Analysis of effects and usage indicators for a ICT-based fall prevention system in community dwelling older adults

Falls are a serious problem in aging societies. A sedentary life style and low levels of physical activity are major factors aggravating older adults’ fall risk. Information and communication technology (ICT)-based fall prevention interventions are a promising approach to counteract the fall risk of this target group. For some time now, fall prevention interventions have put emphasize to video game based solutions, as video games have become more popular and accepted among older adults. Studies show that such ICT-based fall prevention interventions significantly reduce fall risk in older adults. Nevertheless, the population of older adults is fairly heterogeneous, and factors like gender, age, fitness, sociability, and so on may influence the use of such systems. Therefore, the analysis of subgroups is a common procedure to investigate the affects of various factors on the effectiveness of ICT-based systems. Many of these studies analyze the effectiveness of the system with quantitative measures only. However, the effectiveness of ICT-based fall prevention systems always depends on the sustainable system use by the target group. Qualitative analyses is generally the prime selection to identify determining usage indicators for system usage. Therefore, it seems likely that combined quantitative and qualitative investigations will generate detailed information about system effectiveness and relevant usage indicators for respective target groups. Here, we analyze the ICT-based fall prevention system, iStoppFalls, incorporating exergames and a mobility monitor as well, targeting three aims, (1) is the system effective for different subgroups of older adults, (2) what are the factors influencing fall risk reduction in older adults using the system and are there combined effects of exergaming and activity monitoring on fall risk reduction, and (3) which usage indicators explain the usage of such a system by older adults. This paper will provide a better understanding of the effectiveness of ICT-based fall prevention for different subgroups and the indicators that determine the use of such technologies by older adults.