How to make loss aversion disappear and reverse: Tests of the decision by sampling origin of loss aversion.

Walasek, Lukasz; Stewart, Neil

doi:10.1037/xge0000039

Cited by 140 publications

(198 citation statements)

References 26 publications

(39 reference statements)

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“…We selected those parameters that mostly closely resembled the original task for this pilot purpose. This range also produced loss aversion in the aforementioned study (λ = 1.79; Walasek and Stewart, 2015) as well as other demonstrations of loss aversion in healthy participants (λ = 1.93; Tom et al, 2007). Thus, it is unlikely that the loss equivalence observed was due to this procedural variation.…”

Section: Discussionsupporting

confidence: 74%

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A pilot study of loss aversion for drug and non-drug commodities in cocaine users

Strickland

Beckmann

Rush

et al. 2017

Drug and Alcohol Dependence

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Background Numerous studies in behavioral economics have demonstrated that individuals are more sensitive to the prospect of a loss than a gain (i.e., loss aversion). Although loss aversion has been well described in “healthy” populations, little research exists in individuals with substance use disorders. This gap is notable considering the prominent role that choice and decision-making play in drug use. The purpose of this pilot study was to evaluate loss aversion in active cocaine users. Methods Current cocaine users (N = 38; 42% female) participated in this within-subjects laboratory pilot study. Subjects completed a battery of tasks designed to assess loss aversion for drug and non-drug commodities under varying risk conditions. Standardized loss aversion coefficients (λ) were compared to theoretically and empirically relevant normative values (i.e., λ = 2). Results Compared to normative loss aversion coefficient values, a precise and consistent decrease in loss aversion was observed in cocaine users (sample λ ≈ 1). These values were observed across drug and non-drug commodities as well as under certain and risky conditions. Conclusions These data represent the first systematic study of loss aversion in cocaine-using populations and provide evidence for equal sensitivity to losses and gains or loss equivalence. Futures studies should evaluate the specificity of these effects to a history of cocaine use as well as the impact of manipulations of loss aversion on drug use to determine how this phenomenon may contribute to intervention development efforts.

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Section: Discussionsupporting

confidence: 74%

“…It is possible that a wider range of loss values would have produced higher rates of systematic responding. However, a recent study found that the gain/loss ranges used could influence λ (Walasek and Stewart, 2015). We selected those parameters that mostly closely resembled the original task for this pilot purpose.…”

Section: Discussionmentioning

confidence: 99%

A pilot study of loss aversion for drug and non-drug commodities in cocaine users

Strickland

Beckmann

Rush

et al. 2017

Drug and Alcohol Dependence

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“…ADO procedures naturally tend to make decisions maximally difficult over trials and change the statistics of the choice set (e.g., the range of gains and losses). Therefore, during ADO-based experiments, participants might be more likely to make random choices with difficult options, behave very differently [62], or experience more negative feelings compared to during non-ADO experiments. To address the concerns, several adjustments have been used: inserting easy trials between tough trials [61], stopping data collection when the same small subset of trials are presented repeatedly, and reducing the number of required trials for convergence by running simulations and identifying an optimal set of choices prior to experimentation [60].…”

Section: Introductionmentioning

confidence: 99%

Challenges and promises for translating computational tools into clinical practice

Ahn

Busemeyer

2016

Current Opinion in Behavioral Sciences

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Computational modeling and associated methods have greatly advanced our understanding of cognition and neurobiology underlying complex behaviors and psychiatric conditions. Yet, no computational methods have been successfully translated into clinical settings. This review discusses three major methodological and practical challenges (A. precise characterization of latent neurocognitive processes, B. developing optimal assays, C. developing large-scale longitudinal studies and generating predictions from multi-modal data) and potential promises and tools that have been developed in various fields including mathematical psychology, computational neuroscience, computer science, and statistics. We conclude by highlighting a strong need to communicate and collaborate across multiple disciplines.

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“…More generally, our data bring a new perspective to the growing body of research on how the environmental distribution of monetary payoffs and probabilities influences how otherwise identical options are evaluated (Birnbaum, ; Ludvig et al, , ; Stewart et al, ; Stewart et al, ; Walasek & Stewart, ). Here we show that people go beyond evaluating options from the given information.…”

Section: Discussionmentioning

confidence: 70%

“…Another, related, reason is that prominent theories of risky choice tend to assume that risks and rewards are treated as independent attributes that determine the subjective value of an option and ultimately choice (von Neumann & Morgenstern, ; Tversky & Kahneman, ). Yet there is a growing body of evidence that people are sensitive to the choice ecologies in which they make decisions (Birnbaum, ; Ludvig et al, , ; Walasek & Stewart, ). Relatedly, people's evaluations of payoffs or probabilities can depend on the marginal distributions of payoffs or probabilities they experienced (Stewart, Chater, & Brown, ).…”

Section: Introductionmentioning

confidence: 99%

Too good to be true? Psychological responses to uncommon options in risk–reward environments

Leuker

Pachur

Hertwig

et al. 2019

Behavioral Decision Making

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Risks and rewards, or payoffs and probabilities, are inversely related in many choice environments. We investigated people's psychological responses to uncommon combinations of risk and reward that deviate from learned regularities (e.g., options that offer a high payoff with an unusually high probability) as they evaluated risky options. In two experiments (N = 183), participants first priced monetary gambles drawn from environments in which risks and rewards were negatively correlated, positively correlated, or uncorrelated. In later trials, they evaluated gambles with uncommon combinations of risk and reward—that is, options that deviated from the respective environment's risk–reward structure. Pricing, response times, and (in Experiment 2) pupil dilation were recorded. In both experiments, participants took more time when responding to uncommon compared to foreseeable options or when the same options were presented in an uncorrelated risk–reward environment. This result was most pronounced when the uncommon gambles offered higher expected values compared to the other gambles in the set. Moreover, these uncommon, high‐value options were associated with an increase in pupil size. These results suggest that people's evaluations of risky options are based not only on the options' payoffs and probabilities but also on the extent to which they fit the risk–reward structure of the environment.

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How to make loss aversion disappear and reverse: Tests of the decision by sampling origin of loss aversion.

Cited by 140 publications

References 26 publications

A pilot study of loss aversion for drug and non-drug commodities in cocaine users

A pilot study of loss aversion for drug and non-drug commodities in cocaine users

Challenges and promises for translating computational tools into clinical practice

Too good to be true? Psychological responses to uncommon options in risk–reward environments

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