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Published on 05.05.16 in Vol 3, No 2 (2016): Apr-Jun

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

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

According to Crossref, the following articles are citing this article (DOI 10.2196/mental.5165):

(note that this is only a small subset of citations)

  1. Jacobson NC, Bentley KH, Walton A, Wang SB, Fortgang RG, Millner AJ, Coombs G, Rodman AM, Coppersmith DDL. Ethical dilemmas posed by mobile health and machine learning in psychiatry research. Bulletin of the World Health Organization 2020;98(4):270
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  9. Shaw RJ, Yang Q, Barnes A, Hatch D, Crowley MJ, Vorderstrasse A, Vaughn J, Diane A, Lewinski AA, 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
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  12. Panda N, Solsky I, Huang EJ, Lipsitz S, Pradarelli JC, Delisle M, Cusack JC, Gadd MA, Lubitz CC, Mullen JT, Qadan M, Smith BL, Specht M, Stephen AE, Tanabe KK, Gawande AA, Onnela J, Haynes AB. Using Smartphones to Capture Novel Recovery Metrics After Cancer Surgery. JAMA Surgery 2020;155(2):123
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  14. Støme LN, Moger T, Kidholm K, Kværner KJ. A Web-Based Communication Platform to Improve Home Care Services in Norway (DigiHelse): Pilot Study. JMIR Formative Research 2020;4(1):e14780
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  15. Yang Q, Hatch D, Crowley MJ, Lewinski AA, Vaughn J, Steinberg D, Vorderstrasse A, Jiang M, Shaw RJ. 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
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  16. Snyder JM, Pawloski JA, Poisson LM. Developing Real-world Evidence-Ready Datasets: Time for Clinician Engagement. Current Oncology Reports 2020;22(5)
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  17. 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
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  19. Tekin . Is Big Data the New Stethoscope? Perils of Digital Phenotyping to Address Mental Illness. Philosophy & Technology 2020;
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  23. Liang Y, Zheng X, Zeng DD. A survey on big data-driven digital phenotyping of mental health. Information Fusion 2019;52:290
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  24. Rieger A, Gaines A, Barnett I, Baldassano CF, Connolly Gibbons MB, 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
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  25. Gaskins AJ, Hart JE. The use of personal and indoor air pollution monitors in reproductive epidemiology studies. Paediatric and Perinatal Epidemiology 2019;
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  26. Bell IH, Alvarez-Jimenez M. Digital Technology to Enhance Clinical Care of Early Psychosis. Current Treatment Options in Psychiatry 2019;6(3):256
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  29. 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
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  30. 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
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  31. Fraccaro P, Beukenhorst A, Sperrin M, Harper S, Palmier-Claus J, Lewis S, Van der Veer SN, 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
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  32. Bentley KH, Kleiman EM, Elliott G, Huffman JC, Nock MK. Real-time monitoring technology in single-case experimental design research: Opportunities and challenges. Behaviour Research and Therapy 2019;117:87
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  33. Torous J, Gershon A, Hays R, Onnela J, Baker JT. Digital Phenotyping for the Busy Psychiatrist: Clinical Implications and Relevance. Psychiatric Annals 2019;49(5):196
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  34. 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
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  35. Rizzo CJ, Collibee C, Nugent NR, Armey MF. Let's Get Digital: Understanding Adolescent Romantic Relationships Using Naturalistic Assessments of Digital Communication. Child Development Perspectives 2019;13(2):104
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  36. Green MF, Horan WP, Lee J. Nonsocial and social cognition in schizophrenia: current evidence and future directions. World Psychiatry 2019;18(2):146
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  37. Predmore Z, Hatef E, Weiner JP. 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
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  38. Nebeker C, Leow AD, Moore RC. 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
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  39. Barrigon ML, Courtet P, Oquendo M, Baca-García E. Precision Medicine and Suicide: an Opportunity for Digital Health. Current Psychiatry Reports 2019;21(12)
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  40. Torous J, Woodyatt J, Keshavan M, Tully LM. A new hope for early psychosis care: the evolving landscape of digital care tools. The British Journal of Psychiatry 2019;214(5):269
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  41. 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
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  42. Lee J, Kim H, Kim D. Recent Technology-Driven Advancements in Cardiovascular Disease Prevention in Korea. Cardiovascular Prevention and Pharmacotherapy 2019;1(2):43
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  43. Jacobson NC, Weingarden H, Wilhelm S. Using Digital Phenotyping to Accurately Detect Depression Severity. The Journal of Nervous and Mental Disease 2019;207(10):893
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  44. Cote DJ, Barnett I, Onnela J, Smith TR. Digital Phenotyping in Patients with Spine Disease: A Novel Approach to Quantifying Mobility and Quality of Life. World Neurosurgery 2019;126:e241
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  45. Bhattacharya K, Kaski K. Social physics: uncovering human behaviour from communication. Advances in Physics: X 2019;4(1):1527723
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  46. Panda N, Solsky I, Haynes AB. Redefining shared decision-making in the digital era. European Journal of Surgical Oncology 2019;45(12):2287
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  47. 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
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  48. Berrouiguet S, Barrigón ML, Castroman JL, 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)
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  49. 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
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  50. 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
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  51. 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
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  52. Berry JD, Paganoni S, Carlson K, Burke K, Weber H, Staples P, Salinas J, Chan J, Green JR, Connaghan K, Barback J, Onnela JP. Design and results of a smartphone‐based digital phenotyping study to quantify ALS progression. Annals of Clinical and Translational Neurology 2019;6(5):873
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  53. 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)
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  54. de Francisco Carvalho L, Sette CP, Bacciotti JT, 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
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  55. 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 JA, 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
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  56. Pratap A, Atkins DC, Renn BN, Tanana MJ, Mooney SD, Anguera JA, Areán PA. The accuracy of passive phone sensors in predicting daily mood. Depression and Anxiety 2019;36(1):72
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  57. 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
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  58. Wright AA, Raman N, Staples P, Schonholz S, Cronin A, Carlson K, Keating NL, Onnela J. The HOPE Pilot Study: Harnessing Patient-Reported Outcomes and Biometric Data to Enhance Cancer Care. JCO Clinical Cancer Informatics 2018;(2):1
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  59. Berrouiguet S, Ramírez D, Barrigón ML, 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
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  60. 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
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  61. Boonstra TW, Nicholas J, Wong QJ, 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
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  62. 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)
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  63. Wilson JL, Altman RB. Biomarkers: Delivering on the expectation of molecularly driven, quantitative health. Experimental Biology and Medicine 2018;243(3):313
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  64. 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
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  65. Reinertsen E, Clifford GD. A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses. Physiological Measurement 2018;39(5):05TR01
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  66. . Theme 10 Disease stratification and phenotyping. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration 2018;19(sup1):282
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  67. Torous J, Staples P, Barnett I, Sandoval LR, 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)
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  68. Melamed A, Wright AA. Patient Reported Outcomes: Recent Successes and Future Opportunities. Gynecologic Oncology 2018;148(1):1
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  69. Firth J, Stubbs B, Vancampfort D, Schuch FB, Rosenbaum S, Ward PB, Firth JA, Sarris J, Yung AR. 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
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  70. Lind MN, Byrne ML, Wicks G, Smidt AM, Allen NB. The Effortless Assessment of Risk States (EARS) Tool: An Interpersonal Approach to Mobile Sensing. JMIR Mental Health 2018;5(3):e10334
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  71. Roberts LW, Chan S, Torous J. New tests, new tools: mobile and connected technologies in advancing psychiatric diagnosis. npj Digital Medicine 2018;1(1)
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  72. Meyer N, Kerz M, Folarin A, Joyce DW, 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
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  73. Kaufmann CN, Gershon A, Depp CA, Miller S, Zeitzer JM, Ketter TA. Daytime midpoint as a digital biomarker for chronotype in bipolar disorder. Journal of Affective Disorders 2018;241:586
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  74. 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
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  75. Carvalho LF, Sette CP, Ferrari BL. Problematic smartphone use relationship with pathological personality traits: Systematic review and meta-analysis. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2018;12(3)
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  76. Barnett I, Onnela J. Inferring mobility measures from GPS traces with missing data. Biostatistics 2018;
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  77. Sano A, Taylor S, McHill AW, Phillips AJ, Barger LK, 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
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  78. Firth J, Torous J, Carney R, Newby J, Cosco TD, Christensen H, Sarris J. Digital Technologies in the Treatment of Anxiety: Recent Innovations and Future Directions. Current Psychiatry Reports 2018;20(6)
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According to Crossref, the following books are citing this article (DOI 10.2196/mental.5165)

