Advancing shared decision making for symptom monitoring in people living beyond cancer.
Heathcote Lauren C,Goldberg Daniel S,Eccleston Christopher,Spunt Sheri L,Simons Laura E,Sharpe Louise,Earp Brian D
The Lancet. Oncology
Wellbeing after successful cancer treatment depends on more than merely reducing the risk of disease recurrence. Cancer survival can be characterised by uncertainty, fear, and the interpretation of bodily sensations as potentially symptomatic of cancer recurrence. This fear can lead to over-vigilance about bodily sensations and precautionary visits to the doctor, both of which can increase the chance of early detection but can also increase anxiety and decrease quality of life. In this Personal View, we consider the medical, psychological, and ethical issues related to the practice of self-directed symptom monitoring after completion of cancer treatment, focusing on the role of doctor-patient communication. We ask how clinicians can account for the plurality of values that patients might have when it comes to deciding on how to manage and respond to experiences of post-cancer symptoms. We advocate a shared decision-making approach that incorporates the assessment of an individual's cancer recurrence risks as well as psychosocial considerations regarding fear of cancer recurrence and mental health. We aim to raise awareness of the potential quality-of-life implications of symptom-monitoring practices, emphasising the need for a balance between physical and psychological health in people living beyond cancer.
Parent psychology and the decision to delay childhood vaccination.
Callaghan Timothy,Motta Matthew,Sylvester Steven,Lunz Trujillo Kristin,Blackburn Christine Crudo
Social science & medicine (1982)
OBJECTIVE:The study of vaccine hesitancy identifies parental decisions to delay childhood vaccinations as an important public health issue, with consequences for immunization rates, the pursuit of nonmedical exemptions in states, and disease outbreaks. While prior work has explored the demographic and social underpinnings of parental decisions to delay childhood vaccinations, little is known about how the psychological dispositions of parents are associated with this choice. We analyze public opinion data to assess the role of psychological factors in reported parental decisions to delay childhood vaccination. RATIONALE:We anticipate that parents with certain psychological characteristics will be more likely to delay childhood vaccination. Specifically, we explore the roles of conspiratorial thinking, dispositions towards needle sensitivity, and moral purity; expecting that parents with high levels of any of these characteristics will be more likely to delay vaccinating their children. METHOD:In an original survey of 4010 American parents weighted to population benchmarks, we asked parents about delay-related vaccination behavior, demographic questions, and several psychological batteries. We then developed a vaccination delay scale and modeled delay as a function of conspiratorial thinking, needle sensitivity, moral purity, and relevant demographic controls. We then re-specified our models to look specifically at the predictors of delaying HPV vaccination, which has a low uptake rate in the United States. RESULTS:Controlling for other common predictors of hesitant behavior, we find that parents with high levels of conspiratorial thinking and needle sensitivity are more likely to report pursuing alternative vaccination schedules. When analyzing the specific decision by parents to delay HPV vaccination, we find that tendencies towards moral purity and, in turn, sexual deviance are also associated with vaccine seeking behavior. CONCLUSION:Parental decisions to delay childhood vaccinations are an important public health concern that are associated with conspiratorial thinking and needle sensitivity.
Supported Decision-Making: Implications from Positive Psychology for Assessment and Intervention in Rehabilitation and Employment.
Uyanik Hatice,Shogren Karrie A,Blanck Peter
Journal of occupational rehabilitation
Purpose This article reviews existing literature on positive psychology, supported decision-making (SDM), employment, and disability. It examines interventions and assessments that have been empirically evaluated for the enhancement of decision-making and overall well-being of people with disabilities. Additionally, conceptual themes present in the literature were explored. Methods A systematic review was conducted across two databases (ERIC and PsychINFO) using various combination of keywords of 'disabilit*', work rehabilitation and employment terms, positive psychology terms, and SDM components. Seven database searches were conducted with diverse combinations of keywords, which identified 1425 results in total to be screened for relevance using their titles and abstracts. Database search was supplemented with hand searches of oft-cited journals, ancestral search, and supplemental search from grey literature. Results Only four studies were identified in the literature targeting SDM and positive psychology related constructs in the employment and job development context. Results across the studies indicated small to moderate impacts of the assessment and interventions on decision-making and engagement outcomes. Conceptually there are thematic areas of potential overlap, although they are limited in the explicit integration of theory in supported decision-making, positive psychology, disability, and employment. Conclusion Results suggest a need for additional scholarship in this area that focuses on theory development and integration as well as empirical work. Such work should examine the potential utility of considering positive psychological interventions when planning for SDM in the context of career development activities to enhance positive outcomes related to decision-making, self-determination, and other positive psychological constructs.
Toward a synthesis of cognitive biases: how noisy information processing can bias human decision making.
A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelated cognitive decision-making biases. During the past 6 decades, hundreds of empirical studies have resulted in a variety of rules of thumb that specify how humans systematically deviate from what is normatively expected from their decisions. Several complementary generative mechanisms have been proposed to explain those cognitive biases. Here it is suggested that (at least) 8 of these empirically detected decision-making biases can be produced by simply assuming noisy deviations in the memory-based information processes that convert objective evidence (observations) into subjective estimates (decisions). An integrative framework is presented to show how similar noise-based mechanisms can lead to conservatism, the Bayesian likelihood bias, illusory correlations, biased self-other placement, subadditivity, exaggerated expectation, the confidence bias, and the hard-easy effect. Analytical tools from information theory are used to explore the nature and limitations that characterize such information processes for binary and multiary decision-making exercises. The ensuing synthesis offers formal mathematical definitions of the biases and their underlying generative mechanism, which permits a consolidated analysis of how they are related. This synthesis contributes to the larger goal of creating a coherent picture that explains the relations among the myriad of seemingly unrelated biases and their potential psychological generative mechanisms. Limitations and research questions are discussed.
Biased sequential sampling underlies the effects of time pressure and delay in social decision making.
Chen Fadong,Krajbich Ian
Social decision making involves balancing conflicts between selfishness and pro-sociality. The cognitive processes underlying such decisions are not well understood, with some arguing for a single comparison process, while others argue for dual processes (one intuitive and one deliberative). Here, we propose a way to reconcile these two opposing frameworks. We argue that behavior attributed to intuition can instead be seen as a starting point bias of a sequential sampling model (SSM) process, analogous to a prior in a Bayesian framework. Using mini-dictator games in which subjects make binary decisions about how to allocate money between themselves and another participant, we find that pro-social subjects become more pro-social under time pressure and less pro-social under time delay, while selfish subjects do the opposite. Our findings help reconcile the conflicting results concerning the cognitive processes of social decision making and highlight the importance of modeling the dynamics of the choice process.
Memory and decision making interact to shape the value of unchosen options.
Biderman Natalie,Shohamy Daphna
The goal of deliberation is to separate between options so that we can commit to one and leave the other behind. However, deliberation can, paradoxically, also form an association in memory between the chosen and unchosen options. Here, we consider this possibility and examine its consequences for how outcomes affect not only the value of the options we chose, but also, by association, the value of options we did not choose. In five experiments (total n = 612), including a preregistered experiment (n = 235), we found that the value assigned to unchosen options is inversely related to their chosen counterparts. Moreover, this inverse relationship was associated with participants' memory of the pairs they chose between. Our findings suggest that deciding between options does not end the competition between them. Deliberation binds choice options together in memory such that the learned value of one can affect the inferred value of the other.
Early childhood investment impacts social decision-making four decades later.
Luo Yi,Hétu Sébastien,Lohrenz Terry,Hula Andreas,Dayan Peter,Ramey Sharon Landesman,Sonnier-Netto Libbie,Lisinski Jonathan,LaConte Stephen,Nolte Tobias,Fonagy Peter,Rahmani Elham,Montague P Read,Ramey Craig
Early childhood educational investment produces positive effects on cognitive and non-cognitive skills, health, and socio-economic success. However, the effects of such interventions on social decision-making later in life are unknown. We recalled participants from one of the oldest randomized controlled studies of early childhood investment-the Abecedarian Project (ABC)-to participate in well-validated interactive economic games that probe social norm enforcement and planning. We show that in a repeated-play ultimatum game, ABC participants who received high-quality early interventions strongly reject unequal division of money across players (disadvantageous or advantageous) even at significant cost to themselves. Using a multi-round trust game and computational modeling of social exchange, we show that the same intervention participants also plan further into the future. These findings suggest that high quality early childhood investment can result in long-term changes in social decision-making and promote social norm enforcement in order to reap future benefits.
Current Status and Future Prospects of Clinical Psychology: Toward a Scientifically Principled Approach to Mental and Behavioral Health Care.
Baker Timothy B,McFall Richard M,Shoham Varda
Psychological science in the public interest : a journal of the American Psychological Society
The escalating costs of health care and other recent trends have made health care decisions of great societal import, with decision-making responsibility often being transferred from practitioners to health economists, health plans, and insurers. Health care decision making increasingly is guided by evidence that a treatment is efficacious, effective-disseminable, cost-effective, and scientifically plausible. Under these conditions of heightened cost concerns and institutional-economic decision making, psychologists are losing the opportunity to play a leadership role in mental and behavioral health care: Other types of practitioners are providing an increasing proportion of delivered treatment, and the use of psychiatric medication has increased dramatically relative to the provision of psychological interventions. Research has shown that numerous psychological interventions are efficacious, effective, and cost-effective. However, these interventions are used infrequently with patients who would benefit from them, in part because clinical psychologists have not made a convincing case for the use of these interventions (e.g., by supplying the data that decision makers need to support implementation of such interventions) and because clinical psychologists do not themselves use these interventions even when given the opportunity to do so. Clinical psychologists' failure to achieve a more significant impact on clinical and public health may be traced to their deep ambivalence about the role of science and their lack of adequate science training, which leads them to value personal clinical experience over research evidence, use assessment practices that have dubious psychometric support, and not use the interventions for which there is the strongest evidence of efficacy. Clinical psychology resembles medicine at a point in its history when practitioners were operating in a largely prescientific manner. Prior to the scientific reform of medicine in the early 1900s, physicians typically shared the attitudes of many of today's clinical psychologists, such as valuing personal experience over scientific research. Medicine was reformed, in large part, by a principled effort by the American Medical Association to increase the science base of medical school education. Substantial evidence shows that many clinical psychology doctoral training programs, especially PsyD and for-profit programs, do not uphold high standards for graduate admission, have high student-faculty ratios, deemphasize science in their training, and produce students who fail to apply or generate scientific knowledge. A promising strategy for improving the quality and clinical and public health impact of clinical psychology is through a new accreditation system that demands high-quality science training as a central feature of doctoral training in clinical psychology. Just as strengthening training standards in medicine markedly enhanced the quality of health care, improved training standards in clinical psychology will enhance health and mental health care. Such a system will (a) allow the public and employers to identify scientifically trained psychologists; (b) stigmatize ascientific training programs and practitioners; (c) produce aspirational effects, thereby enhancing training quality generally; and (d) help accredited programs improve their training in the application and generation of science. These effects should enhance the generation, application, and dissemination of experimentally supported interventions, thereby improving clinical and public health. Experimentally based treatments not only are highly effective but also are cost-effective relative to other interventions; therefore, they could help control spiraling health care costs. The new Psychological Clinical Science Accreditation System (PCSAS) is intended to accredit clinical psychology training programs that offer high-quality science-centered education and training, producing graduates who are successful in generating and applying scientific knowledge. Psychologists, universities, and other stakeholders should vigorously support this new accreditation system as the surest route to a scientifically principled clinical psychology that can powerfully benefit clinical and public health.
