Sparse Sampling-Based Estimation of the Retention of Rarely Used Procedural Knowledge
Abstract
In this project, we assessed whether cognitive measures can be used to predict performance on Cardiopulmonary Resuscitation (CPR), a complex, life-saving task. More specifically, we collected detailed performance measures during the (re-)learning of CPR and on a number of carefully selected cognitive tasks, and correlated these with CPR performance months to years after the initial training. We assessed CPR performance in a group of German young adults who all had received CPR training (as part of their drivers licence exam)months to years prior to their participation in the study. Even though their initial CPR performance was far below the required proficiency levels, a quick, video-based retraining increased CPR performance to well above minimal proficiency levels. Based on these findings, we have published guidelines and a recommendation for regular, low-cost video-based refresher training sessions to keep CPR performance of the general population at reasonable levels (Maass et al., 2019). During this initial session, we also collected performance data on a number of traditional, cognitive laboratory tasks that were selected based on their relation to aspects of the CPR task. For example, we assessed participants capacity to follow a rhythm similar to the compression frequency during CPR, or their capacity to memorize simple facts as CPR training also involved the memorization of certain procedures and the parameters of these procedures. Our goal was to assess whether such measures predict (1) CPR performance, and (2) the decline in CPR performance over time. As this resulted in an uniquely rich dataset of both laboratory tasks and a well-described, real-life task, we have ensured that this data will be available to the scientific community at-large by depositing all data and an extensive description of this data in an open access scientific data-paper (Sense et al., 2019).
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 04, 2022
- Accession Number
- AD1165471
Entities
People
- Florian Sense
- Hedderik van Rijn
- Sarah Maass
Organizations
- University of Groningen