Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44502, first published .
Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health

Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health

Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health

Journals

  1. Bassil K. Balancing the Double-Edged Implications of AI in Psychiatric Digital Phenotyping. The American Journal of Bioethics 2024;24(2):113 View
  2. Schoeller F, Christov-Moore L, Lynch C, Diot T, Reggente N, Boggio P. Predicting individual differences in peak emotional response. PNAS Nexus 2024;3(3) View
  3. Solsky I, Haynes A. Beyond the physical: Digital phenotyping and the complexity of surgical recovery. Surgery 2024;176(2):519 View
  4. Ciharova M, Amarti K, van Breda W, Peng X, Lorente-Català R, Funk B, Hoogendoorn M, Koutsouleris N, Fusar-Poli P, Karyotaki E, Cuijpers P, Riper H. Use of Machine Learning Algorithms Based on Text, Audio, and Video Data in the Prediction of Anxiety and Posttraumatic Stress in General and Clinical Populations: A Systematic Review. Biological Psychiatry 2024;96(7):519 View
  5. D’Alfonso S, Coghlan S, Schmidt S, Mangelsdorf S. Ethical Dimensions of Digital Phenotyping Within the Context of Mental Healthcare. Journal of Technology in Behavioral Science 2024;10(1):132 View
  6. Kramer M, Hirsch D, Sacic A, Sader A, Willms J, Juckel G, Mavrogiorgou P. AI-enhanced analysis of naturalistic social interactions characterizes interaffective impairments in schizophrenia. Journal of Psychiatric Research 2024;178:210 View
  7. Nehls S, Dukart J, Enzensberger C, Stickeler E, Eickhoff S, Chechko N. Vorhersage und frühzeitige Identifikation einer postpartalen Depression: Ergebnisse der longitudinalen RiPoD-Studie im Kontext der Literatur. Der Nervenarzt 2025;96(2):176 View
  8. Malden D, Gee J, Glenn S, Li Z, Ryan D, Gu Z, Bezi C, Kim S, Jazwa A, McNeil M, Weintraub E, Tartof S. A Texting- and Internet-Based Self-Reporting System for Enhanced Vaccine Safety Surveillance With Insights From a Large Integrated Health Care System in the United States: Prospective Cohort Study. JMIR mHealth and uHealth 2024;12:e58991 View
  9. Karas M, Huang D, Clement Z, Millner A, Kleiman E, Bentley K, Zuromski K, Fortgang R, DeMarco D, Haim A, Donovan A, Buonopane R, Bird S, Smoller J, Nock M, Onnela J. Smartphone Screen Time Characteristics in People With Suicidal Thoughts: Retrospective Observational Data Analysis Study. JMIR mHealth and uHealth 2024;12:e57439 View
  10. Hong M, Kang R, Yang J, Rhee S, Lee H, Kim Y, Lee K, Kim H, Lee Y, Youn T, Kim S, Ahn Y. Comprehensive Symptom Prediction in Inpatients With Acute Psychiatric Disorders Using Wearable-Based Deep Learning Models: Development and Validation Study. Journal of Medical Internet Research 2024;26:e65994 View
  11. Liu Q, Ning E, Ross M, Cladek A, Kabir S, Barve A, Kennelly E, Hussain F, Duffecy J, Langenecker S, Nguyen T, Tulabandhula T, Zulueta J, Demos A, Leow A, Ajilore O. Digital Phenotypes of Mobile Keyboard Backspace Rates and Their Associations With Symptoms of Mood Disorder: Algorithm Development and Validation. Journal of Medical Internet Research 2024;26:e51269 View
  12. De la Torre K, Min S, Lee H, Kang D. The Application of Preventive Medicine in the Future Digital Health Era. Journal of Medical Internet Research 2025;27:e59165 View
  13. Simard M, Goulet M, Hudson É, Coulombe V, Lainesse S. Bernadette au fil du temps : une perspective évolutive des soins psychiatriques de l’internement aux alternatives à l’hospitalisation. Santé mentale au Québec 2024;49(2):315 View
  14. Moussaoui J, Smith A, Velkoff E. Latent subtypes of self‐injurious urges among adults engaging in disordered eating and non‐suicidal self‐injury. Suicide and Life-Threatening Behavior 2025;55(2) View
  15. 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
  16. Sidani L, Nadar S, Tfaili J, El Rayes S, Sharara F, Elhage J, Fakhoury M. Digital Psychiatry: Opportunities, Challenges, and Future Directions. Journal of Psychiatric Practice 2024;30(6):400 View
  17. Rocchi G, Vocaj E, Moawad S, Antonucci A, Grigioni C, Giuffrida V, Bordini J. Optimizing personalized psychological well-being interventions through digital phenotyping: results from a randomized non-clinical trial. Frontiers in Psychology 2025;15 View
  18. Fonseca L, Hawks Z, Beeri M, Jung L, Kudva Y, Rizvi S, Bulger J, Grinspoon E, Janess K, Sliwinski M, Pratley R, Rickels M, Weinstock R, Chhatwal J, Kivisäkk P, Germine L, Chaytor N. Cognitive vulnerability to glucose fluctuations: A digital phenotype of neurodegeneration. Alzheimer's & Dementia 2025;21(2) View
