Do employees' work schedules put them at-risk? The role of shift scheduling and holidays in predicting near miss and incident likelihood. (December 2022)

• Record Type: Journal Article
• Authors: Laske, Matthew M.; Hinson, Philip E.; Acikgoz, Yalcin; Ludwig, Timothy D.; Foreman, Anne M.; Bergman, Shawn M.
• Is Part Of: Journal of safety research. Volume 83(2022)
• Page Start: 1
• Page End: 7
• Publication Date: 2022-12
• Subjects: Shift-schedule -- Consecutive shifts -- Holiday schedule -- Injury prediction -- Near miss prediction; Industrial safety -- Periodicals; Accidents -- Prevention -- Periodicals; Safety -- Periodicals; Accidents, Occupational -- Periodicals; Sécurité du travail -- Périodiques; Accidents -- Prévention -- Périodiques; Accidents -- Prevention; Industrial safety; Periodicals; 363.1
• DOI: 10.1016/j.jsr.2022.07.015
• Languages: English
• ISSNs: 0022-4375

Abstract

Highlights: Working consecutive day shifts increases the probability of an incident occurring. Fourth consecutive day shift results in the most risk. The first and second shifts of a night schedule have a greater chance of incident. Shifts near holidays did not have a significantly higher risk than other shifts. Abstract: Introduction: Using crew scheduling and injury incident data from a Fortune 500 manufacturing company, this study analyzed the effect of consecutive shifts and shifts near holidays on near misses and incidents. Methods: Logistic regressions were conducted with consecutive workdays, days near holidays, and time of shift as predictors of incident and near miss outcomes. Results: The logistic regression analysis indicated that working consecutive day shifts increases the probability of an incident occurring, with the fourth consecutive shift resulting in the most risk. The consecutive shift pattern did not replicate to employees working the night shift. However, the first and second shifts when transferring to a night schedule appear to have a greater chance of incident. Shifts near holidays did not have a significantly higher risk than other shifts. Practical application: The current research suggests that organizations can use similar analytic techniques to determine if shift scheduling might be related to increased risk and allocate resources to mitigate hazards during those peak probability shifts.