Machine Learning-Based Evaluation of Suicide Risk Assessment in Crisis Counseling Calls.

ABSTRACT:

Objective

Counselor assessment of suicide risk is one key component of crisis counseling, and standards require risk assessment in every crisis counseling conversation. Efforts to increase risk assessment frequency are limited by quality improvement tools that rely on human evaluation of conversations, which is labor intensive, slow, and impossible to scale. Advances in machine learning (ML) have made possible the development of tools that can automatically and immediately detect the presence of risk assessment in crisis counseling conversations.

Methods

To train models, a coding team labeled every statement in 476 crisis counseling calls (193,257 statements) for a core element of risk assessment. The authors then fine-tuned a transformer-based ML model with the labeled data

SUBMITTER: Imel ZE 

PROVIDER: S-EPMC11530329 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature