Berthet (2021) argues that addressing individual differences in susceptibility to cognitive biases requires the development of standardized and reliable measurement tools.
G. Saposnik, D. Redelmeier, C. C. Ruff, and P. N. Tobler published 'Cognitive biases associated with medical decisions: a systematic review' in BMC Medical Informatics and Decision Making in 2016.
Stanovich et al. (2008) advanced various taxonomies of cognitive biases based on dual-process models.
Guthrie et al. (2001) applied the concept of cognitive bias to legal rules by presenting judges with a problem based on the 1863 English case Byrne v. Boadle to assess their judgment regarding warehouse negligence.
Institutional investors are prone to various cognitive biases, though research by Kaustia et al. (2008) suggests they are prone to them to a lesser extent than individual investors.
Blumenthal-Barby and Krieger (2015) noted that researchers studying cognitive biases in medical decision-making use diverse strategies, though vignette-based studies are the most frequent.
Studies that review past medical errors to identify cognitive biases are vulnerable to hindsight bias because reviewers are aware that an error was committed, making them prone to identify biases ex post, according to Wears and Nemeth (2007).
The inventory of cognitive biases in medicine developed by Hershberger et al. (1994) measures 10 cognitive biases in doctors using 22 medical scenarios, including insensitivity to prior probability and insensitivity to sample size.
There is significant research interest in the impact of cognitive biases on professional decision-making across the fields of management, finance, medicine, and law.
Management professionals are prone to cognitive biases, specifically risky-choice framing effects and overconfidence among CEOs, which impact their decision-making.
The study titled 'The Impact of Cognitive Biases on Professionals' Decision-Making' reviews research on the impact of cognitive biases on professional decision-making in four specific areas: management, finance, medicine, and law.
Judicial decision-making may be influenced by cognitive biases such as framing and omission bias, as noted by Rachlinski (2018).
The true prevalence of cognitive biases influencing medical decisions remains unknown because 85% of studies targeted only one or two biases.
Guthrie et al. (2001) reported that federal magistrate judges were susceptible to cognitive biases, including anchoring, framing, hindsight bias, inverse fallacy, and egocentric bias, though to varying extents.
In the study by Zwaan et al. (2017), physicians identified more cognitive biases when the case outcome implied an incorrect diagnosis (3.45 on average) than when it implied a correct diagnosis (1.75 on average).
Blumenthal-Barby and Krieger (2015) identified a potential lack of ecological validity in vignette studies, which are frequently used to research cognitive biases.
The presence of cognitive biases was associated with diagnostic inaccuracies in 36.5% to 77% of case-scenarios.
Research in the field of medicine regarding cognitive biases includes studies by Blumenthal-Barby and Krieger (2015) (review), Croskerry (2003) (narrative), Crowley et al. (2013) (empirical), Dawson and Arkes (1987) (narrative), Detmer et al. (1978) (narrative), Elstein (1999) (narrative), Graber et al. (2005) (empirical), Klein (2005) (narrative), Mamede et al. (2010) (availability bias, empirical), Ogdie et al. (2012) (empirical), Redelmeier (2005) (narrative), Saposnik et al. (2016) (review), Schmitt and Elstein (1988) (narrative), Schnapp et al. (2018) (empirical), Stiegler and Ruskin (2012) (review), Wears and Nemeth (2007) (hindsight bias, narrative), and Zwaan et al. (2017) (empirical).
D. A. Redelmeier published 'The cognitive psychology of missed diagnoses' in the Annals of Internal Medicine in 2005, which discusses cognitive biases in medical contexts.
Generic, non-contextualized measures of cognitive biases are suitable for research aimed at describing general aspects of decision-making, as noted by Parker and Fischhoff (2005) and Bruine de Bruin et al. (2007).
Programs aimed at improving financial literacy have been used to mitigate the impact of cognitive biases on financial decision-making, as noted by Lusardi and Mitchell (2014).
The study 'The Impact of Cognitive Biases on Professionals' Decision-Making' aims to assess the claim that cognitive biases impact professionals' decision-making, assess the level of evidence reported in empirical studies, and identify research gaps.
Peer and Gamliel (2013) reviewed how cognitive biases intervene in the judicial process, specifically confirmation and hindsight bias during hearings, the inability to ignore inadmissible evidence during rulings, and anchoring effects during sentencing.
The author identifies a potential lack of ecological validity in vignette studies, which are frequently used to research cognitive biases in professional decision-making.
Das and Teng (1999) hypothesized that the presence of specific cognitive biases is contingent upon the specific decision-making process engaged in by the decision maker, rather than being robust across all processes.
