Published on in Vol 3, No 2 (2016): Apr-Jun

New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research

New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research

New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research

Journals

  1. Jacobson N, Bentley K, Walton A, Wang S, Fortgang R, Millner A, Coombs G, Rodman A, Coppersmith D. Ethical dilemmas posed by mobile health and machine learning in psychiatry research. Bulletin of the World Health Organization 2020;98(4):270 View
  2. Wisniewski H, Henson P, Torous J. Using a Smartphone App to Identify Clinically Relevant Behavior Trends via Symptom Report, Cognition Scores, and Exercise Levels: A Case Series. Frontiers in Psychiatry 2019;10 View
  3. Firth J, Stubbs B, Vancampfort D, Schuch F, Rosenbaum S, Ward P, Firth J, Sarris J, Yung A. The Validity and Value of Self-reported Physical Activity and Accelerometry in People With Schizophrenia: A Population-Scale Study of the UK Biobank. Schizophrenia Bulletin 2018;44(6):1293 View
  4. Torous J, Woodyatt J, Keshavan M, Tully L. A new hope for early psychosis care: the evolving landscape of digital care tools. The British Journal of Psychiatry 2019;214(5):269 View
  5. Sezgin E, Noritz G, Elek A, Conkol K, Rust S, Bailey M, Strouse R, Chandawarkar A, von Sadovszky V, Lin S, Huang Y. Capturing At-Home Health and Care Information for Children With Medical Complexity Using Voice Interactive Technologies: Multi-Stakeholder Viewpoint. Journal of Medical Internet Research 2020;22(2):e14202 View
  6. Spinazze P, Rykov Y, Bottle A, Car J. Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol. BMJ Open 2019;9(12):e032255 View
  7. Bassett D, Khambhati A, Grafton S. Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity. Annual Review of Biomedical Engineering 2017;19(1):327 View
  8. Lind M, Byrne M, Wicks G, Smidt A, Allen N. The Effortless Assessment of Risk States (EARS) Tool: An Interpersonal Approach to Mobile Sensing. JMIR Mental Health 2018;5(3):e10334 View
  9. Jacobson N, Weingarden H, Wilhelm S. Using Digital Phenotyping to Accurately Detect Depression Severity. Journal of Nervous & Mental Disease 2019;207(10):893 View
  10. Roberts L, Chan S, Torous J. New tests, new tools: mobile and connected technologies in advancing psychiatric diagnosis. npj Digital Medicine 2018;1(1) View
  11. Place S, Blanch-Hartigan D, Rubin C, Gorrostieta C, Mead C, Kane J, Marx B, Feast J, Deckersbach T, Pentland A, Nierenberg A, Azarbayejani A. Behavioral Indicators on a Mobile Sensing Platform Predict Clinically Validated Psychiatric Symptoms of Mood and Anxiety Disorders. Journal of Medical Internet Research 2017;19(3):e75 View
  12. Fisher C, Appelbaum P. Beyond Googling: The Ethics of Using Patients' Electronic Footprints in Psychiatric Practice. Harvard Review of Psychiatry 2017;25(4):170 View
  13. Panda N, Solsky I, Haynes A. Redefining shared decision-making in the digital era. European Journal of Surgical Oncology 2019;45(12):2287 View
  14. Panda N, Solsky I, Huang E, Lipsitz S, Pradarelli J, Delisle M, Cusack J, Gadd M, Lubitz C, Mullen J, Qadan M, Smith B, Specht M, Stephen A, Tanabe K, Gawande A, Onnela J, Haynes A. Using Smartphones to Capture Novel Recovery Metrics After Cancer Surgery. JAMA Surgery 2020;155(2):123 View
  15. Sequeira L, Battaglia M, Perrotta S, Merikangas K, Strauss J. Digital Phenotyping With Mobile and Wearable Devices: Advanced Symptom Measurement in Child and Adolescent Depression. Journal of the American Academy of Child & Adolescent Psychiatry 2019;58(9):841 View
  16. Berrouiguet S, Barrigón M, Castroman J, Courtet P, Artés-Rodríguez A, Baca-García E. Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol. BMC Psychiatry 2019;19(1) View
  17. Radhakrishnan K, Kim M, Burgermaster M, Brown R, Xie B, Bray M, Fournier C. The potential of digital phenotyping to advance the contributions of mobile health to self-management science. Nursing Outlook 2020;68(5):548 View
  18. Meyer N, Kerz M, Folarin A, Joyce D, Jackson R, Karr C, Dobson R, MacCabe J. Capturing Rest-Activity Profiles in Schizophrenia Using Wearable and Mobile Technologies: Development, Implementation, Feasibility, and Acceptability of a Remote Monitoring Platform. JMIR mHealth and uHealth 2018;6(10):e188 View
  19. Kaufmann C, Gershon A, Depp C, Miller S, Zeitzer J, Ketter T. Daytime midpoint as a digital biomarker for chronotype in bipolar disorder. Journal of Affective Disorders 2018;241:586 View
  20. . Digital Sensory Phenotyping for Psychiatric Disorders. Journal of Psychiatry and Brain Science 2020 View
  21. Fagherazzi G. Deep Digital Phenotyping and Digital Twins for Precision Health: Time to Dig Deeper. Journal of Medical Internet Research 2020;22(3):e16770 View
  22. Huang E, Onnela J. Augmented Movelet Method for Activity Classification Using Smartphone Gyroscope and Accelerometer Data. Sensors 2020;20(13):3706 View
  23. H. Birk R, Samuel G. Can digital data diagnose mental health problems? A sociological exploration of ‘digital phenotyping’. Sociology of Health & Illness 2020;42(8):1873 View
  24. Mohr D, Zhang M, Schueller S. Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning. Annual Review of Clinical Psychology 2017;13(1):23 View
  25. Aledavood T, Triana Hoyos A, Alakörkkö T, Kaski K, Saramäki J, Isometsä E, Darst R. Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype. JMIR Research Protocols 2017;6(6):e110 View
  26. Barnett I, Torous J, Staples P, Keshavan M, Onnela J. Beyond smartphones and sensors: choosing appropriate statistical methods for the analysis of longitudinal data. Journal of the American Medical Informatics Association 2018;25(12):1669 View
  27. Panda N, Haynes A. Prioritizing the Patient Perspective in Oncologic Surgery. Annals of Surgical Oncology 2020;27(1):43 View
  28. Sano A, Taylor S, McHill A, Phillips A, Barger L, Klerman E, Picard R. Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study. Journal of Medical Internet Research 2018;20(6):e210 View
  29. Huckvale K, Venkatesh S, Christensen H. Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety. npj Digital Medicine 2019;2(1) View
