Evaluation And Treatment Of A Heterogenous Group Of Chronic Pain Patients: Assessing The Effect Size Of Outcome Measures

Abstract

The aim of the present study was to evaluate an array of psychometric tests administered to a heterogeneous group of chronic pain patients at pre- and post- treatment to determine the effect sizes of the measures. The sample included patients (N=312) who participated in an interdisciplinary treatment program, which included medical, psychological, psychiatric, and physical therapy components. This sample was narrowed to include only those who completed treatment (n=262). Subjects were evaluated on a variety of physical/functional, psychosocial, and coping measures, including the Visual Analog Scale (VAS), Million Visual Analog Scale (MVAS), Oswestry Low Back Pain Disability Questionnaire (OSW), Pain Medication Questionnaire (PMQ), Medical Outcomes Survey 36-Item Short Form Health Survey (SF-36), Beck Depression Inventory-II (BDI-II), and Multidimensional Pain Inventory (MPI). Paired sample t-tests were conducted to evaluate each measure for pre- to post-treatment change. These measures were further analyzed using Cohen's d (1992) to obtain the effect size. Results indicated that the instruments showing the greatest effect size were the VAS (d= 1.27) and the MVAS (d=0.94), both within the large effect size range. The OSW (d=0.67) showed a medium effect size, while the SF-36/PCS (d=0.19) had the lowest effect size of the physical measures. Results indicated a medium effect size for psychosocial measures. The PMQ (d=0.79) BDI-II (d=0.72) and the SF-36/MCS (d=0.62). The MPI exhibited an extremely low effect size (d=0.03). The heterogeneous population was also broken down into three categories of pain diagnoses including musculoskeletal, all other single pain diagnoses (e.g. headache, neuropathy, reflex sympathetic dystrophy, firbomyalgia), and multiple diagnoses (more than one type of pain). Overall, this study offers information on the effect sizes of different measures in order to facilitate the decision making process when selecting assessment tools to use with chronic pain populations, and supports the use of multiple assessment measures.