Investigating daily fatigue scores during two-week offshore day shifts

This study examined daily scores of fatigue and circadian rhythm markers over two-week offshore day shift periods.

A prospective cohort study among N = 60 offshore day-shift workers working two-week offshore shifts was conducted. Offshore day shifts lasted from 07:00 - 19:00 h. Fatigue was measured objectively with pre- and post-shift scores of the 3-minute psychomotor vigilance tasks (PVT-B) parameters (reaction times, number of lapses, errors and false starts) and subjectively with pre- and post-shift Karolinska Sleepiness Scale (KSS) ratings. Evening saliva samples were collected on offshore days 2,7 and 13 to measure circadian rhythm markers such as dim-light melatonin onset times and cortisol. Generalized and linear mixed model analyses were used to examine daily fatigue scores over time.

Complete data from N = 42 offshore day shift workers was analyzed. Daily parameters of objective fatigue, PVT-B scores (reaction times, average number of lapses, errors and false starts), remained stable over the course of the two-week offshore day shifts. Daily subjective post-shift fatigue scores significantly increased over the course of the two-week offshore shifts. Each day offshore was associated with an increased post-shift subjective fatigue score of 0.06 points (95%CI: .03 - .09 p < .001). No significant statistical differences in subjective pre-shift fatigue scores were found. Neither a circadian rhythm phase shift of melatonin nor an effect on the pattern and levels of evening cortisol was found.

Daily parameters of objective fatigue scores remained stable over the course of the two-week offshore day shifts. Daily subjective post-shift fatigue scores significantly increased over the course of the two-week offshore shifts. No significant changes in circadian rhythm markers were found. Increased post-shift fatigue scores, especially during the last days of an offshore shift, should be considered and managed in (offshore) fatigue risk management programs and fatigue risk prediction models.