Published on in Vol 20, No 7 (2018): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9775, first published .
Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study

Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study

Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study

Journals

  1. 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
  2. Allen S. Artificial Intelligence and the Future of Psychiatry. IEEE Pulse 2020;11(3):2 View
  3. Potier R. The Digital Phenotyping Project: A Psychoanalytical and Network Theory Perspective. Frontiers in Psychology 2020;11 View
  4. Birnbaum M, Ernala S, Rizvi A, Arenare E, R. Van Meter A, De Choudhury M, Kane J. Detecting relapse in youth with psychotic disorders utilizing patient-generated and patient-contributed digital data from Facebook. npj Schizophrenia 2019;5(1) View
  5. Seppälä J, De Vita I, Jämsä T, Miettunen J, Isohanni M, Rubinstein K, Feldman Y, Grasa E, Corripio I, Berdun J, D'Amico E, Bulgheroni M. Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review. JMIR Mental Health 2019;6(2):e9819 View
  6. Daus H, Bloecher T, Egeler R, De Klerk R, Stork W, Backenstrass M. Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder. JMIR Mental Health 2020;7(7):e14267 View
  7. Jacobson N, Chung Y. Passive Sensing of Prediction of Moment-To-Moment Depressed Mood among Undergraduates with Clinical Levels of Depression Sample Using Smartphones. Sensors 2020;20(12):3572 View
  8. Mastoras R, Iakovakis D, Hadjidimitriou S, Charisis V, Kassie S, Alsaadi T, Khandoker A, Hadjileontiadis L. Touchscreen typing pattern analysis for remote detection of the depressive tendency. Scientific Reports 2019;9(1) View
  9. Stange J, Kleiman E, Mermelstein R, Trull T. Using ambulatory assessment to measure dynamic risk processes in affective disorders. Journal of Affective Disorders 2019;259:325 View
  10. Rashidisabet H, Thomas P, Ajilore O, Zulueta J, Moore R, Leow A. A systems biology approach to the digital behaviorome. Current Opinion in Systems Biology 2020;20:8 View
  11. 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
  12. Campbell L, Tang B, Watson W, Higgins M, Cherner M, Henry B, Moore R. Cannabis Use is Associated with Greater Total Sleep Time in Middle-Aged and Older Adults with and without HIV: A Preliminary Report Utilizing Digital Health Technologies. Cannabis 2020;3(2):180 View
  13. Walker W, Walton J, DeVries A, Nelson R. Circadian rhythm disruption and mental health. Translational Psychiatry 2020;10(1) View
  14. Victory A, Letkiewicz A, Cochran A. Digital solutions for shaping mood and behavior among individuals with mood disorders. Current Opinion in Systems Biology 2020;21:25 View
  15. Piau A, Wild K, Mattek N, Kaye J. Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review. Journal of Medical Internet Research 2019;21(8):e12785 View
  16. Brietzke E, Hawken E, Idzikowski M, Pong J, Kennedy S, Soares C. Integrating digital phenotyping in clinical characterization of individuals with mood disorders. Neuroscience & Biobehavioral Reviews 2019;104:223 View
  17. Zulueta J, Leow A, Ajilore O. Real-Time Monitoring: A Key Element in Personalized Health and Precision Health. FOCUS 2020;18(2):175 View
  18. Bidmon S, Elshiewy O, Terlutter R, Boztug Y. What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data. Journal of Medical Internet Research 2020;22(2):e13830 View
  19. Purswani J, Dicker A, Champ C, Cantor M, Ohri N. Big Data From Small Devices: The Future of Smartphones in Oncology. Seminars in Radiation Oncology 2019;29(4):338 View
  20. Rudd B, Beidas R. Digital Mental Health: The Answer to the Global Mental Health Crisis?. JMIR Mental Health 2020;7(6):e18472 View
  21. 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
  22. Vesel C, Rashidisabet H, Zulueta J, Stange J, Duffecy J, Hussain F, Piscitello A, Bark J, Langenecker S, Young S, Mounts E, Omberg L, Nelson P, Moore R, Koziol D, Bourne K, Bennett C, Ajilore O, Demos A, Leow A. Effects of mood and aging on keystroke dynamics metadata and their diurnal patterns in a large open-science sample: A BiAffect iOS study. Journal of the American Medical Informatics Association 2020;27(7):1007 View
  23. Diamantaris M, Marcantoni F, Ioannidis S, Polakis J. The Seven Deadly Sins of the HTML5 WebAPI. ACM Transactions on Privacy and Security 2020;23(4):1 View
  24. Birnbaum M, Kulkarni P, Van Meter A, Chen V, Rizvi A, Arenare E, De Choudhury M, Kane J. Utilizing Machine Learning on Internet Search Activity to Support the Diagnostic Process and Relapse Detection in Young Individuals With Early Psychosis: Feasibility Study. JMIR Mental Health 2020;7(9):e19348 View