Research in the field of law regarding cognitive biases includes studies by Berlin and Hendrix (1998) (hindsight bias, narrative), Bystranowski et al. (2021) (anchoring effect, review), Casper et al. (1989) (hindsight bias, empirical), Chapman and Bornstein (1996) (anchoring effect, empirical), Cheney et al. (1989) (hindsight bias, empirical), Englich et al. (2005) (anchoring effect, empirical), Englich et al. (2006) (anchoring effect, empirical), Enough and Mussweiler (2001) (anchoring effect, empirical), Findley and Scott (2006) (confirmation bias, theoretical), Guthrie et al. (2001) (empirical), Guthrie et al. (2007) (empirical), Guthrie et al. (2002) (narrative), Harley (2007) (hindsight bias, review), Hastie et al. (1999) (anchoring effect, empirical), Helm et al. (2016) (empirical), Hinsz and Indahl (1995) (anchoring effect, empirical), Kamin and Rachlinski (1995) (hindsight bias, empirical), LaBine and LaBine (1996) (hindsight bias, empirical), Lidén et al. (2019) (confirmation bias, empirical), O’Brien (2009) (confirmation bias, empirical), Oeberst and Goeckenjan (2016) (hindsight bias, review), Peer and Gamliel (2013) (narrative), Rachlinski and Wistrich (2017) (narrative), Rachlinski (2018) (framing effect, empirical), Rachlinski et al. (2011) (hindsight bias, empirical), Rachlinski et al. (2015) (anchoring effect, empirical), and Robbennolt and Studebaker (1999) (anchoring effect, empirical).
Helm, Wistrich, and Rachlinski (2016) investigated whether arbitrators are subject to human cognitive biases in their decision-making processes.
The author argues that the neglect of individual differences in cognitive biases may lead to the incorrect assumption that all professionals are susceptible to biases to the same extent.
Research in management decision-making has documented various cognitive biases, including overconfidence (Ben-David et al. 2013; Malmendier and Tate 2005, 2008; Moore et al. 2007), hindsight bias (Bukszar and Connolly 1988), the framing effect (Hodgkinson et al. 1999), the anchoring effect (Joyce and Biddle 1981), and blind spot bias (Zajac and Bazerman 1991).
Only 35% (seven studies) of reviewed studies provided information to evaluate the association between physicians' cognitive biases and therapeutic or management errors.
71.4% (five of seven) of studies that evaluated the association between cognitive biases and therapeutic or management errors found a positive association.
Judges often dismiss evidence regarding the impact of cognitive biases on judicial decisions by arguing that most studies fail to investigate decisions made in real cases, as noted by Dhami and Belton in 2017.
There is evidence for individual differences in susceptibility to cognitive biases, as documented by Bruine de Bruin et al. (2007).
Overconfidence and the disposition effect are two cognitive biases frequently studied in investment decision-making, according to a systematic review by Kumar and Goyal (2015).
Financial economists distinguish between two types of investors: arbitrageurs, who are assumed to be fully rational, and noise traders, who are prone to cognitive biases.
Early papers on cognitive bias in medical decision-making, such as those by Dawson and Arkes (1987), Elstein (1999), and Redelmeier (2005), primarily utilized narrative reviews to describe how cognitive shortcuts can lead physicians to make poor decisions like wrong diagnoses.
Maule and Hodgkinson (2002) argued that the claim that cognitive biases influence strategic decisions requires direct testing through laboratory research and experimental studies.
Noise traders, who are prone to cognitive biases, often hold under-diversified portfolios, leading to suboptimal portfolio management.
Hershberger et al. (1994) developed a test to measure cognitive bias specifically within the context of medical decision-making.
L. Zwaan, S. Monteiro, J. Sherbino, J. Ilgen, B. Howey, and G. Norman published 'Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups' in BMJ Quality & Safety in 2017.
Decision-making research generally neglects individual differences in cognitive biases, a limitation noted by Stanovich et al. (2011) and Mohammed and Schwall (2012).
Guthrie et al. (2001) surveyed 167 federal magistrate judges to assess the impact of five cognitive biases—anchoring, framing, hindsight bias, inverse fallacy, and egocentric bias—on their decisions regarding litigation problems.
Blumenthal-Barby and Krieger (2015) published a systematic review of 213 studies on the impact of cognitive biases on medical decision-making.
The literature search for the study 'The Impact of Cognitive Biases on Professionals' Decision-Making' was conducted using the Web of Science (WoS) database with the search terms 'cognitive biases AND decision making' and included research articles, review articles, or book chapters without time restrictions.
