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

Engagement with and Adherence to Digital Health Interventions, Law of Attrition (531) Digital Biomarkers and Digital Phenotyping (222) Mobile Health in Psychiatry (473) mHealth for Wellness, Behavior Change and Prevention (3067) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1762)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39258, first published .
Digital Phenotyping Data to Predict Symptom Improvement and Mental Health App Personalization in College Students: Prospective Validation of a Predictive Model

Digital Phenotyping Data to Predict Symptom Improvement and Mental Health App Personalization in College Students: Prospective Validation of a Predictive Model

Digital Phenotyping Data to Predict Symptom Improvement and Mental Health App Personalization in College Students: Prospective Validation of a Predictive Model

Authors of this article:

Danielle Currey1, 2 Author Orcid Image ;   John Torous1 Author Orcid Image
Article Authors Cited by (10) Tweetations (14) Metrics

Journals

  1. Currey D, Torous J. Increasing the value of digital phenotyping through reducing missingness: a retrospective review and analysis of prior studies. BMJ Mental Health 2023;26(1):e300718 View
  2. Oudin A, Maatoug R, Bourla A, Ferreri F, Bonnot O, Millet B, Schoeller F, Mouchabac S, Adrien V. Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health. Journal of Medical Internet Research 2023;25:e44502 View
  3. Cohen A, Naslund J, Lane E, Bhan A, Rozatkar A, Mehta U, Vaidyam A, Byun A, Barnett I, Torous J. Digital phenotyping data and anomaly detection methods to assess changes in mood and anxiety symptoms across a transdiagnostic clinical sample. Acta Psychiatrica Scandinavica 2025;151(3):388 View
  4. Matthews P, Rhodes-Maquaire C. Personalisation and Recommendation for Mental Health Apps: A Scoping Review. Behaviour & Information Technology 2024:1 View
  5. 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
  6. Weiner L, Crowley R, Sheeber L, Koegler F, Davis J, Wells M, Funkhouser C, Auerbach R, Allen N. Engagement, Acceptability, and Effectiveness of the Self-Care and Coach-Supported Versions of the Vira Digital Behavior Change Platform Among Young Adults at Risk for Depression and Obesity: Pilot Randomized Controlled Trial. JMIR Mental Health 2024;11:e51366 View
  7. Dwyer B, Flathers M, Burns J, Mikkelson J, Perlmutter E, Chen K, Ram N, Torous J. Assessing Digital Phenotyping for App Recommendations and Sustained Engagement: Cohort Study. JMIR Formative Research 2024;8:e62725 View
  8. Macrynikola N, Chang S, Torous J. Emotion Regulation Self-Efficacy as a Mechanism of Alliance and Outcomes in a Brief, Transdiagnostic Digital Mental Health Intervention: L'auto-efficacité de la régulation des émotions en tant que mécanisme d'alliance et de résultats dans une brève intervention transdiagnostique numérique en santé mentale. The Canadian Journal of Psychiatry 2024 View
  9. 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
  10. Zhang Y, Wang J, Zong H, Singla R, Ullah A, Liu X, Wu R, Ren S, Shen B. The comprehensive clinical benefits of digital phenotyping: from broad adoption to full impact. npj Digital Medicine 2025;8(1) View