Observed and Normative Discount Functions in Addiction and other Diseases.

Area of Science:

• Behavioral Economics
• Neuroscience
• Mathematical Modeling

Background:

• Addiction and certain diseases exhibit discounting behaviors, characterized by impatience and dynamic inconsistency.
• Existing discount functions may not adequately capture the complexities of disease progression under treatment.
• Understanding these behaviors is crucial as excessive discounting can underlie various disorders.

Purpose of the Study:

• To identify a discount function that accurately models disease progression as a discounting process.
• To analyze experimental discount functions related to addictive behaviors and hyperbolic functions.
• To propose a novel discount function that accounts for patience and dynamic inconsistency in treated individuals.

Main Methods:

• Analysis of discount functions from experiments on addictive and problematic behaviors.
• Evaluation of hyperbola-like discount functions for fitting patient data.
• Mathematical modeling using the (generalized) exponentiated hyperbolic discount function.

Main Results:

• Addiction is associated with high discount rates (impatience) and preference reversals (dynamic inconsistency).
• The proposed (generalized) exponentiated hyperbolic discount function can model disease progression under treatment.
• This function captures the dynamic inconsistency observed, with a decreasing discount rate after an initial increase.

Conclusions:

• The (generalized) exponentiated hyperbolic discount function offers a suitable model for disease progression during treatment.
• This approach helps in understanding and potentially managing conditions characterized by excessive discounting.
• Accurate modeling of discounting is essential for addressing trans-disease processes in addiction and related disorders.