In person impression formation, target characteristics such as suitability for a vacant position or interpersonal likeability are inferred from information samples. This process strongly depends on the diagnosticity of observed (i.e., sampled) behaviors. Applying a likelihood-based conceptualization of diagnosticity, we tested two major implications: First, diagnosticity depends on the hypothesis being tested, and second, it is shaped by situational base-rates. We examined both facets by manipulating the extent of positive versus negative valence within the big two (agency vs. communion). In Experiment 1, we varied the hypothesis to be tested by providing different job profiles in a personnel selection task. Consistent with the predictions, hypothesis-relevant information impacted both sampling and judgment behavior more than hypothesis-irrelevant information. In Experiments 2A and 2B, we manipulated big-two specific valence base-rate expectations on target persons characterized as psychotherapy patients: Genuinely diagnostic violations of group-based expectancies turned out to result in strongest judgments. The findings suggest that participants' sampling patterns and judgments follow the proposed likelihood-based diagnosticity concept.

When searching for information before making a decision, one faces a fundamental trade-off. On the one hand, more information will almost always improve the decision outcome. On the other hand, spending more time, money, or effort on further information search may be more costly than that improvement is beneficial. If decision makers are adaptive, they should use their resources in information searches efficiently. Using a sampling-based decision paradigm with financial costs for each observation, we conducted five experiments to investigate whether and how participants adapt their information amount to relevant aspects of the environment. Experiment 1a (N = 67) and 1b (N = 79) focused on changes in response to different ratios of information cost and decision payoffs, revealing that participants are capable of adapting, but seem to do so mainly based on a priori planning. Experiment 2 (N = 131) assessed the role of a second process, online adjustment, by varying whether participants received feedback. Surprisingly, participants changed their behavior to the same extent irrespective of whether they received feedback. To further improve the opportunities for metacognitive monitoring and control, Experiments 3a and 3b (N = 160 and N = 318) implemented different feedback types across more decision trials for three different ratios of information cost and decision outcomes, which stayed constant per participant. Whether participants changed their sample size and efficiency across trials depended on that ratio, but not on the type of feedback. This provides crucial insights into how participants adapt and what challenges might befall the necessary metacognitive monitoring, serving as a valuable prompt for future research.

There is a trepidation, anxiety, or intuition, which has persisted for more than a century, that psychology theories are less anchored in fundamental laws than physics theories. Rather than attempt to refute the concern, the present work accepts it and tries out candidate explanations. These pertain to empirical laws, parsimony, scope, reductionism, falsifiability, mathematical operations (multiplication vs. addition), internal coherence, ceteris paribus stipulations, and purposeful omission of relevant factors (idealization). The conceptions underlying these explanations are not strictly independent, but they point to different distinctive features that might account for the unequal status of physics and psychological science and to different means of improving contemporary psychology. Although the available evidence for or against these candidate explanations is scarce and relies mainly on a few telling examples, we conclude that the last of our candidate explanations-reliance on idealized universes-works best and leads to the most insights about what psychology might learn from physics and what research strategies might foster the ideal of theory-driven psychological science in the future. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Scientific evidence and rigor are commonly assumed to afford an appropriate remedy to the hazards of fake news and uncritical or even naïve misbeliefs. Yet, the present chapter shows that science is by no means immune to such anomalies. Rather, the scientific community, of which we all are a part, believes in a variety of collectively transmitted tribal misbeliefs and false behavioral conventions, the invalidity of which is uncontested and well understood by a vast majority of scientists, who nevertheless continue to follow and normatively reify the misbeliefs. Prominent examples of such collective anomalies, which meet all defining features of tribalism in scientific practice, include ignorance of regressive shrinkage (e.g., in replication science), neglect of manipulation checks, the confident distinction of confirmatory versus exploratory research, continued reliance on null-hypothesis significance testing and statistical power control, and the strict discrimination of experimental from correlational research. The concluding section is devoted to discussing possible explanations and remedies for these conspicuous anomalies.

The focus of the present article is not on failures to replicate but on the more optimistically framed and more fruitful question: What stable findings can be reproduced reliably and can be trusted by decision makers, managers, health agents, or politicians? We propagate the working hypothesis that a twofold key to stable and replicable findings lies in the existence of theoretical constraints and, no less important, in researchers' sensitivity to metatheoretical, auxiliary assumptions. We introduce a hierarchy of four levels of theoretical constraints-a priori principles, psychophysical, empirical, and modelling constraints-combined with the TASI taxonomy of theoretical, auxiliary, statistical, and inferential assumptions Trafimow, Journal for the Theory of Social Behaviour, 52, 37-48, (2022). Although theoretical constraints clearly facilitate stable and replicable research findings, TASI reminds us of various reasons why even perfectly valid hypotheses need not always be borne out. The presented framework should help researchers to operationalize conditions under which theoretical constraints render empirical findings most predictable.

