scholarly journals Dread Aversion and Economic Preferences

2021 ◽  
Author(s):  
Christopher Dawson ◽  
Samuel Gregory Blane Johnson

We are often preoccupied with the future, experiencing dread at the thought of future misery and savoring the thought of future pleasure. Prior lab studies have found that these anticipatory emotions influence decision-making. In this article, using a novel approach, we use economic survey data to estimate individual differences in anticipatory emotions, finding that the tendency to feel displeasure (dread) from anticipating future losses outweighs the pleasure (savoring) from anticipating equal gains—that is, people are dread-averse. We then relate anticipatory emotions to key economic preferences, finding that more dread-averse people are more risk-averse (because they obtain more disutility from contemplating downside risk) and more impatient (because they want to minimize the time spent contemplating risks). We conclude by considering how dread aversion can provide novel explanations for a variety of intertemporal and risky choice phenomena. Dread aversion explains why people are both risk-averse and impatient and provides suggestive evidence as to why these traits are linked.

2020 ◽  
Author(s):  
Kaileigh A. Byrne ◽  
Stephanie Gabrielle Six ◽  
Reza Ghaiumy Anaraky ◽  
Maggie W. Harris ◽  
Emma L. Winterlind

To reduce the spread of COVID-19 transmission, government agencies in the United States (US) have recommended COVID prevention guidelines, including wearing masks and social distancing. However, compliance with these guidelines have been inconsistent. This study examined whether individual differences in decision-making and motivational propensities predicted compliance with COVID-19 preventative behaviors in a representative sample of US adults (N=225). Participants completed an online study in September 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 risky decision-making behavior and temporal discounting were associated with less appropriate mask-wearing behavior and social distancing. Additionally, demographic factors, including political affiliation and income level, 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 61% 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.


2018 ◽  
Vol 122 (4) ◽  
pp. 1412-1431 ◽  
Author(s):  
Marco Lauriola ◽  
Angelo Panno ◽  
Joshua A. Weller

People who anticipate the potential regret of one’s decisions are believed to act in a more risk-averse manner and, thus, display fewer risk-taking behaviors across many domains. We conducted two studies to investigate whether individual differences in regret-based decision-making (a) reflect a unitary cognitive-style dimension, (b) are stable over time, and (c) predict later risk-taking behavior. In Study 1, 332 participants completed a regret-based decision-making style scale (RDS) to evaluate its psychometric qualities. In Study 2, participants ( N = 119) were tested on two separate occasions to assess the association between RDS and risk-taking. At Time 1, participants completed the RDS, as well as trait measures of anxiety and depression. One month later, they completed the Balloon Analogue Risk Task (BART) and state mood (Positive/Negative affect) scales. The RDS had a sound unidimensional factorial structure and was stable over time. Further, higher reported RDS scores were significantly associated with less risk-taking on the BART, holding other variables constant. These studies suggest that individual differences in regret-based decision-making may lead to a more cautious approach to real-world risk behaviors.


PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251073
Author(s):  
Kaileigh A. Byrne ◽  
Stephanie G. Six ◽  
Reza Ghaiumy Anaraky ◽  
Maggie W. Harris ◽  
Emma L. Winterlind

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.


2017 ◽  
Author(s):  
Andrea Kóbor ◽  
Ádám Takács ◽  
Karolina Janacsek ◽  
Zsófia Kardos ◽  
Valéria Csépe ◽  
...  

AbstractProbabilistic sequence learning involves a set of robust mechanisms that enable the extraction of statistical patterns embedded in the environment. It contributes to different perceptual and cognitive processes as well as to effective behavior adaptation, which is a crucial aspect of decision making. Although previous research attempted to model reinforcement learning and reward sensitivity in different risky decision-making paradigms, the basic mechanism of the sensitivity to statistical regularities has not been anchored to external tasks. Therefore, the present study aimed to investigate the statistical learning mechanism underlying individual differences in risky decision making. To reach this goal, we tested whether implicit probabilistic sequence learning and risky decision making share common variance. To have a more complex characterization of individual differences in risky decision making, hierarchical cluster analysis was conducted on performance data obtained in the Balloon Analogue Risk Task (BART) in a large sample of healthy young adults. Implicit probabilistic sequence learning was measured by the Alternating Serial Reaction Time (ASRT) task. According to the results, a four-cluster structure was identified involving average risk-taking, slowly responding, risk-taker, and risk-averse groups of participants, respectively. While the entire sample showed significant learning on the ASRT task, we found greater sensitivity to statistical regularities in the risk-taker and risk-averse groups than in participants with average risk-taking. These findings revealed common mechanisms in risky decision making and implicit probabilistic sequence learning and an adaptive aspect of higher risk taking on the BART. Our results could help to clarify the neurocognitive complexity of decision making and its individual differences.


2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.


1994 ◽  
Author(s):  
Susan L. Joslyn ◽  
Earl Hunt ◽  
Tom Sanquist

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