This study tested the proposition that deficient decision making under stress is due, to a significant extent, to the individual's failure to fulfill adequately an elementary requirement of the decision-making process, that is, the systematic consideration of all relevant alternatives. One hundred one undergraduate students (59 women and 42 men), aged 20-40, served as subjects in this experiment. They were requested to solve decision problems, using an interactive computer paradigm, while being exposed to controllable stress, uncontrollable stress, or no stress at all. There was no time constraint for the performance of the task. The controllability of the stressor was found to have no effect on the participants' performance. However, those who were exposed to either controllable or uncontrollable stress showed a significantly stronger tendency to offer solutions before all available alternatives had been considered and to scan their alternatives in a nonsystematic fashion than did participants who were not exposed to stress. In addition, patterns of alternative scanning were found to be correlated with the correctness of solutions to decision problems.

Download full-text PDF

Source
http://dx.doi.org/10.1037//0022-3514.52.3.639DOI Listing

Publication Analysis

Top Keywords

decision making
8
making stress
8
controllable uncontrollable
8
decision problems
8
exposed controllable
8
uncontrollable stress
8
stress
7
decision
4
stress scanning
4
alternatives
4

Similar Publications

Cost reductions are essential for accelerating clean technology deployment. Because multiple factors influence costs, traditional one-factor learning models, solely relying on cumulative installed capacity as an explanatory variable, may oversimplify cost dynamics. In this study, we disentangle learning and economies of scale effects at unit and project levels and introduce a knowledge gap concept to quantify rapid technological change's impact on costs.

View Article and Find Full Text PDF

Introduction: When implemented by national and regional regulatory agencies good review practices (GRevPs) support the timely high-quality review of medicines for enhanced patients' availability to safe, quality and efficacious innovative and generic products. It is important that all aspects of GRevPs are continuously evaluated and updated to promote the continuous improvement of regulatory systems at national and regional levels. The aim of this study was to assess and compare the GRevPs of the national medicines regulatory agencies (NMRAs) of Burkina Faso, Cote d'Ivoire, Ghana, Nigeria, Senegal, Sierra Leone and Togo, who are active participants of the ECOWASMRH initiative to identify opportunities for improvement.

View Article and Find Full Text PDF

Exploring using HBsAg to predict interferon treatment course to achieve clinical cure in chronic hepatitis B patients: a clinical study.

Front Immunol

January 2025

Department of Gastroenterology and Hepatology, Tianjin Third Central Hospital, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Institute of Hepatobiliary Disease, Tianjin, China.

Objective: Although pegylated interferon α-2b (PEG-IFN α-2b) therapy for chronic hepatitis B has received increasing attention, determining the optimal treatment course remains challenging. This research aimed to develop an efficient model for predicting interferon (IFN) treatment course.

Methods: Patients with chronic hepatitis B, undergoing PEG-IFN α-2b monotherapy or combined with NAs (Nucleoside Analogs), were recruited from January 2018 to December 2023 at Tianjin Third Central Hospital.

View Article and Find Full Text PDF

Background: Most patients initially diagnosed with non-muscle invasive bladder cancer (NMIBC) still have frequent recurrence after urethral bladder tumor electrodesiccation supplemented with intravesical instillation therapy, and their risk of recurrence is difficult to predict. Risk prediction models used to predict postoperative recurrence in patients with NMIBC have limitations, such as a limited number of included cases and a lack of validation. Therefore, there is an urgent need to develop new models to compensate for the shortcomings and potentially provide evidence for predicting postoperative recurrence in NMIBC patients.

View Article and Find Full Text PDF

Background: Multidrug-resistant Klebsiella pneumoniae (MDR-KP) infections pose a significant global healthcare challenge, particularly due to the high mortality risk associated with septic shock. This study aimed to develop and validate a machine learning-based model to predict the risk of MDR-KP-associated septic shock, enabling early risk stratification and targeted interventions.

Methods: A retrospective analysis was conducted on 1,385 patients with MDR-KP infections admitted between January 2019 and June 2024.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!