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Life Support Course for Nurses: beyond competency training.

Yen Tjuin Eugene Teoh1, Jenny Jok Hiok Chew2, Ai Ling Irene Lee1

  • 1Nursing Service (Education and Development), Tan Tock Seng Hospital, Singapore.

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|January 10, 2022
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Summary

The Life Support Course for Nurses (LSCN) enhances nurses' ability to respond to cardiac arrests. This study emphasizes the critical roles of deep learning and reflection in the LSCN program for effective resuscitation training.

Keywords:
Life Support Course For Nursesdeep learningreflectionresuscitation

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Area of Science:

  • Medical Education
  • Emergency Medicine
  • Nursing Resuscitation Training

Background:

  • The Life Support Course for Nurses (LSCN) is crucial for equipping nurses with essential resuscitation skills for in-hospital cardiac arrests.
  • Prior research on LSCN primarily focused on its development, nurses' confidence, defibrillation experience, barriers, and perceived usefulness.

Purpose of the Study:

  • To highlight the significance of deep learning and reflection as key learning methodologies within the LSCN.
  • To underscore the impact of these methodologies on nurses' preparedness for cardiac arrest response.

Main Methods:

  • Focus on pedagogical approaches within the Life Support Course for Nurses.
  • Analysis of learning methodologies, specifically deep learning and reflection.
  • Qualitative or quantitative assessment of skill acquisition and knowledge retention through these methods (details not specified in abstract).

Main Results:

  • Deep learning and reflection are identified as pivotal components of the LSCN.
  • These methodologies are crucial for enhancing nurses' resuscitation skills and confidence.
  • Effective implementation of deep learning and reflection contributes to better patient outcomes during cardiac events.

Conclusions:

  • The LSCN program's effectiveness is significantly enhanced by incorporating deep learning and reflective practices.
  • Nurses benefit from these methodologies, improving their capacity as first responders in critical cardiac arrest situations.
  • Further emphasis on deep learning and reflection is recommended for optimizing resuscitation training for nurses.