Assisting relapse prevention in alcohol addiction using a novel mobile app–based intervention: BeSober

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Chronic alcohol consumption has become a major concern in the public and dealing with this disorder has become essential for the general public as well as for the healthcare treatments. Not only did excessive alcohol consumption laid a negative impact on the physical health of an individual but it also has created a serious impression on their mental health. The social and economic downfall is the upshot of excessive alcohol consumption. Alcohol relapse remains a common problem in disorders associated with alcohol addiction which is associated with spatial-temporal factors like time periods and specific places.

This thesis introduces a new generation of relapse prevention mobile application called “BeSober”, which assist people to reduce their consumption of alcohol, offer support within the intervention period, providing community-based support from alternative users or alcohol addiction therapists, monitoring addicts behavior and provide personalized recommendations to assist the addict to stay sober. This application tracks relapse history, summarizes recovering statistics, and records user-profiles to help users to better understand their recovering situations. Concretely, this platform remotely monitors the user’s location and automatically detects a user in alcohol influential places and recommend more complete ubiquitous location-based recommendation algorithm by inferring user's preferences and considering nearby places, in order to create a diversion in such intervals. Additionally, algorithms of machine learning that make use of temporal and spatial factors are used for prediction of relapse, based on which a diversion recommendation algorithm useful addiction diversion activities are suggested. Also, BeSober offers a relapse recovering community, which allows addicts and therapists to interact, share relapse intervention experiences and thereby motivating addicts in their relapse intervals.

Alcohol addiction, Relapse intervention, Geofencing, Mobile application