Introduction: The ability to perform optimally under pressure is critical across many occupations, including the military, first responders, and competitive sport. Despite recognition that such performance depends on a range of cognitive factors, how common these factors are across performance domains remains unclear. The current study sought to integrate existing knowledge in the performance field in the form of a transdisciplinary expert consensus on the cognitive mechanisms that underlie performance under pressure. Methods: International experts were recruited from four performance domains [(i) Defense; (ii) Competitive Sport; (iii) Civilian High-stakes; and (iv) Performance Neuroscience]. Experts rated constructs from the Research Domain Criteria (RDoC) framework (and several expert-suggested constructs) across successive rounds, until all constructs reached consensus for inclusion or were eliminated. Finally, included constructs were ranked for their relative importance. Results: Sixty-eight experts completed the first Delphi round, with 94% of experts retained by the end of the Delphi process. The following 10 constructs reached consensus across all four panels (in order of overall ranking): (1) Attention; (2) Cognitive Control-Performance Monitoring; (3) Arousal and Regulatory Systems-Arousal; (4) Cognitive Control-Goal Selection, Updating, Representation, and Maintenance; (5) Cognitive Control-Response Selection and Inhibition/Suppression; (6) Working memory-Flexible Updating; (7) Working memory-Active Maintenance; (8) Perception and Understanding of Self-Self-knowledge; (9) Working memory-Interference Control, and (10) Expert-suggested-Shifting. Discussion: Our results identify a set of transdisciplinary neuroscience-informed constructs, validated through expert consensus. This expert consensus is critical to standardizing cognitive assessment and informing mechanism-targeted interventions in the broader field of human performance optimization.

Building a transdisciplinary expert consensus on the cognitive drivers of performance under pressure: An international multi-panel Delphi study

Marcora, Samuele M;
2023

Abstract

Introduction: The ability to perform optimally under pressure is critical across many occupations, including the military, first responders, and competitive sport. Despite recognition that such performance depends on a range of cognitive factors, how common these factors are across performance domains remains unclear. The current study sought to integrate existing knowledge in the performance field in the form of a transdisciplinary expert consensus on the cognitive mechanisms that underlie performance under pressure. Methods: International experts were recruited from four performance domains [(i) Defense; (ii) Competitive Sport; (iii) Civilian High-stakes; and (iv) Performance Neuroscience]. Experts rated constructs from the Research Domain Criteria (RDoC) framework (and several expert-suggested constructs) across successive rounds, until all constructs reached consensus for inclusion or were eliminated. Finally, included constructs were ranked for their relative importance. Results: Sixty-eight experts completed the first Delphi round, with 94% of experts retained by the end of the Delphi process. The following 10 constructs reached consensus across all four panels (in order of overall ranking): (1) Attention; (2) Cognitive Control-Performance Monitoring; (3) Arousal and Regulatory Systems-Arousal; (4) Cognitive Control-Goal Selection, Updating, Representation, and Maintenance; (5) Cognitive Control-Response Selection and Inhibition/Suppression; (6) Working memory-Flexible Updating; (7) Working memory-Active Maintenance; (8) Perception and Understanding of Self-Self-knowledge; (9) Working memory-Interference Control, and (10) Expert-suggested-Shifting. Discussion: Our results identify a set of transdisciplinary neuroscience-informed constructs, validated through expert consensus. This expert consensus is critical to standardizing cognitive assessment and informing mechanism-targeted interventions in the broader field of human performance optimization.
2023
Albertella, Lucy; Kirkham, Rebecca; Adler, Amy B; Crampton, John; Drummond, Sean P A; Fogarty, Gerard J; Gross, James J; Zaichkowsky, Leonard; Andersen, Judith P; Bartone, Paul T; Boga, Danny; Bond, Jeffrey W; Brunyé, Tad T; Campbell, Mark J; Ciobanu, Liliana G; Clark, Scott R; Crane, Monique F; Dietrich, Arne; Doty, Tracy J; Driskell, James E; Fahsing, Ivar; Fiore, Stephen M; Flin, Rhona; Funke, Joachim; Gatt, Justine M; Hancock, P A; Harper, Craig; Heathcote, Andrew; Heatown, Kristin J; Helsen, Werner F; Hussey, Erika K; Jackson, Robin C; Khemlani, Sangeet; Killgore, William D S; Kleitman, Sabina; Lane, Andrew M; Loft, Shayne; MacMahon, Clare; Marcora, Samuele M; McKenna, Frank P; Meijen, Carla; Moulton, Vanessa; Moyle, Gene M; Nalivaiko, Eugene; O'Connor, Donna; O'Conor, Dorothea; Patton, Debra; Piccolo, Mark D; Ruiz, Coleman; Schücker, Linda; Smith, Ron A; Smith, Sarah J R; Sobrino, Chava; Stetz, Melba; Stewart, Damien; Taylor, Paul; Tucker, Andrew J; van Stralen, Haike; Vickers, Joan N; Visser, Troy A W; Walker, Rohan; Wiggins, Mark W; Williams, Andrew Mark; Wong, Leonard; Aidman, Eugene; Yücel, Murat
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