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A New Tool to Measure the Relationship between Health-Related Quality of Life and Workforce Productivity

Quality of life and productivity are two important measures in health outcomes that usually require the use of self-reported surveys for accurate assessment. Measuring health-related quality of life (HRQOL) has been established as an important field in the past century, and many psychometrically validated instruments exist for both general and specific population use. Another health measure that has attracted a significant amount of attention in recent years, although there is no gold standard, is that of workforce productivity. Most productivity studies measure the amount of work loss incurred by employees in the form of absenteeism and presenteeism.

A new survey that combines questions from existing HRQOL and workforce productivity surveys, the Health-Related Quality of Life and Work Productivity Questionnaire (HQWP), was constructed and tested using a descriptive, cross-sectional study of faculty and staff at a major research university. As expected, HRQOL and work loss were found to be negatively correlated. In addition, staff were found to have statistically higher levels of absenteeism than faculty, but faculty had higher levels of presenteeism. Using multivariate regression models on several measures of productivity, including both absenteeism and presenteeism, we concluded that mental health measures were stronger predictors of productivity than physical health measures for our overall sample, as well as faculty and staff groups separately. In addition, those who work extra hours to make up for lost production had significantly lower social function scores compared to those who do not. Other statistical analyses performed include PCA factor analyses on presenteeism covariates. Lastly, we performed economics analyses on the cost savings that could be achieved through health management programs to reduce absenteeism and presenteeism levels.

A better understanding of reasons for absenteeism and presenteeism could help inform targeted workplace programs to reduce employer indirect costs related to lost productivity. Moreover, such programs could reduce rates of turnover due to increased employee satisfaction, as well as improve both quantity and quality of life years.

Committee Members:
Brani Vidakovic, Ph.D. (Advisor)
Paula Edwards, Ph.D. (Co-Advisor)
Dave Goldsman, Ph.D.
Paul Griffin, Ph.D.
Eva Lee, Ph.D.

Principal Investigator: David Huang, Ph.D.

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