Online survey among maritime pilots: job-related stress and strain and the effects on their work ability

Unveiling nuances in data analysis to illuminate marine pilot strain

Maritime studies, encompassing a range of disciplines, increasingly rely on advanced data analytics, particularly in the context of navigation. As technology advances, the statistical averaging of large datasets has become a critical component of these analyses. However, recent studies have highlighted discrepancies between statistical predictions and observable realities, especially in high-stress environments like port approach procedures conducted by marine pilots. This study analyzed physiological responses recorded during simulation exercises involving experienced marine pilots. The focus was not on the specific outcomes of the simulations but on the potential faults arising from conventional statistical signal processing, particularly mean-centered approaches. A large dataset of signals was generated, including one signal with a dominant characteristic intentionally designed to introduce imbalance, mimicking the uneven distribution of real-world data. Initial analysis suggested that the average physiological response of the pilots followed an S-shaped curve, indicative of a psycho-physiological reaction to stress. However, further post hoc analysis revealed that this pattern was primarily influenced by a single participant's data. This finding raises concerns about the generalizability of the S-curve as a typical stress response in maritime pilots. The results underscore the limitations of relying solely on conventional statistical methods, such as mean-centered approaches, in interpreting complex datasets. The study calls into question the validity of standardizing data interpretations based on dominant characteristic curves, particularly in environments as intricate as maritime navigation. The research highlights the need for a re-evaluation of these methods to ensure more reliable and nuanced conclusions in maritime studies. This study contributes to the ongoing discourse on data interpretation in maritime research, emphasizing the critical need to re-assess conventional statistical signal processing techniques. By recognizing the potential pitfalls in data generalization, the study advocates for more robust analytical approaches to better capture the complexities of real-world maritime challenges.

The impact of COVID-19 on maritime pilots: Evidence and lessons

The COVID-19 pandemic led to port congestion and disruption to global logistics and supply chains. While previous research has examined the impact on port performance and economics, social issues, such as the impact on port personnel (including pilots), have been overlooked. In this context, this paper examines the challenges experienced by Chinese pilots during the pandemic through in-depth interviews with 28 pilots. It shows that the draconian pandemic control measures adopted in China, rather than the pandemic itself, impaired pilots' physical and mental health, reduced their availability, and introduced new safety hazards, which curtailed both the port's capacity and ability to provide efficient and safe pilotage and resulted in sub-standard services. The findings suggest that there is a serious issue regarding the absence of effective mechanisms for pilots to raise their health and safety concerns and how these might be addressed by port administrators and/or local authorities. Worker participation and involvement in occupational health and safety management was problematic. These findings have implications for pilot station management at both company and government administrative and legislative levels.