Navigating complex decision spaces: Problems and paradigms in sequential choice.
Walsh Matthew M,Anderson John R
To behave adaptively, we must learn from the consequences of our actions. Doing so is difficult when the consequences of an action follow a delay. This introduces the problem of temporal credit assignment. When feedback follows a sequence of decisions, how should the individual assign credit to the intermediate actions that comprise the sequence? Research in reinforcement learning provides 2 general solutions to this problem: model-free reinforcement learning and model-based reinforcement learning. In this review, we examine connections between stimulus-response and cognitive learning theories, habitual and goal-directed control, and model-free and model-based reinforcement learning. We then consider a range of problems related to temporal credit assignment. These include second-order conditioning and secondary reinforcers, latent learning and detour behavior, partially observable Markov decision processes, actions with distributed outcomes, and hierarchical learning. We ask whether humans and animals, when faced with these problems, behave in a manner consistent with reinforcement learning techniques. Throughout, we seek to identify neural substrates of model-free and model-based reinforcement learning. The former class of techniques is understood in terms of the neurotransmitter dopamine and its effects in the basal ganglia. The latter is understood in terms of a distributed network of regions including the prefrontal cortex, medial temporal lobes, cerebellum, and basal ganglia. Not only do reinforcement learning techniques have a natural interpretation in terms of human and animal behavior but they also provide a useful framework for understanding neural reward valuation and action selection.
Sequential Sampling Models in Cognitive Neuroscience: Advantages, Applications, and Extensions.
Forstmann B U,Ratcliff R,Wagenmakers E-J
Annual review of psychology
Sequential sampling models assume that people make speeded decisions by gradually accumulating noisy information until a threshold of evidence is reached. In cognitive science, one such model--the diffusion decision model--is now regularly used to decompose task performance into underlying processes such as the quality of information processing, response caution, and a priori bias. In the cognitive neurosciences, the diffusion decision model has recently been adopted as a quantitative tool to study the neural basis of decision making under time pressure. We present a selective overview of several recent applications and extensions of the diffusion decision model in the cognitive neurosciences.
Beyond Willpower: Strategies for Reducing Failures of Self-Control.
Duckworth Angela L,Milkman Katherine L,Laibson David
Psychological science in the public interest : a journal of the American Psychological Society
Almost everyone struggles to act in their individual and collective best interests, particularly when doing so requires forgoing a more immediately enjoyable alternative. Other than exhorting decision makers to "do the right thing," what can policymakers do to reduce overeating, undersaving, procrastination, and other self-defeating behaviors that feel good now but generate larger delayed costs? In this review, we synthesize contemporary research on approaches to reducing failures of self-control. We distinguish between self-deployed and other-deployed strategies and, in addition, between situational and cognitive intervention targets. Collectively, the evidence from both psychological science and economics recommends psychologically informed policies for reducing failures of self-control.
Meeting the decision-making preferences of patients with breast cancer in oncology consultations: impact on decision-related outcomes.
Brown Richard,Butow Phyllis,Wilson-Genderson Maureen,Bernhard Juerg,Ribi Karin,Juraskova Ilona
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE:To investigate how involvement preferences of patients with breast cancer change during the treatment decision-making process and determine the impact of meeting patients' expectations on decision-making outcomes. PATIENTS AND METHODS:Participants were 683 patients with breast cancer from 62 oncologists in five different countries recruited to an International Breast Cancer Study Group (IBCSG 33-03) project. Questionnaires elicited patients' pre- and postconsultation preferences for involvement in treatment decision making and whether these were met or not. Decision-related outcomes were assessed postconsultation. RESULTS:Before the consultation, most patients preferred shared or patient-directed treatment decision making. After the consultation, 43% of patients' preferences changed, and most shifted toward patient-directed decisions. The actual postconsultation decision was more likely to be made according to postconsultation rather than preconsultation preferences. Compared with patients who were less involved than they had hoped to be, patients who were as involved as they had hoped to be or were even more involved in decision making had significantly better decision-related outcomes. This was true regardless of whether preference change occurred. CONCLUSION:Many patients with early-stage breast cancer have treatment options and approach treatment decisions with a desire for decisional control, which may increase after their consultation. Patients' ultimate involvement preferences were more likely to be consistent with the way the decision was actually made, suggesting that patients need to feel concordance between their preference and the actual decision. Patients who directed decisions, even if more than they hoped for, fared better on all decision-related outcomes. These results emphasize the need for oncologists to endorse and facilitate patient participation in treatment decision making.
Neural computations underlying strategic social decision-making in groups.
Park Seongmin A,Sestito Mariateresa,Boorman Erie D,Dreher Jean-Claude
When making decisions in groups, the outcome of one's decision often depends on the decisions of others, and there is a tradeoff between short-term incentives for an individual and long-term incentives for the groups. Yet, little is known about the neurocomputational mechanisms at play when weighing different utilities during repeated social interactions. Here, using model-based fMRI and Public-good-games, we find that the ventromedial prefrontal cortex encodes immediate expected rewards as individual utility while the lateral frontopolar cortex encodes group utility (i.e., pending rewards of alternative strategies beneficial for the group). When it is required to change one's strategy, these brain regions exhibited changes in functional interactions with brain regions engaged in switching strategies. Moreover, the anterior cingulate cortex and the temporoparietal junction updated beliefs about the decision of others during interactions. Together, our findings provide a neurocomputational account of how the brain dynamically computes effective strategies to make adaptive collective decisions.
Using large-scale experiments and machine learning to discover theories of human decision-making.
Peterson Joshua C,Bourgin David D,Agrawal Mayank,Reichman Daniel,Griffiths Thomas L
Science (New York, N.Y.)
Predicting and understanding how people make decisions has been a long-standing goal in many fields, with quantitative models of human decision-making informing research in both the social sciences and engineering. We show how progress toward this goal can be accelerated by using large datasets to power machine-learning algorithms that are constrained to produce interpretable psychological theories. Conducting the largest experiment on risky choice to date and analyzing the results using gradient-based optimization of differentiable decision theories implemented through artificial neural networks, we were able to recapitulate historical discoveries, establish that there is room to improve on existing theories, and discover a new, more accurate model of human decision-making in a form that preserves the insights from centuries of research.
Unconscious influences on decision making: a critical review.
Newell Ben R,Shanks David R
The Behavioral and brain sciences
To what extent do we know our own minds when making decisions? Variants of this question have preoccupied researchers in a wide range of domains, from mainstream experimental psychology (cognition, perception, social behavior) to cognitive neuroscience and behavioral economics. A pervasive view places a heavy explanatory burden on an intelligent cognitive unconscious, with many theories assigning causally effective roles to unconscious influences. This article presents a novel framework for evaluating these claims and reviews evidence from three major bodies of research in which unconscious factors have been studied: multiple-cue judgment, deliberation without attention, and decisions under uncertainty. Studies of priming (subliminal and primes-to-behavior) and the role of awareness in movement and perception (e.g., timing of willed actions, blindsight) are also given brief consideration. The review highlights that inadequate procedures for assessing awareness, failures to consider artifactual explanations of "landmark" results, and a tendency to uncritically accept conclusions that fit with our intuitions have all contributed to unconscious influences being ascribed inflated and erroneous explanatory power in theories of decision making. The review concludes by recommending that future research should focus on tasks in which participants' attention is diverted away from the experimenter's hypothesis, rather than the highly reflective tasks that are currently often employed.
The evolutionary roots of human decision making.
Santos Laurie R,Rosati Alexandra G
Annual review of psychology
Humans exhibit a suite of biases when making economic decisions. We review recent research on the origins of human decision making by examining whether similar choice biases are seen in nonhuman primates, our closest phylogenetic relatives. We propose that comparative studies can provide insight into four major questions about the nature of human choice biases that cannot be addressed by studies of our species alone. First, research with other primates can address the evolution of human choice biases and identify shared versus human-unique tendencies in decision making. Second, primate studies can constrain hypotheses about the psychological mechanisms underlying such biases. Third, comparisons of closely related species can identify when distinct mechanisms underlie related biases by examining evolutionary dissociations in choice strategies. Finally, comparative work can provide insight into the biological rationality of economically irrational preferences.
Large-scale dynamics of perceptual decision information across human cortex.
Wilming Niklas,Murphy Peter R,Meyniel Florent,Donner Tobias H
Perceptual decisions entail the accumulation of sensory evidence for a particular choice towards an action plan. An influential framework holds that sensory cortical areas encode the instantaneous sensory evidence and downstream, action-related regions accumulate this evidence. The large-scale distribution of this computation across the cerebral cortex has remained largely elusive. Here, we develop a regionally-specific magnetoencephalography decoding approach to exhaustively map the dynamics of stimulus- and choice-specific signals across the human cortical surface during a visual decision. Comparison with the evidence accumulation dynamics inferred from behavior disentangles stimulus-dependent and endogenous components of choice-predictive activity across the visual cortical hierarchy. We find such an endogenous component in early visual cortex (including V1), which is expressed in a low (<20 Hz) frequency band and tracks, with delay, the build-up of choice-predictive activity in (pre-) motor regions. Our results are consistent with choice- and frequency-specific cortical feedback signaling during decision formation.
Patient and physician decision styles and breast cancer chemotherapy use in older women: Cancer and Leukemia Group B protocol 369901.
