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Exploring the Prediction of Personality Traits from Drug Consumption Profiles
- Source :
- UMAP (Adjunct Publication)
- Publication Year :
- 2020
- Publisher :
- Tekniska Högskolan, Jönköping University, JTH, Datateknik och informatik, 2020.
-
Abstract
- The number of people that have been in touch with drugs is continuously increasing. Excessive intake of drugs becomes problematic when it turns into disorderly behaviors, such as addictions. In order to treat these disorderly behaviors, treatment plans often adhere to a one-size-fits-all approach with fixed and standardized steps. However, for effective treatment of disorderly behaviors it has been acknowledged that personalized treatment programs are necessary. The personality of people has been argued to be a factor that plays an important role in setting up effective treatment plans. In this work we explored the predictability of people's personality traits based on their drug consumption profile. Based on self-reported consumption frequencies of "abusable psychoactive drugs," we found among 1878 respondents that drug consumption profiles can be used to predict people's personality traits. The prediction of personality traits can be used to circumvent intruding questionnaires and to implicitly create personalized treatment programs.
- Subjects :
- Computer and Information Sciences
Computer science
media_common.quotation_subject
Personalized treatment
02 engineering and technology
01 natural sciences
0202 electrical engineering, electronic engineering, information engineering
Personality
Effective treatment
personalized treatment plans
Big Five personality traits
media_common
Consumption (economics)
user modeling
Addiction
User modeling
drug consumption
010401 analytical chemistry
020207 software engineering
Data- och informationsvetenskap
0104 chemical sciences
personality
Drug consumption
addiction
Social psychology
disorderly behaviors
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- UMAP (Adjunct Publication)
- Accession number :
- edsair.doi.dedup.....26d8a21196d8c48fe6f0a3b1fe854f53