Complexity aversion in risky choices and valuations: Moderators and possible causes

In the age of digitalization and globalization, an abundance of information is available, and our decision environments have become increasingly complex. However, it remains unclear under what circumstances complexity affects risk taking. In two experiments with monetary lotteries (one with a stratified national sample), we investigate behavioral effects and provide a cognitive explanation for the impact of complexity on risk taking. Results show that complexity, defined as the number of possible outcomes of a risky lottery, decreased the choice probability of an option but had a smaller and less consistent effect when evaluating lotteries independently. Importantly, choices of participants who spent more time looking at the complex option were less affected by complexity. A tendency to avoid cognitive effort can explain these effects, as the effort associated with evaluating the complex option can be sidestepped in choice tasks, but less so in valuation tasks. Further, the effect of complexity on valuations was influenced by individual differences in cognitive ability, such that people with higher cognitive ability showed less complexity aversion. Together, the results show that the impact of complexity on risk taking depends on both, decision format and individual differences and we discuss cognitive processes that could give rise to these effects

Psychophysiological arousal and inter- and intraindividual differences in risk-sensitive decision making.

This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1111/psyp.12627The current study assessed peripheral responses during decision making under explicit risk, and tested whether intraindividual variability in choice behavior can be explained by fluctuations in peripheral arousal. Electrodermal activity (EDA) and heart rate (HR) were monitored in healthy volunteers (N = 68) during the Roulette Betting Task. In this task, participants were presented with risky gambles to bet on, with the chances of winning varying across trials. Hierarchical Bayesian analyses demonstrated that EDA and HR acceleration responses during the decision phase were sensitive to the chances of winning. Interindividual differences in this peripheral reactivity during risky decision making were related to trait sensitivity to punishment and trait sensitivity to reward. Moreover, trial-by-trial variation in EDA and HR acceleration responses predicted a small portion of intraindividual variability in betting choices. Our results show that psychophysiological responses are sensitive to explicit risk and can help explain intraindividual heterogeneity in choice behavior.This work was completed within the Behavioural and Clinical Neuroscience Institute, supported by a consortium award from the Medical Research Council and Wellcome Trust. The Centre for Gambling Research at UBC is supported by funding from the British Columbia Lottery Corporation and the Province of British Columbia government

What's in a sample? Epistemic uncertainty and metacognitive awareness in risk taking

In a fundamentally uncertain world, sound information processing is a prerequisite for effective behavior. Given that information processing is subject to inevitable cognitive imprecision, decision makers should adapt to this imprecision and to the resulting epistemic uncertainty when taking risks. We tested this metacognitive ability in two experiments in which participants estimated the expected value of different number distributions from sequential samples and then bet on their own estimation accuracy. Results show that estimates were imprecise, and this imprecision increased with higher distributional standard deviations. Importantly, participants adapted their risk-taking behavior to this imprecision and hence deviated from the predictions of Bayesian models of uncertainty that assume perfect integration of information. To explain these results, we developed a computational model that combines Bayesian updating with a metacognitive awareness of cognitive imprecision in the integration of information. Modeling results were robust to the inclusion of an empirical measure of participants' perceived variability. In sum, we show that cognitive imprecision is crucial to understanding risk taking in decisions from experience. The results further demonstrate the importance of metacognitive awareness as a cognitive building block for adaptive behavior under (partial) uncertainty. [Abstract copyright: Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.

A hierarchical Bayesian model of the influence of run length on sequential predictions

Two models of how people predict the next outcome in a sequence of binary events were developed and compared on the basis of gambling data from a lab experiment using hierarchical Bayesian techniques. The results from a student sample (N = 39) indicated that a model that considers run length ("drift model”)—that is, how often the same event has previously occurred in a row—provided a better description of the data than did a stationary model taking only the immediately prior event into account. Both, expectation of negative and of positive recency was observed, and these tendencies mostly grew stronger with run length. For some individuals, however, the relationship was reversed, leading to a qualitative shift from expecting positive recency for short runs to expecting negative recency for long runs. Both patterns could be accounted for by the drift model but not the stationary model. The results highlight the importance of applying hierarchical analyses that provide both group- and individual-level estimates. Further extensions and applications of the approach in the context of the prediction literature are discussed

Change and status quo in decisions with defaults: The effect of incidental emotions depends on the type of default

