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22 - Digital phenotyping: Using smartphone metadata to predict mental health symptoms
Manage episode 442827522 series 2938734
In this episode, I catch up with Dr Taylor A. Braund to hear about his research into digital phenotyping. In particular, we discuss the link between mental health symptoms and keystroke metadata from smartphones.
Dr Taylor A. Braund is a Research Fellow at Black Dog Institute and UNSW School of Clinical Medicine, Australia. To see more of Taylor’s work, you can reach out on LinkedIn or Twitter.
Research mentioned in this episode
Braund, T.A. (2024). The continued hype and hope of digital phenotyping. Nature Reviews Psychology, 3(448).
Braund, T. A., O’Dea, B., Bal, D., Maston, K., Larsen, M., Werner-Seidler, A., Tillman, G., & Christensen, H. (2023). Associations between smartphone keystroke metadata and mental health symptoms in adolescents: Findings from the Future Proofing Study. JMIR Mental Health, 10(e44986).
Braund, T. A., Zin, M. T., Boonstra, T. W., Wong, Q. J. J., Larsen, M. E., Christensen, H., Tillman, G., O’Dea, B. (2022). Smartphone sensor data for identifying and monitoring symptoms of mood disorders: A longitudinal observational study. JMIR Mental Health, 9(5):e35549
O’Dea, B., Braund, T. A., Batterham, P. J., Larsen, M. E., Glozier, N., & Whitton, A. E. (2024). Reading between the lines: Identifying the linguistic markers of Anhedonia for the stratification of depression. CHI Conference on Human Factors in Computing Systems. (Paper)
Seminal digital phenotyping papers
Huckvale, K., Venkatesh, S., & Christensen, H. (2019). Toward clinical digital phenotyping: A timely opportunity to consider purpose, quality, and safety. npj Digital Medicine, 2(88).
Insel, T. R. (2017). Digital phenotyping: Technology for a new science of behavior. JAMA, 318(13):1215–1216.
Torous, J., Kiang, M. V., Lorme, J., & Onnela, J. P. (2016). New tools for new research in psychiatry: A scalable and customizable platform to empower data driven smartphone research. JMIR Mental Health, 3(2):e16.
Some available digital phenotyping platforms
https://www.hsph.harvard.edu/onnela-lab/beiwe-research-platform/
https://www.digitalpsych.org/lamp.html
Cite this episode
MacDonald, J. B. & Braund, T. A. (2024, Oct 1). Digital phenotyping: Using smartphone metadata to predict mental health symptoms (No. 22) [Audio podcast episode]. In Psych Attack. www.psychattack.com
Transcript
The transcript for this episode was developed using transcription software. There may be some errors in the content as I do not have capacity to review for accuracy.
Acknowledgements
Psych Attack is created and hosted by Dr Jasmine B. MacDonald. The video and audio for this episode was edited by Morgan McRae. Special thanks to Dr Taylor A. Braund for sharing your time and expertise. Please note that the views and opinions expressed by Taylor in this episode are his own and do not necessarily reflect the official position or policy of his employer.
22 episoder
Manage episode 442827522 series 2938734
In this episode, I catch up with Dr Taylor A. Braund to hear about his research into digital phenotyping. In particular, we discuss the link between mental health symptoms and keystroke metadata from smartphones.
Dr Taylor A. Braund is a Research Fellow at Black Dog Institute and UNSW School of Clinical Medicine, Australia. To see more of Taylor’s work, you can reach out on LinkedIn or Twitter.
Research mentioned in this episode
Braund, T.A. (2024). The continued hype and hope of digital phenotyping. Nature Reviews Psychology, 3(448).
Braund, T. A., O’Dea, B., Bal, D., Maston, K., Larsen, M., Werner-Seidler, A., Tillman, G., & Christensen, H. (2023). Associations between smartphone keystroke metadata and mental health symptoms in adolescents: Findings from the Future Proofing Study. JMIR Mental Health, 10(e44986).
Braund, T. A., Zin, M. T., Boonstra, T. W., Wong, Q. J. J., Larsen, M. E., Christensen, H., Tillman, G., O’Dea, B. (2022). Smartphone sensor data for identifying and monitoring symptoms of mood disorders: A longitudinal observational study. JMIR Mental Health, 9(5):e35549
O’Dea, B., Braund, T. A., Batterham, P. J., Larsen, M. E., Glozier, N., & Whitton, A. E. (2024). Reading between the lines: Identifying the linguistic markers of Anhedonia for the stratification of depression. CHI Conference on Human Factors in Computing Systems. (Paper)
Seminal digital phenotyping papers
Huckvale, K., Venkatesh, S., & Christensen, H. (2019). Toward clinical digital phenotyping: A timely opportunity to consider purpose, quality, and safety. npj Digital Medicine, 2(88).
Insel, T. R. (2017). Digital phenotyping: Technology for a new science of behavior. JAMA, 318(13):1215–1216.
Torous, J., Kiang, M. V., Lorme, J., & Onnela, J. P. (2016). New tools for new research in psychiatry: A scalable and customizable platform to empower data driven smartphone research. JMIR Mental Health, 3(2):e16.
Some available digital phenotyping platforms
https://www.hsph.harvard.edu/onnela-lab/beiwe-research-platform/
https://www.digitalpsych.org/lamp.html
Cite this episode
MacDonald, J. B. & Braund, T. A. (2024, Oct 1). Digital phenotyping: Using smartphone metadata to predict mental health symptoms (No. 22) [Audio podcast episode]. In Psych Attack. www.psychattack.com
Transcript
The transcript for this episode was developed using transcription software. There may be some errors in the content as I do not have capacity to review for accuracy.
Acknowledgements
Psych Attack is created and hosted by Dr Jasmine B. MacDonald. The video and audio for this episode was edited by Morgan McRae. Special thanks to Dr Taylor A. Braund for sharing your time and expertise. Please note that the views and opinions expressed by Taylor in this episode are his own and do not necessarily reflect the official position or policy of his employer.
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