Gender differences in characteristics of Chinese treatment-seeking problem gamblers.

Full Abstract

A total of 952 (841 men and 111 women) Chinese treatment-seeking problem gamblers completed self-report assessment forms. Female in contrast to male gamblers were more likely to be older, married, less educated, and without employment. Female gamblers also started gambling at an older age, had a shorter gambling history, preferred casino and mahjong gambling, and reported more somatic complaints and suicidal thoughts. Male and female gamblers accumulated similar amount of gambling debt and reported an average of 12 gambling-related problems on the Chinese version of the South Oaks Gambling Screen [Lesieur and Blume (Am J Psychiatry 144:1184-1188, 1987)]. Both groups were similarly troubled by their indebtedness, inability to control gambling, and gambling-related interpersonal problems. However, female gamblers had fewer means to pay their gambling debt. Given that significant gender-related differences were observed in Chinese problem gamblers, prevention and treatment services should attend to specific needs of male and female gamblers.

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Author information

Author/s: Tang, Catherine So-kum (CS); Wu, Anise M S (AM); Tang, Joe Y C (JY);

Affiliation: Department of Psychology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong. ctang(-atsign-)cuhk.edu.hk

Journal and publication information

Publication Type: Journal Article

Journal: Journal of gambling studies / co-sponsored by the National Council on Problem Gambling and Institute for the Study of Gambling and Commercial Gaming (J Gambl Stud), published in United States. (Language: eng)

Reference: 2007-Jun; vol 23 (issue 2) : pp 145-56

Dates: Created 2007/04/16; Completed 2007/11/08;

PMID: 17245660, status: MEDLINE (last retrieval date: 12/26/2008)

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Adolescent
Behavior, Addictive - epidemiology; psychology
China - epidemiology
Female
Gambling - psychology
Humans
Male
Prevalence

Prevalence
Questionnaires
Regression Analysis
Risk Assessment - statistics & numerical data
Risk Factors
Severity of Illness Index
Sex Distribution
Social Environment

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