Published on in Vol 5, No 8 (2017): August
Journals
- Berman A, Carter G. Technological Advances and the Future of Suicide Prevention: Ethical, Legal, and Empirical Challenges. Suicide and Life-Threatening Behavior 2020;50(3):643 View
- Thong M, Chan R, van den Hurk C, Fessele K, Tan W, Poprawski D, Fernández-Ortega P, Paterson C, Fitch M. Going beyond (electronic) patient-reported outcomes: harnessing the benefits of smart technology and ecological momentary assessment in cancer survivorship research. Supportive Care in Cancer 2021;29(1):7 View
- Jones M, Johnson M, Shervey M, Dudley J, Zimmerman N. Privacy-Preserving Methods for Feature Engineering Using Blockchain: Review, Evaluation, and Proof of Concept. Journal of Medical Internet Research 2019;21(8):e13600 View
- Yim S, Lui L, Lee Y, Rosenblat J, Ragguett R, Park C, Subramaniapillai M, Cao B, Zhou A, Rong C, Lin K, Ho R, Coles A, Majeed A, Wong E, Phan L, Nasri F, McIntyre R. The utility of smartphone-based, ecological momentary assessment for depressive symptoms. Journal of Affective Disorders 2020;274:602 View
- Montag C, Sindermann C, Baumeister H. Digital phenotyping in psychological and medical sciences: a reflection about necessary prerequisites to reduce harm and increase benefits. Current Opinion in Psychology 2020;36:19 View
- 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
- Trifan A, Oliveira M, Oliveira J. Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations. JMIR mHealth and uHealth 2019;7(8):e12649 View
- Jim H, Hoogland A, Brownstein N, Barata A, Dicker A, Knoop H, Gonzalez B, Perkins R, Rollison D, Gilbert S, Nanda R, Berglund A, Mitchell R, Johnstone P. Innovations in research and clinical care using patient‐generated health data. CA: A Cancer Journal for Clinicians 2020;70(3):182 View
- 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
- Boukhechba M, Chow P, Fua K, Teachman B, Barnes L. Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study. JMIR Mental Health 2018;5(3):e10101 View
- Obuchi M, Huckins J, Wang W, daSilva A, Rogers C, Murphy E, Hedlund E, Holtzheimer P, Mirjafari S, Campbell A. Predicting Brain Functional Connectivity Using Mobile Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(1):1 View
- Pisco Almeida A, Almeida H, Figueiredo-Braga M. Mobile solutions in depression: enhancing communication with patients using an SMS-based intervention. Procedia Computer Science 2018;138:89 View
- Liu T, Nicholas J, Theilig M, Guntuku S, Kording K, Mohr D, Ungar L. Machine Learning for Phone-Based Relationship Estimation. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019;3(4):1 View
- Nepal S, Mirjafari S, Martinez G, Audia P, Striegel A, Campbell A. Detecting Job Promotion in Information Workers Using Mobile Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(3):1 View
- 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
- Burgess E, Ringland K, Nicholas J, Knapp A, Eschler J, Mohr D, Reddy M. "I think people are powerful". Proceedings of the ACM on Human-Computer Interaction 2019;3(CSCW):1 View
- Miralles I, Granell C. Considerations for Designing Context-Aware Mobile Apps for Mental Health Interventions. International Journal of Environmental Research and Public Health 2019;16(7):1197 View
- Pastor N, Khalilian E, Caballeria E, Morrison D, Sanchez Luque U, Matrai S, Gual A, López-Pelayo H. Remote Monitoring Telemedicine (REMOTE) Platform for Patients With Anxiety Symptoms and Alcohol Use Disorder: Protocol for a Case-Control Study. JMIR Research Protocols 2020;9(6):e16964 View
- Pulantara I, Parmanto B, Germain A. Development of a Just-in-Time Adaptive mHealth Intervention for Insomnia: Usability Study. JMIR Human Factors 2018;5(2):e21 View
- Pulantara I, Parmanto B, Germain A. Clinical Feasibility of a Just-in-Time Adaptive Intervention App (iREST) as a Behavioral Sleep Treatment in a Military Population: Feasibility Comparative Effectiveness Study. Journal of Medical Internet Research 2018;20(12):e10124 View
- Luo X, Chen Z. English text quality analysis based on recurrent neural network and semantic segmentation. Future Generation Computer Systems 2020;112:507 View
- dos Santos Paula L, Barbosa J, Dias L. A model for assisting in the treatment of anxiety disorder. Universal Access in the Information Society 2022;21(2):533 View
- Sheu Y. Illuminating the Black Box: Interpreting Deep Neural Network Models for Psychiatric Research. Frontiers in Psychiatry 2020;11 View
