Sandra Monteiro

Sample size calculations: should the emperor’s clothes be off the peg or made to measure?

Ethics committees require estimates of sample size for all trials, but statistical calculations are no more accurate than estimates from historical data. Geoffrey Norman and colleagues propose some “one size fits all” numbers for different study designs

The etiology of diagnostic errors: a controlled trial of system 1 versus system 2 reasoning.

Purpose Diagnostic errors are thought to arise from cognitive biases associated with System 1 reasoning, which is rapid and unconscious. The primary hypothesis of this study was that the instruction to be slow and thorough will have no advantage in diagnostic accuracy over the instruction to proceed rapidly. Method Participants were second-year residents who volunteered after they had taken the Medical Council of Canada (MCC) Qualifying Examination Part II. Participants were tested at three Canadian medical schools (McMaster, Ottawa, and McGill) in 2010 (n = 96) and 2011 (n = 108). The intervention consisted of 20 computer-based internal medicine cases, with instructions either (1) to be as quick as possible but not make mistakes (the Speed cohort, 2010), or (2) to be careful, thorough, and reflective (the Reflect cohort, 2011). The authors examined accuracy scores on the 20 cases, time taken to diagnose cases, and MCC examination performance. Results Overall accuracy in the Speed condition was 44.5%, and in the Reflect condition was 45.0%; this was not significant. The Speed cohort took an average of 69 seconds per case versus 89 seconds for the Reflect cohort (P < .001). In both cohorts, cases diagnosed incorrectly took an average of 17 seconds longer than cases diagnosed correctly. Diagnostic accuracy was moderately correlated with performance on both written and problem-solving components of the MCC licensure examination and inversely correlated with time. Conclusions The study demonstrates that simply encouraging slowing down and increasing attention to analytical thinking is insufficient to increase diagnostic accuracy.

Predictable chaos: a review of the effects of emotions on attention, memory and decision making

Healthcare practice and education are highly emotional endeavors. While this is recognized by educators and researchers seeking to develop interventions aimed at improving wellness in health professionals and at providing them with skills to deal with emotional interpersonal situations, the field of health professions education has largely ignored the role that emotions play on cognitive processes. The purpose of this review is to provide an introduction to the broader field of emotions, with the goal of better understanding the integral relationship between emotions and cognitive processes. Individuals, at any given time, are in an emotional state. This emotional state influences how they perceive the world around them, what they recall from it, as well as the decisions they make. Rather than treating emotions as undesirable forces that wreak havoc on the rational being, the field of health professions education could be enriched by a greater understanding of how these emotions can shape cognitive processes in increasingly predictable ways.

The Causes of Errors in Clinical Reasoning: Cognitive Biases, Knowledge Deficits, and Dual Process Thinking

Contemporary theories of clinical reasoning espouse a dual processing model, which consists of a rapid, intuitive component (Type 1) and a slower, logical and analytical component (Type 2). Although the general consensus is that this dual processing model is a valid representation of clinical reasoning, the causes of diagnostic errors remain unclear. Cognitive theories about human memory propose that such errors may arise from both Type 1 and Type 2 reasoning. Errors in Type 1 reasoning may be a consequence of the associative nature of memory, which can lead to cognitive biases. However, the literature indicates that, with increasing expertise (and knowledge), the likelihood of errors decreases. Errors in Type 2 reasoning may result from the limited capacity of working memory, which constrains computational processes. In this article, the authors review the medical literature to answer two substantial questions that arise from this work: (1) To what extent do diagnostic errors originate in Type 1 (intuitive) processes versus in Type 2 (analytical) processes? (2) To what extent are errors a consequence of cognitive biases versus a consequence of knowledge deficits? The literature suggests that both Type 1 and Type 2 processes contribute to errors. Although it is possible to experimentally induce cognitive biases, particularly availability bias, the extent to which these biases actually contribute to diagnostic errors is not well established. Educational strategies directed at the recognition of biases are ineffective in reducing errors; conversely, strategies focused on the reorganization of knowledge to reduce errors have small but consistent benefits.

Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups

Background Many authors have implicated cognitive biases as a primary cause of diagnostic error. If this is so, then physicians already familiar with common cognitive biases should consistently identify biases present in a clinical workup. The aim of this paper is to determine whether physicians agree on the presence or absence of particular biases in a clinical case workup and how case outcome knowledge affects bias identification. Methods We conducted a web survey of 37 physicians. Each participant read eight cases and listed which biases were present from a list provided. In half the cases the outcome implied a correct diagnosis; in the other half, it implied an incorrect diagnosis. We compared the number of biases identified when the outcome implied a correct or incorrect primary diagnosis. Additionally, the agreement among participants about presence or absence of specific biases was assessed. Results When the case outcome implied a correct diagnosis, an average of 1.75 cognitive biases were reported; when incorrect, 3.45 biases (F=71.3, p<0.00001). Individual biases were reported from 73% to 125% more often when an incorrect diagnosis was implied. There was no agreement on presence or absence of individual biases, with κ ranging from 0.000 to 0.044. Interpretation Individual physicians are unable to agree on the presence or absence of individual cognitive biases. Their judgements are heavily influenced by hindsight bias; when the outcome implies a diagnostic error, twice as many biases are identified. The results present challenges for current error reduction strategies based on identification of cognitive biases.

