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The Effects of Social Context and Acute Stress on Decision Making Under Uncertainty.

ABSTRACT: Uncertainty preferences are typically studied in neutral, nonsocial contexts. This approach, however, fails to capture the dynamic factors that influence choices under uncertainty in the real world. Our goal was twofold: to test whether uncertainty valuation is similar across social and nonsocial contexts, and to investigate the effects of acute stress on uncertainty preferences. Subjects completed matched gambling and trust games following either a control or a stress manipulation. Those who were not under stress exhibited no differences between the amount of money gambled and the amount of money entrusted to partners. In comparison, stressed subjects gambled more money but entrusted less money to partners. We further found that irrespective of stress, subjects were highly attuned to irrelevant feedback in the nonsocial, gambling context, believing that every loss led to a greater chance of winning (the gamblers' fallacy). However, when deciding to trust a stranger, control subjects behaved rationally, treating each new interaction as independent. Stress compromised this adaptive behavior, increasing sensitivity to irrelevant social feedback.

SUBMITTER: FeldmanHall O

PROVIDER: S-EPMC4679610 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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The Effects of Social Context and Acute Stress on Decision Making Under Uncertainty.

FeldmanHall Oriel O Raio Candace M CM Kubota Jennifer T JT Seiler Morgan G MG Phelps Elizabeth A EA

Psychological science 20151105 12

Uncertainty preferences are typically studied in neutral, nonsocial contexts. This approach, however, fails to capture the dynamic factors that influence choices under uncertainty in the real world. Our goal was twofold: to test whether uncertainty valuation is similar across social and nonsocial contexts, and to investigate the effects of acute stress on uncertainty preferences. Subjects completed matched gambling and trust games following either a control or a stress manipulation. Those who we ...[more]

PMID: 26546080

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Project description:BackgroundStatistical inference based on small datasets, commonly found in precision oncology, is subject to low power and high uncertainty. In these settings, drawing strong conclusions about future research utility is difficult when using standard inferential measures. It is therefore important to better quantify the uncertainty associated with both significant and non-significant results based on small sample sizes.MethodsWe developed a new method, Bayesian Additional Evidence (BAE), that determines (1) how much additional supportive evidence is needed for a non-significant result to reach Bayesian posterior credibility, or (2) how much additional opposing evidence is needed to render a significant result non-credible. Although based in Bayesian analysis, a prior distribution is not needed; instead, the tipping point output is compared to reasonable effect ranges to draw conclusions. We demonstrate our approach in a comparative effectiveness analysis comparing two treatments in a real world biomarker-defined cohort, and provide guidelines for how to apply BAE in practice.ResultsOur initial comparative effectiveness analysis results in a hazard ratio of 0.31 with 95% confidence interval (0.09, 1.1). Applying BAE to this result yields a tipping point of 0.54; thus, an observed hazard ratio of 0.54 or smaller in a replication study would result in posterior credibility for the treatment association. Given that effect sizes in this range are not extreme, and that supportive evidence exists from a similar published study, we conclude that this problem is worthy of further research.ConclusionsOur proposed method provides a useful framework for interpreting analytic results from small datasets. This can assist researchers in deciding how to interpret and continue their investigations based on an initial analysis that has high uncertainty. Although we illustrated its use in estimating parameters based on time-to-event outcomes, BAE easily applies to any normally-distributed estimator, such as those used for analyzing binary or continuous outcomes.

Project description:Background. Previous research has examined the individual effects of uncertainty, time pressure, perceived stress, and team support on decision making. However, scant research has investigated how team support and perceived stress collectively influence providers' perception of decision conflict and satisfaction with decision. Objectives. The present study aims to fill this void by examining the potential mediating role of perceived stress and team support in the relationship between time pressure, uncertainty, decision satisfaction, and decision conflict. Methods. Obstetrics and gynecology (Obs and Gynae) physicians (N = 347) working in tertiary care hospitals were approached through snowball and purposive convenient sampling. Self-reported data were collected in the form of questionnaires. Results. Structural equation modeling was used to uncover the complex linkages. Perceived stress was found to be a significant mediator between uncertainty and decision conflict (b = -0.033, P < 0.05). In addition, team support was also found to be a significant mediator between uncertainty and decision satisfaction (b = 0.082, P < 0.05) as well as between time pressure and decision satisfaction (b = 0.086, P < 0.05). Conclusion. Team support acts as a bridge between uncertainty and decision satisfaction and also between time pressure and decision satisfaction, underscoring its critical role in provider perceptions of decision making in the Obs and Gynae context. Implications. This study highlights the significance of managing stress, enhancing team support, and giving priority to patient-centered care. These findings provide insights into risk and uncertainty management in medical decision making, advancing patient-centered care, and optimizing health care outcomes.HighlightsStressors in hospital settings such as the complexity and uncertainty of tasks create stress among physicians, potentially leading to decision conflicts.Team support plays a fundamental role in mitigating the negative effects of stressors such as time pressure and uncertainty.Implementing stress management and team support interventions such as cognitive-behavioral therapy and mindfulness may enhance decision making among Obs and Gynae physicians.

Dataset Information

The Effects of Social Context and Acute Stress on Decision Making Under Uncertainty.

Publications

The Effects of Social Context and Acute Stress on Decision Making Under Uncertainty.

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