The Role of Representative Design in an Ecological Approach to Cognition

Assessing the validity of using serious game technology to analyze physician decision making

Background

Physician non-compliance with clinical practice guidelines remains a critical barrier to high quality care. Serious games (using gaming technology for serious purposes) have emerged as a method of studying physician decision making. However, little is known about their validity.

Methods

We created a serious game and evaluated its construct validity. We used the decision context of trauma triage in the Emergency Department of non-trauma centers, given widely accepted guidelines that recommend the transfer of severely injured patients to trauma centers. We designed cases with the premise that the representativeness heuristic influences triage (i.e. physicians make transfer decisions based on archetypes of severely injured patients rather than guidelines). We randomized a convenience sample of emergency medicine physicians to a control or cognitive load arm, and compared performance (disposition decisions, number of orders entered, time spent per case). We hypothesized that cognitive load would increase the use of heuristics, increasing the transfer of representative cases and decreasing the transfer of non-representative cases.

Findings

We recruited 209 physicians, of whom 168 (79%) began and 142 (68%) completed the task. Physicians transferred 31% of severely injured patients during the game, consistent with rates of transfer for severely injured patients in practice. They entered the same average number of orders in both arms (control (C): 10.9 [SD 4.8] vs. cognitive load (CL):10.7 [SD 5.6], p = 0.74), despite spending less time per case in the control arm (C: 9.7 [SD 7.1] vs. CL: 11.7 [SD 6.7] minutes, p<0.01). Physicians were equally likely to transfer representative cases in the two arms (C: 45% vs. CL: 34%, p = 0.20), but were more likely to transfer non-representative cases in the control arm (C: 38% vs. CL: 26%, p = 0.03).

Conclusions

We found that physicians made decisions consistent with actual practice, that we could manipulate cognitive load, and that load increased the use of heuristics, as predicted by cognitive theory.

The role of ANS acuity and numeracy for the calibration and the coherence of subjective probability judgments

The purpose of the study was to investigate how numeracy and acuity of the approximate number system (ANS) relate to the calibration and coherence of probability judgments. Based on the literature on number cognition, a first hypothesis was that those with lower numeracy would maintain a less linear use of the probability scale, contributing to overconfidence and nonlinear calibration curves. A second hypothesis was that also poorer acuity of the ANS would be associated with overconfidence and non-linearity. A third hypothesis, in line with dual-systems theory (e.g., Kahneman and Frederick, 2002) was that people higher in numeracy should have better access to the normative probability rules, allowing them to decrease the rate of conjunction fallacies. Data from 213 participants sampled from the Swedish population showed that: (i) in line with the first hypothesis, overconfidence and the linearity of the calibration curves were related to numeracy, where people higher in numeracy were well calibrated with zero overconfidence. (ii) ANS was not associated with overconfidence and non-linearity, disconfirming the second hypothesis. (iii) The rate of conjunction fallacies was slightly, but to a statistically significant degree decreased by numeracy, but still high at all numeracy levels. An unexpected finding was that participants with better ANS acuity gave more realistic estimates of their performance relative to others.

Unconscious influences on decision making: a critical review

To what extent do we know our own minds when making decisions? Variants of this question have preoccupied researchers in a wide range of domains, from mainstream experimental psychology (cognition, perception, social behavior) to cognitive neuroscience and behavioral economics. A pervasive view places a heavy explanatory burden on an intelligent cognitive unconscious, with many theories assigning causally effective roles to unconscious influences. This article presents a novel framework for evaluating these claims and reviews evidence from three major bodies of research in which unconscious factors have been studied: multiple-cue judgment, deliberation without attention, and decisions under uncertainty. Studies of priming (subliminal and primes-to-behavior) and the role of awareness in movement and perception (e.g., timing of willed actions, blindsight) are also given brief consideration. The review highlights that inadequate procedures for assessing awareness, failures to consider artifactual explanations of "landmark" results, and a tendency to uncritically accept conclusions that fit with our intuitions have all contributed to unconscious influences being ascribed inflated and erroneous explanatory power in theories of decision making. The review concludes by recommending that future research should focus on tasks in which participants' attention is diverted away from the experimenter's hypothesis, rather than the highly reflective tasks that are currently often employed.

