Abstract
Based on the relevant elements of the theory of planned behavior and its practical application, this paper builds a design model of walking health APP for the elderly and performs the design research process according to the design model. Guided by the theory of planned behavior, the non-interventional behavior observation method and semi-structured interviews were used to investigate the elderly groups in five typical communities in Beijing, and the behavioral characteristics of the elderly were recorded and analyzed in the process of walking behavior in different scenarios, to obtain the factors influencing the walking behavior of the elderly group. Through the analysis of laboratory video data and the transformation of influencing factors, four typical walking modes of the elderly were output. At the same time, combined with the travel mode and the aging design method, the design strategy suitable for the APP of walking health of the elderly is proposed, and the analysis and evaluation of the walking behavior and the travel behavior of the elderly are recorded and tracked in the form of an APP. Based on the principle of cognitive walking, the Smart Healthy Walking APP is tested by the 5-level Likert scale to verify the effectiveness of the proposed design strategy. The research in this paper provides a new idea for the user research of health products for the elderly and provides a solution for the analysis, evaluation and transformation of the elderly’s travel environment.
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Acknowledgments
This work was supported by the National Key R&D Program of China (2021YFE0111800).
This work was supported by Humanities and Social Sciences Foundation of Ministry of Education of the people’s Republic of China (Grant Number: 18YJC760039).
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Niu, X., Li, H., Zhang, C. (2023). A Study on the Design Strategy of Walking Health APP for the Elderly from the Behavioral Theory Perspective. In: Gao, Q., Zhou, J., Duffy, V.G., Antona, M., Stephanidis, C. (eds) HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14055. Springer, Cham. https://doi.org/10.1007/978-3-031-48041-6_12
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