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

Mobile Health in Psychiatry (473) Digital Biomarkers and Digital Phenotyping (222) Wearable Devices and Sensors (976)

Published on in Vol 8, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25019, first published .
mPulse Mobile Sensing Model for Passive Detection of Impulsive Behavior: Exploratory Prediction Study

mPulse Mobile Sensing Model for Passive Detection of Impulsive Behavior: Exploratory Prediction Study

mPulse Mobile Sensing Model for Passive Detection of Impulsive Behavior: Exploratory Prediction Study

Authors of this article:

Hongyi Wen1 Author Orcid Image ;   Michael Sobolev1, 2 Author Orcid Image ;   Rachel Vitale3 Author Orcid Image ;   James Kizer1 Author Orcid Image ;   JP Pollak1 Author Orcid Image ;   Frederick Muench3 Author Orcid Image ;   Deborah Estrin1 Author Orcid Image
Article Authors Cited by (15) Tweetations (67) Metrics

Journals

  1. Moura I, Teles A, Viana D, Marques J, Coutinho L, Silva F. Digital Phenotyping of Mental Health using multimodal sensing of multiple situations of interest: A Systematic Literature Review. Journal of Biomedical Informatics 2023;138:104278 View
  2. Kulkarni P, Kirkham R, McNaney R. Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review. Sensors 2022;22(10):3893 View
  3. Lauvsnes A, Hansen T, Ankill S, Bae S, Gråwe R, Braund T, Larsen M, Langaas M. Mobile Assessments of Mood, Cognition, Smartphone-Based Sensor Activity, and Variability in Craving and Substance Use in Patients With Substance Use Disorders in Norway: Prospective Observational Feasibility Study. JMIR Formative Research 2023;7:e45254 View
  4. Ruf A, Neubauer A, Koch E, Ebner-Priemer U, Reif A, Matura S. Microtemporal Dynamics of Dietary Intake, Physical Activity, and Impulsivity in Adult Attention-Deficit/Hyperactivity Disorder: Ecological Momentary Assessment Study Within Nutritional Psychiatry. JMIR Mental Health 2023;10:e46550 View
  5. Sun Y, Kargarandehkordi A, Slade C, Jaiswal A, Busch G, Guerrero A, Phillips K, Washington P. Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment Study. JMIR Research Protocols 2024;13:e46493 View
  6. Choi A, Ooi A, Lottridge D. Digital Phenotyping for Stress, Anxiety, and Mild Depression: Systematic Literature Review. JMIR mHealth and uHealth 2024;12:e40689 View
  7. dos Santos M, Heckler W, Bavaresco R, Barbosa J. Machine learning applied to digital phenotyping: A systematic literature review and taxonomy. Computers in Human Behavior 2024;161:108422 View
  8. Ahn J, Jeong I, Park S, Lee J, Jeon M, Lee S, Do G, Jung D, Park J. App-Based Ecological Momentary Assessment of Problematic Smartphone Use During Examination Weeks in University Students: 6-Week Observational Study. Journal of Medical Internet Research 2025;27:e69320 View
  9. Lamichhane B, Moukaddam N, Salas R, Goodman W, Sabharwal A. Multimodal objective assessment of impulsivity in healthy and mood disorder participants. NPP—Digital Psychiatry and Neuroscience 2025;3(1) View
  10. Lamichhane B, Li Z, Sabharwal A, Moukaddam N. Impulsivity: A Transdiagnostic Approach to Understanding Adolescent Substance Use. Adolescent Psychiatry 2025;15(1):28 View
  11. Ajilore O, Bark J, Demos A, Zulueta J, Stange J, Duffecy J, Hussain F, Langenecker S, Nelson P, Ryan K, McInnis M, Leow A. Assessment of cognitive function in bipolar disorder with passive smartphone keystroke metadata: a BiAffect digital phenotyping study. Frontiers in Psychiatry 2025;16 View
  12. Linardon J, Chen K, Gajjar S, Eadara A, Wang S, Flathers M, Burns J, Torous J. Smartphone digital phenotyping in mental health disorders: A review of raw sensors utilized, machine learning processing pipelines, and derived behavioral features. Psychiatry Research 2025;348:116483 View

Books/Policy Documents

  1. Schmitt H, Elhai J, Montag C. The Psychology and Neuroscience of Impulsivity. View