Abstract
The topic of recreational drug consumption is still largely controversial around the globe. Factors that predispose people and lead to initial drug use include, among others, personality traits. The study of personality is a well-established domain of psychology, with multiple models having been developed, which are capable of predicting predisposition to a certain degree. Furthermore, addiction and other mental health issues carry stigma, which inhibits affected people from reaching out for support. Online web-based tools and automated systems have shown to be fairly effective in tackling stigma by eliminating the human factor. As such, a web-based decision support system (DSS) is developed and made publicly available, in order to inform users about their drug predisposition through an online personality survey. To accomplish the latter, the DSS utilizes multiple machine learning algorithms to extract patterns of personality, as modeled by the Big Five personality traits. The utilized algorithms turn out to be effective at predicting drug use for most of the 17 drugs that are considered, even in cases of high-class imbalance.
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Zervopoulos, A., Papamichail, A., Exarchos, T.P. (2021). A Decision Support System for the Prediction of Drug Predisposition Through Personality Traits. In: Vlamos, P. (eds) GeNeDis 2020. Advances in Experimental Medicine and Biology, vol 1338. Springer, Cham. https://doi.org/10.1007/978-3-030-78775-2_6
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