  30. Chong N, Chu Shan Elaine C, de Korne D. Creating a Learning Televillage and Automated Digital Child Health Ecosystem. Pediatric Clinics of North America 2020;67(4):707 View
  31. Carvalho L, Sette C, Ferrari B. Problematic smartphone use relationship with pathological personality traits: Systematic review and meta-analysis. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2018;12(3) View
  32. Barnett I, Onnela J. Inferring mobility measures from GPS traces with missing data. Biostatistics 2020;21(2):e98 View
  33. Severus E, Ebner-Priemer U, Beier F, Mühlbauer E, Ritter P, Hill H, Bauer M. Ambulantes Monitoring und digitale Phänotypisierung in Diagnostik und Therapie bipolarer Erkrankungen. Der Nervenarzt 2019;90(12):1215 View
  34. Torous J, Summergrad P, Nassir Ghaemi S. Bipolar disorder in the digital age: new tools for the same illness. International Journal of Bipolar Disorders 2016;4(1) View
  35. Lin Y, Chen S, Lin P, Tai A, Pan Y, Hsieh C, Lin S. Assessing User Retention of a Mobile App: Survival Analysis. JMIR mHealth and uHealth 2020;8(11):e16309 View
  36. de Francisco Carvalho L, Sette C, Bacciotti J, Pianowski G, Marino C. Narcissistic and Histrionic Pathological Traits Association with Passive Data from Facebook Profile. Journal of Technology in Behavioral Science 2019;4(3):274 View
  37. Liu G, Henson P, Keshavan M, Pekka-Onnela J, Torous J. Assessing the potential of longitudinal smartphone based cognitive assessment in schizophrenia: A naturalistic pilot study. Schizophrenia Research: Cognition 2019;17:100144 View
  38. Barrigon M, Courtet P, Oquendo M, Baca-García E. Precision Medicine and Suicide: an Opportunity for Digital Health. Current Psychiatry Reports 2019;21(12) View
  39. Shaw R, Yang Q, Barnes A, Hatch D, Crowley M, Vorderstrasse A, Vaughn J, Diane A, Lewinski A, Jiang M, Stevenson J, Steinberg D. Self-monitoring diabetes with multiple mobile health devices. Journal of the American Medical Informatics Association 2020;27(5):667 View
  40. Melamed A, Wright A. Patient Reported Outcomes: Recent Successes and Future Opportunities. Gynecologic Oncology 2018;148(1):1 View
  41. Green M, Horan W, Lee J. Nonsocial and social cognition in schizophrenia: current evidence and future directions. World Psychiatry 2019;18(2):146 View
  42. Firth J, Torous J, Carney R, Newby J, Cosco T, Christensen H, Sarris J. Digital Technologies in the Treatment of Anxiety: Recent Innovations and Future Directions. Current Psychiatry Reports 2018;20(6) View
  43. Weizenbaum E, Torous J, Fulford D. Cognition in Context: Understanding the Everyday Predictors of Cognitive Performance in a New Era of Measurement. JMIR mHealth and uHealth 2020;8(7):e14328 View
  44. Bassett D, Mattar M. A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior. Trends in Cognitive Sciences 2017;21(4):250 View
  45. Bhidayasiri R, Mari Z. Digital phenotyping in Parkinson's disease: Empowering neurologists for measurement-based care. Parkinsonism & Related Disorders 2020;80:35 View
  46. Nugent N, Pendse S, Schatten H, Armey M. Innovations in Technology and Mechanisms of Change in Behavioral Interventions. Behavior Modification 2023;47(6):1292 View
  47. Panda N, Solsky I, Hawrusik B, Liu G, Reeder H, Lipsitz S, Desai E, Lowery K, Miller K, Gadd M, Lubitz C, Smith B, Specht M, Onnela J, Haynes A. Smartphone Global Positioning System (GPS) Data Enhances Recovery Assessment After Breast Cancer Surgery. Annals of Surgical Oncology 2021;28(2):985 View
  48. Piau A, Rumeau P, Nourhashemi F, Martin M. Information and Communication Technologies, a Promising Way to Support Pharmacotherapy for the Behavioral and Psychological Symptoms of Dementia. Frontiers in Pharmacology 2019;10 View
  49. Liang Y, Zheng X, Zeng D. A survey on big data-driven digital phenotyping of mental health. Information Fusion 2019;52:290 View
  50. Gaskins A, Hart J. The use of personal and indoor air pollution monitors in reproductive epidemiology studies. Paediatric and Perinatal Epidemiology 2020;34(5):513 View
  51. Engelhard M, Oliver J, McClernon F. Digital envirotyping: quantifying environmental determinants of health and behavior. npj Digital Medicine 2020;3(1) View
  52. Snyder J, Poisson L, Noushmehr H, Castro A, deCarvalho A, Robin A, Mukherjee A, Lee I, Walbert T. Clinical and Research Applications of a Brain Tumor Tissue Bank in the Age of Precision Medicine. Personalized Medicine 2019;16(2):145 View
  53. DiRisio A, Harary M, van Westrhenen A, Nassr E, Ermakova A, Smith T, Dirven L, Taphoorn M, Mekary R, Broekman M. Quality of reporting and assessment of patient-reported health-related quality of life in patients with brain metastases: a systematic review. Neuro-Oncology Practice 2018;5(4):214 View
  54. Kenny R, Dooley B, Fitzgerald A. Ecological Momentary Assessment of Adolescent Problems, Coping Efficacy, and Mood States Using a Mobile Phone App: An Exploratory Study. JMIR Mental Health 2016;3(4):e51 View
  55. Eddens K, Fagan J, Collins T. An Interactive, Mobile-Based Tool for Personal Social Network Data Collection and Visualization Among a Geographically Isolated and Socioeconomically Disadvantaged Population: Early-Stage Feasibility Study With Qualitative User Feedback. JMIR Research Protocols 2017;6(6):e124 View
  56. Frangou S. Commentary on: Objective smartphone data as a potential diagnostic marker of bipolar disorder. Australian & New Zealand Journal of Psychiatry 2019;53(2):170 View
  57. Fraccaro P, Beukenhorst A, Sperrin M, Harper S, Palmier-Claus J, Lewis S, Van der Veer S, Peek N. Digital biomarkers from geolocation data in bipolar disorder and schizophrenia: a systematic review. Journal of the American Medical Informatics Association 2019;26(11):1412 View
  58. Bentley K, Kleiman E, Elliott G, Huffman J, Nock M. Real-time monitoring technology in single-case experimental design research: Opportunities and challenges. Behaviour Research and Therapy 2019;117:87 View
