Measuring job satisfaction among healthcare staff in the United States: a confirmatory factor analysis of the Satisfaction of Employees in Health Care (SEHC) survey

Int J Qual Health Care. 2017 Apr 1;29(2):262-268. doi: 10.1093/intqhc/mzx012.

Abstract

Objective: To validate the Satisfaction of Employees in Health Care (SEHC) survey with multidisciplinary, healthcare staff in the United States (U.S.).

Design: A cross-sectional psychometric study using confirmatory factor analysis. The original three-factor model was tested and modified using half-samples. Models were assessed using goodness-of-fit measures. Scale reliability and validity were tested with Cronbach's α coefficient and correlation of total SEHC score with two global satisfaction items, respectively.

Setting: We administered a web-based survey from January to May 2015 to healthcare staff participating in initiatives aimed at delivering better care and reducing costs.

Participants: The overall response rate was 38% (N = 1089), and respondents were from 86 healthcare projects. A total of 928 respondents completed the SEHC survey in full and were used in this study.

Main outcome measures: Model fit of 18 SEHC items and total SEHC score.

Results: The mean SEHC score was 77.6 (SD: 19.0). A one-factor model of job satisfaction had high loadings on all items, and demonstrated adequate model fit (second half-sample RMSEA: 0.069). The scale demonstrated high reliability (Cronbach's alpha = 0.942) and validity (r = 0.77 and 0.76, both P < 0.05).

Conclusions: The SEHC appears to measure a single general job satisfaction construct. The scale has adequate reliability and validity to recommend its use to assess satisfaction among multidisciplinary, U.S. healthcare staff. Our findings suggest that this survey is a good candidate for reduction to a short-form, and future research should validate this survey in other healthcare populations.

Keywords: confirmatory factor analysis; healthcare workforce/staff; job satisfaction.

MeSH terms

  • Cross-Sectional Studies
  • Factor Analysis, Statistical*
  • Health Personnel / psychology*
  • Health Personnel / statistics & numerical data
  • Humans
  • Job Satisfaction*
  • Psychometrics
  • Reproducibility of Results
  • Surveys and Questionnaires*
  • United States