Addressing the Need for Scalable Fatigue Feedback from Pilots: Challenges and Opportunities

Introduction: Current fatigue reporting procedures in aviation have significant limitations in providing a comprehensive understanding of fatigue risk exposure for airline operators. They also fail to generate sufficient data to refine bio-mathematical fatigue models. Three key shortcomings of traditional fatigue reporting systems include: 1. Time-consuming process – Filling out a fatigue report takes ~10–15 minutes, a considerable burden for an already exhausted pilot leading to significant under-reporting. 2. One-sided data – Reports are only submitted when fatigue is experienced, preventing insights into working patterns that pilots tolerate well. 3. Inconsistent reporting frequency – Submission rates are highly sensitive to external factors, such as reminders from management, labor disputes, or industry-wide disruptions (e.g., COVID-19). This study explored a scalable, technology-driven approach to complement traditional fatigue reporting by introducing a high-volume, representative data stream that serves as a proxy for overall fatigue risk exposure.

Methods: A smartphone app was developed to allow pilots to quickly and easily record their Karolinska Sleepiness Scale (KSS) score (1–9), with additional optional fields for: • Usage of controlled rest • Prior sleep last 24 hours • Mental effort rating • Free-text comments Only the KSS assessment was mandatory, ensuring minimal burden on users. The app was deployed in collaboration with several airline operators as a supplementary (not replacement) tool for fatigue reporting. Pilots could use the app on personal devices or company-provided iPads. Crew members were assigned a de-identified user account by their airline to ensure data privacy. The study aimed to assess how taxing this data collection method was for pilots, both in terms of time consumption and sustained participation.

Results: The implementation generated over 250,000 data points over a one-year period, with pilots spending an average of 22 seconds per entry (SD = 7.1s). Pilot interviews indicated that the main challenge was simply remembering to record data, rather than the time required to do so. The large dataset, when mapped onto flight rosters, immediately demonstrated added value for bio-mathematical fatigue model development. In particular, it enabled the detection of long-term effects of sleep deprivation, which had previously been difficult to identify in field data.

Conclusion: The use of non-intrusive, scalable technology for fatigue data collection presents a promising path forward for both airline fatigue risk management and bio-mathematical model improvement. Implementing routine KSS assessments as a standard operating procedure, similar to fuel checks, could provide the industry with a more detailed, real-time understanding of fatigue risk trends across different aviation sectors. By embedding KSS assessments into daily workflow, airlines could monitor risk development, contribute to enhancing fatigue model accuracy, improve their roster planning, and even in broader collaborations refine flight and duty time regulations. Fuel check = KSS check - a new memory item for pilots?

No conflict of interest has been declared by the author(s).

Publication History

Article published online:
08 October 2025