Mandelblatt Jeanne S,Faul Leigh Anne,Luta George,Makgoeng Solomon B,Isaacs Claudine,Taylor Kathryn,Sheppard Vanessa B,Tallarico Michelle,Barry William T,Cohen Harvey J
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE Physician and patient decision styles may influence breast cancer care for patients ≥ 65 years ("older") because there is uncertainty about chemotherapy benefits in this group. We evaluate associations between decision-making styles and actual treatment. METHODS Data were collected from women treated outside of clinical trials for newly diagnosed stage I to III breast cancer (83% response) from January 2004 through April 2011 in 75 cooperative group sites. Physicians completed a one-time mailed survey (91% response), and clinical data were abstracted from charts. Patient decision style was measured on a five-point scale. Oncologists' preference for prescribing chemotherapy was based on standardized vignettes. Regression and multiple imputation were used to assess associations between chemotherapy and other variables. Results There were 1,174 women seen by 212 oncologists; 43% of women received chemotherapy. One-third of women preferred to make their own treatment decision. Patient and physician decision styles were independently associated with chemotherapy. Women who preferred less physician input had lower odds of chemotherapy than women who preferred more input (odds ratio [OR] = 0.79 per 1-point change; 95% CI, 0.65 to 0.97; P = .02) after considering covariates. Patients whose oncologists had a high chemotherapy preference had higher odds of receiving chemotherapy (OR = 2.65; 95% CI, 1.80 to 3.89; P < .001) than those who saw oncologists with a low preference. CONCLUSION Physicians' and older patients' decision styles are each associated with breast cancer chemotherapy use. It will be important to re-evaluate the impact of decision styles when there is greater empirical evidence about the benefits and risks of chemotherapy in older patients.
A brain network supporting social influences in human decision-making.
Humans learn from their own trial-and-error experience and observing others. However, it remains unknown how brain circuits compute expected values when direct learning and social learning coexist in uncertain environments. Using a multiplayer reward learning paradigm with 185 participants (39 being scanned) in real time, we observed that individuals succumbed to the group when confronted with dissenting information but observing confirming information increased their confidence. Leveraging computational modeling and functional magnetic resonance imaging, we tracked direct valuation through experience and vicarious valuation through observation and their dissociable, but interacting neural representations in the ventromedial prefrontal cortex and the anterior cingulate cortex, respectively. Their functional coupling with the right temporoparietal junction representing instantaneous social information instantiated a hitherto uncharacterized social prediction error, rather than a reward prediction error, in the putamen. These findings suggest that an integrated network involving the brain's reward hub and social hub supports social influence in human decision-making.
Learning, Reward, and Decision Making.
O'Doherty John P,Cockburn Jeffrey,Pauli Wolfgang M
Annual review of psychology
In this review, we summarize findings supporting the existence of multiple behavioral strategies for controlling reward-related behavior, including a dichotomy between the goal-directed or model-based system and the habitual or model-free system in the domain of instrumental conditioning and a similar dichotomy in the realm of Pavlovian conditioning. We evaluate evidence from neuroscience supporting the existence of at least partly distinct neuronal substrates contributing to the key computations necessary for the function of these different control systems. We consider the nature of the interactions between these systems and show how these interactions can lead to either adaptive or maladaptive behavioral outcomes. We then review evidence that an additional system guides inference concerning the hidden states of other agents, such as their beliefs, preferences, and intentions, in a social context. We also describe emerging evidence for an arbitration mechanism between model-based and model-free reinforcement learning, placing such a mechanism within the broader context of the hierarchical control of behavior.
How did that individual make that perceptual decision?
Booth David A
The Behavioral and brain sciences
Suboptimality of decision making needs no explanation. High-level accounts of suboptimality in diverse tasks cannot add up to a mechanistic theory of perceptual decision making. Mental processes operate on the contents of information brought by the experimenter and the participant to the task, not on the amount of information in the stimuli without regard to physical and social context.
Computational Mechanisms of Effort and Reward Decisions in Patients With Depression and Their Association With Relapse After Antidepressant Discontinuation.
Berwian Isabel M,Wenzel Julia G,Collins Anne G E,Seifritz Erich,Stephan Klaas E,Walter Henrik,Huys Quentin J M
Importance:Nearly 1 in 3 patients with major depressive disorder who respond to antidepressants relapse within 6 months of treatment discontinuation. No predictors of relapse exist to guide clinical decision-making in this scenario. Objectives:To establish whether the decision to invest effort for rewards represents a persistent depression process after remission, predicts relapse after remission, and is affected by antidepressant discontinuation. Design, Setting, and Participants:This longitudinal randomized observational prognostic study in a Swiss and German university setting collected data from July 1, 2015, to January 31, 2019, from 66 healthy controls and 123 patients in remission from major depressive disorder in response to antidepressants prior to and after discontinuation. Study recruitment took place until January 2018. Exposure:Discontinuation of antidepressants. Main Outcomes and Measures:Relapse during the 6 months after discontinuation. Choice and decision times on a task requiring participants to choose how much effort to exert for various amounts of reward and the mechanisms identified through parameters of a computational model. Results:A total of 123 patients (mean [SD] age, 34.5 [11.2] years; 94 women [76%]) and 66 healthy controls (mean [SD] age, 34.6 [11.0] years; 49 women [74%]) were recruited. In the main subsample, mean (SD) decision times were slower for patients (n = 74) compared with controls (n = 34) (1.77 [0.38] seconds vs 1.61 [0.37] seconds; Cohen d = 0.52; P = .02), particularly for those who later relapsed after discontinuation of antidepressants (n = 21) compared with those who did not relapse (n = 39) (1.95 [0.40] seconds vs 1.67 [0.34] seconds; Cohen d = 0.77; P < .001). This slower decision time predicted relapse (accuracy = 0.66; P = .007). Patients invested less effort than healthy controls for rewards (F1,98 = 33.970; P < .001). Computational modeling identified a mean (SD) deviation from standard drift-diffusion models that was more prominent for patients than controls (patients, 0.67 [1.56]; controls, -0.71 [1.93]; Cohen d = 0.82; P < .001). Patients also showed higher mean (SD) effort sensitivity than controls (patients, 0.31 [0.92]; controls, -0.08 [1.03]; Cohen d = 0.51; P = .05). Relapsers differed from nonrelapsers in terms of the evidence required to make a decision for the low-effort choice (mean [SD]: relapsers, 1.36 [0.35]; nonrelapsers, 1.17 [0.26]; Cohen d = 0.65; P = .02). Group differences generally did not reach significance in the smaller replication sample (27 patients and 21 controls), but decision time prediction models from the main sample generalized to the replication sample (validation accuracy = 0.71; P = .03). Conclusions and Relevance:This study found that the decision to invest effort was associated with prospective relapse risk after antidepressant discontinuation and may represent a persistent disease process in asymptomatic remitted major depressive disorder. Markers based on effort-related decision-making could potentially inform clinical decisions associated with antidepressant discontinuation.
Social Decision-Making and the Brain: A Comparative Perspective.
Tremblay Sébastien,Sharika K M,Platt Michael L
Trends in cognitive sciences
The capacity and motivation to be social is a key component of the human adaptive behavioral repertoire. Recent research has identified social behaviors remarkably similar to our own in other animals, including empathy, consolation, cooperation, and strategic deception. Moreover, neurobiological studies in humans, nonhuman primates, and rodents have identified shared brain structures (the so-called 'social brain') apparently specialized to mediate such functions. Neuromodulators may regulate social interactions by 'tuning' the social brain, with important implications for treating social impairments. Here, we survey recent findings in social neuroscience from a comparative perspective, and conclude that the very social behaviors that make us human emerge from mechanisms shared widely with other animals, as well as some that appear to be unique to humans and other primates.
Frontopolar theta oscillations link metacognition with prospective decision making.
Soutschek Alexander,Moisa Marius,Ruff Christian C,Tobler Philippe N
Prospective decision making considers the future consequences of actions and therefore requires agents to represent their present subjective preferences reliably across time. Here, we test the link of frontopolar theta oscillations to both metacognitive ability and prospective choice behavior. We target these oscillations with transcranial alternating current stimulation while participants make decisions between smaller-sooner and larger-later monetary rewards and rate their choice confidence after each decision. Stimulation designed to enhance frontopolar theta oscillations increases metacognitive accuracy in reports of subjective uncertainty in intertemporal decisions. Moreover, the stimulation also enhances the willingness of participants to restrict their future access to short-term gratification by strengthening the awareness of potential preference reversals. Our results suggest a mechanistic link between frontopolar theta oscillations and metacognitive knowledge about the stability of subjective value representations, providing a potential explanation for why frontopolar cortex also shields prospective decision making against future temptation.
The Psychology of Reaching: Action Selection, Movement Implementation, and Sensorimotor Learning.
Kim Hyosub E,Avraham Guy,Ivry Richard B
Annual review of psychology
The study of motor planning and learning in humans has undergone a dramatic transformation in the 20 years since this journal's last review of this topic. The behavioral analysis of movement, the foundational approach for psychology, has been complemented by ideas from control theory, computer science, statistics, and, most notably, neuroscience. The result of this interdisciplinary approach has been a focus on the computational level of analysis, leading to the development of mechanistic models at the psychological level to explain how humans plan, execute, and consolidate skilled reaching movements. This review emphasizes new perspectives on action selection and motor planning, research that stands in contrast to the previously dominant representation-based perspective of motor programming, as well as an emerging literature highlighting the convergent operation of multiple processes in sensorimotor learning.
Identification and disruption of a neural mechanism for accumulating prospective metacognitive information prior to decision-making.
Miyamoto Kentaro,Trudel Nadescha,Kamermans Kevin,Lim Michele C,Lazari Alberto,Verhagen Lennart,Wittmann Marco K,Rushworth Matthew F S
More than one type of probability must be considered when making decisions. It is as necessary to know one's chance of performing choices correctly as it is to know the chances that desired outcomes will follow choices. We refer to these two choice contingencies as internal and external probability. Neural activity across many frontal and parietal areas reflected internal and external probabilities in a similar manner during decision-making. However, neural recording and manipulation approaches suggest that one area, the anterior lateral prefrontal cortex (alPFC), is highly specialized for making prospective, metacognitive judgments on the basis of internal probability; it is essential for knowing which decisions to tackle, given its assessment of how well they will be performed. Its activity predicted prospective metacognitive judgments, and individual variation in activity predicted individual variation in metacognitive judgments. Its disruption altered metacognitive judgments, leading participants to tackle perceptual decisions they were likely to fail.
Switching Tracks? Towards a Multidimensional Model of Utilitarian Psychology.