  59. Glenn J, Nobles A, Barnes L, Teachman B. Can Text Messages Identify Suicide Risk in Real Time? A Within-Subjects Pilot Examination of Temporally Sensitive Markers of Suicide Risk. Clinical Psychological Science 2020;8(4):704 View
  60. Marsch L. Digital health data-driven approaches to understand human behavior. Neuropsychopharmacology 2021;46(1):191 View
  61. Onnela J. Opportunities and challenges in the collection and analysis of digital phenotyping data. Neuropsychopharmacology 2021;46(1):45 View
  62. Torous J, Gershon A, Hays R, Onnela J, Baker J. Digital Phenotyping for the Busy Psychiatrist: Clinical Implications and Relevance. Psychiatric Annals 2019;49(5):196 View
  63. Kleinstäuber M, Gottschalk J, Ruckmann J, Probst T, Rief W. Acceptance and Cognitive Reappraisal as Regulation Strategies for Symptom Annoyance in Individuals with Medically Unexplained Physical Symptoms. Cognitive Therapy and Research 2019;43(3):570 View
  64. Arevian A, O'Hora J, Rosser J, Mango J, Miklowitz D, Wells K. Patient and Provider Cocreation of Mobile Texting Apps to Support Behavioral Health: Usability Study. JMIR mHealth and uHealth 2020;8(7):e12655 View
  65. Benoit J, Onyeaka H, Keshavan M, Torous J. Systematic Review of Digital Phenotyping and Machine Learning in Psychosis Spectrum Illnesses. Harvard Review of Psychiatry 2020;28(5):296 View
  66. Huys Q, Renz D. A Formal Valuation Framework for Emotions and Their Control. Biological Psychiatry 2017;82(6):413 View
  67. Dissing A, Lakon C, Gerds T, Rod N, Lund R, Podobnik B. Measuring social integration and tie strength with smartphone and survey data. PLOS ONE 2018;13(8):e0200678 View
  68. Støme L, Moger T, Kidholm K, Kværner K. A Web-Based Communication Platform to Improve Home Care Services in Norway (DigiHelse): Pilot Study. JMIR Formative Research 2020;4(1):e14780 View
  69. Yang Q, Hatch D, Crowley M, Lewinski A, Vaughn J, Steinberg D, Vorderstrasse A, Jiang M, Shaw R. Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis. JMIR mHealth and uHealth 2020;8(6):e17730 View
  70. Maymone M, Venkatesh S, Secemsky E, Reddy K, Vashi N. Research Techniques Made Simple: Web-Based Survey Research in Dermatology: Conduct and Applications. Journal of Investigative Dermatology 2018;138(7):1456 View
  71. Mohr D, Shilton K, Hotopf M. Digital phenotyping, behavioral sensing, or personal sensing: names and transparency in the digital age. npj Digital Medicine 2020;3(1) View
  72. Langford A, Orellana K, Kalinowski J, Aird C, Buderer N. Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study. JMIR mHealth and uHealth 2020;8(8):e19531 View
  73. Torous J, Staples P, Barnett I, Sandoval L, Keshavan M, Onnela J. Characterizing the clinical relevance of digital phenotyping data quality with applications to a cohort with schizophrenia. npj Digital Medicine 2018;1(1) View
  74. Nebeker C, Leow A, Moore R. From Return of Information to Return of Value: Ethical Considerations when Sharing Individual-Level Research Data. Journal of Alzheimer's Disease 2019;71(4):1081 View
  75. Pratap A, Atkins D, Renn B, Tanana M, Mooney S, Anguera J, Areán P. The accuracy of passive phone sensors in predicting daily mood. Depression and Anxiety 2019;36(1):72 View
  76. Hennemann S, Farnsteiner S, Sander L. Internet- and mobile-based aftercare and relapse prevention in mental disorders: A systematic review and recommendations for future research. Internet Interventions 2018;14:1 View
  77. Torous J, Firth J, Mueller N, Onnela J, Baker J. Methodology and Reporting of Mobile Health and Smartphone Application Studies for Schizophrenia. Harvard Review of Psychiatry 2017;25(3):146 View
  78. Snyder J, Pawloski J, Poisson L. Developing Real-world Evidence-Ready Datasets: Time for Clinician Engagement. Current Oncology Reports 2020;22(5) View
  79. Rizzo C, Collibee C, Nugent N, Armey M. Let's Get Digital: Understanding Adolescent Romantic Relationships Using Naturalistic Assessments of Digital Communication. Child Development Perspectives 2019;13(2):104 View
  80. Biagianti B, Hidalgo-Mazzei D, Meyer N. Developing digital interventions for people living with serious mental illness: perspectives from three mHealth studies. Evidence Based Mental Health 2017;20(4):98 View
  81. Bourla A, Ferreri F, Ogorzelec L, Guinchard C, Mouchabac S. Évaluation des troubles thymiques par l’étude des données passives : le concept de phénotype digital à l’épreuve de la culture de métier de psychiatre. L'Encéphale 2018;44(2):168 View
  82. Meers K, Dejonckheere E, Kalokerinos E, Rummens K, Kuppens P. mobileQ: A free user-friendly application for collecting experience sampling data. Behavior Research Methods 2020;52(4):1510 View
  83. Bond R, Moorhead A, Mulvenna M, O'Neill S, Potts C, Murphy N. Exploring temporal behaviour of app users completing ecological momentary assessments using mental health scales and mood logs. Behaviour & Information Technology 2019;38(10):1016 View
  84. Rieger A, Gaines A, Barnett I, Baldassano C, Connolly Gibbons M, Crits-Christoph P. Psychiatry Outpatients’ Willingness to Share Social Media Posts and Smartphone Data for Research and Clinical Purposes: Survey Study. JMIR Formative Research 2019;3(3):e14329 View
  85. Torous J, Onnela J, Keshavan M. New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices. Translational Psychiatry 2017;7(3):e1053 View
  86. Braga R, Buckner R. Parallel Interdigitated Distributed Networks within the Individual Estimated by Intrinsic Functional Connectivity. Neuron 2017;95(2):457 View
  87. Bell I, Alvarez-Jimenez M. Digital Technology to Enhance Clinical Care of Early Psychosis. Current Treatment Options in Psychiatry 2019;6(3):256 View
  88. Reinertsen E, Clifford G. A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses. Physiological Measurement 2018;39(5):05TR01 View
  89. Campbell L, Paolillo E, Heaton A, Tang B, Depp C, Granholm E, Heaton R, Swendsen J, Moore D, Moore R. Daily Activities Related to Mobile Cognitive Performance in Middle-Aged and Older Adults: An Ecological Momentary Cognitive Assessment Study. JMIR mHealth and uHealth 2020;8(9):e19579 View
