Psychometric evaluation of the NORC diagnostic screen for gambling problems (NODS) for the assessment of DSM-5 gambling disorder

被引:12
作者
Brazeau, Brad W. [1 ]
Hodgins, David C. [1 ]
机构
[1] Univ Calgary, Dept Psychol, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada
关键词
Gambling disorder; DSM-5; NODS; Validation; Psychometric; Assessment; VALIDITY;
D O I
10.1016/j.addbeh.2022.107310
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
The National Opinion Research Center (NORC) Diagnostic Screen for Gambling Problems (NODS) is one of the most used outcome measures in gambling intervention trials. However, a screen based on DSM-5 gambling disorder criteria has yet to be developed or validated since the DSM-5 release in 2013. This omission is possibly because the criteria for gambling disorder only underwent minor changes from DSM-IV to DSM-5: the diagnostic threshold was reduced from 5 to 4 criteria, and the illegal activity criterion was removed. Validation of a measure that captures these changes is still warranted. The current study examined the psychometric properties of an online self-report past-year adaptation of the NODS based on DSM-5 diagnostic criteria for gambling disorder (i. e., NODS-GD). A diverse sample of participants (N = 959) was crowdsourced via Amazon's TurkPrime. Internal consistency and one-week test-retest reliability were good. High correlations (r = 0.74-0.77) with other measures of gambling problem severity were observed in addition to moderate correlations (r = 0.21-0.36) with related but distinct constructs (e.g., gambling expenditures, time spent gambling, other addictive behaviors). All nine of the DSM-5 criteria loaded positively on one principal component, which accounted for 40% of the variance. Classification accuracy (i.e., sensitivity, specificity, predictive power) was generally very good with respect to the PGSI and ICD-10 diagnostic criteria. Future studies are encouraged to establish a gold standard selfreport measure of gambling problems and develop agreed-upon recommendations for the use and interpretation of crowdsourced addiction data.
引用
收藏
页数:6
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