Aim And Objectives: This study aimed to compare between the use of hands-on simulation training sessions versus video training on students' confidence in suturing skills. The study measured the effect of using hands-on simulation training versus video-recorded simulation training on medical students' suturing skills.
Methods: This study was conducted at College of Medicine, Jouf University. All third-year medical students (n=98) were invited to participate in the study. However, only 81 (male=57, female=24) of them participated in this study. A randomized pretest-posttest control group study design was used to assess self-ratings of confidence in skills. All participants attended a lecture and were then divided into two groups: the experimental group (n=34) had simulation activities, while the control group (n=47) watched video-recorded training. A paired -test was used to assess the difference between the pretest and post-test scores within each group. The independent -test was used to compare the overall mean between both groups.
Results: Statistically significant differences (improvements) of students' confidence in skills were detected in both groups. The mean difference between pre- and post-test scores for the experimental group was 1.47 (p<0.001), and it was 0.92 (p<0.001) for the control group.
Conclusion: Both hands-on simulation training sessions and video training sessions are beneficial for teaching suturing skills for students. Furthermore, a long-term follow-up multicenter study that evaluates the impact of confidence in skin suturing skills on competence development is warranted among different university students in Saudi Arabia.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9527699 | PMC |
| http://dx.doi.org/10.2147/CCID.S369359 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Machine-Learning Electron Dynamics with Moment Propagation Theory: Application to Optical Absorption Spectrum Computation Using Real-Time TDDFT.
J Chem Theory Comput
December 2024
Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States.
We present an application of our new theoretical formulation of quantum dynamics, moment propagation theory (MPT) (Boyer et al., J. Chem.
View Article and Find Full Text PDFEnhancing Nursing Students' Attitudes Toward Older Adults Through an Artificial Intelligence Virtual Simulation: A Mixed-Method Design.
Nurs Rep
December 2024
School of Data Science and Analytics, Kennesaw State University, Kennesaw, GA 30144, USA.
Background/objectives: The projected increase from 58 million older adults in 2022 to 82 million by 2050 in the United States highlights the urgency of preparing nursing students to care for this aging population. However, studies reveal negative attitudes among nursing students toward older adults. A three-phased educational intervention that included an artificial intelligence (AI)-driven virtual simulation was implemented to address this.
View Article and Find Full Text PDFEnhancing Nursing Competencies: An Assessment of Knowledge and Attitudes Toward Dental Trauma Management Among Nursing Students-An Interventional Study.
Nurs Rep
November 2024
Department of Stomatology, Faculty of Dentistry, University of Seville, 41009 Sevilla, Spain.
Introduction: Traumatic dental injuries (TDIs) present a significant challenge for healthcare professionals. Nurses, often the first point of contact for patients, may lack essential knowledge in dental trauma first aid, as noted in the existing literature.
Objective: To assess the knowledge of traumatic dental injuries (TDIs) among undergraduate nursing students before and after a targeted educational intervention.
Combined Dielectric-Optical Characterization of Single Cells Using Dielectrophoresis-Imaging Flow Cytometry.
Biosensors (Basel)
November 2024
Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.
In this paper, we present a microfluidic flow cytometer for simultaneous imaging and dielectric characterization of individual biological cells within a flow. Utilizing a combination of dielectrophoresis (DEP) and high-speed imaging, this system offers a dual-modality approach to analyze both cell morphology and dielectric properties, enhancing the ability to analyze, characterize, and discriminate cells in a heterogeneous population. A high-speed camera is used to capture images of and track multiple cells in real-time as they flow through a microfluidic channel.
View Article and Find Full Text PDFTrajectory Tracking Control for Robotic Manipulator Based on Soft Actor-Critic and Generative Adversarial Imitation Learning.
Biomimetics (Basel)
December 2024
School of Computer Science and Technology, Dongguan University of Technology, Dongguan 523808, China.
In this paper, a deep reinforcement learning (DRL) approach based on generative adversarial imitation learning (GAIL) and long short-term memory (LSTM) is proposed to resolve tracking control problems for robotic manipulators with saturation constraints and random disturbances, without learning the dynamic and kinematic model of the manipulator. Specifically, it limits the torque and joint angle to a certain range. Firstly, in order to cope with the instability problem during training and obtain a stability policy, soft actor-critic (SAC) and LSTM are combined.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!