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  1. Mammi M, Boaro A, Kavouridis V, Hulsbergen AF, Senders JT, Gormley WB, Smith TR, Arnaout O. Artificial Intelligence in Precision Health. 2020. :203
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  2. Bell IH, Lim MH, Thomas N. A Clinical Introduction to Psychosis. 2020. :637
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  3. Holt-Lunstad J, Lefler M. Encyclopedia of Gerontology and Population Aging. 2020. Chapter 646-2:1
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  4. Zeng Y, Fraccaro P, Peek N. Artificial Intelligence in Medicine. 2019. Chapter 29:233
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  5. Senders JT, Maher N, Hulsbergen AFC, Lamba N, Bredenoord AL, Broekman MLD. Ethics of Innovation in Neurosurgery. 2019. Chapter 14:129
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  6. Ebert DD, Harrer M, Apolinário-Hagen J, Baumeister H. Frontiers in Psychiatry. 2019. Chapter 29:583
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  7. Holt-Lunstad J, Lefler MK. Encyclopedia of Gerontology and Population Aging. 2019. Chapter 646-1:1
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  8. Stanimirovic A. Chronic Stress and Its Effect on Brain Structure and Connectivity. 2019. chapter 9:168
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  9. Torous J, Namiri N, Keshavan M. Personalized Psychiatry. 2019. Chapter 3:37
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  10. Karhade AV, Gormley WB, Smith TR. Quality and Safety in Neurosurgery. 2018. :205
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