Using a computational cognitive model to simulate the effects of personal and social network experiences on seasonal influenza vaccination decisions.

Abstract

Introduction: Seasonal influenza poses significant societal costs, including illness, mortality, and reduced work productivity. Vaccination remains the most effective strategy for preventing the disease, yet vaccination rates in the United States fall below 50% for adults. Understanding the factors influencing vaccination decisions is crucial for designing interventions to improve uptake. This study investigates how personal experiences and the experiences of social contacts affect individual decisions to get vaccinated against influenza.

Methods: A multi-year longitudinal survey study was conducted to examine the impact of personal and social network experiences on vaccination decisions. Participants' vaccination behaviors and experiences with influenza were tracked over time. To model these influences, we developed a memory-based vaccination decision model using the Adaptive Control of Thought - Rational (ACT-R) integrated cognitive architecture, which incorporates cognitive processes associated with memory and decision-making.

Results: The survey results demonstrated that both personal experiences with influenza and the experiences of close social contacts significantly influenced vaccination decisions. The memory-based model, built within the ACT-R framework, effectively captured these effects, providing a computational representation of how personal and social factors contribute to vaccination behaviors.

Discussion: The findings suggest that personal and social experiences play a critical role in shaping vaccination decisions, which can inform the development of targeted interventions to increase vaccination uptake. By incorporating cognitive processes into the model, we identified potential strategies to enhance vaccine promotion efforts, such as recalling past experiences with illness to motivate individuals to get vaccinated.