45 0.58 0.42 0.47IC-cont4 0.59 0.42 0.89 0.52 0.58 0.31 0.45 0.68 0.54 0.46IC-cont5 0.49 0.46 0.81 0.49 0.60 0.29 0.43 0.62 0.51 0.54IC-begin1 0.32 0.48 0.55 0.89 0.66 0.36 0.44 0.49 0.59 0.61IC-begin2 0.38 0.46 0.54 0.91 0.65 0.35 0.38 0.55 0.62 0.67IC-begin3 0.36 0.35 0.51 0.80 0.58 0.33 0.42 0.51 0.48 0.54Persist1 0.32 0.54 0.47 0.61 0.81 0.44 0.56 0.45 0.62 0.66Persist2 0.37 0.48 0.56 0.58 0.79 0.36 0.47 0.53 0.63 0.65Persist3 0.39 0.52 0.58 0.57 0.84 0.37 0.49 0.59 0.63 0.64Persist4 0.39 0.54 0.61 © 0.66 0.89 0.40 0.56 0.58 0.63 0.74 18

Erroneous Cognitions:BeliefsPreoccupation DesireRisky Practices: EarlierImpaired Control:ContinueErroneous Cognitions:MotivesPreoccupation: ObsessedImpaired Control: BeginRisky Practices: LaterNegative ConsequencesPersistenceSquare Root of AVE and Inter-construct Correlations to Test for Divergent Validity(Compeau et al. 1999). Adequate discriminant validity is indicated if the square rootof the construct’s AVE is greater than its correlations with the other constructs.Erroneous Cognitions:Beliefsn.a.Preoccupation Desire 0.40 0.80Risky Practices: Earlier 0.43 0.54 n.a.Impaired Control: Continue 0.36 0.64 0.76 0.84Erroneous Cognitions:Motives0.49 0.39 0.58 0.53 n.a.Preoccupation: Obsessed 0.50 0.44 0.50 0.52 0.55 0.83Impaired Control: Begin 0.40 0.41 0.59 0.61 0.48 0.50 0.87Risky Practices: Later 0.45 0.48 0.67 0.60 0.59 0.61 0.66 n.a.Negative Consequences 0.44 0.40 0.61 0.59 0.62 0.56 0.70 0.74 n.a.Persistence 0.47 0.44 © 0.65 Focal Research0.67 0.63 0.63 0.73 0.75 0.81 0.83 19

Measures of Internal ConsistencyErroneous Cognitions: Beliefs(Formative)Erroneous Cognitions: Motives(Formative)AverageVarianceExtracted (AVE)CompositeReliabilityAverageCommunalityna na 0.31na na 0.49Preoccupation Desire (Reflective) 0.64 0.88 0.64Preoccupation: Obsessed (Reflective) 0.68 0.81 0.68Impaired Control: Begin (Reflective) 0.75 0.90 0.75Impaired Control: Continue (Reflective) 0.70 0.92 0.70Formative ConstructsRisky Practices: Earlier (Formative) na na 0.40Risky Practices: Later (Formative) na na 0.51Negative Consequences (Formative) na na 0.41© Focal ResearchPersistence (Reflective) 0.69 0.90 0.6920

Sample Formative Constructs: Risky Practices Early and LaterRisky Practices Early StatementHeirarchyFrequency Rank R PGSI VIFI sometimes exceed the amount of money I intended to spend inorder to win back money I have lost. 29.7% 40 0.71 1.52When gambling on the slots I usually use my bank or debit card toget more money so I can keep playing. 19.8% 53 0.53 1.58I play max bet if I’m on a winning streak. 29.7% 6 0.28 1.15If I win big I am likely to put the money back into a machine andkeep playing. 17.6% 51 0.40 1.34When gambling on a slot machine I usually play as fast as I can. 15.0% 39 0.36 1.17I have sometimes gambled for more than six hours straight when Iwas playing the slots. 34.8% 11 0.41 1.24Risky Practices Later StatementHeirarchyFrequency Rank R PGSI VIFAfter losing more money than I wanted on the slots I usually try towin it back by playing again either later that day or on anotherday. 14.7% 81 0.56 1.63When gambling on the slots I usually use my credit card to getmore money so I can keep playing. 10.7% 84 0.42 1.37When I gamble with friends or family I sometimes stay andcontinue to play after they have stopped or left. 8.0% 103 0.41 1.64I have sometimes borrowed money from others so I could go andgamble on the slots. 4.3% 111 0.34 1.75I have borrowed money from other people at the casino in orderto continue gambling. 4.0% 117 0.35 1.84I have left the casino to get more money so I can come back andkeep on gambling. 7.8% 97 0.40 1.60 21© Focal Research

SensitivityROC for Negative Consequences usingPGSI Score 8+ for State Variable Value1.00.80.60.40.20.00.00.20.40.6© Focal Research1 - Specificity0.81.022

Coordinates of the Curve forConsequences and PGSI 8+Positive ifGreater Thanor Equal ToSensitivity(Proportion)1 – Specificity(Proportion)0 1.000 1.0001 0.952 0.2042 0.952 0.0883 0.905 0.0514 0.667 0.0235 0.667 0.0176 0.476 0.0117 0.429 0.0068 0.429 0.0039 0.333 0.00010 0.238 0.00011 0.143 0.00012 0.048 0.000© Focal Research23

FLAGS (EGM)Preliminary Results of Phase IV:development of the FocaL AdultGambling ScreenTony Schellinck, Focal Research and Dalhousie UniversityTracy Schrans, President of Focal ResearchMichael Bliemel , Dalhousie UniversityHeather Schellinck, Dalhousie UniversityResearch funded by Ontario Problem Gambling Research Centre – stillunder review© Focal Research24