Collecting an adequate amount of information for a decision is an important skill. However, previous experiments on speed-accuracy trade-offs in sample-based decisions revealed marked oversampling that was impervious to various interventions (Fiedler, McCaughey, et al., 2021). When faced with the threat of being preempted by a rival in making decisions, participants seem to reduce information search substantially (Phillips et al., 2014). Such a decrease provides unique opportunities for metareasoning, which should advance people's understanding of the task and improve their performance. To test this possibility, in the present research (N = 101), participants had to compete with a fast (computer-simulated) rival and indeed substantially reduced self-determined sample size compared to a control condition. This speed increase also carried over to a subsequent decision block without rival, albeit participants regressed to a slower strategy. Mere exposure to a teammate using small samples either in an equivalent competitive version of the task or the standard solitary version led to similar reductions in sample size. This demonstrates that competition is not a necessary requirement for participants to make use of the metareasoning opportunity to improve task performance. Further research is needed to uncover the metacognitive underpinnings of improving performance and facilitate people taking full advantage of such opportunities for metareasoning.

Data sets and data analysis script (in R) for Ziegler, J., & Fiedler, K. (2024) Small sample size and group homogeneity: A crucial ingredient to inter-group bias. Personality and Social Psychology Bulletin.

Contingency assessment is a major module of adaptive cognition and a prominent topic of ecological rationality. Virtually all influential theories assume that contingency estimates between Y and X are inferred from subjective conditional probabilities of focal Y levels given different X levels, p ( Y focal | X different levels ) . Yet, conditional probabilities are cognitively demanding, as Yfocal must be assessed separately for all levels of Xdifferent level. Pseudocontingencies (PCs) afford an alternative mechanism relying on base rates. In a PC, the more frequent level on one attribute appears contingent on the more frequent level on another attribute. When PCs are manipulated orthogonally to conditional probabilities, the former dominate the latter (Fiedler, 2010). PC dominance is shown in Experiments 1 and 1a to be particularly striking when a multivariate task setting calls for the assessment of all k(k - 1)/2 pairwise contingencies between k attributes. Experiment 2 shows that contingency judgments are dissociated from evaluative conditioning.

Applying a recently developed framework for the study of sample-based person impressions to the level of group impressions resulted in convergent evidence for a highly robust judgment process. How stimulus traits mapped on the resulting group impressions was subject to two distinct moderators, diagnosticity of traits, and the amplifying impact of early sample truncation. Three indices of diagnosticity-negative valence, extremity, and distance to other traits in a density framework-determined participants' decision to truncate trait sampling early and hence the final group judgments. When trait samples were negative and extreme and when the distance between high-density traits was small, early truncation of the trait samples fostered high group homogeneity and polarized impressions. Granting that mental representations of in-groups and out-groups rely on systematically different samples, our sampling approach can account for various inter-group biases: out-group homogeneity, out-group polarization and (because negative traits are more diagnostic) out-group derogation.

The cumulative redundancy bias (CRB) refers to people’s difficulty to ignore the redundancy in cumulatively presented information. For instance, when people consider which of two teams is better, they should focus on the total number of points that each team has at the time. Yet, people are also influenced by the sequence of events that led to that accumulated score, such that if one team was ahead most of the season, people consider it better – even if those teams are currently tied. However, an opposite bias emerges when participants focus on performance trends (performance trend bias; PTB): When the trailing team is catching up to the leading team, people judge it as the better team – even if the other team is still ahead. In three experiments where we manipulated slope magnitude, we obtained both effects: the PTB was observed when the slope was big; the CRB emerged when the slope was small. These studies demonstrate a striking malleability of the cognitive system, flexibly weighing different cues. Results are discussed in terms of metacognitive regulation.

Why can initial biases persist in repeated choice tasks? Previous research has shown that frequent rewards can lure the decision maker into premature exploitation of a supposedly best option, which can result in the persistence of initial biases. Here, we demonstrate that even in the absence of rewards, initial biases can be perpetuated through a positive testing strategy. After eliciting a biased preference for one of two equally rewarding options, participants (N = 203) could sample freely from both options without the lure of any financial rewards. When participants were told to rule out alternatives in this phase, they explored the supposedly worse option and thereby managed to overcome their initial bias. When told to optimize their strategy, however, they exhibited a positive testing strategy resulting in the continued exploitation of the supposedly better option, a bias they maintained in an incentivized choice phase and later judgments. Across all participants, individual tendencies to exploit one option in earlier phases predicted biased behavior in subsequent phases. The findings highlight that not only the pursuit of instrumental rewards can lead to exploitation and the maintenance of initial biases. We discuss potential consequences for interventions.

In hindsight, when the outcome of an uncertain scenario is already known, we typically feel that this outcome was always likely; hindsight judgments of outcome probabilities exceed foresight judgments of the same probabilities without outcome knowledge. We extend prior accounts of hindsight bias with the influence of pragmatic communication inherent in the task and the consolidation of self-generated responses across time. In a novel 3 × 2 within-participants design, with three sequential judgments of outcome probabilities in two scenarios, we replicated the within-participants hindsight bias observed in the classic memory design and the between-participants hindsight bias in a hypothetical design simultaneously. Moreover, we reversed the classic memory design and showed that subjective probabilities also decreased when participants encountered foresight instructions after hindsight instructions, demonstrating that previously induced outcome knowledge did not prevent unbiased judgments. The constructive impact of self-generated and communicated judgments ("saying is believing") was apparent after a 2-week consolidation period: Not outcome knowledge, but rather the last pragmatic response (either biased or unbiased) determined judgments at the third measurement. These findings highlight the short-term malleability of hindsight influences in response to task pragmatics and has major implications for debiasing.

