A study to determine the possible links between subjective (fatigue questionnaires) and objective (bio-mathematical fatigue prevention model) fatigue detection methods

Abstract

Introduction: Application of objective fatigue detection tools in aviation bases is limited. This study was envisaged to conduct a systematic comparative analysis between a well-established objective method and short fatigue questionnaires which are used in fatigue research to employ them as a fatigue screening tool for aviation personnel. Material and Methods: Thirty-eight aviation personnel volunteered for this cross-sectional observational study. Work-rest/sleep data collected using actigraphy over 1 week were fed to a PC running Fatigue Avoidance Scheduling Tool. Objective fatigue parameters in the form of Fatigue Risk Time (FRT) and Fatigue Free Occupational Time (FFOT) were retrieved. Fatigue questionnaires Groningen Sleep Quality Scale (GSQS) for assessing sleep quality and Stanford Sleepiness Scale (SSS) to detect day-time sleepiness were used as subjective fatigue parameters. Comparative analysis was carried out using appropriate statistical tests. Results: A consistent Total Sleep Time (TST) ranging from 353 to 378 min in the week of the study with no statistically significant differences between the nights were recorded. The increasing trend of FRT and decreasing trend of FFOT over the week were observed. The GSQS, SSS (morning), and SSS (afternoon) also demonstrated a progressive increase in the scores, but only the increase from day 1 to day 2 was statistically significant. Conclusion: Gradual increase in FRT with a reciprocal decrease in FFOT, which was observed, in this study, could be attributed to a progressive increase in sleep debt over the week. A consistent TST of the duration, which is less than the optimal duration of 7–8 h for night sleep, can lead to a gradual increase in sleep debt. The regression equations computed for FFOT was: FFOT = 657 + (0.24 × TST in min) – {(27 × Morning GSQS) + (73 × Day factor)}. This regression equation could be used to extrapolate the fatigue free occupation time for aviation personnel. The study has confirmed the effectiveness of both GSQS and SSS as the fatigue prevention tool and their application in the field setup, especially in the absence of any objective fatigue detection tool.