Integrating dual-process decision making and social dynamics: A formal modeling framework for addiction

Area of Science:

• Behavioral economics
• Computational psychiatry
• Mathematical modeling

Background:

• Current addiction models fail to integrate individual decision-making and social dynamics.
• This integration is crucial for a comprehensive understanding of addiction.

Purpose of the Study:

• To propose a novel nonlinear dynamical modeling framework for addiction.
• To integrate individual and social levels of addictive behavior.
• To explain key addiction phenomena using this integrated framework.

Main Methods:

• Formalizing a dual-process theory at the individual level.
• Incorporating incentive sensitization, selection homophily, and peer influence at the social level.
• Adapting an ecological model (spruce budworm population dynamics) for addiction.

Main Results:

• The integrated model explains gradual transitions to heavy use, sudden relapse/quitting, and stable use states.
• The framework accounts for social contagion, outbreaks, user clustering, and social aid in recovery.
• Demonstrated extensibility to model complex interactions between different addictive behaviors.

Conclusions:

• The proposed integrated modeling framework offers a unified approach to understanding addiction.
• This framework can generate new insights and predictions for addiction research.
• Highlights potential for future research into multifaceted aspects of addictive behaviors.