Hal R. Arkes

Attributions of Implicit Prejudice, or "Would Jesse Jackson 'Fail' the Implicit Association Test?"

Measures of implicit prejudice are based on associations between race-related stimuli and valenced words. Reaction time (RT) data have been characterized as showing implicit prejudice when White names or faces are associated with positive concepts and African-American names or faces with negative concepts, compared to the reverse pairings. We offer three objections to the inferential leap from the comparative RT of different associations to the attribution of implicit prejudice: (a) The data may reflect shared cultural stereotypes rather than personal animus, (b) the affective negativity attributed to participants may be due to cognitions and emotions that are not necessarily prejudiced, and (c) the patterns of judgment deemed to be indicative of prejudice pass tests deemed to be diagnostic of rational behavior.

Systematic errors in medical decision making: judgment limitations.

Much of medical practice involves the exercise of such basic cognitive tasks as estimating probabilities and synthesizing information. Scientists studying cognitive processes have identified impediments to accurate performance on these tasks. Together the impediments foster “cognitive bias.” Five factors that can detract from accurate probability estimation and three that impair accurate information synthesis are discussed. Examples of all eight factors are illustrated by reference to published articles. The authors suggest ways to minimize the negative influences of these factors.

Overconfidence in Judgmental Forecasting

Overconfidence is a common finding in the forecasting research literature. Judgmental overconfidence leads people (1) to neglect decision aids, (2) to make predictions contrary to the base rate, and (3) to succumb to “groupthink.” To counteract overconfidence forecasters should heed six principles: (1) Consider alternatives, especially in new situations; (2) List reasons why the forecast might be wrong; (3) In group interaction, appoint a devil’s advocate; (4) Make an explicit prediction and then obtain feedback; (5) Treat the feedback you receive as valuable information; (6) When possible, conduct experiments to test prediction strategies. These principles can help people to avoid generating only reasons that bolster their predictions and to learn optimally by comparing a documented prediction with outcome feedback.

Patients Derogate Physicians Who Use a Computer-Assisted Diagnostic Aid

Objective . To ascertain whether a physician who uses a computer-assisted diagnostic support system (DSS) would be rated less capable than a physician who does not. Method . Students assumed the role of a patient with a possible ankle fracture (experiment 1) or a possible deep vein thrombosis (experiment 2). They read a scenario that described an interaction with a physician who used no DSS, one who used an unspecified DSS, or one who used a DSS developed at a prestigious medical center. Participants were then asked to rate the interaction on 5 criteria, the most important of which was the diagnostic ability of the physician. In experiment 3, 74 patients in the waiting room of a clinic were randomly assigned to the same 3 types of groups as used in experiment 1. In experiment 4, 131 3rd- and 4th-year medical students read a scenario of a physician-patient interaction and were randomly assigned to 1 of 4 groups: the physician used no DSS, heeded the recommendation of a DSS, defied a recommendation of a DSS by treating in a less aggressive manner, or defied a recommendation of a DSS by treating in a more aggressive manner . Results . The participants always deemed the physician who used no decision aid to have the highest diagnostic ability. Conclusion . Patients may surmise that a physician who uses a DSS is not as capable as a physician who makes the diagnosis with no assistance from a DSS. Key words: decision support techniques; diagnosis computer assisted; patient satisfaction. (Med Decis Making 2007; 27: 189—202)

Psychological Research and the Prostate-Cancer Screening Controversy

In October of 2011, the U.S. Preventive Services Task Force released a draft report in which they recommended against using the prostate-specific antigen (PSA) test to screen for prostate cancer. We attempt to show that four factors documented by psychological research can help explain the furor that followed the release of the task force’s report. These factors are the persuasive power of anecdotal (as opposed to statistical) evidence, the influence of personal experience, the improper evaluation of data, and the influence of low base rates on the efficacy of screening tests. We suggest that augmenting statistics with facts boxes or pictographs might help such committees communicate more effectively with the public and with the U.S. Congress.

Failure to Adopt Beneficial Therapies Caused by Bias in Medical Evidence Evaluation

Background. Although it is known that many evidencebased therapies are underutilized, the causes of the research-practice gap are not well understood. The authors sought to determine if there is a bias in the evaluation of new evidence that leads to low rates of adoption of beneficial therapies compared to abandonment of harmful ones. Methods. Two case vignettes describing hypothetical clinical trials were administered to 2 independent samples of pulmonary and critical care practitioners. Each vignette was presented in 2 different ways; in one version, the results of the hypothetical trial showed that a treatment was harmful, and in the other version, the same treatment was shown to be beneficial. Prospective respondents from each sample were randomized to receive 1 version of each vignette (intersubject design). The main outcome was respondents willingness to apply the results of the hypothetical trial to patient care. Results. There were 174 participants for trial 1 and 138 participants for trial 2 (enrollment rates of 44.2% and 41.8%, respectively). For trial 1, respondents were 2.3 times less likely to change clinical practice based on results indicating benefit as opposed to harm (33.3% v. 76.5%; P < 0.0001). Similarly, for trial 2, respondents were 2.57 times less likely to change practice when trial results showed that early use was beneficial as opposed to showing that early use was harmful (37.1% v. 95.3%; P < 0.0001). Conclusions. When evaluating clinical trials, physicians demonstrate less willingness to adopt beneficial therapies than to abandon harmful ones. This difference may contribute to the research-practice gap.

