Epidemiology of DSM-5 Alcohol Use Disorder in U.S. Military Veterans: Results from the National Health and Resilience in Veterans Study

2021 ◽  
pp. 109240
Author(s):  
Kaitlyn E. Panza ◽  
Alexander C. Kline ◽  
Peter J. Na ◽  
Marc N. Potenza ◽  
Sonya B. Norman ◽  
...  
Author(s):  
Silke Behrendt ◽  
Barbara Braun ◽  
Randi Bilberg ◽  
Gerhard Bühringer ◽  
Michael Bogenschutz ◽  
...  

Abstract. Background: The number of older adults with alcohol use disorder (AUD) is expected to rise. Adapted treatments for this group are lacking and information on AUD features in treatment seeking older adults is scarce. The international multicenter randomized-controlled clinical trial “ELDERLY-Study” with few exclusion criteria was conducted to investigate two outpatient AUD-treatments for adults aged 60+ with DSM-5 AUD. Aims: To add to 1) basic methodological information on the ELDERLY-Study by providing information on AUD features in ELDERLY-participants taking into account country and gender, and 2) knowledge on AUD features in older adults seeking outpatient treatment. Methods: baseline data from the German and Danish ELDERLY-sites (n=544) were used. AUD diagnoses were obtained with the Mini International Neuropsychiatric Interview, alcohol use information with Form 90. Results: Lost control, desired control, mental/physical problem, and craving were the most prevalent (> 70 %) AUD-symptoms. 54.9 % reported severe DSM-5 AUD (moderate: 28.2 %, mild: 16.9 %). Mean daily alcohol use was 6.3 drinks at 12 grams ethanol each. 93.9 % reported binging. More intense alcohol use was associated with greater AUD-severity and male gender. Country effects showed for alcohol use and AUD-severity. Conclusion: European ELDERLY-participants presented typical dependence symptoms, a wide range of severity, and intense alcohol use. This may underline the clinical significance of AUD in treatment-seeking seniors.


Author(s):  
Silke Behrendt ◽  
Alexis Kuerbis ◽  
Barbara Braun‐Michl ◽  
Randi Bilberg ◽  
Gerhard Bühringer ◽  
...  

2019 ◽  
Vol 201 ◽  
pp. 147-154 ◽  
Author(s):  
Rohan H.C. Palmer ◽  
Leslie A. Brick ◽  
Yi-Ling Chou ◽  
Arpana Agrawal ◽  
John E. McGeary ◽  
...  

2018 ◽  
Vol 49 (6) ◽  
pp. 931-939 ◽  
Author(s):  
Cheryl D. Raffo ◽  
Deborah S. Hasin ◽  
Paul Appelbaum ◽  
Melanie M. Wall

AbstractBackgroundAlthough the DSM is a widely used diagnostic guide, lengthy criteria sets can be problematic and provide the primary motivation to identify short-forms. Using the 11 diagnostic criteria provided by the DSM-5 for alcohol use disorder (AUD), the present study develops a data-driven method to systematically identify subsets and associated cut-offs that yield diagnoses as similar as possible to use all 11 criteria.MethodRelying on data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III), our methodology identifies diagnostic short-forms for AUD by: (1) maximizing the association between the sum scores of all 11 criteria with newly constructed subscales from subsets of criteria; (2) optimizing the similarity of AUD prevalence between the current DSM-5 rule and newly constructed diagnostic short-forms; (3) maximizing sensitivity and specificity of the short-forms against the current DSM-5 rule; and (4) minimizing differences in the accuracy of the short-form across chosen covariates. Replication is shown using NESARC-Wave 2.ResultsMore than 11 000 diagnostic short-forms for DSM-5 AUD can be created and our method narrows down the optimal choices to eight. Results found that ‘Neglecting major roles’ and ‘Activities given up’ could be dropped with practically no change in who is diagnosed (specificity = 100%, sensitivity ⩾ 99.6%) or the severity of those diagnosed (κ = 0.97).ConclusionsWith a continuous improvement model adopted by the APA for DSM revisions, we offer a data-driven tool (a SAS Macro) that identifies diagnostic short-forms in a systematic and reproducible way to help advance potential improvements in future DSM revisions.


2020 ◽  
Vol 119 ◽  
pp. 108143
Author(s):  
Silke Behrendt ◽  
Alexis Kuerbis ◽  
Randi Bilberg ◽  
Barbara Braun-Michl ◽  
Anna Mejldal ◽  
...  

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