A model for predicting acute and chronic fatigue in Chinese nurses

Abstract

Aim: To explore a model designed to examine direct and indirect effects of variables on acute and chronic fatigue.

Background: Although influencing factors for fatigue have been studied extensively, direct and indirect effects of predictors for acute and chronic fatigue remain poorly understood. Therefore, we proposed an original prediction model for acute and chronic fatigue in Chinese nurses based on previous studies.

Design: Cross-sectional, descriptive, correlational design.

Methods: We used a multi-stage sampling process to finally include 581 nurses working in the general hospitals in Chengdu, China. Data were collected between November 2007-March 2008 by using questionnaires. A path analysis was applied to test the fit of the hypothesized model and analysis of variance.

Results: The final model fits the data well. A total of 44·8% of variance in acute fatigue was directly and indirectly explained by job demand, job control, support at work, exposure to hazards in work environments and sleep quality, and only indirectly influenced by intershift recovery and shift work. Moreover, 61·5% of total chronic fatigue was directly and indirectly accounted for by anxiety, depression, job dissatisfaction, intershift recovery, and acute fatigue, and only indirectly influenced by job control, support at work, exposure to hazards in work environments, shift work, and sleep quality.

Conclusion: Acute and chronic fatigue is affected by different factors and nurse managers should generate specific interventions to decrease them.