The underlying study purpose was to design a system to collect data and then compare “with clinical balance scales in an attempt to identify fall status predictors.” The clinical balance scale used was the sit to stand (five times sit to stand test). This is not an independent measure of balance from the other parameters measured in the study that are based off the sit to stand. The relationship between LE power and fall risk (based on fall status) as represented in the above DAG specifically identifies decreased muscle force to decreased LE strength to decreased LE power to fall risk (assumed causal chain). Since power is both work and velocity then speed of movement is identified and adjusted for in the study (measured). Balance is related to speed of movement (including stabilizing from movement) and independently related to fall risk. By not measuring balance independent of speed of movement (that is adjustment for balance), balance becomes a confounder and without information about it we cannot know for sure what the impact of speed of movement or dec LE power is on fall risk. The authors simply point out that SP may be associated with balance but they cannot say more because balance was not assessed.
With the above DAG in existence (online here) it can be built on further. It can be used by researchers planning to do another study, modified when additional studies are reviewed, debated and discussed. All of the assumptions about causal associations become clear for further study, debate and discussion; and for the clinical practice side of KBP, for considering what to test clinically (abduction) and how to intervene (deduction). On the DAGitty site where the model is posted you can see the adjustment set (upper right), the DAGitty code (lower right) which can be cut and pasted into another DAGitty code window to make your own version for modification and saving if interested. The DAGitty repository is a nice way to share models that have been published, but I am working on another approach to organizing models for use by a broader community of physical therapy researchers using DAGitty for their research that allows searching and browsing of models by topic area, and then going back to DAGitty for development and modification.
As I read more research methods mid terms and come across more studies I will share when I can examples of DAGs and adjustment sets and how their use could be helpful moving forward. After all - there is a reason I identified DAGs and adjustment sets when asked to provide some posts on moving forward.