A systematic review of structural equation modelling in nursing research
Intended for healthcare professionals
Evidence and practice    

A systematic review of structural equation modelling in nursing research

Saeed Pahlevan Sharif Senior lecturer, Business school, Taylor’s University, Subang Jaya, Malaysia
Imtiaz Mostafiz PhD student, Taylor’s University, Subang Jaya, Malaysia
Vinitha Guptan Dean, Business school, Taylor’s University, Subang Jaya, Malaysia

Background A growing number of nursing studies have used structural equation modelling (SEM) analysis. However, there is little research assessing the use of SEM analysis in nursing research.

Aim To present a systematic review of nursing research that uses SEM.

Discussion The review revealed poor reporting of information about the determination of sample size, missing data, normality and outliers. Most studies neither computed composite reliability nor assessed convergent and discriminant validity. There was a lack of consistency in performing the analysis. Some of the studies conducted exploratory factor analysis before performing confirmatory factor analysis, without discussing its necessity. Although most studies declared the estimation method and software used, there were many that did not.

Conclusion Little information about the different steps of conducting SEM analysis was provided in the studies. Several weaknesses and areas of improvement for future empirical SEM studies were identified.

Implications for practice When conducting SEM, there are many issues that should be addressed. Overlooking these issues may invalidate findings. The results of this review provide nurse researchers with best practice guidelines for conducting SEM and pave the way for researchers to adopt this method in their studies.

Nurse Researcher. doi: 10.7748/nr.2018.e1577


Pahlevan Sharif S, Mostafiz I, Guptan V (2018) A systematic review of structural equation modelling in nursing research. Nurse Researcher. doi: 10.7748/nr.2018.e1577

Peer review

This article has been subject to external double-blind peer review and has been checked for plagiarism using automated software



Conflict of interest

None declared

Published online: 12 September 2018

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