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Published on: June 5, 2016
Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective.
Giles W Story1, Ivo Vlaev2, Ben Seymour3
1Department of Surgery and Cancer, Centre for Health Policy, Institute of Global Health Innovation, Imperial College London London, UK ; Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London London, UK.
High temporal discounting rates predict unhealthy behaviors. However, intention-incongruent actions are often habitual, driven by cues, not just hyperbolic discounting. Computational models may reveal health decision phenotypes.
Area of Science:
- Behavioral Economics
- Neuroscience
- Health Psychology
Background:
- Unhealthy choices are common despite awareness of risks.
- Temporal discounting, devaluing future rewards, is a proposed mechanism.
- Hyperbolic discounting specifically may explain intention-behavior gaps.
Purpose of the Study:
- To review evidence linking temporal discount rates to unhealthy behaviors.
- To assess if hyperbolic discounting explains intention-incongruent unhealthy actions.
- To propose a framework for understanding health decision-making.
Main Methods:
- Systematic literature review of studies on discounting and health behaviors.
- Analysis of intention-incongruent actions in relation to hyperbolic discounting.
- Proposal of a dual-system reinforcement learning framework (model-based vs. model-free).
Main Results:
- High discount rates for rewards (money, food, drugs) correlate with unhealthy behaviors and health status markers.
- Intention-incongruent unhealthy actions are often triggered by environmental cues or motivational shifts, not solely by hyperbolic discounting.
- Unhealthy behaviors can become habitual (model-free) through repetition, persisting even with changing goals.
Conclusions:
- Temporal discounting is a promising predictor of unhealthy behaviors.
- Hyperbolic discounting alone does not fully explain intention-incongruent unhealthy actions.
- A dual-system model (goal-directed and habitual) offers a framework for understanding state-based effects in health decisions, potentially identifying distinct phenotypes.
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