The elusive search for stable risk preferences

Prefrontal control of social influence in risk decision making

To optimize our decisions, we may change our mind by utilizing social information. Here, we examined how changes of mind were modulated by Social Misalignment Sensitivity (SMS), egocentric tendency, and decision preferences in a decision-making paradigm including both risk and social information. Combining functional magnetic resonance imaging with computational modeling, we showed that both SMS and egocentric tendency modulated changes of mind under the influence of social information. While SMS was represented in the dorsal anterior cingulate cortex (dACC) and superior parietal gyrus (SPG) in the socially aligned situation, a distributed brain network was activated in the misaligned condition, including not only the dACC and SPG but also superior frontal gyrus and precuneus. These results suggest that SMS is related to a monitoring brain system, the scope of which varies according to the level of misalignment with social majority. The dorsolateral prefrontal cortex selectively interacted with SMS among the participants with a low switching threshold, indicating that its regulation on SMS may be sensitive to inter-individual variation. Our findings highlight the predominant roles of SMS and the prefrontal control system towards changes of mind under social influence.

The Car Cushion Hypothesis: Bigger Cars Lead to More Risk Taking-Evidence from Behavioural Data

Car traffic and accidents involving cars create an enormous societal cost, particularly in terms of negative consequences for public health. Mitigating these effects is a daily concern for public and private institutions and people around the world. At least a subset of accidents is attributable to the amount of risk drivers allow in their driving and in related behaviour like mobile phone use or substance abuse. Our study looks at the effect of car size on risk taking. While literature highlights several behavioural effects of car size, the direction of causality of these effects is not always clear, and empirical evidence is lacking. Two behavioural and consequential studies support that car size affects risk taking in driving and that this increase in risk taking generalizes to other domains as well. Based on these results and in line with literature showing that social stability and security can affect financial risk taking, we propose the "car cushion hypothesis." This hypothesis suggests that bigger cars make people feel more secure, which affects their behaviour in terms of generalized risk taking. We discuss policy implications aimed at contributing to reducing the societal and public health cost of car traffic.

Personality Profile of Risk-Takers

Abstract. Risk-taking is a long-standing area of inquiry among psychologists and economists. In this paper, we examine the personality profile of risk-takers in two independent samples. Specifically, we examined the association between the Big Five facets and risk-taking propensity across two measures: The Domain-Specific Risk-Taking Scale (DOSPERT) and the General Risk Propensity Scale (GRiPS). At the Big Five domain level, we found that extraversion and agreeableness were the primary predictors of risk-taking. However, facet-level analyses revealed that responsibility, a facet of conscientiousness, explained most of the total variance accounted for by the Big Five in both risk-taking measures. Based on our findings across two samples ( n = 764), we find that the personality profile of a risk-taker is extraverted, open to experiences, disagreeable, emotionally stable, and irresponsible. Implications for the risk measurement are discussed.

Gender Matter, Social Phobia and High-Risk Behaviors in Young Medical Students

Background

Young is one of the most sensitive stages of human life. Social phobia and high-risk behaviors are factors that enhance young crises. This study aimed to determine the relationship between gender role, social phobia and high-risk behaviors among young medical students.

Methods

In this descriptive correlational study, 400 students were selected by quota sampling method from a medical university in Southeastern Iran. For data collection, the demographic information questionnaire, Gender Trait Index (GTI), Social Phobia Inventory (SPIN), and Iranian Adolescent and Young Risk-Taking Scale (IAYRS) were used. Data were analyzed using descriptive statistics including mean and SD and analytic statistics such as Kolmogorov-Smirnov, Mann-Whitney U and Kruskal-Wallis tests using SPSS 25 and p ≤ .05.

