{"version":1,"type":"story","url":"https://digestai.news/story/mit-researchers-develop-tool-to-estimate-suicide-risk-from-text-messag","json":"https://digestai.news/story/mit-researchers-develop-tool-to-estimate-suicide-risk-from-text-messag.json","markdown":"https://digestai.news/story/mit-researchers-develop-tool-to-estimate-suicide-risk-from-text-messag.md","slug":"mit-researchers-develop-tool-to-estimate-suicide-risk-from-text-messag","headline":"MIT researchers develop tool to estimate suicide risk from Text messages","summary":"Researchers at MIT’s McGovern Institute, led by former graduate student Daniel Low and senior scientist Satra Ghosh, created a language‑processing tool that estimates suicide risk from text conversations. Using a custom lexicon of about 60 words or phrases for each of 49 risk factors, they analyzed de‑identified data from roughly 16,000 Crisis Text Line chats that were classified into non‑suicidal, suicidal ideation and imminent risk categories.\n\nThe team reports that their lightweight machine‑learning model accurately predicts risk severity in new conversations, flagging high‑impact factors such as mentions of lethal means, substance use, active suicidal ideation and self‑injury. Because the model links each term to a specific factor, it remains interpretable and can run on a personal computer, reducing cost and privacy concerns. The researchers are openly sharing both the lexicon and the software package so other scientists can build similar tools for mental‑health conditions, and they see potential for clinical and crisis‑support settings after further validation.","keyPoints":["Researchers analyzed de‑identified texts from ~16,000 Crisis Text Line conversations to train a suicide‑risk prediction model.","The model uses a custom lexicon of ~60 words/phrases for each of 49 risk factors and outperforms typical symptom cues.","The lightweight, interpretable model runs on a personal computer; the lexicon and software package are being openly shared."],"whyItMatters":"Accurate, interpretable detection of suicide risk from real‑time text can help counselors intervene earlier, while the low‑cost, open tool enables broader research and clinical adoption.","category":{"slug":"research","name":"Research","url":"https://digestai.news/category/research"},"entities":{"companies":["Crisis Text Line"],"models":[],"people":["Daniel Low","Satra Ghosh"]},"firstPublishedAt":"2026-09-24T21:00:00Z","updatedAt":"2026-09-24T21:00:00Z","sourceCount":1,"hasPrimarySource":true,"sources":[{"outlet":"MIT News on AI","title":"Estimating suicide risk from text","url":"https://news.mit.edu/2026/estimating-suicide-risk-from-text-0924","publishedAt":"2026-09-24T21:00:00Z","type":"primary","primary":true,"lead":true}],"sourceNotes":null,"discussions":[],"thread":null,"cite":{"text":"Digest AI, \"MIT researchers develop tool to estimate suicide risk from Text messages\", 24 September 2026, https://digestai.news/story/mit-researchers-develop-tool-to-estimate-suicide-risk-from-text-messag","publisher":"Digest AI","title":"MIT researchers develop tool to estimate suicide risk from Text messages","datePublished":"2026-09-24T21:00:00Z","url":"https://digestai.news/story/mit-researchers-develop-tool-to-estimate-suicide-risk-from-text-messag"},"generatedBy":"Written by Digest AI's editorial model from the linked sources; the sources are the record.","license":"Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse"}