  19. Riisager L, Huniche L, Larsen J, Christiansen T, Kring L, Palic S, Moeller S. Fostering engagement using a wearable for self-tracking assisted psychotherapy with refugees diagnosed with complex PTSD: a feasibility pilot study. Frontiers in Psychiatry 2025;16 View
  20. Ruotsalainen P, Blobel B. A System Model and Requirements for Transformation to Human-Centric Digital Health. Journal of Medical Internet Research 2025;27:e68661 View
  21. Dammas S, Weyde T, Tapper K, Spanakis G, Roefs A, Pothos E. Prediction of Snacking Behavior Involving Snacks Having High Levels of Saturated Fats, Salt, or Sugar Using Only Information on Previous Instances of Snacking: Survey- and App-Based Study. JMIR Medical Informatics 2025;13:e57530 View
  22. Putica A, Yurtbasi M, Khanna R. Integrating digital health technologies for ecological validity in computational psychiatry: challenges and solutions. AI & SOCIETY 2025;40(7):5509 View
  23. Zhong R, Wu X, Chen J, Fang Y. Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review. Journal of Medical Internet Research 2025;27:e72229 View
  24. Beames J, Dabash O, Spoelma M, Shvetcov A, Zheng W, Slade A, Han J, Hoon L, Kupper J, Parker R, Mitchell B, Martin N, Newby J, Whitton A, Christensen H. Feasibility of Collecting and Linking Digital Phenotyping, Clinical, and Genetics Data for Mental Health Research: Pilot Observational Study. JMIR Formative Research 2025;9:e71377 View
  25. Stern E, Brune S, Mouchabac S, Dubroc A, de la Personne C, Geoffroy P. Innovative Digital Cognitive Behavioral Treatment for Insomnia Disorder in Adults (dCBT-i): Framework Development. JMIR Human Factors 2025;12:e70193 View
  26. Jeong J, Jeon Y, Kim H, Yeom J, Shin Y, Kim S, Pack S, Lee H, Cheong T, Cho C. Machine learning-based prediction of restless legs syndrome using digital phenotypes from wearables and smartphone data. Scientific Reports 2025;15(1) View
  27. Cho M, Park D, Choo M, Han D, Kim J. Impact of Digital Phenotypes and Question-Asking on Emotional Disorders in Adolescents: 4-Week Field Study. JMIR Human Factors 2025;12:e66536 View
  28. Ciharova M, Amarti K, van Breda W, Gevonden M, Ghassemi S, Kleiboer A, Vinkers C, Sep M, Trofimova S, Cooper A, Peng X, Schulte M, Karyotaki E, Cuijpers P, Riper H. Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned. Frontiers in Psychiatry 2025;16 View
  29. Lans L, Huijbregts K, Westerhof G, Haeyen S, Derks Y, Noordzij M. How to integrate physiological data from wearables in treatment of personality disorders: a narrative review. Frontiers in Psychiatry 2025;16 View
  30. . Selected Abstracts from the 2025 International Neuroethics Society Annual Meeting. AJOB Neuroscience 2025;16(3) View
  31. Prégent J, Chung V, El Adib I, Désilets M, Hudon A. Applications of Artificial Intelligence in Psychiatry and Psychology Education: Scoping Review. JMIR Medical Education 2025;11:e75238 View
  32. Wang P, Liu H, Shi Y, Liu A, Zhu Q, Albu I, Pacholec M, Cheng L, Sun X, Chi X. Harnessing Small‐Data Machine Learning for Transformative Mental Health Forecasting: Towards Precision Psychiatry With Personalised Digital Phenotyping. Med Research 2025;1(2):226 View
  33. Petrušić I. Digital phenotyping for migraine: A game-changer for research and management. Cephalalgia 2025;45(7) View
  34. Marano G, Lisci F, Boggio G, Marzo E, Abate F, Sfratta G, Traversi G, Mazza O, Pola R, Sani G, Gaetani E, Mazza M. Future Pharmacotherapy for Bipolar Disorders: Emerging Trends and Personalized Approaches. Future Pharmacology 2025;5(3):42 View
  35. Holley D, Daly B, Beverly B, Wamsley B, Brooks A, Zaubler T. Evaluating Generative Pretrained Transformer (GPT) models for suicide risk assessment in synthetic patient journal entries. BMC Psychiatry 2025;25(1) View
  36. Garcia B, Chua E, Brah H. The problem of atypicality in LLM-powered psychiatry. Journal of Medical Ethics 2025:jme-2025-110972 View
  37. Zakai J, Alharthi S. Harnessing Digital Phenotyping for Early Self-Detection of Psychological Distress. Healthcare 2025;13(16):2008 View
  38. Alam N, Surani M, Das C, Giacco D, Singh S, Jilka S. Challenges and standardisation strategies for sensor-based data collection for digital phenotyping. Communications Medicine 2025;5(1) View
  39. Choudhary S, Nelson B, Jones N, Mehta U, Torous J. Telehealth and Pharmacotherapy: The Role of Synchronous and Novel Asynchronous Digital Health Tools in Psychiatry. Pharmaceutical Medicine 2025;39(6):413 View
