Airport security screening is a visual inspection task comprising search and decision. Problem solving is used to support decision making. However, it is not well understood. This study investigated how airport security screeners employ problem solving during x-ray screening, and how strategies change with experience. Thirty-nine professional security screeners were observed performing x-ray screening in the field at an Australian International Airport. Video and eye-tracking data were collected and analysed to explore activity phases and problem-solving strategies. Less-experienced screeners performed more problem solving and preferred problem-solving strategies that rely on visual examination without decision support or that defer decision making, compared to more-experienced screeners, who performed efficient and independent strategies. Findings also show that screeners need more time to develop problem-solving skills than visual scanning skills. Screeners would benefit from problem-solving support tools and intensified training and mentorship within the first six months of experience to advance problem-solving competencies.
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http://dx.doi.org/10.1016/j.apergo.2024.104273 | DOI Listing |
Appl Ergon
January 2025
Department of Learning Informatics Management and Ethics, Karolinska Institute, Stockholm, Sweden; Paediatric Emergency Department, Karolinska University Hospital, Stockholm, Sweden; Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden.
Emergency departments accommodate high-acuity patients in complex, high risk environments with high variability in patient flow and resource availability. Strategies for enabling adaptive capacity are necessary for adjusting activities in response to the variability of overall workload and individual patient acuity. This study aims to identify and describe the strategies used by lead-nurses to inform recommendations for training and education.
View Article and Find Full Text PDFJMIR Form Res
January 2025
The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Background: Singapore's large aging population poses significant challenges for the health care system in managing cognitive decline, underscoring the importance of identifying and implementing effective interventions. Cognitive training delivered remotely as a digital therapeutic (DTx) may serve as a scalable and accessible approach to overcoming these challenges. While previous studies indicate the potential of cognitive training as a promising solution for managing cognitive decline, understanding the attitudes and experiences of older adults toward using such DTx platforms remains relatively unexplored.
View Article and Find Full Text PDFJ Eval Clin Pract
February 2025
Department of Medical Services and Techniques, First and Emergency Aid Programme, Vocational School of Health Services, Akdeniz Unıversıty, Antalya, Turkey.
Background: Problem-solving skills are some of the leading strategies for dynamism in the content and quality of nursing care.
Aim: The present study is aimed at determining nursing students' problem-solving, solution-focused thinking, and emotional intelligence levels and investigating the relationship between their problem-solving skills and these variables.
Methods: The study comprised 305 nursing students in Turkey.
BMJ Open Qual
January 2025
Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Background: Attending to patient-reported outcomes (PROs) using data visualisation dashboards could enhance shared decision-making (SDM) and care delivery for serious chronic illnesses. However, few studies have evaluated real-world strategies and resulting implementation outcomes of PRO dashboards.
Method: From June 2020 to January 2022, we implemented an electronic health record (EHR)-integrated PRO dashboard for advanced cancer and chronic kidney disease.
Sci Rep
January 2025
School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China.
Multi-objective and multi-stage decision-making problems require balancing multiple objectives at each stage and making optimal decision in multi-dimensional control variables, where the commonly used intelligent optimization algorithms suffer from low solving efficiency. To this end, this paper proposes an efficient algorithm named non-dominated sorting dynamic programming (NSDP), which incorporates non-dominated sorting into the traditional dynamic programming method. To improve the solving efficiency and solution diversity, two fast non-dominated sorting methods and a dynamic-crowding-distance based elitism strategy are integrated into the NSDP algorithm.
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