Mary Beth Miller1, Angelo M DiBello2, Jennifer E Merrill2, Kate B Carey2. 1. Department of Psychiatry, University of Missouri School of Medicine, 1 Hospital Dr DC067.00, Columbia, MO 65212, USA; Center for Alcohol and Addiction Studies, Department of Behavioral and Social Sciences, Brown University School of Public Health, Box G-S121-5, Providence, RI 02912, USA. Electronic address: millmary@health.missouri.edu. 2. Center for Alcohol and Addiction Studies, Department of Behavioral and Social Sciences, Brown University School of Public Health, Box G-S121-5, Providence, RI 02912, USA.
Abstract
BACKGROUND: Blackouts are common among young adults and predict alcohol-related harm. However, existing measures do not capture the range of alcohol-induced memory impairment involved in blackout experiences and do not differentiate between fragmentary and en bloc blackouts. This study aimed to develop and validate a brief, reliable measure of alcohol-induced blackouts among young adults. METHODS: College students reporting alcohol-induced memory impairment in the past year were recruited via Qualtrics to participate in an online survey (N = 350, 56% female). A subsample (n = 109, 67% female) completed a one-month follow-up. Principal component analysis was used to determine the structure of the Alcohol-Induced Blackout Measure (ABOM), which was designed to reflect two components (fragmentary and en bloc blackouts). The reliability and validity of the total ABOM score was assessed. RESULTS: The final five items fit in a two-component scale structure; however, a single principal component accounted for 73% of variance in blackout items, all of which demonstrated high component loadings and communalities. The total blackout score demonstrated strong internal consistency, test-retest reliability, and convergent and incremental validity. ABOM scores predicted alcohol-related consequences at baseline and one-month follow-up. CONCLUSIONS: The ABOM is a brief and reliable, self-report measure that quantifies the frequency of a range of blackout experiences in the past 30 days. Accounting for this range of experiences improved predictive validity over single-item blackout measures. Blackout frequency is a strong, unique predictor of alcohol-related problems.
BACKGROUND: Blackouts are common among young adults and predict alcohol-related harm. However, existing measures do not capture the range of alcohol-induced memory impairment involved in blackout experiences and do not differentiate between fragmentary and en bloc blackouts. This study aimed to develop and validate a brief, reliable measure of alcohol-induced blackouts among young adults. METHODS: College students reporting alcohol-induced memory impairment in the past year were recruited via Qualtrics to participate in an online survey (N = 350, 56% female). A subsample (n = 109, 67% female) completed a one-month follow-up. Principal component analysis was used to determine the structure of the Alcohol-Induced Blackout Measure (ABOM), which was designed to reflect two components (fragmentary and en bloc blackouts). The reliability and validity of the total ABOM score was assessed. RESULTS: The final five items fit in a two-component scale structure; however, a single principal component accounted for 73% of variance in blackout items, all of which demonstrated high component loadings and communalities. The total blackout score demonstrated strong internal consistency, test-retest reliability, and convergent and incremental validity. ABOM scores predicted alcohol-related consequences at baseline and one-month follow-up. CONCLUSIONS: The ABOM is a brief and reliable, self-report measure that quantifies the frequency of a range of blackout experiences in the past 30 days. Accounting for this range of experiences improved predictive validity over single-item blackout measures. Blackout frequency is a strong, unique predictor of alcohol-related problems.
Authors: Jennifer E Merrill; Hayley Treloar; Anne C Fernandez; Mollie A Monnig; Kristina M Jackson; Nancy P Barnett Journal: Psychol Addict Behav Date: 2016-10-13
Authors: Christopher W Kahler; John Hustad; Nancy P Barnett; David R Strong; Brian Borsari Journal: J Stud Alcohol Drugs Date: 2008-07 Impact factor: 2.582
Authors: Mary Beth Miller; Angelo M DiBello; Ellen Meier; Eleanor L S Leavens; Jennifer E Merrill; Kate B Carey; Thad R Leffingwell Journal: Behav Ther Date: 2018-03-21
Authors: Chan Jeong Park; Lindsey K Freeman; Nicole A Hall; Samyukta Singh; Kate B Carey; Jennifer E Merrill; Angelo M DiBello; Mary Beth Miller Journal: J Am Coll Health Date: 2021-03-02