  40. Hailemariam M, Rosen R, Sneed R, Brown G, Clark K, Mackey B, Eshetu H, Wei J, Taxman F, Johnson J. Use of data-driven decision-making among agencies serving individuals with criminal-legal system involvement: a qualitative study. BMC Health Services Research 2025;25(1) View
  41. Salahuddin M, Walker J, Zambrana E, Gupta V, Jung K, Pandi-Perumal S, Manzar M. Self-Regulation Mediates the Relationship Between Stress and Quality of Life in Shift-Working Healthcare Professionals: Behavioral Clustering Insights. European Journal of Investigation in Health, Psychology and Education 2025;15(9):180 View
  42. Ito S, Ang C, Kampman O, Rokde K, Buddhika T, Heaukulani C, Tan Z, Dewanti F, Au E, Huan V, Morris R, Khong A, Ho A. Harnessing digital phenotyping to advance university student mental health (Brightline) in Singapore: study protocol for a prospective observational study. BMJ Open 2025;15(9):e103652 View
  43. Zheng H, Zhang X. Psychiatry in the age of AI: transforming theory, practice, and medical education. Frontiers in Public Health 2025;13 View
  44. Chen K, Torous J, Cheong J. The Current State/ Trends in Digital Phenotyping for Mental Health Research and Care. Psychiatric Clinics of North America 2025 View
  45. LaMonica H, Hickie I, Capon W, Ahia M, Ewing L, Lee W, Iorfino F, Song Y, McKenna S, Cleverley K. Digital Tools to Support Post‐Secondary Student Mental Health and Wellbeing. Early Intervention in Psychiatry 2025;19(10) View
  46. Choi A, Lottridge D, Warren J. Personalised modelling of routine variability and affective states. npj Digital Medicine 2025;8(1) View
  47. Riisager L, Larsen J, Huniche L, Christiansen T, Moeller S. Collaborative Development of a Self-Tracking Assisted Psychotherapy Treatment Concept for Refugees With Complex Posttraumatic Stress Disorder: Participatory Action Research. JMIR Formative Research 2025;9:e66663 View
  48. Volpe U, Ramalho R, Gaebel W. Risks of digitalization in mental health care. neuropsychiatrie 2025 View
  49. Oso T, Okesanya O, Adebayo U, Obadeyi K, Musa S, Ahmed M, Ayankola A, Ogundele A, Oso J, Eshun G, Lucero-Prisno D. Advancing our understanding of schizophrenia: insights from recent research, emerging therapies, and future directions. Exploration of Neuroscience 2025;4 View
  50. Tan C, Koh J, Ang W, Tan X, Koh S, Lin W, Lee J, Chew H. State-of-the-art digital phenotyping methods for cardiometabolic risk prevention and management: a scoping review. International Journal of Medical Informatics 2026;206:106133 View
  51. Blott H, Hind E, Brown C, Forrester A. Artificial intelligence in forensic psychiatry: potential applications and key considerations. Journal of Forensic and Legal Medicine 2025;116:103016 View
  52. Palaniyappan L, Sabesan P. Quantitative semiology: harnessing AI-generated teaching signals in psychiatry. Journal of Psychiatry and Neuroscience 2025;50(5):E318 View
  53. Kaštelan S, Kozina L, Tomić Z, Bakija I, Matejić T, Vidović D. Dry Eye Disease and Psychiatric Disorders: Neuroimmune Mechanisms and Therapeutic Perspectives. International Journal of Molecular Sciences 2025;26(21):10699 View
  54. Soulier T, Burgos N, Hassanaly R, Pitombeira M, Solal M, Roy H, Hamzaoui M, Yazdan-Panah A, de Paula Faria D, Louapre C, Bodini B, Bottlaender M, Ayache N, Colliot O, Stankoff B. Artificial intelligence in presymptomatic neurological diseases: Bridging normal variation and prodromal signatures. Revue Neurologique 2025;181(9):944 View
  55. Alimour S, Alrabeei M. Redefining psychopathology in the context of digital overload: emerging disorders in the age of information saturation. Frontiers in Digital Health 2025;7 View
  56. Gong X, Cheng Q, Wu Y, Wang S, Xu K, Qin L, He F, Cheng J. Influencing factors of depressive symptoms in middle-aged and elderly people and its regional differences in china: a study based on Bayesian network model. Journal of Health, Population and Nutrition 2025;44(1) View
  57. Kostick-Quenet K, Storch E. Toward Human-Centered Digital Health Interventions. Psychiatric Clinics of North America 2025 View
  58. Kostick-Quenet K, Hurley M, Ayaz S, Herrington J, Zampella C, Parrish-Morris J, Tunç B, Lázaro-Muñoz G, Blumenthal-Barby J, Storch E. Stakeholder Perspectives on Humanistic Implementation of Computer Perception in Healthcare: A Qualitative Study (Preprint). JMIR Mental Health 2025 View
  59. Vecchio I, Mifsud L, Castro e Almeida S, Passecker J. Diagnostic digital phenotyping in schizophrenia-spectrum disorders: a systematic review. npj Digital Medicine 2025 View

