Engel, C., J. Golder, and R.-M. Rahal. 2026. “ Who Is Afraid of the Pink Elephant? Evidence on (Not) Ignoring Inadmissible Evidence and Debiasing Interventions.” Journal of Behavioral Decision Making 39, no. 1: e70064. https://doi.org/10.1002/bdm.70064.
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Open access funding was provided by the Wirtschaftsuniversitat Wien/KEMÖ.
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Danwitz, L., L. Hornuf, S. Fehrler, et al. 2025. “ Similarity and Consistency in Algorithm-Guided Exploration.” Journal of Behavioral Decision Making 38, no. 5: e70055. https://doi.org/10.1002/bdm.70055.
The displayed order of authors was incorrectly published as: “Ludwig Danwitz, Lars Hornuf, Sebastian Fehrler, Hsuan-Yu Lin, Yongping Bao, Fabian Dvorak, Bettina von Helversen”.
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The asymmetric subjective opportunity cost (ASOC) effect in intertemporal choice refers to the increase of an individual's preference for a larger and later (LL) option when the opportunity cost of the smaller and sooner (SS) option is highlighted compared to when it is not, while the individual's intertemporal preference is unaffected when the opportunity cost of the LL option is highlighted. This study, based on the attribute-based models, investigated the attentional mechanism by which opportunity costs implication influence intertemporal choice in conjunction with the eye-tracking method. Results showed that when the opportunity cost of the SS option was highlighted, participants were more likely to choose the LL option; the mean gaze time of the delay dimension was decreased, and the proportion of the gaze time in the money dimension relative to the delay dimension to the total gaze time increased; both variables mediated the impact of highlighting the opportunity cost of the SS option on intertemporal choice. This study explored the asymmetric subjective opportunity cost effect from the perspective of dimensional attention and adds evidence to the explanatory power of attribute-based models for intertemporal choices.
Sequential collaboration describes an aggregation process intensively researched for numerical judgments which is characterized by a first contributor creating a judgment that is subsequently adjusted or maintained by following contributors. In previous research, participants performing sequential collaboration were only provided with information about the judgment of the person immediately preceding them in a sequential chain. However, in real-world collaborative projects (e.g., Wikipedia and Google Docs projects), more information about the past development of a sequential chain is often accessible or even directly displayed. As a concise piece of such information, we used judgment invariance, that is, the number of times a current judgment remained unchanged in the immediately preceding steps of a sequential chain. We hypothesized that increasing judgment invariance decreases both the probability and the magnitude of participants' judgment changes. Additionally, we hypothesized that the influence would be weakened with increasing expertise of participants. In three preregistered experiments, (G)LMM analyses suggested that increasing judgment invariance decreased the probability and magnitude of judgment changes confirming our hypothesized main effects. Concerning the interaction hypothesis of judgment invariance and expertise, a more ambiguous picture emerged. Experiment 1 was completely consistent with the interaction hypothesis. Experiment 2 supported it concerning the probability but not the magnitude of participants' judgment changes. In Experiment 3, a directionally reversed interaction effect was observed, possibly due to unconscientious participation. We conclude that the insight into the past development of a sequential chain, specifically information on judgment invariance, influences the judgment behavior of contributors in sequential collaborations. In summary, judgment invariance could be established as a substantial influence in sequential collaboration, which comes with practical implications for real-world collaborative projects.
People are often unable or unwilling to ignore thoughts they should disregard. This issue is particularly problematic in legal contexts, where defendants should be judged on the merits of the case, not on prejudice, rumors, or evidence obtained through questionable methods. This is why criminal law of procedure regulates which information can be introduced in a trial. In a series of online vignette experiments involving 1432 US participants, we examine the biasing impact of two types of inadmissible evidence: prior convictions (character evidence) and wiretap confessions. We failed to show that character evidence biases jurors' judgments of the defendant's guilt, whereas wiretap evidence had a strong effect. We also assess the effectiveness of four debiasing interventions aimed at helping jurors ignore inadmissible evidence. While these interventions reduced bias, they did not fully eliminate it. These results provide nuance in the debate about information in the courtroom that should be suppressed.
