Objective: To determine agreement between two posture assessment survey instruments and which, if any, were correlated with experiencing upper extremity musculoskeletal symptoms.
Methods: Thirty undergraduate participants had three postural assessment surveys completed, one each for three separate 7-day data collection periods during a semester. Two observation assessment tools were used, a modified Rapid Upper Limb Assessment (mRULA) for computer users for the right and left limbs and the University of California Computer Use Checklist. Concurrently, upper extremity musculoskeletal symptom experience paired to each postural assessment was measured. Lin's concordance correlation coefficient evaluated survey agreement and multi-level statistical models described associations between survey responses and symptoms.
Results: There was no agreement between the two postural assessment tool scores (p> 0.85). In adjusted models, the UC Computer Use Checklist was positively associated with symptoms occurrence (OR=1.4, 90% CI 1.2-1.6 for any symptoms; OR=1.3, 90% CI 1.0-1.6 for moderate or greater symptoms). Associations with mRULA scores were inconsistent in that they were sometimes protective and sometimes indicators of risk, depending on the covariates included in the models.
Conclusion: The mRULA for computer users and the UC Computer Use Checklist were independent of each other; however, due to the inconsistent associations with symptoms we cannot conclude one instrument is superior to the other. Our data do suggest the UC Computer Use Checklist demonstrates a traditional relationship with symptoms, where increasing scores signifiy greater risk. We observed a nontraditional relatioship with symptoms for the mRULA for computer users that needs to be further examined. This is a pilot study and, thus, findings should be interpreted as exploratory. Associations observed in the current study will be used to test hypotheses in the cohort study recently conducted.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3268067 | PMC |
http://dx.doi.org/10.3233/WOR-2009-0942 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!