Published on 15.07.15 in Vol 17, No 7 (2015): July
Works citing "Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.4273):
(note that this is only a small subset of citations)
-
Reinertsen E, Clifford GD. A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses. Physiological Measurement 2018;39(5):05TR01
CrossRef -
Mei G, Xu W, Li L, Zhao Z, Li H, Liu W, Jiao Y. The Role of Campus Data in Representing Depression Among College Students: Exploratory Research. JMIR Mental Health 2020;7(1):e12503
CrossRef -
Gong J, Huang Y, Chow PI, Fua K, Gerber MS, Teachman BA, Barnes LE. Understanding behavioral dynamics of social anxiety among college students through smartphone sensors. Information Fusion 2019;49:57
CrossRef -
Ai P, Liu Y, Zhao X. Big Five personality traits predict daily spatial behavior: Evidence from smartphone data. Personality and Individual Differences 2019;147:285
CrossRef -
Wang W. Smartphones as Social Actors? Social dispositional factors in assessing anthropomorphism. Computers in Human Behavior 2017;68:334
CrossRef -
Rohani DA, Tuxen N, Quemada Lopategui A, Kessing LV, Bardram JE. Data-Driven Learning in High-Resolution Activity Sampling From Patients With Bipolar Depression: Mixed-Methods Study. JMIR Mental Health 2018;5(2):e10122
CrossRef -
Razavi R, Gharipour A, Gharipour M. Depression screening using mobile phone usage metadata: a machine learning approach. Journal of the American Medical Informatics Association 2020;27(4):522
CrossRef -
Masud MT, Mamun MA, Thapa K, Lee D, Griffiths MD, Yang S. Unobtrusive monitoring of behavior and movement patterns to detect clinical depression severity level via smartphone. Journal of Biomedical Informatics 2020;103:103371
CrossRef -
Saeb S, Lonini L, Jayaraman A, Mohr DC, Kording KP. The need to approximate the use-case in clinical machine learning. GigaScience 2017;6(5)
CrossRef -
Pratap A, Renn BN, Volponi J, Mooney SD, Gazzaley A, Arean PA, Anguera JA. Using Mobile Apps to Assess and Treat Depression in Hispanic and Latino Populations: Fully Remote Randomized Clinical Trial. Journal of Medical Internet Research 2018;20(8):e10130
CrossRef -
Otte C, Gold SM, Penninx BW, Pariante CM, Etkin A, Fava M, Mohr DC, Schatzberg AF. Major depressive disorder. Nature Reviews Disease Primers 2016;2(1)
CrossRef -
Johnson M, Jones M, Shervey M, Dudley JT, Zimmerman N. Building a Secure Biomedical Data Sharing Decentralized App (DApp): Tutorial. Journal of Medical Internet Research 2019;21(10):e13601
CrossRef -
Wang R, Wang W, Aung MSH, Ben-Zeev D, Brian R, Campbell AT, Choudhury T, Hauser M, Kane J, Scherer EA, Walsh M. Predicting Symptom Trajectories of Schizophrenia using Mobile Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2017;1(3):1
CrossRef -
Nugent NR, Pendse SR, Schatten HT, Armey MF. Innovations in Technology and Mechanisms of Change in Behavioral Interventions. Behavior Modification 2019;:014544551984560
CrossRef -
Majumder S, Deen MJ. Smartphone Sensors for Health Monitoring and Diagnosis. Sensors 2019;19(9):2164
CrossRef -
Bauer M, Glenn T, Monteith S, Bauer R, Whybrow PC, Geddes J. Ethical perspectives on recommending digital technology for patients with mental illness. International Journal of Bipolar Disorders 2017;5(1)
CrossRef -
Luhmann M. Using Big Data to study subjective well-being. Current Opinion in Behavioral Sciences 2017;18:28
CrossRef -
Helbich M. Toward dynamic urban environmental exposure assessments in mental health research. Environmental Research 2018;161:129
CrossRef -
Aung MH, Matthews M, Choudhury T. Sensing behavioral symptoms of mental health and delivering personalized interventions using mobile technologies. Depression and Anxiety 2017;34(7):603
CrossRef -
Becker D, van Breda W, Funk B, Hoogendoorn M, Ruwaard J, Riper H. Predictive modeling in e-mental health: A common language framework. Internet Interventions 2018;12:57
CrossRef -
Rashid H, Mendu S, Daniel KE, Beltzer ML, Teachman BA, Boukhechba M, Barnes LE. Predicting Subjective Measures of Social Anxiety from Sparsely Collected Mobile Sensor Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(3):1
CrossRef -
Cornet VP, Holden RJ. Systematic review of smartphone-based passive sensing for health and wellbeing. Journal of Biomedical Informatics 2018;77:120
CrossRef -
Aung MSH, Alquaddoomi F, Hsieh C, Rabbi M, Yang L, Pollak JP, Estrin D, Choudhury T. Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain. IEEE Journal of Selected Topics in Signal Processing 2016;10(5):962
CrossRef -
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
CrossRef -
Fairburn CG, Patel V. The impact of digital technology on psychological treatments and their dissemination. Behaviour Research and Therapy 2017;88:19
