Thriving under pressure: The effects of stress-related wise interventions on affect, sleep, and exam performance for disadvantaged college students
Nearly all students experience stress as they pursue important academic goals. Because stress can be magnified for students from disadvantaged backgrounds, it becomes important to identify interventions that can help mitigate this stress, particularly for these populations as they enter academic environments. We examine the effects of stress mindset and stress management interventions administered to students from disadvantaged backgrounds (N = 140) before freshman year.
Regional personality differences predict variation in COVID-19 infections and social distancing behavior
The early stages of the COVID-19 pandemic revealed stark regional variation in the spread of the virus. While previous research has highlighted the impact of regional differences in sociodemographic and economic factors, we argue that regional differences in social and compliance behaviors-the very behaviors through which the virus is transmitted-are critical drivers of the spread of COVID-19, particularly in the early stages of the pandemic.
Identifying Factors Predicting Kidney Graft Survival in Chile Using Elastic-Net-Regularized Cox Regression
We developed a predictive statistical model to identify donor–recipient characteristics related to kidney graft survival in the Chilean population. Given the large number of potential predictors relative to the sample size, we implemented an automated variable selection mechanism that could be revised in future studies as more national data is collected. Materials and Methods: A retrospective multicenter study was conducted to analyze data from 822 adult kidney transplant recipients from adult donors between 1998 and 2018.
Utilizing Partial Flexibility to Improve Emergency Department Flow: Theory and Implementation
Emergency Departments (EDs) typically have multiple areas where patients of different acuity levels receive treatments. In practice, different areas often operate with fixed nurse staffing levels. When there are substantial imbalances in congestion among different areas, it could be beneficial to deviate from the original assignment and reassign nurses. However, reassignments typically are only feasible at the beginning of 8-12-hour shifts, providing partial flexibility in adjusting staffing levels.
Quantifying utilitarian outcomes to inform triage ethics: Simulated performance of a ventilator triage protocol under Sars-CoV-2 pandemic surge conditions
Background
Equitable protocols to triage life-saving resources must be specified prior to shortages in order to promote transparency, trust and consistency. How well proposed utilitarian protocols perform to maximize lives saved is unknown. We aimed to estimate the survival rates that would be associated with implementation of the New York State 2015 guidelines for ventilator triage, and to compare them to a first-come-first-served triage method.
Methods
Service design to balance waiting time and infection risk: An application for elections during the COVID-19 pandemic
The COVID-19 pandemic has caused great disruption to the service sector, and it has, in turn, adapted by implementing measures that reduce physical contact among employees and users; examples include home-office work and the setting of occupancy restrictions at indoor locations.
The social divide of social distancing: Shelter-in-place behavior in Santiago during the COVID-19 pandemic
Optimal Scheduling of Proactive Service with Customer Deterioration and Improvement
Service systems are typically limited resource environments where scarce capacity is reserved for the most urgent customers. However, there has been a growing interest in the use of proactive service when a less urgent customer may become urgent while waiting. On one hand, providing service for customers when they are less urgent could mean that fewer resources are needed to fulfill their service requirement. On the other hand, using limited capacity for customers who may never need the service in the future takes the capacity away from other more urgent customers who need it now.
Differences in Consumer-Benefiting Misconduct by Nonprofit, For-profit, and Public Organizations
We examine how organizations of different types --public, non-profit and for-profit -- engage in consumer-benefiting misconduct (CBM) by examining which patients benefit from hospitals of the three types gaming the market for liver transplants. Consistent with our theory, we find that public firms are the least likely of the three organization types to engage in CBM.
Information Avoidance and Information Seeking Among Parents of Children with ASD
We estimated the effects of information avoidance and information seeking among parents of children diagnosed with ASD on age of diagnosis. An online survey was completed by 1,815 parents of children with ASD. Children of parents who self-reported that they had preferred "not to know," reported diagnoses around 3 months later than other children.
Dynamic Server Assignment in Multiclass Queues with Shifts, with Applications to Nurse Staffing in Emergency Departments
Many service systems are staffed by workers who work in shifts. In this work, we study the dynamic assignment of servers to different areas of a service system at the beginning of discrete time-intervals, i.e., shifts. The ability to reassign servers at discrete intervals, rather than continuously, introduces a partial flexibility that provides an opportunity for reducing the expected waiting time of customers.
Robustness of proactive ICU transfer policies, Operations Research, to appear
Patients whose transfer to the Intensive Care Unit (ICU) is unplanned are prone to higher mortality rates and longer length-of-stay than those who were admitted directly to the ICU. Recent advances in machine learning to predict patient deterioration have introduced the possibility of proactive transfer from the ward to the ICU. In this work, we study the problem of finding robust patient transfer policies which account for uncertainty in statistical estimates due to data limitations when optimizing to improve overall patient care.