Everett Jim A C,Kahane Guy
Trends in cognitive sciences
Sacrificial moral dilemmas are widely used to investigate when, how, and why people make judgments that are consistent with utilitarianism. However, to what extent can responses to sacrificial dilemmas shed light on utilitarian decision making? We consider two key questions. First, how meaningful is the relationship between responses to sacrificial dilemmas, and what is distinctive about a utilitarian approach to morality? Second, to what extent do findings about sacrificial dilemmas generalize to other moral contexts where there is tension between utilitarianism and common-sense intuitions? We argue that sacrificial dilemmas only capture one point of conflict between utilitarianism and common-sense morality, and new paradigms will be necessary to investigate other key aspects of utilitarianism, such as its radical impartiality.
Functional versus chronological age: geriatric assessments to guide decision making in older patients with cancer.
Soto-Perez-de-Celis Enrique,Li Daneng,Yuan Yuan,Lau Yat Ming,Hurria Arti
The Lancet. Oncology
As the worldwide population ages, oncologists are often required to make difficult and complex decisions regarding the treatment of older people (aged 65 years and older) with cancer. Chronological age alone is often a poor indicator of the physiological and functional status of older adults, and thus should not be the main factor guiding treatment decisions in oncology. By contrast, a geriatric assessment can provide a much more comprehensive understanding of the functional and physiological age of an older person with cancer. The geriatric assessment is a multidimensional tool that evaluates several domains, including physical function, cognition, nutrition, comorbidities, psychological status, and social support. In this Series paper, we discuss the use of a geriatric assessment-based approach to cancer care, and provide clinicians with tools to better assess the risks and benefits of treatment to engage in shared decision making and provide better personalised care for older people with cancer.
Dissociated functional significance of decision-related activity in the primate dorsal stream.
Katz Leor N,Yates Jacob L,Pillow Jonathan W,Huk Alexander C
During decision making, neurons in multiple brain regions exhibit responses that are correlated with decisions. However, it remains uncertain whether or not various forms of decision-related activity are causally related to decision making. Here we address this question by recording and reversibly inactivating the lateral intraparietal (LIP) and middle temporal (MT) areas of rhesus macaques performing a motion direction discrimination task. Neurons in area LIP exhibited firing rate patterns that directly resembled the evidence accumulation process posited to govern decision making, with strong correlations between their response fluctuations and the animal's choices. Neurons in area MT, in contrast, exhibited weak correlations between their response fluctuations and choices, and had firing rate patterns consistent with their sensory role in motion encoding. The behavioural impact of pharmacological inactivation of each area was inversely related to their degree of decision-related activity: while inactivation of neurons in MT profoundly impaired psychophysical performance, inactivation in LIP had no measurable impact on decision-making performance, despite having silenced the very clusters that exhibited strong decision-related activity. Although LIP inactivation did not impair psychophysical behaviour, it did influence spatial selection and oculomotor metrics in a free-choice control task. The absence of an effect on perceptual decision making was stable over trials and sessions and was robust to changes in stimulus type and task geometry, arguing against several forms of compensation. Thus, decision-related signals in LIP do not appear to be critical for computing perceptual decisions, and may instead reflect secondary processes. Our findings highlight a dissociation between decision correlation and causation, showing that strong neuron-decision correlations do not necessarily offer direct access to the neural computations underlying decisions.
Affect and Decision Making: Insights and Predictions from Computational Models.
Roberts Ian D,Hutcherson Cendri A
Trends in cognitive sciences
In recent years interest in integrating the affective and decision sciences has skyrocketed. Immense progress has been made, but the complexities of each field, which can multiply when combined, present a significant obstacle. A carefully defined framework for integration is needed. The shift towards computational modeling in decision science provides a powerful basis and a path forward, but one whose synergistic potential will only be fully realized by drawing on the theoretical richness of the affective sciences. Reviewing research using a popular computational model of choice (the drift diffusion model), we discuss how mapping concepts to parameters reduces conceptual ambiguity and reveals novel hypotheses.
Modeling other minds: Bayesian inference explains human choices in group decision-making.
Khalvati Koosha,Park Seongmin A,Mirbagheri Saghar,Philippe Remi,Sestito Mariateresa,Dreher Jean-Claude,Rao Rajesh P N
To make decisions in a social context, humans have to predict the behavior of others, an ability that is thought to rely on having a model of other minds known as "theory of mind." Such a model becomes especially complex when the number of people one simultaneously interacts with is large and actions are anonymous. Here, we present results from a group decision-making task known as the volunteer's dilemma and demonstrate that a Bayesian model based on partially observable Markov decision processes outperforms existing models in quantitatively predicting human behavior and outcomes of group interactions. Our results suggest that in decision-making tasks involving large groups with anonymous members, humans use Bayesian inference to model the "mind of the group," making predictions of others' decisions while also simulating the effects of their own actions on the group's dynamics in the future.
The suboptimality of perceptual decision making with multiple alternatives.
Yeon Jiwon,Rahnev Dobromir
It is becoming widely appreciated that human perceptual decision making is suboptimal but the nature and origins of this suboptimality remain poorly understood. Most past research has employed tasks with two stimulus categories, but such designs cannot fully capture the limitations inherent in naturalistic perceptual decisions where choices are rarely between only two alternatives. We conduct four experiments with tasks involving multiple alternatives and use computational modeling to determine the decision-level representation on which the perceptual decisions are based. The results from all four experiments point to the existence of robust suboptimality such that most of the information in the sensory representation is lost during the transformation to a decision-level representation. These results reveal severe limits in the quality of decision-level representations for multiple alternatives and have strong implications about perceptual decision making in naturalistic settings.
Prefrontal-amygdala circuits in social decision-making.
Gangopadhyay Prabaha,Chawla Megha,Dal Monte Olga,Chang Steve W C
An increasing amount of research effort is being directed toward investigating the neural bases of social cognition from a systems neuroscience perspective. Evidence from multiple animal species is beginning to provide a mechanistic understanding of the substrates of social behaviors at multiple levels of neurobiology, ranging from those underlying high-level social constructs in humans and their more rudimentary underpinnings in monkeys to circuit-level and cell-type-specific instantiations of social behaviors in rodents. Here we review literature examining the neural mechanisms of social decision-making in humans, non-human primates and rodents, focusing on the amygdala and the medial and orbital prefrontal cortical regions and their functional interactions. We also discuss how the neuropeptide oxytocin impacts these circuits and their downstream effects on social behaviors. Overall, we conclude that regulated interactions of neuronal activity in the prefrontal-amygdala pathways critically contribute to social decision-making in the brains of primates and rodents.
An Integrated Model of Action Selection: Distinct Modes of Cortical Control of Striatal Decision Making.
Annual review of psychology
Making decisions in environments with few choice options is easy. We select the action that results in the most valued outcome. Making decisions in more complex environments, where the same action can produce different outcomes in different conditions, is much harder. In such circumstances, we propose that accurate action selection relies on top-down control from the prelimbic and orbitofrontal cortices over striatal activity through distinct thalamostriatal circuits. We suggest that the prelimbic cortex exerts direct influence over medium spiny neurons in the dorsomedial striatum to represent the state space relevant to the current environment. Conversely, the orbitofrontal cortex is argued to track a subject's position within that state space, likely through modulation of cholinergic interneurons.
Suboptimality in perceptual decision making.
Rahnev Dobromir,Denison Rachel N
The Behavioral and brain sciences
Human perceptual decisions are often described as optimal. Critics of this view have argued that claims of optimality are overly flexible and lack explanatory power. Meanwhile, advocates for optimality have countered that such criticisms single out a few selected papers. To elucidate the issue of optimality in perceptual decision making, we review the extensive literature on suboptimal performance in perceptual tasks. We discuss eight different classes of suboptimal perceptual decisions, including improper placement, maintenance, and adjustment of perceptual criteria; inadequate tradeoff between speed and accuracy; inappropriate confidence ratings; misweightings in cue combination; and findings related to various perceptual illusions and biases. In addition, we discuss conceptual shortcomings of a focus on optimality, such as definitional difficulties and the limited value of optimality claims in and of themselves. We therefore advocate that the field drop its emphasis on whether observed behavior is optimal and instead concentrate on building and testing detailed observer models that explain behavior across a wide range of tasks. To facilitate this transition, we compile the proposed hypotheses regarding the origins of suboptimal perceptual decisions reviewed here. We argue that verifying, rejecting, and expanding these explanations for suboptimal behavior - rather than assessing optimality per se - should be among the major goals of the science of perceptual decision making.
Decision-making in sensorimotor control.
Gallivan Jason P,Chapman Craig S,Wolpert Daniel M,Flanagan J Randall
Nature reviews. Neuroscience
Skilled sensorimotor interactions with the world result from a series of decision-making processes that determine, on the basis of information extracted during the unfolding sequence of events, which movements to make and when and how to make them. Despite this inherent link between decision-making and sensorimotor control, research into each of these two areas has largely evolved in isolation, and it is only fairly recently that researchers have begun investigating how they interact and, together, influence behaviour. Here, we review recent behavioural, neurophysiological and computational research that highlights the role of decision-making processes in the selection, planning and control of goal-directed movements in humans and nonhuman primates.
Formalizing planning and information search in naturalistic decision-making.
Decisions made by mammals and birds are often temporally extended. They require planning and sampling of decision-relevant information. Our understanding of such decision-making remains in its infancy compared with simpler, forced-choice paradigms. However, recent advances in algorithms supporting planning and information search provide a lens through which we can explain neural and behavioral data in these tasks. We review these advances to obtain a clearer understanding for why planning and curiosity originated in certain species but not others; how activity in the medial temporal lobe, prefrontal and cingulate cortices may support these behaviors; and how planning and information search may complement each other as means to improve future action selection.
Calculated avoidance: Math anxiety predicts math avoidance in effort-based decision-making.
Choe Kyoung Whan,Jenifer Jalisha B,Rozek Christopher S,Berman Marc G,Beilock Sian L
Math anxiety-negative feelings toward math-is hypothesized to be associated with the avoidance of math-related activities such as taking math courses and pursuing STEM careers. However, there is little experimental evidence for the math anxiety-avoidance link. Such evidence is important for formulating how to break this relationship. We hypothesize that math avoidance emerges when one perceives the costs of effortful math engagement to outweigh its benefits and that this perception depends on individual differences in math anxiety. To test this hypothesis, we developed an effort-based decision-making task in which participants chose between solving easy, low-reward problems and hard, high-reward problems in both math and nonmath contexts. Higher levels of math anxiety were associated with a tendency to select easier, low-reward problems over harder, high-reward math (but not word) problems. Addressing this robust math anxiety-avoidance link has the potential to increase interest and success in STEM fields.
