Toward a General Framework of Biased Reasoning: Coherence-Based Reasoning

A considerable amount of experimental research has been devoted to uncovering biased forms of reasoning. Notwithstanding the richness and overall empirical soundness of the bias research, the field can be described as disjointed, incomplete, and undertheorized. In this article, we seek to address this disconnect by offering "coherence-based reasoning" as a parsimonious theoretical framework that explains a sizable number of important deviations from normative forms of reasoning. Represented in connectionist networks and processed through constraint-satisfaction processing, coherence-based reasoning serves as a ubiquitous, essential, and overwhelmingly adaptive apparatus in people's mental toolbox. This adaptive process, however, can readily be overrun by bias when the network is dominated by nodes or links that are incorrect, overweighted, or otherwise nonnormative. We apply this framework to explain a variety of well-established biased forms of reasoning, including confirmation bias, the halo effect, stereotype spillovers, hindsight bias, motivated reasoning, emotion-driven reasoning, ideological reasoning, and more.

Rational inference strategies and the genesis of polarization and extremism

Polarization and extremism are often viewed as the product of psychological biases or social influences, yet they still occur in the absence of any bias or irrational thinking. We show that individual decision-makers implementing optimal dynamic decision strategies will become polarized, forming extreme views relative to the true information in their environment by virtue of how they sample new information. Extreme evidence enables decision makers to stop considering new information, whereas weak or moderate evidence is unlikely to trigger a decision and is thus under-sampled. We show that this information polarization effect arises empirically across choice domains including politically-charged, affect-rich and affect-poor, and simple perceptual decisions. However, this effect can be disincentivized by asking participants to make a judgment about the difference between two options (estimation) rather than deciding. We experimentally test this intervention by manipulating participants’ inference goals (decision vs inference) in an information sampling task. We show that participants in the estimation condition collect more information, hold less extreme views, and are less polarized than those in the decision condition. Estimation goals therefore offer a theoretically-motivated intervention that could be used to alleviate polarization and extremism in situations where people traditionally intend to decide.

Ambivalence in decision making: An eye tracking study

An intuition of ambivalence in cognition is particularly strong for complex decisions, for which the merits and demerits of different options are roughly equal but hard to compare. We examined information search in an experimental paradigm which tasked participants with an ambivalent question, while monitoring attentional dynamics concerning the information relevant to each option in different Areas of Interest (AOIs). We developed two dynamical models for describing eye tracking curves, for each response separately. The models incorporated a drift mechanism towards the various options, as in standard drift diffusion theory. In addition, they included a mechanism for intrinsic oscillation, which competed with the drift process and undermined eventual stabilization of the dynamics. The two models varied in the range of drift processes postulated. Higher support was observed for the simpler model, which only included drifts from an uncertainty state to either of two certainty states. In addition, model parameters could be weakly related to the eventual decision, complementing our knowledge of the way eye tracking structure relates to decision (notably the gaze cascade effect).

Salience effects in information acquisition: No evidence for a top-down coherence influence

The Integrated Coherence-Based Decision and Search (iCodes) model proposed by Jekel et al. (Psychological Review, 125 (5), 744-768, 2018) formalizes both decision making and pre-decisional information search as coherence-maximization processes in an interactive network. Next to bottom-up attribute influences, the coherence of option information exerts a top-down influence on the search processes in this model, predicting the tendency to continue information search with the currently most attractive option. This hallmark "attraction search effect" (ASE) has been demonstrated in several studies. In three experiments with 250 participants altogether, a more subtle prediction of an extended version of iCodes including exogenous influence factors was tested: The salience of information is assumed to have both a direct (bottom-up) and an indirect (top-down) effect on search, the latter driven by the match between information valence and option attractiveness. The results of the experiments largely agree in (1) showing a strong ASE, (2) demonstrating a bottom-up salience effect on search, but (3) suggesting the absence of the hypothesized indirect top-down salience effect. Hence, only two of three model predictions were confirmed. Implications for various implementations of exogenous factors in the iCodes model are discussed.

A dual process model for paleopathological diagnosis

OBJECTIVES

This paper aims to provide an explicit theoretical model for the cognitive processes involved in paleopathological diagnosis.

METHODS

The approach adopted is a dual process model (DPM). DPMs recognize that cognition is a result of both Type 1 (intuitive) and Type 2 (analytical) processes. DPMs have been influential for understanding decision-making in a range of fields, including diagnosis in clinical medicine. Analogies are drawn between diagnosis in a clinical and a paleopathological setting.