Why Do Patients Derogate Physicians Who Use a Computer-Based Diagnostic Support System?

Objective. To better understand 1) why patients have a negative perception of the use of computerized clinical decision support systems (CDSSs) and 2) what contributes to the documented heterogeneity in the evaluations of physicians who use a CDSS. Methods. Three vignette-based studies examined whether negative perceptions stemmed directly from the use of a computerized decision aid or the need to seek external advice more broadly (experiment 1) and investigated the contributing role of 2 individual difference measures, attitudes toward statistics (ATS; experiment 2) and the Multidimensional Health Locus of Control Scale (MHLC; experiment 3), to these findings. Results. A physician described as making an unaided diagnosis was rated significantly more positively on a number of attributes than a physician using a computerized decision aid but not a physician who sought the advice of an expert colleague (experiment 1). ATS were unrelated to perceptions of decision aid use (experiment 2); however, greater internal locus of control was associated with more positive feelings about unaided care and more negative feelings about care when a decision aid was used (experiment 3). Conclusion. Negative perceptions of computerized decision aid use may not be a product of the need to seek external advice more generally but may instead be specific to the use of a nonhuman tool and may be associated with individual differences in locus of control. Together, these 3 studies may be used to guide education efforts for patients.

The Consequences of the Hindsight Bias in Medical Decision Making

The hindsight bias manifests in the tendency to exaggerate the extent to which a past event could have been predicted beforehand. This bias has particularly detrimental effects in the domain of medical decision making. I present a demonstration of the bias, its contribution to overconfidence, and its involvement in judgments of medical malpractice. Finally, I point out that physicians and psychologists can collaborate to the mutual benefit of both professions.

Are Residents’ Decisions Influenced More by a Decision Aid or a Specialist’s Opinion? A Randomized Controlled Trial

BACKGROUNDPhysicians are reluctant to use decision aids despite their ability to improve care. A potential reason may be that physicians do not believe decision aid advice.OBJECTIVETo determine whether internal medicine residents lend more credence to contradictory decision aid or human advice.DESIGNRandomized controlled trial. Residents read a scenario of a patient with community-acquired pneumonia and were asked whether they would admit the patient to the intensive care unit or the floor. Residents were randomized to receive contrary advice from either a referenced decision aid or an anonymous pulmonologist. They were then asked, in light of this new information, where they would admit the patient.PARTICIPANTSOne hundred eight internal medicine residents.MEASUREMENTSThe percentage of residents who changed their admission location and the change in confidence in the decision.MAIN RESULTSResidents were more likely to change their original admission location (OR 2.3, 95% CI 1.04 to 5.1, P = 0.04) and to reduce their confidence in the decision (adjusted difference between means −12.9%, 95% CI −3.0% to −22.8%, P = 0.011) in response to the referenced decision aid than to the anonymous pulmonologist. Confidence in their decision was more likely to change if they initially chose to admit the patient to the floor.CONCLUSIONSIn a hypothetical case of community-acquired pneumonia, physicians were influenced more by contrary advice from a referenced decision aid than an anonymous specialist. Whether this holds for advice from a respected specialist or in actual practice remains to be studied.

The Influence of Treatment Effect Size on Willingness to Adopt a Therapy

Background. Physicians are slow to adopt novel therapies, and the reasons for this are poorly understood. The authors sought to determine if the size of the treatment effect of a novel therapy influences willingness to adopt it. Methods. We developed 2 experimental vignette pairs describing a trial of a therapy for a hypothetical disease that showed a statistically significant mortality benefit. The size of the mortality effect was varied in vignettes of a pair (3% v. 10%). The 2 experimental vignette pairs differed in whether study enrollment was reported. Vignettes were mailed to a random sample of physicians using an intersubject design. The main study outcome was respondents’ willingness to adopt the hypothetical therapy, based on the results of the hypothetical trial. Results. There were 124 and 89 respondents to vignette pairs 1 and 2, respectively. In vignette pair 1, 91% versus 71% of respondents adopted the therapy when it reduced mortality by 10% and 3%, respectively (P = 0.0058). For vignette pair 2, 88% versus 51% of respondents adopted the therapy when it reduced mortality by 10% and 3%, respectively (P = 0.0002). In both vignette pairs, nonadopters were more likely than adopters to report side effects of the therapy as a principal reason for their decision. Conclusions. In this study, respondents were less likely to adopt a lifesaving therapy if its associated mortality reduction was 3% compared to 10%. Because most therapies for major medical conditions reduce mortality within or below this range, and because there were no opportunity costs associated with the adoption of the therapy, we believe that this effect represents a bias. Further investigation will be required to determine its prevalence and mechanism.