Cognitive aging: is there a dark side to environmental support?

It has been known for some time that memory deficits among older adults increase when self-initiated processing is required and decrease when the environment provides task-appropriate cues. We propose that this observation is not confined to memory but can be subsumed under a more general developmental trend. In perception, learning or memory, and action management, older adults often rely more on external information than younger adults do, probably both as a direct reflection and indirect adaptation to difficulties in internally triggering and maintaining cognitive representations. This age-graded shift from internal towards environmental control is often associated with compromised performance. Cognitive aging research and the design of aging-friendly environments can benefit from paying closer attention to the developmental dynamics and implications of this shift.

Validating a vignette-based instrument to study physician decision making in trauma triage

BACKGROUND

The evidence supporting the use of vignettes to study physician decision making comes primarily from the study of low-risk decisions and the demonstration of good agreement at the group level between vignettes and actual practice. The validity of using vignettes to predict decision making in more complex, high-risk contexts and at the individual level remains unknown.

METHODS

We had previously developed a vignette-based instrument to study physician decision making in trauma triage. Here, we measured the retest reliability, internal consistency, known-groups performance, and criterion validity of the instrument. Thirty-two emergency physicians, recruited at a national academic meeting, participated in reliability testing. Twenty-eight trauma surgeons, recruited using personal contacts, participated in known-groups testing. Twenty-eight emergency physicians, recruited from physicians working at hospitals for which we had access to medical records, participated in criterion validity testing. We measured rates of undertriage (the proportion of severely injured patients not transferred to trauma centers) and overtriage (the proportion of patients transferred with minor injuries) on the instrument. For physicians participating in criterion validity testing, we compared rates of triage on the instrument with rates in practice, based on chart review.

RESULTS

Physicians made similar transfer decisions for cases (κ = 0.42, P < 0.01) on 2 administrations of the instrument. Responses were internally consistent (Kuder-Richardson, 0.71-0.91). Surgeons had lower rates of undertriage than emergency physicians (13% v. 70%, P < 0.01). No correlation existed between individual rates of under- or overtriage on the vignettes and in practice (r = -0.17, P = 0.4; r = -0.03, P = 0.85).

CONCLUSIONS

The instrument developed to assess trauma triage decision making performed reliably and detected known group differences. However, it did not predict individual physician performance.

Perceptuo-motor, cognitive, and description-based decision-making seem equally good

Classical studies suggest that high-level cognitive decisions (e.g., choosing between financial options) are suboptimal. In contrast, low-level decisions (e.g., choosing where to put your feet on a rocky ridge) appear near-optimal: the perception-cognition gap. Moreover, in classical tasks, people appear to put too much weight on unlikely events. In contrast, when people can learn through experience, they appear to put too little weight on unlikely events: the description-experience gap. We eliminated confounding factors and, contrary to what is commonly believed, found results suggesting that (i) the perception-cognition gap is illusory and due to differences in the way performance is assessed; (ii) the description-experience gap arises from the assumption that objective probabilities match subjective ones; (iii) people's ability to make decisions is better than the classical literature suggests; and (iv) differences between decision-makers are more important for predicting peoples' choices than differences between choice tasks.

Abnormality, rationality, and sanity

A growing body of studies suggests that neurological and mental abnormalities foster conformity to norms of rationality that are widely endorsed in economics and psychology, whereas normality stands in the way of rationality thus defined. Here, we outline the main findings of these studies, discuss their implications for experimental design, and consider how 'sane' some benchmarks of rationality really are.

