Quantifying repetitive hand activity for epidemiological research on musculoskeletal disorders – Part II: comparison of different methods of measuring force level and repetitiveness

Abstract

This paper focuses on comparisons between the different methods of assessing repetitive hand activities. Various methods were used to measure hand force and repetitiveness of hand activities on 733 subjects in the study described by Bao et al. (2006). Two definitions of repetitiveness were used in analysis of detailed time studies of repetitive hand activities and four parameters of the American Conference of Governmental Industrial Hygienists (ACGIH) hand activity level (HAL) and the Strain Index methods were estimated by ergonomists and used to quantify repetitiveness. Hand forces were measured or estimated using three different methods: 1) measured with a force gauge or mimicked on a force gauge (force matching); 2) estimated by ergonomists using rating scales; 3) self-reports by subjects. The jobs were also evaluated using the ACGIH HAL and Strain Index methods when different repetitiveness quantification methods were used. Results showed that different definitions of repetitive exertion might lead to measuring different physical exposure phenomena and produce very different results. There were poor correlations between the measures of repetitiveness estimated by the different methods. Correlations between force quantifications using different methods were also poor. This suggests that parameters measured by different methods might not be interchangeable. Both the ACGIH HAL and Strain Index methods identified more ‘hazardous’ jobs when repetitiveness was estimated by ergonomists than when it was calculated by detailed time studies of forceful hand exertions. The Strain Index method identified more ‘hazardous’ jobs than the ACGIH HAL method. Overall, the between-methods agreements were found to be moderate to substantial.

Keywords:

• Exposure quantification
• Repetition
• Inter-method comparison
• Hand force
• Job evaluation

Acknowledgement

We acknowledge the important contributions of Ruby Irving, Benjamin Hamilton, Cindy Orr, Jessica Keller, Larry Taing, Pat Woods, Tiffany Ballard, Hieu Pham, Christina Buntin and Nancy Caldwell in data collection and processing, Caroline Smith in coordination of field data collections, Joyce Fan for providing subject demographic information, Eira Viikari-Juntura for review of the manuscript and Nayak Polissar for suggestions on statistical analysis. This research was funded in part by the US National Institute for Occupational Safety and Health (OH1007316) and the Washington State Department of Labor and Industries.