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BACKGROUND: The role of e-learning in contemporary healthcare education is quickly developing. The aim of this study was to examine the relationship between the use of an e-learning simulation programme (Microsim, Laerdal, UK) prior to attending an Advanced Life Support (ALS) course and the subsequent relationship to candidate performance. METHODS: An open label, multi-centre randomised controlled study was conducted. The control group received a course manual and pre-course MCQ four weeks prior to the face to face course. The intervention group in addition received the Microsim programme on a CD. The primary outcome was performance during a simulated cardiac arrest at the end of the course. Secondary outcomes were performance during multiple choice exams, resuscitation skills assessments and feedback to Microsim programme. RESULTS: 572 participants were randomised (287 Microsim, 285 control). There were no significant differences in the primary outcome (performance during a standard cardiac arrest simulation) or secondary outcomes. User evaluations were favorable. 79% would recommend it to colleagues. 9% stated Microsim could replace the entire ALS course, 25% parts. Over 70% of participants' perceived that Microsim improved their understanding of the key learning domains of the ALS course. CONCLUSION: Distributing Microsim to healthcare providers prior to attending an ALS courses did not improve either cognitive or psychomotor skills performance during cardiac arrest simulation testing. The challenge that lies ahead is to identify the optimal way to use e-learning as part of a blended approach to learning for this type of training programme.

Original publication

DOI

10.1016/j.resuscitation.2010.03.019

Type

Journal article

Journal

Resuscitation

Publication Date

07/2010

Volume

81

Pages

877 - 881

Keywords

Advanced Cardiac Life Support, Cardiopulmonary Resuscitation, Chi-Square Distribution, Clinical Competence, Computer-Assisted Instruction, Curriculum, Educational Measurement, Female, Heart Arrest, Humans, Male, Reference Values, Statistics, Nonparametric, Time Factors, United Kingdom