A lack of appetite for information and computation. Simple heuristics in food choice

The predominant, but largely untested, assumption in research on food choice is that people obey the classic commandments of rational behavior: they carefully look up every piece of relevant information, weight each piece according to subjective importance, and then combine them into a judgment or choice. In real world situations, however, the available time, motivation, and computational resources may simply not suffice to keep these commandments. Indeed, there is a large body of research suggesting that human choice is often better accommodated by heuristics-simple rules that enable decision making on the basis of a few, but important, pieces of information. We investigated the prevalence of such heuristics in a computerized experiment that engaged participants in a series of choices between two lunch dishes. Employing MouselabWeb, a process-tracing technique, we found that simple heuristics described an overwhelmingly large proportion of choices, whereas strategies traditionally deemed rational were barely apparent in our data. Replicating previous findings, we also observed that visual stimulus segments received a much larger proportion of attention than any nutritional values did. Our results suggest that, consistent with human behavior in other domains, people make their food choices on the basis of simple and informationally frugal heuristics.

The effect of improving task representativeness on capturing nurses' risk assessment judgements: a comparison of written case simulations and physical simulations

Background

The validity of studies describing clinicians’ judgements based on their responses to paper cases is questionable, because - commonly used - paper case simulations only partly reflect real clinical environments. In this study we test whether paper case simulations evoke similar risk assessment judgements to the more realistic simulated patients used in high fidelity physical simulations.

Methods

97 nurses (34 experienced nurses and 63 student nurses) made dichotomous assessments of risk of acute deterioration on the same 25 simulated scenarios in both paper case and physical simulation settings. Scenarios were generated from real patient cases. Measures of judgement ‘ecology’ were derived from the same case records. The relationship between nurses’ judgements, actual patient outcomes (i.e. ecological criteria), and patient characteristics were described using the methodology of judgement analysis. Logistic regression models were constructed to calculate Lens Model Equation parameters. Parameters were then compared between the modeled paper-case and physical-simulation judgements.

Results

Participants had significantly less achievement (r_a) judging physical simulations than when judging paper cases. They used less modelable knowledge (G) with physical simulations than with paper cases, while retaining similar cognitive control and consistency on repeated patients. Respiration rate, the most important cue for predicting patient risk in the ecological model, was weighted most heavily by participants.

Conclusions

To the extent that accuracy in judgement analysis studies is a function of task representativeness, improving task representativeness via high fidelity physical simulations resulted in lower judgement performance in risk assessments amongst nurses when compared to paper case simulations. Lens Model statistics could prove useful when comparing different options for the design of simulations used in clinical judgement analysis. The approach outlined may be of value to those designing and evaluating clinical simulations as part of education and training strategies aimed at improving clinical judgement and reasoning.

Correlates of diagnostic accuracy in patients with nonspecific complaints

OBJECTIVE

To investigate diagnostic accuracy in patient histories involving nonspecific complaints and the extent to which characteristics of physicians and structural properties of patient histories are associated with accuracy.

METHODS

Six histories of patients presenting to the emergency department (ED) with nonspecific complaints were provided to 112 physicians: 36 ED physicians, 50 internists, and 26 family practitioners. Physicians listed the 3 most likely diagnoses for each history and indicated which cue(s) they considered crucial. Four weeks later, a subset of 20 physicians diagnosed the same 6 histories again. For each history, experts had previously determined the correct diagnoses and the diagnostic cues.

RESULTS

Accuracy ranged from 14% to 64% correct diagnoses (correct diagnosis listed as the most likely) and from 29% to 87% correct differential diagnoses (correct diagnosis listed in the differential). Acute care physicians (ED physicians and internists) included the correct diagnosis in the differential in, on average, 3.4 histories, relative to 2.6 for the family practitioners (P = 0.001, d = .75). Diagnostic performance was fairly reliable (r = .61, P < 0.001). Clinical experience was negatively correlated with diagnostic accuracy (r = -.25, P = 0.008). Two structural properties of patient histories-cue consensus and cue substitutability-were significantly associated with diagnostic accuracy, whereas case difficulty was not. Finally, prevalence of diagnosis also proved significantly correlated with accuracy.

