Objective: To evaluate construct and content validity as well as learners' perceptions of CathSim, a virtual reality intravenous (IV) insertion simulator.
Methods: A prospective cohort study design was employed to determine construct validity, and a participant survey was used to ascertain content validity as well as user perceptions of CathSim. Forty-one attendings, residents, and medical students in emergency medicine and anesthesia attempted five simulated IV insertions on CathSim. Subject performances were scored by the computer, and subject perceptions of the simulator were measured using a Likert scale questionnaire (1 = worst rating; 5 = best rating). The subjects were divided into three groups (novices, intermediates, and experts) based on previous IV experience. To determine construct validity, performances of the three groups were compared using one-way analysis of variance (ANOVA). To determine content validity, the experts' perceptions of the simulator's realism and usefulness were assessed. Study subjects' perceptions of the simulator's ease of use and overall appeal were analyzed.
Results: The experts scored better than the others in five of nine scoring parameters (p < 0.05). The experts rated the realism of CathSim's four major simulation components at 3.85, 3.46, 3.69, and 3.46; the overall realism of CathSim at 2.93; and its utility for medical student training at 4.57. The simulator's ease of use was rated at 2.34 by all subjects. Novices reported a score of 4.59 regarding their likelihood to use the simulator.
Conclusions: CathSim demonstrated construct validity in five of nine internal scoring parameters and was judged to be adequately realistic and highly useful for medical student training. Despite being difficult to learn to use, it remained appealing to the users, especially the novices.
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http://dx.doi.org/10.1111/j.1553-2712.2002.tb01594.x | DOI Listing |
Pharmazie
December 2024
Centre of Excellence for Pharmaceutical Sciences (Pharmacen™), North-West University, Potchefstroom, Republic of South Africa.
The COVID-19 pandemic caused global pandemonium, and due to an unprecedented global response, the popularity and use of (veterinary) ivermectin, amongst many other conceivable 'treatments', experienced a meteoric rise. Ivermectin is a macrocyclic lactone compound belonging to the avermectin drug class and is a registered medicine in many countries, although the most common use is as veterinary medicine. In this study, a fast HPLC method was developed and validated for the quantification of ivermectin in veterinary products that were used off-label by a substantial number of people during COVID-19.
View Article and Find Full Text PDFInt Urol Nephrol
January 2025
Department of Urology and Urosurgery, Medical Faculty Mannheim, University Medical Centre Mannheim (UMM), University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Baden-Württemberg, Germany.
Purpose: To identify prognostic factors for overall survival (OS) and develop a prognostic score in patients receiving docetaxel in metastatic castration-resistant prostate cancer (mCRPC).
Methods: Retrospective analysis was conducted on mCRPC patients treated with docetaxel at a German tertiary center between March 2010 and November 2023. Prognostic clinical and laboratory factors were analyzed using uni- and multivariable logistic regression.
Behav Res Methods
January 2025
Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, 999078, Macau, China.
The autobiographical implicit association test (aIAT) is an approach of memory detection that can be used to identify true autobiographical memories. This study incorporates mouse-tracking (MT) into aIAT, which offers a more robust technique of memory detection. Participants were assigned to mock crime and then performed the aIAT with MT.
View Article and Find Full Text PDFJ Voice
January 2025
Department of Otorhinolaryngology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China. Electronic address:
Objective: The Mandarin Chinese version of the Vocal Performance Questionnaire (VPQ-CM) for evaluating vocal performance.
Methods: A total of 120 participants with vocal disorders and 120 healthy participants completed this study. Investigators translated the original VPQ into the VPQ-CM, and participants completed the questionnaire fill it.
J Dent
January 2025
Department of Oral & Maxillofacial Radiology, Peking University School & Hospital of Stomatology, Beijing 100081, China; National Center for Stomatology & National Clinical Research Center for Oral Diseases, Beijing 100081, China; National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing 100081, China; Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China. Electronic address:
Objectives: In this study, artificial intelligence techniques were used to achieve automated diagnosis and classification of temporomandibular joint (TMJ) degenerative joint disease (DJD) on cone beam computed tomography (CBCT) images.
Methods: An AI model utilizing the YOLOv10 algorithm was trained, validated and tested on 7357 annotated and corrected oblique sagittal TMJ images (3010 images of normal condyles and 4347 images of condyles with DJD) from 1018 patients who visited Peking University School and Hospital of Stomatology for temporomandibular disorders and underwent TMJ CBCT examinations. This model could identify DJD as well as the radiographic signs of DJD, namely, erosion, osteophytes, sclerosis and subchondral cysts.
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