CrossRef -
Boukhechba M, Daros AR, Fua K, Chow PI, Teachman BA, Barnes LE. DemonicSalmon: Monitoring mental health and social interactions of college students using smartphones. Smart Health 2018;9-10:192
CrossRef -
Lee U, Han K, Cho H, Chung K, Hong H, Lee S, Noh Y, Park S, Carroll JM. Intelligent positive computing with mobile, wearable, and IoT devices: Literature review and research directions. Ad Hoc Networks 2019;83:8
CrossRef -
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
CrossRef -
Palmer KM, Burrows V. Ethical and Safety Concerns Regarding the Use of Mental Health–Related Apps in Counseling: Considerations for Counselors. Journal of Technology in Behavioral Science 2021;6(1):137
CrossRef -
Asselbergs J, Ruwaard J, Ejdys M, Schrader N, Sijbrandij M, Riper H. Mobile Phone-Based Unobtrusive Ecological Momentary Assessment of Day-to-Day Mood: An Explorative Study. Journal of Medical Internet Research 2016;18(3):e72
CrossRef -
Saha K, Chan L, De Barbaro K, Abowd GD, De Choudhury M. Inferring Mood Instability on Social Media by Leveraging Ecological Momentary Assessments. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2017;1(3):1
CrossRef -
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
CrossRef -
Harari GM, Müller SR, Mishra V, Wang R, Campbell AT, Rentfrow PJ, Gosling SD. An Evaluation of Students’ Interest in and Compliance With Self-Tracking Methods. Social Psychological and Personality Science 2017;8(5):479
CrossRef -
Kamilaris A, Pitsillides A. Mobile Phone Computing and the Internet of Things: A Survey. IEEE Internet of Things Journal 2016;3(6):885
CrossRef -
Brietzke E, Hawken ER, Idzikowski M, Pong J, Kennedy SH, Soares CN. Integrating digital phenotyping in clinical characterization of individuals with mood disorders. Neuroscience & Biobehavioral Reviews 2019;104:223
CrossRef -
Schneble CO, Elger BS, Shaw DM. All Our Data Will Be Health Data One Day: The Need for Universal Data Protection and Comprehensive Consent. Journal of Medical Internet Research 2020;22(5):e16879
CrossRef -
Cao J, Truong AL, Banu S, Shah AA, Sabharwal A, Moukaddam N. Tracking and Predicting Depressive Symptoms of Adolescents Using Smartphone-Based Self-Reports, Parental Evaluations, and Passive Phone Sensor Data: Development and Usability Study. JMIR Mental Health 2020;7(1):e14045
CrossRef -
Henson P, Barnett I, Keshavan M, Torous J. Towards clinically actionable digital phenotyping targets in schizophrenia. npj Schizophrenia 2020;6(1)
CrossRef -
Kirchner TR, Shiffman S. Spatio-temporal determinants of mental health and well-being: advances in geographically-explicit ecological momentary assessment (GEMA). Social Psychiatry and Psychiatric Epidemiology 2016;51(9):1211
CrossRef -
Tuerk PW, Schaeffer CM, McGuire JF, Adams Larsen M, Capobianco N, Piacentini J. Adapting Evidence-Based Treatments for Digital Technologies: a Critical Review of Functions, Tools, and the Use of Branded Solutions. Current Psychiatry Reports 2019;21(10)
CrossRef -
Kang Y. Ontology Components for the Depression Management based on Context. Journal of the Korea Institute of Information and Communication Engineering 2016;20(9):1785
CrossRef -
Schoedel R, Au Q, Völkel ST, Lehmann F, Becker D, Bühner M, Bischl B, Hussmann H, Stachl C. Digital Footprints of Sensation Seeking. Zeitschrift für Psychologie 2018;226(4):232
CrossRef -
Price M, Van Stolk-Cooke K, Legrand AC, Brier ZMF, Ward HL, Connor JP, Gratton J, Freeman K, Skalka C. Implementing assessments via mobile during the acute posttrauma period: feasibility, acceptability and strategies to improve response rates. European Journal of Psychotraumatology 2018;9(sup1):1500822
CrossRef -
Dogrucu A, Perucic A, Isaro A, Ball D, Toto E, Rundensteiner EA, Agu E, Davis-Martin R, Boudreaux E. Moodable: On feasibility of instantaneous depression assessment using machine learning on voice samples with retrospectively harvested smartphone and social media data. Smart Health 2020;17:100118
CrossRef -
Sabharwal A, Veeraraghavan A. Bio-Behavioral Sensing. GetMobile: Mobile Computing and Communications 2017;21(3):11
CrossRef -
DeMasi O, Feygin S, Dembo A, Aguilera A, Recht B. Well-Being Tracking via Smartphone-Measured Activity and Sleep: Cohort Study. JMIR mHealth and uHealth 2017;5(10):e137
CrossRef -
Suffoletto B, Aguilera A. Expanding Adolescent Depression Prevention Through Simple Communication Technologies. Journal of Adolescent Health 2016;59(4):373
CrossRef -
Armstrong CM, Ciulla RP, Williams SA, Micheel LJ. An Applied Test of Knowledge Translation Methods Using a Mobile Health Solution. Military Medicine 2020;185(Supplement_1):526
