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The Behavioral and Brain Sciences May 2019Rationalization occurs when a person has performed an action and then concocts the beliefs and desires that would have made it rational. Then, people often adjust their...
Rationalization occurs when a person has performed an action and then concocts the beliefs and desires that would have made it rational. Then, people often adjust their own beliefs and desires to match the concocted ones. While many studies demonstrate rationalization, and a few theories describe its underlying cognitive mechanisms, we have little understanding of its function. Why is the mind designed to construct post hoc rationalizations of its behavior, and then to adopt them? This may accomplish an important task: transferring information between the different kinds of processes and representations that influence our behavior. Human decision making does not rely on a single process; it is influenced by reason, habit, instinct, norms, and so on. Several of these influences are not organized according to rational choice (i.e., computing and maximizing expected value). Rationalization extracts implicit information - true beliefs and useful desires - from the influence of these non-rational systems on behavior. This is a useful fiction - fiction, because it imputes reason to non-rational psychological processes; useful, because it can improve subsequent reasoning. More generally, rationalization belongs to the broader class of representational exchange mechanisms, which transfer information between many different kinds of psychological representations that guide our behavior. Representational exchange enables us to represent any information in the manner best suited to the particular tasks that require it, balancing accuracy, efficiency, and flexibility in thought. The theory of representational exchange reveals connections between rationalization and theory of mind, inverse reinforcement learning, thought experiments, and reflective equilibrium.
Topics: Achievement; Choice Behavior; Cognition; Decision Making; Humans; Rationalization
PubMed: 31133084
DOI: 10.1017/S0140525X19001730 -
Neuron May 2022Logistic regressions were developed in economics to model individual choice behavior. In recent years, they have become an important tool in decision neuroscience. Here,... (Review)
Review
Logistic regressions were developed in economics to model individual choice behavior. In recent years, they have become an important tool in decision neuroscience. Here, I describe and discuss different logistic models, emphasizing the underlying assumptions and possible interpretations. Logistic models may be used to quantify a variety of behavioral traits, including the relative subjective value of different goods, the choice accuracy, risk attitudes, and choice biases. More complex logistic models can be used for choices between good bundles, in cases of nonlinear value functions, and for choices between multiple options. Finally, logistic models can quantify the explanatory power of neuronal activity on choices, thus providing a valid alternative to receiver operating characteristic (ROC) analyses.
Topics: Choice Behavior; Decision Making; Neurons; Neurosciences
PubMed: 35334232
DOI: 10.1016/j.neuron.2022.03.002 -
Annual Review of Neuroscience Jul 2018In everyday life, the outcomes of our actions are rarely certain. Further, we often lack the information needed to precisely estimate the probability and value of... (Review)
Review
In everyday life, the outcomes of our actions are rarely certain. Further, we often lack the information needed to precisely estimate the probability and value of potential outcomes as well as how much effort will be required by the courses of action under consideration. Under such conditions of uncertainty, individual differences in the estimation and weighting of these variables, and in reliance on model-free versus model-based decision making, have the potential to strongly influence our behavior. Both anxiety and depression are associated with difficulties in decision making. Further, anxiety is linked to increased engagement in threat-avoidance behaviors and depression is linked to reduced engagement in reward-seeking behaviors. The precise deficits, or biases, in decision making associated with these common forms of psychopathology remain to be fully specified. In this article, we review evidence for which of the computations supporting decision making are altered in anxiety and depression and consider the potential consequences for action selection. In addition, we provide a schematic framework that integrates the findings reviewed and will hopefully be of value to future studies.
Topics: Animals; Anxiety; Computer Simulation; Decision Making; Depression; Humans; Reward
PubMed: 29709209
DOI: 10.1146/annurev-neuro-080317-062007 -
Neuroscience and Biobehavioral Reviews May 2022
Topics: Cognition; Decision Making; Humans; Inhibition, Psychological; Motivation
PubMed: 35248675
DOI: 10.1016/j.neubiorev.2022.104600 -
The American Journal of Emergency... Jul 2024Emergency physicians (EPs) navigate high-pressure environments, making rapid decisions amidst ambiguity. Their choices are informed by a complex interplay of experience,... (Review)
Review
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. Using tactics such as selective data dissemination, framing, and financial incentives, these actors can exploit pre-existing cognitive biases like anchoring, confirmation, and availability. This creates fertile ground for reflexive control, where EPs may believe they are acting independently while unknowingly serving the goals of external influencers. The consequences of manipulated decision making can be severe: misdiagnoses, inappropriate treatments, and increased healthcare costs. Ethical dilemmas arise when external pressures conflict with patient well-being. Recognizing these dangers empowers EPs to resist reflexive control through (1) critical thinking: examining information for potential biases and prioritizing evidence-based practices, (2) continuous education: learning about cognitive biases and mitigation strategies, and (3) institutional policies: implementing regulations to reduce external influence and to promote transparency. This vulnerability of emergency medicine decision making highlights the need for awareness, education, and robust ethical frameworks. Understanding reflexive control techniques is crucial for safeguarding patient care and promoting independent, ethical decision making in emergency medicine.
