Detection of suicide risk using event-related potentials: a comprehensive systematic review and meta-analysis

Abstract

Background: Suicide has profound effects on individuals, families, and societies globally, underscoring the urgent need for effective early detection and prevention strategies. This systematic review aims to investigate the use of event-related potentials (ERPs) as a tool for identifying and monitoring suicide risk.

Methods: A comprehensive literature search was conducted, resulting in the inclusion of 23 articles that met the eligibility criteria. The review synthesized findings related to various ERP components associated with suicide risk.

Results: The analysis revealed that individuals with a history of suicide risk exhibited significantly reduced P3 amplitudes in response to novel stimuli during the go/no-go paradigm compared to healthy controls [standardized mean difference (SMD) = −0.53, 95% confidence interval (CI) = [−0.96; −0.10]]. Additionally, altered P3 responses to positive feedback on rewards indicated impairments in those at risk (SMD = −1.12, 95% CI = [−1.74; −0.49]). Variability in other ERP components was also highlighted, with several moderators, such as sample characteristics and methodological design, influencing ERP components.

Conclusion: The findings suggest that specific ERP components, particularly the P3, may serve as valuable indicators for assessing suicide risk. The review emphasizes the need for future research to utilize larger, more homogeneous samples and advanced analytical techniques to enhance detection accuracy. The application of ERPs is posited as a promising avenue for improving understanding of the neurocognitive mechanisms associated with suicide risk and enhancing prevention efforts.

Keywords

electroencephalography (EEG) / event-related potentials (ERPs) / suicide risk / P3 / cognitive processing / neural indicators

Supplementary data

Supplementary data are available at PSYRAD Journal online.

Author contributions

Qianlan Yin (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Visualization, Writing - original draft, Writing - review & editing), Huijing Xu (Conceptualization, Data curation, Investigation, Methodology, Project administration, Writing - original draft, Writing - review & editing), Zhuyu Chen (Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing), Qian Jiang (Investigation, Project administration, Validation, Writing - original draft, Writing - review & editing), Taosheng Liu (Conceptualization, Project administration, Supervision, Validation, Visualization, Writing - review & editing).

Conflict of interests

The authors declare no conflict of interest.

Acknowledgements

The study was supported by the Project of prevention and protection for mental health ([2024]432-73) and Collaborative Research Project of Institutes (2023-TQ-LC-013). We would like to acknowledge the use of AI-driven language tools (Grammarly) in the initial drafting and enhancement of the cover letter content for this paper. These tools were employed solely for language improvement and did not contribute to the research design, data analysis, or writing of the manuscript itself.

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