Background: The primary aim of our systematic scoping review was to explore the factors influencing team function and performance across various industries and discuss findings in the context of the high-performance sport support team setting. These outcomes may also be used to inform future research into high-performance teamwork in sport.
Methods: A systematic scoping review of literature published in English since 2000 reporting team-based performance outcomes and included a performance metric that was 'team outcome based' was conducted using search of the Academic Search Ultimate, Medline, Business Source Ultimate, APA PsycInfo, CINAHL, SPORTDiscus, and Military database (ProQuest) using the terms: 'team', 'function' OR 'dysfunction', 'Perform*' OR 'outcome'.
Results: Application of the search strategy identified a total of 11,735 articles for title and abstract review. Seventy-three articles were selected for full-text assessment with the aim to extract data for either quantitative or qualitative analysis. Forty-six of the 73 articles met our inclusion criteria; 27 articles were excluded as they did not report a performance metric. Eleven studies explored leadership roles and styles on team performance, three studies associated performance feedback to team performance, and 12 studies explored the relationship between supportive behaviour and performance. Team orientation and adaptability as key figures of team performance outcomes were explored in 20 studies.
Conclusions: Our findings identified 4 key variables that were associated with team function and performance across a variety of industries; (i) leadership styles, (ii) supportive team behaviour, (iii) communication, and (iv) performance feedback. High-performance teams wishing to improve performance should examine these factors within their team and its environment. It is widely acknowledged that the dynamics of team function is important for outcomes in high-performance sport, yet there is little evidence to provide guidance. This inequality between real-world need and the available evidence should be addressed in future research.
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http://dx.doi.org/10.1186/s40798-021-00406-7 | DOI Listing |
Introduction: The complexity of healthcare is dynamic and requires educators to evaluate how to prepare pediatric nurse practitioners (PNPs). The research team sought to evaluate procedures currently being performed by primary and acute care PNPs in clinical practice and determine how this aligns with the educational preparation recommended for certification.
Method: A cross-sectional survey of primary and acute care PNPs were evaluated through an online survey.
Sensors (Basel)
December 2024
Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea.
Several approaches have been developed to generate synthetic object points using real LiDAR point cloud data for advanced driver-assistance system (ADAS) applications. The synthetic object points generated from a scene (both the near and distant objects) are essential for several ADAS tasks. However, generating points from distant objects using sparse LiDAR data with precision is still a challenging task.
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December 2024
School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
Coronary artery stenosis detection remains a challenging task due to the complex vascular structure, poor quality of imaging pictures, poor vessel contouring caused by breathing artifacts and stenotic lesions that often appear in a small region of the image. In order to improve the accuracy and efficiency of detection, a new deep-learning technique based on a coronary artery stenosis detection framework (DCA-YOLOv8) is proposed in this paper. The framework consists of a histogram equalization and canny edge detection preprocessing (HEC) enhancement module, a double coordinate attention (DCA) feature extraction module and an output module that combines a newly designed loss function, named adaptive inner-CIoU (AICI).
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December 2024
Department of Computer Engineering, Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia.
In the field of muscle fatigue models (MFMs), the prior research has demonstrated success in fitting data in specific contexts, but it falls short in addressing the diverse efforts and rapid changes in exertion typical of soccer matches. This study builds upon the existing model, aiming to enhance its applicability and robustness to dynamic demand shifts. The objective is to encapsulate the complexities of soccer dynamics with a streamlined set of parameters.
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December 2024
Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, 40127 Bologna, Italy.
Temporal parameters are crucial for understanding running performance, especially in elite sports environments. Traditional measurement methods are often labor-intensive and not suitable for field conditions. This study seeks to provide greater clarity in parameter estimation using a single device by comparing it to the gold standard.
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