PURPOSE: To model the effects of computer use on reported visual and physical symptoms and to measure the effects upon quality of life measures. METHODS: 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-reported eye symptoms are associated with perceived quality of life. The study also explored the factors that are associated with eye symptoms. Structural equation modeling and multiple regression analyses were used to assess the hypotheses. RESULTS: Seventy percent of the employees used some form of vision correction during computer use, 2.9% used glasses specifically prescribed for computer use, and 8% had had refractive surgery. Employees spent an average of 6 h per day at the computer. In a multiple regression framework, the latent variable eye symptoms was significantly associated with a composite quality of life variable (p = 0.02) 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. After adjusting for age, gender, ergonomics, hours at the computer, and exercise, eye symptoms were significantly associated with physical symptoms (p < 0.001) accounting for 48% of the variance. CONCLUSIONS: Environmental variability at work was associated with eye symptoms and eye symptoms demonstrated a significant impact on quality of life and physical symptoms.
PURPOSE: To model the effects of computer use on reported visual and physical symptoms and to measure the effects upon quality of life measures. METHODS: 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-reported eye symptoms are associated with perceived quality of life. The study also explored the factors that are associated with eye symptoms. Structural equation modeling and multiple regression analyses were used to assess the hypotheses. RESULTS: Seventy percent of the employees used some form of vision correction during computer use, 2.9% used glasses specifically prescribed for computer use, and 8% had had refractive surgery. Employees spent an average of 6 h per day at the computer. In a multiple regression framework, the latent variable eye symptoms was significantly associated with a composite quality of life variable (p = 0.02) 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. After adjusting for age, gender, ergonomics, hours at the computer, and exercise, eye symptoms were significantly associated with physical symptoms (p < 0.001) accounting for 48% of the variance. CONCLUSIONS: Environmental variability at work was associated with eye symptoms and eye symptoms demonstrated a significant impact on quality of life and physical symptoms.
Authors: P Ranasinghe; W S Wathurapatha; Y S Perera; D A Lamabadusuriya; S Kulatunga; N Jayawardana; P Katulanda Journal: BMC Res Notes Date: 2016-03-09