Concurrent training

INTRODUCTION: Assessing the internal dynamics of organizations has been shown to provide information that can help planners and policymakers improve service delivery. A good organizational climate, which in this study incorporates mission clarity, team cohesion, staff autonomy, communication, levels of stress, and openness to change has been shown to be of particular importance. Still, there is a dearth of evidence in this area, and while relationships between organizational factors have been identified, little is known about the mechanisms that might underpin these relationships, and there is little understanding of how to address deficits once they are identified...

BACKGROUND: Chronic pain affects approximately 8 million Canadians (~20%), impacting their physical and mental health while burdening the health care system with costs of upwards of US $60 billion a year. Indeed, patients are often trialed on numerous medications over several years without reductions to their symptoms. Therefore, there is an urgent need to identify new therapies for chronic pain to improve patients' quality of life, increase the availability of treatment options, and reduce the burden on the health care system...

BACKGROUND: There is a growing, global awareness and recognition of the important, interdependent relationships between our natural world and human health. Several contemporary health organizations have placed calls to action and emphasize an urgent need for collaboration and interdisciplinary research, education, and clinical work to address the increasing degradation of our planetary and human health. With more research dedicated to nature's health impacts, health professions schools would benefit by including such training in their programs while also cultivating a comprehensive mind-body health perspective to support both the health of student practitioners and their future patients...

Cognitive flexibility increases when switch demands increase. In task switching experiments, repeated pairing of flexibility-demanding situations with specific contexts leads subjects to become more prepared to adapt to changing task demands in those contexts. One form of such upregulated cognitive flexibility has been demonstrated with a list-wide switch probability (LWSP) effect, where switch costs are smaller in lists with frequent switches than in lists with rare switches. According to a recent proposal, the LWSP effect is supported by a concurrent activation mechanism whereby both task rules are kept available simultaneously in working memory...

New transfer coefficient (TC) values were derived for vineyard workers handling treated grapevines during harvesting and crop maintenance activities. Re-entry exposure and dislodgeable foliar residue (DFR) studies were performed in Europe, covering hand harvesting, pruning/training, pruning/tying and pruning /shoot lifting. Foliar applications of fungicides (iprovalicarb, dimethomorph, dithianon, pyrimethanil and fenbuconazole) were made and 73 workers at 16 sites were monitored over one working day. Exposure was measured on inner and outer dosimeters, face/neck wipes and hand washes...

BACKGROUND CONTEXT: Traditional 3D motion analysis typically considers the spine as a rigid entity. Nevertheless, previous single-joint models have proven inadequate in evaluating the movement across different spinal segments in patients with idiopathic scoliosis (IS). Scoliosis significantly impairs movement functions, especially during activities such as ascending and descending stairs. There is a lack of research on the patterns of stair movement specifically for patients with IS. PURPOSE: This study aims to investigate the trunk kinematics in college students with IS during stair ascent and descent tasks...

Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0...

Opioid use disorder is known to be under-coded as a diagnosis, yet problematic opioid use can be documented in clinical notes, which are included in electronic health records. We sought to identify problematic opioid use from a full range of clinical notes and compare the demographic and clinical characteristics of patients identified as having problematic opioid use exclusively in clinical notes to patients documented through ICD opioid use disorder diagnostic codes. We developed and applied a natural language processing (NLP) tool that combines rule-based pattern analysis and a trained support vector machine to the clinical notes of a patient cohort (n = 222,371) from two Veteran Affairs service regions to identify patients with problematic opioid use...

BACKGROUND: The worldwide COVID-19 pandemic has initiated a change in medical education and the development of new teaching concepts has become inevitable to maintain adequate training. OBJECTIVE: This pilot study aims to compare teledidactic teaching with traditional face-to-face teaching for abdominal, thoracic, and thyroid ultrasound. DESIGN: Concurrently, a teledidactic and a face-to-face ultrasound course were held. The students completed seven 90-min modules using mobile ultrasound probes (Butterfly IQ)...

Children with autism often display differences in functional and symbolic play and may experience barriers to social inclusion with peers in preschool settings. Therefore, interventions supporting social play between children with autism and their peers that can be feasibly implemented by teachers in inclusive settings are needed. A teacher-implemented peer-mediated Stay Play Talk (SPT; Goldstein et al. in Top Lang Disord 27(2):182-199, 2007) intervention package targeting the type of play children with autism engage in with peers was implemented using a concurrent multiple baseline design across four participant/peer dyads...