Kahneman, Slovic, and Tversky (1982) edited a collection of research titled 'Judgment Under Uncertainty: Heuristics and Biases', which established the study of cognitive biases in decision-making.
Debiasing has been proposed as a method to reduce the effects of cognitive biases in medical decision-making, according to research by Graber et al. (2002, 2012), Croskerry (2003), and Croskerry et al. (2013).
Heuristics are simplified information processing strategies that people use when making judgments or decisions, which can result in systematic, predictable errors known as cognitive biases.
Research suggests that legal professionals, including judges and prosecutors, may rely on heuristics to make decisions, which creates opportunities for cognitive biases to influence outcomes.
Herding is a cognitive bias where investors blindly follow the actions of other investors, as noted by Grinblatt et al. (1995).
T. K. Das and B. Teng published 'Cognitive biases and strategic decision processes: An integrative perspective' in the Journal of Management Studies in 1999.
Research in behavioral finance has identified several cognitive biases affecting financial decision-making, including overconfidence (Barber and Odean 2000, 2001; Chuang and Lee 2006; Glaser and Weber 2007; Odean 1999), loss aversion (Benartzi and Thaler 1995), the disposition effect (Boolell-Gunesh et al. 2009; Odean 1998; Shefrin and Statman 1985), home bias (Coval and Moskowitz 1999), regression to the mean (De Bondt and Thaler 1985), and herding behavior (Grinblatt et al. 1995).
A methodology for studying cognitive biases in medical decision-making involves reviewing instances where errors occurred to determine if cognitive biases contributed to the error, as seen in Graber et al. (2005).
While the influence of cognitive biases on strategic decision-making is widely recognized, the empirical evidence supporting this connection is considered weak, with most existing research relying on narrative papers, documentary sources, and anecdotal evidence.
Research on cognitive biases has expanded from lay participants to professional decision-making in management (Maule and Hodgkinson, 2002), finance (Baker and Nofsinger, 2002), medicine (Blumenthal-Barby and Krieger, 2015), and law (Rachlinski, 2018).
The framework proposed by Das and Teng (1999) regarding the relationship between cognitive biases and decision-making modes lacks support from rigorous empirical evidence.
The paper 'The Impact of Cognitive Biases on Professionals' Decision-Making' aims to provide an overview of the impact of cognitive biases on professional decision-making in the fields of management, finance, medicine, and law.
Saposnik et al. (2016) conducted a systematic review on the impact of cognitive biases on medical decision-making that included 20 studies.
Home bias is a cognitive bias where investors allocate the majority of their portfolio to domestic equities rather than diversifying into foreign equities, as described by Coval and Moskowitz (1999).
60% of studies (N = 12) targeted cognitive biases in diagnostic tasks.
In their review of 213 studies, Blumenthal-Barby and Krieger (2015) found that 77% (N=164) were based on hypothetical vignettes, 34% (N=73) investigated medical personnel, 82% (N=175) were conducted with representative populations, and 68% (N=145) confirmed a bias or heuristic in the study population.
The article 'The Impact of Cognitive Biases on Professionals' Decision-Making: A Review of Four Occupational Areas' examines the role of cognitive biases and heuristics within the fields of management, finance, medicine, and law.
Research on cognitive biases in finance relies primarily on secondary data, whereas research in medicine and law relies mainly on primary data from vignette studies.
The study selected 79 eligible articles for the final review based on two inclusion criteria: the article had a clear focus on cognitive biases and decision-making, and the article reported a review or a representative empirical study.
Das and Teng (1999) proposed a framework linking four cognitive biases (prior hypotheses and focusing on limited targets, exposure to limited alternatives, insensitivity to outcome probabilities, and illusion of manageability) to five modes of decision-making (rational, avoidance, logical incrementalist, political, and garbage can).
While reliable measures exist for approximately a dozen cognitive biases, measures for key biases such as confirmation bias and availability bias are currently lacking.
Research on cognitive biases in strategic decision-making is scarce, likely due to a lack of ecological validity, which is considered an issue of primary importance in management research by Schwenk (1982).
The article titled 'The Impact of Cognitive Biases on Professionals' Decision-Making: A Review of Four Occupational Areas' by V. Berthet was published in Frontiers in Psychology on January 4, 2022.
Framing effect and overconfidence were the most common cognitive biases studied (N = 5 each), while tolerance to risk or ambiguity was the most common personality trait studied (N = 5).
A review of research on cognitive biases in management, finance, medicine, and law identified that a dozen cognitive biases impact professional decision-making, with overconfidence being the most recurrent bias.
Zwaan et al. (2017) conducted a study where 37 physicians read eight cases and identified which cognitive biases were present from a provided list.