- Maharjan S, Poudyal A, van Heerden A, Byanjankar P, Thapa A, Islam C, Kohrt B, Hagaman A. Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability. BMC Medical Informatics and Decision Making 2021;21(1) View
- Sheikh M, Qassem M, Kyriacou P. Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring. Frontiers in Digital Health 2021;3 View
- 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
- Montag C, Rumpf H. The Potential of Digital Phenotyping and Mobile Sensing for Psycho-Diagnostics of Internet Use Disorders. Current Addiction Reports 2021;8(3):422 View
- Teepe G, Da Fonseca A, Kleim B, Jacobson N, Salamanca Sanabria A, Tudor Car L, Fleisch E, Kowatsch T. Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review. Journal of Medical Internet Research 2021;23(9):e29412 View
- D’Mello R, Melcher J, Torous J. Similarity matrix-based anomaly detection for clinical intervention. Scientific Reports 2022;12(1) View
- Hart A, Reis D, Prestele E, Jacobson N. Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment. Journal of Medical Internet Research 2022;24(4):e34015 View
- van Berkel N, D’Alfonso S, Kurnia Susanto R, Ferreira D, Kostakos V. AWARE-Light: a smartphone tool for experience sampling and digital phenotyping. Personal and Ubiquitous Computing 2023;27(2):435 View
- MacLeod L, Suruliraj B, Gall D, Bessenyei K, Hamm S, Romkey I, Bagnell A, Mattheisen M, Muthukumaraswamy V, Orji R, Meier S. A Mobile Sensing App to Monitor Youth Mental Health: Observational Pilot Study. JMIR mHealth and uHealth 2021;9(10):e20638 View
- Baglione A, Cai L, Bahrini A, Posey I, Boukhechba M, Chow P. Understanding the Relationship Between Mood Symptoms and Mobile App Engagement Among Patients With Breast Cancer Using Machine Learning: Case Study. JMIR Medical Informatics 2022;10(6):e30712 View
- Montag C, Elhai J, Dagum P. On Blurry Boundaries When Defining Digital Biomarkers: How Much Biology Needs to Be in a Digital Biomarker?. Frontiers in Psychiatry 2021;12 View
- Li T, Zhang M, Li Y, Lagerspetz E, Tarkoma S, Hui P. The Impact of Covid-19 on Smartphone Usage. IEEE Internet of Things Journal 2021;8(23):16723 View
- Gopalakrishnan A, Venkataraman R, Gururajan R, Zhou X, Genrich R. Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review. PeerJ Computer Science 2022;8:e1042 View
- Jacobson N, Feng B. Digital phenotyping of generalized anxiety disorder: using artificial intelligence to accurately predict symptom severity using wearable sensors in daily life. Translational Psychiatry 2022;12(1) View
- Fukazawa Y. Estimating Mental Health Using Human-generated Big Data and Machine Learning. The Brain & Neural Networks 2022;29(2):78 View
- Jacobson N, Bhattacharya S. Digital biomarkers of anxiety disorder symptom changes: Personalized deep learning models using smartphone sensors accurately predict anxiety symptoms from ecological momentary assessments. Behaviour Research and Therapy 2022;149:104013 View
- Montag C, Dagum P, Hall B, Elhai J. How the study of digital footprints can supplement research in behavioral genetics and molecular psychology. Molecular Psychology: Brain, Behavior, and Society 2022;1:2 View
- Highland D, Zhou G. A review of detection techniques for depression and bipolar disorder. Smart Health 2022;24:100282 View
- Paula L, Pfeiffer Salomão Dias L, Francisco R, Barbosa J. Analysing IoT Data for Anxiety and Stress Monitoring: A Systematic Mapping Study and Taxonomy. International Journal of Human–Computer Interaction 2024;40(5):1174 View
- Hong J, Kim J, Kim S, Oh J, Lee D, Lee S, Uh J, Yoon J, Choi Y. Depressive Symptoms Feature-Based Machine Learning Approach to Predicting Depression Using Smartphone. Healthcare 2022;10(7):1189 View
- Asani F, Patel B, Srikanthan S, Agu E. BioscoreNet: Traumatic Brain Injury (TBI) detection using a multimodal self-attention fusion neural network and a passive bioscore monitoring framework from smartphone sensor data. Smart Health 2023;27:100352 View
- 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
- Meyerhoff J, Liu T, Kording K, Ungar L, Kaiser S, Karr C, Mohr D. Evaluation of Changes in Depression, Anxiety, and Social Anxiety Using Smartphone Sensor Features: Longitudinal Cohort Study. Journal of Medical Internet Research 2021;23(9):e22844 View
- Chia A, Zhang M. Digital phenotyping in psychiatry: A scoping review. Technology and Health Care 2022;30(6):1331 View
