Human suffering is often detected after it becomes visible: after withdrawal, crisis, hospitalization, burnout, social collapse, or functional breakdown. Flourishing is often studied as a static state rather than a dynamic capacity. This paper proposes a state-space research architecture for modeling shortterm and medium-term transitions toward suffering and flourishing using validated instruments, ecological momentary assessment, optional passive sensing, and ethically constrained prediction. The framework does not claim to replace established theories of well-being, self-determination, mental health continua, capability, hopelessness, entrapment, burnout, allostatic load, social support, or network models of psychopathology. Instead, it translates selected constructs from these traditions into a programmable prediction-and-simulation architecture. The framework makes five methodological commitments. First, latent distress and latent capacity are specified through both transition equations and measurement equations, so observed domain scores are not ambiguously used as both causes and indicators. Second, the triadic amplifier is specified as a thresholded co-occurrence feature, TriadHigh, with continuous residualized interactions reserved for sensitivity analysis. Third, missing ecological momentary assessment data are modeled as potentially missing not at random through a shared-parameter observation process, with pattern-mixture analyses as robustness checks. Fourth, the model is framed not only as an early-warning system but also as a counterfactual simulation engine that can compare plausible intervention routes before real-world deployment. Fifth, individual probabilistic monitoring remains consent-tiered; prediction for prevention must not become hidden surveillance. The intended audience is psychiatric data science, computational psychology, digital mental health, and prevention science. The contribution is not a validated clinical model but a formal research program: a way to test whether trajectories of burden, agency, belonging, horizon, meaning, opportunity, non-response, and latent distress/capacity can predict preventable suffering while preserving autonomy and dignity. Keywords: suffering, flourishing, state-space model, ecological momentary assessment, missing not at random, shared parameter model, digital phenotyping, JITAI, micro-randomized trial, counterfactual simulation, computational psychiatry
Navin Kamble (Mon,) studied this question.