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

Formative Evaluation of Digital Health Interventions (2193) Design and Formative Evaluation of Mobile Apps (661) mHealth for Wellness, Behavior Change and Prevention (2728) Anxiety and Stress Disorders (999) Depression and Mood Disorders; Suicide Prevention (1271) Mobile Health in Psychiatry (399) Social Anxiety Disorder (SAD) (47) Speech and Phonetics in Verbal Protocols (Think Aloud, Recall, and Explanation Tasks) (91)

Published on in Vol 5, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22723, first published .
Smartphone-Detected Ambient Speech and Self-Reported Measures of Anxiety and Depression: Exploratory Observational Study

Smartphone-Detected Ambient Speech and Self-Reported Measures of Anxiety and Depression: Exploratory Observational Study

Smartphone-Detected Ambient Speech and Self-Reported Measures of Anxiety and Depression: Exploratory Observational Study

Authors of this article:

Daniel Di Matteo1 Author Orcid Image ;   Wendy Wang1 Author Orcid Image ;   Kathryn Fotinos2 Author Orcid Image ;   Sachinthya Lokuge2 Author Orcid Image ;   Julia Yu2 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 (13) Tweetations (3) Metrics

Journals

  1. Di Matteo D, Fotinos K, Lokuge S, Mason G, Sternat T, Katzman M, Rose J. Automated Screening for Social Anxiety, Generalized Anxiety, and Depression From Objective Smartphone-Collected Data: Cross-sectional Study. Journal of Medical Internet Research 2021;23(8):e28918 View
  2. Newn J, Kelly R, D'Alfonso S, Lederman R. Examining and Promoting Explainable Recommendations for Personal Sensing Technology Acceptance. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2022;6(3):1 View
  3. 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
  4. 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
  5. 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
  6. Koops S, Brederoo S, de Boer J, Nadema F, Voppel A, Sommer I. Speech as a Biomarker for Depression. CNS & Neurological Disorders - Drug Targets 2023;22(2):152 View
  7. Zarate D, Stavropoulos V, Ball M, de Sena Collier G, Jacobson N. Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence. BMC Psychiatry 2022;22(1) View
  8. Li N, Feng L, Hu J, Jiang L, Wang J, Han J, Gan L, He Z, Wang G. Using deeply time-series semantics to assess depressive symptoms based on clinical interview speech. Frontiers in Psychiatry 2023;14 View
  9. Duey A, Rana A, Siddi F, Hussein H, Onnela J, Smith T. Daily Pain Prediction Using Smartphone Speech Recordings of Patients With Spine Disease. Neurosurgery 2023;93(3):670 View
  10. 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
  11. 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
  12. 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
  13. Shin J, Bae S. Use of voice features from smartphones for monitoring depressive disorders: Scoping review. DIGITAL HEALTH 2024;10 View