The Prediction of Alcohol Use Disorder: A Scoping Review

Ali Ebrahimi*, Anette Søgaard Nielsen, Uffe Kock Wiil, Marjan Mansourvar

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


The prediction of Alcohol Use Disorder (AUD) may help to alleviate the number of deaths caused by alcohol related diseases, which had amounted to 3.3 million in 2014, worldwide. This article reports on the results of a scoping review of literature which focused on the prediction of AUD. A search in the academic databases including Medline, Web of Science and EBSCOhost had identified 28 articles which were published from 1980 to 2018, and which fulfilled our inclusion criteria related to the prediction of AUD. The findings suggest that research focusing on the prediction of AUD has been solid, with majority of the investigations focusing on genetics and family history, and psychological factors. It was observed that no study had tried to extract the predictor variables of AUD from their collected samples. Further, while a few studies had applied the machine learning approach in this domain, most investigations were based on statistical methods. Our review also suggests that compared to other regions where the rate of harmful drinking and mortality caused by alcoholism is high, Denmark is a country that has been less explored.
Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE Symposium on Computers and Communications (ISCC)
Publication date2019
ISBN (Print)978-1-7281-3000-2
ISBN (Electronic)978-1-7281-2999-0
Publication statusPublished - 2019
Event2019 IEEE Symposium on Computers and Communications, ISCC 2019 - Barcelona, Spain
Duration: 29. Jun 20193. Jul 2019


Conference2019 IEEE Symposium on Computers and Communications, ISCC 2019
SeriesIEEE International Symposium on Computers and Communications


  • Alcohol use disorder
  • prediction
  • scoping review


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