Assessing self‐reported expenditures on gambling

Volberg, Rachel A.; Gerstein, Dean R.; Christiansen, Eugene Martin; Baldridge, John

doi:10.1002/mde.999

Cited by 37 publications

(16 citation statements)

References 17 publications

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“…Next, male legislators vote more liberally on lottery votes; this issue area includes all gambling‐related votes as well as lottery votes. Other research has found that women generally are less likely to view gambling favorably and to participate in illegal gambling (Volberg et al, :84); taken together, these findings suggest that female legislators approach this issue differently than men, even after controlling for their political beliefs.…”

Section: Resultsmentioning

confidence: 72%

How Gender Influences Roll Call Voting^*

Jenkins

2012

Social Science Quarterly

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Objective. Research has established that female legislators act differently than their male counterparts in state legislatures. But the effect of gender on roll call voting is less clear, due in part to the fact that research has not properly differentiated between the multiple ways gender can influence roll call voting. Methods. In order to better understand the relationship between gender and roll call voting, structural equation modeling is used to examine roll call voting in numerous issue areas in five state legislatures. Results. Gender rarely exerts a direct influence on roll call voting. Instead, the influence of gender is manifested through ideology and party. Conclusion. The primary effect of gender on roll call voting is that it leads female legislators to make different choices in ideology and partisanship as compared to their male counterparts.

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Section: Resultsmentioning

confidence: 72%

How Gender Influences Roll Call Voting^*

Jenkins

2012

Social Science Quarterly

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“…blood alcohol). Consequently, measuring levels of involvement relies entirely upon self‐report methods, which have been shown to be unreliable . Although Walker et al .’s paper aims to facilitate cross‐comparability of outcomes, it does not endorse specific instruments designed to assess each domain.…”

Section: Introductionmentioning

confidence: 99%

Measuring treatment outcomes in gambling disorders: a systematic review

et al. 2017

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Background and AimsConsiderable variation of outcome variables used to measure recovery in the gambling treatment literature has precluded effective cross‐study evaluations and hindered the development of best‐practice treatment methodologies. The aim of this systematic review was to describe current diffuse concepts of recovery in the gambling field by mapping the range of outcomes and measurement strategies used to evaluate treatments, and to identify more commonly accepted indices of recovery.MethodsA systematic search of six academic databases for studies evaluating treatments (psychological and pharmacological) for gambling disorders with a minimum 6‐month follow‐up. Data from eligible studies were tabulated and analysis conducted using a narrative approach. Guidelines of the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) were adhered to.ResultsThirty‐four studies were reviewed systematically (RCTs = 17, comparative designs = 17). Sixty‐three different outcome measures were identified: 25 (39.7%) assessed gambling‐specific constructs, 36 (57.1%) assessed non‐gambling specific constructs, and two instruments were used across both categories (3.2%). Self‐report instruments ranged from psychometrically validated to ad‐hoc author‐designed questionnaires. Units of measurement were inconsistent, particularly in the assessment of gambling behaviour. All studies assessed indices of gambling behaviour and/or symptoms of gambling disorder. Almost all studies (n = 30; 88.2%) included secondary measures relating to psychiatric comorbidities, psychological processes linked to treatment approach, or global functioning and wellbeing.ConclusionsIn research on gambling disorders, the incorporation of broader outcome domains that extend beyond disorder‐specific symptoms and behaviours suggests a multi‐dimensional conceptualization of recovery. Development of a single comprehensive scale to measure all aspects of gambling recovery could help to facilitate uniform reporting practices across the field.

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“…Some behavioural characteristics that were used to diagnose/identify problem gambler, including chasing losses or increasing bet sizes (American Psychiatric Association, 2000;Ferris & Wynne, 2001;Lesieur & Blume, 1987), can be monitored in a manner that is more reliable than past research tools such as survey self-report data (Hodgins & Makarchuk, 2003;Volberg, Gerstein, Christiansen, & Baldridge, 2001). Osborn, Skelt, Delfabbro, Nevile, and McMillen (2007) and Schellinck and Schrans (2007) conducted major empirical studies that examined observable signs of problem gambling in gaming venues.…”

Section: Empirical Studiesmentioning

confidence: 99%

Identifying high-risk online gamblers: a comparison of data mining procedures

Philander

2013

International Gambling Studies

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Using play data from a sample of virtual live action sports betting gamblers, this study evaluates a set of classification and regression algorithms to determine which techniques are more effective in identifying probable disordered gamblers. This study identifies a clear need for validating results using players not appearing in the original sample, as even methods that use in-sample cross-validation can show substantial differences in performance from one data set to another. Many methods are found to be quite accurate in correctly identifying player types in training data, but perform poorly when used on new samples. Artificial neural networks appear to be the most reliable classification method overall, but still fail to identify a large group of likely problem gamblers. Bet intensity, variability, frequency and trajectory, as well as age and gender are noted to be insufficient variables to classify probable disordered gamblers with arbitrarily reasonable accuracy.

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Assessing self‐reported expenditures on gambling

Cited by 37 publications

References 17 publications

How Gender Influences Roll Call Voting^*

How Gender Influences Roll Call Voting^*

Measuring treatment outcomes in gambling disorders: a systematic review

Identifying high-risk online gamblers: a comparison of data mining procedures

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Assessing self‐reported expenditures on gambling

Cited by 37 publications

References 17 publications

How Gender Influences Roll Call Voting*

How Gender Influences Roll Call Voting*

Measuring treatment outcomes in gambling disorders: a systematic review

Identifying high-risk online gamblers: a comparison of data mining procedures

Contact Info

Product

Resources

About

How Gender Influences Roll Call Voting^*

How Gender Influences Roll Call Voting^*