부산대학교 도서관

Background and aims: The focus of this paper is on the improvement of substance use disorder (SUD) screening and measurement. Using a multi‐dimensional item response theory model, the bifactor model, we provide a psychometric harmonization between SUD, depression, anxiety, trauma, social isolation, functional impairment and risk‐taking behavior symptom domains, providing a more balanced view of SUD. The aims are to (1) develop the item‐bank, (2) calibrate the item‐bank using a bifactor model that includes a primary dimension and symptom‐specific subdomains, (3) administer using computerized adaptive testing (CAT) and (4) validate the CAT‐SUD in Spanish and English in the United States and Spain. Design Item bank construction, item calibration phase, CAT‐SUD validation phase. Setting: Primary care, community clinics, emergency departments and patient‐to‐patient referrals in Spain (Barcelona and Madrid) and the United States (Boston and Los Angeles). Participants/cases: Calibration phase: the CAT‐SUD was developed via simulation from complete item responses in 513 participants. Validation phase: 297 participants received the Composite International Diagnostic Interview (CIDI) and the CAT‐SUD. Measurements A total of 252 items from five subdomains: (1) SUD, (2) psychological disorders, (3) risky behavior, (4) functional impairment and (5) social support. CAT‐SUD scale scores and CIDI SUD diagnosis. Findings Calibration: the bifactor model provided excellent fit to the multi‐dimensional item bank; 168 items had high loadings (> 0.4 with the majority > 0.6) on the primary SUD dimension. Using an average of 11 items (four to 26), which represents a 94% reduction in respondent burden (average administration time of approximately 2 minutes), we found a correlation of 0.91 with the 168‐item scale (precision of 5 points on a 100‐point scale). Validation: strong agreement was found between the primary CAT‐SUD dimension estimate and the results of a structured clinical interview. There was a 20‐fold increase in the likelihood of a CIDI SUD diagnosis across the range of the CAT‐SUD (AUC = 0.85). Conclusions: We have developed a new approach for the screening and measurement of SUD and related severity based on multi‐dimensional item response theory. The bifactor model harmonized information from mental health, trauma, social support and traditional SUD items to provide a more complete characterization of SUD. The CAT‐SUD is highly predictive of a current SUD diagnosis based on a structured clinical interview, and may be predictive of the development of SUD in the future. [ABSTRACT FROM AUTHOR]