Results

The mean scores of masculinity and femininity gender roles were 38.98 ± 7.92 and 44.12 ± 7.76, respectively. Also, 70.5% of the students had dominant feminine traits, and the gender identity was high in 58.8% of the students and moderate in 40.2% of them. Social phobia (37.12 ± 12.61) and high-risk behaviors (81.77 ± 26.08) were moderate. A significant inverse relationship was found between masculine traits and social phobia (p <0.001). Another significant inverse relationship was observed between feminine traits and high-risk behaviors (p <0.05).

Conclusion

Given the poor relationship between gender role, social phobia and high-risk behaviors, it is essential to conduct further studies to determine the predictors of social phobia and high-risk behaviors in medical students.

Age Group Differences in Household Accident Risk Perceptions and Intentions to Reduce Hazards

Very little is known about the extent to which seemingly vulnerable younger and older adults appraise household risks and relatedly whether safety information focused on raising risk awareness influences intentions to reduce hazards in the home. The present study assessed age differences in accident experience, risk attitudes, household accident risk perceptions, comparative optimism, personal control, efficacy judgements, and intentions to remove household hazards. It also examined the predictors of these intentions. Thirty-eight younger adults (aged 18 to 25) and forty older adults (aged 65 to 87) completed study booklets containing all measures. There were significant age group differences for all accident experience and risk-related variables. Younger adults experienced more accidents, had riskier attitudes, and had significantly lower cognitive risk perceptions (i.e., they were less likely to be injured due to a household accident). They also had lower affective risk perceptions (i.e., they were less worried) about their accident risk and perceived more personal control over the risk compared with older adults. Young adults were comparatively optimistic about their risk while older adults were pessimistic. Older adults had higher response efficacy and intentions to reduce hazards in the home. Only worry, response efficacy, and risk attitudes predicted intention, however, these relationships were not moderated by age or efficacy appraisal. Although tentative theoretical and practical implications are presented, further research is required in order to better understand the objective and subjective risk associated with household accidents, and to determine the factors that may improve safety, particularly for those most vulnerable.

Risk Taking Runners Slow More in the Marathon

Much research has explored the physiological, energetic, environmental, and psychological factors that influence pacing in endurance events. Although this research has generally neglected the role of psychological variation across individuals, recent studies have hinted at its importance. Here we conducted an online survey of over 1,300 marathon runners, testing whether any of five psychological constructs - competitiveness, goal achievement, risk taking in pace (RTP), domain-specific risk taking, and willingness to suffer in the marathon - predicted slowing in runners' most recent marathons. Analyses revealed that RTP - the extent to which runners agreed that they began the marathon at a pace that was so fast that it would jeopardize their capacity to maintain this pace throughout the event - was a robust predictor of marathon slowing. RTP proved a substantial predictor even in regression models controlling for the other psychological constructs, training, experience, and other known pacing correlates. This result suggests that marathoners consider trade-offs when making pacing decisions, and that individuals vary in their pacing decision making.

Medical Marijuana and Marijuana Legalization

State-level marijuana liberalization policies have been evolving for the past five decades, and yet the overall scientific evidence of the impact of these policies is widely believed to be inconclusive. In this review we summarize some of the key limitations of the studies evaluating the effects of decriminalization and medical marijuana laws on marijuana use, highlighting their inconsistencies in terms of the heterogeneity of policies, the timing of the evaluations, and the measures of use being considered. We suggest that the heterogeneity in the responsiveness of different populations to particular laws is important for interpreting the mixed findings from the literature, and we highlight the limitations of the existing literature in providing clear insights into the probable effects of marijuana legalization.

