Literature DB >> 30822151

Cardiac Measures of Cognitive Workload: A Meta-Analysis.

Ashley M Hughes1, Gabriella M Hancock2, Shannon L Marlow3, Kimberly Stowers4, Eduardo Salas5.   

Abstract

OBJECTIVE: We aimed to provide an assessment of the impact of workload manipulations on various cardiac measurements. We further sought to determine the most effective measurement approaches of cognitive workload as well as quantify the conditions under which these measures are most effective for interpretation.
BACKGROUND: Cognitive workload affects human performance, particularly when load is relatively high (overload) or low (underload). Despite ongoing interest in assessing cognitive workload through cardiac measures, it is currently unclear which cardiac-based assessments best indicate cognitive workload. Although several quantitative studies and qualitative reviews have sought to provide guidance, no meta-analytic integration of cardiac assessment(s) of cognitive workload exists to date.
METHOD: We used Morris and DeShon's meta-analytic procedures to quantify the changes in cardiac measures due to task load conditions.
RESULTS: Sample-weighted Cohen's d values suggest that several metrics of cardiac activity demonstrate sensitivity in response to cognitive workload manipulations. Heart rate variability measures show sensitivity to task load, conditions of event rate, and task duration. Authors of future work should seek to quantify the utility of leveraging multiple metrics to understand workload.
CONCLUSION: Results suggest that assessment of cognitive workload can be done using various cardiac activity indicators. Further, given the number of valid and reliable measures available, researchers and practitioners should base their selection of a psychophysiological measure on the experimental and practical concerns inherent to their task/protocol. APPLICATIONS: Findings bear implications for future assessment of cognitive workload within basic and applied settings. Future research should seek to validate conditions under which measurements are best interpreted, including but not limited to individual differences.

Entities:  

Keywords:  cardiac activity; cognition; mental workload; meta-analysis

Mesh:

Year:  2019        PMID: 30822151     DOI: 10.1177/0018720819830553

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  8 in total

1.  Physiological synchronization and entropy as measures of team cognitive load.

Authors:  Roger D Dias; Marco A Zenati; Ronald Stevens; Jennifer M Gabany; Steven J Yule
Journal:  J Biomed Inform       Date:  2019-07-08       Impact factor: 6.317

2.  All clinical stressors are not created equal: Differential task stress in a simulated clinical environment.

Authors:  Melissa Joseph; Jessica M Ray; Jungsoo Chang; Laura D Cramer; James W Bonz; Thomas J Yang; Ambrose H Wong; Marc A Auerbach; Leigh V Evans
Journal:  AEM Educ Train       Date:  2022-04-01

3.  Association Between Operating Room Noise and Team Cognitive Workload in Cardiac Surgery.

Authors:  Lauren R Kennedy-Metz; Maria Arshanskiy; Sandra Keller; David Arney; Roger D Dias; Marco A Zenati
Journal:  IEEE Conf Cogn Comput Asp Situat Manag       Date:  2022-07-22

Review 4.  Cognitive Engineering to Improve Patient Safety and Outcomes in Cardiothoracic Surgery.

Authors:  Marco A Zenati; Lauren Kennedy-Metz; Roger D Dias
Journal:  Semin Thorac Cardiovasc Surg       Date:  2019-10-17

5.  Analysis of Dynamic Changes in Cognitive Workload During Cardiac Surgery Perfusionists' Interactions With the Cardiopulmonary Bypass Pump.

Authors:  Lauren R Kennedy-Metz; Roger D Dias; Rithy Srey; Geoffrey C Rance; Heather M Conboy; Miguel E Haime; Jacquelyn A Quin; Steven J Yule; Marco A Zenati
Journal:  Hum Factors       Date:  2020-12-16       Impact factor: 2.888

6.  Autonomic Activity and Surgical Flow Disruptions in Healthcare Providers during Cardiac Surgery.

Authors:  Lauren R Kennedy-Metz; Andrea Bizzego; Gianluca Esposito; Roger D Dias; Marco A Zenati; Cesare Furlanello
Journal:  IEEE Conf Cogn Comput Asp Situat Manag       Date:  2020-10-07

7.  Pattern Recognition of Cognitive Load Using EEG and ECG Signals.

Authors:  Ronglong Xiong; Fanmeng Kong; Xuehong Yang; Guangyuan Liu; Wanhui Wen
Journal:  Sensors (Basel)       Date:  2020-09-08       Impact factor: 3.576

8.  An evidence-based, structured, expert approach to selecting essential indicators of primary care quality.

Authors:  Sylvia J Hysong; Kelley Arredondo; Ashley M Hughes; Houston F Lester; Frederick L Oswald; Laura A Petersen; LeChauncy Woodard; Edward Post; Shelly DePeralta; Daniel R Murphy; Jason McKnight; Karin Nelson; Paul Haidet
Journal:  PLoS One       Date:  2022-01-18       Impact factor: 3.240

  8 in total

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