Detecting suicide risk among U.S. servicemembers and veterans: a deep learning approach using social media data.

ABSTRACT:

Background

Military Servicemembers and Veterans are at elevated risk for suicide, but rarely self-identify to their leaders or clinicians regarding their experience of suicidal thoughts. We developed an algorithm to identify posts containing suicide-related content on a military-specific social media platform.

Methods

Publicly-shared social media posts (n = 8449) from a military-specific social media platform were reviewed and labeled by our team for the presence/absence of suicidal thoughts and behaviors and used to train several machine learning models to identify such posts.

Results

The best performing model was a deep learning (RoBERTa) model that incorporated post text and metadata and detected the presence of suicidal posts with relatively high sensitivit

SUBMITTER: Zuromski KL 

PROVIDER: S-EPMC12315600 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature