These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Nurse Burnout Revisited: A Comparison of Computational Methods.
    Author: Dutra HS, Guirardello EB, Li Y, Cimiotti JP.
    Journal: J Nurs Meas; 2019 Apr 01; 27(1):E17-E33. PubMed ID: 31068498.
    Abstract:
    BACKGROUND AND PURPOSE: To examine computational measures of job-related burnout to determine the best computation to estimate job satisfaction and intent to leave in Brazilian nursing professionals. METHODS: Maslach Burnout Inventory-Human Services Survey (MBI-HSS) was used assess burnout in 452 hospital-based nursing professionals. Adjusted logistic regression models were fit using different computations of burnout to estimate outcomes of interest. RESULTS: Total mean score of burnout subscales was the best estimate of job satisfaction (Cox-Snell R2 = 0.312; Nagelkerke R2 = 0.450) and intent to leave (Cox-Snell R2 = 0.156; Nagelkerke R2 = 0.300), as was high emotional exhaustion (Cox-Snell R2 = 0.219; Nagelkerke R2 = 0.316). CONCLUSION: We have provided evidence that different computations of data from the Portuguese (Brazil) MBI-HSS can be used in to estimate the effect of job-related burnout on nurse outcomes.
    [Abstract] [Full Text] [Related] [New Search]