CONCLUSIONS

Average diagnostic accuracy in cases with nonspecific complaints far exceeds chance performance, and accuracy varies with medical specialty. Analyzing cue properties in patient histories can help shed light on determinants of diagnostic performance and thus suggest ways to enhance physicians' ability to accurately diagnose cases with nonspecific complaints.

Looking at Patients’ Choices through the Lens of Expected Utility

The expected utility framework underlies much research in medical decision making. Because the framework requires decisions to be decomposed into probabilities of states and the values of those states, researchers have investigated the two components separately from each other and from patients’ actual decisions. The authors propose that it would be productive to focus more research on the relationships among risk perceptions, outcome valuations, and choices in the same decision makers. They outline exploratory analyses based on two existing national surveys, the Medical Expenditure Panel Survey and the Joint Canada/United States Survey of Health.

When are two heads better than one and why?

A recent study, using a perceptual task, indicated that two heads were better than one provided that the members could communicate freely, presumably sharing their confidence in their judgments. Capitalizing on recent work on subjective confidence, I replicated this effect in the absence of any dyadic interaction by selecting on each trial the decision of the more confident member of a virtual dyad. However, because subjective confidence monitors the consensuality rather than the accuracy of a decision, when most participants were in error, reliance on the more confident member yielded worse decisions than those of the better individual. Assuming that for each issue group decisions are dominated by the more confident member, these results help specify when groups will be more or less accurate than individuals.

Revisiting Truth or Triviality: The External Validity of Research in the Psychological Laboratory

Anderson, Lindsay, and Bushman (1999) compared effect sizes from laboratory and field studies of 38 research topics compiled in 21 meta-analyses and concluded that psychological laboratories produced externally valid results. A replication and extension of Anderson et al. (1999) using 217 lab-field comparisons from 82 meta-analyses found that the external validity of laboratory research differed considerably by psychological subfield, research topic, and effect size. Laboratory results from industrial-organizational psychology most reliably predicted field results, effects found in social psychology laboratories most frequently changed signs in the field (from positive to negative or vice versa), and large laboratory effects were more reliably replicated in the field than medium and small laboratory effects.

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.

Diagnostic Task Selection for Strategy Classification in Judgment and Decision Making: Theory, Validation, and Implementation in R

One major statistical and methodological challenge in Judgment and Decision Making research is the reliable identification of individual decision strategies by selection of diagnostic tasks, that is, tasks for which predictions of the strategies differ sufficiently. The more strategies are considered, and the larger the number of dependent measures simultaneously taken into account in strategy classification (e.g., choices, decision time, confidence ratings; Glöckner, 2009), the more complex the selection of the most diagnostic tasks becomes. We suggest the Euclidian Diagnostic Task Selection (EDTS) method as a standardized solution for the problem. According to EDTS, experimental tasks are selected that maximize the average difference between strategy predictions for any multidimensional prediction space. In a comprehensive model recovery simulation, we evaluate and quantify the influence of diagnostic task selection on identification rates in strategy classification. Strategy classification with EDTS shows superior performance in comparison to less diagnostic task selection algorithms such as representative sampling. The advantage of EDTS is particularly large if only few dependent measures are considered. We also provide an easy-to-use function in the free software package R that allows generating predictions for the most commonly considered strategies for a specified set of tasks and evaluating the diagnosticity of those tasks via EDTS; thus, to apply EDTS, no prior programming knowledge is necessary.

