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

Special Theme Issue 2022 Mental Health Internet Interventions (5) Mental Health Issues in Adolescence (637) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2111) Digital Biomarkers and Digital Phenotyping (284) mHealth for Data Collection and Research (1196) Methods and New Tools in Mental Health Research (558) Machine Learning (2076) Depression and Mood Disorders; Suicide Prevention (1691) Artificial Intelligence (2129)

Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44986, first published .
Associations Between Smartphone Keystroke Metadata and Mental Health Symptoms in Adolescents: Findings From the Future Proofing Study

Associations Between Smartphone Keystroke Metadata and Mental Health Symptoms in Adolescents: Findings From the Future Proofing Study

Associations Between Smartphone Keystroke Metadata and Mental Health Symptoms in Adolescents: Findings From the Future Proofing Study

Authors of this article:

Taylor A Braund1, 2 Author Orcid Image ;   Bridianne O’Dea1, 2 Author Orcid Image ;   Debopriyo Bal2 Author Orcid Image ;   Kate Maston2 Author Orcid Image ;   Mark Larsen1, 2 Author Orcid Image ;   Aliza Werner-Seidler1, 2 Author Orcid Image ;   Gabriel Tillman3 Author Orcid Image ;   Helen Christensen1, 2 Author Orcid Image
Article Authors Cited by (9) Tweetations (12) Metrics

Journals

  1. Alexander J, Linkersdörfer J, Toda-Thorne K, Sullivan R, Cummins K, Tomko R, Allen N, Bagot K, Baker F, Fuemmeler B, Hoffman E, Kiss O, Mason M, Nguyen-Louie T, Tapert S, Smith C, Squeglia L, Wade N. Passively sensing smartphone use in teens with rates of use by sex and across operating systems. Scientific Reports 2024;14(1) View
  2. 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
  3. Jang M, Cho Y, Kim D, Park S, Park S, Hur J, Kim M, Cho K, Lee C, Kwon J. Associations between keystroke and stylus metadata and depressive symptoms in adolescents. Psychological Medicine 2024;54(11):3109 View
  4. Smrke U, Mlakar I, Rehberger A, Žužek L, Plohl N. Decoding anxiety: A scoping review of observable cues. DIGITAL HEALTH 2024;10 View
  5. 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
  6. Heckler W, Feijó L, de Carvalho J, Barbosa J. Digital phenotyping for mental health based on data analytics: A systematic literature review. Artificial Intelligence in Medicine 2025;163:103094 View
  7. Braund T, Bal D, Christensen H, Batterham P, Vilus B, Maston K, Larsen M, Werner-Seidler A, Huckvale K, Whitton A, Tillman G, O’Dea B. Tapping into truth: an exploratory cross-sectional analysis of psychomotor symptoms and typing behaviour in an adolescent observational cohort. NPP—Digital Psychiatry and Neuroscience 2025;3(1) View
  8. Chitale V, Henry J, Matthews B, Cobham V, Baghaei N. Leveraging Swipe Gesture Interactions From Mobile Games as Indicators of Anxiety and Depression: Exploratory Study. JMIR Mental Health 2025;12:e70577 View

Books/Policy Documents

  1. Farida J, Ali K, Mohamed F. The Second International Symposium on Generative AI and Education (ISGAIE’2025). View