Disrupting diagnostic reasoning: do interruptions, instructions, and experience affect the diagnostic accuracy and response time of residents and emergency physicians?

Purpose Others have suggested that increased time pressure, sometimes caused by interruptions, may result in increased diagnostic errors. The authors previously found, however, that increased time pressure alone does not result in increased errors, but they did not test the effect of interruptions. It is unclear whether experience modulates the combined effects of time pressure and interruptions. This study investigated whether increased time pressure, interruptions, and experience level affect diagnostic accuracy and response time. Method In October 2012, 152 residents were recruited at five Medical Council of Canada Qualifying Examination Part II test sites. Forty-six emergency physicians were recruited from one Canadian and one U.S. academic health center. Participants diagnosed 20 written general medicine cases. They were randomly assigned to receive fast (time pressure) or slow condition instructions. Visual and auditory case interruptions were manipulated as a within-subject factor. Results Diagnostic accuracy was not affected by interruptions or time pressure but was related to experience level: Emergency physicians were more accurate (71%) than residents (43%) (F = 234.0, P < .0001) and responded more quickly (54 seconds) than residents (65 seconds) (F = 9.0, P < .005). Response time was shorter for participants in the fast condition (55 seconds) than in the slow condition (73 seconds) (F = 22.2, P < .0001). Interruptions added about 8 seconds to response time. Conclusions Experienced emergency physicians were both faster and more accurate than residents. Instructions to proceed quickly and interruptions had a small effect on response time but no effect on accuracy.

Event-related potentials as brain correlates of item specific proportion congruent effects.

The item-specific proportion congruency (ISPC) effect is consistent with the idea that control processes can be applied rapidly in accord with previously experienced conflict for a particular category. An alternative account of this effect is that it reflects item-specific learning processes unrelated to control at the level of the category. The accounts predict the same behaviour but differ in terms of electrophysiological predictions. Two experiments examined the ISPC effect with a particular focus on neural correlates that might reveal whether, and how early in processing, high and low proportion congruent items are treated as distinct classes of stimuli. For both tasks, the proportion congruency category was distinguished prior to the congruence of the specific stimulus, as early as 100 ms post-stimulus onset for the global/local identification task (Experiment 1) and 150 ms for the Stroop task (Experiment 2). The results support an on-line control account of ISPC effects.

Examining the Influence of Context and Professional Culture on Clinical Reasoning Through Rhetorical-Narrative Analysis

According to the dual process model of reasoning, physicians make diagnostic decisions using two mental systems: System 1, which is rapid, unconscious, and intuitive, and System 2, which is slow, rational, and analytical. Currently, little is known about physicians’ use of System 1 or intuitive reasoning in practice. In a qualitative study of clinical reasoning, physicians were asked to tell stories about times when they used intuitive reasoning while working up an acutely unwell patient, and we combine socio-narratology and rhetorical theory to analyze physicians’ stories. Our analysis reveals that in describing their work, physicians draw on two competing narrative structures: one that is aligned with an evidence-based medicine approach valuing System 2 and one that is aligned with cooperative decision making involving others in the clinical environment valuing System 1. Our findings support an understanding of clinical reasoning as distributed, contextual, and influenced by professional culture.

The 3 faces of clinical reasoning: Epistemological explorations of disparate error reduction strategies

There is general consensus that clinical reasoning involves 2 stages: a rapid stage where 1 or more diagnostic hypotheses are advanced and a slower stage where these hypotheses are tested or confirmed. The rapid hypothesis generation stage is considered inaccessible for analysis or observation. Consequently, recent research on clinical reasoning has focused specifically on improving the accuracy of the slower, hypothesis confirmation stage. Three perspectives have developed in this line of research, and each proposes different error reduction strategies for clinical reasoning. This paper considers these 3 perspectives and examines the underlying assumptions. Additionally, this paper reviews the evidence, or lack of, behind each class of error reduction strategies. The first perspective takes an epidemiological stance, appealing to the benefits of incorporating population data and evidence-based medicine in every day clinical reasoning. The second builds on the heuristic and bias research programme, appealing to a special class of dual process reasoning models that theorizes a rapid error prone cognitive process for problem solving with a slower more logical cognitive process capable of correcting those errors. Finally, the third perspective borrows from an exemplar model of categorization that explicitly relates clinical knowledge and experience to diagnostic accuracy.

Eyeballing: the use of visual appearance to diagnose ‘sick’

Prior studies suggest that clinicians can categorise patients in an emergency room as ‘sick’ or ‘not sick’ using rapid visual assessment. The rapid nature of these decisions suggests clinicians are relying on pattern recognition or System 1 processing; however, this has not been studied experimentally. In this study, we explore the accuracy of these decisions using patient disposition (discharge, admission to ward or admission to critical care) as an objective outcome, and collect evidence to argue for the use of System 1 processing in the ‘sick’ or ‘not sick’ decision process.