Longitudinal clinical validation of the model

Establish whether the stochastic, stress-modulated compartmental stochastic differential equation model of suicidal state transitions in U.S. veterans accurately predicts longitudinal clinical outcomes by validating its simulated trajectories against real-world time-series mental health data.

Background

The paper introduces a continuous-time stochastic compartmental model with five mental health states (Healthy, Passive Ideation, Active Ideation, Attempt, Removed) and stress-driven transition rates modulated by clinical covariates. While simulations and sensitivity analyses demonstrate plausible behaviors and tipping dynamics, the authors acknowledge that the model has not been tested against actual longitudinal clinical outcomes.

Validating the model against time-series data is essential for assessing predictive accuracy, calibrating parameters, and determining clinical utility for risk assessment and decision support.