Behavioral preference in sequential decision-making and its association with anxiety

In daily life, people often make consecutive decisions before the ultimate goal is reached (i.e., sequential decision-making). However, this kind of decision-making has been largely overlooked in the literature. The current study investigated whether behavioral preference would change during sequential decisions, and the neural processes underlying the potential changes. For this purpose, we revised the classic balloon analogue risk task and recorded the electroencephalograph (EEG) signals associated with each step of decision-making. Independent component analysis performed on EEG data revealed that four EEG components elicited by periodic feedback in the current step predicted participants' decisions (gamble vs. no gamble) in the next step. In order of time sequence, these components were: bilateral occipital alpha rhythm, bilateral frontal theta rhythm, middle frontal theta rhythm, and bilateral sensorimotor mu rhythm. According to the information flows between these EEG oscillations, we proposed a brain model that describes the temporal dynamics of sequential decision-making. Finally, we found that the tendency to gamble (as well as the power intensity of bilateral frontal theta rhythms) was sensitive to the individual level of trait anxiety in certain steps, which may help understand the role of emotion in decision-making.

A Walk on the Wild Side: The Impact of Music on Risk-Taking Likelihood

From a marketing perspective, there has been substantial interest in on the role of risk-perception on consumer behavior. Specific ‘problem music’ like rap and heavy metal has long been associated with delinquent behavior, including violence, drug use, and promiscuous sex. Although individuals’ risk preferences have been investigated across a range of decision-making situations, there has been little empirical work demonstrating the direct role music may have on the likelihood of engaging in risky activities. In the exploratory study reported here, we assessed the impact of listening to different styles of music while assessing risk-taking likelihood through a psychometric scale. Risk-taking likelihood was measured across ethical, financial, health and safety, recreational and social domains. Through the means of a canonical correlation analysis, the multivariate relationship between different music styles and individual risk-taking likelihood across the different domains is discussed. Our results indicate that listening to different types of music does influence risk-taking likelihood, though not in areas of health and safety.

Learning about and from others' prudence, impatience or laziness: The computational bases of attitude alignment

Peoples' subjective attitude towards costs such as, e.g., risk, delay or effort are key determinants of inter-individual differences in goal-directed behaviour. Thus, the ability to learn about others' prudent, impatient or lazy attitudes is likely to be critical for social interactions. Conversely, how adaptive such attitudes are in a given environment is highly uncertain. Thus, the brain may be tuned to garner information about how such costs ought to be arbitrated. In particular, observing others' attitude may change one's uncertain belief about how to best behave in related difficult decision contexts. In turn, learning from others' attitudes is determined by one's ability to learn about others' attitudes. We first derive, from basic optimality principles, the computational properties of such a learning mechanism. In particular, we predict two apparent cognitive biases that would arise when individuals are learning about others’ attitudes: (i) people should overestimate the degree to which they resemble others (false-consensus bias), and (ii) they should align their own attitudes with others’ (social influence bias). We show how these two biases non-trivially interact with each other. We then validate these predictions experimentally by profiling people's attitudes both before and after guessing a series of cost-benefit arbitrages performed by calibrated artificial agents (which are impersonating human individuals).

What do people learn from observing others' attitudes, such as "prudence", "impatience" or "laziness"? Rather than viewing these attitudes as examples of highly subjective personality traits, we assume that they derive from uncertain (and mostly implicit) beliefs about how to best weigh risks, delays and efforts in ensuing cost-benefit trade-offs. In this view, it is adaptive to update one's belief after having observed others' attitude, which provides valuable information regarding how to best behave in related difficult decision contexts. This is the starting point of our computational model of attitude alignment, which we derive from first optimality principles as well as from recent neuroscientific findings. Critical here is the impact of one's ability to learn about others' covert mental states or attitudes, which is known as "mentalizing" or "Theory of Mind". In particular, this model makes two (otherwise unrelated) predictions that conform to known but puzzling cognitive biases of social cognition in humans, namely: "false consensus" and "social influence". It also shows how attitude alignment may eventually follow from the interaction between these two biases. Using state-of-the-art behavioural and computational methods, we provide experimental evidence that confirm these predictions. Finally, we discuss the relevance and implications of this work, both from a neuroscientific and economic perspective.