Decision making in the ageing brain: changes in affective and motivational circuits.
Samanez-Larkin Gregory R,Knutson Brian
Nature reviews. Neuroscience
As the global population ages, older decision makers will be required to take greater responsibility for their own physical, psychological and financial well-being. With this in mind, researchers have begun to examine the effects of ageing on decision making and associated neural circuits. A new 'affect-integration-motivation' (AIM) framework may help to clarify how affective and motivational circuits support decision making. Recent research has shed light on whether and how ageing influences these circuits, providing an interdisciplinary account of how ageing can alter decision making.
Stable Representations of Decision Variables for Flexible Behavior.
Bari Bilal A,Grossman Cooper D,Lubin Emily E,Rajagopalan Adithya E,Cressy Jianna I,Cohen Jeremiah Y
Decisions occur in dynamic environments. In the framework of reinforcement learning, the probability of performing an action is influenced by decision variables. Discrepancies between predicted and obtained rewards (reward prediction errors) update these variables, but they are otherwise stable between decisions. Although reward prediction errors have been mapped to midbrain dopamine neurons, it is unclear how the brain represents decision variables themselves. We trained mice on a dynamic foraging task in which they chose between alternatives that delivered reward with changing probabilities. Neurons in the medial prefrontal cortex, including projections to the dorsomedial striatum, maintained persistent firing rate changes over long timescales. These changes stably represented relative action values (to bias choices) and total action values (to bias response times) with slow decay. In contrast, decision variables were weakly represented in the anterolateral motor cortex, a region necessary for generating choices. Thus, we define a stable neural mechanism to drive flexible behavior.
Diffusion Decision Model: Current Issues and History.
Ratcliff Roger,Smith Philip L,Brown Scott D,McKoon Gail
Trends in cognitive sciences
There is growing interest in diffusion models to represent the cognitive and neural processes of speeded decision making. Sequential-sampling models like the diffusion model have a long history in psychology. They view decision making as a process of noisy accumulation of evidence from a stimulus. The standard model assumes that evidence accumulates at a constant rate during the second or two it takes to make a decision. This process can be linked to the behaviors of populations of neurons and to theories of optimality. Diffusion models have been used successfully in a range of cognitive tasks and as psychometric tools in clinical research to examine individual differences. In this review, we relate the models to both earlier and more recent research in psychology.
A meta-analysis of blood glucose effects on human decision making.
Orquin Jacob L,Kurzban Robert
The academic and public interest in blood glucose and its relationship to decision making has been increasing over the last decade. To investigate and evaluate competing theories about this relationship, we conducted a psychometric meta-analysis on the effect of blood glucose on decision making. We identified 42 studies relating to 4 dimensions of decision making: willingness to pay, willingness to work, time discounting, and decision style. We did not find a uniform influence of blood glucose on decision making. Instead, we found that low levels of blood glucose increase the willingness to pay and willingness to work when a situation is food related, but decrease willingness to pay and work in all other situations. Low levels of blood glucose increase the future discount rate for food; that is, decision makers become more impatient, and to a lesser extent increase the future discount rate for money. Low levels of blood glucose also increase the tendency to make more intuitive rather than deliberate decisions. However, this effect was only observed in situations unrelated to food. We conclude that blood glucose has domain-specific effects, influencing decision making differently depending on the relevance of the situation to acquiring food. (PsycINFO Database Record
Human stereoEEG recordings reveal network dynamics of decision-making in a rule-switching task.
Ter Wal Marije,Platonov Artem,Cardellicchio Pasquale,Pelliccia Veronica,LoRusso Giorgio,Sartori Ivana,Avanzini Pietro,Orban Guy A,Tiesinga Paul H E
The processing steps that lead up to a decision, i.e., the transformation of sensory evidence into motor output, are not fully understood. Here, we combine stereoEEG recordings from the human cortex, with single-lead and time-resolved decoding, using a wide range of temporal frequencies, to characterize decision processing during a rule-switching task. Our data reveal the contribution of rostral inferior parietal lobule (IPL) regions, in particular PFt, and the parietal opercular regions in decision processing and demonstrate that the network representing the decision is common to both task rules. We reconstruct the sequence in which regions engage in decision processing on single trials, thereby providing a detailed picture of the network dynamics involved in decision-making. The reconstructed timeline suggests that the supramarginal gyrus in IPL links decision regions in prefrontal cortex with premotor regions, where the motor plan for the response is elaborated.
Bridging Neural and Computational Viewpoints on Perceptual Decision-Making.
O'Connell Redmond G,Shadlen Michael N,Wong-Lin KongFatt,Kelly Simon P
Trends in neurosciences
Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these models share the basic principle that decisions are formed by accumulating sensory evidence to a bound, they come in many forms that can make similar predictions of choice behaviour despite invoking fundamentally different mechanisms. The identification of neural signals that reflect some of the core computations underpinning decision formation offers new avenues for empirically testing and refining key model assumptions. Here, we highlight recent efforts to explore these avenues and, in so doing, consider the conceptual and methodological challenges that arise when seeking to infer decision computations from complex neural data.
Auditory information enhances post-sensory visual evidence during rapid multisensory decision-making.
Franzen Léon,Delis Ioannis,De Sousa Gabriela,Kayser Christoph,Philiastides Marios G
Despite recent progress in understanding multisensory decision-making, a conclusive mechanistic account of how the brain translates the relevant evidence into a decision is lacking. Specifically, it remains unclear whether perceptual improvements during rapid multisensory decisions are best explained by sensory (i.e., 'Early') processing benefits or post-sensory (i.e., 'Late') changes in decision dynamics. Here, we employ a well-established visual object categorisation task in which early sensory and post-sensory decision evidence can be dissociated using multivariate pattern analysis of the electroencephalogram (EEG). We capitalize on these distinct neural components to identify when and how complementary auditory information influences the encoding of decision-relevant visual evidence in a multisensory context. We show that it is primarily the post-sensory, rather than the early sensory, EEG component amplitudes that are being amplified during rapid audiovisual decision-making. Using a neurally informed drift diffusion model we demonstrate that a multisensory behavioral improvement in accuracy arises from an enhanced quality of the relevant decision evidence, as captured by the post-sensory EEG component, consistent with the emergence of multisensory evidence in higher-order brain areas.
The elusiveness of context effects in decision making.
Spektor Mikhail S,Bhatia Sudeep,Gluth Sebastian
Trends in cognitive sciences
Contextual features influence human and non-human decision making, giving rise to preference reversals. Decades of research have documented the species and situations in which these effects are observed. More recently, however, researchers have focused on boundary conditions, that is, settings in which established effects disappear or reverse. This work is scattered across academic disciplines and some results appear to contradict each other. We synthesize recent findings and resolve apparent contradictions by considering them in terms of three core categories of decision context: spatial arrangement, attribute concreteness, and deliberation time. We suggest that these categories could be understood using theories of choice representation, which specify how context shapes the information over which deliberation processes operate.
Decision making: the neuroethological turn.
Pearson John M,Watson Karli K,Platt Michael L
Neuroeconomics applies models from economics and psychology to inform neurobiological studies of choice. This approach has revealed neural signatures of concepts like value, risk, and ambiguity, which are known to influence decision making. Such observations have led theorists to hypothesize a single, unified decision process that mediates choice behavior via a common neural currency for outcomes like food, money, or social praise. In parallel, recent neuroethological studies of decision making have focused on natural behaviors like foraging, mate choice, and social interactions. These decisions strongly impact evolutionary fitness and thus are likely to have played a key role in shaping the neural circuits that mediate decision making. This approach has revealed a suite of computational motifs that appear to be shared across a wide variety of organisms. We argue that the existence of deep homologies in the neural circuits mediating choice may have profound implications for understanding human decision making in health and disease.
Effectiveness of the DECIDE Interventions on Shared Decision Making and Perceived Quality of Care in Behavioral Health With Multicultural Patients: A Randomized Clinical Trial.
Alegria Margarita,Nakash Ora,Johnson Kirsten,Ault-Brutus Andrea,Carson Nicholas,Fillbrunn Mirko,Wang Ye,Cheng Alice,Harris Treniece,Polo Antonio,Lincoln Alisa,Freeman Elmer,Bostdorf Benjamin,Rosenbaum Marcos,Epelbaum Claudia,LaRoche Martin,Okpokwasili-Johnson Ebele,Carrasco MaJose,Shrout Patrick E
Importance:Few randomized clinical trials have been conducted with ethnic/racial minorities to improve shared decision making (SDM) and quality of care. Objective:To test the effectiveness of patient and clinician interventions to improve SDM and quality of care among an ethnically/racially diverse sample. Design, Setting, and Participants:This cross-level 2 × 2 randomized clinical trial included clinicians at level 2 and patients (nested within clinicians) at level 1 from 13 Massachusetts behavioral health clinics. Clinicians and patients were randomly selected at each site in a 1:1 ratio for each 2-person block. Clinicians were recruited starting September 1, 2013; patients, starting November 3, 2013. Final data were collected on September 30, 2016. Data were analyzed based on intention to treat. Interventions:The clinician intervention consisted of a workshop and as many as 6 coaching telephone calls to promote communication and therapeutic alliance to improve SDM. The 3-session patient intervention sought to improve SDM and quality of care. Main Outcomes and Measures:The SDM was assessed by a blinded coder based on clinical recordings, patient perception of SDM and quality of care, and clinician perception of SDM. Results:Of 312 randomized patients, 212 (67.9%) were female and 100 (32.1%) were male; mean (SD) age was 44.0 (15.0) years. Of 74 randomized clinicians, 56 (75.7%) were female and 18 (4.3%) were male; mean (SD) age was 39.8 (12.5) years. Patient-clinician pairs were assigned to 1 of the following 4 design arms: patient and clinician in the control condition (n = 72), patient in intervention and clinician in the control condition (n = 68), patient in the control condition and clinician in intervention (n = 83), or patient and clinician in intervention (n = 89). All pairs underwent analysis. The clinician intervention significantly increased SDM as rated by blinded coders using the 12-item Observing Patient Involvement in Shared Decision Making instrument (b = 4.52; SE = 2.17; P = .04; Cohen d = 0.29) but not as assessed by clinician or patient. More clinician coaching sessions (dosage) were significantly associated with increased SDM as rated by blinded coders (b = 12.01; SE = 3.72; P = .001; Cohen d = 0.78). The patient intervention significantly increased patient-perceived quality of care (b = 2.27; SE = 1.16; P = .05; Cohen d = 0.19). There was a significant interaction between patient and clinician dosage (b = 7.40; SE = 3.56; P = .04; Cohen d = 0.62), with the greatest benefit when both obtained the recommended dosage. Conclusions and Relevance:The clinician intervention could improve SDM with minority populations, and the patient intervention could augment patient-reported quality of care. Trial Registration:clinicaltrials.gov Identifier: NCT01947283.
