Confirmatory factor analysis and sample invariance of the Chinese Patient Satisfaction Questionnaire (ChPSQ-9) among patients with breast and lung cancer

Value Health. 2009 Jun;12(4):597-605. doi: 10.1111/j.1524-4733.2008.00480.x. Epub 2009 Jan 21.

Abstract

Objectives: Previous exploratory factor analysis of the 9-item Chinese Patient Satisfaction Questionnaire (ChPSQ-9) identified two dominant factors: doctor and nurse. The present study employed confirmatory factor analysis (CFA) to examine the factorial invariance of the ChPSQ-9 between and within samples of Chinese patients with breast or lung cancer.

Methods: Longitudinal data were analyzed from Chinese breast and lung cancer patients who had completed the ChPSQ-9 during their first outpatient visit, at 3 months, and at 6 months after baseline. CFAs tested the fit of a one-factor model, a hierarchical model that comprised a general latent factor and two first-order factors, and a correlated model that comprised two correlated first-order factors to the data. The factorial invariance of the ChPSQ-9 between six independent samples across time was investigated using multigroup CFAs.

Results: The CFA's results demonstrated a better fit of the correlated model over the one-factor model and the hierarchical model in the breast and lung cancer samples. The correlated model showed evidence of cross-sample and longitudinal factorial invariance. Patients were generally satisfied with services provided by doctors and nurses. Internal consistency of the scale was also good for both cancer samples across time.

Conclusions: The ChPSQ-9 is a valid and reliable instrument to be employed among breast and lung cancer patients, in clinical settings or intervention research, to evaluate group differences in patient satisfaction and its association with intervention effectiveness.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms*
  • China
  • Factor Analysis, Statistical*
  • Female
  • Humans
  • Longitudinal Studies
  • Lung Neoplasms*
  • Male
  • Middle Aged
  • Models, Statistical
  • Nurses
  • Patient Satisfaction / statistics & numerical data*
  • Physicians
  • Reproducibility of Results
  • Statistics as Topic
  • Surveys and Questionnaires / standards*