The use and reporting of cluster analysis in health psychology: a review

Br J Health Psychol. 2005 Sep;10(Pt 3):329-58. doi: 10.1348/135910705X25697.


Purpose: Cluster analysis is a collection of relatively simple descriptive statistical techniques with potential value in health psychology, addressing both theoretical and practical problems. There are many methods of cluster analysis from which to choose, with no clear guidelines to aid researchers. In the absence of guidelines it is likely that methods already reported by published researchers will be adopted, and so clear reporting of statistical methodology, while always important, is particularly crucial with cluster analysis. The aim of this review is to describe and evaluate the reporting of cluster analysis in health psychology publications.

Methods: Electronic searches of 18 health psychology journals identified 59 articles using cluster analysis published between 1984 and 2002. Articles were submitted to systematic evaluation against published criteria for the reporting of cluster analysis.

Results: Just 27% of the papers reviewed met all five criteria, although 61% met at least four. Details of the similarity measure and the computer program used were most frequently omitted. Furthermore, while researchers usually reported the procedures employed to determine the number of clusters and to validate the clusters, these procedures were often lacking in rigour, and were reported in insufficient detail for replication.

Conclusions: The reporting of cluster analysis was found to be generally unsatisfactory, with many studies failing to provide enough information to allow replication or the evaluation of the quality of the research. Clear guidelines for conducting and reporting cluster analyses in health psychology are needed.

MeSH terms

  • Behavioral Medicine / statistics & numerical data*
  • Cluster Analysis*
  • Humans
  • Mathematical Computing
  • Periodicals as Topic
  • Reproducibility of Results
  • Research Design / statistics & numerical data
  • Research* / statistics & numerical data
  • Software