title: Baseline adjustment increases accurate interpretation of posturographic sway scores.
abstract: Postural steadiness may be quantified using posturographic sway measures. These measures are commonly used to differentiate between a person's baseline balance and balance related to some physiological condition. However, the difference in sway scores between the two conditions may be difficult to detect due to large inter-subject variation. We compared detection accuracy provided by three models that linearly regress a sway measure (mean distance, velocity, or frequency) on the effect of eye closure on balance (eyes open (EO) vs. eyes closed (EC)). In Model 1 the dependent variable is a single sway score (EO or EC), whereas in Models 2 and 3 it is a change score (EO-EO or EC-EO). The independent variable is always the group (group=0: EO or group=1: EC). Model 3 also accounts for the regression to the mean effect (RTM), by considering the baseline value (EO) as a covariate. When differentiating between EO and EC conditions, 94% accuracy can be achieved when using mean velocity as sway measure and either Model 2 or 3. Thus by adjusting for baseline score one increases the accurate interpretation of posturographic sway scores.
authors.affiliation: Department of Physics, University of Helsinki, Helsinki, Finland. Electronic address: aino.tietavainen@helsinki.fi.
authors.forename: A
authors.initials: A
authors.lastname: Tietäväinen
authors.affiliation: Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland. Electronic address: jukka.corander@helsinki.fi.
authors.forename: J
authors.initials: J
authors.lastname: Corander
authors.affiliation: Department of Physics, University of Helsinki, Helsinki, Finland. Electronic address: edward.haeggstrom@helsinki.fi.
authors.forename: E
authors.initials: E
authors.lastname: Hæggström
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D004856:Postural Balance / Q000502:physiology*; D011897:Random Allocation; D013647:Task Performance and Analysis
keywords: ANCOVA; Change score analysis; Linear regression; Postural steadiness; Regression to the mean