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In which environments is impulsive behavior adaptive? A cross-discipline review and integration of formal models

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Frankenhuis,  Willem E.
Criminology, Max Planck Institute for the Study of Crime, Security and Law, Max Planck Society;

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Citation

Fenneman, J., Frankenhuis, W. E., & Todd, P. M. (2022). In which environments is impulsive behavior adaptive? A cross-discipline review and integration of formal models. Psychological Bulletin, 148(7-8), 555-587. doi:10.1037/bul0000375.


Cite as: https://hdl.handle.net/21.11116/0000-000E-9219-1
Abstract
Are impulsive behaviors an adaptive response to living in harsh or unpredictable environments? Formal models help address this question by providing cost–benefit analyses across a broad range of environmental conditions, but their various results have not been systematically integrated. Here, we survey models from diverse disciplines including psychology, biology, economics, and management to develop a conceptual framework of impulsivity. Using this framework, we integrated results from 30 models to review whether impulsivity is adaptive across a range of environmental conditions. We focus on information impulsivity, that is, acting without considering consequences, and temporal impulsivity, that is, the tendency to pick sooner outcomes over later ones. Results show that both types are adaptive when individuals are close to a critical threshold (e.g., bankruptcy), resources are predictable, or interruptions are common. When resources are scarce, impulsivity can be adaptive or maladaptive, depending on the type and degree of scarcity. Information impulsivity is also adaptive when environments do not change over time or change very often (but maladaptive in between), or if local resource patches have similar properties, reducing the need to gather further information. Temporal impulsivity is adaptive when environments do not change over time and when local resource patches differ. Our review shows theoreticians how ideas from different disciplines are connected, affords formal modelers to see similarities and differences between their own models and those of others, and informs researchers about which empirical predictions generalize across a broad range of environmental conditions and which ones do not. To end, we provide concrete recommendations for future empirical studies.