Prospective validity assessment of a friction prediction model based on tread outsole features of slip-resistant shoes

Abstract

Shoe outsole design strongly influences slip and fall risk. Certain tread features that can be readily measured have been shown to predict friction performance. This research aimed to replicate those findings and quantify their ability to predict slipping. Participants (n = 34) were exposed to a low friction oil-coated floor surface, while wearing slip-resistant shoes. The coefficient of friction (COF) of each shoe were predicted based on tread surface area, the presence of a bevel, and hardness. The COF was measured, and the slip outcome was determined. Predicted and measured COF were correlated, and measured COF was a sensitive predictor of slip outcome. The relationship of predicted COF on slip outcome was weaker than anticipated and was not statistically significant. This study partially confirmed the ability of previous regression equations to predict COF. However, the effect size was weaker than previously reported and predicted COF was not sensitive for predicting slips.

Keywords: And falls; Footwear; Friction; Slips; Trips.

Figure 1:

The test used to assess whether shoes contained a bevel. The back of the heel and the back of the USB latches (rectangular holes) were aligned with the side of a table. If there was enough space to accommodate the portion of the USB port in front of the latches, the shoe was considered to be beveled.

Figure 2:

The logistic regression plot for the univariate analysis where slip outcome is fit by the predicted COF values from the model. Each point represents the outcome from an individual participant, while the line represents the fit line.

Figure 3:

A: Scatter plot of the measured COF plotted against the predicted COF. The black line represents the linear fit (r = 0.5). B: The logistic regression analysis between the measured COF and the slip outcome.