Work

Information security and confidentiality in health chatbots: A scoping review and development of a conceptual model

Year: 2025

Type: article

Abstract: Objectives: The present study aims to identify the key challenges related to information security and confidentiality in health chatbots, extract relevant solutions, and propose a conceptual model to ensure secure and confidential data management within such systems. Methods: To achieve the study's objectives, a scoping review was conducted. This phase focused on identifying reported challenges and proposed solutions in prior studies regarding information security and confidentiality in health chatbots. In this context, we selected English-language articles in international journals and conferences related to information security and confidentiality in health chatbots. After that, relevant international frameworks, studies, and guidelines on information security, confidentiality, and privacy were systematically reviewed and analyzed and then, a conceptual model was created which was further developed and refined through validation by a panel of experts. Results: Out of 1233 articles screened, 16 met the inclusion criteria. Recurring challenges in health chatbots, such as breaches of privacy, no transparency, incomplete consent, technical issues in data handling, lack of legal frameworks, and emerging threats, were identified in the results. The literature suggested measures like encryption, risk management, access control, standardization, and regular evaluations. Based on international frameworks, a comprehensive conceptual model with four key dimensions was developed, integrating software, hardware, and middleware layers to improve data security and confidentiality. Conclusion: These findings can benefit users, health practitioners, the regulatory authorities, and chatbot developers who want to increase the safety and credibility of health chatbot systems.

Source: Digital Health

DOI: 10.1177/20552076251406637

Authors: Tahere Talebi Azadboni, Fahimeh Solat, Hanieh Hematti, Meysam Rahmani

Institution: Saveh University of Medical Sciences

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,000