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      Responsiveness of five condition-specific and generic outcome assessment instruments for chronic pain

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          Abstract

          Background

          Changes of health and quality-of-life in chronic conditions are mostly small and require specific and sensitive instruments. The aim of this study was to determine and compare responsiveness, i.e. the sensitivity to change of five outcome instruments for effect measurement in chronic pain.

          Methods

          In a prospective cohort study, 273 chronic pain patients were assessed on the Numeric Rating Scale (NRS) for pain, the Short Form 36 (SF-36), the Multidimensional Pain Inventory (MPI), the Hospital Anxiety and Depression Scale (HADS), and the Coping Strategies Questionnaire (CSQ). Responsiveness was quantified by effect size (ES) and standardized response mean (SRM) before and after a four week in-patient interdisciplinary pain program and compared by the modified Jacknife test.

          Results

          The MPI measured pain more responsively than the SF-36 (ES: 0.85 vs 0.72, p = 0.053; SRM: 0.72 vs 0.60, p = 0.027) and the pain NRS (ES: 0.85 vs 0.62, p < 0.001; SRM: 0.72 vs 0.57, p = 0.001). Similar results were found for the dimensions of role and social interference with pain. Comparison in function was limited due to divergent constructs. The responsiveness of the MPI and the SF-36 was equal for affective health but both were better than the HADS (e.g. MPI vs HADS depression: ES: 0.61 vs 0.43, p = 0.001; SF-36 vs HADS depression: ES: 0.54 vs 0.43, p = 0.004). In the "ability to control pain" coping dimension, the MPI was more responsive than the CSQ (ES: 0.46 vs 0.30, p = 0.011).

          Conclusion

          The MPI was most responsive in all comparable domains followed by the SF-36. The pain-specific MPI and the generic SF-36 can be recommended for comprehensive and specific bio-psycho-social effect measurement of health and quality-of-life in chronic pain.

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          Most cited references39

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            The West Haven-Yale Multidimensional Pain Inventory (WHYMPI).

            The complexity of chronic pain has represented a major dilemma for clinical researchers interested in the reliable and valid assessment of the problem and the evaluation of treatment approaches. The West Haven-Yale Multidimensional Pain Inventory (WHYMPI) was developed in order to fill a widely recognized void in the assessment of clinical pain. Assets of the inventory are its brevity and clarity, its foundation in contemporary psychological theory, its multidimensional focus, and its strong psychometric properties. Three parts of the inventory, comprised of 12 scales, examine the impact of pain on the patients' lives, the responses of others to the patients' communications of pain, and the extent to which patients participate in common daily activities. The instrument is recommended for use in conjunction with behavioral and psychophysiological assessment strategies in the evaluation of chronic pain patients in clinical settings. The utility of the WHYMPI in empirical investigations of chronic pain is also discussed.
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              Effect sizes for interpreting changes in health status.

              Health status measures are being used with increasing frequency in clinical research. Up to now the emphasis has been on the reliability and validity of these measures. Less attention has been given to the sensitivity of these measures for detecting clinical change. As health status measures are applied more frequently in the clinical setting, we need a useful way to estimate and communicate whether particular changes in health status are clinically relevant. This report considers effect sizes as a useful way to interpret changes in health status. Effect sizes are defined as the mean change found in a variable divided by the standard deviation of that variable. Effect sizes are used to translate "the before and after changes" in a "one group" situation into a standard unit of measurement that will provide a clearer understanding of health status results. The utility of effect sizes is demonstrated from four different perspectives using three health status data sets derived from arthritis populations administered the Arthritis Impact Measurement Scales (AIMS). The first perspective shows how general and instrument-specific benchmarks can be developed and how they can be used to translate the meaning of clinical change. The second perspective shows how effect sizes can be used to compare traditional clinical measures with health status measures in a standard clinical drug trial. The third application demonstrates the use of effect sizes when comparing two drugs tested in separate drug trials and shows how they can facilitate this type of comparison. Finally, our health status results show how effect sizes can supplement standard statistical testing to give a more complete and clinically relevant picture of health status change. We conclude that effect sizes are an important tool that will facilitate the use and interpretation of health status measures in clinical research in arthritis and other chronic diseases.
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                Author and article information

                Journal
                BMC Med Res Methodol
                BMC Medical Research Methodology
                BioMed Central
                1471-2288
                2008
                25 April 2008
                : 8
                : 26
                Affiliations
                [1 ]Research department, Rehaclinic Zurzach, Bad Zurzach, Switzerland
                [2 ]Department of Epidemiology and Caphri Research Institute, Maastricht University, Maastricht, The Netherlands
                Article
                1471-2288-8-26
                10.1186/1471-2288-8-26
                2386498
                18439285
                28b6a1e7-56ac-46ef-bc4b-efb602f754cd
                Copyright © 2008 Angst et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 5 December 2007
                : 25 April 2008
                Categories
                Research Article

                Medicine
                Medicine

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