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Scientific Reports Oct 2023During insightful problem solving, the solution appears unexpectedly and is accompanied by the feeling of an AHA!. Research suggests that this affective component of...
During insightful problem solving, the solution appears unexpectedly and is accompanied by the feeling of an AHA!. Research suggests that this affective component of insight can have consequences beyond the solution itself by motivating future behavior, such as risky (high reward and high uncertainty) decision making. Here, we investigate the behavioral and neural support for the motivational role of AHA in decision making involving monetary choices. The positive affect of the AHA! experience has been linked to internal reward. Reward in turn has been linked to dopaminergic signal transmission in the Nucleus Accumbens (NAcc) and risky decision making. Therefore, we hypothesized that insight activates reward-related brain areas, modulating risky decision making. We tested this hypothesis in two studies. First, in a pre-registered online study (Study 1), we demonstrated the behavioral effect of insight-related increase in risky decision making using a visual Mooney identification paradigm. Participants were more likely to choose the riskier monetary payout when they had previously solved the Mooney image with high compared to low accompanied AHA!. Second, in an fMRI study (Study 2), we measured the effects of insight on NAcc activity using a similar Mooney identification paradigm to the one of Study 1. Greater NAcc activity was found when participants solved the Mooney image with high vs low AHA!. Taken together, our results link insight to enhanced NAcc activity and a preference for high but uncertain rewards, suggesting that insight enhances reward-related brain areas possibly via dopaminergic signal transmission, promoting risky decision making.
Topics: Humans; Nucleus Accumbens; Decision Making; Brain; Uncertainty; Problem Solving; Dopamine; Reward; Risk-Taking
PubMed: 37821507
DOI: 10.1038/s41598-023-44293-2 -
Anaesthesia Feb 2023
Topics: Humans; Uncertainty; Emotions; Decision Making; Communication
PubMed: 36196780
DOI: 10.1111/anae.15875 -
PloS One 2023We present a novel mathematical model of two adversarial forces in the vicinity of a non-combatant population in order to explore the impact of each force pursuing...
We present a novel mathematical model of two adversarial forces in the vicinity of a non-combatant population in order to explore the impact of each force pursuing specific decision-making strategies. Each force has the opportunity to draw support by enabling the decision-making initiative of the population, in tension with maintaining tactical and organisational effectiveness over their adversary. Each dynamic model component of force, population and decision-making, is defined by the archetypal Lanchester, Lotka-Volterra and Kuramoto-Sakaguchi models, with feedback between each component adding heterogeneity. Developing a scheme where cultural factors determine decision-making strategies for each force, this work highlights the parametric and topological factors that influence favourable results in a non-linear system where physical outcomes are highly dependent on the non-physical and cognitive nature of each force's intended strategy.
Topics: Decision Making; Models, Theoretical
PubMed: 36745613
DOI: 10.1371/journal.pone.0281169 -
Neuroscience and Biobehavioral Reviews Aug 2019Social animals must detect, evaluate and respond to the emotional states of other individuals in their group. A constellation of gestures, vocalizations, and... (Review)
Review
Social animals must detect, evaluate and respond to the emotional states of other individuals in their group. A constellation of gestures, vocalizations, and chemosignals enable animals to convey affect and arousal to others in nuanced, multisensory ways. Observers integrate social information with environmental and internal factors to select behavioral responses to others via a process call social decision-making. The Social Decision Making Network (SDMN) is a system of brain structures and neurochemicals that are conserved across species (mammals, reptiles, amphibians, birds) that are the proximal mediators of most social behaviors. However, how sensory information reaches the SDMN to shape behavioral responses during a social encounter is not well known. Here we review the empirical data that demonstrate the necessity of sensory systems in detecting social stimuli, as well as the anatomical connectivity of sensory systems with each node of the SDMN. We conclude that the insular cortex is positioned to link integrated social sensory cues to this network to produce flexible and appropriate behavioral responses to socioemotional cues.
Topics: Animals; Behavior, Animal; Cerebral Cortex; Decision Making; Emotions; Humans; Nerve Net; Social Behavior; Social Perception
PubMed: 31194999
DOI: 10.1016/j.neubiorev.2019.06.005 -
International Journal of Older People... Jan 2023Transitions to long-term care are challenging for individuals and often associated with a loss of autonomy. Positive experiences are noted, especially when decisions... (Review)
Review
BACKGROUND
Transitions to long-term care are challenging for individuals and often associated with a loss of autonomy. Positive experiences are noted, especially when decisions involve the individual in a person-centred way which are respectful of the person's human rights. One approach which facilitates self-determination during a transitional period is shared decision-making, but there is a lack of clarity on the nature and extent of research evidence in this area.