CrossRef -
Hung GC, Yang P, Chang C, Chiang J, Chen Y. Predicting Negative Emotions Based on Mobile Phone Usage Patterns: An Exploratory Study. JMIR Research Protocols 2016;5(3):e160
CrossRef -
Mandryk RL, Birk MV. Toward Game-Based Digital Mental Health Interventions: Player Habits and Preferences. Journal of Medical Internet Research 2017;19(4):e128
CrossRef -
Scott SB, Munoz E, Mogle JA, Gamaldo AA, Smyth JM, Almeida DM, Sliwinski MJ. Perceived neighborhood characteristics predict severity and emotional response to daily stressors. Social Science & Medicine 2018;200:262
CrossRef -
Donker T, Van Esveld S, Fischer N, Van Straten A. 0Phobia – towards a virtual cure for acrophobia: study protocol for a randomized controlled trial. Trials 2018;19(1)
CrossRef -
Chib A, Lin SH. Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps. Journal of Health Communication 2018;23(10-11):909
CrossRef -
Tseng VW, Sano A, Ben-Zeev D, Brian R, Campbell AT, Hauser M, Kane JM, Scherer EA, Wang R, Wang W, Wen H, Choudhury T. Using behavioral rhythms and multi-task learning to predict fine-grained symptoms of schizophrenia. Scientific Reports 2020;10(1)
CrossRef -
Di Matteo D, Fotinos K, Lokuge S, Yu J, Sternat T, Katzman MA, Rose J. The Relationship Between Smartphone-Recorded Environmental Audio and Symptomatology of Anxiety and Depression: Exploratory Study. JMIR Formative Research 2020;4(8):e18751
CrossRef -
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
CrossRef -
Palmius N, Saunders KEA, Carr O, Geddes JR, Goodwin GM, De Vos M. Group-Personalized Regression Models for Predicting Mental Health Scores From Objective Mobile Phone Data Streams: Observational Study. Journal of Medical Internet Research 2018;20(10):e10194
CrossRef -
Zulueta J, Leow AD, Ajilore O. Real-Time Monitoring: A Key Element in Personalized Health and Precision Health. FOCUS 2020;18(2):175
CrossRef -
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
CrossRef -
Khan SA, Farhan AA, Fahad LG, Tahir SF. Personal productivity monitoring through smartphones. Journal of Ambient Intelligence and Smart Environments 2020;12(4):327
CrossRef -
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
CrossRef -
Porras-Segovia A, Molina-Madueño RM, Berrouiguet S, López-Castroman J, Barrigón ML, Pérez-Rodríguez MS, Marco JH, Díaz-Oliván I, de León S, Courtet P, Artés-Rodríguez A, Baca-García E. Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study. Journal of Affective Disorders 2020;274:733
CrossRef -
Thomée S. Mobile Phone Use and Mental Health. A Review of the Research That Takes a Psychological Perspective on Exposure. International Journal of Environmental Research and Public Health 2018;15(12):2692
CrossRef -
Aguilera A, Bruehlman-Senecal E, Demasi O, Avila P. Automated Text Messaging as an Adjunct to Cognitive Behavioral Therapy for Depression: A Clinical Trial. Journal of Medical Internet Research 2017;19(5):e148
CrossRef -
Dogan E, Sander C, Wagner X, Hegerl U, Kohls E. Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review. Journal of Medical Internet Research 2017;19(7):e262
CrossRef -
Harari GM, Müller SR, Aung MS, Rentfrow PJ. Smartphone sensing methods for studying behavior in everyday life. Current Opinion in Behavioral Sciences 2017;18:83
CrossRef -
Ram N, Brinberg M, Pincus AL, Conroy DE. The Questionable Ecological Validity of Ecological Momentary Assessment: Considerations for Design and Analysis. Research in Human Development 2017;14(3):253
CrossRef -
Rohani DA, Faurholt-Jepsen M, Kessing LV, Bardram JE. Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review. JMIR mHealth and uHealth 2018;6(8):e165
CrossRef -
Barrigón ML, Baca-García E. Current challenges in research on suicide. Revista de Psiquiatría y Salud Mental (English Edition) 2018;11(1):1
CrossRef -
Mehrotra A, Musolesi M. Using Autoencoders to Automatically Extract Mobility Features for Predicting Depressive States. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(3):1
CrossRef -
Cai L, Boukhechba M, Gerber MS, Barnes LE, Showalter SL, Cohn WF, Chow PI. An integrated framework for using mobile sensing to understand response to mobile interventions among breast cancer patients. Smart Health 2020;15:100086
CrossRef -
Saeb S, Lattie EG, Schueller SM, Kording KP, Mohr DC. The relationship between mobile phone location sensor data and depressive symptom severity. PeerJ 2016;4:e2537
CrossRef -
Sultana M, Al-Jefri M, Lee J. Using Machine Learning and Smartphone and Smartwatch Data to Detect Emotional States and Transitions: An Exploratory Study (Preprint). JMIR mHealth and uHealth 2020;
CrossRef -
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
