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Digital Phenotyping for Mental Health: Reviewing the Challenges of Using Data to Monitor and Predict Mental Health Problems

Research output: Contribution to journalArticlepeer-review

Rasmus Hoffman Birk, Gabrielle Samuel

Original languageEnglish
Pages (from-to)523-528
Number of pages6
Issue number10
Early online date22 Aug 2022
Accepted/In press7 Jul 2022
E-pub ahead of print22 Aug 2022
PublishedOct 2022

King's Authors


Purpose of Review: We review recent developments within digital phenotyping for mental health, a field dedicated to using digital data for diagnosing, predicting, and monitoring mental health problems. We especially focus on recent critiques and challenges to digital phenotyping from within the social sciences. Recent Findings: Three significant strands of criticism against digital phenotyping for mental health have been developed within the social sciences. This literature problematizes the idea that digital data can be objective, that it can be unbiased, and argues that it has multiple ethical and practical challenges. Summary: Digital phenotyping for mental health is a rapidly growing and developing field, but with considerable challenges that are not easily solvable. This includes when, and if, data from digital phenotyping is actionable in practice; the involvement of user and patient perspectives in digital phenotyping research; the possibility of biased data; and challenges to the idea that digital phenotyping can be more objective than other forms of psychiatric assessment.

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