Explaining financial and prosocial biases in favor of attractive people: Interdisciplinary perspectives from economics, social psychology, and evolutionary psychology.
Maestripieri Dario,Henry Andrea,Nickels Nora
The Behavioral and brain sciences
Financial and prosocial biases in favor of attractive adults have been documented in the labor market, in social transactions in everyday life, and in studies involving experimental economic games. According to the taste-based discrimination model developed by economists, attractiveness-related financial and prosocial biases are the result of preferences or prejudices similar to those displayed toward members of a particular sex, racial, ethnic, or religious group. Other explanations proposed by economists and social psychologists maintain that attractiveness is a marker of personality, intelligence, trustworthiness, professional competence, or productivity. Evolutionary psychologists have argued that attractive adults are favored because they are preferred sexual partners. Evidence that stereotypes about attractive people are causally related to financial or prosocial biases toward them is weak or nonexistent. Consistent with evolutionary explanations, biases in favor of attractive women appear to be more consistent or stronger than those in favor of attractive men, and biases are more consistently reported in interactions between opposite-sex than same-sex individuals. Evolutionary explanations also account for increased prosocial behavior in situations in which attractive individuals are simply bystanders. Finally, evolutionary explanations are consistent with the psychological, physiological, and behavioral changes that occur when individuals are exposed to potential mates, which facilitate the expression of courtship behavior and increase the probability of occurrence of mating. Therefore, multiple lines of evidence suggest that mating motives play a more important role in driving financial and prosocial biases toward attractive adults than previously recognized.
Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention.
Children with Attention Deficit Hyperactivity Disorder (ADHD) have prominent deficits in sustained attention that manifest as elevated intra-individual response variability and poor decision-making. Influential neurocognitive models have linked attentional fluctuations to aberrant brain dynamics, but these models have not been tested with computationally rigorous procedures. Here we use a Research Domain Criteria approach, drift-diffusion modeling of behavior, and a novel Bayesian Switching Dynamic System unsupervised learning algorithm, with ultrafast temporal resolution (490 ms) whole-brain task-fMRI data, to investigate latent brain state dynamics of salience, frontoparietal, and default mode networks and their relation to response variability, latent decision-making processes, and inattention. Our analyses revealed that occurrence of a task-optimal latent brain state predicted decreased intra-individual response variability and increased evidence accumulation related to decision-making. In contrast, occurrence and dwell time of a non-optimal latent brain state predicted inattention symptoms and furthermore, in a categorical analysis, distinguished children with ADHD from controls. Importantly, functional connectivity between salience and frontoparietal networks predicted rate of evidence accumulation to a decision threshold, whereas functional connectivity between salience and default mode networks predicted inattention. Taken together, our computational modeling reveals dissociable latent brain state features underlying response variability, impaired decision-making, and inattentional symptoms common to ADHD. Our findings provide novel insights into the neurobiology of attention deficits in children.
Experimental Games and Social Decision Making.
van Dijk Eric,De Dreu Carsten K W
Annual review of psychology
Experimental games model situations in which the future outcomes of individuals and groups depend on their own choices and on those of other (groups of) individuals. Games are a powerful tool to identify the neural and psychological mechanisms underlying interpersonal and group cooperation and coordination. Here we discuss recent developments in how experimental games are used and adapted, with an increased focus on repeated interactions, partner control through sanctioning, and partner (de)selection for future interactions. Important advances have been made in uncovering the neurobiological underpinnings of key factors involved in cooperation and coordination, including social preferences, cooperative beliefs, (emotion) signaling, and, in particular, reputations and (in)direct reciprocity. Emerging trends at the cross-sections of psychology, economics, and the neurosciences include an increased focus on group heterogeneities, intergroup polarization and conflict, cross-cultural differences in cooperation and norm enforcement, and neurocomputational modeling of the formation and updating of social preferences and beliefs.
Extracting the dynamics of behavior in sensory decision-making experiments.
Roy Nicholas A,Bak Ji Hyun, ,Akrami Athena,Brody Carlos D,Pillow Jonathan W
Decision-making strategies evolve during training and can continue to vary even in well-trained animals. However, studies of sensory decision-making tend to characterize behavior in terms of a fixed psychometric function that is fit only after training is complete. Here, we present PsyTrack, a flexible method for inferring the trajectory of sensory decision-making strategies from choice data. We apply PsyTrack to training data from mice, rats, and human subjects learning to perform auditory and visual decision-making tasks. We show that it successfully captures trial-to-trial fluctuations in the weighting of sensory stimuli, bias, and task-irrelevant covariates such as choice and stimulus history. This analysis reveals dramatic differences in learning across mice and rapid adaptation to changes in task statistics. PsyTrack scales easily to large datasets and offers a powerful tool for quantifying time-varying behavior in a wide variety of animals and tasks.
Spontaneous Brain Oscillations and Perceptual Decision-Making.
Samaha Jason,Iemi Luca,Haegens Saskia,Busch Niko A
Trends in cognitive sciences
Making rapid decisions on the basis of sensory information is essential to everyday behaviors. Why, then, are perceptual decisions so variable despite unchanging inputs? Spontaneous neural oscillations have emerged as a key predictor of trial-to-trial perceptual variability. New work casting these effects in the framework of models of perceptual decision-making has driven novel insight into how the amplitude of spontaneous oscillations impact decision-making. This synthesis reveals that the amplitude of ongoing low-frequency oscillations (<30 Hz), particularly in the alpha-band (8-13 Hz), bias sensory responses and change conscious perception but not, surprisingly, the underlying sensitivity of perception. A key model-based insight is that various decision thresholds do not adapt to alpha-related changes in sensory activity, demonstrating a seeming suboptimality of decision mechanisms in tracking endogenous changes in sensory responses.
A cortical circuit mechanism for structural knowledge-based flexible sensorimotor decision-making.
Liu Yanhe,Xin Yu,Xu Ning-Long
Making flexible decisions based on prior knowledge about causal environmental structures is a hallmark of goal-directed cognition in mammalian brains. Although several association brain regions, including the orbitofrontal cortex (OFC), have been implicated, the precise neuronal circuit mechanisms underlying knowledge-based decision-making remain elusive. Here, we established an inference-based auditory categorization task where mice performed within-session flexible stimulus re-categorization by inferring the changing task rules. We constructed a reinforcement learning model to recapitulate the inference-based flexible behavior and quantify the hidden variables associated with task structural knowledge. Combining two-photon population imaging and projection-specific optogenetics, we found that auditory cortex (ACx) neurons encoded the hidden task rule variable, which requires feedback input from the OFC. Silencing OFC-ACx input specifically disrupted re-categorization behavior. Direct imaging from OFC axons in the ACx revealed task state-related feedback signals, supporting the knowledge-based updating mechanism. Our data reveal a cortical circuit mechanism underlying structural knowledge-based flexible decision-making.
An online healthy relationship tool and safety decision aid for women experiencing intimate partner violence (I-DECIDE): a randomised controlled trial.
Hegarty Kelsey,Tarzia Laura,Valpied Jodie,Murray Elizabeth,Humphreys Cathy,Taft Angela,Novy Kitty,Gold Lisa,Glass Nancy
The Lancet. Public health
BACKGROUND:Evidence for online interventions to help women experiencing intimate partner violence is scarce. We assessed whether an online interactive healthy relationship tool and safety decision aid (I-DECIDE) would increase women's self-efficacy and improve depressive symptoms compared with an intimate partner violence information website. METHODS:In this two-group pragmatic randomised controlled trial, we enrolled women who had screened positive for any form of intimate partner violence or fear of a partner in the 6 months before recruitment. Women aged 16-50 years currently residing in Australia, who had safe access to a computer and an internet connection, and who answered positively to one of the screening questions in English were eligible for inclusion. Participants were randomly assigned (1:1) by computer to receive either the intervention or control website. The intervention website consisted of modules on healthy relationships, abuse and safety, and relationship priority setting, and a tailored action plan. The control website was a static intimate partner violence information website. As the initial portion of the website containing the baseline questions was identical for both groups, there was no way for women to tell which group they had been allocated to, and the research team were also masked to participant allocation until after analysis of the 12-month data. Data were collected at baseline, immediately after completion of the website, at 6 months, and 12 months. Primary outcomes were mean general self-efficacy score (immediately after website completion, and at 6 months and 12 months) and mean depression score (at 6 months and 12 months). Data analyses were done according to intention-to-treat principles, accounting for missing data, and adjusted for outcome baseline scores. This trial was registered with the Australian New Zealand Clinical Trials Registry, ACTRN 12614001306606. FINDINGS:Between Jan 16, and Aug 28, 2015, 584 patients registered for the study and were assessed for eligibility. 422 eligible participants were randomly allocated to the intervention group (227 patients) or control group (195 patients). 179 (79%) participants in the intervention group and 156 (80%) participants in the control group completed 12-month follow-up. Mean self-efficacy at 6 months and 12 months was lower for participants in the intervention group than for participants in the control group, although this did not meet the prespecified mean difference (6 months: 27·5 [SD 5·1] vs 28·1 [4·4], imputed mean difference 1·3 [95% CI 0·3 to 2·3]; 12 months: 27·8 [SD 5·4] vs 29·0 [5·0], imputed mean difference 1·6 [95% CI 0·5 to 2·7]). We found no difference between groups in depressive symptoms at 6 months or 12 months (6 months: 22·5 [SD 17·1] vs 24·2 [17·2], imputed mean difference -0·3 [95% CI -3·5 to 3·0]; 12 months: 21·9 [SD 19·3] vs 21·5 [19·3], imputed mean difference -1·9 [95% CI -5·6 to 1·7]). Qualitative findings indicated that participants found the intervention supportive and a motivation for action. INTERPRETATION:Our findings highlight the need for further research, development, and refinement of online interventions for women experiencing intimate partner violence, particularly into the duration needed for interventions. Although we detected no meaningful differences between groups, our qualitative results indicated that some women find an online tool a helpful source of motivation and support. FUNDING:Australian Research Council.
