This article was migrated. The article was marked as recommended. The results from a comprehensive survey of students' perceptions of their educational environment using the Dundee Ready Educational Environment Measure (DREEM) in our Medical School were compared with students' school learning scores. The subjects (n=495) were medical students beyond their first year of medical school. The students were asked to read each DREEM statement carefully and respond using a 5-point Likert-type scale, with responses ranging from strongly agree to strongly disagree. The mean total DREEM score was 113.4, and there was no significant difference among total DREEM scores for students in different school years. Sixth-year students scored significantly higher than those in the second year for the Academic Self-Perception and Social Self-Perception domains. Females had higher school learning scores and also had better total and Perception of Course Organizers DREEM scores. The DREEM score tended to be lower for those with lower school learning scores, with significant differences found for total, Academic Self-Perception and Social Self-Perception scores. This is the first study to use the DREEM score for Japanese medical students, and further prospective research is required to obtain a complete understanding of the results.
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http://dx.doi.org/10.15694/mep.2019.000013.1 | DOI Listing |
J Med Internet Res
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Learning and Capacity Development Unit, Health Emergencies Programme, World Health Organization, Geneva, Switzerland.
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View Article and Find Full Text PDFJ Chem Inf Model
January 2025
School of Information and Artificial Intelligence, Anhui Provincial Engineering Research Center for Beidou Precision Agriculture Information, Key Laboratory of Agricultural Sensors for Ministry of Agriculture and Rural Affairs, Anhui Agricultural University, Hefei, Anhui 230036, China.
Antimicrobial peptides (AMPs) are small peptides that play an important role in disease defense. As the problem of pathogen resistance caused by the misuse of antibiotics intensifies, the identification of AMPs as alternatives to antibiotics has become a hot topic. Accurately identifying AMPs using computational methods has been a key issue in the field of bioinformatics in recent years.
View Article and Find Full Text PDFJ Occup Health
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Panasonic Corporation, Department Electric Works Company/Engineering Division, Osaka, Japan.
Background: Falls are among the most prevalent workplace accidents, necessitating thorough screening for susceptibility to falls and customization of individualized fall prevention programs. The aim of this study was to develop and validate a high fall risk prediction model using machine learning (ML) and video-based first three steps in middle-aged workers.
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Esophagus
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Department of Surgery, Tohoku University Graduate School of Medicine, 1-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8574, Japan.
Background: Neoadjuvant chemotherapy is standard for advanced esophageal squamous cell carcinoma, though often ineffective. Therefore, predicting the response to chemotherapy before treatment is desirable. However, there is currently no established method for predicting response to neoadjuvant chemotherapy.
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