This study examines whether medical students' views of treatments for 'schizophrenia' and of patients' rights to be informed about their condition and their medication were influenced by diagnostic labeling and causal explanations and whether they differed over medical training. Three hundred and eighty-one Italian students attending their first or fifth/sixth year of medical studies read a vignette portraying someone who met diagnostic criteria for 'schizophrenia' and completed a self-report questionnaire. The study found that labeling the case as 'schizophrenia' and naming heredity among its causes were associated with confidence in psychiatrists and psychiatric drugs. Naming psychological traumas among the causes was associated with confidence in psychologists and greater acknowledgment of users' right to be informed about drugs. Compared to first year students, those at their fifth/sixth-year of studies more strongly endorsed drugs, had less confidence in psychologists and family support, and were less keen to share information on drugs with patients. These findings highlight that students' beliefs vary during training and are significantly related to diagnostic labeling and belief in a biogenetic causal model. Psychiatric curricula for medical students should include greater integration of psychological and medical aspects in clinical management of 'schizophrenia'; more information on the psychosocial causes of mental health problems.
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http://dx.doi.org/10.1016/j.psychres.2013.07.022 | DOI Listing |
NPJ Digit Med
January 2025
Neurofibromatosis Type 1 Center and Laboratory for Neurofibromatosis Type 1 Research, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Electronical Engineering, Yaşar University, Bornova, İzmir, Turkey.
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.
View Article and Find Full Text PDFPurpose: To evaluate the effect of osilodrostat and hypercortisolism control on blood pressure (BP) and glycemic control in patients with Cushing's disease.
Methods: Pooled analysis of two Phase III osilodrostat studies (LINC 3 and LINC 4), both comprising a 48-week core phase and an optional open-label extension. Changes from baseline in systolic and diastolic BP (SBP and DBP), fasting plasma glucose (FPG), and glycated hemoglobin (HbA) were evaluated during osilodrostat treatment in patients with/without hypertension or diabetes at baseline.
Methods Cell Biol
January 2025
Institut de Recherche en Cancérologie de Montpellier (IRCM), INSERM U1194, Université de Montpellier, Institut régional du Cancer de Montpellier (ICM), Montpellier, France. Electronic address:
Currently, Ovarian Cancer (OC) is the most lethal gynecological malignancy. In most patients, it progresses without clinical signs or symptoms, leading to a late diagnosis when it has already spread in the peritoneal cavity as peritoneal carcinomatosis (PC). To date, OC PC management is based on cytoreductive surgery to remove the macroscopic disease, followed by chemotherapy.
View Article and Find Full Text PDFLancet
January 2025
British Heart Foundation Centre of Research Excellence, University of Edinburgh, Edinburgh, UK; Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
Background: The Scottish Computed Tomography of the Heart (SCOT-HEART) trial demonstrated that management guided by coronary CT angiography (CCTA) improved the diagnosis, management, and outcome of patients with stable chest pain. We aimed to assess whether CCTA-guided care results in sustained long-term improvements in management and outcomes.
Methods: SCOT-HEART was an open-label, multicentre, parallel group trial for which patients were recruited from 12 outpatient cardiology chest pain clinics across Scotland.
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