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The Development of a Multi-dimensional Gambling Accessibility Scale

Overview of attention for article published in Journal of Gambling Studies, July 2009
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Title
The Development of a Multi-dimensional Gambling Accessibility Scale
Published in
Journal of Gambling Studies, July 2009
DOI 10.1007/s10899-009-9144-x
Pubmed ID
Authors

Nerilee Hing, John Haw

Abstract

The aim of the current study was to develop a scale of gambling accessibility that would have theoretical significance to exposure theory and also serve to highlight the accessibility risk factors for problem gambling. Scale items were generated from the Productivity Commission's (Australia's Gambling Industries: Report No. 10. AusInfo, Canberra, 1999) recommendations and tested on a group with high exposure to the gambling environment. In total, 533 gaming venue employees (aged 18-70 years; 67% women) completed a questionnaire that included six 13-item scales measuring accessibility across a range of gambling forms (gaming machines, keno, casino table games, lotteries, horse and dog racing, sports betting). Also included in the questionnaire was the Problem Gambling Severity Index (PGSI) along with measures of gambling frequency and expenditure. Principal components analysis indicated that a common three factor structure existed across all forms of gambling and these were labelled social accessibility, physical accessibility and cognitive accessibility. However, convergent validity was not demonstrated with inconsistent correlations between each subscale and measures of gambling behaviour. These results are discussed in light of exposure theory and the further development of a multi-dimensional measure of gambling accessibility.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 51 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 17%
Student > Master 8 15%
Student > Doctoral Student 6 12%
Other 5 10%
Student > Ph. D. Student 4 8%
Other 8 15%
Unknown 12 23%
Readers by discipline Count As %
Medicine and Dentistry 11 21%
Psychology 8 15%
Social Sciences 7 13%
Business, Management and Accounting 2 4%
Computer Science 2 4%
Other 9 17%
Unknown 13 25%