This review evaluates the gap between lab-based decision-making research and real-life decision-making, proposing a cognitive-computational framework that integrates high-resolution spatiotemporal tracking technologies with formal psychological theory to study everyday decisions at a process level.
The authors identify that existing approaches either sacrifice ecological validity (lab experiments) or mechanistic detail (real-life observation), and propose that recent high-resolution tracking tools—paired with appropriate statistical models—can bridge this gap in a theory-driven way.
As a theoretical review and framework proposal, no empirical data or effect sizes are reported; the practical feasibility and scalability of integrating tracking technologies with cognitive-computational models in diverse real-life settings remains to be demonstrated.
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