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The objective of this study was to compare three different surgical skills practice environments while performing a virtual laparoscopic surgical training task using a multi-degree of freedom joystick, a commercial manipulator or a training box. Nine subjects performed a virtual peg transfer task and their upper extremity muscle effort and fatigue were measured. The results demonstrated a similar muscle effort and fatigue of the upper extremity among the three training environments. Subjects with medical backgrounds used significantly higher muscle effort when they performed the training task using the joystick than the manipulator, but used similar muscle effort between the joystick and the training box. This study suggests that the multi-degree of freedom joystick could provide more options to practice virtual laparoscopic surgical training tasks with muscle effort and fatigue similar to other traditional training boxes. [ABSTRACT FROM AUTHOR]

A RESEARCH programme was undertaken over a two-year period to develop a valid and reliable set of health locus of control scales for use with young ado lescents. The scales were based upon a wider percep tion of health than existing scales. The research programme was carried out in four phases with the main survey being undertaken with 310 pupils in six Wiltshire schools. In addition to validating the scales, a great deal of information was gathered regarding young people's health beliefs. [ABSTRACT FROM PUBLISHER]

Background and Purpose: Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However, the use of artificial intelligence by trainees across different levels of experience has not been well-studied. This study investigates the impact of artificial intelligence assistance on the diagnostic accuracy for intracranial hemorrhage and large-vessel occlusion by medical students and resident trainees., Materials and Methods: This prospective study was conducted between March 2023 and October 2023. Medical students and resident trainees were asked to identify intracranial hemorrhage and large-vessel occlusion in 100 noncontrast head CTs and 100 head CTAs, respectively. One group received diagnostic aid simulating artificial intelligence for intracranial hemorrhage only ( n = 26); the other, for large-vessel occlusion only ( n = 28). Primary outcomes included accuracy, sensitivity, and specificity for intracranial hemorrhage/large-vessel occlusion detection without and with aid. Study interpretation time was a secondary outcome. Individual responses were pooled and analyzed with the t test; differences in continuous variables were assessed with ANOVA., Results: Forty-eight participants completed the study, generating 10,779 intracranial hemorrhage or large-vessel occlusion interpretations. With diagnostic aid, medical student accuracy improved 11.0 points ( P < .001) and resident trainee accuracy showed no significant change. Intracranial hemorrhage interpretation time increased with diagnostic aid for both groups ( P < .001), while large-vessel occlusion interpretation time decreased for medical students ( P < .001). Despite worse performance in the detection of the smallest-versus-largest hemorrhages at baseline, medical students were not more likely to accept a true-positive artificial intelligence result for these more difficult tasks. Both groups were considerably less accurate when disagreeing with the artificial intelligence or when supplied with an incorrect artificial intelligence result., Conclusions: This study demonstrated greater improvement in diagnostic accuracy with artificial intelligence for medical students compared with resident trainees. However, medical students were less likely than resident trainees to overrule incorrect artificial intelligence interpretations and were less accurate, even with diagnostic aid, than the artificial intelligence was by itself., (© 2024 by American Journal of Neuroradiology.)