Literature DB >> 33983970

Risk-taking unmasked: Using risky choice and temporal discounting to explain COVID-19 preventative behaviors.

Kaileigh A Byrne1, Stephanie G Six1, Reza Ghaiumy Anaraky2, Maggie W Harris1, Emma L Winterlind1.   

Abstract

To reduce the spread of COVID-19 transmission, government agencies in the United States (US) recommended precautionary guidelines, including wearing masks and social distancing to encourage the prevention of the disease. However, compliance with these guidelines has been inconsistent. This correlational study examined whether individual differences in risky decision-making and motivational propensities predicted compliance with COVID-19 preventative behaviors in a sample of US adults (N = 404). Participants completed an online study from September through December 2020 that included a risky choice decision-making task, temporal discounting task, and measures of appropriate mask-wearing, social distancing, and perceived risk of engaging in public activities. Linear regression results indicated that greater temporal discounting and risky decision-making were associated with less appropriate mask-wearing behavior and social distancing. Additionally, demographic factors, including personal experience with COVID-19 and financial difficulties due to COVID-19, were also associated with differences in COVID-19 preventative behaviors. Path analysis results showed that risky decision-making behavior, temporal discounting, and risk perception collectively predicted 55% of the variance in appropriate mask-wearing behavior. Individual differences in general decision-making patterns are therefore highly predictive of who complies with COVID-19 prevention guidelines.

Entities:  

Mesh:

Year:  2021        PMID: 33983970      PMCID: PMC8118306          DOI: 10.1371/journal.pone.0251073

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  47 in total

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7.  Reduced social distancing early in the COVID-19 pandemic is associated with antisocial behaviors in an online United States sample.

Authors:  Katherine O'Connell; Kathryn Berluti; Shawn A Rhoads; Abigail A Marsh
Journal:  PLoS One       Date:  2021-01-07       Impact factor: 3.240

8.  Evaluating Amazon's Mechanical Turk as a tool for experimental behavioral research.

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9.  Decomposing the roles of perseveration and expected value representation in models of the Iowa gambling task.

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  8 in total

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Journal:  PLoS One       Date:  2022-01-24       Impact factor: 3.240

3.  Viruses, Vaccines, and COVID-19: Explaining and Improving Risky Decision-making.

Authors:  Valerie F Reyna; David A Broniatowski; Sarah M Edelson
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4.  Implementation of a Rural Community Diagnostic Testing Strategy for SARS-CoV-2 in Upstate South Carolina.

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6.  Patient-reported factors associated with avoidance of in-person care during the COVID-19 pandemic: Results from a national survey.

Authors:  Bengt B Arnetz; Courtney Goetz; John vanSchagen; William Baer; Stacy Smith; Judith E Arnetz
Journal:  PLoS One       Date:  2022-08-05       Impact factor: 3.752

7.  Delay discounting of money and health outcomes, and adherence to policy guidelines during the COVID-19 pandemic.

Authors:  Jakub M Krawiec; Szymon Mizak; Marco Tagliabue; Wojciech Białaszek
Journal:  Front Public Health       Date:  2022-08-22

8.  Thinking of future as an older individual increases perceived risks for age-related diseases but not for COVID-19.

Authors:  Dario Monzani; Marco Marinucci; Luca Pancani; Patrice Rusconi; Davide Mazzoni; Gabriella Pravettoni
Journal:  Int J Psychol       Date:  2021-06-24
  8 in total

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