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

Digital Biomarkers and Digital Phenotyping (198) mHealth in a Clinical Setting (624) mHealth for Wellness, Behavior Change and Prevention (2922) mHealth for Data Collection and Research (981) Ontologies, Classifications, and Coding (243) eHealth Infrastructures (357) Crowdsourcing, Big Data, Quantified Self-based Research Data (9) Big Data (245) Data Science (278) Mobile Health (mhealth) (2982)

Published on in Vol 10, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30557, first published .
Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study

Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study

Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study

Authors of this article:

Aditya Vaidyam1 Author Orcid Image ;   John Halamka2 Author Orcid Image ;   John Torous1 Author Orcid Image
Article Authors Cited by (40) Tweetations (16) Metrics

Journals

  1. Hussein R, Griffin A, Pichon A, Oldenburg J. A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs). Journal of the American Medical Informatics Association 2023;30(4):787 View
  2. Richey A, Kovacs I, Browne S. Use of an Ingestible, Sensor-Based Digital Adherence System to Strengthen the Therapeutic Relationship in Serious Mental Illness. JMIR Mental Health 2022;9(12):e39047 View
  3. Currey D, Torous J. Digital Phenotyping Data to Predict Symptom Improvement and Mental Health App Personalization in College Students: Prospective Validation of a Predictive Model. Journal of Medical Internet Research 2023;25:e39258 View
  4. Currey D, Torous J. Digital phenotyping correlations in larger mental health samples: analysis and replication. BJPsych Open 2022;8(4) View
  5. Niemeijer K, Mestdagh M, Verdonck S, Meers K, Kuppens P. Combining Experience Sampling and Mobile Sensing for Digital Phenotyping With m-Path Sense: Performance Study. JMIR Formative Research 2023;7:e43296 View
  6. Currey D, Torous J. Digital Phenotyping Data to Predict Symptom Improvement and App Personalization: Protocol for a Prospective Study. JMIR Research Protocols 2022;11(11):e37954 View
  7. Moscarelli M, Min J, Kopelowicz A, Torous J, Chavez O, Gómez-de-Regil L, Salvador-Carulla L, Ochoa S, Gamez M, Vila-Badia R, Romero-Lopez-Alberca C, Ahmed A. The scale for the assessment of the passively received experiences (PRE) in schizophrenia and digital mental health. Schizophrenia Research 2023;251:91 View
  8. Senaratne H, Oviatt S, Ellis K, Melvin G. A Critical Review of Multimodal-multisensor Analytics for Anxiety Assessment. ACM Transactions on Computing for Healthcare 2022;3(4):1 View
  9. Schmidt S, D'Alfonso S. Clinician perspectives on how digital phenotyping can inform client treatment. Acta Psychologica 2023;235:103886 View
  10. González-Pérez A, Matey-Sanz M, Granell C, Díaz-Sanahuja L, Bretón-López J, Casteleyn S. AwarNS: A framework for developing context-aware reactive mobile applications for health and mental health. Journal of Biomedical Informatics 2023;141:104359 View
  11. Currey D, Torous J. Increasing the value of digital phenotyping through reducing missingness: a retrospective review and analysis of prior studies. BMJ Mental Health 2023;26(1):e300718 View
  12. Langholm C, Alon N, Perret S, Torous J. Risk scores in digital psychiatry: Expanding the reach of complex smartphone data by condensing it into simple results. Journal of Behavioral and Cognitive Therapy 2023;33(2):90 View
  13. Aalami O, Hittle M, Ravi V, Griffin A, Schmiedmayer P, Shenoy V, Gutierrez S, Venook R. CardinalKit: open-source standards-based, interoperable mobile development platform to help translate the promise of digital health. JAMIA Open 2023;6(3) View
  14. Green J, Rodriguez J, Keshavan M, Lizano P, Torous J. Implementing Technologies to Enhance Coordinated Specialty Care Framework: Implementation Outcomes From a Development and Usability Study. JMIR Formative Research 2023;7:e46491 View
  15. Macrynikola N, Nguyen N, Lane E, Yen S, Torous J. The Digital Clinic: An Innovative Mental Health Care Delivery Model Utilizing Hybrid Synchronous and Asynchronous Treatment. NEJM Catalyst 2023;4(9) View
  16. Emerson M, Perret S, Chinn H, Alon N, Watanabe-Galloway S, Johnson D, Dinkel D, Torous J. A Systematic Review and Exploration of Smartphone App Interventions for Perinatal Depression With Case Study. Current Treatment Options in Psychiatry 2023;10(3):136 View
  17. Nghiem J, Adler D, Estrin D, Livesey C, Choudhury T. Understanding Mental Health Clinicians’ Perceptions and Concerns Regarding Using Passive Patient-Generated Health Data for Clinical Decision-Making: Qualitative Semistructured Interview Study. JMIR Formative Research 2023;7:e47380 View
