Predicting U.S. county opioid poisoning mortality from multi-modal social media and psychological self-report data.

ABSTRACT: Opioid poisoning mortality is a substantial public health crisis in the United States, with opioids involved in approximately 75% of the nearly 1 million drug related deaths since 1999. Research suggests that the epidemic is driven by both over-prescribing and social and psychological determinants such as economic stability, hopelessness, and isolation. Hindering this research is a lack of measurements of these social and psychological constructs at fine-grained spatial and temporal resolutions. To address this issue, we use a multi-modal data set consisting of natural language from Twitter, psychometric self-reports of depression and well-being, and traditional area-based measures of socio-demographics and health-related risk factors. Unlike previous work using social media data, we do no

SUBMITTER: Giorgi S 

PROVIDER: S-EPMC10238775 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature