Psychometric Evaluation of Cognitive Load and Unintended Consequences of Electronic Health Records in US Emergency Nurses

This study utilized a longitudinal quantitative design to investigate the psychometric measurements of the Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire and the National Aeronautics and Space Administration Task Load Index instruments in emergency department nurses within the United States. This is the first study to our knowledge to examine these survey instruments' internal consistency reliability, test-retest reliability, and construct validity measurements in the emergency nursing population. The Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire tool indicated good test-retest stability reliability and excellent internal consistency reliability. The National Aeronautics and Space Administration Task Load Index survey had moderate reliability for both the internal consistency reliability and the test-retest stability reliability. The findings related to the psychometric measurement of internal consistency reliability and test-retest stability reliability supported the use of the National Aeronautics and Space Administration Task Load Index and the Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire in additional healthcare research studies of emergency department nurses. Further research related to nurses' cognitive load and unintended consequences of the electronic health record topics are recommended for knowledge acquisition to fill the profound literature gaps. Thus, this publication supports the use of measurement tools to conduct these studies.

Authors

Publication Details

Journal
Scholar Commons (University of South Carolina)
Published
2025-10-01
DOI
https://doi.org/10.1097/cin.0000000000001365">https://doi.org/10.1097/cin.0000000000001365</a></p
Primary Topic
Electronic Health Records Systems
Type
article
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article

Psychometric Evaluation of Cognitive Load and Unintended Consequences of Electronic Health Records in US Emergency Nurses

Sheila M. Gephart, Carolyn S. Harmon, Sara B. Donevant, Adams, Swann Arp, Ph.D., MS, FACE et al.
Scholar Commons (University of South Carolina)
Electronic Health Records Systems
article

Psychometric Evaluation of Cognitive Load and Unintended Consequences of Electronic Health Records in US Emergency Nurses

Sheila M. Gephart, Carolyn S. Harmon, Sara B. Donevant, Adams, Swann Arp, Ph.D., MS, FACE, Jean E. Davis
article en

Abstract

This study utilized a longitudinal quantitative design to investigate the psychometric measurements of the Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire and the National Aeronautics and Space Administration Task Load Index instruments in emergency department nurses within the United States. This is the first study to our knowledge to examine these survey instruments' internal consistency reliability, test-retest reliability, and construct validity measurements in the emergency nursing population. The Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire tool indicated good test-retest stability reliability and excellent internal consistency reliability. The National Aeronautics and Space Administration Task Load Index survey had moderate reliability for both the internal consistency reliability and the test-retest stability reliability. The findings related to the psychometric measurement of internal consistency reliability and test-retest stability reliability supported the use of the National Aeronautics and Space Administration Task Load Index and the Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire in additional healthcare research studies of emergency department nurses. Further research related to nurses' cognitive load and unintended consequences of the electronic health record topics are recommended for knowledge acquisition to fill the profound literature gaps. Thus, this publication supports the use of measurement tools to conduct these studies.

Scholar Commons (University of South Carolina)
Openalex Percentile: Top 22%
Electronic Health Records Systems
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