BACKGROUND: To assess relevant environmental conditions in any work-setting requires a multidisciplinary perspective that is practical, valid, and reliable. This includes the physical, environmental, and psychosocial risk-factors. The Structured Multidisciplinary work Evaluation Tool (SMET) questionnaire simultaneously considers multiple work-related demands.

OBJECTIVE: This study translated and culturally adapted the SMET into Persian and evaluated its psychometric properties in Persian industrial workers.

METHODS: Cross-sectional translation and cross-cultural adaptation in five standardized phases. A convenience sample (n = 211) recruited from an industrial-occupation setting completed: the SMET; and the Rapid Upper Limb Assessment (RULA), and National Aeronautics and Space Administration Task Load Index (NASA-TLX) criteria; plus light and noise levels were concurrently assessed. Psychometric properties included: validity, with face (from confirmed language clarity, simplicity, and readability), content (via the content validity index, CVI, for equivalency and relevancy), criterion (through Pearson's r correlation with relevant criteria), and construct (through known group validity between participants with/without work-related musculoskeletal disorders, WMSDs); internal consistency (Cronbach's α); and test-retest reliability (intraclass correlation coefficient, ICC2.1).

RESULTS: Validity was confirmed with: face through the adaptation; content from suitable CVI values for items (CVI range = 0.78-1.0) and scale-total (CVI = 0.86); criterion from SMET associations with levels for light (r = - 0.42) and noise (r = 0.21), plus RULA (r = 0.42) and NASA-TLX (r = 0.39); and construct through participants with WMSD having significantly higher SMET total-scores (p = 0.01). Internal consistency (α= 0.89) and reliability (ICC2.1 = 0.87) were acceptable and strong.

CONCLUSION: This study indicated that the SMET Persian version had acceptable psychometric properties in an industrial occupational setting. Further investigation in longitudinal populations is recommended.