Kerman University of Medical Sciences

Document Type: Original Article

Authors

1 Department of Social Work, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

2 Department of Neuroscience and Addiction Studies, School of Advance Medical Technologies, Tehran University of Medical Sciences, Tehran, Iran

3 Oriental Institute, University of Oxford, Oxford, UK

4 Students Research Committee, Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran

5 Department of Nutrition and Health Science, Ball State University, Indiana, USA

6 Department of Statistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

Abstract

Background: Gambling disorder (GD) and substance use disorder (SUD) have mutual impact and each could
aggravate the effects of the other. This is the first study on GD among Iranian substance users to develop and
validate a GD Screening Questionnaire-Persian (GDSQ-P).
Methods: Iranian male adults (n = 503) with SUDs were recruited via clustered sampling. Problem gambling
screening instruments and Diagnostic and Statistical Manual of Mental Disorders-5th Edition (DSM-5)
criteria for GD were used to develop the tool which was sequentially assessed for face validity, content
validity index (CVI), content validity ratio (CVR), and reliability (Kuder-Richardson coefficient). To establish
construct validity, interviews based on DSM-5 as a gold standard method were used. A receiver operating
characteristic (ROC) curve was conducted to determine sensitivity and specificity.
Findings: After removing items with low CVI values, 27 final items remained in GDSQ-P with impact score
greater than 1.5. Card games (33.8%), dice gambling methods (26.6%), betting on sports teams and players
(24.1%), and betting on horseback, rooster, pigeon, dog, or other animals (16.7%) were common gambling
methods among participants. Overall Kuder-Richardson coefficient was 0.95. Cut-off threshold for GDSQ-P
was calculated as 4.5 with 98.9% sensitivity and 98.3% specificity. The interviewers confirmed GD for
participants based on DSM-5 as the gold standard. The prevalence of GD among participants was 17.9%
based on GDSQ-P and 19.1% based on DSM-5 criteria.
Conclusion: GDSQ-P is a valid and reliable tool to screen for GD in SUD treatment centers and probably in
the general population.


