Multidimensional Pain Inventory: Revised Profile Classification Based on Clinical Observations in a Pain Setting
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Abstract
The purpose of this study was to build a new profile classification system for the Multidimensional Pain Inventory (MPI). According to some clinical researchers, the current profiles of the MPI do not fully portray how chronic pain patients evaluate and manage their pain because of the great variability in each subgroup. This study tried to revise the current profile classifications based on clinical observations, which may then lead to facilitate improved patient assessment, professional communication, and treatment planning. Participants, who completed pre- and post- treatment MPI measures, were randomly selected from the interdisciplinary program at the Eugene McDermott Center for Pain Management at UT Southwestern Medical Center at Dallas. Two hundred and eighty patients were then assigned to three different groups depending upon the re-coded scores from their pre-treatment MPI. Patients were grouped according to their MPI subscale scores. In order to determine if the hypotheses were supported or not, paired t-test were completed on six different psychosocial and functional outcome measures. Analyses were also conducted to check for differences among the nine different groups. As postulated, a number of significant relationships were identified. Paired t-test analyses demonstrated the significance of the relationship between certain MPI subscales. When Pain Severity (PS) and Interference (I) were below average (as determined by recoded T scores), patients had a good prognosis. When Life Control (LC) equaled Affective Distress (AD), participants were seen to have a good prognosis as well. Associations between the other MPI subscales were also assessed, but data did not support those hypotheses. The majority of the outcomes did not meet expectation, because of several limitations with the study design.