The Role of Self-Study in Addressing Competency Decline Among Airline Pilots During the COVID-19 Pandemic

Hum Factors. 2024 Mar;66(3):807-817. doi: 10.1177/00187208221113614. Epub 2022 Jul 6.

Abstract

Objective: This study aimed to investigate the self-study methods used by pilots while grounded and their perception of competence decline and confidence upon their return to flying.

Background: Previously, long absences from flying were managed on a case-by-case basis. Thousands of pilots returning to flying as the pandemic eases have burdened airline training systems. Limited research has been conducted on the decline in skills of airline pilots while operationally absent from the cockpit. Few studies have considered this topic in the context of a pandemic.

Method: A questionnaire study was conducted with 234 airline pilots who were grounded during the COVID-19 pandemic.

Results: Uncertainty regarding sudden and indefinite periods of grounding made it challenging to maintain motivation to self-study. This matter was aggravated by the additional financial and personal stress caused by the state of the airline industry and the outcomes of the pandemic. The participants anticipated a decline in manual flying skills as the worst outcome after being absent from the flight deck. However, these pilots proved quick to recover these skills when they resumed flying. It took significantly more time for pilots to regain proficiency in applying knowledge, procedures and compliance with regulations, situation awareness and workload management.

Conclusion: The study proposes recommendations for pilots and airlines to harness essential self-study practices in competency areas identified to have significantly declined.

Application: The outcome of this paper guides airlines, pilots and regulators in better understanding how grounded pilots observe skill decline in a broader range of competencies.

Keywords: competency-based training; distance learning; flight proficiency; skill retention; training evaluation.

MeSH terms

  • COVID-19*
  • Humans
  • Pandemics*
  • Time Factors
  • Workload