## 5 Discussion
Future research should explore potential interaction effects, non-linear relationships, and larger sample sizes to enhance the predictive accuracy of physiological stress models. In addition to the ANOVA and t-test analyses, we conducted multiple linear regression analyses to investigate potential predictors of subjective workloads across different NASA-TLX subdimensions. The results showed that age and the LF/HF ratio in segment 2 significantly predicted the TD scores (\(p=0.0327\) and \(p=0.0123\), respectively), indicating that age-related physiological shifts and sympathetic arousal during high-alert crossings may contribute to an increased temporal workload. Moreover, the LF/HF ratio in segment 6 was significantly associated with the OP (\(p\) = 0.0285), indicating that elevated sympathetic activity in this segment may contribute to increased performance-related workload. While the model fit was modest (adjusted R\({}^{2}\) scores of 0.169 for temporal and 0.143 for performance results), these findings offer additional insight into how physiological signals during specific navigational encounters contribute to subjective workload experiences. The ordinal regression model yielded interpretable coefficients and passed the proportional odds assumption test. However, due to the limited sample size, uncorrected multiple comparisons, and reliance on segment-level HRV inputs, the robustness of the model's labeling may be constrained. As such, the model should be considered preliminary, with future validation recommended using larger datasets and external cohorts to ensure its generalizability. The experience-related variability in stress perceptions further highlights the interplay between personal resilience, stress management strategies, and job demands. While low-experience individuals may struggle more with stress due to a lack of familiarity, those in moderate- or high-experience groups may have already developed the necessary skills and coping mechanisms to handle stressors, making their stress levels more stable over time. Thus, the variability in stress perceptions based on experience highlights the evolving nature of stress responses as individuals gain exposure and mastery within their roles. Although this study primarily categorized experience by age and years of service, we acknowledge that an individual's operational competence and stress-coping ability are also shaped by factors such as their rank, vessel type, and propulsion system familiarity. For instance, extensive experience aboard smaller platform supply vessels (PSVs) may not directly translate to effective command performance on large commercial carriers, particularly those transporting passengers or hazardous cargo such as gas. These vessels differ markedly in their maneuverability, propulsion systems, and risk exposure. Although all participants in this study held valid certifications and possessed diverse sea service backgrounds, we did not stratify their experience by vessel class or propulsion system. Future research studies would benefit from incorporating more granular metrics such as the vessel type, engine configuration, and training specialization to better understand how domain-specific experience affects an individual's cognitive load and physiological stress responses in simulation-based scenarios. The regression analysis showed no significant prediction of perceived stress based on an individual's (CoC) status, last rank, last ship type, age, or total seafaring experience. This suggests that within simulated environments, an individual's hierarchical status and formal qualifications may not meaningfully differentiate their stress perception results. However, the non-parametric analysis using the Kruskal-Wallis test identified a significant difference in NASA-TLX frustration scores between the CoC groups (\(p\) = 0.0125).