OBJECTIVE
The purpose of this scoping review is to identify and document research related to shared decision-making and transitioning to long-term care.
METHODS
A comprehensive search in CINAHL, Medline and Psych-info identified papers which included evidence of shared decision-making during transitions to a long-term care setting. The review following the JBI and PAGER framework for scoping reviews. Data were extracted, charted and analysed according to patterns, advances, gaps, research recommendations and evidence for practice.
RESULTS
Eighteen papers met the inclusion criteria. A body of knowledge was identified encompassing the pattern advancements in shared decision-making during transitions to long-term care, representing developments in both the evidence base and methodological approaches. Further patterns offer evidence of the facilitators and barriers experienced by the person, their families and the professional's involved.
CONCLUSIONS
The evidence identified the complexity of such decision-making with efforts to engage in shared decision-making often constrained by the availability of resources, the skills of professionals and time. The findings recognise the need for partnership and person-centred approaches to optimise transitions. The review demonstrates evidence of approaches that can inform future practice and research to support all adult populations who may be faced with a transitional decision to actively participate in decision-making.
Topics: Humans; Long-Term Care; Decision Making, Shared; Decision Making
PubMed: 36480119
DOI: 10.1111/opn.12518 -
Journal of Healthcare Engineering 2021In decision-making systems, how to measure uncertain information remains an open issue, especially for information processing modeled on complex planes. In this paper, a...
In decision-making systems, how to measure uncertain information remains an open issue, especially for information processing modeled on complex planes. In this paper, a new complex entropy is proposed to measure the uncertainty of a complex-valued distribution (CvD). The proposed complex entropy is a generalization of Gini entropy that has a powerful capability to measure uncertainty. In particular, when a CvD reduces to a probability distribution, the complex entropy will degrade into Gini entropy. In addition, the properties of complex entropy, including the nonnegativity, maximum and minimum entropies, and boundedness, are analyzed and discussed. Several numerical examples illuminate the superiority of the newly defined complex entropy. Based on the newly defined complex entropy, a multisource information fusion algorithm for decision-making is developed. Finally, we apply the decision-making algorithm in a medical diagnosis problem to validate its practicability.
Topics: Algorithms; Decision Making; Diagnosis; Entropy; Humans; Probability; Uncertainty
PubMed: 33777342
DOI: 10.1155/2021/5559529 -
Addictive Behaviors Aug 2023The Iowa Gambling Task (IGT) is one of the most widely used paradigms for assessing decision-making. An impairment in this process may be linked to several...
The Iowa Gambling Task (IGT) is one of the most widely used paradigms for assessing decision-making. An impairment in this process may be linked to several psychopathological disorders, such as obsessive-compulsive disorder (OCD), substance abuse disorder (SUD) or attention-deficit/hyperactivity disorder (ADHD), which could make it a good candidate for being consider a transdiagnostic domain. Resting-state functional connectivity (rsFC) has been proposed as a promising biomarker of decision-making. In this study, we aimed to identify idiosyncratic decision-making profiles among healthy people and impulsive-compulsive spectrum patients during the IGT, and to investigate the role of frontoparietal network (FPN) rsFC as a possible biomarker of different decision-making patterns. Using functional near-infrared spectroscopy (fNIRS), rsFC of 114 adults (34 controls; 25 OCD; 41 SUD; 14 ADHD) was obtained. Then, they completed the IGT. Hybrid clustering methods based on individual deck choices yielded three decision-makers subgroups. Cluster 1 (n = 27) showed a long-term advantageous strategy. Cluster 2 (n = 25) presented a maladaptive decision-making strategy. Cluster 3 (n = 62) did not develop a preference for any deck during the task. Interestingly, the proportion of participants in each cluster was not different between diagnostic groups. A Bayesian general linear model showed no credible differences in the IGT performance between diagnostic groups nor credible evidence to support the role of FPN rsFC as a biomarker of decision-making under the IGT context. This study highlights the importance of exploring in depth the behavioral and neurophysiological variables that may drive decision-making in clinical and healthy populations.
Topics: Adult; Humans; Decision Making; Bayes Theorem; Neuropsychological Tests; Gambling; Substance-Related Disorders; Biomarkers
PubMed: 36963236
DOI: 10.1016/j.addbeh.2023.107683 -
ELife Feb 2023Perceptual decisions are biased toward higher-value options when overall gains can be improved. When stimuli demand immediate reactions, the neurophysiological decision...
