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A New Zealand replication of the IPAM clustering model for low back patients.

作者信息

Strong J, Large R G, Ashton R, Stewart A

机构信息

Department of Occupational Therapy, University of Queensland, Brisbane, Australia.

出版信息

Clin J Pain. 1995 Dec;11(4):296-306. doi: 10.1097/00002508-199512000-00007.

Abstract

OBJECTIVE

This study examined the reliability of the three-cluster model for chronic low back pain patients found using the Integrated Psychosocial Assessment Model (IPAM). A replication study using a sample of patients from a different country was completed.

PATIENTS

Seventy patients (average age = 47.05 years, SD = 16.11) with chronic low back pain of noncancer origin participated in the study. Sixty-two of these patients were attending The Auckland New Zealand Regional Pain Service, while a further eight were attending a private practice pain service in Auckland.

OUTCOME MEASURES

Subjects were assessed on the IPAM, which measures pain intensity, disability, coping strategies, attitudes towards and beliefs about pain, depression and illness behaviour, the Medical Examination and Diagnostic Information Coding System, and the Multidimensional Pain Inventory.

RESULTS

Cluster analyses using the kappa-means algorithm were performed on the IPAM data. The three-cluster solution was preferred according to both the Variance Ratio Criterion and cluster interpretability. Two of the three clusters correlated highly with clusters retrieved in the original study (r = 0.78, r = 0.71), while the third cluster showed partial resemblance (correlation of r = 0.31). Clusters were named "In Control," "Depressed and Disabled," and "High Deniers and Somatizisers." No differences were found on the physical pathology scores between clusters. Decision rules for cluster assignation resulted in 68% of the sample being correctly assigned.

CONCLUSIONS

Support for this cluster model from two countries suggests its value in providing a multidimensional picture of patients with chronic low back pain. The possibility of using such cluster groups for determining treatment type is discussed.

摘要

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