Simply criminal: predicting burglars' occupancy decisions with a simple heuristic

Rational choice theories of criminal decision making assume that offenders weight and integrate multiple cues when making decisions (i.e., are compensatory). We tested this assumption by comparing how well a compensatory strategy called Franklin's Rule captured burglars' decision policies regarding residence occupancy compared to a non-compensatory strategy (i.e., Matching Heuristic). Forty burglars each decided on the occupancy of 20 randomly selected photographs of residences (for which actual occupancy was known when the photo was taken). Participants also provided open-ended reports on the cues that influenced their decisions in each case, and then rated the importance of eight cues (e.g., deadbolt visible) over all decisions. Burglars predicted occupancy beyond chance levels. The Matching Heuristic was a significantly better predictor of burglars' decisions than Franklin's Rule, and cue use in the Matching Heuristic better corresponded to the cue ecological validities in the environment than cue use in Franklin's Rule. The most important cue in burglars' models was also the most ecologically valid or predictive of actual occupancy (i.e., vehicle present). The majority of burglars correctly identified the most important cue in their models, and the open-ended technique showed greater correspondence between self-reported and captured cue use than the rating over decision technique. Our findings support a limited rationality perspective to understanding criminal decision making, and have implications for crime prevention.

Recognition-based judgments and decisions: What we have learned (so far)

This special issue on recognition processes in inferential decision making represents an adversarial collaboration among the three guest editors. This introductory article to the special issue’s third and final part comes in three sections. In Section 1, we summarize the six papers that appear in this part. In Section 2, we give a wrap-up of the lessons learned. Specifically, we discuss (i) why studying the recognition heuristic has led to so much controversy, making it difficult to settle on mutually accepted empirically grounded assumptions, (ii) whether the development of the recognition heuristic and its theoretical descriptions could explain some of the past controversies and misconceptions, (iii) how additional cue knowledge about unrecognized objects could enter the decision process, (iv) why recognition heuristic theory should be complemented by a probabilistic model of strategy selection, and (v) how recognition information might be related to other information, especially when considering real-world applications. In Section 3, we present an outlook on the thorny but fruitful road to cumulative theory integration. Future research on recognition-based inferences should (i) converge on overcoming past controversies, taking an integrative approach to theory building, and considering theories and findings from neighboring fields (such as marketing science and artificial intelligence), (ii) build detailed computational process models of decision strategies, grounded in cognitive architectures, (iii) test existing models of such strategies competitively, (iv) design computational models of the mechanisms of strategy selection, and (v) effectively extend its scope to decision making in the wild, outside controlled laboratory situations.

Repeated judgment sampling: Boundaries

This paper investigates the boundaries of the recent result that eliciting more than one estimate from the same person and averaging these can lead to accuracy gains in judgment tasks. It first examines its generality, analysing whether the kind of question being asked has an effect on the size of potential gains. Experimental results show that the question type matters. Previous results reporting potential accuracy gains are reproduced for year-estimation questions, and extended to questions about percentage shares. On the other hand, no gains are found for general numerical questions. The second part of the paper tests repeated judgment sampling’s practical applicability by asking judges to provide a third and final answer on the basis of their first two estimates. In an experiment, the majority of judges do not consistently average their first two answers. As a result, they do not realise the potential accuracy gains from averaging.

Voodoo Correlations Are Everywhere—Not Only in Neuroscience

A recent set of articles in Perspectives on Psychological Science discussed inflated correlations between brain measures and behavioral criteria when measurement points (voxels) are deliberately selected to maximize criterion correlations (the target article was Vul, Harris, Winkielman, & Pashler, 2009). However, closer inspection reveals that this problem is only a special symptom of a broader methodological problem that characterizes all paradigmatic research, not just neuroscience. Researchers not only select voxels to inflate effect size, they also select stimuli, task settings, favorable boundary conditions, dependent variables and independent variables, treatment levels, moderators, mediators, and multiple parameter settings in such a way that empirical phenomena become maximally visible and stable. In general, paradigms can be understood as conventional setups for producing idealized, inflated effects. Although the feasibility of representative designs is restricted, a viable remedy lies in a reorientation of paradigmatic research from the visibility of strong effect sizes to genuine validity and scientific scrutiny.

