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The Clinical Utility of the Multidimensional Pain Inventory (MPI) in Characterizing Chronic Disabling Occupational Musculoskeletal Disorders.
- Source :
- Journal of Occupational Rehabilitation; Jun2013, Vol. 23 Issue 2, p239-247, 9p
- Publication Year :
- 2013
-
Abstract
- Purpose The Multidimensional Pain Inventory (MPI) was designed to help capture unique characteristics of chronic pain patients. The present study examined the proportion of subgroups classified by the MPI in a chronic disabling occupational musculoskeletal disorder (CDOMD) patient cohort, and described characteristics of MPI profile groups in terms of other psychosocial variables. Methods A cohort of 1,270 CDOMD patients undergoing an interdisciplinary functional restoration program was studied. Before the start of the program, all patients received a standard psychosocial assessment battery. A MPI computer program scored and identified pre-defined MPI subgroups: Adaptive Coper (AC); Interpersonally Distressed (ID); and Dysfunctional (DYS). Results The distribution of MPI profiles for CDOMD patients was similar with those of highly disabled patients, with the largest proportion of patients having the DYS profile (44 %), followed by AC (33 %) and ID (23 %). The DYS profile group showed the highest level of pain severity, and psychosocial distress; the ID group had a moderate level; and the AC profile group had the lowest level. Higher rates of psychiatric disorders were also found in the DYS and ID groups. The DYS profile group was less likely to complete the treatment program. Conclusion The present study further demonstrated the clinical utility of the MPI classification in a large cohort of CDOMD patients, indicating that the MPI profiles successfully distinguish among patients who may require extra psychosocial attention to achieve successful treatment gains and program completion. [ABSTRACT FROM AUTHOR]
- Subjects :
- CHRONIC pain & psychology
PSYCHOLOGICAL adaptation
ANALYSIS of variance
CHI-squared test
CHRONIC pain
EMPLOYMENT
LONGITUDINAL method
MULTIVARIATE analysis
MUSCULOSKELETAL system diseases
OCCUPATIONAL diseases
PROBABILITY theory
PSYCHOLOGICAL tests
QUESTIONNAIRES
STATISTICS
VOCATIONAL rehabilitation
WORK capacity evaluation
DATA analysis
EFFECT sizes (Statistics)
PAIN measurement
DATA analysis software
DISEASE complications
Subjects
Details
- Language :
- English
- ISSN :
- 10530487
- Volume :
- 23
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Journal of Occupational Rehabilitation
- Publication Type :
- Academic Journal
- Accession number :
- 87799117
- Full Text :
- https://doi.org/10.1007/s10926-012-9393-x