Characterizing Relationships Among the Cognitive, Physical, Social-emotional, and Health-related Traits of Military Personnel
Author:
Giles Grace E12, Navarro Ester2, Elkin-Frankston Seth12, Brunyé Tad T12, Elmore Wade R1, Seay Joseph F1, McKenzie Kari L1, O’Fallon Kevin S1, Brown Stephanie A1, Parham Joseph L1, Garlie Todd N1, DeSimone Linda1, Villa Jose D1, Choi-Rokas Hyegjoo E1, Mitchell K Blake1, Racicot Kenneth1, Soares Jason W1, Caruso Christina1, Anderson Debra1, Cantelon Julie A1, Gardony Aaron L1, Smith Tracey J3, Karl J Philip3, Jayne Julianna M3, Christopher John J4, Talarico Maria K5, Sperlein Jennifer Neugebauer5, Boynton Angela C5, Jensen Andrew6, Ramsay John W1, Eddy Marianna D12
Affiliation:
1. United States Army Combat Capabilities Development Command Soldier Center , Natick, MA 01760, USA 2. Center for Applied Brain and Cognitive Sciences , Medford, MA 02155, USA 3. United States Army Research Institute of Environmental Medicine , Natick, MA 01760, USA 4. United States Army Aberdeen Test Center , Aberdeen Proving Ground, MD 21005, USA 5. United States Army Combat Capabilities Development Command Analysis Center , Aberdeen Proving Ground, MD 21005, USA 6. Naval Health Research Center , San Diego, CA 92152, USA
Abstract
ABSTRACT
Introduction
Personnel engaged in high-stakes occupations, such as military personnel, law enforcement, and emergency first responders, must sustain performance through a range of environmental stressors. To maximize the effectiveness of military personnel, an a priori understanding of traits can help predict their physical and cognitive performance under stress and adversity. This work developed and assessed a suite of measures that have the potential to predict performance during operational scenarios. These measures were designed to characterize four specific trait–based domains: cognitive, health, physical, and social-emotional.
Materials and Methods
One hundred and ninety-one active duty U.S. Army soldiers completed interleaved questionnaire–based, seated task–based, and physical task–based measures over a period of 3-5 days. Redundancy analysis, dimensionality reduction, and network analyses revealed several patterns of interest.
Results
First, unique variable analysis revealed a minimally redundant battery of instruments. Second, principal component analysis showed that metrics tended to cluster together in three to five components within each domain. Finally, analyses of cross-domain associations using network analysis illustrated that cognitive, health, physical, and social-emotional domains showed strong construct solidarity.
Conclusions
The present battery of metrics presents a fieldable toolkit that may be used to predict operational performance that can be clustered into separate components or used independently. It will aid predictive algorithm development aimed to identify critical predictors of individual military personnel and small-unit performance outcomes.
Funder
U.S. Army Combat Capabilities Development Command Soldier Center
Publisher
Oxford University Press (OUP)
Subject
Public Health, Environmental and Occupational Health,General Medicine
Cited by
2 articles.
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