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This paper is in the following e-collection/theme issue:

RCTs - Protocols/Proposals (eHealth) (1426) Adoption and Change Management of eHealth Systems (1176) mHealth for Wellness, Behavior Change and Prevention (4373) Depression and Mood Disorders; Suicide Prevention (2560) Anxiety and Stress Disorders (1678)

Published on in Vol 11, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37954, first published .
Person entering PIN code on a smartphone screen

Digital Phenotyping Data to Predict Symptom Improvement and App Personalization: Protocol for a Prospective Study

Digital Phenotyping Data to Predict Symptom Improvement and App Personalization: Protocol for a Prospective Study

Authors of this article:

Danielle Currey1 Author Orcid Image ;   John Torous1 Author Orcid Image
Article Authors Cited by (10) Tweetations (10) Metrics

Journals

  1. Currey D, Torous J. Digital Phenotyping Data to Predict Symptom Improvement and Mental Health App Personalization in College Students: Prospective Validation of a Predictive Model. Journal of Medical Internet Research 2023;25:e39258 View
  2. Langholm C, Byun A, Mullington J, Torous J. Monitoring sleep using smartphone data in a population of college students. npj Mental Health Research 2023;2(1) View
  3. Matthews P, Rhodes-Maquaire C. Personalisation and Recommendation for Mental Health Apps: A Scoping Review. Behaviour & Information Technology 2025;44(10):2389 View
  4. Gray L, Marcynikola N, Barnett I, Torous J. The Potential for Digital Phenotyping in Understanding Mindfulness App Engagement Patterns: A Pilot Study. Journal of Integrative and Complementary Medicine 2024;30(11):1108 View
  5. Patel J, Hung C, Katapally T. Evaluating predictive artificial intelligence approaches used in mobile health platforms to forecast mental health symptoms among youth: a systematic review. Psychiatry Research 2025;343:116277 View
  6. Heckler W, Feijó L, de Carvalho J, Barbosa J. Digital phenotyping for mental health based on data analytics: A systematic literature review. Artificial Intelligence in Medicine 2025;163:103094 View
  7. Brennenstuhl S, Agard C, Ho R, Cleverley K, Mugauri H. Stepped care, stepped care “lite” & matching intervention components to individual mental health needs: A rapid scoping review of mental health and substance use interventions for post-secondary students. PLOS ONE 2025;20(3):e0319473 View
  8. Torous J, Linardon J, Goldberg S, Sun S, Bell I, Nicholas J, Hassan L, Hua Y, Milton A, Firth J. The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality. World Psychiatry 2025;24(2):156 View

Books/Policy Documents

  1. Brand C, Adebesin F. Proceedings of 11th International Congress on Information and Communication Technology. View

Conference Proceedings

  1. Barrios P, Reales E, Cantillo L, Mendoza P, Conde W, Brochero E. 2025 IEEE Colombian Caribbean Conference (C3). Technology-Driven Strategies for Emotional Well-Being in Higher Education: a Systematic Literature Review View