Books/Policy Documents

  1. Cho C, Lee H, Kim Y. Recent Advances and Challenges in the Treatment of Major Depressive Disorder. View
  2. Irmak-Yazicioglu M, Arslan A. Recent Advances and Challenges in the Treatment of Major Depressive Disorder. View
  3. Gargot T, Guneysu A, Cifuentes C, Orlandi S. Digital Mental Health. View
  4. Rebouças D, Barreto P, Noronha L, Roza T, Passos I. Bipolar Disorder. View
  5. Bhola P, Duggal C, Isaac R. Reflective Practice in Psychotherapy and Counselling. View
  6. Amjad E, Sokouti B. The Palgrave Encyclopedia of Disability. View

Conference Proceedings

  1. So J, Yang F, Gupta A, Gajos K. The 26th International ACM SIGACCESS Conference on Computers and Accessibility. "It's Better to be Grounded in Reality": a Speculative Exploration of Patient-Centered Digital Phenotyping for Neurological Conditions View
  2. Bogdanova K, Cila N, Kudina O, Bozzon A. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. Digital Phenotyping as Felt Informatics: Designing AI-Based Mental Health Diagnostic Tools Through Aesthetics View
  3. Krishnamoorthy Srinivasan S, Bahadur A, Singh S, Kedia gupta S, Jain V, Deb K, Kumar M, Singh P. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. Demystifying Mental Health Reports Through an LLM-based Approach View
  4. Joshi Y, Gupta N, Mishra D. 2025 World Skills Conference on Universal Data Analytics and Sciences (WorldSUAS). The Role of Artificial Intelligence in Mental Health Support: Present Implementations, Innovative Tools, and Research Horizons View