Published on in Vol 11 (2023)

This is a member publication of University of Bristol (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44123, first published .
The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review

The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review

The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review

Authors of this article:

Doaa Alamoudi1 Author Orcid Image ;   Emma Breeze2 Author Orcid Image ;   Esther Crawley3 Author Orcid Image ;   Ian Nabney1 Author Orcid Image

Journals

  1. Fainardi V, Capoferri G, Tornesello M, Pisi G, Esposito S. Telemedicine and Its Application in Cystic Fibrosis. Journal of Personalized Medicine 2023;13(7):1041 View
  2. Negev M, Magal T, Kaphzan H. Attitudes of psychiatrists toward telepsychiatry: A policy Delphi study. DIGITAL HEALTH 2023;9 View
  3. Montag C, Hall B. Enhancing real-time digital surveillance can guide evidence-based policymaking to improve global mental health. Nature Mental Health 2023;1(10):697 View
  4. Alamoudi D, Nabney I, Crawley E. Evaluating the Effectiveness of the SleepTracker App for Detecting Anxiety- and Depression-Related Sleep Disturbances. Sensors 2024;24(3):722 View
  5. Corda E, Massa S, Riboni D. Context-Aware Behavioral Tips to Improve Sleep Quality via Machine Learning and Large Language Models. Future Internet 2024;16(2):46 View
  6. Zhao M, Wang R, Zhao Z, Li L, Luo H, Wu L. The relationship between boredom proneness, the behavioral inhibition system, and anxiety in college students: variable-centered and person-centered analytic approaches. Frontiers in Psychology 2024;15 View
  7. Kim S. Trends and Perspectives of mHealth in Obesity Control. Applied Sciences 2024;15(1):74 View
  8. 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
  9. Wan Q, Liu K, Bo Y, Yuan X, Li M, Wang X, Chen C, Liu L, Wu W. Predicting Insomnia Response to Acupuncture With the Development of Innovative Machine Learning. IEEE Access 2025;13:45964 View
  10. Gao T, Xiang H, Wu Q, Zhu L, Pei W, Fu W, Chou T. Advances in the research of comorbid insomnia and depression: mechanisms, impacts, and interventions. Frontiers in Psychiatry 2025;16 View
  11. Conejero I, Villalba M, Matos V, Jiménez O, García R, Albarracín-García L, Porras-Segovia A, Barrigón M, Lopez-Castroman J, Artés-Rodriguez A, Baca-Garcia E. Feasibility of digital monitoring in patients receiving ambulatory psychiatric care. Journal of Psychiatric Research 2025;189:184 View
  12. 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
  13. Leimhofer J, Petrovic M, Dominik A, Heider D, Hegerl U. Cross-Platform Availability of Smartphone Sensors for Depression Indication Systems: Mixed-Methods Umbrella Review. Interactive Journal of Medical Research 2025;14:e69686 View
  14. Bai X, Liu Y, Ma J, Wu F, Dai Z, Chen Y, Fang P. Roles and features of smart control and sensing applications for sleep quality improvement: a scoping review. BMJ Open 2025;15(8):e099831 View
  15. Villarreal R, Singhal S, Dempsey A, Shore J. The Future of Digital Mental Health. Psychiatric Clinics of North America 2025 View

Books/Policy Documents

  1. Rodriguez-Tenorio J, Borja V, Ramírez-Reivich A. 7th EAI International Conference on Computer Science and Engineering in Health Services. View