People as Intuitive Scientists: Reconsidering Statistical Explanations of Decision Making.
Szollosi Aba,Newell Ben R
Trends in cognitive sciences
A persistent metaphor in decision-making research casts people as intuitive statisticians. Popular explanations based on this metaphor assume that the way in which people represent the environment is specified and fixed a priori. A major flaw in this account is that it is not clear how people know what aspects of an environment are important, how to interpret those aspects, and how to make decisions based on them. We suggest a theoretical reorientation away from assuming people's representations towards a focus on explaining how people themselves specify what is important to represent. This perspective casts decision makers as intuitive scientists able to flexibly construct, modify, and replace the representations of the decision problems they face.
Anxiety, Depression, and Decision Making: A Computational Perspective.
Bishop Sonia J,Gagne Christopher
Annual review of neuroscience
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.
The Role of the Lateral Intraparietal Area in (the Study of) Decision Making.
Huk Alexander C,Katz Leor N,Yates Jacob L
Annual review of neuroscience
Over the past two decades, neurophysiological responses in the lateral intraparietal area (LIP) have received extensive study for insight into decision making. In a parallel manner, inferred cognitive processes have enriched interpretations of LIP activity. Because of this bidirectional interplay between physiology and cognition, LIP has served as fertile ground for developing quantitative models that link neural activity with decision making. These models stand as some of the most important frameworks for linking brain and mind, and they are now mature enough to be evaluated in finer detail and integrated with other lines of investigation of LIP function. Here, we focus on the relationship between LIP responses and known sensory and motor events in perceptual decision-making tasks, as assessed by correlative and causal methods. The resulting sensorimotor-focused approach offers an account of LIP activity as a multiplexed amalgam of sensory, cognitive, and motor-related activity, with a complex and often indirect relationship to decision processes. Our data-driven focus on multiplexing (and de-multiplexing) of various response components can complement decision-focused models and provides more detailed insight into how neural signals might relate to cognitive processes such as decision making.
The ease and sureness of a decision: evidence accumulation of conflict and uncertainty.
Mandali Alekhya,Weidacker Kathrin,Kim Seung-Goo,Voon Valerie
Brain : a journal of neurology
The likelihood of an outcome (uncertainty or sureness) and the similarity between choices (conflict or ease of a decision) are often critical to decision-making. We often ask ourselves: how likely are we to win or lose? And how different is this option's likelihood from the other? Uncertainty is a characteristic of the stimulus and conflict between stimuli, but these dissociable processes are often confounded. Here, applying a novel hierarchical drift diffusion approach, we study their interaction using a sequential learning task in healthy volunteers and pathological groups characterized by compulsive behaviours, by posing it as an evidence accumulation problem. The variables, Conflict (difficult or easy; difference between reward probabilities of the stimuli) and Uncertainty (low, medium or high; inverse U-shaped probability-uncertainty function) were then used to extract threshold ('a', amount of evidence accumulated before making a decision) and drift rate ('v', information processing speed) parameters. Critically, when a decision was both difficult (high conflict) and uncertain, relative to other conditions, healthy volunteers unexpectedly accumulated less evidence with lower decision thresholds and accuracy rates at chance levels. In contrast, patients with obsessive-compulsive disorder had slower processing speeds during these difficult uncertain decisions; yet, despite this more cautious approach, performed suboptimally with poorer accuracy relative to healthy volunteers below that of chance level. Thus, faced with a difficult uncertain decision, healthy controls are capable of rapid possibly random decisions, displaying almost a willingness to 'walk away', whereas those with obsessive compulsive disorder become more deliberative and cautious but despite appearing to learn the differential contingencies, still perform poorly. These observations might underlie disordered behaviours characterized by pathological uncertainty or doubt despite compulsive checking with impaired performance. In contrast, alcohol-dependent subjects show a different pattern relative to healthy controls with difficulties in adjusting their behavioural patterns with slower drift rates or processing speed despite decisions being easy or low conflict. We emphasize the multidimensional nature of compulsive behaviours and the utility of computational models in detecting subtle underlying processes relative to behavioural measures. These observations have implications for targeted behavioural interventions for specific cognitive impairments across psychiatric disorders.
What factors hinder the decision-making process for women with cancer and contemplating fertility preservation treatment?
Jones Georgina,Hughes Jane,Mahmoodi Neda,Smith Emily,Skull Jonathan,Ledger William
Human reproduction update
BACKGROUND:Although fertility preservation (FP) treatment options have increased, the existing evidence suggests that many women with cancer do not feel well supported in making these decisions, but find them stressful and complex and fail to take up fertility care at this crucial time. Whilst existing reviews have all made important contributions to our understanding of the FP decision-making process, none of them examine solely and specifically these processes for women of reproductive age with a diagnosis of any cancer, leaving a gap in the knowledge base. Given the expectation that care is patient-centred, our review aims to address this gap which may be of help to those managing patients struggling to make difficult decisions in the often brief period before potentially sterilizing cancer treatment is started. OBJECTIVE AND RATIONALE:Underpinning this narrative review was the question 'What factors hinder the decision-making process for women with any cancer and contemplating FP treatment?' Our objectives were to (i) assess and summarize this existing literature, (ii) identify the factors that hinder this decision-making process, (iii) explore to what extent these factors may differ for women choosing different methods of FP and (iv) make recommendations for service delivery and future research. SEARCH METHODS:A systematic search of the medical and social science literature from the 1 January 2005 up to the end of January 2016 was carried out using three electronic databases (Web of Science (PubMed), Ovid SP Medline and CINAHL via Ebsco). Included in the review were quantitative, qualitative and mixed-method studies. Reference lists of relevant papers were also hand searched. From the 983 papers identified, 46 papers were included. Quality assessment was undertaken using the Mixed Methods Appraisal Tool and thematic analysis was used to analyse the data. OUTCOMES:From the analysis, 6 key themes with 15 sub-themes emerged: (i) fertility information provision (lack of information, timing of the information, patient-provider communication); (ii) fear concerning the perceived risks associated with pursuing FP (delaying cancer treatment, aggravating a hormone positive cancer and consequences of a future pregnancy); (iii) non-referral from oncology (personal situation, having a hormone positive cancer, FP not a priority and transition between service issues); (iv) the dilemma (in survival mode, whether to prioritize one treatment over another); (v) personal situation (parity, relationship status) and (iv) costs (financial concerns). WIDER IMPLICATIONS:This review has found that a wide range of internal and external factors impact the FP decision-making process. Key external issues related to current service delivery such as the provision and timing of FP information, and lack of referral from oncology to the fertility clinic. However, internal issues such as women's fears concerning the perceived risks associated with pursuing FP also hindered decision-making but these 'risks' were typically overestimated and non-evidence based. These findings suggest that the implementation of a range of decision support interventions may be of benefit within the clinical care pathway of FP and cancer. Women would benefit from the provision of more evidence-based FP information, ideally received at cancer diagnosis, in advance of seeing a fertility specialist, for example through the implementation of patient decision aids. Healthcare professionals in both oncology and fertility services may also benefit from the implementation of training programmes and educational tools targeted at improving the communication skills needed to improve collaborative decision-making and deliver care that is patient-centred. Exploration of the current barriers, both intellectual and practical, that prevent some patients from accepting FP will help care providers to do better for their patients in the future. Finally, the extent to which a poorer prognosis and moral, ethical and religious beliefs influence the FP decision-making process also warrant further research.
The Psychology and Neuroscience of Financial Decision Making.
Frydman Cary,Camerer Colin F
Trends in cognitive sciences
Financial decisions are among the most important life-shaping decisions that people make. We review facts about financial decisions and what cognitive and neural processes influence them. Because of cognitive constraints and a low average level of financial literacy, many household decisions violate sound financial principles. Households typically have underdiversified stock holdings and low retirement savings rates. Investors overextrapolate from past returns and trade too often. Even top corporate managers, who are typically highly educated, make decisions that are affected by overconfidence and personal history. Many of these behaviors can be explained by well-known principles from cognitive science. A boom in high-quality accumulated evidence-especially how practical, low-cost 'nudges' can improve financial decisions-is already giving clear guidance for balanced government regulation.
Characteristics Associated With Preferences for Parent-Centered Decision Making in Neonatal Intensive Care.
Weiss Elliott Mark,Xie Dawei,Cook Noah,Coughlin Katherine,Joffe Steven
Importance:Little is known about how characteristics of particular clinical decisions influence decision-making preferences by patients or their surrogates. A better understanding of the factors underlying preferences is essential to improve the quality of shared decision making. Objective:To identify the characteristics of particular decisions that are associated with parents' preferences for family- vs medical team-centered decision making across the spectrum of clinical decisions that arise in the neonatal intensive care unit (NICU). Design, Setting, and Participants:This cross-sectional survey assessed parents' preferences for parent- vs medical team-centered decision making across 16 clinical decisions, along with parents' assessments of 7 characteristics of those decisions. Respondents included 136 parents of infants in 1 of 3 academically affiliated hospital NICUs in Philadelphia, Pennsylvania, from January 7 to July 8, 2016. Respondents represented a wide range of educational levels, employment status, and household income but were predominantly female (109 [80.1%]), white (68 [50.0%]) or African American (53 [39.0%]), and married (81 of 132 responding [61.4%]). Main Outcomes and Measures:Preferences for parent-centered decision making. For each decision characteristic (eg, urgency), multivariable analyses tested whether middle and high levels of that characteristic (compared with low levels) were associated with a preference for parent-centered decision making, resulting in 2 odds ratios (ORs) per decision characteristic. Results:Among the 136 respondents (109 women [80.1%] and 27 men [19.9%]; median age, 30 years [range, 18-43 years]), preferences for parent-centered decision making were positively associated with decisions that involved big-picture goals (middle OR, 2.01 [99% CI, 0.83-4.86]; high OR, 3.38 [99% CI, 1.48-7.75]) and that had the potential to harm the infant (middle OR, 1.32 [99% CI, 0.84-2.08]; high OR, 2.62 [99% CI, 1.67-4.11]). In contrast, preferences for parent-centered decision making were inversely associated with the following 4 decision characteristics: technical decisions (middle OR, 0.82 [99% CI, 0.45-1.52]; high OR, 0.48 [99% CI, 0.25-0.93]), the potential to benefit the infant (middle OR, 0.42 [99% CI, 0.16-1.05]; high OR, 0.21 [99% CI, 0.08-0.52]), requires medical expertise (middle OR, 0.48 [99% CI, 0.22-1.05]; high OR, 0.21 [99% CI, 0.10-0.48]), and a high level of urgency (middle OR, 0.47 [99% CI, 0.24-0.92]; high OR, 0.42 [99% CI, 0.22-0.83]). Conclusions and Relevance:Preferences for parent-centered vs medical team-centered decision making among parents of infants in the NICU may vary systematically by the characteristics of particular clinical decisions. Incorporating this variation into shared decision making and endorsing models that allow parents to cede control to physicians in appropriate clinical circumstances might improve the quality and outcomes of medical decisions.