Topics: Humans; Emergency Medicine; Clinical Decision-Making; Decision Making
PubMed: 38677197
DOI: 10.1016/j.ajem.2024.04.037 -
BMJ (Clinical Research Ed.) Apr 2022Prognostication is crucial in the neurological intensive care unit (neuroICU). Patients with severe acute brain injury (SABI) are unable to make their own decisions... (Review)
Review
Prognostication is crucial in the neurological intensive care unit (neuroICU). Patients with severe acute brain injury (SABI) are unable to make their own decisions because of the insult itself or sedation needs. Surrogate decision makers, usually family members, must make decisions on the patient's behalf. However, many are unprepared for their role as surrogates owing to the sudden and unexpected nature of SABI. Surrogates rely on clinicians in the neuroICU to provide them with an outlook (prognosis) with which to make substituted judgments and decide on treatments and goals of care on behalf of the patient. Therefore, how a prognostic estimate is derived, and then communicated, is extremely important. Prognostication in the neuroICU is highly variable between clinicians and institutions, and evidence based guidelines are lacking. Shared decision making (SDM), where surrogates and clinicians arrive together at an individualized decision based on patient values and preferences, has been proposed as an opportunity to improve clinician-family communication and ensure that patients receive treatments they would choose. This review outlines the importance and current challenges of prognostication in the neuroICU and how prognostication and SDM intersect, based on relevant research and expert opinion.
Topics: Communication; Decision Making; Decision Making, Shared; Humans; Intensive Care Units; Professional-Family Relations
PubMed: 35696329
DOI: 10.1136/bmj-2021-060154 -
Patient Education and Counseling Jan 2023
Topics: Humans; Decision Making, Shared; Patient Participation; Decision Making
PubMed: 36333194
DOI: 10.1016/j.pec.2022.10.352 -
Biological Psychology Jan 2023This study investigates whether decision-making under uncertainty is influenced by the cardiac cycle. To test this hypothesis, we examined the influence of the cardiac...
This study investigates whether decision-making under uncertainty is influenced by the cardiac cycle. To test this hypothesis, we examined the influence of the cardiac cycle on an individual's decision-making process in a gambling experiment. Participants were asked to choose one option with a sure payout or uncertain option with varying degrees of winning probability, ambiguity, and monetary amounts. The onset of presentation of the options is timed to coincide with either cardiac ventricular systole or diastole. The results show that, for most participants, the risk aversion score was lower in the systole trial than in the diastole trial. Model-based exploratory analysis revealed that the higher propensity to take risks in the systole trial compared with that in the diastole trial could be captured better by the change in the gambling bias against the utility of the risky options, rather than by a change in risk attitude. The results provide evidence that the natural fluctuation of cardiac afferent signals can affect risky decision-making.
Topics: Humans; Decision Making; Gambling; Risk-Taking; Uncertainty; Systole; Diastole
PubMed: 36464201
DOI: 10.1016/j.biopsycho.2022.108471 -
Therapeutische Umschau. Revue... 2022Shared Decision-Making in Preventive Activities Shared Decision-Making (SDM) is particularly useful in conditions where decisions are preference-sensitive, i.e., where... (Review)
Review
Shared Decision-Making in Preventive Activities Shared Decision-Making (SDM) is particularly useful in conditions where decisions are preference-sensitive, i.e., where preferences and values of patients are crucial for the further proceeding. This typically applies to conditions where the potential benefit and the potential harm are similar. Preventive activities are characterized by the fact that there is no current burden of disease and the benefit to expect is far in the future. Therefore, it is preference-sensitive if the current effort really pays off. The procedure of SDM in (preventive) counselling can be classified into three steps: , and . For every step, we present examples of how to talk. After an overview of the current evidence, we present four examples of how to apply SDM in preventive conditions: quit-smoking counselling, lifestyle coaching, vaccination counselling and screening for cancer. Finally, we focus on the role of activated patients and point out the opportunity for SDM during . For all these implementation issues useful tools and links are presented. In summary, important elements of SDM, such as patient centeredness, clarifying needs/goals and shared responsibility, are crucial for the entire spectre of caring for patients, not only for prevention.
Topics: Decision Making; Decision Making, Shared; Humans; Patient Participation
PubMed: 36164734
DOI: 10.1024/0040-5930/a001378 -
Expert Review of Pharmacoeconomics &... 2023
Topics: Humans; Uncertainty; Decision Making
PubMed: 37539711
DOI: 10.1080/14737167.2023.2245138