Investigating the Effects of Big Five Personality Traits on Suicide Severity Level Detection with Large Language Models

ACL ARR 2026 January Submission9681 Authors

Keywords: Suicide severity level detection, C-SSRS, Personality, Persona induction, Big Five personality traits, Large Language Model, Natural Language Processing

Abstract:

Sensitive content warning: This paper contains sensitive content related to suicide.
Suicide is one of the leading causes of global mortality, making risk detection a critical public health priority.
Although psychological studies have observed a tangible link between personality and suicide, this relationship has yet to be empirically tested and applied using LLMs.In this study, we investigate the ability of LLMs to observe and leverage the relation between these two domains during suicide severity level detection. We propose inducing user persona via profiles compiled using the Big Five personality traits within a zero-shot setting, assessing the impact of persona information on detection performance. Experimental results demonstrated that the persona induction approach showed a marginal but positive impact on detection for most models, suggesting LLMs partially comprehend the inter-domain relationship and that further refinement could significantly boost performance.

Paper Type: Long

Research Area: Clinical and Biomedical Applications

Research Area Keywords: mental health, automatic evaluation, inference methods, applications, prompting, cognitive modeling, computational psycholinguistics,

Contribution Types: Model analysis & interpretability

Languages Studied: English

Submission Number: 9681