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Pain Research and Management
Volume 16, Issue 4, Pages 239-244
http://dx.doi.org/10.1155/2011/873424
Original Article

Improving the Usefulness of the Multidimensional Pain Inventory

Jeffrey M McKillop1 and Warren R Nielson2

1Private Practice, London, Ontario, Canada
2Beryl and Richard Ivey Rheumatology Day Programs, St Joseph’s Health Care, London, Ontario, Canada

Copyright © 2011 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

BACKGROUND: The Multidimensional Pain Inventory (MPI) is a reliable and valid self-report instrument that measures the impact of pain on an individual’s life, quality of social support and general activity. Criticism of the MPI has focused on this instrument’s internal structure and the stability of its classification taxonomy.

OBJECTIVES: To determine whether empirical summary scales could be developed for the MPI based on a large sample of respondents diagnosed with fibromyalgia syndrome. It was hypothesized that summary scales would improve the psychometric quality of the MPI and increase the stability of respondents’ taxonomy profiles across time.

METHODS: Respondents completed the MPI on two occasions before their admission to a multidisciplinary pain management program.

RESULTS AND CONCLUSIONS: Based on principal components analysis, three summary scales were developed that reflected level of impairment, social support and activity. Summary scales possessed good psychometric qualities and, when cluster analyzed, replicated the MPI taxonomy. Exploratory analyses of the MPI taxonomy revealed that goodness-of-fit values generally became less reliable as respondent profiles approached the overall sample mean. When the relative distance between respondents fit to taxonomy profiles and the distance from the sample mean was considered, profile stability using summary scales was predicted with good precision. These results suggest that summary scales may enhance the usefulness of the MPI, and that the traditional method of determining profile fit within the MPI is not stable and needs to be reconsidered.