User perception and continuous intention to use dynamic consent in the healthcare industry

Abstract

Healthcare data is increasingly exposed to external threats due to digitalization, the reuse of datasets, and advancements in information technology. Consequently, the consent process in biomedical research has become a major concern, and the limitations of the traditional consent model have been highlighted. As a result, dynamic consent was introduced. However, despite the various benefits it offers, dynamic consent is not widely adopted, and there is a lack of empirical support for the concept. In this paper, we aim to fill this gap by developing a conceptual framework that analyzes user perception and continuous intention to use dynamic consent. To achieve this, we constructed a questionnaire to measure several items. Our findings confirm the hypothesis made and indicate that perceived controllability, perceived privacy/security, and perceived switching costs are factors that positively affect continuous intention to use. These findings provide a deeper understanding of the differences perceived by participants and explain the reasons why they are willing to embrace dynamic consent over a traditional consent model. Therefore, future research should provide further empirical support to the dynamic consent process.