  90. Predmore Z, Hatef E, Weiner J. Integrating Social and Behavioral Determinants of Health into Population Health Analytics: A Conceptual Framework and Suggested Road Map. Population Health Management 2019;22(6):488 View
  91. Torous J, Wisniewski H, Bird B, Carpenter E, David G, Elejalde E, Fulford D, Guimond S, Hays R, Henson P, Hoffman L, Lim C, Menon M, Noel V, Pearson J, Peterson R, Susheela A, Troy H, Vaidyam A, Weizenbaum E, Naslund J, Keshavan M. Creating a Digital Health Smartphone App and Digital Phenotyping Platform for Mental Health and Diverse Healthcare Needs: an Interdisciplinary and Collaborative Approach. Journal of Technology in Behavioral Science 2019;4(2):73 View
  92. Torous J, Staples P, Barnett I, Onnela J, Keshavan M. A crossroad for validating digital tools in schizophrenia and mental health. npj Schizophrenia 2018;4(1) View
  93. Maramis C, Moulos I, Ioakimidis I, Papapanagiotou V, Langlet B, Lekka I, Bergh C, Maglaveras N. A smartphone application for semi-controlled collection of objective eating behavior data from multiple subjects. Computer Methods and Programs in Biomedicine 2020;194:105485 View
  94. Berry J, Paganoni S, Carlson K, Burke K, Weber H, Staples P, Salinas J, Chan J, Green J, Connaghan K, Barback J, Onnela J. Design and results of a smartphone‐based digital phenotyping study to quantify ALS progression. Annals of Clinical and Translational Neurology 2019;6(5):873 View
  95. Wilson J, Altman R. Biomarkers: Delivering on the expectation of molecularly driven, quantitative health. Experimental Biology and Medicine 2018;243(3):313 View
  96. Barnett S, Huckvale K, Christensen H, Venkatesh S, Mouzakis K, Vasa R. Intelligent Sensing to Inform and Learn (InSTIL): A Scalable and Governance-Aware Platform for Universal, Smartphone-Based Digital Phenotyping for Research and Clinical Applications. Journal of Medical Internet Research 2019;21(11):e16399 View
  97. Boonstra T, Nicholas J, Wong Q, Shaw F, Townsend S, Christensen H. Using Mobile Phone Sensor Technology for Mental Health Research: Integrated Analysis to Identify Hidden Challenges and Potential Solutions. Journal of Medical Internet Research 2018;20(7):e10131 View
  98. Panda N, Solsky I, Onnela J, Haynes A. ASO Author Reflections: Applications of Smartphone-Based Digital Phenotyping in Supplementing Recovery Assessment After Cancer Surgery. Annals of Surgical Oncology 2020;27(S3):909 View
  99. Barnett I, Torous J, Staples P, Sandoval L, Keshavan M, Onnela J. Relapse prediction in schizophrenia through digital phenotyping: a pilot study. Neuropsychopharmacology 2018;43(8):1660 View
  100. Onnela J, Rauch S. Harnessing Smartphone-Based Digital Phenotyping to Enhance Behavioral and Mental Health. Neuropsychopharmacology 2016;41(7):1691 View
  101. Bhattacharya K, Kaski K. Social physics: uncovering human behaviour from communication. Advances in Physics: X 2019;4(1):1527723 View
  102. Cote D, Barnett I, Onnela J, Smith T. Digital Phenotyping in Patients with Spine Disease: A Novel Approach to Quantifying Mobility and Quality of Life. World Neurosurgery 2019;126:e241 View
  103. Berrouiguet S, Ramírez D, Barrigón M, Moreno-Muñoz P, Carmona Camacho R, Baca-García E, Artés-Rodríguez A. Combining Continuous Smartphone Native Sensors Data Capture and Unsupervised Data Mining Techniques for Behavioral Changes Detection: A Case Series of the Evidence-Based Behavior (eB2) Study. JMIR mHealth and uHealth 2018;6(12):e197 View
  104. Torous J, Rodriguez J, Powell A. The New Digital Divide For Digital Biomarkers. Digital Biomarkers 2017;1(1):87 View
  105. Wright A, Raman N, Staples P, Schonholz S, Cronin A, Carlson K, Keating N, Onnela J. The HOPE Pilot Study: Harnessing Patient-Reported Outcomes and Biometric Data to Enhance Cancer Care. JCO Clinical Cancer Informatics 2018;(2):1 View
  106. Gruber W, Powell A, Torous J. The power of capturing and using information at the point of care. Healthcare 2017;5(3):86 View
  107. Lee J, Kim H, Kim D. Recent Technology-Driven Advancements in Cardiovascular Disease Prevention in Korea. Cardiovascular Prevention and Pharmacotherapy 2019;1(2):43 View
  108. Tekin Ş. Is Big Data the New Stethoscope? Perils of Digital Phenotyping to Address Mental Illness. Philosophy & Technology 2021;34(3):447 View
  109. . Theme 10 Disease stratification and phenotyping. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration 2018;19(sup1):282 View
  110. Melcher J, Hays R, Torous J. Digital phenotyping for mental health of college students: a clinical review. Evidence Based Mental Health 2020;23(4):161 View
  111. de Moura I, Teles A, Endler M, Coutinho L, da Silva e Silva F. Recognizing Context-Aware Human Sociability Patterns Using Pervasive Monitoring for Supporting Mental Health Professionals. Sensors 2020;21(1):86 View
  112. Davidson B. The crossroads of digital phenotyping. General Hospital Psychiatry 2022;74:126 View
  113. Rodriguez-Villa E, Mehta U, Naslund J, Tugnawat D, Gupta S, Thirtalli J, Bhan A, Patel V, Chand P, Rozatkar A, Keshavan M, Torous J. Smartphone Health Assessment for Relapse Prevention (SHARP): a digital solution toward global mental health. BJPsych Open 2021;7(1) View
  114. Gauld C, Dumas G, Fakra É, Mattout J, Micoulaud-Franchi J. Les trois cultures de la psychiatrie computationnelle. Annales Médico-psychologiques, revue psychiatrique 2021;179(1):63 View
  115. Barnett I, Torous J, Reeder H, Baker J, Onnela J. Determining sample size and length of follow-up for smartphone-based digital phenotyping studies. Journal of the American Medical Informatics Association 2020;27(12):1844 View
  116. Orsolini L, Fiorani M, Volpe U. Digital Phenotyping in Bipolar Disorder: Which Integration with Clinical Endophenotypes and Biomarkers?. International Journal of Molecular Sciences 2020;21(20):7684 View
  117. Jagesar R, Roozen M, van der Heijden I, Ikani N, Tyborowska A, Penninx B, Ruhe H, Sommer I, Kas M, Vorstman J. Digital phenotyping and the COVID-19 pandemic: Capturing behavioral change in patients with psychiatric disorders. European Neuropsychopharmacology 2021;42:115 View
