Global Sensitivity Analysis for a Mathematical Model of the General Escape Theory of Suicide
| Authors |
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| Publication date | 2025 |
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| Book title | Computational Science – ICCS 2025 Workshops |
| Book subtitle | 25th International Conference, Singapore, Singapore, July 7–9, 2025 : proceedings |
| ISBN |
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| ISBN (electronic) |
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| 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 |
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| 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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