Modern technologies enable new options in the delivery of physical exercise programs. Specially designed app-based programs can be used to help older people in particular to integrate physical exercise into their daily lives. This study examines the influence of an app-based physical exercise program on selected parameters of physical fitness, such as muscular strength, balance, and flexibility. The women (n = 110) were on average 65.3 (± 1.5) years old and, compared to age-specific norm values, healthy. The 14-week intervention consisted of an app-based, unsupervised physical exercise program, in which the exercise frequency and duration of sessions were self-selected. The physical exercise program consisted of simple, functional exercises such as arm circles, squats, lateral raises. The participants were provided with an elastic resistance band and an exercise ball allowing them to increase exercise intensity if needed. Participants were randomly assigned to intervention group (IG) and control group (CG). 71% of the IG used the physical exercise program at least 1.2 times per week, whereas 25% of the IG showed usage rates above four times per week. Significant effects were found in the domains of muscular strength and flexibility. While IG could maintain their performance in isometric muscular strength tests and increased their flexibility, CG faced a decrease in those parameters. Thus, this app-based physical exercise program had positively influenced muscular strength and flexibility in women over 60 years of age.

Background: To empower healthy aging, digital solutions embed multiple modules for physical activity, cognitive health promotion, and social engagement. Integrating new empowering technologies such as digital exercise monitoring requires assessment measures and analysis procedures, considering variable compliance of users with different modules. Objective: This study aims to assess the influence of a tablet-based and a feedback system–based exercise module on balance and leg strength by considering use adherence instead of the use of the entire multimodular system. Methods: In the prospective cohort study within the fit4AAL project, 83 users (n=67, 81% women; n=16, 19% men; mean age 66.2, SD 2.3 years) used the 2 digital exercise modules of a multimodular physical activity promotion system for >18 weeks. A data-driven clustering method based on the average use frequency of the exercise modules determined the number of user types that met the World Health Organization–recommended training frequency of at least twice per week. On the basis of this use adherence, statistical analysis was performed with features of functional performance tests (unipedal stance, 30-second chair rise, Y-balance, and hurdle step tests). The tests were conducted 6 months before the intervention, immediately before the intervention, and after the intervention, comparing the baseline phase with the 3 feedback use groups of the study (using only the tablet, the tablet and the feedback system, or only the feedback system). Results: Of the 83 users, 43 (52%) met the World Health Organization–recommended frequency of muscle-strengthening activities. Overall, the feedback use groups achieved, on average, more chair rises in 30 seconds than the baseline group (P=.01; moderate effect size of 0.07). Of the 43 users, 26 (60%) additionally used the feedback system–based exercise module. They improved in balance compared with the users using either the tablet or the feedback system (P=.02). In addition, they improved their leg strength within the group (P=.04) and compared with the baseline (P=.01). Conclusions: The additional use of a feedback system showed a tendency to positively maintain and influence the already exceptionally high functional performance of older adults. Considering use adherence in future multimodular system studies is crucial to assess the influence of single and combined use of exercise modules on functional performance.

Background: Physical inactivity remains a leading risk factor for mortality worldwide. Owing to increasing sedentary behavior (activities in a reclining, seated, or lying position with low-energy expenditures), vehicle-based transport, and insufficient physical workload, the prevalence of physical activity decreases significantly with age. To promote sufficient levels of participation in physical activities, the research prototype Fit-mit-ILSE was developed with the goal of making adults aged ≥55 years physically fit and fit for the use of assistive technologies. The system combines active and assisted living technologies and smart services in the ILSE app. Objective: The clustering of health and fitness app user types, especially in the context of active and assisted living projects, has been mainly defined by experts through 1D cluster thresholds based on app usage frequency. We aimed to investigate and present data-driven methods for clustering app user types and to identify usage patterns based on the ILSE app function Fit at home. Methods: During the 2 phases of the field trials, ILSE app log data were collected from 165 participants. Using this data set, 2 data-driven approaches were applied for clustering to group app users who were similar to each other. First, the common approach of user-type clustering based on expert-defined thresholds was replaced by a data-driven derivation of the cluster thresholds using the Jenks natural breaks algorithm. Second, a multidimensional clustering approach using the Partitioning Around Medoids algorithm was explored to consider the detailed app usage pattern data. Results: Applying the Jenks clustering algorithm to the mean usage per day and clustering the users into 4 groups showed that most of the users (63/165, 38.2%) used the Fit at home function between once a week and every second day. More men were in the low usage group than women. In addition, the younger users were more often identified as moderate or high users than the older users, who were mainly classified as low users; moreover, the regional differences between Vienna and Salzburg were identified. In addition, the multidimensional approach identified 4 different user groups that differed mainly in terms of time of use, gender, and region. Overall, the younger women living in Salzburg were the users with highest average app usage. Conclusions: The application of different clustering approaches showed that data-driven calculations of user groups can complement expert-based definitions, provide objective thresholds for the analysis of app usage data, and identify groups that can be targeted individually based on their specific group characteristics.

Zusammenfassung: Es scheint viel Potenzial in Tablet und Co zu schlummern. Kann man der älteren Generation Programme zur Gesundheitsförderung via Smartphone und Applikationen näherbringen, sodass es ihr möglich ist mit diesen neuen Technologien länger fit und autonom in den eigenen vier Wänden zu leben? Ob diese Frage aufgrund vorliegender Erkenntnisse bestätigt werden kann oder doch wieder verworfen werden muss, versucht dieser Artikel zu ergründen.

The aim of this study is to compare data on the health status, self-reported exercise and non-exercise physical activity as well as fitness parameters, such as grip strength, of people in retirement in two cities that are both considered urban centres according to the statistical office of the European Union (EUROSTAT), but differ by geographic location. Self-reported physical activity questionnaires and objective assessments of physical fitness indicators collected by sports scientists were used and examined for differences. A total of 210 people (66.3 years ± 2.3) in Salzburg (n = 90) and Vienna (n = 120) was analysed. While no differences were found in self-reported health, there were differences in self-reported exposure to self-reported exercise and non-exercise physical activity, with the Viennese population being more inactive than their more western comparison group. In addition, the objective indicators for muscle strength, balance and flexibility of the lower extremities differed significantly in favour of the more western Austrian population. We recommend assessing the situation of older people in Austria regarding their physical activity and fitness on a regional basis, even if they live in cities of the same category. Future projects should therefore aim to consider specific regional needs during development and incorporate both subjective and objective indicators when monitoring the success of such programs.