  118. Pavarini G, McMillan R, Robinson A, Singh I. Design Bioethics: A Theoretical Framework and Argument for Innovation in Bioethics Research. The American Journal of Bioethics 2021;21(6):37 View
  119. Henson P, Peck P, Torous J. Considering the Therapeutic Alliance in Digital Mental Health Interventions. Harvard Review of Psychiatry 2019;27(4):268 View
  120. Bukowski R, Schulz K, Gaither K, Stephens K, Semeraro D, Drake J, Smith G, Cordola C, Zariphopoulou T, Hughes T, Zarins C, Kusnezov D, Howard D, Oden T. Computational medicine, present and the future: obstetrics and gynecology perspective. American Journal of Obstetrics and Gynecology 2021;224(1):16 View
  121. Pedrelli P, Fedor S, Ghandeharioun A, Howe E, Ionescu D, Bhathena D, Fisher L, Cusin C, Nyer M, Yeung A, Sangermano L, Mischoulon D, Alpert J, Picard R. Monitoring Changes in Depression Severity Using Wearable and Mobile Sensors. Frontiers in Psychiatry 2020;11 View
  122. Moshe I, Terhorst Y, Opoku Asare K, Sander L, Ferreira D, Baumeister H, Mohr D, Pulkki-Råback L. Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data. Frontiers in Psychiatry 2021;12 View
  123. Mendes-Santos C, Andersson G, Weiderpass E, Santana R. Mitigating COVID-19 Impact on the Portuguese Population Mental Health: The Opportunity That Lies in Digital Mental Health. Frontiers in Public Health 2020;8 View
  124. Jagesar R, Vorstman J, Kas M. Requirements and Operational Guidelines for Secure and Sustainable Digital Phenotyping: Design and Development Study. Journal of Medical Internet Research 2021;23(4):e20996 View
  125. Van Daele T, Best P, Bernaerts S, Van Assche E, De Witte N. Dropping the E: The potential for integrating e-mental health in psychotherapy. Current Opinion in Psychology 2021;41:46 View
  126. Camacho E, Brady R, Lizano P, Keshavan M, Torous J. Advancing translational research through the interface of digital phenotyping and neuroimaging: A narrative review. Biomarkers in Neuropsychiatry 2021;4:100032 View
  127. Melcher J, Lavoie J, Hays R, D'Mello R, Rauseo-Ricupero N, Camacho E, Rodriguez-Villa E, Wisniewski H, Lagan S, Vaidyam A, Torous J. Digital phenotyping of student mental health during COVID-19: an observational study of 100 college students. Journal of American College Health 2023;71(3):736 View
  128. Henson P, Rodriguez-Villa E, Torous J. Investigating Associations Between Screen Time and Symptomatology in Individuals With Serious Mental Illness: Longitudinal Observational Study. Journal of Medical Internet Research 2021;23(3):e23144 View
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  249. Xia C, Barnett I, Tapera T, Adebimpe A, Baker J, Bassett D, Brotman M, Calkins M, Cui Z, Leibenluft E, Linguiti S, Lydon-Staley D, Martin M, Moore T, Murtha K, Piiwaa K, Pines A, Roalf D, Rush-Goebel S, Wolf D, Ungar L, Satterthwaite T. Mobile footprinting: linking individual distinctiveness in mobility patterns to mood, sleep, and brain functional connectivity. Neuropsychopharmacology 2022;47(9):1662 View
  250. Coppersmith D, Wang S, Kleiman E, Maimone J, Fedor S, Bentley K, Millner A, Fortgang R, Picard R, Beck S, Huffman J, Nock M. Real-time digital monitoring of a suicide attempt by a hospital patient. General Hospital Psychiatry 2023;80:35 View
  251. Choudhary S, Thomas N, Ellenberger J, Srinivasan G, Cohen R. A Machine Learning Approach for Detecting Digital Behavioral Patterns of Depression Using Nonintrusive Smartphone Data (Complementary Path to Patient Health Questionnaire-9 Assessment): Prospective Observational Study. JMIR Formative Research 2022;6(5):e37736 View
  252. Ren B, Xia C, Gehrman P, Barnett I, Satterthwaite T. Measuring Daily Activity Rhythms in Young Adults at Risk of Affective Instability Using Passively Collected Smartphone Data: Observational Study. JMIR Formative Research 2022;6(9):e33890 View
  253. Staples P, Torous J, Barnett I, Carlson K, Sandoval L, Keshavan M, Onnela J. A comparison of passive and active estimates of sleep in a cohort with schizophrenia. npj Schizophrenia 2017;3(1) View
  254. Stampfler T, Elgendi M, Fletcher R, Menon C. The use of deep learning for smartphone-based human activity recognition. Frontiers in Public Health 2023;11 View
  255. Marciano L, Saboor S. Reinventing mental health care in youth through mobile approaches: Current status and future steps. Frontiers in Psychology 2023;14 View
  256. Haddas R, Lawlor M, Moghadam E, Fields A, Wood A. Spine patient care with wearable medical technology: state-of-the-art, opportunities, and challenges: a systematic review. The Spine Journal 2023;23(7):929 View
  257. Langener A, Stulp G, Kas M, Bringmann L. Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review. JMIR Mental Health 2023;10:e42646 View
  258. Xia W, Basford M, Carroll R, Clayton E, Harris P, Kantacioglu M, Liu Y, Nyemba S, Vorobeychik Y, Wan Z, Malin B. Managing re-identification risks while providing access to the All of Us research program. Journal of the American Medical Informatics Association 2023;30(5):907 View
  259. Čermák J, Pietrucha S, Nawka A, Lipone P, Ruggieri A, Bonelli A, Comandini A, Cattaneo A. An Observational Pilot Study using a Digital Phenotyping Approach in Patients with Major Depressive Disorder Treated with Trazodone. Frontiers in Psychiatry 2023;14 View
  260. Langholm C, Byun A, Mullington J, Torous J. Monitoring sleep using smartphone data in a population of college students. npj Mental Health Research 2023;2(1) View
  261. Kim W, Kim H, Pack S, Lim J, Cho C, Lee H. Machine Learning–Based Prediction of Attention-Deficit/Hyperactivity Disorder and Sleep Problems With Wearable Data in Children. JAMA Network Open 2023;6(3):e233502 View
  262. Kalisperakis E, Karantinos T, Lazaridi M, Garyfalli V, Filntisis P, Zlatintsi A, Efthymiou N, Mantas A, Mantonakis L, Mougiakos T, Maglogiannis I, Tsanakas P, Maragos P, Smyrnis N. Smartwatch digital phenotypes predict positive and negative symptom variation in a longitudinal monitoring study of patients with psychotic disorders. Frontiers in Psychiatry 2023;14 View
