The validity and reliability of CPGI, SOGS, GA20 and DSMIV as measures of problem gambling in Singap

1
The validity and reliability of CPGI, SOGS, GA-20
and DSM-IV as measures of problem gambling in
Singapore Principal Investigator David Arthur
(Professor Head) Alice Lee Centre for Nursing
Studies Yong Loo Lin School of
Medicine Co-Investigators Ai Yun Hing
(Associate Professor)
Department of Sociology at Faculty of Arts
Social Sciences
Miharu Sagara-Rosemeyer (Assistant Professor)
Alice Lee Centre for
Nursing Studies at Yong Loo Lin School of
Medicine Ee Heok Kua
(Professor Head)
Department of Psychological Medicine at
Yong Loo Lin School of Medicine Research
Assistants Wai Leng Tong and Chia Pei Chen
Alice Lee Centre
for Nursing Studies at Yong Loo Lin School of
Medicine 5 July 2007
2
Background and Significance

• This study was conducted to
• a) Understand the local culture of gambling in
• young people
• b) Discover the prevalence of gambling problems
• among university students
• c) Develop reliable and valid measures

3
Measures

• Diagnostic and Statistical Manual of Mental
• Disorders (DSM-IV)
• Gamblers Anonymous (GA-20)
• South Oaks Gambling Screen (SOGS)
• Canadian Problem Gambling Index (CPGI)

4
Demographics of the respondents

• 193 out of 212 (91.0) questionnaires answered
  completely
• Female students (53.3) gt male counterparts
  (46.7)
• 152 Aged 21 to 26 (78.8), 107 Employed (55.4)
• 158 Chinese (81.9), 13 Malay (6.7), 7 Indian
  (3.6),
• 9 with Other Ethnicity (4.7)
• 134 Bachelor (69.4), 11 Master (5.7), 3
  Professional
• degree (1.6)
• 60 with no specific religion (31), 36
  Protestant (18.7),
• 38 Buddhist (19.7), 11 Catholic (5.7), 16
  Muslim (8.3),
• 6 Hindu (3.1) and 19 with Other Religion
  (9.8)
• Chi-Square test shows that there were
  significant differences
• between age and religion by gender

5
Reliability and Validity test of four
instruments Internal Consistency and Convergent
Validity

• Table 1 Reliability and Validity
  test for four instruments

??Correlation is significant at the 0.01 level
(2-tailed) n148 (missing values excluded)
6
Reliability and Validity test of four
instruments Construct Validity

• Table 1 Reliability and Validity test for
  four instruments (Continued)

Note ? p lt .05 ??plt.01 ???plt.005
7
Prevalence of gambling behaviour in Singapore
university students
Table 2 Comparison of 4 instruments on
prevalence of gambling
behaviour in Singapore university students
?? Note ? p lt .05 ??plt.01 ???plt.005 gambling
categories or gambling risk level were defined
differently
8
Prevalence of gambling behaviour in Singapore
university students

• Chi-Square test shows that there were significant
  differences between
• numbers of gamblers by each instrument
• GA-20 was able to identify more at-risk/
  social gamblers
• (n40, 20.7)
• DSM-IV was able to identify more
  moderate/problem
• gamblers (n25, 13)
• SOGS was able to identify more
  Severe/Compulsive/
• Pathological Gamblers (n13, 8.7)

9
Result and Discussion

• The CPGI demonstrated the highest reliability
  coefficient (a0.922).
• The CPGI also correlates significantly with the
  DSM-IV, often considered the
• gold standard(Stinchfield, 2001).
• In addition, the CPGI stood out for its
  unidimensional structure as compared
• to other instruments.
• Almost all the items of CPGI had factor loadings
  ranging from 0.44 to 0.88.
• Only one item, ? 12 is problematic (loading
  value0.28).
• Unfortunately, its difficulty in implementation
  detracts from its use in such a
• sample.
• The findings suggest that a revision of the CPGI
  instrument based on
• psychometric analysis catering for a local use
  is important, and a reduction in
• the number of items and better worded items
  would improve its use.

10
Limitation on this research Acknowledgement

• Definition of gambling behaviour has to be
  clarified clearly.
• Participants reluctance to expose their gambling
  history.
• The financial support came from Cross-Faculty
  Research
• Grant approved by National University of
  Singapore.
• Thanks to Dr. Tony Chan Moon Fai (BSc, PhD,
  CStat,
• Assistant Professor of School of Nursing at
  The Hong Kong
• Polytechnic University) for his advice on
  statistical analysis.