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

New Methods (1030) Anxiety and Stress Disorders (1178) Depression and Mood Disorders; Suicide Prevention (1514) mHealth for Data Collection and Research (1080) Diagnostic Tools in Mental Health (279) Digital Biomarkers and Digital Phenotyping (227) Mobile Health in Psychiatry (478) Wearable Devices and Sensors (993) Methods and New Tools in Mental Health Research (497) mHealth for Screening (257)

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 Matteo1 Author Orcid Image ;   Kathryn Fotinos2 Author Orcid Image ;   Sachinthya Lokuge2 Author Orcid Image ;   Geneva Mason2 Author Orcid Image ;   Tia Sternat2, 3 Author Orcid Image ;   Martin A Katzman2, 3, 4, 5 Author Orcid Image ;   Jonathan Rose1 Author Orcid Image
Article Authors Cited by (27) 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 2024;18(1):1 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
  12. Fernández-Álvarez J, Colombo D, Gómez Penedo J, Pierantonelli M, Baños R, Botella C. Studies of Social Anxiety Using Ambulatory Assessment: Systematic Review. JMIR Mental Health 2024;11:e46593 View
  13. Li W, Xu T, Diao L, Wu Q. The Impact of Perceived Discrimination on Mobile Phone Addiction Among Chinese Higher Vocational College Students: A Chain Mediating Role of Negative Emotions and Learning Burnout. Psychology Research and Behavior Management 2024;Volume 17:401 View
  14. Flandreau E, Risbrough V. Reframing and refining model system validity for anxiety and depression research: A commentary on Gencturk & Unal (2024). Cognitive, Affective, & Behavioral Neuroscience 2024;24(2):225 View
  15. Zierer C, Behrendt C, Lepach-Engelhardt A. Digital biomarkers in depression: A systematic review and call for standardization and harmonization of feature engineering. Journal of Affective Disorders 2024;356:438 View
  16. Sahu N, Yadav M, Lone H. Unveiling Social Anxiety: Analyzing Acoustic and Linguistic Traits in Impromptu Speech within a Controlled Study. ACM Journal on Computing and Sustainable Societies 2024;2(2):1 View
  17. 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
  18. Chitale V, Henry J, Liang H, Matthews B, Baghaei N. Virtual reality analytics map (VRAM): A conceptual framework for detecting mental disorders using virtual reality data. New Ideas in Psychology 2025;76:101127 View
  19. Oliveira F, Neri D, Ribeiro K, Oliveira L, Santos E, Pereira M, Lima S. O USO DA INTELIGÊNCIA ARTIFICIAL NA IDENTIFICAÇÃO DO PACIENTE PSIQUIÁTRICO COM TENDÊNCIA SUICIDA. Revista Contemporânea 2024;4(10):e6253 View
  20. Smrke U, Mlakar I, Rehberger A, Žužek L, Plohl N. Decoding anxiety: A scoping review of observable cues. DIGITAL HEALTH 2024;10 View
  21. Li P, Chen J, Duan Z, Xu W, Feng Y. Relationship Between Problematic Smartphone Use and Graduate Students’ Research Self-Efficacy: A Moderated Mediation Model. Behavioral Sciences 2024;14(12):1191 View
  22. Yokotani K, Takano M, Abe N, Kato T. Predicting social anxiety disorder based on communication logs and social network data from a massively multiplayer online game: Using a graph neural network. Psychiatry and Clinical Neurosciences 2025;79(5):274 View
  23. 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
  24. Yang M, Ngai E, Hu X, Hu B, Liu J, Gelenbe E, Leung V. Digital Phenotyping and Feature Extraction on Smartphone Data for Depression Detection. Proceedings of the IEEE 2024;112(12):1773 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

Conference Proceedings

  1. Yamada Y, Shinakwa K, Kobayashi M, Nemoto M, Ota M, Nemoto K, Arai T. 2023 IEEE International Conference on Digital Health (ICDH). Smartwatch-derived Acoustic Markers for Deficits in Cognitively Relevant Everyday Functioning View