CrossRef -
Shaffer JA, Kronish IM, Falzon L, Cheung YK, Davidson KW. N-of-1 Randomized Intervention Trials in Health Psychology: A Systematic Review and Methodology Critique. Annals of Behavioral Medicine 2018;52(9):731
CrossRef -
Torous J, Kiang MV, Lorme J, Onnela J. New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research. JMIR Mental Health 2016;3(2):e16
CrossRef -
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)
CrossRef -
Darvariu V, Convertino L, Mehrotra A, Musolesi M. Quantifying the Relationships between Everyday Objects and Emotional States through Deep Learning Based Image Analysis Using Smartphones. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(1):1
CrossRef -
Suffoletto B, Scaglione S. Using Digital Interventions to Support Individuals with Alcohol Use Disorder and Advanced Liver Disease: A Bridge Over Troubled Waters. Alcoholism: Clinical and Experimental Research 2018;42(7):1160
CrossRef -
Huckins JF, daSilva AW, Wang R, Wang W, Hedlund EL, Murphy EI, Lopez RB, Rogers C, Holtzheimer PE, Kelley WM, Heatherton TF, Wagner DD, Haxby JV, Campbell AT. Fusing Mobile Phone Sensing and Brain Imaging to Assess Depression in College Students. Frontiers in Neuroscience 2019;13
CrossRef -
Armontrout J, Torous J, Fisher M, Drogin E, Gutheil T. Mobile Mental Health: Navigating New Rules and Regulations for Digital Tools. Current Psychiatry Reports 2016;18(10)
CrossRef -
Balicer RD, Luengo-Oroz M, Cohen-Stavi C, Loyola E, Mantingh F, Romanoff L, Galea G. Using big data for non-communicable disease surveillance. The Lancet Diabetes & Endocrinology 2018;6(8):595
CrossRef -
Silvera-Tawil D, Hussain MS, Li J. Emerging technologies for precision health: An insight into sensing technologies for health and wellbeing. Smart Health 2020;15:100100
CrossRef -
Narziev N, Goh H, Toshnazarov K, Lee SA, Chung K, Noh Y. STDD: Short-Term Depression Detection with Passive Sensing. Sensors 2020;20(5):1396
CrossRef -
Busk J, Faurholt-Jepsen M, Frost M, Bardram JE, Vedel Kessing L, Winther O. Forecasting Mood in Bipolar Disorder From Smartphone Self-assessments: Hierarchical Bayesian Approach. JMIR mHealth and uHealth 2020;8(4):e15028
CrossRef -
Barnett I, Onnela J. Inferring mobility measures from GPS traces with missing data. Biostatistics 2020;21(2):e98
CrossRef -
Ware S, Yue C, Morillo R, Lu J, Shang C, Kamath J, Bamis A, Bi J, Russell A, Wang B. Large-scale Automatic Depression Screening Using Meta-data from WiFi Infrastructure. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(4):1
CrossRef -
Renn BN, Pratap A, Atkins DC, Mooney SD, Areán PA. Smartphone-based passive assessment of mobility in depression: Challenges and opportunities. Mental Health and Physical Activity 2018;14:136
CrossRef -
Cuttone A, Bækgaard P, Sekara V, Jonsson H, Larsen JE, Lehmann S, Zhou W. SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events. PLOS ONE 2017;12(1):e0169901
CrossRef -
Rawtaer I, Mahendran R, Kua EH, Tan HP, Tan HX, Lee T, Ng TP. Early Detection of Mild Cognitive Impairment With In-Home Sensors to Monitor Behavior Patterns in Community-Dwelling Senior Citizens in Singapore: Cross-Sectional Feasibility Study. Journal of Medical Internet Research 2020;22(5):e16854
CrossRef -
Trifan A, Oliveira M, Oliveira JL. Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations. JMIR mHealth and uHealth 2019;7(8):e12649
CrossRef -
Aubourg T, Demongeot J, Renard F, Provost H, Vuillerme N. Association between social asymmetry and depression in older adults: A phone Call Detail Records analysis. Scientific Reports 2019;9(1)
CrossRef -
Meng J, Hussain SA, Mohr DC, Czerwinski M, Zhang M. Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study. Journal of Medical Internet Research 2018;20(7):e10139
CrossRef -
Holtz BE, McCarroll AM, Mitchell KM. Perceptions and Attitudes Toward a Mobile Phone App for Mental Health for College Students: Qualitative Focus Group Study. JMIR Formative Research 2020;4(8):e18347
CrossRef -
Perle JG. A Practical Guide for Health Service Providers on the Design, Development, and Deployment of Smartphone Apps for the Delivery of Clinical Services. Journal of Technology in Behavioral Science 2020;5(1):1
CrossRef -
Hekler E, Tiro JA, Hunter CM, Nebeker C. Precision Health: The Role of the Social and Behavioral Sciences in Advancing the Vision. Annals of Behavioral Medicine 2020;54(11):805
CrossRef -
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
CrossRef -
Fillekes MP, Giannouli E, Kim E, Zijlstra W, Weibel R. Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research. International Journal of Health Geographics 2019;18(1)
CrossRef -
