{"title":"Choosing the right patient transfer assistive device: Application of confidence ellipse quadrant analysis for decision-making","authors":"","doi":"10.1016/j.ergon.2024.103628","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Adopting patient transfer assistive devices in healthcare is challenging, and poor decision-making can lead to low adoption. This study aims to demonstrate a technique of the decision-making process of selection of patient transfer assistive devices based on work-related musculoskeletal disorders (WMSDs) risk, nurses’ instantaneous emotions, and perceptions.</p></div><div><h3>Methods</h3><p>A case study based on four different patient transfer assistive devices is used to demonstrate this technique. Seven nurses were recruited. Three confidence ellipse graphs were plotted: the intention of the use scores vs (1) National Aeronautics and Space Administration Task Load Index (NASA-TLX) overall scores, (2) Rapid Entire Body Assessment (REBA) scores, and (3) valence scores of the nurses.</p></div><div><h3>Results</h3><p>When a large ellipse is represented by an intervention, it suggests poor agreement among users regarding the intervention, whereas a small ellipse indicates a strong consensus. The upper left quadrant, where the intention of use is high and REBA, NASA-TLX, and valence scores are low, is the most optimal location for selecting a device. In the case study, the motorised transfer was identified as the best device as the datasets were located there.</p></div><div><h3>Conclusions</h3><p>Using this tool allows for the objective selection of patient transfer assistive devices, which can then be communicated to all stakeholders involved. Additionally, the tool helps to identify areas for improvement within each intervention.</p></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Industrial Ergonomics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169814124000842","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Adopting patient transfer assistive devices in healthcare is challenging, and poor decision-making can lead to low adoption. This study aims to demonstrate a technique of the decision-making process of selection of patient transfer assistive devices based on work-related musculoskeletal disorders (WMSDs) risk, nurses’ instantaneous emotions, and perceptions.
Methods
A case study based on four different patient transfer assistive devices is used to demonstrate this technique. Seven nurses were recruited. Three confidence ellipse graphs were plotted: the intention of the use scores vs (1) National Aeronautics and Space Administration Task Load Index (NASA-TLX) overall scores, (2) Rapid Entire Body Assessment (REBA) scores, and (3) valence scores of the nurses.
Results
When a large ellipse is represented by an intervention, it suggests poor agreement among users regarding the intervention, whereas a small ellipse indicates a strong consensus. The upper left quadrant, where the intention of use is high and REBA, NASA-TLX, and valence scores are low, is the most optimal location for selecting a device. In the case study, the motorised transfer was identified as the best device as the datasets were located there.
Conclusions
Using this tool allows for the objective selection of patient transfer assistive devices, which can then be communicated to all stakeholders involved. Additionally, the tool helps to identify areas for improvement within each intervention.
期刊介绍:
The journal publishes original contributions that add to our understanding of the role of humans in today systems and the interactions thereof with various system components. The journal typically covers the following areas: industrial and occupational ergonomics, design of systems, tools and equipment, human performance measurement and modeling, human productivity, humans in technologically complex systems, and safety. The focus of the articles includes basic theoretical advances, applications, case studies, new methodologies and procedures; and empirical studies.