Literature DB >> 35515742

Workload of learners during simulated paediatric cardiopulmonary resuscitation.

Ann L Young1, Cara B Doughty2, Kaitlin C Williamson3, Sharon K Won2, Marideth C Rus2, Nadia N Villarreal4, Elizabeth A Camp2, Daniel S Lemke2.   

Abstract

Introduction: Learner workload during simulated team-based resuscitations is not well understood. In this descriptive study, we measured the workload of learners in different team roles during simulated paediatric cardiopulmonary resuscitation.
Methods: Paediatric emergency nurses and paediatric and emergency medicine residents formed teams of four to eight and randomised into roles to participate in simulation-based, paediatric resuscitation. Participant workload was measured using the NASA Task Load Index, which provides an average workload score (from 0 to 100) across six subscores: mental demand, physical demand, temporal demand, performance, frustration and mental effort. Workload is considered low if less than 40, moderate if between 40 and 60 and high if greater than 60.
Results: There were 210 participants representing 40 simulation teams. 138 residents (66%) and 72 nurses (34%) participated. Team lead reported the highest workload at 65.2±10.0 (p=0.001), while the airway reported the lowest at 53.9±10.8 (p=0.001); team lead had higher scores for all subscores except physical demand. Team lead reported the highest mental demand (p<0.001), while airway reported the lowest. Cardiopulmonary resuscitation coach and first responder reported the highest physical demands (p<0.001), while team lead and nurse recorder reported the lowest (p<0.001). Conclusions: Workload for learners in paediatric simulated resuscitation teams was moderate to high and varied significantly based on team role. Composition of workload varied significantly by team role. Measuring learner workload during simulated resuscitations allows improved processes and choreography to optimise workload distribution. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  cardiopulmonary resuscitation; cognitive load; education; emergency paediatrics; medical; simulation

Year:  2020        PMID: 35515742      PMCID: PMC8936742          DOI: 10.1136/bmjstel-2020-000652

Source DB:  PubMed          Journal:  BMJ Simul Technol Enhanc Learn        ISSN: 2056-6697


  30 in total

1.  Cognitive Load Theory for the Design of Medical Simulations.

Authors:  Kristin L Fraser; Paul Ayres; John Sweller
Journal:  Simul Healthc       Date:  2015-10       Impact factor: 1.929

2.  Pediatric resident confidence in resuscitation skills relates to mock code experience.

Authors:  Sandrijn M van Schaik; Isabelle Von Kohorn; Patricia O'Sullivan
Journal:  Clin Pediatr (Phila)       Date:  2008-05-12       Impact factor: 1.168

3.  A novel approach to life support training using "action-linked phrases".

Authors:  Elizabeth A Hunt; Hillenn Cruz-Eng; Jamie Haggerty Bradshaw; Melanie Hodge; Tammi Bortner; Christie L Mulvey; Kristen N McMillan; Hannah Galvan; Jordan M Duval-Arnould; Kareen Jones; Nicole A Shilkofski; David L Rodgers; Elizabeth H Sinz
Journal:  Resuscitation       Date:  2014-10-18       Impact factor: 5.262

Review 4.  Part 12: Pediatric Advanced Life Support: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care.

Authors:  Allan R de Caen; Marc D Berg; Leon Chameides; Cheryl K Gooden; Robert W Hickey; Halden F Scott; Robert M Sutton; Janice A Tijssen; Alexis Topjian; Élise W van der Jagt; Stephen M Schexnayder; Ricardo A Samson
Journal:  Circulation       Date:  2015-11-03       Impact factor: 29.690

5.  Measuring mental workload with the NASA-TLX needs to examine each dimension rather than relying on the global score: an example with driving.

Authors:  Edith Galy; Julie Paxion; Catherine Berthelon
Journal:  Ergonomics       Date:  2017-09-08       Impact factor: 2.778

6.  Simulation-based mock codes significantly correlate with improved pediatric patient cardiopulmonary arrest survival rates.

Authors:  Pamela Andreatta; Ernest Saxton; Maureen Thompson; Gail Annich
Journal:  Pediatr Crit Care Med       Date:  2011-01       Impact factor: 3.624

7.  Higher mental workload is associated with poorer laparoscopic performance as measured by the NASA-TLX tool.

Authors:  Yuliya Y Yurko; Mark W Scerbo; Ajita S Prabhu; Christina E Acker; Dimitrios Stefanidis
Journal:  Simul Healthc       Date:  2010-10       Impact factor: 1.929

8.  Factors affecting team size and task performance in pediatric trauma resuscitation.

Authors:  Deirdre C Kelleher; Mark L Kovler; Lauren J Waterhouse; Elizabeth A Carter; Randall S Burd
Journal:  Pediatr Emerg Care       Date:  2014-04       Impact factor: 1.454

9.  Delays and errors in cardiopulmonary resuscitation and defibrillation by pediatric residents during simulated cardiopulmonary arrests.

Authors:  Elizabeth A Hunt; Kimberly Vera; Marie Diener-West; Jamie A Haggerty; Kristen L Nelson; Donald H Shaffner; Peter J Pronovost
Journal:  Resuscitation       Date:  2009-05-06       Impact factor: 5.262

10.  Assessment of workload during pediatric trauma resuscitation.

Authors:  Samantha E Parsons; Elizabeth A Carter; Lauren J Waterhouse; Aleksandra Sarcevic; Karen J O'Connell; Randall S Burd
Journal:  J Trauma Acute Care Surg       Date:  2012-11       Impact factor: 3.313

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