An individual's ability to live independently is commonly measured in health research interested in identifying risk factors associated with disablement processes. In order to inform clinical practice, population research has attempted to identify the contraction of “lived-space” by using various survey instruments.Problem:
Studies assessing habitual movements over the environment with the Life-Space Assessment (LSA) survey instrument should carefully consider how the LSA Composite Score (LSA-CS) is computed. Until now, no publication has carefully delineated the assumptions guiding the internal logic used in the computation of the LSA-CS.Core argument:
Because the internal logic of the LSA may need further justification, a non-data-editing scoring algorithm should be considered.Solution:
Compute LSA-CS by only using non-edited data.Specific aim:
Paper first delineates the logic guiding the algorithm used in the formation of the LSA-CS and explains how the scoring creates and changes participant responses when they conflict with its internal logic. An easy-to-use SAS® 9.3 program for estimating a Non-Data-Edited LSA-CS (NDE-LSA-CS) is also presented.Conclusion:
Researchers interested in assessing lived-space should carefully consider if the internal logic of the LSA-CS is warranted. Clinicians should know it is important to understand the strengths and weaknesses of outcome measures used when deciding on whether to apply the results of research to direct clinical practice.