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J Nurs Scholarsh. 2017 Sep;49(5):537-547. doi: 10.1111/jnu.12317. Epub 2017 Jul 12.

Nonlinear Analysis to Detect if Excellent Nursing Work Environments Have Highest Well-Being.

Author information

1
Doctoral student, University of Munich, Department of Statistics, Ludwigstr, Munich, Germany.
2
Full Professor, KU Leuven-University of Leuven, Leuven Biostatistics and Statistical Bioinformatics Centre, Leuven, Belgium.
3
Full Professor, University of Munich, Department of Statistics, Munich, Germany.
4
Post-doctoral researcher, KU Leuven-University of Leuven, Institute for Healthcare Policy, Leuven, Belgium.

Abstract

PURPOSE:

To detect potentially nonlinear associations between nurses' work environment and nurse staffing on the one hand and nurse burnout on the other hand.

DESIGN:

A cross-sectional multicountry study for which data collection using a survey of 33,731 registered nurses in 12 European countries took place during 2009 to 2010.

METHODS:

A semiparametric latent variable model that describes both linear and potentially nonlinear associations between burnout (Maslach Burnout Inventory: emotional exhaustion, depersonalization, personal accomplishment) and work environment (Practice Environment Scale of the Nursing Work Index: managerial support for nursing, doctor-nurse collegial relations, promotion of care quality) and staffing (patient-to-nurse ratio).

FINDINGS:

Similar conclusions are reached from linear and nonlinear models estimating the association between work environment and burnout. For staffing, an increase in the patient-to-nurse ratio is associated with an increase in emotional exhaustion. At about 15 patients per nurse, no further increase in emotional exhaustion is seen.

CONCLUSIONS:

Absence of evidence for diminishing returns of improving work environments suggests that continuous improvement and achieving excellence in nurse work environments pays off strongly in terms of lower nurse-reported burnout rates. Nurse staffing policy would benefit from a larger number of studies that identify specific minimum as well as maximum thresholds at which inputs affect nurse and patient outcomes.

CLINICAL RELEVANCE:

Nurse burnout is omnipresent and has previously been shown to be related to worse patient outcomes. Additional increments in characteristics of excellent work environments, up to the highest possible standard, correspond to lower nurse burnout.

KEYWORDS:

Bayesian models; latent variable models; nursing staff/psychology; professional burnout; statistical models; surveys and questionnaires; workplace

PMID:
28700123
DOI:
10.1111/jnu.12317
[Indexed for MEDLINE]

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