This article, “Reconciling healthism and techno-solutionism: An observational study of a digital mental health trial” by Ben Berners-Lee, published in Sociology of Health & Illness in 2023, presents an in-depth observational study of a digital mental health trial. The research focuses on the development of an algorithmic system in digital psychiatry that utilizes data collected from wearable devices and self-reports of mood to offer recommendations for behavioral modifications aimed at improving mood.
The study’s core insight revolves around the conceptualization of this trial, which emphasizes a paradoxical dynamic:
- On one hand, it highlights the powerful role of the intrinsically motivated and responsible participant. This aligns with sociological discussions of ‘healthism,’ which posits that the responsibility for health outcomes primarily lies with the supposedly empowered patient, often minimizing structural and environmental factors.
- On the other hand, it champions the empowering machine learning (ML)-based technology. This corresponds to ‘techno-solutionism,’ a critical perspective that focuses on the promising epistemological power of new technology to solve complex problems.
The author demonstrates how these two critical sociological theories—healthism and techno-solutionism—are made compatible within the digital psychiatry context. Formal accounts of the trial often present a cohesive view where the empowered participant and the insightful ML system work together. However, the study reveals that maintaining this conceptualization requires continual “discursive work” and addressing inherent contradictions. For instance, a disagreement between the principal investigators (PIs) about the balance of agency between data insights and intrinsic participant motivation highlights this tension. This reflects a “libertarian paternalism” where freedom is sustained through continuous discipline, a concept central to neoliberalism.
A significant contribution of the study is its focus on the Personalized Wellness Plan (PWP) guides. While formal accounts of the trial often relegate these guides to a minimal, mediatory, or even replaceable role (e.g., suggesting they could be replaced by a chatbot), ethnographic observations reveal their critical and indispensable importance. The guides perform essential ‘invisible work,’ which often involves forms of care like attentive listening and engagement that exceed the formal, technical descriptions of their duties. This unseen labor serves to bridge the gaps and inconsistencies that arise when data science projects encounter the complexities of real-life situations. The study shows how the formal characterization of guidance work as technical influences how guides perceive and carry out their tasks, leading them to structure their work around maintaining a technical support status.
The methodology employed is ethnographic observation of a translational psychiatry laboratory (TPL) over a nine-month period, including lab meetings, guide training sessions, and the PWP guidance sessions themselves, many of which occurred via ZOOM teleconferencing. The author utilized a “trace ethnography” approach, combining observational data with technical documents and digital traces. This remote observational approach also allows for unique insights into scientific and telehealth work conducted at a distance, despite differing from traditional embodied ethnography.
Ultimately, the article contributes to sociological discussions by elaborating on how new forms of human labor become minimized or ‘invisible’ within digital health interventions and how this conceptualization affects social scientific inquiries into computational projects. It argues for the value of attending to the human, interactive roles within health technology development, supporting moves towards co-design that acknowledge the crucial work of guides and coaches.
Reference: Berners-Lee, B. (2024). Reconciling healthism and techno-solutionism: An observational study of a digital mental health trial. Sociology of Health & Illness, 46(1), 39–58. https://doi.org/10.1111/1467-9566.13683
