ABSTRACT
Background: The Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) is an interview that assesses psychiatric symptoms and diagnoses, including substance use disorders and anxiety and mood (i.e., internalizing) disorders. Although the SSAGA is widely used, there exists no overall internalizing characteristics scale based on items drawn from SSAGA’s mood and anxiety disorder sections. Objectives: To design and assess a SSAGA-based measurement instrument capturing the overall internalizing dimension that underlies more specific internalizing conditions. Methods: We developed, assessed, and characterized a new scale for measuring internalizing problematic characteristics derived from the SSAGA interview. All samples were drawn from the Collaborative Studies on the Genetics of Alcoholism, a prospective multi-site genetic study of families at high risk for alcohol use disorders. All participants taking part in the study between September 2005 and September 2017 were eligible (n = 904, 52.2% female). Results: The scale had adequate internal consistency (ordinal α = 0.85, 95% CI = [0.81, 0.89]). Construct validity was supported by its association with other measures of internalizing characteristics (Internalizing Scale from Achenbach Self Reports; Neuroticism Scale from the Neuroticism-Extraversion-Openness Five-Factor Personality Inventory). Several indices of alcohol, marijuana, and nicotine misuse were also positively associated with Internalizing Scale scores. Conclusions: The Internalizing Scale has very good psychometric properties and can be used in studies that incorporate the SSAGA interview to study the association between internalizing characteristics and problematic alcohol and other substance use. These associations can potentially be utilized to identify individuals at risk for substance problems and to design treatments targeting such individuals.
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Acknowledgments
The Collaborative Study on the Genetics of Alcoholism (COGA), Principal Investigators B. Porjesz, V. Hesselbrock, H. Edenberg, and L. Bierut, includes 11 different centers: University of Connecticut (V. Hesselbrock); Indiana University (H.J. Edenberg, J. Nurnberger Jr., T. Foroud); University of Iowa (S. Kuperman, J. Kramer); SUNY Downstate (B. Porjesz); Washington University in St. Louis (L. Bierut, J. Rice, K. Bucholz, A. Agrawal); University of California at San Diego (M. Schuckit); Rutgers University (J. Tischfield, A. Brooks); Department of Biomedical and Health Informatics, The Children’s Hospital of Philadelphia; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA (L. Almasy), Virginia Commonwealth University (D. Dick), Icahn School of Medicine at Mount Sinai (A. Goate), and Howard University (R. Taylor). Other COGA collaborators include: L. Bauer (University of Connecticut); J. McClintick, L. Wetherill, X. Xuei, Y. Liu, D. Lai, S. O’Connor, M. Plawecki, S. Lourens (Indiana University); G. Chan (University of Iowa; University of Connecticut); J. Meyers, D. Chorlian, C. Kamarajan, A. Pandey, J. Zhang (SUNY Downstate); J.-C. Wang, M. Kapoor, S. Bertelsen (Icahn School of Medicine at Mount Sinai); A. Anokhin, V. McCutcheon, S. Saccone (Washington University); J. Salvatore, F. Aliev, B. Cho (Virginia Commonwealth University); and Mark Kos (University of Texas Rio Grande Valley). A. Parsian and M. Reilly are the NIAAA Staff Collaborators.
We continue to be inspired by our memories of Henri Begleiter and Theodore Reich, founding PI and Co-PI of COGA, and also owe a debt of gratitude to other past organizers of COGA, including Ting-Kai Li, P. Michael Conneally, Raymond Crowe, and Wendy Reich, for their critical contributions.
Disclosure
The authors report no relevant financial conflicts.
Supplementary data
Supplemental material for this article can be accessed here.