A computational cognitive model of behaviors and decisions that modulate pandemic transmission: Expectancy-value, attitudes, self-efficacy, and motivational intensity

Peter Pirolli; Christian Lebiere; Mark Orr

doi:10.3389/fpsyg.2022.981983

A computational cognitive model of behaviors and decisions that modulate pandemic transmission: Expectancy-value, attitudes, self-efficacy, and motivational intensity

Front Psychol. 2023 Jan 13:13:981983. doi: 10.3389/fpsyg.2022.981983. eCollection 2022.

Authors

Peter Pirolli¹, Christian Lebiere², Mark Orr³

Affiliations

¹ Institute for Human and Machine Cognition, Pensacola, FL, United States.
² School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States.
³ Biocomplexity Institute, University of Virginia, Charlottesville, VA, United States.

Abstract

We present a computational cognitive model that incorporates and formalizes aspects of theories of individual-level behavior change and present simulations of COVID-19 behavioral response that modulates transmission rates. This formalization includes addressing the psychological constructs of attitudes, self-efficacy, and motivational intensity. The model yields signature phenomena that appear in the oscillating dynamics of mask wearing and the effective reproduction number, as well as the overall increase of rates of mask-wearing in response to awareness of an ongoing pandemic.

Keywords: ACT-R; COVID-19; basic reproduction number; cognition; non-pharmaceutical interventions.