Integrating emotional and cognitive biases in graded decision-making models
Insights from a theoretical case study in healthcare
Bibliographic Data
| ID | 9406111 |
|---|---|
| Authors | Matteo Maria Cati (0000-0002-1601-092X, corresponding author) |
| Year | 2025 |
| Volume | 261 |
| Pages | 105915-105915 |
| Publication date | 2025-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Acta Psychologica (JOURNAL) |
| Journal identifiers | ISSN: 0001-6918 • E-ISSN: 1873-6297 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.actpsy.2025.105915 |
| PMID | 41270554 |
| OpenAlex | W4416449615 |
| Language | EN |
| References cited | 36 |
Classical decision theory has long been anchored in the ideal of the rational actor, guided by internally consistent preferences and the axioms of Expected Utility Theory (EUT). Behavioral economics and cognitive psychology have enriched this framework by revealing systematic deviations driven by cognitive biases, while affective science has exposed the profound role of emotional states in shaping perception, valuation, and choice. Yet, in most formal models, cognition and emotion remain analytically segregated, treated as distinct modifiers rather than dynamically coupled determinants of behavior. This paper introduces the Integrated Behavioral Decision-Making Model (IBDM), a formal, parameterized framework that unifies graded emotional states and cognitive distortions into a single utility structure. Drawing inspiration from Vernon L. Smith's reinterpretation of Adam Smith's Theory of Moral Sentiments, the IBDM incorporates the boundedness of human rationality not as a deviation from a normative standard, but as a structural feature of decision-making. Fear and optimism are modeled as graded intensities that interact multiplicatively with cognitive biases such as loss aversion and anchoring, altering decision utility in nonlinear and path-dependent ways. A theoretical case study in healthcare decision-making, whether to undergo high-risk surgery, is simulated using Python. Results demonstrate that small changes in emotional intensity can reverse predicted preferences under traditional models, revealing regions of decision-space where affective forces dominate over risk-return trade-offs. This insight reframes the design of interventions in personalized medicine and public health, highlighting the necessity of emotionally intelligent policy tools. The IBDM is not merely a theoretical innovation: it is an epistemic bridge between normative theory, empirical behavioral evidence, and the lived emotional realities of decision contexts. It provides a blueprint for experimental validation, cross-disciplinary integration, and the next generation of computational behavioral models
A framework for studying the neurobiology of value-based decision making
Emotions in Economic Theory and Economic Behavior
The Probability Weighting Function
Constructivist and Ecological Rationality in Economics
The Anchoring-and-Adjustment Heuristic
Dispositional optimism
Psychology and Economics
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Risk as feelings
| Highly cited | No |
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