A multicountry comparative survey about organizational resilience in anaesthesia

J Eval Clin Pract. 2018 Dec;24(6):1347-1357. doi: 10.1111/jep.13054. Epub 2018 Oct 18.

Abstract

Rationale, aims, and objectives: The application of resilience in health care requires the shift from a cause-effect approach to a systemic approach, yet few tools have been developed to measure resilience potential in this specific context. This study tests a resilience assessment grid (RAG) questionnaire to measure the resilience of anaesthesiologists, with a cross-country survey.

Method: A study was conducted with an analytic hierarchy process (AHP) questionnaire containing 57 detailed questions; 16 nations and 172 respondents were involved in the study. The data were statistically analysed to identify insights from the questionnaire, main improvements for further assessment, and confirmation of the design of the questionnaire. The questionnaire reliability was assessed by Cronbach analysis. Weak items were identified by a detailed correlations analysis and through a weight-polarization matrix. Construct validity was confirmed by principal component analysis (PCA) and factor analysis (FA).

Results: The α level of Cronbach analysis is 0.910. PCA and FA confirmed the absence of underlying unexpected factors, with less than 8% from the first factor and a total of just 54% of variability explained by 17 factors. Suggestions for revising the questionnaire ensue from the analysis, with improvements for the questionnaire's significance.

Conclusion: The questionnaire shows the potential to assess proxy measures of resilience, even confirming the relevance of a structured weighting approach based on the AHP. The exemplar statistical cross-country analyses encourage the widespread use of a centralized resilience questionnaire to support standardized analyses and the diffusion of best practices among organizations.

Keywords: AHP; RAG; anaesthesia; questionnaire; resilience.

MeSH terms

  • Adult
  • Anesthesiologists / psychology*
  • Cross-Cultural Comparison*
  • Cross-Sectional Studies
  • Factor Analysis, Statistical
  • Female
  • Humans
  • Learning
  • Male
  • Middle Aged
  • Principal Component Analysis
  • Psychometrics
  • Reproducibility of Results
  • Resilience, Psychological*
  • Surveys and Questionnaires / standards*