Motivational Affordance and Risk-Taking Across Decision Domains

We propose a motivational affordance account to explain both stability and variability in risk-taking propensity in major decision domains. We draw on regulatory focus theory to differentiate two types of motivation (prevention, promotion) that play a key role in predicting risk-taking. Study 1 demonstrated that prevention motivation is negatively associated with risk-taking across six key decision domains, including health/safety, ethics, recreation, gambling, investment, and social. In contrast, promotion motivation is positively associated with risk-taking in the social and investment domains. Study 2 replicated the same pattern and provided direct evidence that promotion motivation is a strong predictor of risk-taking only in domains where there is true potential for gains. Study 3 manipulated promotion (vs. prevention) motivation experimentally to demonstrate that motivational affordance is a critical mechanism for understanding risk-taking behaviors.

Predicting risky choices from brain activity patterns

Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights.

Developmental reversals in risky decision making: intelligence agents show larger decision biases than college students

Intelligence agents make risky decisions routinely, with serious consequences for national security. Although common sense and most theories imply that experienced intelligence professionals should be less prone to irrational inconsistencies than college students, we show the opposite. Moreover, the growth of experience-based intuition predicts this developmental reversal. We presented intelligence agents, college students, and postcollege adults with 30 risky-choice problems in gain and loss frames and then compared the three groups' decisions. The agents not only exhibited larger framing biases than the students, but also were more confident in their decisions. The postcollege adults (who were selected to be similar to the students) occupied an interesting middle ground, being generally as biased as the students (sometimes more biased) but less biased than the agents. An experimental manipulation testing an explanation for these effects, derived from fuzzy-trace theory, made the students look as biased as the agents. These results show that, although framing biases are irrational (because equivalent outcomes are treated differently), they are the ironical output of cognitively advanced mechanisms of meaning making.

Predicting risk-taking behavior from prefrontal resting-state activity and personality

Risk-taking is subject to considerable individual differences. In the current study, we tested whether resting-state activity in the prefrontal cortex and trait sensitivity to reward and punishment can help predict risk-taking behavior. Prefrontal activity at rest was assessed in seventy healthy volunteers using electroencephalography, and compared to their choice behavior on an economic risk-taking task. The Behavioral Inhibition System/Behavioral Activation System scale was used to measure participants' trait sensitivity to reward and punishment. Our results confirmed both prefrontal resting-state activity and personality traits as sources of individual differences in risk-taking behavior. Right-left asymmetry in prefrontal activity and scores on the Behavioral Inhibition System scale, reflecting trait sensitivity to punishment, were correlated with the level of risk-taking on the task. We further discovered that scores on the Behavioral Inhibition System scale modulated the relationship between asymmetry in prefrontal resting-state activity and risk-taking. The results of this study demonstrate that heterogeneity in risk-taking behavior can be traced back to differences in the basic physiology of decision-makers' brains, and suggest that baseline prefrontal activity and personality traits might interplay in guiding risk-taking behavior.

Dual conception of risk in the Iowa Gambling Task: effects of sleep deprivation and test-retest gap

