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Phonotype: a New Taxonomy for mHealth Research

  • Bruce L. RollmanEmail author
  • David A. Brent
Viewpoint

Our phones and computers have become reflections of our personalities, our interests, and our identities. They hold much that is important to us.1

James B. Comey, Former FBI Director

Genotype and phenotype are established terms used to describe the set of genes that are unique to a person’s genetic makeup, and the observable characteristics resulting from the interaction of that genotype with the environment, respectively. Adding to this taxonomy, we propose a new term, “phonotype,” to describe how information collected by an individual’s smartphone can be utilized to understand their behavior and promote health.

While similar phrases including reality mining, digital phenotyping, and personal informatics have also been used to describe research involving smartphone-collected data,2we advocate for the term “phonotype” instead given its (1) clear connotation to smartphones; (2) “-type” suffix consistency with genotype and phenotype; and (3) single-word simplicity. Moreover, the term...

Notes

Acknowledgments

We thank David C. Mohr for his helpful feedback on a draft of this paper.

Funding Information

This work is supported by a grant from the National Institute of Mental Health (P50MH115838).

Compliance with Ethical Standards

The opinions and content expressed are solely the responsibility of the authors and do not necessarily represent the official views of our funding organization.

Conflict of Interest

The authors declare that they do not have a conflict of interest.

References

  1. 1.
    Comey JB. New Technologies Should Not Hinder Law Enforcement Surveillance. In: Merino N, ed. Domestic Surveillance. Farmington Hills, MI: Greenhaven Press, Reprint Edition; 2015.Google Scholar
  2. 2.
    Mohr DC, Zhang M, Schueller SM. Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning. Annu Rev Clin Psychol 2017;13:23–47.CrossRefGoogle Scholar
  3. 3.
    Taylor K, Silver L. Smartphone Ownership Is Growing Rapidly Around the World, but Not Always Equally. Global Attitudes & Trends Web site. Published 2019. Updated February 5, 2019. Accessed August 12, 2019.Google Scholar
  4. 4.
    Mobile Fact Sheet. Pew Research Center. Internet & Technology Web site. https://www.pewinternet.org/fact-sheet/mobile/. Published 2019. Accessed August 12, 2019.
  5. 5.
    Torous J, Larsen ME, Depp C, et al. Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps. Curr Psychiatry Rep 2018;20:51.CrossRefGoogle Scholar
  6. 6.
    Nahum-Shani I, Smith SN, Spring BJ, et al. Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support. Ann Behav Med 2017;52:446–462.CrossRefGoogle Scholar
  7. 7.
    Allen NB, Nelson BW, Brent D, Auerbach RP. Short-term prediction of suicidal thoughts and behaviors in adolescents: Can recent developments in technology and computational science provide a breakthrough? J Affect Disord 2019;250:163–169.CrossRefGoogle Scholar

Copyright information

© Society of General Internal Medicine 2019

Authors and Affiliations

  1. 1.Division of General Internal Medicine, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghUSA
  2. 2.Center for Behavioral Health and Smart TechnologyUniversity of Pittsburgh School of MedicinePittsburghUSA
  3. 3.Division of Child & Adolescent Psychiatry, Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghUSA

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