Methodological Issues in Analyzing Real-World Longitudinal Occupational Health Data: A Useful Guide to Approaching the Topic

Abstract

Ever greater technological advances and democratization of digital tools such as computers and smartphones offer researchers new possibilities to collect large amounts of health data in order to conduct clinical research. Such data, called real-world data, appears to be a perfect complement to traditional randomized clinical trials and has become more important in health decisions. Due to its longitudinal nature, real-world data is subject to specific and well-known methodological issues, namely issues with the analysis of cluster-correlated data, missing data and longitudinal data itself. These concepts have been widely discussed in the literature and many methods and solutions have been proposed to cope with these issues. As examples, mixed and trajectory models have been developed to explore longitudinal data sets, imputation methods can resolve missing data issues, and multilevel models facilitate the treatment of cluster-correlated data. Nevertheless, the analysis of real-world longitudinal occupational health data remains difficult, especially when the methodological challenges overlap. The purpose of this article is to present various solutions developed in the literature to deal with cluster-correlated data, missing data and longitudinal data, sometimes overlapped, in an occupational health context. The novelty and usefulness of our approach is supported by a step-by-step search strategy and an example from the Wittyfit database, which is an epidemiological database of occupational health data. Therefore, we hope that this article will facilitate the work of researchers in the field and improve the accuracy of future studies.

Stress and job satisfaction over time, the influence of the managerial position: A bivariate longitudinal modelling of Wittyfit data

“…These two results suggest that the managerial position may act as a long-term factor in reducing stress and improving job satisfaction. Further analyses of the average changes in managers and the individual multi-trajectories of group 2 and group 3 especially, including the use of static covariates, could reveal the protective and risk factors associated with good occupational health of workers [ 41 ].…”

“…However, the database grows over the years [ 22 ], and further studies with larger populations and longer time periods could be designed to confirm or add to these initial results. It would also be very valuable to compare the results of this study, based on a real-world database and therefore constitutes real evidence, with those of a randomized clinical trial [ 41 ].…”

Work-related stress of companies' directors during the first lockdown due to the COVID-19

“…Future studies should also investigate more deeply psychosocial risk factors than we did with our single measure of stress using a single item. For example, using complementary validated questionnaires such as job-demand-control-support or effort-reward-imbalance models ( 41 ) may offer the possibility to build efficient preventive strategy, using predictive models ( 43 , 44 ). Our study may have practical implications considering the putative very long-term (several years) impact of the pandemic on mental health, as we demonstrated on other population during the SARS-CoV-1 epidemic in 2003 ( 45 ).…”