Cognitive bias and decision making

BACKGROUND: Large language models (LLMs) are computational artificial intelligence systems with advanced natural language processing capabilities that have recently been popularized among health care students and educators due to their ability to provide real-time access to a vast amount of medical knowledge. The adoption of LLM technology into medical education and training has varied, and little empirical evidence exists to support its use in clinical teaching environments. OBJECTIVE: The aim of the study is to identify and qualitatively evaluate potential use cases and limitations of LLM technology for real-time ward-based educational contexts...

We examined whether and how embodied decision biases-related to motor costs (MC) as well as cognitive crosstalk (CC) due to the body state-are influenced by extended deliberation time. Participants performed a tracking task while concurrently making reward-based decisions, with rewards being presented with varying preview time. In Experiment 1 ( N = 58), we observed a reduced CC bias with extended preview time. Partially, this was due to participants slightly adapting tracking to serialize it in relation to decision making...

BACKGROUND: Zoledronate, a bisphosphonate, is a potent first-line treatment for osteoporosis. It is also a preferred treatment for hypercalcemia especially when unresponsive to intravenous fluids. Bisphosphonates can cause acute phase reactions that mimic opioid withdrawal symptoms, which can confound provider decision-making. Our case highlights cognitive bias involving a patient with opioid use disorder who received zoledronate for hypercalcemia secondary to immobilization and significant bone infection...

INTRODUCTION: Despite converging evidence that people more closely associate the construct of criminality with Black people who exhibit a more African facial phenotype than Black people who express a more European phenotype, eyewitness researchers have largely ignored phenotypic bias as a potential contributor to the racial disparities in the criminal legal system. If this form of phenotypic bias extends to eyewitness identification tasks, eyewitnesses may be more likely to identify Black suspects with an African rather than European phenotype, regardless of their guilt status...

Humans, even as infants, use cognitive strategies, such as exploration and hypothesis testing, to learn about causal interactions in the environment. In animal learning studies, however, it is challenging to disentangle higher-order behavioral strategies from errors arising from imperfect task knowledge or inherent biases. Here, we trained head-fixed mice on a wheel-based auditory two-choice task and exploited the intra- and inter-animal variability to understand the drivers of errors during learning. During learning, performance errors are dominated by a choice bias, which, despite appearing maladaptive, reflects a dynamic strategy...

Emergency physicians (EPs) navigate high-pressure environments, making rapid decisions amidst ambiguity. Their choices are informed by a complex interplay of experience, information, and external forces. While cognitive shortcuts (heuristics) expedite assessments, there are multiple ways they can be subtly manipulated, potentially leading to reflexive control: external actors steering EPs' decisions for their own benefit. Pharmaceutical companies, device manufacturers, and media narratives are among the numerous factors that influence the EPs' information landscape...

Policy compression is a computational framework that describes how capacity-limited agents trade reward for simpler action policies to reduce cognitive cost. In this study, we present behavioral evidence that humans prefer simpler policies, as predicted by a capacity-limited reinforcement learning model. Across a set of tasks, we find that people exploit structure in the relationships between states, actions, and rewards to "compress" their policies. In particular, compressed policies are systematically biased towards actions with high marginal probability, thereby discarding some state information...

UNLABELLED: The Human Papillomavirus (HPV) is a frequently occurring sexually transmitted infection in adults and is associated with various cancers that can affect both males and females. Recently, the Advisory Committee on Immunization Practices (ACIP) expanded its recommendations for the HPV vaccine to include patients aged 27-45 years with shared clinical decision-making. A commonly reported obstacle to receiving the HPV vaccine among adults is a lack of healthcare provider recommendations...

RATIONALE & OBJECTIVE: Older people with progressive chronic kidney disease (CKD) have complex health care needs. Geriatric evaluation preceding decision making for kidney replacement is recommended in guidelines, but implementation is lacking in routine care. We aimed to evaluate implementation of geriatric assessment in CKD care. STUDY DESIGN: Mixed methods implementation study. SETTING & PARTICIPANTS: Dutch nephrology centers were approached for implementation of geriatric assessment in patients aged ≥70 years and with an estimated glomerular filtration rate of ≤20 mL/min/1...

Interdisciplinary fetal neonatal neurology (FNN) training requires integration of reproductive health factors into evaluations of the maternal-placental-fetal (MPF) triad, neonate, and child over the first 1000 days. Serial events that occur before one or multiple pregnancies impact successive generations. A maternal-child dyad history highlights this continuity of health risk, beginning with a maternal grandmother's pregnancy. Her daughter was born preterm and later experienced polycystic ovarian syndrome further complicated by cognitive and mental health disorders...

