A Study of the Psychometric Properties of the Persian Version of the Online Gambling Symptom Assessment Scale in the Iranian Population

Document Type : Original Article


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

2 Operating Room Instructor, Faculty of Paramedicine, Zabul University of Medical Sciences, Zabol, Iran

3 Department of Clinical Psychology, Iran University Medical Sciences, Tehran, Iran



Background: The primary objective of the current paper was to assess the psychometric attributes of the Persian version of the 
Online Gambling Symptom Assessment Scale (P-OGSAS) within the Iranian population.
Methods: The current study was conducted through a convenient sampling method between September and November 2021, 
involving 187 participants who had experienced online gambling at least once a month for the last 3 months. OGSAS was translated 
from English into Persian using the forward-backward translation method. Cronbach’s alpha coefficient and principal component 
analysis (PCA) were employed to evaluate the reliability and validity of the scale, respectively. Participants were administered 
a battery of assessments, including P-OGSAS, Persian Gambling Disorder Screening Questionnaire (GDSQ-P), Patient Health 
Questionnaire-9 Items (PHQ-9), and Generalized Anxiety Disorder Questionnaire (GADQ-7), to assess validity and reliability.
Findings: The results showed that the 3-factor model of this scale provides the highest level of predictability. The 3-factor model 
accounts for 54.8% of the square load. With a Cronbach’s alpha coefficient of 0.807, P-OGSAS demonstrated satisfactory reliability. 
Finally, OGSAS has a significant correlation with other scales, and as a result, this scale has suitable convergent validity.
Conclusion: P-OGSAS can adequately assess the symptoms and severity of online gambling. Therefore, clinicians could use this 
scale to evaluate the problems related to online gambling in the Iranian population.


Mohammadreza Davoudi: (Google Scholar) (PubMed)

Tayebeh Azarmehr: (Google Scholar) (PubMed)

Fatemeh Abdoli: (Google Scholar) (PubMed)

AmirHossein sadeghi: (Google Scholar) (PubMed)

Sarah salehi inanloo: (Google Scholar) (PubMed)

Fereshteh Momeni: (Google Scholar) (PubMed)

Zahra Khalili: (Google Scholar) (PubMed)

Sahar Aliyaki: (Google Scholar) (PubMed)


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