  263. Walk D, Nicholson K, Locatelli E, Chan J, Macklin E, Ferment V, Manousakis G, Chase M, Connolly M, Dagostino D, Hall M, Ostrow J, Pothier L, Lieberman C, Gelevski D, Randall R, Sherman A, Steinhart E, Walker D, Walker J, Yu H, Wills A, Schwarzschild M, Beukenhorst A, Onnela J, Berry J, Cudkowicz M, Paganoni S. Randomized trial of inosine for urate elevation in amyotrophic lateral sclerosis. Muscle & Nerve 2023;67(5):378 View
  264. Duey A, Rana A, Siddi F, Hussein H, Onnela J, Smith T. Daily Pain Prediction Using Smartphone Speech Recordings of Patients With Spine Disease. Neurosurgery 2023;93(3):670 View
  265. Alfalahi H, Dias S, Khandoker A, Chaudhuri K, Hadjileontiadis L. A scoping review of neurodegenerative manifestations in explainable digital phenotyping. npj Parkinson's Disease 2023;9(1) View
  266. Hicks J, Boswell M, Althoff T, Crum A, Ku J, Landay J, Moya P, Murnane E, Snyder M, King A, Delp S. Leveraging Mobile Technology for Public Health Promotion: A Multidisciplinary Perspective. Annual Review of Public Health 2023;44(1):131 View
  267. Hidd V, López E, Centellegher S, Roberts S, Lepri B, Dunbar R. The stability of transient relationships. Scientific Reports 2023;13(1) View
  268. Yang F, Shah D, Tahk A, Vjorn O, Dietz S, Pe-Romashko K, Bailey E, Gicquelais R, Hwang J, Gustafson D, Westergaard R. mHealth and social mediation: Mobile support among stigmatized people living with HIV and substance use disorder. New Media & Society 2023;25(4):702 View
  269. Ren B, Barnett I. Combining Mixed Effects Hidden Markov Models with Latent Alternating Recurrent Event Processes to Model Diurnal Active–Rest Cycles. Biometrics 2023;79(4):3402 View
  270. Lam S, Xie Q, Goldberg S. Situating Meditation Apps Within the Ecosystem of Meditation Practice: Population-Based Survey Study. JMIR Mental Health 2023;10:e43565 View
  271. Shen F, Baum M, Martinez-Martin N, Miner A, Abraham M, Brownstein C, Cortez N, Evans B, Germine L, Glahn D, Grady C, Holm I, Hurley E, Kimble S, Lázaro-Muñoz G, Leary K, Marks M, Monette P, Onnela J, O’Rourke P, Rauch S, Shachar C, Sen S, Vahia I, Vassy J, Baker J, Bierer B, Silverman B. Returning Individual Research Results from Digital Phenotyping in Psychiatry. The American Journal of Bioethics 2024;24(2):69 View
  272. Mittermaier M, Venkatesh K, Kvedar J. Digital health technology in clinical trials. npj Digital Medicine 2023;6(1) View
  273. Bell I, Eisner E, Allan S, Cartner S, Torous J, Bucci S, Thomas N. Methodological Characteristics and Feasibility of Ecological Momentary Assessment Studies in Psychosis: a Systematic Review and Meta-Analysis. Schizophrenia Bulletin 2024;50(2):238 View
  274. Gupta P, Muneshwar K, Juganavar A, Shegekar T. Beyond the Asylum Walls: Tracing the Tapestry of Mental Health Interventions Across Eras and Cultures. Cureus 2023 View
  275. Jordan Y. Arpilleda . Predictive Maintenance Strategies for Electrical Equipment: A Literature Review. International Journal of Advanced Research in Science, Communication and Technology 2023:612 View
  276. Li A, Liu R, Liu X, Han J. Editorial: Improving the clinical value of digital phenotyping in mental health. Frontiers in Psychiatry 2023;14 View
  277. Spanakis P, Lorimer B, Newbronner E, Wadman R, Crosland S, Gilbody S, Johnston G, Walker L, Peckham E. Digital health literacy and digital engagement for people with severe mental ill health across the course of the COVID-19 pandemic in England. BMC Medical Informatics and Decision Making 2023;23(1) View
  278. Misiak B, Samochowiec J, Kowalski K, Gaebel W, Bassetti C, Chan A, Gorwood P, Papiol S, Dom G, Volpe U, Szulc A, Kurimay T, Kärkkäinen H, Decraene A, Wisse J, Fiorillo A, Falkai P. The future of diagnosis in clinical neurosciences: Comparing multiple sclerosis and schizophrenia. European Psychiatry 2023;66(1) View
  279. Oueidat K, Baird G, Bernstein M, Kim N, Kim D, Dubel G, Jay B, Maxwell A. A Pilot Study of Accelerometer-Based Biometric Data Collection among Patients Undergoing Locoregional Therapies. Journal of Vascular and Interventional Radiology 2023;34(8):1331 View
  280. Seiferth C, Vogel L, Aas B, Brandhorst I, Carlbring P, Conzelmann A, Esfandiari N, Finkbeiner M, Hollmann K, Lautenbacher H, Meinzinger E, Newbold A, Opitz A, Renner T, Sander L, Santangelo P, Schoedel R, Schuller B, Stachl C, Terhorst Y, Torous J, Wac K, Werner-Seidler A, Wolf S, Löchner J. How to e-mental health: a guideline for researchers and practitioners using digital technology in the context of mental health. Nature Mental Health 2023;1(8):542 View
  281. Kim Y, Shin B, Kim K. Digital Biomarkers for Alzheimer’s Disease. Journal of the Korean Neurological Association 2023;41(4):268 View
  282. Pizzoli S, Monzani D, Conti L, Ferraris G, Grasso R, Pravettoni G. Issues and opportunities of digital phenotyping: ecological momentary assessment and behavioral sensing in protecting the young from suicide. Frontiers in Psychology 2023;14 View
  283. Marder S, Umbricht D. Negative symptoms in schizophrenia: Newly emerging measurements, pathways, and treatments. Schizophrenia Research 2023;258:71 View
  284. Barrigon M, Romero-Medrano L, Moreno-Muñoz P, Porras-Segovia A, Lopez-Castroman J, Courtet P, Artés-Rodríguez A, Baca-Garcia E. One-Week Suicide Risk Prediction Using Real-Time Smartphone Monitoring: Prospective Cohort Study. Journal of Medical Internet Research 2023;25:e43719 View
  285. Patrickson B, Musker M, Thorpe D, van Kasteren Y, Bidargaddi N. In-Depth Co-Design of Mental Health Monitoring Technologies by People with Lived Experience. Future Internet 2023;15(6):191 View
  286. Faurholt-Jepsen M, Kyster N, Dyreholt M, Christensen E, Bondo-Kozuch P, Lerche A, Smidt B, Knorr U, Brøndmark K, Cardoso A, Mathiesen A, Sjælland R, Nørbak-Emig H, Sponsor L, Mardosas D, Sarauw-Nielsen I, Bukh J, Heller T, Frost M, Iversen N, Bardram J, Busk J, Vinberg M, Kessing L. The effect of smartphone-based monitoring and treatment including clinical feedback versus smartphone-based monitoring without clinical feedback in bipolar disorder: the SmartBipolar trial—a study protocol for a randomized controlled parallel-group trial. Trials 2023;24(1) View