Affective states can change how people react to measures aimed at influencing their decisions such as providing a default option. Previous research has shown that when defaults maintain the status quo positive mood increases reliance on the default and negative mood decreases it. Similarly, it has been demonstrated that positive mood enhances the preference for inaction. We extend this research by investigating how mood states influence reliance on the default if the default leads to a change, thus pitting preference for status quo against a preference for inaction. Specifically, we tested in an online study how happiness and sadness influenced reliance on two types of default (1) a default maintaining status quo and (2) a default inducing change. Our results suggest that the effect of emotions depends on the type of default: people in a happy mood were more likely than sad people to follow a default when it maintained status quo but less likely to follow a default when it introduced change. These results are in line with mood maintenance theory

Valuation and estimation from experience

The processing of sequentially presented numerical information is a prerequisite for decisions from experience, where people learn about potential outcomes and their associated probabilities and then make choices between gambles. Little is known, however, about how people's preference for choosing a gamble is affected by how they perceive and process numerical information. To address this, we conducted a series of experiments wherein participants repeatedly sampled numbers from continuous outcome distributions. They were incentivized either to estimate the means of the numbers or to state their minimum selling prices to forgo a consequential draw from the distributions (i.e., the certainty equivalents or valuations). We found that participants valued distributions below their means, valued high-variance sequences lower than low-variance sequences, and valued left-skewed sequences lower than right-skewed sequences. Though less pronounced, similar patterns occurred in the mean estimation task where preferences should not play a role. These results are not consistent with prior findings in decision from experience such as the overweighting of high numbers and the underweighting of rare events. Rather, the qualitative effects, as well as the similarity of effects in valuation and estimation, are consistent with the assumption that people process numbers on a compressed mental number line in valuations from experience

Bayesian Inference for Correlations in the Presence of Measurement Error and Estimation Uncertainty

Whenever parameter estimates are uncertain or observations are contaminated by measurement error, the Pearson correlation coefficient can severely underestimate the true strength of an association. Various approaches exist for inferring the correlation in the presence of estimation uncertainty and measurement error, but none are routinely applied in psychological research. Here we focus on a Bayesian hierarchical model proposed by Behseta, Berdyyeva, Olson, and Kass (2009) that allows researchers to infer the underlying correlation between error-contaminated observations. We show that this approach may be also applied to obtain the underlying correlation between uncertain parameter estimates as well as the correlation between uncertain parameter estimates and noisy observations. We illustrate the Bayesian modeling of correlations with two empirical data sets; in each data set, we first infer the posterior distribution of the underlying correlation and then compute Bayes factors to quantify the evidence that the data provide for the presence of an association.Multivariate analysis of psychological dat

Effects of meal variety on expected satiation : evidence for a 'perceived volume' heuristic

Meal variety has been shown to increase energy intake in humans by an average of 29%. Historically, research exploring the mechanism underlying this effect has focused on physiological and psychological processes that terminate a meal (e.g., sensory-specific satiety). We sought to explore whether meal variety stimulates intake by influencing pre-meal planning. We know that individuals use prior experience with a food to estimate the extent to which it will deliver fullness. These ‘expected satiation’ judgments may be straightforward when only one meal component needs to be considered, but it remains unclear how prospective satiation is estimated when a meal comprises multiple items. We hypothesised that people simplify the task by using a heuristic, or ‘cognitive shortcut.’ Specifically, as within-meal variety increases, expected satiation tends to be based on the perceived volume of food(s) rather than on prior experience. In each trial, participants (N = 68) were shown a plate of food with six buffet food items. Across trials the number of different foods varied in the range one to six. In separate tasks, the participants provided an estimate of their combined expected satiation and volume. When meal variety was high, judgments of perceived volume and expected satiation ‘converged.’ This is consistent with a common underlying response strategy. By contrast, the low variety meals produced dissociable responses, suggesting that judgments of expected satiation were not governed solely by perceived volume. This evidence for a ‘volume heuristic’ was especially clear in people who were less familiar with the meal items. Together, these results are important because they expose a novel process by which meal variety might increase food intake in humans

Facilitating healthy dietary habits:An experiment with a low income population

First published online: October 2020This paper tests an intervention aimed at facilitating (cognitively) the adoption of healthy dietary habits. We provide easy-to-understand information about the risks of developing diabetes or heart diseases and give easy-to-follow dietary recommendations to minimize these risks. We implement two variations, one consisting of generic information, the other consisting of information tailored to the individual, the latter resembling newly developed online health assessment tools. On top of the information treatment, we implement a second experimental variation encouraging people to spend more time thinking about their decisions. We find evidence that the information intervention leads to healthier choices in the short run, but mostly in the generic treatment. Surprisingly, we find that people are on average pessimistic about their health, and therefore receive good news on average when the information is tailored to them. We find no evidence that increasing the time available to make choices leads to healthier choices, and find no evidence of long-term changes in habits. These results do not support a bounded rationality explanation for poor dietary choices. (C) 2020 Elsevier B.V. All rights reserved