Abstract
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.
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Acknowledgments
PS is supported by NIH-95T32ES0071429-32 (PI Coull) and JPO by NIH-1DP2MH1039099-01 (PI Onnela).
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John Torous, Patrick Staples, and Jukka-Pekka Onnela declare that they have no conflict of interest.
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This article does not contain any studies with human or animal subjects performed by any of the authors.
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This article is part of the Topical Collection on Psychiatry in the Digital Age
John Torous and Patrick Staples contributed equally and are co-first authors.
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Torous, J., Staples, P. & Onnela, JP. Realizing the Potential of Mobile Mental Health: New Methods for New Data in Psychiatry. Curr Psychiatry Rep 17, 61 (2015). https://doi.org/10.1007/s11920-015-0602-0
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DOI: https://doi.org/10.1007/s11920-015-0602-0