Objective: The objective of this study was to explore and better characterize the factors affecting confidence during surgical training.
Design: This was a qualitative research study in which we conducted semistructured interviews with surgical residents to explore factors affecting their confidence.
Setting: This study was conducted at the University of Alberta Hospital, a tertiary care center located in Edmonton, Alberta, Canada.
Participants: Residents from the University of Alberta General Surgery residency program were invited to participate from each postgraduate year (PGY) 2, 3, and 4 for a total of 7 participants (3 PGY-2, 3 PGY-3, and 1 PGY-4; 3 male, and 4 female). We excluded residents who had completed or were currently enrolled in dedicated research years.
Results: Resident confidence was found to be influenced by internal and external factors operating before, during, and after a particular surgical task. Internal factors incorporated personal experiences (including operative experience), personal expectations, self-perception, and individual skill development. External factors involved feedback, patient outcomes, relationships with staff, and working within a supportive environment. Interestingly, residents discussed external social factors more than case volume, technical skills, or underlying knowledge. Residents did not feel that their personal lives (e.g. marital status or having children) directly affected their surgical confidence. Regardless of the factor itself, positive experiences helped build and maintain confidence by providing feelings of reassurance, encouragement, comfort, and acceptance.
Conclusions: Surgical confidence is influenced by a range of internal and external factors. Understanding these factors can help educators improve learning experiences for residents and accelerate their progress towards being confident, independent surgeons.
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http://dx.doi.org/10.1016/j.jsurg.2018.10.016 | DOI Listing |
J Affect Disord
January 2025
Department of Psychiatry and Psychotherapy, University of Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), University of Marburg, Germany.
Background: Major depressive disorder (MDD) comes along with an increased risk of recurrence and poor course of illness. Machine learning has recently shown promise in the prediction of mental illness, yet models aiming to predict MDD course are still rare and do not quantify the predictive value of established MDD recurrence risk factors.
Methods: We analyzed N = 571 MDD patients from the Marburg-Münster Affective Disorder Cohort Study (MACS).
Epilepsia
January 2025
Department of Neurosciences, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada.
Objective: Tuberous sclerosis complex (TSC) is a monogenetic disorder associated with sustained mechanistic target of rapamycin (mTOR) activation, leading to heterogeneous clinical manifestations. Epilepsy and renal angiomyolipoma are the most important causes of morbidity in adult people with TSC (pwTSC). mTOR is a key player in inflammation, which in turn could influence TSC-related clinical manifestations.
View Article and Find Full Text PDFACS ES T Water
January 2025
Department of Statistics & Data Science, Dietrich College of Humanities and Social Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.
Since the start of the coronavirus-19 pandemic, the use of wastewater-based epidemiology (WBE) for disease surveillance has increased throughout the world. Because wastewater measurements are affected by external factors, processing WBE data typically includes a normalization step in order to adjust wastewater measurements (e.g.
View Article and Find Full Text PDFTransl Cancer Res
December 2024
Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Background: V-raf murine sarcoma viral oncogene homolog B1 (BRAF) inhibitor (BRAFi) therapy resistance affects approximately 15% of cancer patients, leading to disease recurrence and poor prognosis. The aim of the study was to develop a machine-learning based method to identify patients who are at high-risk of BRAFi resistance and potential biomarker.
Methods: From Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) databases, we collected RNA sequencing and half maximal inhibitory concentration (IC) data from 235 pan-cancer cell lines and then identified 37 significant differential expression genes associated with BRAFi resistance.
Transl Cancer Res
December 2024
Department of Urology, Affiliated Hospital of Chifeng University, Chifeng, China.
Background: Bladder urothelial carcinoma (BLCA) is globally recognized as a prevalent malignancy. Its treatment remains challenging due to the extensive morbidity, high mortality rates, and compromised quality of life from postoperative complications and the lack of specific molecular targets. Our aim was to establish a prognostic model to evaluate the prognostic significance, assess immunotherapy responses, and determine drug susceptibility in patients with BLCA.
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