Aim: To determine whether task deconstruction is superior to full-task training for the acquisition of transurethral resection skills on a transurethral resection of prostate (TURP) virtual reality trainer previously validated for use in residency training.
Methods: Eighteen first- and second-year medical students with no previous exposure to TURP in the operating room participated in the study. The subjects were randomized to two treatment arms: full-task TURP training versus task deconstruction training. A 5-minute full-task exercise was done as a pretest and posttest in both groups. Training time was held constant at 45 minutes for both groups. The first group practiced the full-task resection for 45 minutes, while the second group performed four deconstructed tasks for a total of 45 minutes. This comprised of cystoscopy and identification of anatomy, coagulation, cutting, and complete resection exercises. Statistical analysis was performed by the Mann-Whitney test.
Results: There was a significant difference in improvement comparing the pretest and posttest performance between the two groups, favoring task deconstruction over full-task training in the amount of tissue resected and grams resected/time on cutting pedal. There was no significant difference noted in number of bleeders coagulated, fluid consumed/gram resected, or bleeders coagulated/time on coagulation pedal. There was no difference in perforation rate between two groups. The mean approval rating of the curricular experience on the simulator was 4.0/5.0 in the task deconstruction group and 3.1/5.0 in the case of the full-task training group.
Conclusion: For the acquisition of transurethral resection skills, task deconstruction is superior to full-task training alone, in training novices on the virtual reality TURP trainer. Such a study provides more validity evidence to the unique value of simulation in the urology minimally invasive curriculum.
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http://dx.doi.org/10.1089/end.2008.0531 | DOI Listing |
Neuroimage
December 2024
Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. Electronic address:
Using a combination of fMRI, EEG, and phenomenology ratings, we examined the neurophenomenology of advanced concentrative absorption meditation, namely jhanas (ACAM-J), in a practitioner with over 23,000 h of meditation practice. Our study shows that ACAM-J states induce reliable changes in conscious experience and that these experiences are related to neural activity. Using resting-state fMRI functional connectivity, we found that ACAM-J is associated with decreased within-network modularity, increased global functional connectivity (GFC), and desegregation of the default mode and visual networks.
View Article and Find Full Text PDFJ Thromb Haemost
November 2024
Medicarte IPS, National Comprehensive Hemophilia Treatment Center, Medellin, Colombia.
Recently, the International Society on Thrombosis and Haemostasis (ISTH) Hemophilia Guidelines were published in this journal. The authors of these guidelines should be commended for a herculean task that took years to complete, and while this is no doubt a welcome addition to the literature, it does leave many questions for the clinician. This is primarily because 11 of the 13 recommendations are conditional, essentially meaning "that clinicians and patients need to consider individual preferences as well as the specific circumstances in which the decision is being made for implementation of the recommendation.
View Article and Find Full Text PDFPLoS One
October 2024
Joint BioEnergy Institute, Emeryville, CA, United States of America.
Neural Comput
October 2024
University of Birmingham, School of Psychology and Computer Science, Birmingham B15 2TT, U.K.
Active inference is a theory of perception, learning, and decision making that can be applied to neuroscience, robotics, psychology, and machine learning. Recently, intensive research has been taking place to scale up this framework using Monte Carlo tree search and deep learning. The goal of this activity is to solve more complicated tasks using deep active inference.
View Article and Find Full Text PDFNat Commun
July 2024
Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China.
Cleavage of carbon-carbon bonds remains a challenging task in organic synthesis. Traditional methods for splitting C=C bonds into two halves typically involve non-redox (metathesis) or oxidative (ozonolysis) mechanisms, limiting their synthetic potential. Disproportionative deconstruction of alkenes, which yields one reduced and one oxidized fragment, remains an unexplored area.
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