Keywords

American Psychiatric Association. Diagnostic and
Statistical Manual of Mental Disorders (DSM-5®).
Washington, DC: American Psychiatric Publishing,
Inc.; 2013.
2. Hing N, Russell AM, Gainsbury SM, Blaszczynski
A. Characteristics and help-seeking behaviors of
Internet gamblers based on most problematic mode
of gambling. J Med Internet Res 2015; 17(1): e13.
3. Black DW, Coryell W, Crowe R, McCormick B,
Shaw M, Allen J. Suicide ideations, suicide attempts,
and completed suicide in persons with pathological
gambling and their first-degree relatives. Suicide
Life Threat Behav 2015; 45(6): 700-9.
4. Grant JE, Derbyshire K, Leppink E, Chamberlain
SR. Suicidality in non-treatment seeking young
adults with subsyndromal gambling disorder.
Psychiatr Q 2014; 85(4): 513-22.
5. Black DW, Shaw M, McCormick B, Allen J.
Pathological gambling: Relationship to obesity, selfreported chronic medical conditions, poor lifestyle
choices, and impaired quality of life. Compr
Psychiatry 2013; 54(2): 97-104.
6. Harrison GW, Jessen LJ, Lau MI, Ross D.
Disordered gambling prevalence: Methodological
innovations in a General Danish Population Survey.
J Gambl Stud 2018; 34(1): 225-53.
7. Dowling NA, Youssef GJ, Jackson AC, Pennay DW,
Francis KL, Pennay A, et al. National estimates of
Australian gambling prevalence: Findings from a
dual-frame omnibus survey. Addiction 2016; 111(3):
Gambling Disorder Screening Questionnaire Maarefvand et al.
Addict Health, Spring 2019; Vol 11, No 2 117
http://ahj.kmu.ac.ir, 04 April
420-35.
8. Scalese M, Bastiani L, Salvadori S, Gori M, Lewis I,
Jarre P, et al. Association of problem gambling with
type of gambling among Italian general population. J
Gambl Stud 2016; 32(3): 1017-26.
9. Sassen M, Kraus L, Buhringer G, Pabst A, Piontek
D, Taqi Z. Gambling among adults in Germany:
Prevalence, disorder and risk factors. Sucht 2011;
57(4): 249-57.
10. Barnes GM, Welte JW, Tidwell MC, Hoffman JH.
Gambling and substance use: Co-occurrence among
adults in a recent general population study in the
United States. Int Gambl Stud 2015; 15(1): 55-71.
11. Himelhoch SS, Miles-McLean H, Medoff D,
Kreyenbuhl J, Rugle L, Brownley J, et al. Twelvemonth prevalence of DSM-5 gambling disorder and
associated gambling behaviors among those
receiving methadone maintenance. J Gambl Stud
2016; 32(1): 1-10.
12. Rennert L, Denis C, Peer K, Lynch KG, Gelernter J,
Kranzler HR. DSM-5 gambling disorder: Prevalence
and characteristics in a substance use disorder sample.
Exp Clin Psychopharmacol 2014; 22(1): 50-6.
13. Lorains FK, Cowlishaw S, Thomas SA. Prevalence
of comorbid disorders in problem and pathological
gambling: systematic review and meta-analysis of
population surveys. Addiction 2011; 106(3): 490-8.
14. Cowlishaw S, Merkouris S, Chapman A,
Radermacher H. Pathological and problem
gambling in substance use treatment: A systematic
review and meta-analysis. J Subst Abuse Treat
2014; 46(2): 98-105.
15. Cowlishaw S, Hakes JK. Pathological and problem
gambling in substance use treatment: Results from
the National Epidemiologic Survey on Alcohol and
Related Conditions (NESARC). Am J Addict 2015;
24(5): 467-74.
16. Kausch O. Patterns of substance abuse among
treatment-seeking pathological gamblers. J Subst
Abuse Treat 2003; 25(4): 263-70.
17. Krmpotich T, Mikulich-Gilbertson S, Sakai J,
Thompson L, Banich MT, Tanabe J. Impaired
decision-making, higher impulsivity, and drug
severity in substance dependence and pathological
gambling. J Addict Med 2015; 9(4): 273-80.
18. Mokdad AH, Forouzanfar MH, Daoud F, El
Bcheraoui C, Moradi-Lakeh M, Khalil I, et al. Health
in times of uncertainty in the eastern Mediterranean
region, 1990-2013: A systematic analysis for the
Global Burden of Disease Study 2013. Lancet Glob
Health 2016; 4(10): e704-e713.
19. Ahmad-Abadi FK, Maarefvand M, Aghaei H,
Hosseinzadeh S, Abbasi M, Khubchandani J.
Effectiveness of satir-informed family-therapy on the
codependency of drug dependents' family members
in Iran: A randomized controlled trial. J Evid Inf Soc
Work 2017; 14(4): 301-10.
20. Babaeian N, Maarefvand M, Hosseinzadeh S,
Khubchandani J. Comparison of Iranian Substance
users’ relapse and abstinence duration between peersupported vocational networks and mid term
residential treatment centers. Journal of Psychosocial
Rehabilitation and Mental Health 2019; 6(1): 49-54.
21. Maarefvand M, Babaeian N, Rezazadeh S,
Khubchandani J. Engagement with peer-supported
vocational networks: Recovered iranian substance
users’ perspectives and practices. Journal of
Psychosocial Rehabilitation and Mental Health 2017;
4(1): 89-97.
22. Nikfarjam A, Shokoohi M, Shahesmaeili A,
Haghdoost AA, Baneshi MR, Haji-Maghsoudi S, et
al. National population size estimation of illicit drug
users through the network scale-up method in 2013
in Iran. Int J Drug Policy 2016; 31: 147-52.
23. Gebauer L, LaBrie R, Shaffer HJ. Optimizing DSMIV-TR classification accuracy: a brief biosocial
screen for detecting current gambling disorders
among gamblers in the general household
population. Can J Psychiatry 2010; 55(2): 82-90.
24. Sullivan S. Don’t let an opportunity go by:
Validation of the EIGHT gambling screen. Int J
Ment Health Addict 2007; 5(4): 381-9.
25. Johnson EE, Hamer RM, Nora RM. The Lie/Bet
Questionnaire for screening pathological gamblers:
A follow-up study. Psychol Rep 1998; 83(3 Pt 2):
1219-24.
26. Hodgins DC. Using the NORC DSM Screen for
Gambling Problems as an outcome measure for
pathological gambling: psychometric evaluation.
Addict Behav 2004; 29(8): 1685-90.
27. Toce-Gerstein M, Gerstein DR, Volberg RA. The
NODS-CLiP: A rapid screen for adult pathological
and problem gambling. J Gambl Stud 2009; 25(4):
541-55.
28. Stinchfield R. Reliability, validity, and classification
accuracy of the South Oaks Gambling Screen
(SOGS). Addict Behav 2002; 27(1): 1-19.
29. Tolchard B, Battersby MW. The Victorian Gambling
Screen: Reliability and validation in a clinical
population. J Gambl Stud 2010; 26(4): 623-38.
30. Holtgraves T. Evaluating the problem gambling
severity index. J Gambl Stud 2009; 25(1): 105-20.
31. Cook DA, Beckman TJ. Current concepts in validity
and reliability for psychometric instruments: Theory
and application. Am J Med 2006; 119(2): 166-16.
32. Price JH, Kirchofer GM, Khubchandani J,
Kleinfelder J, Bryant M. Development of a College
Student's Mistrust of Health Care Organizations
Scale. Am J Health Educ 2013; 44(1): 19-25.
33. Polit DF, Beck CT, Owen SV. Is the CVI an
Gambling Disorder Screening Questionnaire Maarefvand et al.
118 Addict Health, Spring 2019; Vol 11, No 2
http://ahj.kmu.ac.ir, 04 April
acceptable indicator of content validity? Appraisal
and recommendations. Res Nurs Health 2007; 30(4):
459-67.
34. Wilson FR, Pan W, Schumsky DA. Recalculation of
the critical values for Lawshe’s Content Validity
Ratio. Meas Eval Couns Dev 2012; 45(3): 197-210.
35. Khubchandani J, Brey R, Kotecki J, Kleinfelder J,
Anderson J. The psychometric properties of PHQ-4
depression and anxiety screening scale among
college students. Arch Psychiatr Nurs 2016; 30(4):
457-62.
36. Himelhoch SS, Miles-McLean H, Medoff DR,
Kreyenbuhl J, Rugle L, Bailey-Kloch M, et al.
Evaluation of brief screens for gambling disorder in
the substance use treatment setting. Am J Addict
2015; 24(5): 460-6.
37. Oei TP, Raylu N. Familial influence on offspring
gambling: A cognitive mechanism for transmission
of gambling behavior in families. Psychol Med
2004; 34(7): 1279-88.
38. van den Brink W. Evidence-based pharmacological
treatment of substance use disorders and pathological
gambling. Curr Drug Abuse Rev 2012; 5(1): 3-31.
39. Grant JE, Odlaug BL, Schreiber LR.
Pharmacological treatments in pathological
gambling. Br J Clin Pharmacol 2014; 77(2): 375-81.