  287. Carlezon W, Timm S. NPP-Digital Psychiatry and Neuroscience (DPN): a new journal for the era upon us. NPP—Digital Psychiatry and Neuroscience 2023;1(1) View
  288. Lenze E, Torous J, Arean P. Digital and precision clinical trials: innovations for testing mental health medications, devices, and psychosocial treatments. Neuropsychopharmacology 2024;49(1):205 View
  289. 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
  290. Kelkar R, Currey D, Nagendra S, Mehta U, Sreeraj V, Torous J, Thirthalli J. Utility of Smartphone-Based Digital Phenotyping Biomarkers in Assessing Treatment Response to Transcranial Magnetic Stimulation in Depression: Proof-of-Concept Study. JMIR Formative Research 2023;7:e40197 View
  291. Muurling M, Pasmooij A, Koychev I, Roik D, Froelich L, Schwertner E, Religa D, Abdelnour C, Boada M, Almici M, Galluzzi S, Cardoso S, de Mendonça A, Owens A, Kuruppu S, Gjestsen M, Lazarou I, Gkioka M, Tsolaki M, Diaz A, Gove D, Visser P, Aarsland D, Lucivero F, de Boer C, Chu D. Ethical challenges of using remote monitoring technologies for clinical research: A case study of the role of local research ethics committees in the RADAR-AD study. PLOS ONE 2023;18(7):e0285807 View
  292. Lozano Hernández C, Medina-García R, de Hoyos-Alonso M, Garrido-Barral A, Minué Lorenzo C, Sanz-Cuesta T, Serrano J, del Rio Ponce A, Gómez-Gascón T, del Cura-González I. Improvement in Quality of Life With the Use of a Technological System Among Patients With Chronic Disease Followed Up in Primary Care (TeNDER Project): Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2023;12:e47331 View
  293. Marin-Dragu S, Forbes A, Sheikh S, Iyer R, Pereira dos Santos D, Alda M, Hajek T, Uher R, Wozney L, Paulovich F, Campbell L, Yakovenko I, Stewart S, Corkum P, Bagnell A, Orji R, Meier S. Associations of active and passive smartphone use with measures of youth mental health during the COVID-19 pandemic. Psychiatry Research 2023;326:115298 View
  294. Pyper E, McKeown S, Hartmann-Boyce J, Powell J. Digital Health Technology for Real-World Clinical Outcome Measurement Using Patient-Generated Data: Systematic Scoping Review. Journal of Medical Internet Research 2023;25:e46992 View
  295. 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
  296. 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
  297. 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
  298. Mayo K, Basford M, Carroll R, Dillon M, Fullen H, Leung J, Master H, Rura S, Sulieman L, Kennedy N, Banks E, Bernick D, Gauchan A, Lichtenstein L, Mapes B, Marginean K, Nyemba S, Ramirez A, Rotundo C, Wolfe K, Xia W, Azuine R, Cronin R, Denny J, Kho A, Lunt C, Malin B, Natarajan K, Wilkins C, Xu H, Hripcsak G, Roden D, Philippakis A, Glazer D, Harris P. The All of Us Data and Research Center: Creating a Secure, Scalable, and Sustainable Ecosystem for Biomedical Research. Annual Review of Biomedical Data Science 2023;6(1):443 View
  299. Lane E, D’Arcey J, Kidd S, Onyeaka H, Alon N, Joshi D, Torous J. Digital Phenotyping in Adults with Schizophrenia: A Narrative Review. Current Psychiatry Reports 2023;25(11):699 View
  300. Valeri L, Rahimi-Eichi H, Liebenthal E, Rauch S, Schutt R, Öngür D, Dixon L, Onnela J, Baker J. Intensive longitudinal assessment of mobility, social activity and loneliness in individuals with severe mental illness during COVID-19. Schizophrenia 2023;9(1) View
  301. Ikäheimonen A, Triana A, Luong N, Ziaei A, Rantaharju J, Darst R, Aledavood T. Niimpy: A toolbox for behavioral data analysis. SoftwareX 2023;23:101472 View
  302. Jenciūtė G, Kasputytė G, Bunevičienė I, Korobeinikova E, Vaitiekus D, Inčiūra A, Jaruševičius L, Bunevičius R, Krikštolaitis R, Krilavičius T, Juozaitytė E, Bunevičius A. Digital Phenotyping for Monitoring and Disease Trajectory Prediction of Patients With Cancer: Protocol for a Prospective Observational Cohort Study. JMIR Research Protocols 2023;12:e49096 View
  303. 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
  304. Pellegrini A, Huang E, Staples P, Hart K, Lorme J, Brown H, Perlis R, Onnela J. Estimating longitudinal depressive symptoms from smartphone data in a transdiagnostic cohort. Brain and Behavior 2022;12(2) View
  305. Jurek M, Calder C, Zigler C. Statistical inference for complete and incomplete mobility trajectories under the flight-pause model. Journal of the Royal Statistical Society Series C: Applied Statistics 2024;73(1):162 View
  306. Breitinger S, Gardea-Resendez M, Langholm C, Xiong A, Laivell J, Stoppel C, Harper L, Volety R, Walker A, D'Mello R, Byun A, Zandi P, Goes F, Frye M, Torous J. Digital Phenotyping for Mood Disorders: Methodology-Oriented Pilot Feasibility Study. Journal of Medical Internet Research 2023;25:e47006 View
  307. 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
  308. Nestor B, Chimoff J, Koike C, Weitzman E, Riley B, Uhl K, Kossowsky J. Adolescent and Parent Perspectives on Digital Phenotyping in Youths With Chronic Pain: Cross-Sectional Mixed Methods Survey Study. Journal of Medical Internet Research 2024;26:e47781 View
  309. Wu T, Sherman G, Giorgi S, Thanneeru P, Ungar L, Kamath P, Simonetto D, Curtis B, Shah V. Smartphone sensor data estimate alcohol craving in a cohort of patients with alcohol-associated liver disease and alcohol use disorder. Hepatology Communications 2023;7(12) View
  310. Grieb N, Schmierer L, Kim H, Strobel S, Schulz C, Meschke T, Kubasch A, Brioli A, Platzbecker U, Neumuth T, Merz M, Oeser A. A digital twin model for evidence-based clinical decision support in multiple myeloma treatment. Frontiers in Digital Health 2023;5 View
  311. Kalman J, Burkhardt G, Samochowiec J, Gebhard C, Dom G, John M, Kilic O, Kurimay T, Lien L, Schouler-Ocak M, Vidal D, Wiser J, Gaebel W, Volpe U, Falkai P. Digitalising mental health care: Practical recommendations from the European Psychiatric Association. European Psychiatry 2024;67(1) View
  312. Kasputytė G, Jenciūtė G, Šakinis N, Bunevičienė I, Korobeinikova E, Vaitiekus D, Inčiūra A, Jaruševičius L, Bunevičius R, Krikštolaitis R, Krilavičius T, Juozaitytė E, Bunevičius A. Smartphone sensors for evaluating COVID-19 fear in patients with cancer: a prospective study. Frontiers in Public Health 2024;11 View
