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Big Data Analytics Help Prevent Adolescents Suicide: An Introduction to Mindpal

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High-Performance Computing and Big Data Analysis (TopHPC 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 891))

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Abstract

Suicide is cited as one of the three leading death causes on the rise, according to the centers for disease control and prevention. The field of adolescent mental health is in urgent need of better methods to lower suicide risk and psychiatric re-admission rates after discharge from inpatient psychiatry. Frequent follow-up is needed to detect fluctuations in suicide risk factors, such as sleep problems, mood disturbances and social withdrawal. Mobile Health approaches and digital phenotyping are proposed as a promising solution. In this paper, we first study the problem of suicide and its relation with data analytics especially among youths. We further present Mindpal Platform developed to provide rich, time-sensitive information about health behaviors by gathering information both in active and passive manner. Further analysis of gathered data Using the Mindpal Platform can help prevent the adolescents suicide.

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Author information

Authors and Affiliations

  1. Department of Psychology, University of Victoria, Victoria, Canada

    Brianna Turner

  2. Department of Psychiatry, University of British Columbia, Vancouver, Canada

    Ali Eslami

Authors
  1. Brianna Turner
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  2. Ali Eslami
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Correspondence to Ali Eslami .

Editor information

Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Lucio Grandinetti

  2. Kharazmi University, Tehran, Iran

    Seyedeh Leili Mirtaheri

  3. University of Calabria, Rende, Italy

    Reza Shahbazian

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Turner, B., Eslami, A. (2019). Big Data Analytics Help Prevent Adolescents Suicide: An Introduction to Mindpal. In: Grandinetti, L., Mirtaheri, S., Shahbazian, R. (eds) High-Performance Computing and Big Data Analysis. TopHPC 2019. Communications in Computer and Information Science, vol 891. Springer, Cham. https://doi.org/10.1007/978-3-030-33495-6_9

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  • DOI: https://doi.org/10.1007/978-3-030-33495-6_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33494-9

  • Online ISBN: 978-3-030-33495-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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