1. Computer Use, Symptoms, and Quality Of Life John Hayes, Jim Sheedy, Joan Stelmack*, Catherine Heaney** College of Optometry, Pacific University, Forest Grove, Oregon, *Illinois College of Optometry, ** Stanford University ABSTRACT Research indicates that as many as 90% of people who use computers for more than two hours a day experience vision-related symptoms. Those that spend more than four hours per day working on computer tasks experience much higher incidence, severity, and duration of computer-related symptoms. The objective of this study was to determine if a simple survey covering a multidimensional array of factors has the sensitivity to detect the effects of the visual environment on eye symptoms and whether eye symptoms are related to perceived quality of life. MATERIALS & METHODS RESULTSRESULTS (cont’d) A priori quality of life structural equation. Ovals represent latent variables that are composed of measured variables. Rectangles represent single measured variables. Solid arrows reflect significant associations between the variables. Double headed arrows test a bi-directional relationship between variables. Single headed arrows test a specific direction of the association. CONCLUSIONS CONTACT INFORMATION A survey of 1000 university employees (70.5% adjusted response rate) assessed visual and physical symptoms, job physical and mental demands, ability to control/influence work, amount of work at a computer, computer work environment, relations with others at work, life and job satisfaction, and quality of life. Data were analyzed to determine whether self- assessment of eye symptoms can affect opinions of quality of life. The study also explored the factors that are associated with eye symptoms. Structural Equation Modeling and multiple regressions were used to assess the hypotheses. ACKNOWLEDGEMENTS 70% of the employees used some form of vision correction during computer use 2.9% used glasses specifically prescribed for computer use 8% had had refractive surgery employees spent an average of 6 hours per day at the computer the latent variable eye symptoms was significantly associated with a composite quality of life variable (p=.02) after adjusting for job quality, job satisfaction, supervisor relations, co- worker relations, mental and physical load of the job, and job demand Age and gender were not significantly associated with symptoms The variables in the model below were developed from 98 questions plus age and gender. Quality of life was a composite of two latent variables. After adjusting for age, gender, ergonomics, hours at the computer, and exercise, eye symptoms were significantly associated with physical symptoms (p<.001) accounting for 48% of the variance. Principal Investigator John R. Hayes T: 503.352.2972 E: haye8350@pacificu.edu This study was designed to look at the relationship between eyes and quality of life in a workforce of computer users. The reported number of hours directly working at the computer was not the major factor impacting quality of life. After controlling for job quality and other factors eye symptoms had a very small but statistically significant relationship with a global measure of quality of life. There was a very large association between eye and physical symptoms. We did not find significant relief from physical symptoms with occupational lenses among the small number of wearers in the sample but did show that lighting was associated with symptoms for some workers. Further research may find that methods addressing eye issues may impact overall physical comfort in the workplace. This study was funded in part by the American Optometric Foundation and the Ohio State University Optometry Coordinating Center, NIH. Hayes J, Sheedy J, Stelmack J, Heaney C. Effects of computer use on symptoms and quality of life. Optom Vis Sci, 2007; 84(8):739-745. The R2 values are displayed as the groups of variables were added to the hierarchical regression model. Asterisks above the bars indicate statistical significance (p<.05) for the simple correlation between the individual variable physical symptoms and for the partial correlation in the context of the full model. Asterisks above the bars indicate statistical significance (p<.05) for the simple correlation between the individual variable eye symptoms and for the partial correlation in the context of the full model. OTHER RESULTS The greatest amount of variance in eye symptoms was accounted for by the lighting question. Blocking the lights with my hand is noticeably more comfortable. THE LIGHTING QUESTION