This research delves into the intricate landscape of Musculoskeletal Disorder (MSD) risk factors, employing a novel fusion of Natural Language Processing (NLP) techniques and mode-based ranking methodologies. The primary objective is to advance the comprehension of MSD risk factors, their classification, and their relative severity, facilitating more targeted preventive and management interventions. The study utilizes eight diverse models, integrating pre-trained transformers, cosine similarity, and various distance metrics to classify risk factors into personal, biomechanical, workplace, psychological, and organizational classes. Key findings reveal that the BERT model with cosine similarity attains an overall accuracy of 28%, while the sentence transformer, coupled with Euclidean, Bray-Curtis, and Minkowski distances, achieves a flawless accuracy score of 100%. In tandem with the classification efforts, the research employs a mode-based ranking approach on survey data to discern the severity hierarchy of MSD risk factors. Intriguingly, the rankings align precisely with the previous literature, reaffirming the consistency and reliability of the approach. ``Working posture" emerges as the most severe risk factor, emphasizing the critical role of proper posture in preventing MSDs. The collective perceptions of survey participants underscore the significance of factors like "Job insecurity," "Effort reward imbalance," and "Poor employee facility" in contributing to MSD risks. The convergence of rankings provides actionable insights for organizations aiming to reduce the prevalence of MSDs. The study concludes with implications for targeted interventions, recommendations for improving workplace conditions, and avenues for future research.

翻译：本研究深入探讨了肌肉骨骼疾患（MSD）风险因素的复杂图景，采用了一种融合自然语言处理（NLP）技术与基于模式排序方法的新颖框架。主要目标在于提升对MSD风险因素、其分类以及相对严重程度的理解，从而为更具针对性的预防和管理干预措施提供支持。研究使用了八种不同模型，整合了预训练变换器、余弦相似度以及多种距离度量，将风险因素划分为个人、生物力学、工作场所、心理和组织五大类别。关键发现表明，采用余弦相似度的BERT模型总体准确率达到28%，而结合欧氏距离、布雷-柯蒂斯距离和闵可夫斯基距离的句子变换器则实现了100%的完美准确率。在分类工作的同时，研究还采用基于模式的排序方法对调查数据进行分析，以辨别MSD风险因素的严重性层级。有趣的是，排序结果与既有文献完全一致，再次验证了该方法的稳定性和可靠性。“工作姿势”被确认为最严重的风险因素，强调了正确姿势在预防MSD中的关键作用。调查参与者的集体感知凸显了“工作不安全感”、“努力-回报失衡”以及“员工设施不足”等因素对MSD风险的重要影响。排序结果的趋同性为旨在降低MSD患病率的组织提供了可操作的见解。研究最后讨论了针对性干预的意义、改善工作条件的建议以及未来研究的方向。