David R Foxcroft1, Lesley A Smith2, Hayley Thomas2, Sarah Howcutt2. 1. Department of Psychology, Social Work and Public Health, Oxford Brookes University, Oxford OX3 0FL, UK david.foxcroft@brookes.ac.uk. 2. Department of Psychology, Social Work and Public Health, Oxford Brookes University, Oxford OX3 0FL, UK.
Abstract
AIMS: To assess the accuracy of Alcohol Use Disorders Identification Test (AUDIT) scores for problem drinking in males and females aged 18-35 in England. METHODS: A method comparison study with 420 primary care patients aged 18-35. Test measures were AUDIT and AUDIT-C. Reference standard measures were (a) Time-Line Follow-Back interview for hazardous drinking; World Mental Health Composite International Diagnostic Interview for (b) DSM-IV alcohol abuse, (c) DSM-IV alcohol dependence, (d) DSM-5 alcohol use disorders. RESULTS: Area under the curve (AUC) was (a) 0.79 (95% CI 0.73-0.85; males) and 0.84 (0.79-0.88; females); (b) 0.62 (0.54-0.72; males) and 0.65 (0.57-0.72; females); (c) 0.77 (0.65-0.87; males) and 0.76 (0.67-0.74; females); (d) 0.70 (0.60-0.78; males) and 0.73 (CI 0.67-0.78; females). Identification of threshold cut-point scores from the AUC was not straightforward. Youden J statistic optimal cut-point scores varied by 4-6 AUDIT scale points for each outcome according to whether sensitivity or specificity were prioritized. Using Bayes' Theorem, the post-test probability of drinking problems changed as AUDIT score increased, according to the slope of the probability curve. CONCLUSION: The full AUDIT scale showed good or very good accuracy for all outcome measures for males and females, except for alcohol abuse which had sufficient accuracy. In a screening scenario where sensitivity might be prioritized, the optimal cut-point is lower than established AUDIT cut-points of 8+ for men and 6+ for women. Bayes' Theorem to calculate individual probabilities for problem drinking offers an alternative to arbitrary cut-point threshold scores in screening and brief intervention programmes.
AIMS: To assess the accuracy of Alcohol Use Disorders Identification Test (AUDIT) scores for problem drinking in males and females aged 18-35 in England. METHODS: A method comparison study with 420 primary care patients aged 18-35. Test measures were AUDIT and AUDIT-C. Reference standard measures were (a) Time-Line Follow-Back interview for hazardous drinking; World Mental Health Composite International Diagnostic Interview for (b) DSM-IV alcohol abuse, (c) DSM-IV alcohol dependence, (d) DSM-5 alcohol use disorders. RESULTS: Area under the curve (AUC) was (a) 0.79 (95% CI 0.73-0.85; males) and 0.84 (0.79-0.88; females); (b) 0.62 (0.54-0.72; males) and 0.65 (0.57-0.72; females); (c) 0.77 (0.65-0.87; males) and 0.76 (0.67-0.74; females); (d) 0.70 (0.60-0.78; males) and 0.73 (CI 0.67-0.78; females). Identification of threshold cut-point scores from the AUC was not straightforward. Youden J statistic optimal cut-point scores varied by 4-6 AUDIT scale points for each outcome according to whether sensitivity or specificity were prioritized. Using Bayes' Theorem, the post-test probability of drinking problems changed as AUDIT score increased, according to the slope of the probability curve. CONCLUSION: The full AUDIT scale showed good or very good accuracy for all outcome measures for males and females, except for alcohol abuse which had sufficient accuracy. In a screening scenario where sensitivity might be prioritized, the optimal cut-point is lower than established AUDIT cut-points of 8+ for men and 6+ for women. Bayes' Theorem to calculate individual probabilities for problem drinking offers an alternative to arbitrary cut-point threshold scores in screening and brief intervention programmes.
Authors: Elena Gervilla; Rafael Jiménez; Joella Anupol; Mariàngels Duch; Albert Sesé Journal: Int J Environ Res Public Health Date: 2020-04-22 Impact factor: 3.390
Authors: Nicolas Bertholet; Elodie Schmutz; Véronique S Grazioli; Mohamed Faouzi; Jennifer McNeely; Gerhard Gmel; Jean-Bernard Daeppen; John A Cunningham Journal: Trials Date: 2020-02-17 Impact factor: 2.279