Abstract

In recent years, smart health (s-Health) services have gained momentum worldwide. The s-Health services obtain personal information and aim to provide efficient health and medical services based on these data. In Japan, active efforts to implement these services have increased, but there is a lack of social acceptance. This study examined social acceptance concerning various factors such as trust in the city government, perceived benefits, perceived necessity, perceived risk, and concern about interventions for individuals. An online survey was conducted, and Japanese participants (N = 720) were presented with a vignette depicting a typical s-Health service overview. The results of structural equation modeling showed that trust was positively related to perceived benefit and necessity and negatively related to perceived risk and concern about interventions for individuals. Perceived benefit and trust were positively related to social acceptance, and perceived risk was negatively related to acceptance. The model obtained in this study can help implement s-Health services in public. Empirical studies that contribute to improving public health by investigating the social acceptance of s-Health services should be conducted in the future.

Highlights

  • We examine the determinants of the social acceptance of s-Health services by referring to a previous study recently conducted in Japan that dealt with the social acceptance of various smart city projects [25]

  • Referring to the previous study, which was conducted recently in Japan and dealt with the social acceptance of an extensive range of smart city projects [25], we examined a model in which trust in the city government influenced social acceptance through the mediation of perceived benefit, perceived necessity, perceived risk, and concern about interventions for individuals

  • There was a significant relationship between perceived benefit and social acceptance, which can be attributed to the s-Health service depicted in our vignette being more closely associated with the individuals’ lives than other kinds of smart city projects and being directly related to their health behaviors

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Summary

Introduction

The implementation of smart cities has been accelerating worldwide, and the development of sustainable and environment-friendly cities using artificial intelligence (AI) and big data has been fostered [1,2,3]. As Lohachab showed, smart health (s-Health) service initiatives are being developed to provide efficient medical and health services by utilizing the networks and infrastructure of smart cities to achieve the above goal [7,8,9]. Initiatives are being conceived, planned, or partially tested to use AI to analyze big data, such as people’s health and medical data, prevent frailty among older adults [12], and improve the quality of healthcare services [13]

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