The purpose of this study was to examine the effects of shaft stiffness on puck velocity and response characteristics of carbon fibre composite ice hockey sticks during a slap shot. Six elite male ice hockey players performed six slap shots with four sticks of different shaft stiffness designated as medium (13 KN m–1), stiff (16 KN m–1), extra (17 KN m –1) and pro stiff (19 KN m–1). These four levels represent the range in stiffness of sticks available to hockey players. The mechanics of the slap shot were evaluated by recording the initial ground reaction forces and stick deformation from high‐speed filming and puck velocity from a radar gun. Data were analysed using a 3‐way repeated measures ANOVA for 7 dependent variables: puck velocity, peak Y (front–back) and Z (vertical) forces, times to achieve peak Y and Z forces, peak deflection and time to peak deflection of the shaft. Results indicated: (1) the stick with lowest shaft stiffness of 13 KN m–1 produced the highest puck velocity, the greatest amount of shaft deflection, the longest time to peak deflection and the lowest peak Z forces; (2) the times to obtain peak forces in the Y and Z directions were similar across the levels of shaft stiffness; (3) puck velocity was influenced by the interaction of subject and stiffness and (4) variability in performance measures across subjects was greater than the variability across stiffness. Future studies are needed to address the effects stick construction has on different shots and stick handling skills, as well as to investigate the specific influence that skill and strength of the player has on the stick’s response.

Wearable fitness devices have the potential to address some of the most challenging public health problems in the United States. But they also raise serious privacy concerns. The data they collect can be combined with personal information from other sources, raising the specter of discriminatory profiling, manipulative marketing, and data breaches. Yet, these devices fall between the cracks of a weak health privacy and a consumer protection system in the United States. This article offers key principles and critical issues that must be considered in order to develop effective privacy, equity, and consumer protections for the emerging digital health marketplace.

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The use of simulation as a modeling and analysis tool is wide spread. Simulation is an enabling tool for experimenting virtually on a validated computer environment. Often the underlying function for the results of a computer simulation experiment has too much curvature to be adequately modeled by a low order polynomial. In such cases finding an appropriate experimental design is not easy. This research uses prediction variance over the volume of the design region to evaluate computer simulation experiments assuming the modeler is interested in fitting a second order polynomial or a Gaussian Process model to the response data. Both space-filling and optimal designs are considered.