Back

An Occupational Health Survey for Port Employees in Shenzhen and A Dataset Management System based on R

Mo, C.; Wang, J.; Huang, Y.; Lin, D.; Situ, J.; Zhang, M.; Zhang, N.

2022-06-28 epidemiology
10.1101/2022.06.27.22276896 medRxiv
Show abstract

BackgroundPort employees is a huge occupational group in industrial economy but the occupational health problem does not receive enough attention and the relative data is still deficient. Hence, the aim of the study was to survey the occupational health condition for port employees and to construct a relative dataset. MethodA cross-sectional study was implemented among the population in a Shenzhen port, they were required to undergo occupational physical examination and questionnaires to learn about physical condition and other information. Description analysis were used to describe the data, and missing value analysis and Cronbachs alpha coefficient were utilized to evaluated the data quality. And management system based on Shiny was constructed to manage and analyze the dataset. ResultA total of 5245 participants involved in this study, 3211 of them received occupational physical examinations, 3946 participants received the questionnaire, and 1912 received the both. Quality analysis suggested that the total missing rate of these three datasets were 10.76%, 0% and 4.78%, respectively. And the total Cronbachs alpha confidence of Effort-Reward Imbalance Questionnaire and National Health Literacy Monitoring Questionnaire was 0.808. Furthermore, a dataset management system with preview overview, selection, output and summary functions was constructed. ConclusionOccupational Health Survey for Port Employees is a reliable survey and its system can be used to manage and analyze the dataset, however, further optimization and improvement are still required.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.