Uncrewed Aerial Systems (UAS) show promise in urban air transport, package delivery, and emergency services. UAS efficiency can be significantly improved by having multiple operators () managing a greater number of vehicles (), or the architecture of operation. The current study investigates how workload affects operators' task-allocation decision-making and the potential mediating effects of two crucial human factors, trust and self-confidence. In the context of a simulated UAS package-delivery task under the architecture, two groups of participants with different levels of expertise in UAS operation will be recruited: UAS pilots and university students. Each participant will watch two sets of videos with different work-load manipulations and report their preferred task-allocation strategy for various subtasks. Measures of perceived workload, trust, and self-confidence will be conducted after each video session. Findings will inform optimizing task-allocation designs for UAS missions, considering operators' decision-making needs and expertise disparities.
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http://dx.doi.org/10.1177/10711813241274652 | DOI Listing |
The Problem: People use social media platforms to chat, search, and share information, express their opinions, and connect with others. But these platforms also facilitate the posting of divisive, harmful, and hateful messages, targeting groups and individuals, based on their race, religion, gender, sexual orientation, or political views. Hate content is not only a problem on the Internet, but also on traditional media, especially in places where the Internet is not widely available or in rural areas.
View Article and Find Full Text PDFActas Esp Psiquiatr
January 2025
Servicio de Promoción y Educación para la Salud, Dirección General de Salud Pública y Adicciones, Consejería de Salud de la Región de Murcia, 30008 Murcia, Spain.
Background: The COVID-19 pandemic was a global public health crisis with an unparalleled impact worldwide, presenting a significant challenge for both physical and mental health. The main objective of this study was to analyze the risk of depression during the COVID-19 pandemic and how this was affected by sociodemographic factors, pandemic fatigue, risk perception, trust in institutions, and perceived self-efficacy.
Methods: A cross-sectional study was conducted in the Region of Murcia through two online surveys completed by 1000 people in June 2021 (Round 1) and March 2022 (Round 2).
Int Wound J
January 2025
Directorate of Nursing, Imperial College Healthcare NHS Trust/Imperial College London Education Centre, Charing Cross Hospital, London, UK.
Guidance for venous leg ulceration (VLU) recommends compression therapy and early referral for specialist vascular assessment within two weeks. Few patients receive timely assessment and referral. Reasons for this are unclear.
View Article and Find Full Text PDFBr J Dermatol
January 2025
Department of Occupational and Environmental Diseases, University Hospital of Centre of Paris, Hotel-Dieu Hospital, and Department of Dermatology, University Hospital of Centre of Paris, Cochin Hospital, AP-HP, Paris, France AP-HP, Paris, France.
Background: The lack of attention to Chronic Hand Eczema (CHE) and the lack of a specific International Classification of Diseases code for CHE may have limited the assessment of CHE prevalence. To date, prevalence estimates have primarily been derived from (partly small) single-country studies.
Objectives: To estimate the annual prevalence of self-reported physician-diagnosed CHE across socio-demographic characteristics among adults in Canada, France, Germany, Italy, Spain, and the United Kingdom (UK).
Behav Anal Pract
December 2024
Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI USA.
Unlabelled: Collecting data and logging behaviors of clients who have autism spectrum disorder (ASD) during applied behavior analysis (ABA) therapy sessions can be challenging in real time, especially when the behaviors require a rapid response, like self-injury or aggression. Little information is available about the automation of data collection in ABA therapy, such as through machine learning (ML). Our survey of ABA therapists nationally revealed mixed levels of familiarity with ML and generally neutral responses to statements endorsing the benefits of ML.
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