a b s t r a c tDecisions in everyday life are commonly made using a combination of descriptive and experiential information, and these two sources of information frequently contradict each other. However, decisionmaking research has mostly focused on description-only or experience-only tasks. Three experiments show that individuals exposed to description and experience simultaneously are influenced by both, particularly in situations in which descriptions are in conflict with experience. We examined cognitive models of how people integrate their experience with descriptions of choice outcomes, with different weights given to each source of information. Experience was the dominant source of information, but descriptions were taken into consideration, albeit at a discounted level, even after many trials. Models that included the descriptive information fitted the human data more accurately than models that did not. Wider implications for understanding how these two commonly available sources of information are combined for daily decision-making are discussed.
The attempts to mitigate the unprecedented health, economic, and social disruptions caused by the COVID-19 pandemic are largely dependent on establishing compliance to behavioral guidelines and rules that reduce the risk of infection. Here, by conducting an online survey that tested participants’ knowledge about the disease and measured demographic, attitudinal, and cognitive variables, we identify predictors of self-reported social distancing and hygiene behavior. To investigate the cognitive processes underlying health-prevention behavior in the pandemic, we co-opted the dual-process model of thinking to measure participants’ propensities for automatic and intuitive thinking vs. controlled and reflective thinking. Self-reports of 17 precautionary behaviors, including regular hand washing, social distancing, and wearing a face mask, served as a dependent measure. The results of hierarchical regressions showed that age, risk-taking propensity, and concern about the pandemic predicted adoption of precautionary behavior. Variance in cognitive processes also predicted precautionary behavior: participants with higher scores for controlled thinking (measured with the Cognitive Reflection Test) reported less adherence to specific guidelines, as did respondents with a poor understanding of the infection and transmission mechanism of the COVID-19 virus. The predictive power of this model was comparable to an approach (Theory of Planned Behavior) based on attitudes to health behavior. Given these results, we propose the inclusion of measures of cognitive reflection and mental model variables in predictive models of compliance, and future studies of precautionary behavior to establish how cognitive variables are linked with people’s information processing and social norms.
Decisions-makers often have access to a combination of descriptive and experiential information, but limited research so far has explored decisions made using both. Three experiments explore the relationship between task complexity and the influence of descriptions. We show that in simple experiencebased decision-making tasks, providing congruent descriptions has little influence on task performance in comparison to experience alone without descriptions, since learning via experience is relatively easy. In more complex tasks, which are slower and more demanding to learn experientially, descriptions have stronger influence and help participants identify their preferred choices. However, when the task gets too complex to be concisely described, the influence of descriptions is reduced hence showing a non-monotonic pattern of influence of descriptions according to task complexity. We also propose a cognitive model that incorporates descriptive information into the traditional reinforcement learning framework, with the impact of descriptions moderated by task complexity. This model fits the observed behavior better than previous models and replicates the observed non-monotonic relationship between impact of descriptions and task complexity. This research has implications for the development of effective warning labels that rely on simple descriptive information to trigger safer behavior in complex environments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.