  313. Higgins B, Jones L, Devraj K, Kilduff C, Moosajee M. ‘It would help people to help me’: Acceptability of digital phenotyping among young people with visual impairment and their families. DIGITAL HEALTH 2024;10 View
  314. London A, Karlawish J, Largent E, Hey S, McCarthy E. Algorithmic identification of persons with dementia for research recruitment: ethical considerations. Informatics for Health and Social Care 2024;49(1):28 View
  315. Langener A, Bringmann L, Kas M, Stulp G. Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks. Administration and Policy in Mental Health and Mental Health Services Research 2024;51(4):455 View
  316. Wadle L, Ebner-Priemer U, Foo J, Yamamoto Y, Streit F, Witt S, Frank J, Zillich L, Limberger M, Ablimit A, Schultz T, Gilles M, Rietschel M, Sirignano L. Speech Features as Predictors of Momentary Depression Severity in Patients With Depressive Disorder Undergoing Sleep Deprivation Therapy: Ambulatory Assessment Pilot Study. JMIR Mental Health 2024;11:e49222 View
  317. Ahn C, Lee J. Digital Phenotyping for Real-Time Monitoring of Nonsuicidal Self-Injury: Protocol for a Prospective Observational Study. JMIR Research Protocols 2024;13:e53597 View
  318. Langener A, Stulp G, Jacobson N, Costanzo A, Jagesar R, Kas M, Bringmann L. It’s All About Timing: Exploring Different Temporal Resolutions for Analyzing Digital-Phenotyping Data. Advances in Methods and Practices in Psychological Science 2024;7(1) View
  319. 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
  320. Fu M, Shen J, Gu C, Oliveira E, Shinchuk E, Isaac H, Isaac Z, Sarno D, Kurz J, Silbersweig D, Onnela J, Barron D. The Pain Intervention & Digital Research Program: an operational report on combining digital research with outpatient chronic disease management. Frontiers in Pain Research 2024;5 View
  321. Jung G, Park S, Ma E, Kim H, Lee U. Tutorial on Matching-based Causal Analysis of Human Behaviors Using Smartphone Sensor Data. ACM Computing Surveys 2024;56(9):1 View
  322. Kilshaw R, Boggins A, Everett O, Butner E, Leifker F, Baucom B. Benchmarking Mental Health Status Using Passive Sensor Data: Protocol for a Prospective Observational Study. JMIR Research Protocols 2024;13:e53857 View
  323. Bryan A, Heinz M, Salzhauer A, Price G, Tlachac M, Jacobson N. Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment. Biomedical Materials & Devices 2024;2(2):778 View
  324. Perlmutter E, Dwyer B, Torous J. Social Media and Youth Mental Health: Assessing the Impact Through Current and Novel Digital Phenotyping Methods. Current Treatment Options in Psychiatry 2024;11(2):34 View
  325. Fowler C, Cai X, Baker J, Onnela J, Valeri L. Testing unit root non-stationarity in the presence of missing data in univariate time series of mobile health studies. Journal of the Royal Statistical Society Series C: Applied Statistics 2024;73(3):755 View
  326. Triana A, Saramäki J, Glerean E, Hayward N. Neuroscience meets behavior: A systematic literature review on magnetic resonance imaging of the brain combined with real‐world digital phenotyping. Human Brain Mapping 2024;45(4) View
  327. Knol L, Nagpal A, Leaning I, Idda E, Hussain F, Ning E, Eisenlohr-Moul T, Beckmann C, Marquand A, Leow A. Smartphone keyboard dynamics predict affect in suicidal ideation. npj Digital Medicine 2024;7(1) View
  328. Zapalac K, Miller M, Champagne F, Schnyer D, Baird B. The effects of physical activity on sleep architecture and mood in naturalistic environments. Scientific Reports 2024;14(1) View
  329. Keshmiri S, Tomonaga S, Mizutani H, Doya K. Respiratory modulation of the heart rate: A potential biomarker of cardiorespiratory function in human. Computers in Biology and Medicine 2024;173:108335 View
  330. Loftness B, Halvorson-Phelan J, O'Leary A, Bradshaw C, Prytherch S, Berman I, Torous J, Copeland W, Cheney N, McGinnis R, McGinnis E. The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health. IEEE Journal of Biomedical and Health Informatics 2024;28(4):2304 View
  331. Li A, Xue C, Wu R, Wu W, Zhao J, Qiang Y. Unearthing Subtle Cognitive Variations: A Digital Screening Tool for Detecting and Monitoring Mild Cognitive Impairment. International Journal of Human–Computer Interaction 2024:1 View
  332. Beames J, Han J, Shvetcov A, Zheng W, Slade A, Ibrahim O, Rosenberg J, O’Dea B, Kasturi S, Hoon L, Whitton A, Christensen H, Newby J. Use of Smartphone Sensor Data in Detecting and Predicting Depression and Anxiety in Young People (12-25 Years): A Scoping Review. SSRN Electronic Journal 2024 View
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  334. Vidal Bustamante C, Coombs III G, Rahimi-Eichi H, Mair P, Onnela J, Baker J, Buckner R. Precision Assessment of Real-World Associations Between Stress and Sleep Duration Using Actigraphy Data Collected Continuously for an Academic Year: Individual-Level Modeling Study. JMIR Formative Research 2024;8:e53441 View
  335. Martin J, Rueda A, Lee G, Tassone V, Park H, Ivanov M, Darnell B, Beavers L, Campbell D, Nguyen B, Torres A, Jung H, Lou W, Nazarov A, Ashbaugh A, Kapralos B, Litz B, Jetly R, Dubrowski A, Strudwick G, Krishnan S, Bhat V. Digital Interventions to Understand and Mitigate Stress Response: Protocol for Process and Content Evaluation of a Cohort Study. JMIR Research Protocols 2024;13:e54180 View
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Books/Policy Documents

  1. Baños R, Vara M, Mira A, García-Palacios A, Botella C. Comprehensive Clinical Psychology. View
  2. Teles A, Barros F, Rodrigues I, Barbosa A, Silva F, Coutinho L, Teixeira S. IoT and ICT for Healthcare Applications. View
  3. Zeng Y, Fraccaro P, Peek N. Artificial Intelligence in Medicine. View
  4. Bell I, Lim M, Thomas N. A Clinical Introduction to Psychosis. View
  5. Senders J, Maher N, Hulsbergen A, Lamba N, Bredenoord A, Broekman M. Ethics of Innovation in Neurosurgery. View
  6. Ebert D, Harrer M, Apolinário-Hagen J, Baumeister H. Frontiers in Psychiatry. View
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