How Fuzzy-trace Theory Predicts Development of Risky Decision Making, with Novel Extensions to Culture and Reward Sensitivity. Academic Article uri icon

Overview

abstract

  • Comprehensive meta-analyses of risky decision making in children, adolescents, and adults have revealed that age trends in disambiguated laboratory tasks confirmed fuzzy-trace theory's prediction that preference for risk decreases monotonically from childhood to adulthood. These findings are contrary to predictions of dual systems or neurobiological imbalance models. Assumptions about increasing developmental reliance on mental representations of the gist of risky options are essential to account for this developmental trend. However, dual systems theory appropriately emphasizes how cultural context changes behavioral manifestation of risk preferences across age and neurobiological imbalance models appropriately emphasize developmental changes in reward sensitivity. All of the major theories include the assumption of increasing behavioral inhibition. Here, we integrate these theoretical constructs-representation, cultural context, reward sensitivity, and behavioral inhibition-to provide a novel framework for understanding and improving risky decision making in youth. We also discuss the roles of critical tests, scientific falsification, disambiguating assessments of psychological and neurological processes, and the misuse of such concepts as ecological validity and reverse inference. We illustrate these concepts by extending fuzzy-trace theory to explain why youth are a major conduit of viral infections, including the virus that causes COVID-19. We conclude by encouraging behavioral scientists to embrace new ways of thinking about risky decision making that go beyond traditional stereotypes about adolescents and that go beyond conceptualizing ideal decision making as trading off degrees of risk and reward.

publication date

  • September 9, 2021

Identity

PubMed Central ID

  • PMC8589284

Scopus Document Identifier

  • 85118792091

Digital Object Identifier (DOI)

  • 10.1016/j.dr.2021.100986

PubMed ID

  • 34776580

Additional Document Info

volume

  • 62