Literature DB >> 18327633

SOGS and CGPI: parallel comparison on a diverse population.

Martin Young1, Matthew Stevens.   

Abstract

The Northern Territory of Australia, one of the most demographically and socially diverse jurisdictions in the country, conducted its first population-based gambling and problem gambling prevalence survey in 2005. Both the South Oaks Gambling Screen (SOGS) and the Canadian Problem Gambling Index (CPGI) were administered to the same sample of respondents. Using data from this survey, the current paper presents a parallel comparison of the respective screens with particular reference to gender, region, and the socio-demographic characteristics of respondents. The respective screens produced significantly different groups of problem gamblers as measured by their association with a range of socio-demographic variables. Specifically, the large number of SOGS items related to money issues may cause selective overrepresentation among low socioeconomic groups, including Indigenous people, who exist in relatively high proportions in the Northern Territory. In addition, there existed substantial gender-based differences within screens. Identified female problem gamblers were associated with household level variables (i.e. employment status, household type and marital status), while males were associated with socio-economic variables including language, education, and income. Further research is required to validate the use of problem gambling screens within the Indigenous population and to understand the role of gender in the experience and categorisation of problem gambling.

Entities:  

Mesh:

Year:  2008        PMID: 18327633     DOI: 10.1007/s10899-007-9087-z

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


  18 in total

1.  Reliability, validity, and classification accuracy of the South Oaks Gambling Screen (SOGS).

Authors:  Randy Stinchfield
Journal:  Addict Behav       Date:  2002 Jan-Feb       Impact factor: 3.913

Review 2.  The South Oaks Gambling Screen: a review with reference to Australian use.

Authors:  Malcolm W Battersby; Lyndall J Thomas; Barry Tolchard; Adrian Esterman
Journal:  J Gambl Stud       Date:  2002

3.  Epidemiological study of gambling in the non-metropolitan region of central Queensland.

Authors:  Grant Schofield; Kerry Mummery; Wei Wang; Geoff Dickson
Journal:  Aust J Rural Health       Date:  2004-02       Impact factor: 1.662

4.  Factors associated with gamblers: a population-based cross-sectional study of South Australian adults.

Authors:  Tiffany Gill; Eleonora Dal Grande; Anne W Taylor
Journal:  J Gambl Stud       Date:  2006-07-14

5.  Risk of harm among gamblers in the general population as a function of level of participation in gambling activities.

Authors:  Shawn R Currie; David C Hodgins; JianLi Wang; Nady el-Guebaly; Harold Wynne; Sophie Chen
Journal:  Addiction       Date:  2006-04       Impact factor: 6.526

Review 6.  What's wrong with Bonferroni adjustments.

Authors:  T V Perneger
Journal:  BMJ       Date:  1998-04-18

7.  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

8.  Is the SOGS an accurate measure of pathological gambling among children, adolescents and adults?

Authors:  R Ladouceur; C Bouchard; N Rhéaume; C Jacques; F Ferland; J Leblond; M Walker
Journal:  J Gambl Stud       Date:  2000

9.  A comparison of treatment-seeking pathological gamblers based on preferred gambling activity.

Authors:  Nancy M Petry
Journal:  Addiction       Date:  2003-05       Impact factor: 6.526

Review 10.  Do multiple outcome measures require p-value adjustment?

Authors:  Ronald J Feise
Journal:  BMC Med Res Methodol       Date:  2002-06-17       Impact factor: 4.615

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  8 in total

1.  Psychometric evaluation of the Problem Gambling Severity Index-Chinese version (PGSI-C).

Authors:  Jasmine M Y Loo; Tian P S Oei; Namrata Raylu
Journal:  J Gambl Stud       Date:  2011-09

2.  Assessing the reliability of the Gambling Functional Assessment: Revised.

Authors:  Jeffrey N Weatherly; Joseph C Miller; Kevin S Montes; Chase Rost
Journal:  J Gambl Stud       Date:  2012-06

3.  An examination of the relationship between gambling and antisocial behavior.

Authors:  Sandeep Mishra; Martin L Lalumière; Michael Morgan; Robert J Williams
Journal:  J Gambl Stud       Date:  2011-09

4.  The prevalence and course of pathological gambling in the mood disorders.

Authors:  Lena C Quilty; Chris Watson; Jennifer J Robinson; Tony Toneatto; R Michael Bagby
Journal:  J Gambl Stud       Date:  2011-06

5.  Validation of the problem gambling severity index using confirmatory factor analysis and rasch modelling.

Authors:  Natalie V Miller; Shawn R Currie; David C Hodgins; David Casey
Journal:  Int J Methods Psychiatr Res       Date:  2013-09-09       Impact factor: 4.035

6.  Personality, perceived luck and gambling attitudes as predictors of gambling involvement.

Authors:  Jamie Chiu; Lance Storm
Journal:  J Gambl Stud       Date:  2010-06

7.  Reliability, validity and classification accuracy of the South Oaks Gambling Screen in a Brazilian sample.

Authors:  Maria Paula Magalhães Tavares de Oliveira; Dartiu Xavier da Silveira; Simone Villas Boas de Carvalho; Silvia Teresa Collakis; Juliana Bizeto; Maria Teresa Araujo Silva
Journal:  J Gambl Stud       Date:  2009-09-23

8.  Gratitude, hope, mindfulness and personal-growth initiative: buffers or risk factors for problem gambling?

Authors:  Jasmine M Y Loo; Jung-Shun Tsai; Namrata Raylu; Tian P S Oei
Journal:  PLoS One       Date:  2014-02-11       Impact factor: 3.240

  8 in total

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