Martinez-Martin N, Insel TR, Dagum P, Greely HT, Cho MK. Data mining for health: staking out the ethical territory of digital phenotyping. npj Digital Medicine 2018;1(1)
CrossRef -
Low CA, Dey AK, Ferreira D, Kamarck T, Sun W, Bae S, Doryab A. Estimation of Symptom Severity During Chemotherapy From Passively Sensed Data: Exploratory Study. Journal of Medical Internet Research 2017;19(12):e420
CrossRef -
Raugh IM, James SH, Gonzalez CM, Chapman HC, Cohen AS, Kirkpatrick B, Strauss GP. Geolocation as a Digital Phenotyping Measure of Negative Symptoms and Functional Outcome. Schizophrenia Bulletin 2020;46(6):1596
CrossRef -
Wicks P, Hotopf M, Narayan VA, Basch E, Weatherall J, Gray M. It’s a long shot, but it just might work! Perspectives on the future of medicine. BMC Medicine 2016;14(1)
CrossRef -
Jones M, Johnson M, Shervey M, Dudley JT, 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
CrossRef -
Faherty LJ, Hantsoo L, Appleby D, Sammel MD, Bennett IM, Wiebe DJ. Movement patterns in women at risk for perinatal depression: use of a
mood-monitoring mobile application in pregnancy. Journal of the American Medical Informatics Association 2017;24(4):746
CrossRef -
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
CrossRef -
Andrade AQ, Roughead EE. Consumer‐directed technologies to improve medication management and safety. Medical Journal of Australia 2019;210(S6)
CrossRef -
Aledavood T, Triana Hoyos AM, Alakörkkö T, Kaski K, Saramäki J, Isometsä E, Darst RK. Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype. JMIR Research Protocols 2017;6(6):e110
CrossRef -
Wang W, Harari GM, Wang R, Müller SR, Mirjafari S, Masaba K, Campbell AT. Sensing Behavioral Change over Time. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(3):1
CrossRef -
Levinson CA, Christian C, Shankar‐Ram S, Brosof LC, Williams B. Sensor technology implementation for research, treatment, and assessment of eating disorders. International Journal of Eating Disorders 2019;52(10):1176
CrossRef -
Wu C, Boukhechba M, Cai L, Barnes LE, Gerber MS. Improving momentary stress measurement and prediction with bluetooth encounter networks. Smart Health 2018;9-10:219
CrossRef -
Sefidgar YS, Seo W, Kuehn KS, Althoff T, Browning A, Riskin E, Nurius PS, Dey AK, Mankoff J. Passively-sensed Behavioral Correlates of Discrimination Events in College Students. Proceedings of the ACM on Human-Computer Interaction 2019;3(CSCW):1
CrossRef -
Tuarob S, Tucker CS, Kumara S, Giles CL, Pincus AL, Conroy DE, Ram N. How are you feeling?: A personalized methodology for predicting mental states from temporally observable physical and behavioral information. Journal of Biomedical Informatics 2017;68:1
CrossRef -
Stachl C, Hilbert S, Au J, Buschek D, De Luca A, Bischl B, Hussmann H, Bühner M, Wrzus C. Personality Traits Predict Smartphone Usage. European Journal of Personality 2017;31(6):701
CrossRef -
Xu X, Chikersal P, Doryab A, Villalba DK, Dutcher JM, Tumminia MJ, Althoff T, Cohen S, Creswell KG, Creswell JD, Mankoff J, Dey AK. Leveraging Routine Behavior and Contextually-Filtered Features for Depression Detection among College Students. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019;3(3):1
CrossRef -
Chow PI, Fua K, Huang Y, Bonelli W, Xiong H, Barnes LE, Teachman BA. Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students. Journal of Medical Internet Research 2017;19(3):e62
CrossRef -
Bhattacharya K, Kaski K. Social physics: uncovering human behaviour from communication. Advances in Physics: X 2019;4(1):1527723
CrossRef -
Turvey C, Fortney J. The Use of Telemedicine and Mobile Technology to Promote Population Health and Population Management for Psychiatric Disorders. Current Psychiatry Reports 2017;19(11)
CrossRef -
Torous J, Levin ME, Ahern DK, Oser ML. Cognitive Behavioral Mobile Applications: Clinical Studies, Marketplace Overview, and Research Agenda. Cognitive and Behavioral Practice 2017;24(2):215
CrossRef -
Morshed MB, Saha K, Li R, D'Mello SK, De Choudhury M, Abowd GD, Plötz T. Prediction of Mood Instability with Passive Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019;3(3):1
CrossRef -
Obuchi M, Huckins JF, 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
CrossRef -
Hird N, Ghosh S, Kitano H. Digital health revolution: perfect storm or perfect opportunity for pharmaceutical R&D?. Drug Discovery Today 2016;21(6):900
CrossRef -
Bruehlman-Senecal E, Aguilera A, Schueller SM. Mobile Phone–Based Mood Ratings Prospectively Predict Psychotherapy Attendance. Behavior Therapy 2017;48(5):614
CrossRef -
Boukhechba M, Chow P, Fua K, Teachman BA, Barnes LE. Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study. JMIR Mental Health 2018;5(3):e10101
