Musculoskeletal disorders and symptoms are common among workers in the semiconductor and related industries. Ergonomic‐related checklists are used to identify musculoskeletal disorder risk factors in the workplace. This study explores the suitability of the Occupational Safety and Health Administration (OSHA) musculoskeletal disorders (MSDs) checklist for use in the semiconductor manufacturing industry. Six companies were enrolled in the current study, and 122 subjects, ranging in age from 21 to 54 years old, were evaluated through a questionnaire survey and field observation using the OSHA MSDs checklist. The observers were administered an ergonomics‐based checklist training course with a duration of 36 hours. Experimental results demonstrated that nearly 50% of subjects reported physical discomfort, with shoulder symptoms (38.5%) being the most common complaint. In addition, the aggregated sensitivity, specificity, and positive predictive values for the MSDs checklist in the six companies were 47.3%, 62.4%, and 30.0%, respectively. This study concluded that the OSHA MSDs checklist appeared to contain better estimates for capturing musculoskeletal discomfort and found that the OSHA MSDs checklist provided an easily administered, proactive surveillance instrument to assist in early identification of musculoskeletal discomfort. © 2012 Wiley Periodicals, Inc.

Musculoskeletal disorders associated with computer use are closely related to the level of computer exposure. Various studies have been conducted for recording and evaluating long-term use of mouse and keyboard in computer workers. However, keyboard exposure is distributed over two hands and different fingers and mouse workload is mainly borne by the dominant hand which is with significantly higher musculoskeletal risk. This study utilizes an external logger for onsite measurements of computer activities in three professional groups over 6 months. All subjects include twelve university administrators, eight computer-aided design (CAD) draftsmen, and eight software programmers. Individual participant’s typing pattern was determined by a novel hardware and software developed in this study to separate keyboarding workload in the dominant hand from that in the nondominant hand. Each participant’s daily computer exposures, number of keystroke typing and mouse clicking, in one’s dominant and nondominant hand were then predicted by individual typing pattern and the logged computer activities. Estimated computer exposures of participants’ dominant and nondominant hand were then correlated with the musculoskeletal complaints collected by a questionnaire of body part discomfort rating. Regression analysis show participants’ average daily computer exposure was only moderately correlated with their hand discomfort. Research finding suggests computer associated discomfort may be affected by factors other than keyboard and mouse exposures.

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