Returning Individual Research Results from Digital Phenotyping in Psychiatry

Area of Science:

• Psychiatry
• Digital Health
• Bioethics

Background:

• Digital phenotyping and AI/ML are increasingly used in psychiatry to study mental illness.
• Tracking various data points (location, online activity, biometrics) generates numerous sensitive individual research results (IRRs).
• Current ethical frameworks are inadequate for managing the return of IRRs from digital phenotyping research.

Purpose of the Study:

• To develop a novel ethical framework for returning individual research results (IRRs) in digital phenotyping research.
• To address the ethical, legal, and social implications (ELSI) of sharing sensitive data from digital mental health studies.
• To provide guidance for researchers, clinicians, and Institutional Review Boards (IRBs).

Main Methods:

• Convened an interdisciplinary expert working group.
• Supported by a National Institute of Mental Health grant.
• Built upon established ethical guidelines and participant-centered research principles.

Main Results:

• Presented a novel framework for returning IRRs in digital phenotyping research.
• The framework addresses the unique challenges posed by the volume and sensitivity of data collected.
• Offers practical guidance for ethical decision-making in digital mental health research.

Conclusions:

• The proposed framework provides essential guidance for the ethical return of individual research results in digital phenotyping.
• Principles developed for psychiatry are adaptable to other therapeutic areas utilizing similar data collection methods.
• Facilitates responsible innovation in digital mental health research while prioritizing participant well-being.