Recognition judgments and the performance of the recognition heuristic depend on the size of the reference class

In a series of three experiments, participants made inferences about which one of a pair of two objects scored higher on a criterion. The first experiment was designed to contrast the prediction of Probabilistic Mental Model theory (Gigerenzer, Hoffrage, & Kleinbölting, 1991) concerning sampling procedure with the hard-easy effect. The experiment failed to support the theory’s prediction that a particular pair of randomly sampled item sets would differ in percentage correct; but the observation that German participants performed practically as well on comparisons between U.S. cities (many of which they did not even recognize) than on comparisons between German cities (about which they knew much more) ultimately led to the formulation of the recognition heuristic. Experiment 2 was a second, this time successful, attempt to unconfound item difficulty and sampling procedure. In Experiment 3, participants’ knowledge and recognition of each city was elicited, and how often this could be used to make an inference was manipulated. Choices were consistent with the recognition heuristic in about 80% of the cases when it discriminated and people had no additional knowledge about the recognized city (and in about 90% when they had such knowledge). The frequency with which the heuristic could be used affected the percentage correct, mean confidence, and overconfidence as predicted. The size of the reference class, which was also manipulated, modified these effects in meaningful and theoretically important ways.

The Judgment of Future Suicide-Related Behavior

Background: Judging whether a youth is at risk for suicide-related behavior (SRB) is considered an extremely challenging task. There are only few studies of helpline counselors, and little is known about their ability to accurately determine the level of risk for SRB. Aims: To examine whether helpline counselors can agree on judgments of risk for SRB, and whether their judgments are consistent with youths’ actual behavior in a 6-month period following intake. Methods: 34 helpline counselors, recruited from three helplines, were studied. Information was collected on their judgments of risk for SRB for each of 45 youths over a 6-month period following initial intake. Results: Contrary to expectations, the counselors had a high rate of agreement (k = .56), and their risk judgments could be used quite successfully (80.0% correct classification) in identifying youths who later engaged in SRB. Conclusions: Unlike most other groups represented in the decision-making literature, helpline counselors agree and are accurate in their judgments of risk for SRB. Our findings suggest that it might be beneficial to apply some of the procedures used to train helpline clinicians to other types of clinicians. Further studies of helpline clinicians are suggested.

Redundancy and reduction: speakers manage syntactic information density

A principle of efficient language production based on information theoretic considerations is proposed: Uniform Information Density predicts that language production is affected by a preference to distribute information uniformly across the linguistic signal. This prediction is tested against data from syntactic reduction. A single multilevel logit model analysis of naturally distributed data from a corpus of spontaneous speech is used to assess the effect of information density on complementizer that-mentioning, while simultaneously evaluating the predictions of several influential alternative accounts: availability, ambiguity avoidance, and dependency processing accounts. Information density emerges as an important predictor of speakers' preferences during production. As information is defined in terms of probabilities, it follows that production is probability-sensitive, in that speakers' preferences are affected by the contextual probability of syntactic structures. The merits of a corpus-based approach to the study of language production are discussed as well.

Exploring methods to investigate sentencing decisions

The determinants of sentencing are of much interest in criminal justice and legal research. Understanding the determinants of sentencing decisions is important for ensuring transparent, consistent, and justifiable sentencing practice that adheres to the goals of sentencing, such as the punishment, rehabilitation, deterrence, and incapacitation of the offender, as well as reparation for the victim. It is important to frame research questions on sentencing that can feasibly be answered by appropriate research methods, within the constraints of limited time and resources. For illustration, this article presents three methodological approaches for investigating the factors that may influence sentencing decisions: multilevel analysis using existing sentencing data; sampling of, and data collection from, sentenced court case files; and experimental designs involving sentencers deciding on hypothetical cases. The strengths and weaknesses of each approach are compared and discussed.

