TY - JOUR
T1 - Improving the interpretation of quality of life evidence in meta-analyses
T2 - the application of minimal important difference units
AU - Johnston, Bradley C.
AU - Thorlund, Kristian
AU - Schünemann, Holger J.
AU - Xie, Feng
AU - Murad, Mohammad H.
AU - Montori, Victor M.
AU - Guyatt, Gordon H.
N1 - Funding Information:
We are indebted to and would like to acknowledge Dr. Ian Shrier for providing us with the original idea to standardize mean differences by minimal important difference units. BCJ holds a Post-Doctoral Fellowship from the SickKids Foundation. KT holds a CANNeCTIN Biostatistics Doctoral Award. HJS holds the Michael Gent Chair in Healthcare Research.
PY - 2010/10/11
Y1 - 2010/10/11
N2 - Systematic reviews of randomized trials that include measurements of health-related quality of life potentially provide critical information for patient and clinicians facing challenging health care decisions. When, as is most often the case, individual randomized trials use different measurement instruments for the same construct (such as physical or emotional function), authors typically report differences between intervention and control in standard deviation units (so-called "standardized mean difference" or "effect size"). This approach has statistical limitations (it is influenced by the heterogeneity of the population) and is non-intuitive for decision makers. We suggest an alternative approach: reporting results in minimal important difference units (the smallest difference patients experience as important). This approach provides a potential solution to both the statistical and interpretational problems of existing methods.
AB - Systematic reviews of randomized trials that include measurements of health-related quality of life potentially provide critical information for patient and clinicians facing challenging health care decisions. When, as is most often the case, individual randomized trials use different measurement instruments for the same construct (such as physical or emotional function), authors typically report differences between intervention and control in standard deviation units (so-called "standardized mean difference" or "effect size"). This approach has statistical limitations (it is influenced by the heterogeneity of the population) and is non-intuitive for decision makers. We suggest an alternative approach: reporting results in minimal important difference units (the smallest difference patients experience as important). This approach provides a potential solution to both the statistical and interpretational problems of existing methods.
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U2 - 10.1186/1477-7525-8-116
DO - 10.1186/1477-7525-8-116
M3 - Article
C2 - 20937092
AN - SCOPUS:77957660942
SN - 1477-7525
VL - 8
JO - Health and Quality of Life Outcomes
JF - Health and Quality of Life Outcomes
M1 - 116
ER -