Literature DB >> 25895650

Gambling and Problem Gambling in Victoria, Australia: Changes over 5 years.

Max Abbott1, Christine A Stone2, Rosa Billi3, Kristal Yeung3.   

Abstract

Rates of gambling and gambling-related harm fluctuate over time, influenced by availability, adaptation and demographic change, among other things. Assessing change is compromised by methodological variation. The main aim of this paper is to assess change in gambling participation and problems in adult Victorians over a 5-year period. Data are from the Victorian Gambling Study (VGS) 2008-2012 (n = 15,000) and the 2003 Victorian Longitudinal Attitudes Survey (n = 8479). An additional aim was to determine the impact of methodological differences on prevalence estimates. Despite gambling availability increasing and more activities being included participation rates declined substantially. Decreases occurred across almost all demographic groups and gambling activities. When adjustments were made for methodological differences there were no significant changes in problem, moderate risk and low risk gambling. Males and people with lower education had higher rates in both surveys. In the latter survey, two groups that experienced large participation reductions, namely young adults and metropolitan residents, emerged as additional groups with higher rates of problem and moderate-risk gambling. Further research is required to discover why overall rates of harm may have plateaued when participation continues to fall and why some groups with reduced participation experience increased harm. The findings suggest that availability and total consumption models are over-simplistic. They further suggest that to be effective prevention programmes will need to extend beyond gambling availability to include interventions directed towards individuals at risk and wider environmental determinants of vulnerability and harm. Additionally this study found that restricting administration of the problem gambling measure to subsets of gamblers generate significantly lower prevalence estimates, implying that many previous surveys under-portray gambling-related harm and that without appropriate adjustment for methodological variation findings cannot be validly compared across studies.

Entities:  

Keywords:  Adaptation; Exposure; PGSI; Prevalence; Problem gambling; Victoria

Mesh:

Year:  2016        PMID: 25895650     DOI: 10.1007/s10899-015-9542-1

Source DB:  PubMed          Journal:  J Gambl Stud        ISSN: 1050-5350


  7 in total

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Authors:  Monika Sassen; Ludwig Kraus; Gerhard Bühringer
Journal:  Int J Methods Psychiatr Res       Date:  2011-12       Impact factor: 4.035

2.  The population mean predicts the number of deviant individuals.

Authors:  G Rose; S Day
Journal:  BMJ       Date:  1990-11-03

3.  Gambling and problem gambling in Sweden: changes between 1998 and 2009.

Authors:  Max W Abbott; Ulla Romild; Rachel A Volberg
Journal:  J Gambl Stud       Date:  2014-12

4.  Estimating the extent and degree of Gambling related problems in the Australian population: A national survey.

Authors:  M G Dickerson; E Baron; S M Hong; D Cottrell
Journal:  J Gambl Stud       Date:  1996-06

5.  The New Zealand national survey of problem and pathological gambling.

Authors:  M W Abbott; R A Volberg
Journal:  J Gambl Stud       Date:  1996-06

6.  The South Oaks Gambling Screen (SOGS): a new instrument for the identification of pathological gamblers.

Authors:  H R Lesieur; S B Blume
Journal:  Am J Psychiatry       Date:  1987-09       Impact factor: 18.112

Review 7.  The road less travelled: moving from distribution to determinants in the study of gambling epidemiology.

Authors:  Howard J Shaffer; Richard A LaBrie; Debi A LaPlante; Sarah E Nelson; Michael V Stanton
Journal:  Can J Psychiatry       Date:  2004-08       Impact factor: 4.356

  7 in total
  19 in total

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Journal:  J Gambl Stud       Date:  2017-12

2.  A Composite Measure of Gambling Exposure: Availability, Accessibility or Both?

Authors:  S M Ofori Dei; D R Christensen; O A Awosoga; B K Lee; A C Jackson
Journal:  J Gambl Stud       Date:  2020-11-28

3.  Gambling Participation, Expenditure and Risk of Harm in Australia, 1997-1998 and 2010-2011.

Authors:  Andrew Richard Armstrong; Anna Thomas; Max Abbott
Journal:  J Gambl Stud       Date:  2018-03

4.  Online Problem Gambling: A Comparison of Casino Players and Sports Bettors via Predictive Modeling Using Behavioral Tracking Data.

Authors:  Ivan Ukhov; Johan Bjurgert; Michael Auer; Mark D Griffiths
Journal:  J Gambl Stud       Date:  2021-09

5.  Prevalence and Trends in Problem Gambling in Denmark with Special Focus on Country of Origin: Results from the Danish Health and Morbidity Surveys.

Authors:  Kamilla Kragelund; Ola Ekholm; Christina V L Larsen; Anne I Christensen
Journal:  J Gambl Stud       Date:  2022-01-06

6.  Health Outcomes in Individuals with Problem and Pathological Gambling: An Analysis of the 2014 North Carolina Behavioral Risk Factor Survey System (BRFSS).

Authors:  Ryan Van Patten; Jeremiah Weinstock; Andrew B McGrath
Journal:  J Gambl Stud       Date:  2018-03

7.  Public Perceptions of Harm for Nine Popular Gambling Products.

Authors:  Leon Booth; Annie S Anderson; Victoria White; Hannah Pierce; Rob Moodie; Simone Pettigrew
Journal:  J Gambl Stud       Date:  2021-02-26

Review 8.  Differences in problem and pathological gambling: A narrative review considering sex and gender.

Authors:  Corinna Gartner; Andreas Bickl; Sabine Härtl; Johanna K Loy; Laura Häffner
Journal:  J Behav Addict       Date:  2022-05-02       Impact factor: 7.772

9.  Comparative Analysis of Potential Risk Factors for at-Risk Gambling, Problem Gambling and Gambling Disorder among Current Gamblers-Results of the Austrian Representative Survey 2015.

Authors:  Sven Buth; Friedrich M Wurst; Natasha Thon; Harald Lahusen; Jens Kalke
Journal:  Front Psychol       Date:  2017-12-14

10.  A meta-regression analysis of 41 Australian problem gambling prevalence estimates and their relationship to total spending on electronic gaming machines.

Authors:  Francis Markham; Martin Young; Bruce Doran; Mark Sugden
Journal:  BMC Public Health       Date:  2017-05-23       Impact factor: 3.295

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