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In a recent article published in big data and society, “Digital phenotyping,” which uses smartphones and other devices to assess mental health and deliver treatment before symptoms appear, is under intense scrutiny. The authors argue that apart from diagnosing and providing therapy, digital phenotyping shapes individual avenues for interpreting everything in neurological terms.
The authors caution that despite using objective data analysis, the method inherently incorporates human biases and cultural norms, and is largely based on personal rather than personal experience. It suggests facilitating new types of self-awareness and truth driven by app-based insights.
According to researchers Rodrigo de la Fabian, Alvaro Jiménez and Francisco Pizarro Obaido, digital phenotyping does not allow us to objectively observe ourselves. It is based on demographics, predefined datasets built using existing neuropsychological assumptions, and human classification processes. They do not see this as a misleading ideological position, but rather as an opportunity for productive inquiry. The discrepancy between what we perceive about ourselves and what digital phenotyping suggests helps us understand our lives through a neuropsychological lens.
“Digital phenotyping does not produce a neutral mirror for self-awareness. Rather than providing personalized diagnosis and treatment, digital phenotyping is directed toward normalization and neuropsychologicalization.” ,” the authors wrote.
The primary purpose of this study was to explore the claims and contradictions of individualized mental health assessments and interventions offered by digital phenotyping. They reviewed scientific publications from the last four years and evaluated applications and platforms that utilize digital phenotyping. This approach has enabled us to understand the scientific and general perceptions and applications associated with digital phenotyping. The focus was not on the “truths” it might reveal about individuals, but on what it caused, such as new ways of being and thinking about knowledge and truth.
This paper examines the recent “neuroturn” in science and society, a shift toward prioritizing biological data over personal stories to understand who we are. starts with. In the past, mental health professionals relied on first-hand testimony to understand the mind. But as the 20th century began, objective biological evidence began to obscure these personal stories that were deemed unreliable.
The National Institute of Mental Health launched the Research Domains Criteria Initiative in 2009 with the goal of identifying biological markers of mental illness similar to those used for physical illness. However, the expected results have not yet been realized. The authors highlight two major issues that hinder this effort.
First, when looking for biomarkers of mental illness, researchers must rely on personal stories to classify mental illness into specific diagnoses such as depression, which they consider unscientific. was given. Second, our mental states are largely shaped by our environment and are not static. Therefore, conducting psychological research in artificial settings, such as laboratories or psychiatrist’s offices, can distort the manifestations of psychiatric disorders and complicate biomarker identification.
The proliferation of smart devices over the past decade has provided researchers with a wealth of data. In the past, the mental health field relied primarily on “active data,” information that is voluntarily provided, such as responses to surveys. However, the advent of the digital age has introduced large amounts of “passive data” generated by interactions with devices. Combined with artificial intelligence, this passive data, largely decoupled from subjective experience, can be analyzed by machines, avoiding human bias.
However, the authors caution that it is impossible to completely eliminate human, subjective, and non-scientific factors from the equation. For example, they point to smartphone apps designed to warn users of potential manic or depressive episodes by analyzing voice changes during phone calls. Creating such a system assumes that the human ear will hear people with mania and depression, showing that passive data still rely on subjective perspectives. Moreover, these apps are developed by diverse people, which unintentionally guides users towards cultural norms and expectations.
Finally, the authors consider how such technologies can create new forms of self-awareness and truth. This kind of passive data collection creates new types of individuals who are constantly being watched and aware of their surveillance. They argue that this self-awareness may motivate us to amplify the physical and mental traits we deem important by the various apps we use.
This could also lead to a new kind of truth where a person may not feel depressed, but mental health apps detect depressive behavior. One might argue that in digital phenotypic analysis, direct testimony is considered unreliable and AI-analyzed passive data is preferred, so it is the app that should be trusted, not human emotions. yeah.
The authors conclude that “From this point of view, the gap with the DP conception is [digital phenotyping] It produces the truth about us and how we perceive it becomes productive. It measures the distance between who we think we are and who we really are. We therefore conclude that DPs still participate in the pre-digital process of neuropsychology, but in a new way. Rather than providing individualized diagnosis and treatment, as DP’s techno-utopia argues, individualized is the path to normalization and neuropsychologicalization. ”
Previous studies have pointed out several issues with digital phenotyping, including threats to privacy and autonomy. Some have raised legal and ethical issues regarding digital mental health technology. Previous research, as well as current research, have argued that digital psychiatry could fundamentally change the way we think about mental health, including through the use of “digital pills” that track users.
Researchers warn of possible abuse and coercion when private companies exploit suffering and profit from the “appification” of mental health services. Studies have also found that mental health apps can lead to overdiagnosis.
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De la Fabian, R., Jimenez Molina, Á., Pizarro Obaido, F. (2023). A critical analysis of digital phenotypes and neuro-digital complexes in psychiatry. big data and society, Ten(1), 205395172211490. https://doi.org/10.1177/20539517221149097 (link)
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