Upper extremity musculoskeletal symptoms and disorders (UEMSDs) have long been an identified occupational health problem. Many studies use symptoms to classify disorders and many classification systems for disorders rely in large part on symptoms. Furthermore, in the epidemiological literature investigating the etiology of upper extremity musculoskeletal symptoms and disorders, symptoms measurement occurs at nonspecific times up to 6 months or a year after risk factors are measured. Thus, there is a need to understand temporal variations in symptoms reporting and questions remain regarding the natural history of UEMSDs.
The temporal variation of upper extremity musculoskeletal symptoms throughout an academic semester was described. In a group of college undergraduates, symptom patterns were found for time of day and number of days into the semester. For number of days into the semester, it could be argued an increasing quadratic effect of days into the semester on symptoms occurrence was discernible. However, because the data is based on a pilot project of 30 participants, a descriptive approach was followed. Number of days into the semester was kept categorical rather than forcing a linear and quadratic term into the model. For both symptoms outcomes, a dip in the odds of experiencing symptoms compared to other times in the semester was noted. One possible explanation for this dip was before this data collection period (77–85 days) Spring Break occurred and at the beginning of the “dip” a week-long university festival was ongoing, giving students a computing break and time to recover if symptomatic. This appears noteworthy as an example of an exposure-response relationship if computer use was associated with symptoms during this semester.
Similar to a previous study examining the effects of an intervention on upper extremity musculoskeletal symptoms among office workers [2
], there was no day of week (workweek) trend. Interestingly, the time of day pattern seen was different for the time of day pattern seen among office workers [2
]; Amick and colleagues found a linear pattern that increased throughout the day. Students responding after midnight were at a substantially increased risk of reporting moderate or greater
symptoms. Differences in work patterns among office workers and student workers may affect the time of day patterns seen in both populations. Interestingly, all of the after midnight events occurred during the first quartile of days into the semester and most occurred on either a Monday or Tuesday.
The relationship between time of day and days into the semester is rather complicated. It appears that as the semester progresses, symptoms are generally less likely to occur, and there are no late night responses (possibly late computing hours) after the first half of the semester. The two time-related predictors together are associated with only moderate or greater symptoms. It is not clear what time of day represents (computer use duration, ability for body to recover from daytime musculoskeletal stressors). We plan to explore the temporal patterns in future analyses to resolve the role time of day plays in upper extremity musculoskeletal symptoms occurrence.
Before each participant was given their handheld computer for the week, they were interviewed as to typical wake time and sleep onset. The program to then randomly beep the students throughout the day everyday for a week was written according to each participant’s sleep/wake cycle so as not to encourage loss to follow-up. Therefore, data collected after midnight was due to self-reported sleep/wake schedules for students identifying themselves as typically up late at night. While programming according to self-reported sleep/wake schedules may present a sampling bias (although it promotes study retention), we have data that will be evaluated in the future that compares actual computing patterns over midnight measured directly through a computer software to determine if self-reported sleep/wake schedules were accurate and if they changed throughout the semester. Thus, the possible issue of sampling bias will be addressed.
The patterns demonstrating changes in symptoms experiences over the day and over a span of months provides insight into outcome measurement issues when studying the epidemiology of computing-related UEMSDs from both a macro and micro scale. Detecting macro versus micro time changes in symptoms raises an important design issue when deciding what perspective in the etiology of UEMSDs is desired and how to measure specific exposures such as sustained posture and other suspected biomechanical factors (Gerr et al., 2006). Furthermore, office ergonomics intervention studies would also benefit from designing outcome measurements to detect time-related symptoms changes, allowing for more accurate assessments of intervention effect.
The models proposed here are meant to describe temporal variations in upper extremity musculoskeletal symptoms that need to be adjusted for before evaluating the main proposed risk factors: computer use duration and non-neutral computing postures. A profile of college students based on the 30 that participated for the current study were constructed to better understand symptoms distribution over time before further modeling symptoms on suspected risk factors. This pilot project was done in the context of a study focused on computing patterns and non-neutral computing patterns and their association with upper extremity musculoskeletal symptoms. The findings presented here regarding the natural history of upper extremity musculoskeletal symptoms are novel and provocative. Further epidemiologic research is needed to confirm symptoms patterns related to computing in both college and office environments. In the meantime, further work in this field, whether in the form of office ergonomic intervention design or epidemiologic research, should measure temporality of musculoskeletal symptoms throughout a day and over extended periods of time (weeks or months) if conclusions about an intervention’s effect or causal role for a risk factor wish to be made.