Neurophysiology of Human Perceptual Decision-Making.
O'Connell Redmond G,Kelly Simon P
Annual review of neuroscience
The discovery of neural signals that reflect the dynamics of perceptual decision formation has had a considerable impact. Not only do such signals enable detailed investigations of the neural implementation of the decision-making process but they also can expose key elements of the brain's decision algorithms. For a long time, such signals were only accessible through direct animal brain recordings, and progress in human neuroscience was hampered by the limitations of noninvasive recording techniques. However, recent methodological advances are increasingly enabling the study of human brain signals that finely trace the dynamics of the unfolding decision process. In this review, we highlight how human neurophysiological data are now being leveraged to furnish new insights into the multiple processing levels involved in forming decisions, to inform the construction and evaluation of mathematical models that can explain intra- and interindividual differences, and to examine how key ancillary processes interact with core decision circuits.
Apathy in small vessel cerebrovascular disease is associated with deficits in effort-based decision making.
Saleh Youssuf,Le Heron Campbell,Petitet Pierre,Veldsman Michele,Drew Daniel,Plant Olivia,Schulz Ursula,Sen Arjune,Rothwell Peter M,Manohar Sanjay,Husain Masud
Brain : a journal of neurology
Patients with small vessel cerebrovascular disease frequently suffer from apathy, a debilitating neuropsychiatric syndrome, the underlying mechanisms of which remain to be established. Here we investigated the hypothesis that apathy is associated with disrupted decision making in effort-based decision making, and that these alterations are associated with abnormalities in the white matter network connecting brain regions that underpin such decisions. Eighty-two patients with MRI evidence of small vessel disease were assessed using a behavioural paradigm as well as diffusion weighted MRI. The decision-making task involved accepting or rejecting monetary rewards in return for performing different levels of physical effort (hand grip force). Choice data and reaction times were integrated into a drift diffusion model that framed decisions to accept or reject offers as stochastic processes approaching a decision boundary with a particular drift rate. Tract-based spatial statistics were used to assess the relationship between white matter tract integrity and apathy, while accounting for depression. Overall, patients with apathy accepted significantly fewer offers on this decision-making task. Notably, while apathetic patients were less responsive to low rewards, they were also significantly averse to investing in high effort. Significant reductions in white matter integrity were observed to be specifically related to apathy, but not to depression. These included pathways connecting brain regions previously implicated in effort-based decision making in healthy people. The drift rate to decision parameter was significantly associated with both apathy and altered white matter tracts, suggesting that both brain and behavioural changes in apathy are associated with this single parameter. On the other hand, depression was associated with an increase in the decision boundary, consistent with an increase in the amount of evidence required prior to making a decision. These findings demonstrate altered effort-based decision making for reward in apathy, and also highlight dissociable mechanisms underlying apathy and depression in small vessel disease. They provide clear potential brain and behavioural targets for future therapeutic interventions, as well as modelling parameters that can be used to measure the effects of treatment at the behavioural level.
Decision-making ability, psychopathology, and brain connectivity.
Moutoussis Michael,Garzón Benjamín,Neufeld Sharon,Bach Dominik R,Rigoli Francesco,Goodyer Ian,Bullmore Edward, ,Guitart-Masip Marc,Dolan Raymond J
Decision-making is a cognitive process of central importance for the quality of our lives. Here, we ask whether a common factor underpins our diverse decision-making abilities. We obtained 32 decision-making measures from 830 young people and identified a common factor that we call "decision acuity," which was distinct from IQ and reflected a generic decision-making ability. Decision acuity was decreased in those with aberrant thinking and low general social functioning. Crucially, decision acuity and IQ had dissociable brain signatures, in terms of their associated neural networks of resting-state functional connectivity. Decision acuity was reliably measured, and its relationship with functional connectivity was also stable when measured in the same individuals 18 months later. Thus, our behavioral and brain data identify a new cognitive construct that underpins decision-making ability across multiple domains. This construct may be important for understanding mental health, particularly regarding poor social function and aberrant thought patterns.
Achieving an Optimal Childhood Vaccine Policy.
Opel Douglas J,Schwartz Jason L,Omer Saad B,Silverman Ross,Duchin Jeff,Kodish Eric,Diekema Douglas S,Marcuse Edgar K,Orenstein Walt
Policies to remove parents' ability to opt-out from school immunization requirements on the basis of religious or personal beliefs (ie, nonmedical exemptions) may be a useful strategy to increase immunization rates and prevent outbreaks of vaccine-preventable disease. However, there is uncertainty about the effectiveness of this strategy and the range of possible outcomes. We advocate for a more deliberative process through which a broad range of outcomes is scrutinized and the balance of values underlying the policy decision to eliminate nonmedical exemptions is clearly articulated. We identify 3 outcomes that require particular consideration before policies to eliminate nonmedical exemptions are implemented widely and outline a process for making the values underlying such policies more explicit.
Shared decision making in endocrinology: present and future directions.
Rodriguez-Gutierrez Rene,Gionfriddo Michael R,Ospina Naykky Singh,Maraka Spyridoula,Tamhane Shrikant,Montori Victor M,Brito Juan P
The lancet. Diabetes & endocrinology
In medicine and endocrinology, there are few clinical circumstances in which clinicians can accurately predict what is best for their patients. As a result, patients and clinicians frequently have to make decisions about which there is uncertainty. Uncertainty results from limitations in the research evidence, unclear patient preferences, or an inability to predict how treatments will fit into patients' daily lives. The work that patients and clinicians do together to address the patient's situation and engage in a deliberative dialogue about reasonable treatment options is often called shared decision making. Decision aids are evidence-based tools that facilitate this process. Shared decision making is a patient-centred approach in which clinicians share information about the benefits, harms, and burden of different reasonable diagnostic and treatment options, and patients explain what matters to them in view of their particular values, preferences, and personal context. Beyond the ethical argument in support of this approach, decision aids have been shown to improve patients' knowledge about the available options, accuracy of risk estimates, and decisional comfort. Decision aids also promote patient participation in the decision-making process. Despite accumulating evidence from clinical trials, policy support, and expert recommendations in endocrinology practice guidelines, shared decision making is still not routinely implemented in endocrine practice. Additional work is needed to enrich the number of available tools and to implement them in practice workflows. Also, although the evidence from randomised controlled trials favours the use of this shared decision making in other settings, populations, and illnesses, the effect of this approach has been studied in a few endocrine disorders. Future pragmatic trials are needed to explore the effect and feasibility of shared decision making implementation into routine endocrinology and primary care practice. With the available evidence, however, endocrinologists can now start to practice shared decision making, partner with their patients, and use their expertise to formulate treatment plans that reflect patient preferences and are more likely to fit into the context of patients' lives. In this Personal View, we describe shared decision making, the evidence behind the approach, and why and how both endocrinologists and their patients could benefit from this approach.
Heuristic and optimal policy computations in the human brain during sequential decision-making.
Korn Christoph W,Bach Dominik R
Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.
Learning Near-Optimal Cost-Sensitive Decision Policy for Object Detection.
Wu Tianfu,Zhu Song-Chun
IEEE transactions on pattern analysis and machine intelligence
Many popular object detectors, such as AdaBoost, SVM and deformable part-based models (DPM), compute additive scoring functions at a large number of windows in an image pyramid, thus computational efficiency is an important consideration in real time applications besides accuracy. In this paper, a decision policy refers to a sequence of two-sided thresholds to execute early reject and early accept based on the cumulative scores at each step. We formulate an empirical risk function as the weighted sum of the cost of computation and the loss of false alarm and missing detection. Then a policy is said to be cost-sensitive and optimal if it minimizes the risk function. While the risk function is complex due to high-order correlations among the two-sided thresholds, we find that its upper bound can be optimized by dynamic programming efficiently. We show that the upper bound is very tight empirically and thus the resulting policy is said to be near-optimal. In experiments, we show that the decision policy outperforms state-of-the-art cascade methods significantly, in several popular detection tasks and benchmarks, in terms of computational efficiency with similar accuracy of detection.
Judgment and Decision Making.
Fischhoff Baruch,Broomell Stephen B
Annual review of psychology
The science of judgment and decision making involves three interrelated forms of research: analysis of the decisions people face, description of their natural responses, and interventions meant to help them do better. After briefly introducing the field's intellectual foundations, we review recent basic research into the three core elements of decision making: judgment, or how people predict the outcomes that will follow possible choices; preference, or how people weigh those outcomes; and choice, or how people combine judgments and preferences to reach a decision. We then review research into two potential sources of behavioral heterogeneity: individual differences in decision-making competence and developmental changes across the life span. Next, we illustrate applications intended to improve individual and organizational decision making in health, public policy, intelligence analysis, and risk management. We emphasize the potential value of coupling analytical and behavioral research and having basic and applied research inform one another.
Guided Policy Exploration for Markov Decision Processes Using an Uncertainty-Based Value-of-Information Criterion.
Sledge Isaac J,Emigh Matthew S,Principe Jose C
IEEE transactions on neural networks and learning systems
Reinforcement learning in environments with many action-state pairs is challenging. The issue is the number of episodes needed to thoroughly search the policy space. Most conventional heuristics address this search problem in a stochastic manner. This can leave large portions of the policy space unvisited during the early training stages. In this paper, we propose an uncertainty-based, information-theoretic approach for performing guided stochastic searches that more effectively cover the policy space. Our approach is based on the value of information, a criterion that provides the optimal tradeoff between expected costs and the granularity of the search process. The value of information yields a stochastic routine for choosing actions during learning that can explore the policy space in a coarse to fine manner. We augment this criterion with a state-transition uncertainty factor, which guides the search process into previously unexplored regions of the policy space. We evaluate the uncertainty-based value-of-information policies on the games Centipede and Crossy Road. Our results indicate that our approach yields better performing policies in fewer episodes than stochastic-based exploration strategies. We show that the training rate for our approach can be further improved by using the policy cross entropy to guide our criterion's hyperparameter selection.