Novel low-error interpolation method for a fall prevention program using the single- subject design statistical model spre

Weissman-Miller, D. and Holmes, W.

Over 30% of adults, aged 65 and older, fall each year (Centers for Disease Control, 2015) and with an aging population, falls, fall related injuries, and costs have become a public health concern (Centers for Disease Control, 2015; Costello and E. Edelstein, 2008).  A fall prevention program, Stepping On®, is a multifaceted, multifactorial community-based program (Clemson, et al., 2004) that has been shown statistically by a new single-subject design model, SPRE (Weissman-Miller, 2013), to improve fall self-efficacy and reduce falls in elders over 13-14 sessions. The purpose of this research paper is to provide a low-error interpolation method so that SPRE can be used to predict the effectiveness of the Stepping On® program for older adults in seven weekly sessions. Stepping On® was delivered to a small group of community-dwelling older adults for seven weeks.  The pilot study data collection included a falls tracking form and Modified Falls Efficacy Scale completed at each session.  SPRE was utilized with the low-error interpolation method to provide 13 data points and data analyzed to allow researchers to identify each individual’s change point.  The low-error interpolation method is derived from numerical analysis and applied to the transformed original data to derive six computed interval data points for each participant, where the error function is very small.  Analysis with SPRE was completed for each of five participants. Ten months later, three of these participants’ results were reviewed.   The data suggests the Stepping On® program results in decreased fear of falling and increased falls self-efficacy. The low-error interpolated data provided statistically accurate results when used with the Stepping On® fall prevention program analyzed with SPRE in Health and Medical Sciences.

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