RESULTS

In clinical medicine, both Type 1 and Type 2 processes play a part in diagnosis. In paleopathology the role of Type 1 processes has been unacknowledged. However, like clinical diagnosis, paleopathological diagnosis is inherently a result of a combination of both Type 1 and Type 2 processes. A model is presented by which Type 1 processes can be explicitly incorporated into a scientific approach to diagnosis from skeletal remains, and in which diagnosis is formalized as a process of hypothesis testing.

SIGNIFICANCE

Accurately modelling our diagnostic processes allows us to understand the biases and limitations in our work and potentially helps us to improve our procedures, including how we impart diagnostic skills in pedagogical settings.

LIMITATIONS

This work provides a theoretical model for paleopathological diagnosis. However, such models are by their nature dynamic and developing rather than static entities; it is hoped that this work stimulates further debate and discussion in this important area.

Ex ante coherence shifts

Cushman characterizes rationalization as the inverse of rational reasoning, but this distinction is psychologically questionable. Coherence-based reasoning highlights a subtler form of bidirectionality: By distorting task attributes to make one course of action appear superior to its rivals, a patina of rationality is bestowed on the choice. This mechanism drives choice and action, rather than just following in their wake.

The information distortion bias: implications for medical decisions

CONTEXT

Every diagnosis involves an act of decision making, which requires proper evaluation of information. However, even seemingly objective information can require interpretation, often without our conscious awareness. In this cross-cutting edge article we describe the phenomenon of leader-driven information distortion (ID) and its implications for medical education.

INFORMATION DISTORTION

Recent research indicates that one threat to good decisions is a biased interpretation of information to favour one alternative course of action over another. Once an alternative emerges as a leader during a decision there is a strong tendency to evaluate subsequent information as supporting that option. This can occur when deciding between two competing diagnoses. It is particularly a concern if diagnostic tests provide potentially ambiguous results. This leader-driven ID is pre-decisional in nature, in that it develops during a decision and involves the interpretation of information available prior to the final decision or diagnosis, with different interpretations possible depending on whichever alternative is the leader. Studies reveal that the distortion bias is pervasive in decisions, and that awareness of the act of distortion is low in decision makers.

APPLICATION TO MEDICAL EDUCATION

Empirical research has confirmed the presence of leader-driven ID in hypothetical diagnoses made by physicians. ID creates two threats to medical decisions: First, it can make a diagnosis sticky in that it is resistant to being overturned by contradictory information. Second, it can promote unwarranted certainty in a diagnosis. The outcome may be premature closure, unnecessary testing or incorrect treatment, resulting in delayed or missed diagnoses.

METHODS

This paper summarises research related to leader-driven ID in medical and professional decisions and discusses various approaches directed towards reducing ID. A framework and language are provided for thinking about and discussing ID in medical decisions and medical education. Courses of action for mitigating the effects of ID are suggested.

Bayesian Revision vs. Information Distortion

The rational status of the Bayesian calculus for revising likelihoods is compromised by the common but still unfamiliar phenomenon of information distortion. This bias is the distortion in the evaluation of a new datum toward favoring the currently preferred option in a decision or judgment. While the Bayesian calculus requires the independent combination of the prior probability and a new datum, information distortion invalidates such independence (because the prior influences the datum). Although widespread, information distortion has not generally been recognized. First, individuals are not aware when they themselves commit this bias. In addition, it is often hidden in more obvious suboptimal phenomena. Finally, the Bayesian calculus is usually explained only with undistortable data like colored balls drawn randomly. Partly because information distortion is unrecognized by the individuals exhibiting it, no way has been devised for eliminating it. Partial reduction is possible in some situations such as presenting all data simultaneously rather than sequentially with revision after each datum. The potential dangers of information distortion are illustrated for three professional revision tasks: forecasting, predicting consumer choices from internet data, and statistical inference from experimental results. The optimality of the Bayesian calculus competes with people's natural desire that their belief systems remain coherent in the face of new data. Information distortion provides this coherence by biasing those data toward greater agreement with the currently preferred position—but at the cost of Bayesian optimality.

