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

Wearable Devices and Sensors (1133) Digital Biomarkers and Digital Phenotyping (284) mHealth for Data Collection and Research (1196) mHealth for Wellness, Behavior Change and Prevention (3315) Ecological Momentary Assessment (EMA) (405)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37469, first published .
Smartphone-Tracked Digital Markers of Momentary Subjective Stress in College Students: Idiographic Machine Learning Analysis

Smartphone-Tracked Digital Markers of Momentary Subjective Stress in College Students: Idiographic Machine Learning Analysis

Smartphone-Tracked Digital Markers of Momentary Subjective Stress in College Students: Idiographic Machine Learning Analysis

Authors of this article:

George Aalbers1, 2 Author Orcid Image ;   Andrew T Hendrickson1 Author Orcid Image ;   Mariek MP Vanden Abeele2, 3 Author Orcid Image ;   Loes Keijsers4 Author Orcid Image
Article Authors Cited by (20) Tweetations (5) Metrics

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  1. Wang X, Oussalah M, Niemilä M, Ristikari T, Virtanen P. Towards AI-governance in psychosocial care: A systematic literature review analysis. Journal of Open Innovation: Technology, Market, and Complexity 2023;9(4):100157 View
  2. Ruotsalainen P, Blobel B. Future pHealth Ecosystem-Holistic View on Privacy and Trust. Journal of Personalized Medicine 2023;13(7):1048 View
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  5. Levinson C, Cusack C, Hunt R, Fitterman-Harris H, Ralph-Nearman C, Hooper S. The future of the eating disorder field: Inclusive, aware of systems, and personalized. Behaviour Research and Therapy 2024;183:104648 View
  6. 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
  7. Monarca I, Cibrian F, Hurtado I, Tentori M. Smartphone Haptics Can Uncover Differences in Touch Interactions Between ASD and Neurotypicals. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2024;8(4):1 View
  8. Takeshige M, Oka T, Ohwan M, Hirai K. Exploring the Utility of a Machine Learning Approach with Mobile‐Based Cognitive Function Tasks for Detecting Depression. Japanese Psychological Research 2025;67(2):195 View
  9. Schaab B, Calvetti P, Hoffmann S, Diaz G, Rech M, Cazella S, Stein A, Barros H, Silva P, Reppold C. How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review. Cadernos de Saúde Pública 2024;40(11) View
  10. Sathiparan N, Jeyananthan P, Subramaniam D. A machine learning approach to predicting pervious concrete properties: a review. Innovative Infrastructure Solutions 2025;10(2) View
  11. Stojchevska M, Van Der Donckt J, Vandenbussche N, De Brouwer M, Paemeleire K, Ongenae F, Van Hoecke S. Uncovering the potential of smartphones for behavior monitoring during migraine follow-up. BMC Medical Informatics and Decision Making 2025;25(1) View
  12. 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
  13. Woll S, Birkenmaier D, Biri G, Nissen R, Lutz L, Schroth M, Ebner-Priemer U, Giurgiu M. Applying AI in the Context of the Association Between Device-Based Assessment of Physical Activity and Mental Health: Systematic Review. JMIR mHealth and uHealth 2025;13:e59660 View
  14. Vanherle R, Beullens K, Kraemer N. The link between social media browsing and emerging adults’ momentary affective well-being: unraveling levels of analysis, underlying reasons, and content valence. Journal of Computer-Mediated Communication 2025;30(5) View

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  3. Saqr M, Ito H, López-Pernas S. Advanced Learning Analytics Methods. View

Conference Proceedings

  1. Geronimo S, Hernandez A, Abisado M. 2023 IEEE 13th International Conference on System Engineering and Technology (ICSET). Academic Stress of Students in Higher Education using Machine Learning: A Systematic Literature Review View
  2. Ito H, López-Pernas S, Saqr M. 2024 IEEE International Conference on Advanced Learning Technologies (ICALT). A Scoping Review of Idiographic Research in Education: Too Little, But Not Too Late View
  3. Amiludin N, Rosli M, Ibrahim N, Hammood W. 2025 International Conference on Advanced Machine Learning and Data Science (AMLDS). Mental Health Prediction Using Ensemble Learning Approaches with Rebalancing Technique View