A psychological assessment model on the commercial maritime transport sector

Abstract

The intricate tapestry of maritime psychology unfolds within the vast expanse of the seas, where over a million seafarers navigate under unique and demanding circumstances. This comprehensive exploration traverses the currents of evolving methodologies, challenges, and trends within the maritime psychology landscape. Anchored in a profound literature review, the study illuminates the tangible challenges faced by seafarers, from isolation and hierarchical structures to harsh conditions and prolonged separation. The maritime industry's sheer scale, combined with the distinct challenges of maritime life, underscores the profound implications for seafarers' mental well-being. In tandem with advancing technology, the study delves into the integration of machine learning and artificial intelligence in psychological assessments, sparking debates on diagnostic criteria, expert opinions, and ethical considerations. This application becomes particularly critical in an industry where traditional support systems are not only physically distant but also lack adequate medical facilities. The study unfolds through a bibliometric analysis, revealing a surge in research activity post-2010, with the highest publication rates in 2021 and 2022. The disruptive impact of the COVID-19 pandemic on seafarers' lives and mental health emerges as a significant catalyst for this increase. Moving beyond theoretical frameworks, the investigation encompasses four thematic clusters: "Research Design," "Spatial Design," "Data Collection Tools," and "Assessment Approaches." Observational studies take precedence, emphasizing the importance of understanding naturally occurring events and relationships in maritime contexts. Spatial design assumes critical importance, distinguishing studies in simulated environments from those in real-life maritime settings. The diverse array of data collection tools, from surveys and questionnaires to interviews and simulator data, reflects the multifaceted nature of maritime psychology. A paradigm shift is evident in assessment approaches, with "Statistical Analysis," "Machine Learning," and "Statement Analysis" taking center stage. The practical application centers around depression, a prominent psychiatric condition affecting seafarers. Leveraging the Beck Depression Inventory-II (BDI-II), a dataset of 746 records is obtained. Fuzzy logic and the Adaptive Neuro-Fuzzy Inference System (ANFIS) methodology, integrated with MATLAB Fuzzy Logic Toolbox, provide a seamless fusion for assessing depression severity. The clustering phase adopts both psychiatric and mathematical approaches, resulting in four distinct clustering groups. The pivotal outcome underscores the high accuracy achievable in predicting depression severity through a machine learning-based approach. The ANFIS model tailored for 2-factor clustering consistently outperforms its 5-factor clustering counterpart. The mathematical approach, specifically the 3-factor clustering, emerges as the more effective choice, highlighting the need for nuanced comprehension of psychiatric factors. The ANFIS model's performance details reveal minimal training RMSE, checking RMSE, and high R 2 scores, emphasizing its efficacy in providing nuanced insights into seafarers' mental well-being. The study navigates ethical considerations associated with data collection, advocating for the necessity of developing culturally sensitive measurement tools. Fuzzy logic, specifically ANFIS, emerges as a vital tool in deciphering complex datasets, promising to revolutionize mental health assessments in the maritime industry. While the study acknowledges limitations and the need for future research with more extensive samples, it contributes significantly to maritime psychology methodologies. In conclusion, this research voyage extends beyond theoretical frameworks, offering a practical tool for assessing and addressing the psychological challenges faced by seafarers. The success of the ANFIS model underscores its potential in fostering a healthier and safer maritime working environment. The study advocates for investments in machine learning-based systems, supported by self-sustaining servers, to enhance mental health services in the maritime sector, charting a course towards a more resilient and supportive maritime industry.