Perceptual decisions are biased toward higher-value options when overall gains can be improved. When stimuli demand immediate reactions, the neurophysiological decision process dynamically evolves through distinct phases of growing anticipation, detection, and discrimination, but how value biases are exerted through these phases remains unknown. Here, by parsing motor preparation dynamics in human electrophysiology, we uncovered a multiphasic pattern of countervailing biases operating in speeded decisions. Anticipatory preparation of higher-value actions began earlier, conferring a 'starting point' advantage at stimulus onset, but the delayed preparation of lower-value actions was steeper, conferring a value-opposed buildup-rate bias. This, in turn, was countered by a transient deflection toward the higher-value action evoked by stimulus detection. A neurally-constrained process model featuring anticipatory urgency, biased detection, and accumulation of growing stimulus-discriminating evidence, successfully captured both behavior and motor preparation dynamics. Thus, an intricate interplay of distinct biasing mechanisms serves to prioritise time-constrained perceptual decisions.
Topics: Humans; Decision Making; Reaction Time; Choice Behavior; Bias
PubMed: 36779966
DOI: 10.7554/eLife.67711 -
The British Journal of General Practice... Aug 2022Shared decision making (SDM), utilising the expertise of both patient and clinician, is a key feature of good-quality patient care. Multimorbidity can complicate SDM,...
BACKGROUND
Shared decision making (SDM), utilising the expertise of both patient and clinician, is a key feature of good-quality patient care. Multimorbidity can complicate SDM, yet few studies have explored this dynamic for older patients with multimorbidity in general practice.
AIM
To explore factors influencing SDM from the perspectives of older patients with multimorbidity and GPs, to inform improvements in personalised care.
DESIGN AND SETTING
Qualitative study. General practices (rural and urban) in Devon, England.
METHOD
Four focus groups: two with patients (aged ≥65 years with multimorbidity) and two with GPs. Data were coded inductively by applying thematic analysis.
RESULTS
Patient acknowledgement of clinician medicolegal vulnerability in the context of multimorbidity, and their recognition of this as a barrier to SDM, is a new finding. Medicolegal vulnerability was a unifying theme for other reported barriers to SDM. These included expectations for GPs to follow clinical guidelines, challenges encountered in applying guidelines and in communicating clinical uncertainty, and limited clinician self-efficacy for SDM. Increasing consultation duration and improving continuity were viewed as facilitators.
CONCLUSION
Clinician perceptions of medicolegal vulnerability are recognised by both patients and GPs as a barrier to SDM and should be addressed to optimise delivery of personalised care. Greater awareness of multimorbidity guidelines is needed. Educating clinicians in the communication of uncertainty should be a core component of SDM training. The incorrect perception that most clinicians already effectively facilitate SDM should be addressed to improve the uptake of personalised care interventions.
Topics: Aged; Clinical Decision-Making; Decision Making; Decision Making, Shared; Humans; Multimorbidity; Patient Participation; Qualitative Research; Uncertainty
PubMed: 35379603
DOI: 10.3399/BJGP.2021.0529 -
Health Expectations : An International... Oct 2020Shared decision making (SDM) has been increasingly implemented to improve health-care outcomes. Despite the mixed efficacy of SDM to provide better patient-guided care,... (Review)
Review
BACKGROUND
Shared decision making (SDM) has been increasingly implemented to improve health-care outcomes. Despite the mixed efficacy of SDM to provide better patient-guided care, its use in surgery has not been studied. The aim of this study was to systematically review SDM application in surgery.
DESIGN
The search strategy, developed with a medical librarian, included nine databases from inception until June 2019. After a 2-person title and abstract screen, full-text publications were analysed. Data collected included author, year, surgical discipline, location, study duration, type of decision aid, survey methodology and variable outcomes. Quantitative and qualitative cross-sectional studies, as well as RCTs, were included.
RESULTS
A total of 6060 studies were retrieved. A total of 148 were included in the final review. The majority of the studies were in plastic surgery, followed by general surgery and orthopaedics. The use of SDM decreased surgical intervention rate (12 of 22), decisional conflict (25 of 29), and decisional regret (5 of 5), and increased decisional satisfaction (17 of 21), knowledge (33 of 35), SDM preference (13 of 16), and physician trust (4 of 6). Time increase per patient encounter was inconclusive. Cross-sectional studies showed that patients prefer shared treatment and surgical treatment varied less. The results of SDM per type of decision aid vary in terms of their outcome.
CONCLUSION
SDM in surgery decreases decisional conflict, anxiety and surgical intervention rates, while increasing knowledge retained decisional satisfaction, quality and physician trust. Surgical patients also appear to prefer SDM paradigms. SDM appears beneficial in surgery and therefore worth promoting and expanding in use.
Topics: Cross-Sectional Studies; Decision Making; Decision Making, Shared; Humans; Patient Participation; Patients
PubMed: 32700367
DOI: 10.1111/hex.13105