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      Exploring the Influencing Factors on User Experience in Robot-Assisted Health Monitoring Systems Combining Subjective and Objective Health Data

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      Applied Sciences
      MDPI AG

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          Abstract

          As the population ages, the demand for care for older adults is increasing. To maintain their independence and autonomy, even with declining health, assistive technologies such as connected medical devices or social robots can be useful. In previous work, we introduced a novel health monitoring system that combines commercially available products with apps designed specifically for older adults. The system is intended for the long-term collection of subjective and objective health data. In this work, we present an exploratory user experience (UX) and usability study we conducted with older adults as the target group of the system and with younger expert users who tested our system. All participants interacted with a social robot conducting a health assessment and tested sensing devices and an app for data visualization. The UX and usability of the individual components of the system were rated highly in questionnaires in all sessions. All participants also said they would use such a system in their everyday lives, demonstrating the potential of these systems for self-managing users’ health. Finally, we found factors such as previous experience with social robots and technological expertise to have an influence on the reported UX of the users.

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          Most cited references38

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          A mathematical model of the finding of usability problems

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            Aging barriers influencing mobile health usability for older adults: A literature based framework (MOLD-US).

            With the growing population of older adults as a potential user group of mHealth, the need increases for mHealth interventions to address specific aging characteristics of older adults. The existence of aging barriers to computer use is widely acknowledged. Yet, usability studies show that mHealth still fails to be appropriately designed for older adults and their expectations. To enhance designs of mHealth aimed at older adult populations, it is essential to gain insight into aging barriers that impact the usability of mHealth as experienced by these adults.
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              On the dimensionality of the System Usability Scale: a test of alternative measurement models.

              The System Usability Scale (SUS), developed by Brooke (Usability evaluation in industry, Taylor & Francis, London, pp 189-194, 1996), had a great success among usability practitioners since it is a quick and easy to use measure for collecting users' usability evaluation of a system. Recently, Lewis and Sauro (Proceedings of the human computer interaction international conference (HCII 2009), San Diego CA, USA, 2009) have proposed a two-factor structure-Usability (8 items) and Learnability (2 items)-suggesting that practitioners might take advantage of these new factors to extract additional information from SUS data. In order to verify the dimensionality in the SUS' two-component structure, we estimated the parameters and tested with a structural equation model the SUS structure on a sample of 196 university users. Our data indicated that both the unidimensional model and the two-factor model with uncorrelated factors proposed by Lewis and Sauro (Proceedings of the human computer interaction international conference (HCII 2009), San Diego CA, USA, 2009) had a not satisfactory fit to the data. We thus released the hypothesis that Usability and Learnability are independent components of SUS ratings and tested a less restrictive model with correlated factors. This model not only yielded a good fit to the data, but it was also significantly more appropriate to represent the structure of SUS ratings.
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                Author and article information

                Contributors
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                Journal
                ASPCC7
                Applied Sciences
                Applied Sciences
                MDPI AG
                2076-3417
                March 2023
                March 10 2023
                : 13
                : 6
                : 3537
                Article
                10.3390/app13063537
                2960b1e2-a93d-4269-8336-ac619358dd30
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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