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

Digital Health Reviews (1315) Digital Biomarkers and Digital Phenotyping (198) Wearable Devices and Sensors (900) Methods and New Tools in Mental Health Research (461) Digital Health, Telehealth and e-Innovation in Clinical Settings (419)

Published on in Vol 24, No 2 (2022): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28735, first published .
Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review

Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review

Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review

Authors of this article:

Jean P M Mendes1 Author Orcid Image ;   Ivan R Moura1 Author Orcid Image ;   Pepijn Van de Ven2 Author Orcid Image ;   Davi Viana1 Author Orcid Image ;   Francisco J S Silva1 Author Orcid Image ;   Luciano R Coutinho1 Author Orcid Image ;   Silmar Teixeira3 Author Orcid Image ;   Joel J P C Rodrigues4, 5 Author Orcid Image ;   Ariel Soares Teles1, 3, 6 Author Orcid Image
Article Authors Cited by (34) Tweetations (3) Metrics

Journals

  1. De La Fabián R, Jiménez-Molina Á, Pizarro Obaid F. A critical analysis of digital phenotyping and the neuro-digital complex in psychiatry. Big Data & Society 2023;10(1) View
  2. 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
  3. Diniz E, Fontenele J, de Oliveira A, Bastos V, Teixeira S, Rabêlo R, Calçada D, dos Santos R, de Oliveira A, Teles A. Boamente: A Natural Language Processing-Based Digital Phenotyping Tool for Smart Monitoring of Suicidal Ideation. Healthcare 2022;10(4):698 View
  4. 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
  5. Elmer T, Lodder G. Modeling social interaction dynamics measured with smartphone sensors: An ambulatory assessment study on social interactions and loneliness. Journal of Social and Personal Relationships 2023;40(2):654 View
  6. de Oliveira A, Diniz E, Teixeira S, Teles A. How can machine learning identify suicidal ideation from user's texts? Towards the explanation of the Boamente system. Procedia Computer Science 2022;206:141 View
  7. Moura I, Teles A, Viana D, Marques J, Coutinho L, Silva F. Digital Phenotyping of Mental Health using multimodal sensing of multiple situations of interest: A Systematic Literature Review. Journal of Biomedical Informatics 2023;138:104278 View
  8. Chen Z, Kulkarni P, Galatzer-Levy I, Bigio B, Nasca C, Zhang Y. Modern views of machine learning for precision psychiatry. Patterns 2022;3(11):100602 View
  9. Kulkarni P, Kirkham R, McNaney R. Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review. Sensors 2022;22(10):3893 View
  10. Bavaresco R, Barbosa J. Ubiquitous computing in light of human phenotypes: foundations, challenges, and opportunities. Journal of Ambient Intelligence and Humanized Computing 2023;14(3):2341 View
  11. Schmidt S, D'Alfonso S. Clinician perspectives on how digital phenotyping can inform client treatment. Acta Psychologica 2023;235:103886 View
  12. Ford T, Buchanan D, Azeez A, Benrimoh D, Kaloiani I, Bandeira I, Hunegnaw S, Lan L, Gholmieh M, Buch V, Williams N. Taking modern psychiatry into the metaverse: Integrating augmented, virtual, and mixed reality technologies into psychiatric care. Frontiers in Digital Health 2023;5 View
  13. Jabir A, Martinengo L, Lin X, Torous J, Subramaniam M, Tudor Car L. Evaluating Conversational Agents for Mental Health: Scoping Review of Outcomes and Outcome Measurement Instruments. Journal of Medical Internet Research 2023;25:e44548 View
  14. Yeo G, Loo G, Oon M, Pang R, Ho D. A Digital Peer Support Platform to Translate Online Peer Support for Emerging Adult Mental Well-being: Randomized Controlled Trial. JMIR Mental Health 2023;10:e43956 View
  15. Galatzer-Levy I, Onnela J. Machine Learning and the Digital Measurement of Psychological Health. Annual Review of Clinical Psychology 2023;19(1):133 View
  16. Marciano L, Vocaj E, Bekalu M, La Tona A, Rocchi G, Viswanath K. The Use of Mobile Assessments for Monitoring Mental Health in Youth: Umbrella Review. Journal of Medical Internet Research 2023;25:e45540 View
  17. Oudin A, Maatoug R, Bourla A, Ferreri F, Bonnot O, Millet B, Schoeller F, Mouchabac S, Adrien V. Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health. Journal of Medical Internet Research 2023;25:e44502 View
  18. Tani N, Fujihara H, Ishii K, Kamakura Y, Tsunemi M, Yamaguchi C, Eguchi H, Imamura K, Kanamori S, Kojimahara N, Ebara T. What digital health technology types are used in mental health prevention and intervention? Review of systematic reviews for systematization of technologies. Journal of Occupational Health 2024;66(1) View
  19. Fuhr D, Wolf-Ostermann K, Hoel V, Zeeb H. Digitale Technologien zur Verbesserung der psychischen Gesundheit. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 2024;67(3):332 View
  20. De La Fabián R. Digital Therapeutic Cultures and Their New Regime of Psychological Truth. Sociological Research Online 2024;29(2):299 View
  21. Schmitter-Edgecombe M, Luna C, Dai S, Cook D. Predicting daily cognition and lifestyle behaviors for older adults using smart home data and ecological momentary assessment. The Clinical Neuropsychologist 2024:1 View
  22. Conrad J. Digitization and its Discontents: The Promise and Limitations of Digital Mental Health Interventions. Journal of Contemporary Psychotherapy 2024;54(3):209 View
  23. Dong T, Yu C, Mao Q, Han F, Yang Z, Yang Z, Pires N, Wei X, Jing W, Lin Q, Hu F, Hu X, Zhao L, Jiang Z. Advances in biosensors for major depressive disorder diagnostic biomarkers. Biosensors and Bioelectronics 2024;258:116291 View
  24. Adhibai R, Kosiyaporn H, Markchang K, Nasueb S, Waleewong O, Suphanchaimat R, Sadek I. Depressive symptom screening in elderly by passive sensing data of smartphones or smartwatches: A systematic review. PLOS ONE 2024;19(6):e0304845 View
  25. Bidargaddi N, Leibbrandt R, Paget T, Verjans J, Looi J, Lipschitz J. Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research. DIGITAL HEALTH 2024;10 View
  26. 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
  27. Annajigowda H, Chaturvedi S. Digital Mental Health: A Way Forward for Public Mental Health. World Social Psychiatry 2023;5(2):153 View
  28. Leijse M, van Dam L, Jambroes T, Timmerman A, Popma A. Using Active and Passive Smartphone Data to Improve Adolescents’ Emotional Awareness in Forensic Outpatient Settings: An Explorative Qualitative Feasibility and Usability Study (Preprint). JMIR Formative Research 2023 View
  29. Sonig A, Deeney C, Hurley M, Storch E, Herrington J, Lázaro-Muñoz G, Zampella C, Tunc B, Parish-Morris J, Blumenthal-Barby J, Kostick-Quenet K. What patients and caregivers want to know when consenting to the use of digital behavioral markers. NPP—Digital Psychiatry and Neuroscience 2024;2(1) View

Books/Policy Documents

  1. Marchionatti L, Mastella N, Bouvier V, Passos I. Digital Mental Health. View
  2. Ahmed M, Ahmed N. Pervasive Computing Technologies for Healthcare. View
  3. Laurindo L, de Moura I, Coutinho L, da Silva e Silva F. Pervasive Computing Technologies for Healthcare. View
  4. Tovino S. Legal Medicine. View