[Alcohol Dependence: one or more nosological entities? Identifying geographical diversities among patients through DSM-4 and Artificial Intelligence].

Abstract

Background: although there is an overabundance of terms that over time have connoted the phenomenon usually defined as Alcoholism, or Alcohol Dependence, this has been universally considered a unitary disease by experts, the media and lay people.

Objectives: to investigate whether there is a variety of configurations of alcohol dependence and alcohol abuse corresponding to different countries.

Design: secondary analysis of a dataset from a European project conducted in 2013-2014. The analysis was carried out mainly based on both artificial intelligence and statistical tools: Self Organizing Map (SOM) Neural Network, Multidimensional Scaling Population Algorithm (MSPA), and K-Means clustering algorithm.

Setting and participants: 1,767 participants in a European project treated in specialist alcohol dependence units in 9 countries/regions of Europe.

Main outcome measures: patients were interviewed to ascertain their correspondence to the 11 DSM-4 symptoms used for the diagnosis of 'alcohol dependence' and 'alcohol abuse', following up on a previous study that used traditional statistical methodology.

Results: results confirm that the symptoms of 'alcohol dependence' and 'alcohol abuse' identified by the DSM-4 are distributed according to distinct European geographical macroareas: Central-Northern and Southern, with an intermediate macroarea. These could partly correspond to different typologies of drinking cultures in the different macroareas.

Conclusions: alcoholism does not appear to be a unitary disease, but varies according to different cultures and social contexts, and should be treated appropriately.