Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health

Abstract

The term “digital phenotype” refers to the digital footprint left by patient-environment interactions. It has potential for both research and clinical applications but challenges our conception of health care by opposing 2 distinct approaches to medicine: one centered on illness with the aim of classifying and curing disease, and the other centered on patients, their personal distress, and their lived experiences. In the context of mental health and psychiatry, the potential benefits of digital phenotyping include creating new avenues for treatment and enabling patients to take control of their own well-being. However, this comes at the cost of sacrificing the fundamental human element of psychotherapy, which is crucial to addressing patients’ distress. In this viewpoint paper, we discuss the advances rendered possible by digital phenotyping and highlight the risk that this technology may pose by partially excluding health care professionals from the diagnosis and therapeutic process, thereby foregoing an essential dimension of care. We conclude by setting out concrete recommendations on how to improve current digital phenotyping technology so that it can be harnessed to redefine mental health by empowering patients without alienating them.

Balancing the Double-Edged Implications of AI in Psychiatric Digital Phenotyping

“…For example, trained AI algorithms could identify behavioral changes and patterns linked to symptoms of mental illness early on and continuously (Oudin et al. 2023 ). The application of AI extends beyond the analysis and interpretation of large digital phenotyping datasets for returning IRRs.…”

Predicting individual differences in peak emotional response

“…1 ), which were empirically confirmed across large samples to elicit chills beforehand in the population of interest ( 41 , 42 ). Advances in data science have revolutionized the scientific study of subjective phenomena by permitting the analysis of massive datasets of publicly available naturalistic reactions to stimuli provided by social media ( 43 , 44 ). Here, we used a novel technique leveraging online social platforms and crowdsourcing to curate and empirically validate a stimulus set for eliciting aesthetic chills.…”