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      Responsiveness and minimal clinically important difference for pain and disability instruments in low back pain patients


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          The choice of an evaluative instrument has been hampered by the lack of head-to-head comparisons of responsiveness and the minimal clinically important difference (MCID) in subpopulations of low back pain (LBP). The objective of this study was to concurrently compare responsiveness and MCID for commonly used pain scales and functional instruments in four subpopulations of LBP patients.


          The Danish versions of the Oswestry Disability Index (ODI), the 23-item Roland Morris Disability Questionnaire (RMQ), the physical function and bodily pain subscales of the SF36, the Low Back Pain Rating Scale (LBPRS) and a numerical rating scale for pain (0–10) were completed by 191 patients from the primary and secondary sectors of the Danish health care system. Clinical change was estimated using a 7-point transition question and a numeric rating scale for importance. Responsiveness was operationalised using standardardised response mean (SRM), area under the receiver operating characteristic curve (ROC), and cut-point analysis. Subpopulation analyses were carried out on primary and secondary sector patients with LBP only or leg pain +/- LBP.


          RMQ was the most responsive instrument in primary and secondary sector patients with LBP only (SRM = 0.5–1.4; ROC = 0.75–0.94) whereas ODI and RMQ showed almost similar responsiveness in primary and secondary sector patients with leg pain (ODI: SRM = 0.4–0.9; ROC = 0.76–0.89; RMQ: SRM = 0.3–0.9; ROC = 0.72–0.88). In improved patients, the RMQ was more responsive in primary and secondary sector patients and LBP only patients (SRM = 1.3–1.7) while the RMQ and ODI were equally responsive in leg pain patients (SRM = 1.3 and 1.2 respectively). All pain measures demonstrated almost equal responsiveness. The MCID increased with increasing baseline score in primary sector and LBP only patients but was only marginally affected by patient entry point and pain location. The MCID of the percentage change score remained constant for the ODI (51%) and RMQ (38%) specifically and differed in the subpopulations.


          RMQ is suitable for measuring change in LBP only patients and both ODI and RMQ are suitable for leg pain patients irrespectively of patient entry point. The MCID is baseline score dependent but only in certain subpopulations. Relative change measured using the ODI and RMQ was not affected by baseline score when patients quantified an important improvement.

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          Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.
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            Measurement of health status. Ascertaining the minimal clinically important difference.

            In recent years quality of life instruments have been featured as primary outcomes in many randomized trials. One of the challenges facing the investigator using such measures is determining the significance of any differences observed, and communicating that significance to clinicians who will be applying the trial results. We have developed an approach to elucidating the significance of changes in score in quality of life instruments by comparing them to global ratings of change. Using this approach we have established a plausible range within which the minimal clinically important difference (MCID) falls. In three studies in which instruments measuring dyspnea, fatigue, and emotional function in patients with chronic heart and lung disease were applied the MCID was represented by mean change in score of approximately 0.5 per item, when responses were presented on a seven point Likert scale. Furthermore, we have established ranges for changes in questionnaire scores that correspond to moderate and large changes in the domains of interest. This information will be useful in interpreting questionnaire scores, both in individuals and in groups of patients participating in controlled trials, and in the planning of new trials.
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              The MOS 36-item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups.

              The widespread use of standardized health surveys is predicated on the largely untested assumption that scales constructed from those surveys will satisfy minimum psychometric requirements across diverse population groups. Data from the Medical Outcomes Study (MOS) were used to evaluate data completeness and quality, test scaling assumptions, and estimate internal-consistency reliability for the eight scales constructed from the MOS SF-36 Health Survey. Analyses were conducted among 3,445 patients and were replicated across 24 subgroups differing in sociodemographic characteristics, diagnosis, and disease severity. For each scale, item-completion rates were high across all groups (88% to 95%), but tended to be somewhat lower among the elderly, those with less than a high school education, and those in poverty. On average, surveys were complete enough to compute scales scores for more than 96% of the sample. Across patient groups, all scales passed tests for item-internal consistency (97% passed) and item-discriminant validity (92% passed). Reliability coefficients ranged from a low of 0.65 to a high of 0.94 across scales (median = 0.85) and varied somewhat across patient subgroups. Floor effects were negligible except for the two role disability scales. Noteworthy ceiling effects were observed for both role disability scales and the social functioning scale. These findings support the use of the SF-36 survey across the diverse populations studied and identify population groups in which use of standardized health status measures may or may not be problematic.

                Author and article information

                BMC Musculoskelet Disord
                BMC Musculoskeletal Disorders
                BioMed Central (London )
                25 October 2006
                : 7
                : 82
                [1 ]Clinical Locomotion Science, Institute of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
                [2 ]Nordic Institute of Chiropractic and Clinical Biomechanics, Odense, Denmark
                [3 ]Backcenter Funen, Ringe, Denmark
                [4 ]Department of Statistics, University of Southern Denmark, Odense, Denmark
                Copyright © 2006 Lauridsen 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.

                : 15 May 2006
                : 25 October 2006
                Research Article



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