Spatial patterning of occupational stress and its related factors in Iranian critical care nurses using a hierarchical Bayesian technique

Abstract

BACKGROUND: In each community, health problems’ patterns and geographical changes are of prime importance to determine high and low-risk areas. OBJECTIVES: This study aimed to investigate the Spatial patterning of occupational stress and its related factors in Iranian critical care nurses using a hierarchical Bayesian technique METHODS: The current research was a cross-sectional descriptive-analytical study. The data includes the number of critical care unit nurses who show a high stress level based on a questionnaire. We used variables such as age, gender, collaboration status, working time, marital status, clinical experience, education, supervisor support, stress score, and working on holiday days for this study. The survey participants had to be at least 18 years old, a registered nurse, and working in the intensive care unit (ICU). OpenBUGS version 3.2.3 was used to implement the Bayesian hierarchical Poisson model and find partial patterning of occupational stress and its related factors. RESULTS: The final sample size was 17414 nurses. The overall prevalence of occupational stress in ICU nurses was estimated at 70%. The lowest and highest prevalence was 65.8% in the North Khorasan province and 75.2% in Golestan province. Occupational stress had a statistically significant association with collaboration status, but with demographic variables, shift work, supportive supervisor, and working on holidays had no statistically significant association. CONCLUSIONS: According to the findings, it is necessary to eliminate or reduce job stress and increase efficiency in Iranian nurses, encourage teamwork and collaboration as an essential element of a healthy workplace environment.