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Researchers and educators in humanities such as computational linguists, digital humanists, and those doing historical reconstructions are increasingly heavy users of computational and/or data resources. Many know about activities, working groups, and initiatives around the findable, accessible, interoperable, reusable (FAIR) principles and are a driving force for improving the sharing of data and software. However, it seems humanities researchers are less aware of the science gateways community and the end-to-end solutions that science gateways could provide, therefore lacking a driving force for adoption of this technology. This small-scale exploratory study will clarify some of the challenges and needs faced by computational researchers in the humanities that may explain their relatively low participation in the science gateways community. For this paper, we present the results of 19 interviews with seven women, 11 men, and one nonbinary individual from seven states and DC in the United States with a range of professional backgrounds and roles. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to describe patient-specific factors predictive of surgical delay in elective surgical cases., Design: Retrospective cohort study., Methods: Data were extracted retrospectively from the electronic health record of 32,818 patients who underwent surgery at a large academic hospital in Los Angeles between May 2012 and April 2017. Following bivariate analysis of patient-specific factors and surgical delay, statistically significant predictors were entered into a logistic regression model to determine the most significant predictors of surgical delay., Findings: Predictors of delay included having monitored anesthesia care (odds ratio [OR], 1.28; 95% confidence intervals [CI], 1.20-1.36), American Society of Anesthesiologist class 3 or above (OR, 1.21; 95% CI, 1.15-1.28), African American race (OR, 1.25; 95% CI, 1.12-1.39), renal failure (OR, 1.20; 95% CI, 1.09-1.32), steroid medication (OR, 1.13; 95% CI, 1.04-1.23) and Medicaid (OR,1.18; 95%CI, 1.09-1.30) or medicare insurance (OR, 1.14; 95% CI, 1.07-1.21). Six surgical specialties also increased the odds of delay. Obesity and cardiovascular anesthesia decreased the odds of delay., Conclusions: Certain patient-specific factors including type of insurance, health status, and race were associated with surgical delay. Whereas monitored anesthesia care anesthesia was predictive of a delay, cardiovascular anesthesia reduced the odds of delay. Additionally, obese patients were less likely to experience a delay. While the electronic health record provided a large amount of detailed information, barriers existed to accessing meaningful data., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The American Society of PeriAnesthesia Nurses. Published by Elsevier Inc. All rights reserved.)