CrossRef -
Briffault X, Morgiève M, Courtet P. From e-Health to i-Health: Prospective Reflexions on the Use of Intelligent Systems in Mental Health Care. Brain Sciences 2018;8(6):98
CrossRef -
Barrigón ML, Baca-García E. Retos actuales en la investigación en suicidio. Revista de Psiquiatría y Salud Mental 2018;11(1):1
CrossRef -
Huguet A, Rao S, McGrath PJ, Wozney L, Wheaton M, Conrod J, Rozario S, Choo KR. A Systematic Review of Cognitive Behavioral Therapy and Behavioral Activation Apps for Depression. PLOS ONE 2016;11(5):e0154248
CrossRef -
Singh VK, Long T. Automatic assessment of mental health using phone metadata. Proceedings of the Association for Information Science and Technology 2018;55(1):450
CrossRef -
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
CrossRef -
Christensen MA, Bettencourt L, Kaye L, Moturu ST, Nguyen KT, Olgin JE, Pletcher MJ, Marcus GM, Romigi A. Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep. PLOS ONE 2016;11(11):e0165331
CrossRef -
Cho A, Lee H, Jo Y, Whang M. Embodied Emotion Recognition Based on Life-Logging. Sensors 2019;19(23):5308
CrossRef -
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
CrossRef -
Klaas V, Troster G, Walt H, Jenewein J. Remotely Monitoring Cancer-Related Fatigue Using the Smart-Phone: Results of an Observational Study. Information 2018;9(11):271
CrossRef -
Basco MR, Kyrarini M, Makedon FS. Personal Devices and Smartphone Applications for Detection of Depression. Psychiatric Annals 2020;50(6):255
CrossRef -
Adler DA, Ben-Zeev D, Tseng VW, Kane JM, Brian R, Campbell AT, Hauser M, Scherer EA, Choudhury T. Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks. JMIR mHealth and uHealth 2020;8(8):e19962
CrossRef -
Lu J, Shang C, Yue C, Morillo R, Ware S, Kamath J, Bamis A, Russell A, Wang B, Bi J. Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(1):1
CrossRef -
Saeb S, Cybulski TR, Kording KP, Mohr DC. Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles. Journal of Medical Internet Research 2017;19(4):e118
CrossRef -
Yim SJ, Lui LM, Lee Y, Rosenblat JD, Ragguett R, Park C, Subramaniapillai M, Cao B, Zhou A, Rong C, Lin K, Ho RC, Coles AS, Majeed A, Wong ER, Phan L, Nasri F, McIntyre RS. The utility of smartphone-based, ecological momentary assessment for depressive symptoms. Journal of Affective Disorders 2020;274:602
CrossRef -
Johansen B, Petersen M, Korzepa M, Larsen J, Pontoppidan N, Larsen J. Personalizing the Fitting of Hearing Aids by Learning Contextual Preferences From Internet of Things Data. Computers 2017;7(1):1
CrossRef -
Miloff A, Marklund A, Carlbring P. The challenger app for social anxiety disorder: New advances in mobile psychological treatment. Internet Interventions 2015;2(4):382
CrossRef -
Malhi GS, Hamilton A, Morris G, Mannie Z, Das P, Outhred T. The promise of digital mood tracking technologies: are we heading on the right track?. Evidence Based Mental Health 2017;20(4):102
CrossRef -
Mohr DC, Zhang M, Schueller SM. Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning. Annual Review of Clinical Psychology 2017;13(1):23
CrossRef -
Nicholas J, Shilton K, Schueller SM, Gray EL, Kwasny MJ, Mohr DC. The Role of Data Type and Recipient in Individuals’ Perspectives on Sharing Passively Collected Smartphone Data for Mental Health: Cross-Sectional Questionnaire Study. JMIR mHealth and uHealth 2019;7(4):e12578
CrossRef -
Frank E, Pong J, Asher Y, Soares CN. Smart phone technologies and ecological momentary data. Current Opinion in Psychiatry 2018;31(1):3
CrossRef -
Goodspeed R, Yan X, Hardy J, Vydiswaran VV, Berrocal VJ, Clarke P, Romero DM, Gomez-Lopez IN, Veinot T. Comparing the Data Quality of Global Positioning System Devices and Mobile Phones for Assessing Relationships Between Place, Mobility, and Health: Field Study. JMIR mHealth and uHealth 2018;6(8):e168
CrossRef -
Aledavood T, Lehmann S, Saramäki J. Digital daily cycles of individuals. Frontiers in Physics 2015;3
CrossRef -
Craske MG. Honoring the Past, Envisioning the Future: ABCT’s 50th Anniversary Presidential Address. Behavior Therapy 2018;49(2):151
CrossRef -
Ware S, Yue C, Morillo R, Lu J, Shang C, Bi J, Kamath J, Russell A, Bamis A, Wang B. Predicting depressive symptoms using smartphone data. Smart Health 2020;15:100093
CrossRef -
Zulueta J, Piscitello A, Rasic M, Easter R, Babu P, Langenecker SA, McInnis M, Ajilore O, Nelson PC, Ryan K, Leow A. Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study. Journal of Medical Internet Research 2018;20(7):e241
CrossRef -
Palmius N, Tsanas A, Saunders KEA, Bilderbeck AC, Geddes JR, Goodwin GM, De Vos M. Detecting Bipolar Depression From Geographic Location Data. IEEE Transactions on Biomedical Engineering 2017;64(8):1761
