JMIR Publications

ABSTRACT

Background:

The increasing use of direct-to-consumer AI-enabled mHealth (AI-mHealth) applications presents an opportunity for more effective health management and monitoring and expanded mHealth capabilities. However, AI’s early developmental stage has prompted ethical concerns related to privacy, informed consent, and bias, among others. While some of these concerns have been explored in early stakeholder research related to AI-mHealth, the limited literature suggests that the broader landscape of considerations that hold ethical significance to users may remain underexplored.

Objective:

Our aim was to document and explore the ethical perspectives of users of mHealth regarding AI-mHealth applications.

Methods:

We conducted semi-structured interviews with users of mHealth applications (N=21) and employed a qualitative descriptive design to document and describe their ethical perspectives.

Results:

Through qualitative analysis, three major categories and nine subcategories describing users’ perspectives were identified. Users described attitudes toward the impact of AI-mHealth on their health and data (i.e., influences on health awareness and management, value for mental versus physical health, and the inevitability of data sharing); influences on their trust in AI-mHealth (i.e., expert recommendations, attitudes toward technology companies, and AI explainability); and their preferences relating to information sharing in AI-mHealth (i.e., the type of data that is collected, future uses of their data, and the accessibility of information).

Conclusions:

This paper provides additional context relating to a number of ethical concerns previously posited or identified in the AI-mHealth literature, including trust, explainability, and information sharing, and revealed additional considerations that have not been previously documented, i.e., users’ differentiation between the value of AI-mHealth for physical and mental health use cases, and their willingness to extend empathy to non-explainable AI. To our best knowledge, this study is the first to apply an open-ended, qualitative descriptive approach to explore the perspectives of end users of direct-to-consumer AI-mHealth applications. Clinical Trial: This study addressed a supplemental aim to an ongoing study about the ethics of AI use in medicine (NCATS R01-TR-003505). This study obtained human subjects research approval from the Institutional Review Board of Stanford University on June 21, 2022 (#58118).