#Quality of life series

He stated that in the context of comparing group averages, a small effect size was 0.2, a medium was 0.5, and a large effect size was 0.8. Perhaps the earliest criterion for identifying important change was devised by Cohen, 6 who expressed differences as an effect size-the average change divided by the baseline SD. Approaches to Estimating the Minimally Important Difference

Finally, we will point out some circumstances that diverge from this consistency. We will argue that this convergence is not accidental, but is a direct consequence of the limit of human discrimination ability. We will show that a multiplicity of methods, using several different scales from time tradeoff to visual analogue, with the number of items ranging from 1 to more than 50, in a diversity of chronic conditions, led to remarkably similar estimates. 1,4,5 It is the thesis of the present article that there is more commonality than difference in the variety of approaches.

#Quality of life series

Certainly, some authors have noted that, over a series of studies with a diversity of conditions and age groups using disease-specific measures with 7-point response scales, the minimally important difference (MID) appears to fall consistently close to 0.5 points on the 7-point scale. However, there is some evidence that some of these various factors may have a relatively small impact on the magnitude of the minimal difference. Collectively, considering all these variables for each measure, this variation represents a prohibitive impediment to the successful implementation of HRQL endpoints in clinical research and practice. clinical staff) could potentially result in a different estimate of important change. testing the efficacy of an intervention) and the identity of the individual performing the assessment (patient vs. The intent of the analysis (making a diagnosis vs. Potential influences related to the questionnaire itself include the relative position of the individual on the HRQL scale (ie, floor and ceiling effects 3), the number of steps on the scale, the number of items, and so forth. It may potentially vary for different questionnaires, different diseases, and different demographic groups. The determination of the minimal level of real change for any HRQL scale can be a daunting task. 1 More recently, researchers have been devising methods to identify a minimal level of change consistent with real, as opposed to statistically significant, benefit. The interpretation of changes in health-related quality of life (HRQL) has been a research focus for more than a decade. In most circumstances, the threshold of discrimination for changes in health-related quality of life for chronic diseases appears to be approximately half a SD. An explanation for this consistency is that research in psychology has shown that the limit of peopleвЂ™s ability to discriminate over a wide range of tasks is approximately 1 part in 7, which is very close to half a SD. Population-based estimation procedures and brief follow-up were associated with smaller ESs, and acute conditions with larger ESs. Negative changes were not associated with larger ESs. There was no consistent relationship with factors such as disease-specific or generic instrument or the number of response options. Results.ДЇor all but 6 studies, the MID estimates were close to one half a SD (mean = 0.495, SD = 0.155). Thirty-eight studies fulfilled the criteria, resulting in 62 ESs. We conducted a systematic review of the literature to identify studies that computed an MID and contained sufficient information to compute an effect size (ES). To determine whether there is consistency in the magnitude of MID estimates from different instruments. A number of studies have computed the minimally important difference (MID) for health-related quality of life instruments.