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User Perceptions Of The Security Of Personal Health Data On Chatgpt In Indonesia

Year: 2026
Type: article
Study design: Observational Study
Abstract: This study aims to explore the relationship between perceptions of data security and privacy, awareness of cyberattacks, and other factors that influence users’ trust in ChatGPT and their willingness to provide personal information. Data was collected via a questionnaire and analyzed using SmartPLS. This study examines eight main variables, namely: Privacy Concern (PC), Perceived Effectiveness of Government Regulation (PEGR), Trust in ChatGPT (TR), Moral Motive (MM), Perceived Intelligence (PI), Perceived Risk (PR), Perceived Benefit (PB), and Sharing Willingness (SW). This study tested nine hypotheses regarding the influence of these variables. Data were collected via a questionnaire using a 1–5 Likert scale and analyzed using SmartPLS to test the relationships among constructs using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. The analysis results indicate that four of the proposed hypotheses were supported, with p-values < 0.05, suggesting that the decision to share personal data is significantly influenced by perceived benefits, which are in turn influenced by perceptions of ChatGPT’s intelligence and trust in the platform. Perceived Risk does not have a significant impact on Sharing Willingness; however, privacy concerns influence users’ perceptions of risk. The results of this study indicate that the benefits of using ChatGPT, significantly influences their willingness to share personal health data. This study suggests that the sample size should be increased to conduct a more in-depth analysis of information-sharing decisions. Keywords: ChatGPT, Data Privacy Calculus, Health Information, Willingness to Share
DOI: 10.33751/jhss.v10i2.102
Open Access status: diamond
OpenAlex ID: W7163681835
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