Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study

Abstract

Background Digital phenotyping (also known as personal sensing, intelligent sensing, or body computing) involves the collection of biometric and personal data in situ from digital devices, such as smartphones, wearables, or social media, to measure behavior or other health indicators. The collected data are analyzed to generate moment-by-moment quantification of a person’s mental state and potentially predict future mental states. Digital phenotyping projects incorporate data from multiple sources, such as electronic health records, biometric scans, or genetic testing. As digital phenotyping tools can be used to study and predict behavior, they are of increasing interest for a range of consumer, government, and health care applications. In clinical care, digital phenotyping is expected to improve mental health diagnoses and treatment. At the same time, mental health applications of digital phenotyping present significant areas of ethical concern, particularly in terms of privacy and data protection, consent, bias, and accountability. Objective This study aims to develop consensus statements regarding key areas of ethical guidance for mental health applications of digital phenotyping in the United States. Methods We used a modified Delphi technique to identify the emerging ethical challenges posed by digital phenotyping for mental health applications and to formulate guidance for addressing these challenges. Experts in digital phenotyping, data science, mental health, law, and ethics participated as panelists in the study. The panel arrived at consensus recommendations through an iterative process involving interviews and surveys. The panelists focused primarily on clinical applications for digital phenotyping for mental health but also included recommendations regarding transparency and data protection to address potential areas of misuse of digital phenotyping data outside of the health care domain. Results The findings of this study showed strong agreement related to these ethical issues in the development of mental health applications of digital phenotyping: privacy, transparency, consent, accountability, and fairness. Consensus regarding the recommendation statements was strongest when the guidance was stated broadly enough to accommodate a range of potential applications. The privacy and data protection issues that the Delphi participants found particularly critical to address related to the perceived inadequacies of current regulations and frameworks for protecting sensitive personal information and the potential for sale and analysis of personal data outside of health systems. Conclusions The Delphi study found agreement on a number of ethical issues to prioritize in the development of digital phenotyping for mental health applications. The Delphi consensus statements identified general recommendations and principles regarding the ethical application of digital phenotyping to mental health. As digital phenotyping for mental health is implemented in clinical care, there remains a need for empirical research and consultation with relevant stakeholders to further understand and address relevant ethical issues.

Data sharing in the age of predictive psychiatry: an adolescent perspective

“…Scientific advances in predictive mental health, alongside the increasing availability of commercial testing services, have sparked significant debate over potential ethical and social implications. 7 8 For instance, researchers have questioned the current utility of predictive tests in psychiatry, given their limited predictive power. 9 10 Others have pointed to the unique sensitivity of mental health data, which may not only be used for accessing health and social services but also for influencing criminal justice proceedings (eg, sentence mitigation), and might attract stigma, discrimination and forced treatment.…”

“… 8 Associated issues surrounding who owns and who should be granted access to mental health data have also been raised. 7 In the context of minors, researchers have debated who has the right to manage a child’s risk, and raised privacy concerns regarding data sharing. 3 11 12 …”

“…Scientific advances in predictive mental health, alongside the increasing availability of commercial testing services, have sparked significant debate over potential ethical and social implications 7 8. For instance, researchers have questioned the current utility of predictive tests in psychiatry, given their limited predictive power 9 10.…”

Data sharing in the age of predictive psychiatry: An adolescent perspective

“…The copyright holder for this this version posted August 26, 2021. ; https://doi.org/10.1101/2021.08. 25.21262234 doi: medRxiv preprint Scientific advances in predictive mental health, alongside the increasing availability of commercial testing services, have sparked significant controversy and debate over potential ethical and social implications [10][11][12]. For instance, researchers have questioned the current utility of predictive tests in psychiatry, given their limited predictive power [13,14].…”

“…There is also enthusiasm for the possibility of linking/sharing data between schools and health systems to support research and intervention in adolescent mental health [8] and for health systems and schools to use social media data to monitor mental health risk [9]. Scientific advances in predictive mental health, alongside the increasing availability of commercial testing services, have sparked significant controversy and debate over potential ethical and social implications [10][11][12]. For instance, researchers have questioned the current utility of predictive tests in psychiatry, given their limited predictive power [13,14].…”