Predicting nurse fatigue from measures of work demands

Appl Ergon. 2021 Apr:92:103337. doi: 10.1016/j.apergo.2020.103337. Epub 2020 Nov 29.

Abstract

Fatigue arising from excessive work demands is a known safety challenge in hospital nurses. This study aimed to determine which measures of work demands during nursing work are most predictive of hospital nurse fatigue levels at the end of the work shift. Measures of work demands of registered nurses from two hospital units in the United States were collected from organizational data sources, wearable sensors, and questionnaires. Fatigue levels were measured at the start and end of each shift using the Brief Fatigue Inventory. Multilevel linear regression analysis was used to predict end of shift fatigue based on work demand variables. The best fit model included multiple variables from organizational data sources and a physical activity variable measured by a wearable sensor. Organizational data can be used to create dynamic measures of work demands as they occur and predict end of shift fatigue levels in hospital nurses.

Keywords: Fatigue; Nurses; Work demands.

MeSH terms

  • Fatigue
  • Humans
  • Nursing Staff, Hospital*
  • Surveys and Questionnaires
  • United States