DOI: 10.4103/ahstj.ahstj_47_25 ISSN: 3117-5422

The Impact of Simulation-based Learning on AlMaarefa University Medical Graduates’ Confidence (2018–2023) in Acquiring Procedural Skills

Salma Hassan Kamal Elgazzar, Anas Omar, Habiba Hassan

Abstract

Background:

Traditional medical education often limits patient-teacher interactions necessary for practicing essential skills. Simulation-based learning (SBL) addresses these challenges by providing a safe environment for clinical practice, minimizing patient risk, and enhancing traditional bedside teaching.

Objectives:

This study explored how SBL influences the confidence of Almaraffa University medical graduates (2018–2023) in basic procedural skills, emphasizing self-confidence and knowledge retention after graduation.

Methods:

A cross-sectional survey was conducted between August 2024 and February 2025 among 405 medical graduates at AlMaarefa University (2018–2023) using a validated self-administered questionnaire, after obtaining ethical approval (IRB24-032), to assess feedback on Clinical Professional Skills Course (Skill 402) regarding SBL assessment and its impact on their efficacy during the postgraduate practice. The response rate was 27.65%, and data analysis included median values, interquartile ranges, frequencies, and statistical tests.

Results:

Most graduates (71.4%) positively viewed SBL, with over 80% fulfilled with the training quality. Highly rated skills included 74.2% for endotracheal and 66% for nasogastric tube insertions, while the speculum procedure received lower ratings, 60.7%. Around 60%–74% indicated a need for more advanced procedure courses and 70.5% suggested course repetition for better skill retention.

Conclusions:

Most participants positively evaluated SBL for enhancing clinical skills, boosting confidence for residency, and were satisfied with medical procedural training. They suggested additional training for complex procedures and recommended a course repetition for better skill retention. Limitations include low response rates and reliance on self-reported data.

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