A machine learning-based screening tool for classifying post-traumatic stress disorder in firefighters: Firefighter Latent Risk Evaluation (FLARE)
Seok Joo Chae, Johanna Inhyang Kim, Hyeontae Jo, Yun Min Song, Saebom Jeon, Sun-Young Moon, Ji-Hye Lee, Sohee Oh, Seockhoon Chung, Jae Kyoung Kim, Jeong-Hyun Kim · 2026
Read A machine learning-based screening tool for classifying post-traumatic stress disorder in firefighters: Firefighter Latent Risk Evaluation (FLARE) by Seok Joo Chae, Johanna Inhyang Kim, Hyeontae Jo, Yun Min Song, Saebom Jeon, Sun-Young Moon, Ji-Hye Lee, Sohee Oh, Seockhoon Chung, Jae Kyoung Kim, Jeong-Hyun Kim (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13531790.txt.
Description
Seok Joo Chae and colleagues build in 2026 a screening model that flags South Korean firefighters at risk of post-traumatic stress. Stigma keeps reported rates low in this workforce, so indirect signals matter. Records covered 52,428 firefighters, of whom 2,305 had probable disorder on a standard checklist.
Seven features carried the model: poor concentration, appetite change, guilt feelings, sleep trouble, work pressure, poor adaptability, and doubts about seeking help for others. The gradient-boosting model classified risk with strong accuracy, and a fresh year of data confirmed the performance. A short flagged list could steer early support toward hidden cases.
Catalog record
| CREATOR | Seok Joo Chae, Johanna Inhyang Kim, Hyeontae Jo, Yun Min Song, Saebom Jeon, Sun-Young Moon, Ji-Hye Lee, Sohee Oh, Seockhoon Chung, Jae Kyoung Kim, Jeong-Hyun Kim |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46084 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |