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      Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change


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          Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes.

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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 Lower Extremity Functional Scale (LEFS): scale development, measurement properties, and clinical application. North American Orthopaedic Rehabilitation Research Network.

            The purpose of this study was to assess the reliability, construct validity, and sensitivity to change of the Lower Extremity Functional Scale (LEFS). The LEFS was administered to 107 patients with lower-extremity musculoskeletal dysfunction referred to 12 outpatient physical therapy clinics. The LEFS was administered during the initial assessment, 24 to 48 hours following the initial assessment, and then at weekly intervals for 4 weeks. The SF-36 (acute version) was administered during the initial assessment and at weekly intervals. A type 2,1 intraclass correlation coefficient was used to estimate test-retest reliability. Pearson correlations and one-way analyses of variance were used to examine construct validity. Spearman rank-order correlation coefficients were used to examine the relationship between an independent prognostic rating of change for each patient and change in the LEFS and SF-36 scores. Test-retest reliability of the LEFS scores was excellent (R = .94 [95% lower limit confidence interval (CI) = .89]). Correlations between the LEFS and the SF-36 physical function subscale and physical component score were r=.80 (95% lower limit CI = .73) and r = .64 (95% lower limit CI = .54), respectively. There was a higher correlation between the prognostic rating of change and the LEFS than between the prognostic rating of change and the SF-36 physical function score. The potential error associated with a score on the LEFS at a given point in time is +/-5.3 scale points (90% CI), the minimal detectable change is 9 scale points (90% CI), and the minimal clinically important difference is 9 scale points (90% CI). The LEFS is reliable, and construct validity was supported by comparison with the SF-36. The sensitivity to change of the LEFS was superior to that of the SF-36 in this population. The LEFS is efficient to administer and score and is applicable for research purposes and clinical decision making for individual patients.
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              Determining a minimal important change in a disease-specific Quality of Life Questionnaire.

              This study was carried out to determine whether the minimal important difference, in evaluative quality of life instruments which use a 7-point scale, is similar across individual domains and for both improvement and deterioration. Thirty nine adults with asthma were studied, using an 8 week cohort with assessments at 0, 4 and 8 weeks. The outcomes were the Asthma Quality of Life Questionnaire and global rating of change. For overall asthma-specific quality of life and for all individual domains (activities, emotions, symptoms), the minimal important difference of quality of life score per item was very close to 0.5 (range: 0.42-0.58); differences of approximately 1.0 represented a moderate change (range: 0.77-1.51); differences greater than 1.5 represented large changes. Changes for improvement and deterioration were very similar. The changes in quality of life score that represent a minimal important difference are very similar to those observed for other evaluative instruments. The observation that the minimal important difference is consistent across domains and for both improvement and deterioration will facilitate interpretation of results of studies examining quality of life.

                Author and article information

                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central (London )
                22 August 2006
                : 4
                : 54
                [1 ]EMGO Institute, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
                Copyright © 2006 de Vet 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.

                : 26 July 2006
                : 22 August 2006

                Health & Social care
                Health & Social care


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