Abstract
The AnyMApp platform enables the testing of mock-ups from web or mobile applications, anonymously, and online, with the integration of three main parts: 1) survey-like questions regarding demographics and information about the project and use-case; 2) the mock-up interfaces of the use-case functionalities to be tested; 3) and survey-like questions regarding satisfaction and experience. The aim of this work is to present the preliminary results of the first use-case tested within the AnyMApp platform. Results show that the integration of diverse data can help define a comprehensive overview and improvement strategy for the tested application. All participants agree the AnyMApp platform is useful and simplifies and quickens usability testing, with bigger samples.
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References
Lu, C., et al.: The use of mobile health applications to improve patient experience: cross-sectional study in Chinese Public Hospitals. JMIR Mhealth Uhealth 6(5), e126 (2018). https://doi.org/10.2196/mhealth.9145
Ferreira, A., Muchagata, J., Vieira-Marques, P., Abrantes, D., Teles, S.: Perceptions of security and privacy in mHealth. In: Moallem, A. (ed.) HCII 2021. LNCS, vol. 12788, pp. 297–309. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-77392-2_19
Billmann, M., Böhm, M., Krcmar, H.: Use of workplace health promotion apps: analysis of employee log data. Health Policy Technol. 9(3), 285–293 (2020). ISSN 2211-8837. https://doi.org/10.1016/j.hlpt.2020.06.003
Tian, Y., Zhou, K., Lalmas, M., Liu, Y., Pelleg, D.: Cohort modeling based app category usage prediction. In: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2020, pp. 248–256. Association for Computing Machinery, New York (2020). https://doi.org/10.1145/3340631.3394849
Sigg, S., Lagerspetz, E., Peltonen, E., Nurmi, P., Tarkoma, S.: Exploiting usage to predict instantaneous app popularity: trend filters and retention rates. ACM Trans. Web 13(2), 1–25 (2019). https://doi.org/10.1145/3199677
Mennig, P., Scherr, S.A., Elberzhager, F.: Supporting rapid product changes through emotional tracking. In: 2019 IEEE/ACM 4th International Workshop on Emotion Awareness in Software Engineering (SEmotion), Montreal, QC, Canada, pp. 8–12 (2019). https://doi.org/10.1109/SEmotion.2019.00009
Donker, T., Petrie, K., Proudfoot, J., Clarke, J., Birch, M.-R., Christensen, H.: Smartphones for smarter delivery of mental health programs: a systematic review. J. Med. Internet Res. 15(11), e247 (2013). https://doi.org/10.2196/jmir.2791
Boateng, G., Batsis, J.A., Halter, R., Kotz, D.: ActivityAware: an app for real-time daily activity level monitoring on the Amulet wrist-worn device. In: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerComWorkshops), Kona, HI, pp. 431–435 (2017). https://doi.org/10.1109/PERCOMW.2017.7917601
Van Schalkwyk, A., Grobbelaar, S., Herselman, M.E.: A scoping review of the use of data analytics for the evaluation of mHealth applications. In: 29th International Conference of the International Association for Management of Technology, Nile University, Cairo, Egypt, 13–17 September 2020 (2020)
Ferreira, A., Chilro, R., Cruz-Correia, R.: AnyMApp framework: anonymous digital twin human-app interactions. In: Kurosu, M., et al. (eds.) HCI International 2022 - Late Breaking Papers. Design, User Experience and Interaction: 24th International Conference on Human-Computer Interaction, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings, pp. 214–225. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-17615-9_15
Nogueira-Silva, L., et al.: Development of a mobile health app for the management of hypertension, including treatment adherence assessment, using image detection technology – inspirers-htn. J. Hypertens. 39(Suppl. 1), e380 (2021). https://doi.org/10.1097/01.hjh.0000748952.19902.f5
Gordon, M.L., Gatys, L., Guestrin, C., Bigham, J.P., Trister, A., Patel, K.: App usage predicts cognitive ability in older adults. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019, vol. 168, pp. 1–12. Association for Computing Machinery, New York (2019). https://doi.org/10.1145/3290605.3300398
Axure RP 10: Software para criação de protótipos e especificações para sites e aplicativos. https://www.axure.com/
Brooke, J.: SUS: A quick and dirty usability scale. Usability Evaluation in Industry, pp. 189–194 (1995)
Acknowledgements
This work is financed by project AnyMApp - Anonymous Digital Twin for Human-App Interactions (EXPL/CCI-COM/0052/2021) (FCT – Fundação para a Ciência e Tecnologia).
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Muchagata, J., Bischoff, F., Almeida, R., Nogueira-Silva, L., Cruz-Correia, R., Ferreira, A. (2024). AnyMApp for Online Usability Testing: The Use-Case of Inspirers-HTN. In: Stephanidis, C., Antona, M., Ntoa, S., Salvendy, G. (eds) HCI International 2023 – Late Breaking Posters. HCII 2023. Communications in Computer and Information Science, vol 1958. Springer, Cham. https://doi.org/10.1007/978-3-031-49215-0_60
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