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Ergonomic Risk Assessment and Work-Related Factors Associated with Musculoskeletal Disorders Among Thai Traditional
Napaporn Houngsuksakul1, Kukiat Tudpor1, Chalermsiri Theppitak2
1Faculty of Public Health, Mahasarakham University, Maha Sarakham, Thailand.
Abstract:
Work-related musculoskeletal disorders (WMSDs) remain a critical occupational health challenge, particularly in high-force and repetitive professions such as Thai traditional massage. While conventional ergonomic assessments rely primarily on self-report and observational tools, there is a growing need for data-driven occupational health informatics approaches to enable real-time risk monitoring and preventive decision support. This study aimed (1) to determine the prevalence and predictors of WMSDs among Thai traditional massage practitioners and (2) to develop a data-driven occupational health informatics framework integrating ergonomic risk profiling with digital monitoring strategies. A cross-sectional study was conducted among 396 certified practitioners working in 204 public health facilities in northeastern Thailand. Standardized instruments included the Perceived Stress Scale (PSS-10), the Modified Nordic Musculoskeletal Questionnaire, and the Body Discomfort Scale. Binary logistic regression was applied to identify significant predictors of WMSDs. The 7-day and 12-month prevalence of WMSDs were 75.0% and 81.31%, respectively. Significant predictors included years of massage experience (OR=4.29), low-level force exertion (∼50 pounds) (OR=4.04), neck extension or trunk hyperextension (OR=15.27), repetitive head movements (OR=5.28), lifting/transferring clients (OR=3.09), use of assistive devices, and adverse environmental conditions (p<0.05). Based on these findings, we propose a digital occupational health informatics framework integrating ergonomic risk stratification with wearable-based posture analytics and real-time feedback mechanisms. The framework supports the development of an assistive massage device incorporating force redistribution and posture-monitoring capabilities. Such data-driven innovations may enhance injury prevention, enable continuous ergonomic surveillance, and improve long-term occupational health sustainability in physically demanding healthcare professions.