In many everyday decisions, individuals choose between trialling something novel or something they know well. Deciding when to try a new option or stick with an option that is already known to you, known as the "explore/exploit" dilemma, is an important feature of cognition that characterises a range of decision-making contexts encountered by humans. Recent evidence has suggested preferences in explore/exploit biases are associated with psychopathology, although this has typically been examined within individual disorders...

Gambles that involve a large but unlikely gain coupled with a small but likely loss-like a lottery ticket-are known as positively-skewed. There is evidence that people tend to prefer these positively skewed choices, leading to what is called a positive-skew bias. In this study, we attempt to better understand under what conditions people are more drawn toward positively skewed, relative to symmetric, gambles. Based on the animal literature, there is reason to believe that preference for skewed gambles is dependent on the strength of the skew, with a greater preference for more strongly skewed options...

Interdisciplinary fetal-neonatal neurology (FNN) training considers a woman's reproductive and pregnancy health histories when assessing the "four great neonatal neurological syndromes". This maternal-child dyad exemplifies the symptomatic neonatal minority, compared with the silent majority of healthy children who experience preclinical diseases with variable expressions over the first 1000 days. Healthy maternal reports with reassuring fetal surveillance testing preceded signs of fetal distress during parturition...

Social information can be used to optimize decision-making. However, the simultaneous presentation of multiple sources of advice can lead to a distinction bias in judging the validity of the information. While the involvement of event-related potential (ERP) components in social information processing has been studied, how they are modulated by (mis)judging an advisor's information validity remains unknown. In two experiments participants performed a decision-making task with highly accurate or inaccurate cues...

BACKGROUND: Alzheimer's disease (AD) is the leading cause of dementia, resulting in impairments in memory, cognition, decision-making, and social skills. Thus, accurate preclinical diagnosis of Alzheimer's disease is paramount. The identification of biomarkers for Alzheimer's disease through magnetic resonance spectroscopy (MRS) represents a novel adjunctive diagnostic approach. OBJECTIVE: This study conducted a meta-analysis of the diagnostic results of this technology to explore its feasibility and accuracy...

Algorithmic bias occurs when algorithms incorporate biases in the human decisions on which they are trained. We find that people see more of their biases (e.g., age, gender, race) in the decisions of algorithms than in their own decisions. Research participants saw more bias in the decisions of algorithms trained on their decisions than in their own decisions, even when those decisions were the same and participants were incentivized to reveal their true beliefs. By contrast, participants saw as much bias in the decisions of algorithms trained on their decisions as in the decisions of other participants and algorithms trained on the decisions of other participants...

Cognitive bias may lead to diagnostic error in the patient encounter. There are hundreds of different cognitive biases, but certain biases are more likely to affect patient diagnosis and management. As during morbidity and mortality rounds, retrospective evaluation of a given case, with comparison to an optimal diagnosis, can pinpoint errors in judgment and decision-making. The study of cognitive bias also illuminates how we might improve the diagnostic process. In Part 1 of this series, cognitive bias is defined and placed within the background of dual process theory, emotion, heuristics, and the more neutral term judgment and decision-making bias...

Cognitive bias may lead to medical error, and awareness of cognitive pitfalls is a potential first step to addressing the negative consequences of cognitive bias (see Part 1). For decision-making processes that occur under uncertainty, which encompass most physician decisions, a so-called "adaptive toolbox" is beneficial for good decisions. The adaptive toolbox is inclusive of broad strategies like cultural humility, emotional intelligence, and self-care that help combat implicit bias, negative consequences of affective bias, and optimize cognition...

INTRODUCTION: Task set inhibition supports optimal switching among tasks by actively suppressing the interference from recently executed competing task sets. It is typically studied in cued task-switching paradigms where there is no uncertainty about the task set or rule to prepare for on each trial. While inhibition has been shown to influence the speed and the accuracy of task execution, affecting task set retrieval, preparation, or implementation in conditions of task set switching, it remains uninvestigated whether it also affects rule selection under uncertainty...

BACKGROUND: Intensive care unit (ICU) clinicians encounter frequent challenges with managing vast amounts of fragmented data while caring for multiple critically ill patients simultaneously. This may lead to increased provider cognitive load that may jeopardize patient safety. OBJECTIVES: This systematic review assesses the impact of centralized multi-patient dashboards on ICU clinician performance, perceptions regarding the use of these tools, and patient outcomes...