Examining the role of personality traits in fatal opioid overdose: Text mining approach

Anton Ivanov, Zhasmina Tacheva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The opioid crisis in the United States has reached epidemic levels, with the number of opioid-related overdose deaths now surpassing car accident fatalities. The severity of this crisis makes identifying the key risk factors associated with opioid overdose behaviors crucial. This research demonstrates the importance of investigating personality traits as a risk factor for opioid overdose mortality. We use the five-factor personality model in conjunction with advanced text mining to infer personality traits from unstructured social media data at the county level. We then employ econometric modeling to estimate the relationships between the inferred personality traits and fatal opioid overdose. Based on the results, conscientiousness and extroversion were found to be negatively associated with fatal opioid overdose, while neuroticism was positively associated with it. Furthermore, a counterintuitive finding suggested that agreeableness had a positive effect. Our results yield several practical implications that can complement existing opioid surveillance practices.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems 2018, ICIS 2018
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683173
StatePublished - 2018
Event39th International Conference on Information Systems, ICIS 2018 - San Francisco, United States
Duration: Dec 13 2018Dec 16 2018

Publication series

NameInternational Conference on Information Systems 2018, ICIS 2018

Conference

Conference39th International Conference on Information Systems, ICIS 2018
Country/TerritoryUnited States
CitySan Francisco
Period12/13/1812/16/18

Keywords

  • Community health
  • Fatal opioid overdose
  • Personality traits
  • Text mining

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences
  • Applied Mathematics

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