  25. Asensio-Cuesta S, Sánchez-García Á, Conejero J, Saez C, Rivero-Rodriguez A, García-Gómez J. Smartphone Sensors for Monitoring Cancer-Related Quality of Life: App Design, EORTC QLQ-C30 Mapping and Feasibility Study in Healthy Subjects. International Journal of Environmental Research and Public Health 2019;16(3):461 View
  26. van der Watt A, Odendaal W, Louw K, Seedat S. Distant mood monitoring for depressive and bipolar disorders: a systematic review. BMC Psychiatry 2020;20(1) View
  27. Antosik-Wójcińska A, Dominiak M, Chojnacka M, Kaczmarek-Majer K, Opara K, Radziszewska W, Olwert A, Święcicki Ł. Smartphone as a monitoring tool for bipolar disorder: a systematic review including data analysis, machine learning algorithms and predictive modelling. International Journal of Medical Informatics 2020;138:104131 View
  28. Mouchabac S, Adrien V, Falala-Séchet C, Bonnot O, Maatoug R, Millet B, Peretti C, Bourla A, Ferreri F. Psychiatric Advance Directives and Artificial Intelligence: A Conceptual Framework for Theoretical and Ethical Principles. Frontiers in Psychiatry 2021;11 View
  29. Zulueta J, Ajilore O. Beyond non-inferior: how telepsychiatry technologies can lead to superior care. International Review of Psychiatry 2021;33(4):366 View
  30. Burgess-Hull A, Epstein D. Ambulatory Assessment Methods to Examine Momentary State-Based Predictors of Opioid Use Behaviors. Current Addiction Reports 2021;8(1):122 View
  31. Sagorac Gruichich T, David Gomez J, Zayas‐Cabán G, McInnis M, Cochran A. A digital self‐report survey of mood for bipolar disorder. Bipolar Disorders 2021 View
  32. Druijff‐van de Woestijne G, McConchie H, Kort Y, Licitra G, Zhang C, Overeem S, Smolders K. Behavioural biometrics: Using smartphone keyboard activity as a proxy for rest–activity patterns. Journal of Sleep Research 2021 View
  33. Jayakumar P, Lin E, Galea V, Mathew A, Panda N, Vetter I, Haynes A. Digital Phenotyping and Patient-Generated Health Data for Outcome Measurement in Surgical Care: A Scoping Review. Journal of Personalized Medicine 2020;10(4):282 View
  34. Hilty D, Armstrong C, Luxton D, Gentry M, Krupinski E. A Scoping Review of Sensors, Wearables, and Remote Monitoring For Behavioral Health: Uses, Outcomes, Clinical Competencies, and Research Directions. Journal of Technology in Behavioral Science 2021;6(2):278 View
  35. 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
  36. Lhaksampa T, Nanavati J, Chisolm M, Miller L. Patient electronic communication data in clinical care: what is known and what is needed. International Review of Psychiatry 2021;33(4):372 View
  37. Davidson B. The crossroads of digital phenotyping. General Hospital Psychiatry 2020 View
  38. Kohli M, Moore D, Moore R. Using health technology to capture digital phenotyping data in HIV-associated neurocognitive disorders. AIDS 2021;35(1):15 View
  39. Opoku Asare K, Terhorst Y, Vega J, Peltonen E, Lagerspetz E, Ferreira D. Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study. JMIR mHealth and uHealth 2021;9(7):e26540 View
  40. Vlisides-Henry R, Gao M, Thomas L, Kaliush P, Conradt E, Crowell S. Digital Phenotyping of Emotion Dysregulation Across Lifespan Transitions to Better Understand Psychopathology Risk. Frontiers in Psychiatry 2021;12 View
  41. Schueller S, Neary M, Lai J, Epstein D. Understanding People’s Use of and Perspectives on Mood-Tracking Apps: Interview Study. JMIR Mental Health 2021;8(8):e29368 View
  42. Beierle F, Schobel J, Vogel C, Allgaier J, Mulansky L, Haug F, Haug J, Schlee W, Holfelder M, Stach M, Schickler M, Baumeister H, Cohrdes C, Deckert J, Deserno L, Edler J, Eichner F, Greger H, Hein G, Heuschmann P, John D, Kestler H, Krefting D, Langguth B, Meybohm P, Probst T, Reichert M, Romanos M, Störk S, Terhorst Y, Weiß M, Pryss R. Corona Health—A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic. International Journal of Environmental Research and Public Health 2021;18(14):7395 View
  43. Martinez-Martin N, Greely H, Cho M. Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study. JMIR mHealth and uHealth 2021;9(7):e27343 View

Books/Policy Documents

  1. Hussain F, Stange J, Langenecker S, McInnis M, Zulueta J, Piscitello A, Cao B, Huang H, Yu P, Nelson P, Ajilore O, Leow A. Digital Phenotyping and Mobile Sensing. View
  2. Chentsova Dutton Y, Lyons S. Emotion Measurement. View
  3. Mao S, Khalifa Y, Zhang Z, Shu K, Suri A, Bouzid Z, Sejdic E. Digital Health. View