Realizing the Potential of Mobile Mental Health: New Methods for New Data in Psychiatry
Smartphones are now ubiquitous and can be harnessed to offer psychiatry a wealth of real-time data regarding patient behavior, self-reported symptoms, and even physiology. The data collected from smartphones meet the three criteria of big data: velocity, volume, and variety. Although these data have tremendous potential, transforming them into clinically valid and useful information requires using new tools and methods as a part of assessment in psychiatry. In this paper, we introduce and explore numerous analytical methods and tools from the computational and statistical sciences that appear readily applicable to psychiatric data collected using smartphones. By matching smartphone data with appropriate statistical methods, psychiatry can better realize the potential of mobile mental health and empower both patients and providers with novel clinical tools.
KeywordsSmartphones Mobile Big data Technology Statistical methods
PS is supported by NIH-95T32ES0071429-32 (PI Coull) and JPO by NIH-1DP2MH1039099-01 (PI Onnela).
Compliance with Ethics Guidelines
Conflict of Interest
John Torous, Patrick Staples, and Jukka-Pekka Onnela declare that they have no conflict of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Papers of particular interest, published recently, have been highlighted as: •• Of major importance
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