Well before the COVID-19 pandemic, proponents of digital psychiatry were touting the promise of various digital tools and techniques to revolutionize mental healthcare. As social distancing and its knock-on effects have strained existing mental health infrastructures, calls have grown louder for implementing various digital mental health solutions at scale. Decisions made today will shape the future of mental healthcare for the foreseeable future. We argue that bioethicists are uniquely positioned to cut through the hype surrounding digital mental health, which can (...) obscure crucial ethical and epistemic gaps that ought to be considered by policymakers before committing to a digital psychiatric future. Here, we describe four such gaps: The evidence gap, the inequality gap, the prediction-intervention gap, and the safety gap. (shrink)

This article identifies and examines a tension in mental health researchers’ growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data points. The (...) imperatives of the “participatory turn” in mental health research may be at odds with the (often unquestioned) assumptions and data collection methods of AI/ML approaches. This article aims to show why this is a problem and how it might be addressed. (shrink)

A recent systematic review of Machine Learning (ML) approaches to health data, containing over 100 studies, found that the most investigated problem was mental health (Yin et al., 2019). Relatedly, recent estimates suggest that between 165,000 and 325,000 health and wellness apps are now commercially available, with over 10,000 of those designed specifically for mental health (Carlo et al., 2019). In light of these trends, the present chapter has three aims: (1) provide an informative overview of some of the recent (...) work taking place at the intersection of text mining and mental health so that we can (2) highlight and analyze several pressing ethical issues that are arising in this rapidly growing field and (3) suggest productive directions for how these issues might be better addressed within future interdisciplinary work to ensure the responsible development of text mining approaches in psychology generally, and in mental health fields, specifically. In Section 1, we review some of the recent literature on text-mining and mental health in the contexts of traditional experimental settings, social media, and research involving electronic health records. Then, in Section 2, we introduce and discuss ethical concerns that arise before, during, and after research is conducted. Finally, in Section 3, we offer several suggestions about how ethical oversight of text-mining research might be improved to be more responsive to the concerns mapped out in Section 2. (shrink)

ABSTRACT: Abilify MyCite was granted regulatory approval in 2017, becoming the world’s first “smart pill” that could digitally track whether patients had taken their medication. The new technology was introduced as one that had gained the support of patients and ethicists alike, and could contribute to solving the widespread and costly problem of patient nonadherence. Here, we offer an in-depth exploration of this narrative, through an examination of the origins and development of Abilify, the drug that would later become MyCite. (...) This history illuminates how an antipsychotic can become a top-selling drug and maintain its blockbuster status for more than a decade. It also provides a detailed case study for how knowledge is constructed within the logic of biomedical capitalism, providing impetus to reexamine claims regarding how MyCite addresses patient nonadherence, engenders patient support, and is ethicist-approved. (shrink)