CrossRef -
Place S, Blanch-Hartigan D, Rubin C, Gorrostieta C, Mead C, Kane J, Marx BP, 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
CrossRef -
Saeb S, Lattie EG, Kording KP, Mohr DC. Mobile Phone Detection of Semantic Location and Its Relationship to Depression and Anxiety. JMIR mHealth and uHealth 2017;5(8):e112
CrossRef -
Spaiser V, Luzzatti D, Gregoriou A, Ferrara E, Chadefaux T. Advancing sustainability: Using smartphones to study environmental behavior in a field-experimental setup. Data Science 2019;2(1-2):277
CrossRef -
Leonard NR, Silverman M, Sherpa DP, Naegle MA, Kim H, Coffman DL, Ferdschneider M. Mobile Health Technology Using a Wearable Sensorband for Female College Students With Problem Drinking: An Acceptability and Feasibility Study. JMIR mHealth and uHealth 2017;5(7):e90
CrossRef -
Harari GM, Lane ND, Wang R, Crosier BS, Campbell AT, Gosling SD. Using Smartphones to Collect Behavioral Data in Psychological Science. Perspectives on Psychological Science 2016;11(6):838
CrossRef -
Torous J, Rodriguez J, Powell A. The New Digital Divide For Digital Biomarkers. Digital Biomarkers 2017;
CrossRef -
Roberts LW, Chan S, Torous J. New tests, new tools: mobile and connected technologies in advancing psychiatric diagnosis. npj Digital Medicine 2018;1(1)
CrossRef -
Jim HSL, Hoogland AI, Brownstein NC, Barata A, Dicker AP, Knoop H, Gonzalez BD, Perkins R, Rollison D, Gilbert SM, Nanda R, Berglund A, Mitchell R, Johnstone PAS. Innovations in research and clinical care using patient‐generated health data. CA: A Cancer Journal for Clinicians 2020;70(3):182
CrossRef -
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
CrossRef -
Mastoras R, Iakovakis D, Hadjidimitriou S, Charisis V, Kassie S, Alsaadi T, Khandoker A, Hadjileontiadis LJ. Touchscreen typing pattern analysis for remote detection of the depressive tendency. Scientific Reports 2019;9(1)
CrossRef -
Webb CA, Rosso IM, Rauch SL. Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions. Harvard Review of Psychiatry 2017;25(3):114
CrossRef -
Kleiman EM, Nock MK. Real-time assessment of suicidal thoughts and behaviors. Current Opinion in Psychology 2018;22:33
CrossRef -
Berrouiguet S, Perez-Rodriguez MM, Larsen M, Baca-García E, Courtet P, Oquendo M. From eHealth to iHealth: Transition to Participatory and Personalized Medicine in Mental Health. Journal of Medical Internet Research 2018;20(1):e2
CrossRef -
Wahle F, Kowatsch T, Fleisch E, Rufer M, Weidt S. Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild. JMIR mHealth and uHealth 2016;4(3):e111
CrossRef -
Bhugra D, Tasman A, Pathare S, Priebe S, Smith S, Torous J, Arbuckle MR, Langford A, Alarcón RD, Chiu HFK, First MB, Kay J, Sunkel C, Thapar A, Udomratn P, Baingana FK, Kestel D, Ng RMK, Patel A, Picker LD, McKenzie KJ, Moussaoui D, Muijen M, Bartlett P, Davison S, Exworthy T, Loza N, Rose D, Torales J, Brown M, Christensen H, Firth J, Keshavan M, Li A, Onnela J, Wykes T, Elkholy H, Kalra G, Lovett KF, Travis MJ, Ventriglio A. The WPA- Lancet Psychiatry Commission on the Future of Psychiatry. The Lancet Psychiatry 2017;4(10):775
CrossRef -
DeMasi O, Kording K, Recht B, Jan Y. Meaningless comparisons lead to false optimism in medical machine learning. PLOS ONE 2017;12(9):e0184604
CrossRef -
Šimon M, Vašát P, Poláková M, Gibas P, Daňková H. Activity spaces of homeless men and women measured by GPS tracking data: A comparative analysis of Prague and Pilsen. Cities 2019;86:145
CrossRef -
Singh VK, Goyal R, Wu S. Riskalyzer. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(1):1
CrossRef -
Eichstaedt JC, Smith RJ, Merchant RM, Ungar LH, Crutchley P, Preoţiuc-Pietro D, Asch DA, Schwartz HA. Facebook language predicts depression in medical records. Proceedings of the National Academy of Sciences 2018;115(44):11203
CrossRef -
Piau A, Rumeau P, Nourhashemi F, Martin MS. Information and Communication Technologies, a Promising Way to Support Pharmacotherapy for the Behavioral and Psychological Symptoms of Dementia. Frontiers in Pharmacology 2019;10
CrossRef -
Li B, Sano A. Extraction and Interpretation of Deep Autoencoder-based Temporal Features from Wearables for Forecasting Personalized Mood, Health, and Stress. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(2):1
CrossRef -
Bourla A, Mouchabac S, El Hage W, Ferreri F. e-PTSD: an overview on how new technologies can improve prediction and assessment of Posttraumatic Stress Disorder (PTSD). European Journal of Psychotraumatology 2018;9(sup1):1424448
CrossRef -
Bidargaddi N, Musiat P, Makinen V, Ermes M, Schrader G, Licinio J. Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies. Molecular Psychiatry 2017;22(2):164