  18. Tsai C, Rajput G, Gao A, Wu Y, Wu D. Improving the design of patient-generated health data visualizations: design considerations from a Fitbit sleep study. Journal of the American Medical Informatics Association 2024;31(2):465 View
  19. Langholm C, Kowatsch T, Bucci S, Cipriani A, Torous J. Exploring the Potential of Apple SensorKit and Digital Phenotyping Data as New Digital Biomarkers for Mental Health Research. Digital Biomarkers 2023:104 View
  20. Chang S, Gray L, Alon N, Torous J. Patient and Clinician Experiences with Sharing Data Visualizations Integrated into Mental Health Treatment. Social Sciences 2023;12(12):648 View
  21. Langholm C, Breitinger S, Gray L, Goes F, Walker A, Xiong A, Stopel C, Zandi P, Frye M, Torous J. Classifying and clustering mood disorder patients using smartphone data from a feasibility study. npj Digital Medicine 2023;6(1) View
  22. Clay I, Peerenboom N, Connors D, Bourke S, Keogh A, Wac K, Gur-Arie T, Baker J, Bull C, Cereatti A, Cormack F, Eggenspieler D, Foschini L, Ganea R, Groenen P, Gusset N, Izmailova E, Kanzler C, Leyens L, Lyden K, Mueller A, Nam J, Ng W, Nobbs D, Orfaniotou F, Perumal T, Piwko W, Ries A, Scotland A, Taptiklis N, Torous J, Vereijken B, Xu S, Baltzer L, Vetter T, Goldhahn J, Hoffmann S. Reverse Engineering of Digital Measures: Inviting Patients to the Conversation. Digital Biomarkers 2023:28 View
  23. Li H, Yang S, Chi H, Xu L, Zhang T, Bao F, Stone W, Wang J. Functionality and feasibility of cognitive function training via mobile health application among youth at risk for psychosis. Exploration of Digital Health Technologies 2024:7 View
  24. Hartstein G, Peck P, Yellowlees P, Torous J. Psychotherapy in the Digital Era: A Case for Hybrid Care and Remote Therapeutic Monitoring. Harvard Review of Psychiatry 2024;32(2):63 View
  25. Harris C, Tang Y, Birnbaum E, Cherian C, Mendhe D, Chen M. Digital Neuropsychology beyond Computerized Cognitive Assessment: Applications of Novel Digital Technologies. Archives of Clinical Neuropsychology 2024;39(3):290 View
  26. Chen K, Lane E, Burns J, Macrynikola N, Chang S, Torous J. The Digital Navigator: Standardizing Human Technology Support in App-Integrated Clinical Care. Telemedicine and e-Health 2024;30(7):e1963 View
  27. Smith K, Hardy A, Vinnikova A, Blease C, Milligan L, Hidalgo-Mazzei D, Lambe S, Marzano L, Uhlhaas P, Ostinelli E, Anmella G, Zangani C, Aronica R, Dwyer B, Torous J, Cipriani A. Digital Mental Health for Schizophrenia and Other Severe Mental Illnesses: An International Consensus on Current Challenges and Potential Solutions. JMIR Mental Health 2024;11:e57155 View
  28. Kasianenko D, Dmitriyev M, Popova O, Isakova N, Drachuk N, Pachevska A. Innovative methods of treating distal occlusion: emphasis on functional restoration of the chewing and facial mimicry system in children. Reports of Vinnytsia National Medical University 2024;28(2):355 View
  29. Kuo Z, Chen K, Tseng Y. MoCab: A framework for the deployment of machine learning models across health information systems. Computer Methods and Programs in Biomedicine 2024;255:108336 View
  30. Perski O, Kale D, Leppin C, Okpako T, Simons D, Goldstein S, Hekler E, Brown J, Or C. Supervised machine learning to predict smoking lapses from Ecological Momentary Assessments and sensor data: Implications for just-in-time adaptive intervention development. PLOS Digital Health 2024;3(8):e0000594 View
  31. 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. Ethical concerns of using computer perception technologies among pediatric patients. AI and Ethics 2024 View
  32. Dwyer B, Flathers M, Burns J, Mikkelson J, Perlmutter E, Chen K, Ram N, Torous J. Assessing Digital Phenotyping for App Recommendations and Sustained Engagement: Cohort Study. JMIR Formative Research 2024;8:e62725 View
  33. Hackett K, Xu S, McKniff M, Paglia L, Barnett I, Giovannetti T. Mobility-Based Smartphone Digital Phenotypes for Unobtrusively Capturing Everyday Cognition, Mood, and Community Life-Space in Older Adults: Feasibility, Acceptability, and Preliminary Validity Study. JMIR Human Factors 2024;11:e59974 View
  34. Kasimovskaya N, Fomina E, Krivetskaya M, Diatlova E, Egorova E, Pavlov D. Determination of digital biomarkers of disease progression for digital phenotyping of patients with arterial hypertension. Vasa 2024;53(6):428 View
  35. Macrynikola N, Chen K, Lane E, Nguyen N, Pinto J, Yen S, Torous J. The Digital Clinic: Testing the Feasibility of an Innovative Digital Mental Health Care Delivery Model Designed to Increase Access to Care (Preprint). JMIR Mental Health 2024 View
  36. Öngür D, Paulus M. Embracing complexity in psychiatry—from reductionistic to systems approaches. The Lancet Psychiatry 2024 View

Books/Policy Documents

  1. Pavão J, Bastardo R, Rocha N. Information Systems and Technologies. View