Emotions beyond the laboratory: theoretical fundaments, study design, and analytic strategies for advanced ambulatory assessment

Questionnaire and interview assessment can provide reliable data on attitudes and self-perceptions on emotion, and experimental laboratory assessment can examine functional relations between stimuli and reactions under controlled conditions. On the other hand, ambulatory assessment is less constrained and provides naturalistic data on emotion in daily life, with the potential to (1) assure external validity of laboratory findings, (2) provide normative data on prevalence, quality and intensity of real-life emotion and associated processes, (3) characterize previously unidentified emotional phenomena, and (4) model real-life stimuli for representative laboratory research design. Technological innovations now allow for detailed ambulatory study of emotion across domains of subjective experience, overt behavior and physiology. However, methodological challenges abound that may compromise attempts to characterize biobehavioral aspects of emotion in the real world. For example, emotional effects can be masked by social engagement, mental and physical workloads, as well as by food intake and circadian and quasi-random variation in metabolic activity. The complexity of data streams and multitude of factors that influence them require a high degree of context specification for meaningful data interpretation. We consider possible solutions to typical and often overlooked issues related to ambulatory emotion research, including aspects of study design decisions, recording devices and channels, electronic diary implementation, and data analysis.

The description-experience gap in risky choice

According to a common conception in behavioral decision research, two cognitive processes-overestimation and overweighting-operate to increase the impact of rare events on people's choices. Supportive findings stem primarily from investigations in which people learn about options via descriptions thereof. Recently, a number of researchers have begun to investigate risky choice in settings in which people learn about options by experiential sampling over time. This article reviews work across three experiential paradigms. Converging findings show that when people make decisions based on experience, rare events tend to have less impact than they deserve according to their objective probabilities. Striking similarities in human and animal experience-based choices, ways of modeling these choices, and their implications for risk and precautionary behavior are discussed.

Theories of truth as assessment criteria in judgment and decision making

Hammond (1996) argued that much of the research in the field of judgment and decision making (JDM) can be categorized as focused on either coherence or correspondence (C&C) and that, in order to understand the findings of the field, one needs to understand the differences between these two criteria. Hammond’s claim is that conclusions about the competence of judgments and decisions will depend upon the selection of coherence or correspondence as the criterion (Hammond, 2008). First, I provide an overview of the terms coherence and correspondence (C&C) as philosophical theories of truth and relate them to the field of JDM. Second, I provide an example of Hammond’s claim by examining literature on base rate neglect. Third, I examine Hammond’s claim as it applies to the broader field of JDM. Fourth, I critique Hammond’s claim and suggest that refinements to the C&C distinction are needed. Specifically, the C&C distinction 1) is more accurately applied to criteria than to researchers, 2) should be refined to include two important types of coherence (inter and intrapersonal coherence) and 3) neglects the third philosophical theory of truth, pragmatism. Pragmatism, as a class of criteria in JDM, is defined as goal attainment. In order to provide the most complete assessment of human judgment possible, and understand different findings in the field of JDM, all three criteria should be considered.

Inferences from memory: strategy- and exemplar-based judgment models compared

What are the cognitive processes underlying people's inferences from memory? To provide an answer, the exemplar-based approach to predicting people's inferences is tested against the strategy-based approach. Exemplar models assume that people make inferences about objects by retrieving similar objects from memory. In contrast, the strategy-based approach assumes that people select cognitive strategies that make inferences based on abstracted knowledge and information the inference situation provides. In Experiment 1, in which dichotomous feedback on the level of pair-comparisons was provided, almost all participants were classified as using a simple lexicographic strategy. In Experiment 2, in which continuous feedback for single objects was provided, most participants were classified as using a compensatory strategy. Both experiments suggest that the strategy-based approach is more suitable for predicting people's inferences from memory than the exemplar-based approach. The strategy-based approach shows how people adapt to inference situations by selecting different cognitive strategies.