Risk in the Iowa Gambling Task (IGT) is often understood in terms of intertemporal choices, i.e., preference for immediate outcomes in favor of delayed outcomes is considered risky decision making. According to behavioral economics, healthy decision makers are expected to refrain from choosing the short-sighted immediate gain because, over time (10 trials of the IGT), the immediate gains result in a long term loss (net loss). Instead decision makers are expected to maximize their gains by choosing options that, over time (10 trials), result in delayed or long term gains (net gain). However, task choices are sometimes made on the basis of the frequency of reward and punishment such that frequent rewards/infrequent punishments are favored over infrequent rewards/frequent punishments. The presence of these two attributes (intertemporality and frequency of reward) in IGT decision making may correspond to the emotion-cognition dichotomy and reflect a dual conception of risk. Decision making on the basis of the two attributes was tested under two conditions: delay in retest and sleep deprivation. An interaction between sleep deprivation and time delay was expected to attenuate the difference between the two attributes. Participants were 40 male university students. Analysis of the effects of IGT attribute type (intertemporal vs. frequency of reinforcement), sleep deprivation (sleep deprivation vs. no sleep deprivation), and test-retest gap (short vs. long delay) showed a significant within-subjects effect of IGT attribute type thus confirming the difference between the two attributes. Sleep deprivation had no effect on the attributes, but test-retest gap and the three-way interaction between attribute type, test-retest gap, and sleep deprivation were significantly different. Post-hoc tests revealed that sleep deprivation and short test-retest gap attenuated the difference between the two attributes. Furthermore, the results showed an expected trend of increase in intertemporal decision making at retest suggesting that intertemporal decision making benefited from repeated task exposure. The present findings add to understanding of the emotion-cognition dichotomy. Further, they show an important time-dependent effect of a universally experienced constraint (sleep deprivation) on decision making. It is concluded that risky decision making in the IGT is contingent on the attribute under consideration and is affected by factors such as time elapsed and constraint experienced before the retest.

Decreasing ventromedial prefrontal cortex activity during sequential risk-taking: an FMRI investigation of the balloon analog risk task

Functional imaging studies examining the neural correlates of risk have mainly relied on paradigms involving exposure to simple chance gambles and an economic definition of risk as variance in the probability distribution over possible outcomes. However, there is little evidence that choices made during gambling tasks predict naturalistic risk-taking behaviors such as drug use, extreme sports, or even equity investing. To better understand the neural basis of naturalistic risk-taking, we scanned participants using fMRI while they completed the Balloon Analog Risk Task, an experimental measure that includes an active decision/choice component and that has been found to correlate with a number of naturalistic risk-taking behaviors. In the task, as in many naturalistic settings, escalating risk-taking occurs under uncertainty and might be experienced either as the accumulation of greater potential rewards, or as exposure to increasing possible losses (and decreasing expected value). We found that areas previously linked to risk and risk-taking (bilateral anterior insula, anterior cingulate cortex, and right dorsolateral prefrontal cortex) were activated as participants continued to inflate balloons. Interestingly, we found that ventromedial prefrontal cortex (vmPFC) activity decreased as participants further expanded balloons. In light of previous findings implicating the vmPFC in value calculation, this result suggests that escalating risk-taking in the task might be perceived as exposure to increasing possible losses (and decreasing expected value) rather than the increasing potential total reward relative to the starting point of the trial. A better understanding of how neural activity changes with risk-taking behavior in the task offers insight into the potential neural mechanisms driving naturalistic risk-taking.

Measuring Risk Literacy: The Berlin Numeracy Test

We introduce the Berlin Numeracy Test, a new psychometrically sound instrument that quickly assesses statistical numeracy and risk literacy. We present 21 studies (n=5336) showing robust psychometric discriminability across 15 countries (e.g., Germany, Pakistan, Japan, USA) and diverse samples (e.g., medical professionals, general populations, Mechanical Turk web panels). Analyses demonstrate desirable patterns of convergent validity (e.g., numeracy, general cognitive abilities), discriminant validity (e.g., personality, motivation), and criterion validity (e.g., numerical and non-numerical questions about risk). The Berlin Numeracy Test was found to be the strongest predictor of comprehension of everyday risks (e.g., evaluating claims about products and treatments; interpreting forecasts), doubling the predictive power of other numeracy instruments and accounting for unique variance beyond other cognitive tests (e.g., cognitive reflection, working memory, intelligence). The Berlin Numeracy Test typically takes about three minutes to complete and is available in multiple languages and formats, including a computer adaptive test that automatically scores and reports data to researchers (http://www.riskliteracy.org). The online forum also provides interactive content for public outreach and education, and offers a recommendation system for test format selection. Discussion centers on construct validity of numeracy for risk literacy, underlying cognitive mechanisms, and applications in adaptive decision support.