Choice-Supportive Misremembering: A New Taxonomy and Review

Although the literature on the influence of memory on decisions is well developed, research on the effects of decision making on memory is rather sparse and scattered. Choice-supportive misremembering (i.e., misremembering choice-related information that boosts the chosen option and/or demotes the foregone options) has been observed in several studies and has the potential to affect future choices. Nonetheless, no attempt has been made to review the relevant literature, categorize the different types of choice-supportive misremembering observed, and critically appraise the existing evidence and proposed explanations. Thus, starting from a new theoretically motivated and empirically grounded taxonomy, we review the current research. Our taxonomy classifies choice-supportive misremembering into four conceptually distinct types: misattribution is when information is attributed to the wrong source, fact distortion when the facts are remembered in a distorted manner, false memory when items that were not part of the original decision scenarios are remembered as presented and, finally, selective forgetting is when information is selectively forgotten. After assessing the impact of various potentially moderating factors, we evaluate the evidence for each type of misremembering and conclude that the support for the phenomenon is solid in relation to misattribution when recognition memory is assessed, but significantly weaker for the other three types, and when other memory tests are used to assess memory. Finally, we review the cognitive and emotional explanations proposed for choice-supportive misremembering in the light of the available evidence and identify the main gaps in the current knowledge and the more promising avenues for future research.

The Role of Physicians' First Impressions in the Diagnosis of Possible Cancers without Alarm Symptoms

BACKGROUND

First impressions are thought to exert a disproportionate influence on subsequent judgments; however, their role in medical diagnosis has not been systematically studied. We aimed to elicit and measure the association between first impressions and subsequent diagnoses in common presentations with subtle indications of cancer.

METHODS

Ninety UK family physicians conducted interactive simulated consultations online, while on the phone with a researcher. They saw 6 patient cases, 3 of which could be cancers. Each cancer case included 2 consultations, whereby each patient consulted again with nonimproving and some new symptoms. After reading an introduction (patient description and presenting problem), physicians could request more information, which the researcher displayed online. In 2 of the possible cancers, physicians thought aloud. Two raters coded independently the physicians' first utterances (after reading the introduction but before requesting more information) as either acknowledging the possibility of cancer or not. We measured the association of these first impressions with the final diagnoses and management decisions.

RESULTS

The raters coded 297 verbalizations with high interrater agreement (Kappa = 0.89). When the possibility of cancer was initially verbalized, the odds of subsequently diagnosing it were on average 5 times higher (odds ratio 4.90 [95% CI 2.72 to 8.84], P < 0.001), while the odds of appropriate referral doubled (OR 1.98 [1.10 to 3.57], P = 0.002). The number of cancer-related questions physicians asked mediated the relationship between first impressions and subsequent diagnosis, explaining 29% of the total effect.

CONCLUSION

We measured a strong association between family physicians' first diagnostic impressions and subsequent diagnoses and decisions. We suggest that interventions to influence and support the diagnostic process should target its early stage of hypothesis generation.

What You Find Depends on How You Measure It: Reactivity of Response Scales Measuring Predecisional Information Distortion in Medical Diagnosis

“Predecisional information distortion” occurs when decision makers evaluate new information in a way that is biased towards their leading option. The phenomenon is well established, as is the method typically used to measure it, termed “stepwise evolution of preference” (SEP). An inadequacy of this method has recently come to the fore: it measures distortion as the total advantage afforded a leading option over its competitor, and therefore it cannot differentiate between distortion to strengthen a leading option (“proleader” distortion) and distortion to weaken a trailing option (“antitrailer” distortion). To address this, recent research introduced new response scales to SEP. We explore whether and how these new response scales might influence the very proleader and antitrailer processes that they were designed to capture (“reactivity”). We used the SEP method with concurrent verbal reporting: fifty family physicians verbalized their thoughts as they evaluated patient symptoms and signs (“cues”) in relation to two competing diagnostic hypotheses. Twenty-five physicians evaluated each cue using the response scale traditional to SEP (a single response scale, returning a single measure of distortion); the other twenty-five did so using the response scales introduced in recent studies (two separate response scales, returning two separate measures of distortion: proleader and antitrailer). We measured proleader and antitrailer processes in verbalizations, and compared verbalizations in the single-scale and separate-scales groups. Response scales did not appear to affect proleader processes: the two groups of physicians were equally likely to bolster their leading diagnosis verbally. Response scales did, however, appear to affect antitrailer processes: the two groups denigrated their trailing diagnosis verbally to differing degrees. Our findings suggest that the response scales used to measure information distortion might influence its constituent processes, limiting their generalizability across and beyond experimental studies.