Duty hour regulations (DHRs) were enforced in 2017 in Korea to prevent the detrimental effects of excessively prolonged working hours among medical residents. We investigated the adoption of and implications of the new DHRs among medical residents and faculty members. Semi-structured interviews were conducted with 15 medical residents and 9 faculty members across general surgery, internal medicine, obstetrics-gynecology, and pediatrics departments at Chonnam National University Hospital. Based on the constructivist grounded theory, we developed themes from the data by concurrent coding and analysis with theoretical sampling until data saturation...

Practice on perceptual tasks can lead to long-lasting, stimulus-specific improvements. Rapid stimulus-specific learning, assessed 24 hours after practice, has been found with just 105 practice trials in a face identification task. However, a much longer time course for stimulus-specific learning has been found in other tasks. Here, we examined 1) whether rapid stimulus-specific learning occurs for unfamiliar, non-face stimuli in a texture identification task; 2) the effects of varying practice across a range from just 21 trials up to 840 trials; and 3) if rapid, stimulus-specific learning persists over a 1-week, as well as a 1-day, interval...

Osteophytes are routinely removed during total knee arthroplasty, yet the preoperative planning currently relies on preoperative computed tomography (CT) scans of the patient's osteoarthritic knee, typically including osteophytic features. This complicates the surgeon's ability to anticipate the exact biomechanical effects of osteophytes and the consequences of their removal before the operation. The aim of this study was to investigate the effect of osteophytes on ligament strains and kinematics, and ascertain whether the osteophyte volume and location determine the extent of this effect...

BACKGROUND: Self-efficacy plays an important role in enhancing the teaching capabilities of attending physicians (APs). The clinical ladder (CL) is an educational approach developed in the field of nursing education that increases difficulty in an incremental manner. However, no previous study has confirmed the effectiveness of CL in medical education. Therefore, this study aimed to examine the effect of clinical clerkship integrated with clinical ladder (CC-CL) on the self-efficacy of APs...

AIM: The research project focuses on the creation and assessment of an innovative computer vision system designed to identify dental irregularities in individuals undergoing orthodontic treatment. MATERIALS AND METHODS: To establish the computer vision system, a comprehensive dataset of dental images was collected, encompassing various orthodontic cases. The system's algorithm was trained to recognize patterns indicative of common dental anomalies, such as malocclusions, spacing issues, and misalignments...

Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials. Such physics-based models, while extensively deployed for predicting the dynamics and properties of nanoscale systems over the past two decades, tend to perform poorly in predicting nanoscale potential energy surfaces (PESs) when compared to high-fidelity first-principles calculations...

Traditional approaches to the intelligent fault diagnosis of rolling bearings have predominantly relied on manual expertise for feature extraction, a practice that compromises robustness. In addition, the existing convolutional neural network (CNN) is characterized by an overabundance of parameters and a substantial requirement for training samples. To address these limitations, this study introduces a novel fault diagnosis algorithm for rolling bearings, integrating a one-dimensional convolutional neural network (1DCNN) with a support vector machine (SVM) to form an enhanced 1DCNN-SVM model...

INTRODUCTION: Collagen peptide supplementation in conjunction with exercise has been shown to improve structural and functional adaptations of both muscles and the extracellular matrix. This study aimed to explore whether specific collagen peptide (SCP) supplementation combined with a concurrent training intervention can improve muscular stress after exercise-induced muscle damage, verified by reliable blood markers. METHODS: 55 sedentary to moderately active males participating in a concurrent training (CT) intervention (3x/week) for 12 weeks were administered either 15 g of SCP or placebo (PLA) daily...

OBJECTIVES: To analyse monthly changes in public access defibrillation (PAD) incidence and outcomes of out-of-hospital cardiac arrest (OHCA) during the 2020-2021 COVID-19 pandemic compared with those during the 2016-2019 prepandemic period with consideration of pandemic-related movement restriction. DESIGN: Retrospective cohort study. SETTING: An extended database was created by combining and reconciling the nationwide Utstein-style OHCA and the emergency medical service (EMS) transportation databases in Japan...

Data-driven chemistry has garnered much interest concurrent with improvements in hardware and the development of new machine learning models. However, obtaining sufficiently large, accurate datasets of a desired chemical outcome for data-driven chemistry remains a challenge. The community has made significant efforts to democratize and curate available information for more facile machine learning applications, but the limiting factor is usually the laborious nature of generating large-scale data. Transfer learning has been noted in certain applications to alleviate some of the data burden, but this protocol is typically carried out on a case-by-case basis, with the transfer learning task expertly chosen to fit the finetuning...