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

New Methods (800) Anxiety and Stress Disorders (915) Depression and Mood Disorders; Suicide Prevention (1172) mHealth for Data Collection and Research (776) Diagnostic Tools in Mental Health (200) Digital Biomarkers and Digital Phenotyping (155) Mobile Health in Psychiatry (374) Wearable Devices and Sensors (736) Methods and New Tools in Mental Health Research (398) mHealth for Screening (167)

Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28918, first published .
Automated Screening for Social Anxiety, Generalized Anxiety, and Depression From Objective Smartphone-Collected Data: Cross-sectional Study

Automated Screening for Social Anxiety, Generalized Anxiety, and Depression From Objective Smartphone-Collected Data: Cross-sectional Study

Automated Screening for Social Anxiety, Generalized Anxiety, and Depression From Objective Smartphone-Collected Data: Cross-sectional Study

Authors of this article:

Daniel Di Matteo 1 Author Orcid Image ;   Kathryn Fotinos 2 Author Orcid Image ;   Sachinthya Lokuge 2 Author Orcid Image ;   Geneva Mason 2 Author Orcid Image ;   Tia Sternat 2, 3 Author Orcid Image ;   Martin A Katzman 2, 3, 4, 5 Author Orcid Image ;   Jonathan Rose 1 Author Orcid Image
Article Authors Cited by (14) Tweetations (6) Metrics

Journals

  1. Girousse E, Vuillerme N. The Use of Passive Smartphone Data to Monitor Anxiety and Depression Among College Students in Real-World Settings: Protocol for a Systematic Review. JMIR Research Protocols 2022;11(12):e38785 View
  2. Teferra B, Borwein S, DeSouza D, Rose J. Screening for Generalized Anxiety Disorder From Acoustic and Linguistic Features of Impromptu Speech: Prediction Model Evaluation Study. JMIR Formative Research 2022;6(10):e39998 View
  3. Kulkarni P, Kirkham R, McNaney R. Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review. Sensors 2022;22(10):3893 View
  4. Maatoug R, Oudin A, Adrien V, Saudreau B, Bonnot O, Millet B, Ferreri F, Mouchabac S, Bourla A. Digital phenotype of mood disorders: A conceptual and critical review. Frontiers in Psychiatry 2022;13 View
  5. Choudhary S, Thomas N, Alshamrani S, Srinivasan G, Ellenberger J, Nawaz U, Cohen R. A Machine Learning Approach for Continuous Mining of Nonidentifiable Smartphone Data to Create a Novel Digital Biomarker Detecting Generalized Anxiety Disorder: Prospective Cohort Study. JMIR Medical Informatics 2022;10(8):e38943 View
  6. Teferra B, Rose J. Predicting Generalized Anxiety Disorder From Impromptu Speech Transcripts Using Context-Aware Transformer-Based Neural Networks: Model Evaluation Study. JMIR Mental Health 2023;10:e44325 View
  7. Teferra B, Borwein S, DeSouza D, Simpson W, Rheault L, Rose J. Acoustic and Linguistic Features of Impromptu Speech and Their Association With Anxiety: Validation Study. JMIR Mental Health 2022;9(7):e36828 View
  8. Dlima S, Shevade S, Menezes S, Ganju A. Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review. JMIR Bioinformatics and Biotechnology 2022;3(1):e39618 View
  9. Mei S, Hu Y, Wu X, Cao R, Kong Y, Zhang L, Lin X, liu Q, Hu Y, Li L. Health Risks of Mobile Phone Addiction Among College Students in China. International Journal of Mental Health and Addiction 2023;21(4):2650 View
  10. Barua P, Vicnesh J, Lih O, Palmer E, Yamakawa T, Kobayashi M, Acharya U. Artificial intelligence assisted tools for the detection of anxiety and depression leading to suicidal ideation in adolescents: a review. Cognitive Neurodynamics 2022 View
  11. Yamada Y, Shinkawa K, Nemoto M, Nemoto K, Arai T. A mobile application using automatic speech analysis for classifying Alzheimer's disease and mild cognitive impairment. Computer Speech & Language 2023;81:101514 View

Books/Policy Documents

  1. Heinz M, Price G, Song S, Bhattacharya S, Jacobson N. Digital Mental Health. View
  2. Gaikwad P, Venkatesan M. Proceedings of Congress on Control, Robotics, and Mechatronics. View