Global Sensitivity Analysis for a Mathematical Model of the General Escape Theory of Suicide

Open Access
Authors
Publication date 2025
Host editors
  • Maciej Paszynski
  • Amanda S. Barnard
  • Yongjie Jessica Zhang
Book title Computational Science – ICCS 2025 Workshops
Book subtitle 25th International Conference, Singapore, Singapore, July 7–9, 2025 : proceedings
ISBN
  • 9783031975721
ISBN (electronic)
  • 9783031975738
Series Lecture Notes in Computer Science
Event Workshops on Computational Science, which were co-organized with the 25th International Conference on Computational Science, ICCS 2025
Volume | Issue number VI
Pages (from-to) 183-197
Number of pages 15
Publisher Cham: Springer
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
  • Faculty of Social and Behavioural Sciences (FMG) - Psychology Research Institute (PsyRes)
Abstract

This study explores a formalized dynamical systems model of the General Escape Theory of Suicide using Sobol and PAWN global sensitivity analyses. The findings highlight the importance of self-feedback loops, the effect of stressors on aversive internal states, and the interaction effects between aversive internal states and the urge to escape on suicidal ideation and non-suicidal escape behaviors. Time-dependent sensitivity analysis also reveals the long-term stability of parameter importance over time. These results hold potential for informing clinical interventions by identifying the most important influences for individual suicidal ideation.

Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-031-97573-8_13
Other links https://www.scopus.com/pages/publications/105010827228
Downloads
978-3-031-97573-8_13 (Final published version)
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