Intertemporal impatience has been proposed to be centrally and transdiagnostically implicated across mental health difficulties, including maladaptive behaviors, psychopathologies, and other psychological outcomes. We empirically tested this proposal using a novel research approach that integrates per-category, trans-category, scale-level, and item-level analyses. First, we studied per-category continuous associations between intertemporal impatience and a broad range of mental health-related behaviors and psychological constructs. Next, we examined which of several latent, trans-category dimensions were associated with impatience, thereby studying which mental health difficulties may be connected through shared impatience. Finally, we investigated which specific symptoms or behaviors were driving these associations. This study was conducted in a community sample of 899 participants who completed an intertemporal choice task and various self-report mental health measures. Per-category analyses involved bivariate correlations and multiple regressions; trans-category analyses involved exploratory factor analyses to identify transdiagnostic dimensions, and structural-after-measurement models to test for associations between the dimensions and intertemporal impatience. Intertemporal impatience was associated with increased nicotine use, reactive aggression, non-planning impulsivity, motor impulsivity, and dispositional greed. Moreover, impatience was positively associated with a transdiagnostic impulsivity dimension (including attention-deficit/hyperactivity disorder, low self-control, and motor and non-planning impulsivity). Symptom-level analyses suggested that this association was mainly driven by information impulsivity (also known as lack of premeditation) and financial impulsivity. Our results provide support for the role of intertemporal impatience across several externalizing but not internalizing mental health difficulties and offer a detailed and nuanced interpretation of the transdiagnostic role of intertemporal impatience across mental health.
The present study was a meta-analysis of previous studies on the correlation between trait anxiety and dispositional risk taking. Although it is often claimed that people who are generally anxious (i.e., higher in trait anxiety) have a strong tendency to avoid taking risks across a variety of situations (i.e., are lower in dispositional risk taking), the mean correlation across 80 effect sizes representing over 8000 unique participants was only −0.07, with a very high level of unexplained heterogeneity. An analysis focusing only on the relatively large subset of studies using the State–Trait Anxiety Inventory (STAI-T) as the measure of anxiety and the Balloon Analog Risk Task (BART) as the measure of dispositional risk taking revealed a mean correlation that was essentially zero. The only statistically significant moderator was the proportion of female participants in the study, with larger proportions associated with stronger negative correlations. However, the analysis also revealed several other moderators that should be studied in future research. Specifically, the correlation may be stronger or more consistently negative when the anxiety measure is something other than the STAI-T, when the risk-taking measure is a self-report risk propensity measure, and when the risk-taking measure precedes the anxiety measure. These results have important implications for the definition and measurement of both trait anxiety and risk taking and for theories about how they are related.
Algorithmic advice has the potential to significantly improve human decision-making, especially in dynamic and complex tasks that require a balance between exploration and exploitation. This study examines conditions under which individuals are willing to accept advice from algorithms in such scenarios, focusing on the interaction between participants' exploration preferences and those of the advising algorithm. In an online experiment, we designed reinforcement learning algorithms to prioritize either exploration or exploitation and observed participants' decision-making behavior, modeled using a cognitive framework analogous to the algorithm. Contrary to expectations, participants did not show a preference for algorithms that matched their own exploration tendencies. In particular, participants were more likely to follow the advice of exploitative, consistent algorithms, possibly interpreting consistency as an indicator of competence. Although the participants benefited from the advice of the exploratory algorithm, their reluctance to follow it, regardless of whether the recommendation had been ignored previously or not, highlights a potential challenge in promoting effective collaboration between humans and algorithms. Explorative algorithms have the potential to promote behavioral diversification, but this effect is negated when humans disregard their advice. In such cases, algorithmic guidance can unintentionally decrease behavioral diversity by reinforcing established patterns.
Nudging as a strategy to alter behaviors has garnered increasing attention from both researchers and policymakers. Here, we conduct a second-order meta-analysis, synthesizing 13 articles (14 meta-analyses) that include 1638 primary studies and approximately 30 million participants. We find a small aggregated effect size across these meta-analyses (d = 0.27, 95% CI [0.16, 0.38]), which drops to d = 0.004 after adjusting for publication bias. Examining the methodological quality of the meta-analyses, we find that most were rated as low or critically low, suggesting that our findings, which inherit these limitations, should be interpreted with caution. This study provides the most comprehensive synthesis of the effectiveness of nudging to date, while underscoring the urgent need for higher quality, preregistered meta-analyses to clarify the true impact.
Many real-world social dilemmas require interdependent people to repeatedly protect against a large loss that has a low probability of occurring. Examples include protecting against disease outbreak (e.g., COVID-19), terrorism (shared border security), or extreme weather events (from climate change). Decisions on whether to invest in protection may be made period by period (e.g., month by month), or investment may be precommitted in advance for a number of periods. How does precommitment influence cooperation in these situations? A series of four studies (plus one supplemental study) investigates this question, using incentive-compatible, repeated social dilemmas with large-magnitude, low-probability losses. These studies found that in stochastic social dilemmas, binding precommitment increases cooperation, but nonbinding precommitment has little effect, and in deterministic social dilemmas, binding precommitment decreases cooperation. These patterns were driven by changes in responsiveness to probabilities and interactions with counterparts, with implications for how to structure real-world dilemmas to increase cooperative investment in protection.
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