- Memon A, Kilby J, Breñosa J, Espinosa J, Ashraf I. Analysis and Implementation of Human Mobility Behavior Using Similarity Analysis Based on Co-Occurrence Matrix. Sensors 2022;22(24):9898 View
- Lee K, Lee T, Yefimova M, Kumar S, Puga F, Azuero A, Kamal A, Bakitas M, Wright A, Demiris G, Ritchie C, Pickering C, Nicholas Dionne-Odom J. Using digital phenotyping to understand health-related outcomes: A scoping review. International Journal of Medical Informatics 2023;174:105061 View
- Zou B, Zhang X, Xiao L, Bai R, Li X, Liang H, Ma H, Wang G. Sequence Modeling of Passive Sensing Data for Treatment Response Prediction in Major Depressive Disorder. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2023;31:1786 View
- Matz S, Beck E, Atherton O, White M, Rauthmann J, Mroczek D, Kim M, Bogg T. Personality Science in the Digital Age: The Promises and Challenges of Psychological Targeting for Personalized Behavior-Change Interventions at Scale. Perspectives on Psychological Science 2024;19(6):1031 View
- Shin J, Bae S. A Systematic Review of Location Data for Depression Prediction. International Journal of Environmental Research and Public Health 2023;20(11):5984 View
- Zhuparris A, Maleki G, van Londen L, Koopmans I, Aalten V, Yocarini I, Exadaktylos V, van Hemert A, Cohen A, Gal P, Doll R, Groeneveld G, Jacobs G, Kraaij W. A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity. Scientific Reports 2023;13(1) View
- Panlilio L, Burgess-Hull A, Feldman J, Rogers J, Tyburski M, Smith K, Epstein D. Activity space during treatment with medication for opioid use disorder: Relationships with personality, mood, and drug use. Journal of Substance Use and Addiction Treatment 2024;157:209219 View
- Mao K, Wu Y, Chen J. A systematic review on automated clinical depression diagnosis. npj Mental Health Research 2023;2(1) View
- Alamoudi D, Nabney I, Crawley E. Evaluating the Effectiveness of the SleepTracker App for Detecting Anxiety- and Depression-Related Sleep Disturbances. Sensors 2024;24(3):722 View
- Mullick T, Shaaban S, Radovic A, Doryab A. Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic and Personalized Modeling. JMIR AI 2024;3:e47805 View
- Janssen Daalen J, van den Bergh R, Prins E, Moghadam M, van den Heuvel R, Veen J, Mathur S, Meijerink H, Mirelman A, Darweesh S, Evers L, Bloem B. Digital biomarkers for non-motor symptoms in Parkinson’s disease: the state of the art. npj Digital Medicine 2024;7(1) View
- Terhorst Y, Knauer J, Philippi P, Baumeister H. The Relation Between Passively Collected GPS Mobility Metrics and Depressive Symptoms: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2024;26:e51875 View
- Ji G, Woo J, Lee G, Msigwa C, Bernard D, Yun J. AIoT-Based Smart Healthcare in Everyday Lives: Data Collection and Standardization From Smartphones and Smartwatches. IEEE Internet of Things Journal 2024;11(16):27597 View
- Müller S, Peters H, Matz S, Wang W, Harari G. Investigating the Relationships between Mobility Behaviours and Indicators of Subjective Well–Being Using Smartphone–Based Experience Sampling and GPS Tracking. European Journal of Personality 2020;34(5):714 View
- Chitale V, Henry J, Liang H, Matthews B, Baghaei N. Virtual reality analytics map (VRAM): A conceptual framework for detecting mental disorders using virtual reality data. New Ideas in Psychology 2025;76:101127 View
- Yi L, Hart J, Straczkiewicz M, Karas M, Wilt G, Hu C, Librett R, Laden F, Chavarro J, Onnela J, James P. Measuring Environmental and Behavioral Drivers of Chronic Diseases Using Smartphone-Based Digital Phenotyping: Intensive Longitudinal Observational mHealth Substudy Embedded in 2 Prospective Cohorts of Adults. JMIR Public Health and Surveillance 2024;10:e55170 View
- Smrke U, Mlakar I, Rehberger A, Žužek L, Plohl N. Decoding anxiety: A scoping review of observable cues. DIGITAL HEALTH 2024;10 View
- Lee K, Azuero A, Engler S, Kumar S, Puga F, Wright A, Kamal A, Ritchie C, Demiris G, Bakitas M, Odom J. Exploring the Relationship Between Smartphone GPS Patterns and Quality of Life in Patients with Advanced Cancer and their Family Caregivers: A longitudinal study (Preprint). JMIR Formative Research 2024 View
Books/Policy Documents
- Iyawa G, Ondiek C, Osakwe J. Smart Medical Data Sensing and IoT Systems Design in Healthcare. View
- Teles A, Barros F, Rodrigues I, Barbosa A, Silva F, Coutinho L, Teixeira S. IoT and ICT for Healthcare Applications. View
- Heinz M, Price G, Song S, Bhattacharya S, Jacobson N. Digital Mental Health. View