Center for Vaccines and Immunity, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH; Department of Pediatrics, Division of Pediatric Infectious Diseases, Nationwide Children's Hospital and The Ohio State University College of Medicine, Columbus, OH.
Center for Perinatal Research, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH; Department of Pediatrics, Division of Neonatology, Nationwide Children's Hospital and The Ohio State University College of Medicine, Columbus, OH.
Department of Pediatrics, Division of Pediatric Infectious Diseases, Nationwide Children's Hospital and The Ohio State University College of Medicine, Columbus, OH; Center for Perinatal Research, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH; Department of Pediatrics, Division of Neonatology, Nationwide Children's Hospital and The Ohio State University College of Medicine, Columbus, OH.
Department of Pediatrics, Division of Neonatology, Nationwide Children's Hospital and The Ohio State University College of Medicine, Columbus, OH. Electronic address: Daniel.Malleske@nationwidechildrens.org.
Department of Surgery, Jichi Medical University Saitama Medical Center, 1-chome-847 Amanuma-cho, Omiya-ku, Saitama City, Saitama, 330-8503, Japan. Electronic address: m02055yt@jichi.ac.jp.
Department of Surgery, Jichi Medical University Saitama Medical Center, 1-chome-847 Amanuma-cho, Omiya-ku, Saitama City, Saitama, 330-8503, Japan. Electronic address: msaito@jichi.ac.jp.
Department of Surgery, Jichi Medical University Saitama Medical Center, 1-chome-847 Amanuma-cho, Omiya-ku, Saitama City, Saitama, 330-8503, Japan. Electronic address: sarusuke_papu22@yahoo.co.jp.
Department of Surgery, Jichi Medical University Saitama Medical Center, 1-chome-847 Amanuma-cho, Omiya-ku, Saitama City, Saitama, 330-8503, Japan. Electronic address: yutamuto@jichi.ac.jp.
Department of Pathology, Jichi Medical University Saitama Medical Center, 1-chome-847 Amanuma-cho, Omiya-ku, Saitama City, Saitama, 330-8503, Japan. Electronic address: atanaka@jichi.ac.jp.
Department of Surgery, Jichi Medical University Saitama Medical Center, 1-chome-847 Amanuma-cho, Omiya-ku, Saitama City, Saitama, 330-8503, Japan. Electronic address: trikiyama@jichi.ac.jp.
This study examined the relationships between training workloads, game workloads, and match performance in an elite netball team....
Ten elite female netball athletes were monitored over a complete season. Training and game external workloads were determined through inertial movement units and expressed as absolute PlayerLoad (PL) ...
Monthly PL, training efficiency index PL, and avgMC PL were statistically significant (P < .05) and positively related to game PL (z = 0.20-0.35, P < .001-.02). For game COD, statistically significant...
Higher monthly workloads are related to higher game workload; however, they are also related to decreases in match performance. Therefore, netball practitioners should consider that increases to train...
The ideal hospitalist workload and optimal way to measure it are not well understood....
To obtain expert consensus on the salient measures of hospitalist workload....
This qualitative study used a 3-round Delphi technique between April 5 and July 13, 2022, involving national experts within and external to the field. Experts included hospitalist clinicians, leaders,...
Three rounds of surveys were conducted, during which participants provided input on the salient measures of hospitalist workload across various domains. In the first round, free-text data collected fr...
Seventeen individuals from 14 organizations, encompassing clinicians, leaders, administrators, and researchers, participated in 3 rounds of surveys. In round 1, participants provided 135 unique qualit...
In this qualitative study measuring hospitalist workload, multiple measures, including those quantifying work demands and the association of those demands with outcomes, were considered relevant for m...
The purpose of the study was to validate WORKLINE, a NICU specific clinician workload model and to evaluate the feasibility of integrating WORKLINE into our EHR....
This was a prospective, observational study of the workload of 42 APPs and physicians in a large academic medical center NICU over a 6-month period. We used regression models with robust clustered sta...
We found significant correlations between WORKLINE and NASA-TLX scores. APP caseload was not significantly associated with WORKLINE scores. We successfully integrated the WORKLINE model into our EHR t...
WORKLINE provides an objective method to quantify the workload of clinicians in the NICU, and for APPs, performed better than caseload numbers to reflect workload. Integrating the WORKLINE model into ...
Live captioning is a challenging task that requires intense concentration to convert audio to text in real-time. Despite the importance of live captioning for accessibility, little is known about the ...
Clinicians that care for hospitalised patients face unprecedented work conditions with exposure to highly infectious disease, exceedingly high patient numbers, and unpredictable work demands, all of w...
We will follow the methodology outlined by Joanna Briggs Institute and Arksey and O'Malley to conduct a comprehensive search of major electronic databases including Ovid Medline (PubMed), Embase (Emba...
This review does not require ethics approval though all included studies will be screened to ensure appropriate approval. The synthesis of this literature will provide a better understanding of the cu...
to analyze midwives' employment situation of midwives and detect their workload measurement needs....
a mixed methodology (quantitative and qualitative), observational, descriptive and cross-sectional study. Two phases were carried out. The first methodological phase consisted of conducting semi-struc...
90.3% of midwives have work overload, since for 80.6% the midwife-pregnant mother ratio is not well established, since the mean execution time of a Nursing Intervention Classification (NIC) interventi...
the need to generate an instrument that considers the diversity of Nursing Intervention Classification (NIC) interventions that develop within the labor room is ratified....
Tillman et al. (2017) used evidence-accumulation modeling to ascertain the effects of a conversation (either with a passenger or on a hands-free cell phone) on a drivers' mental workload. They found t...
This integrative review will examine the current literature assessing student workload, outcomes of increased workload and cognitive load, and approaches to evaluate and reduce student workload. Recom...
Literature supports that perceptions of heavy workload can influence students' approach to learning and lead to the adoption of surface learning rather than a deep approach that involves higher-order ...
Cognitive overload is multifactorial and complicated, given the increased standards of professional education accreditation and licensure requirements. As the Academy deliberately considers methods to...
Research has not yet quantified the effects of workload or duty hours on the accuracy of radiologists. With the exception of a brief reduction in imaging studies during the 2020 peak of the COVID-19 p...
In aviation, any detail can have massive consequences. Among the potential sources of failure, human error is still the most troublesome to handle. Therefore, research concerning the management of men...