While there are abundant reasons that might lead us to form wrong first impressions, further interaction (sampling) opportunities should allow us to attenuate such initial biases. Sometimes, however, theses biases persist despite repeated sampling opportunities, such as in superstitions or stereotypes. In two studies (Ns = 100), we investigate this phenomenon. We demonstrate that in a task in which participants could repeatedly choose between two options to gain rewards, erroneous initial impressions about yielded outcomes can lead to persisting biases toward a clearly inferior option. We argue that a premature focus on reward pursuit (exploitation) rather than exploration is the cause of these biases, which persist despite plenty of opportunities and a presumed motivation to overcome them. By focusing on a supposedly best option, participants never give themselves the chance to sufficiently try out alternatives and thereby overcome their initial biases. We conclude that going for the money is not always the best strategy.

To understand and explain sample-based impression formation, it is necessary to consider both the Brunswikian uncertainty caused by sampling from the stimulus environment and the Thurstonian uncertainty arising from the cognitive processing thereof. Impression judgments must be formed in view of both sources of uncertainty. Even when an ecological sample of a target’s traits is held constant, the resulting distribution of target information in the judge’s mind can vary substantively as a function of semantic and affective responses, top-down inferences, and contextual influences. In the research reviewed in the present chapter, we investigate the interplay of Brunswikian and Thurstonian sampling in a person-impression task based on self-truncated trait samples, in which judges can stop sampling at the very moment when their internal mindset optimally prepares them to form a distinct impression. This task setting produces distinct self-truncation effects; the resulting impression judgments are polarized, conflict-free, and typically driven by small samples (after early truncation). When exactly the same traits are presented in a yoked-control design to other judges, who cannot exploit self-truncation effects, their judgment patterns are similar but clearly less pronounced, reflecting the same Brunswikian trait samples detached from the Thurstonian mindset.

Assessing people’s personalities using self-reports is complicated by three central problems: Low predictability of behavior, discrepancies between self- and observer-reports, and different target reports across multiple observers. Moving beyond existing research on common survey biases, we introduce a sampling bias that can explain all three problems. In judgement and decision-making research, asymmetric sampling proposes that an individual can only generate a sample of information about an object (e.g., environment or person) from their own experience. It follows that any personal sample is limited by the environment and, most importantly, is selective toward positive experiences. We apply the sampling framework to personality assessment and show that selective sampling leads to an asymmetric mental model of one’s personality (e.g., extraversion), in which certain situations are over- or underrepresented. We call this asymmetric sampling of personality (ASP). Asymmetric samples of experienced situations lack the generalizability to reliably predict behavior (as a tendency to behave a certain way across situations). Moreover, differently biased situation samples may explain self-observer discrepancies in personality assessment and divergences between multiple observers, offering a novel interpretation of quality standards for interrater reliability.

The threefold purpose of this initial chapter is to provide a review of the historical origins and the methodological beauty of sampling approaches to judgment and decision-making, to illuminate the most prominent recent developments, and to provide a preview of all chapters included in this volume. Accordingly, the chapter is organized into three parts. The historical review in the first part highlights the progress from purely intra-psychic to cognitive-ecological perspectives on adaptive cognition, conceived as a genuine interaction between environmental constraints and adaptive agents’ sampling strategies. The review of novel trends in the second part testifies to the fertility of sampling approaches and the impressive amount of progress it has inspired in terms of functional-level applications in various areas, but also in terms of mechanistic and computational modeling. A preview of all 22 chapters of the present volume in the final part is organized into six sections, covering the full spectrum of these innovative developments in rationality research during the last 15 years.

Information amount is a crucial determinant of decision outcomes. But how much information one should collect before arriving at a decision depends on a cost–benefit trade-off: Is the expected benefit of increased decision accuracy that can be gained from additional information higher than the additional information costs? To investigate this trade-off with temporal costs for information, we developed a speed–accuracy trade-off paradigm with sample-based decisions, in which the total payoff was the product of the average payoff per decision and the number of decisions completed in a restricted period. Increasing n served to increase the accuracy of choices, but also to decrease the number of completed choices. Yet, whereas the number of completed choices decreases linearly with increasing n, accuracy increases in a clearly sublinear fashion. As a consequence, the sample-based choice task calls for more weight given to speed than to accuracy. However, overly conservative sampling strategies prevented almost all participants from exploiting the speed advantage despite various guiding interventions. Even when the task was enriched by the social aspect of a teammate or rival, who demonstrated the optimal trade-off, participants remained too focussed on accuracy. We also investigate the cost–benefit trade-off with financial information costs, for which participants’ performance was less biased. We propose this to be related to how evaluable the information’s costs were relative to its benefits. Issues of adaptivity in contrast with optimality are addressed in a final discussion.