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Objective: In current objective structured clinical examinations (OSCEs), simulated encounters lacking realism reduce authenticity of assessment as students can take the OSCEs with a search-and-scan approach and trained empathy. Accordingly, patient-centeredness, the fundamental goal of OSCE, is not well assessed. This study evaluated the effect of a change in the OSCE scenario and checklist with respect to detecting students' patient-centeredness.
Methods: A scenario script for valid representation of a real clinical encounter was developed and defined as authenticated scenario. The OSCE scores and the measure of patient-centered communication (MPCC) scores of 79 medical students were compared between the two OSCE stations, one using the traditional scenario and another using the authenticated scenario.
Results: The MPCC total score was higher in the OSCE station using the authenticated scenario than that of the traditional scenario (p < 0.001). For the OSCE scores, the patient satisfaction score and the patient-physician interaction score were higher in the station using the authenticated scenario than the traditional one (p < 0.001).
Conclusion: The OSCE station using the authenticated scenario better detected medical student level of patient-centeredness.
Practice Implications: Strengthening the authenticity of the OSCE scenario is critical for detecting the medical students' levels of patient-centeredness.
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http://dx.doi.org/10.1016/j.pec.2020.10.016 | DOI Listing |
PLoS One
September 2025
Graduate School of Information, Yonsei University, Seoul, South Korea.
With the introduction of Advanced Driver Assistance Systems (ADAS), modern vehicles are equipped with numerous sensors, significantly increasing data communication within the in-vehicle network. However, the limited bandwidth of the Controller Area Network (CAN) poses challenges for high-speed sensor data transmission. To address this, automotive ethernet is emerging as a replacement for CAN, enabling the efficient transmission of large volumes of data, such as from cameras and LiDAR.
View Article and Find Full Text PDFJ Forensic Sci
September 2025
Department of Forensic Science, Punjabi University, Patiala, Punjab, India.
Lipstick traces can be recovered from the crime scene on various substrates and linked to the lipstick worn by the suspect or victim. These samples are usually collected using the swabbing method from the lips. Sometimes, the same samples are stored in forensic laboratories for years due to a backlog of cases, which affects the samples' originality.
View Article and Find Full Text PDFData Brief
October 2025
School of Information and Communication Technology, Mongolian University of Science and Technology, Ulaanbaatar 13341, Mongolia.
Perception plays a crucial role in autonomous driving and computer vision, particularly in interpreting traffic scenes from monocular cameras. In this article, we present a comprehensive collection of traffic scene datasets organized into four distinct groups: (1) Traffic Scene Datasets, (2) Top-View Datasets - both introduced in the authors' earlier research, (3) MultiHeightView Datasets and (4) Depth Datasets. The Traffic Scene Datasets include RealStreet, which captures authentic traffic scenarios, and SynthStreet, its synthetic counterpart.
View Article and Find Full Text PDFJMIR Med Educ
August 2025
Medical Simulation Center, Shantou University Medical College, No. 22 Xinling Road, Shantou, 515041, China, 86 754-88900459.
Background: History-taking is crucial in medical training. However, current methods often lack consistent feedback and standardized evaluation and have limited access to standardized patient (SP) resources. Artificial intelligence (AI)-powered simulated patients offer a promising solution; however, challenges such as human-AI consistency, evaluation stability, and transparency remain underexplored in multicase clinical scenarios.
View Article and Find Full Text PDFSensors (Basel)
August 2025
Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.
Authentication is a critical component of digital security, and traditional methods often encounter significant vulnerabilities and limitations. This study addresses the emerging field of EEG-based authentication systems, highlighting their theoretical advancements and practical applicability. We conducted a systematic review of the existing literature, followed by an experimental evaluation to assess the feasibility, limitations, and scalability of these systems in real-world scenarios.
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