CrossRef -
Kennedy SH, Ceniti AK. Unpacking Major Depressive Disorder: From Classification to Treatment Selection. The Canadian Journal of Psychiatry 2018;63(5):308
CrossRef -
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
CrossRef -
Bader CS, Skurla M, Vahia IV. Technology in the Assessment, Treatment, and Management of Depression. Harvard Review of Psychiatry 2020;28(1):60
CrossRef -
Harari GM. A process-oriented approach to respecting privacy in the context of mobile phone tracking. Current Opinion in Psychology 2020;31:141
CrossRef -
Arean PA, Hallgren KA, Jordan JT, Gazzaley A, Atkins DC, Heagerty PJ, Anguera JA. The Use and Effectiveness of Mobile Apps for Depression: Results From a Fully Remote Clinical Trial. Journal of Medical Internet Research 2016;18(12):e330
CrossRef -
Sarda A, Munuswamy S, Sarda S, Subramanian V. Using Passive Smartphone Sensing for Improved Risk Stratification of Patients With Depression and Diabetes: Cross-Sectional Observational Study. JMIR mHealth and uHealth 2019;7(1):e11041
CrossRef -
Doryab A, Villalba DK, Chikersal P, Dutcher JM, Tumminia M, Liu X, Cohen S, Creswell K, Mankoff J, Creswell JD, Dey AK. Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data. JMIR mHealth and uHealth 2019;7(7):e13209
CrossRef -
Wang R, Wang W, daSilva A, Huckins JF, Kelley WM, Heatherton TF, Campbell AT. Tracking Depression Dynamics in College Students Using Mobile Phone and Wearable Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(1):1
CrossRef -
Singh VK, Ghosh I. Inferring Individual Social Capital Automatically via Phone Logs. Proceedings of the ACM on Human-Computer Interaction 2017;1(CSCW):1
CrossRef -
Jongs N, Jagesar R, van Haren NEM, Penninx BWJH, Reus L, Visser PJ, van der Wee NJA, Koning IM, Arango C, Sommer IEC, Eijkemans MJC, Vorstman JA, Kas MJ. A framework for assessing neuropsychiatric phenotypes by using smartphone-based location data. Translational Psychiatry 2020;10(1)
CrossRef -
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
CrossRef -
Sarikaya R. The Technology Behind Personal Digital Assistants: An overview of the system architecture and key components. IEEE Signal Processing Magazine 2017;34(1):67
CrossRef -
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
CrossRef -
Ha Q, Chen JV, Uy HU, Capistrano EP. Exploring the Privacy Concerns in Using Intelligent Virtual Assistants under Perspectives of Information Sensitivity and Anthropomorphism. International Journal of Human–Computer Interaction 2020;:1
CrossRef -
Thakur SS, Roy RB. Predicting mental health using smart-phone usage and sensor data. Journal of Ambient Intelligence and Humanized Computing 2020;
CrossRef -
Bertoa MF, Moreno N, Perez-Vereda A, Bandera D, Álvarez-Palomo JM, Canal C, Linaje M. Digital Avatars: Promoting Independent Living for Older Adults. Wireless Communications and Mobile Computing 2020;2020:1
CrossRef -
Wang Y, Mao H. Intelligent soccer system based on biosensor network technology. Measurement 2021;173:108564
CrossRef -
Fischer F, Kleen S. Possibilities, Problems, and Perspectives of Data Collection by Mobile Apps in Longitudinal Epidemiological Studies: Scoping Review. Journal of Medical Internet Research 2021;23(1):e17691
CrossRef -
Taeger J, Bischoff S, Hagen R, Rak K. Utilization of Smartphone Depth Mapping Cameras for App-Based Grading of Facial Movement Disorders: Development and Feasibility Study. JMIR mHealth and uHealth 2021;9(1):e19346
CrossRef -
Fulford D, Mote J, Gonzalez R, Abplanalp S, Zhang Y, Luckenbaugh J, Onnela J, Busso C, Gard DE. Smartphone sensing of social interactions in people with and without schizophrenia. Journal of Psychiatric Research 2020;
CrossRef -
Moshe I, Terhorst Y, Opoku Asare K, Sander LB, Ferreira D, Baumeister H, Mohr DC, Pulkki-Råback L. Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data. Frontiers in Psychiatry 2021;12
CrossRef -
Aubourg T, Demongeot J, Vuillerme N. Novel statistical approach for assessing the persistence of the circadian rhythms of social activity from telephone call detail records in older adults. Scientific Reports 2020;10(1)
CrossRef -
Zulueta J, Ajilore OA. Beyond non-inferior: how telepsychiatry technologies can lead to superior care. International Review of Psychiatry 2020;:1
CrossRef -
Kumar D, Jeuris S, Bardram JE, Dragoni N. Mobile and Wearable Sensing Frameworks for mHealth Studies and Applications. ACM Transactions on Computing for Healthcare 2021;2(1):1
CrossRef -
Thongnopakun S, Visanuyothin S, Manwong M, Rodjarkpai Y, Patipat P.
Promoting Health Literacy to Prevent Depression Among Workers in Industrial Factories in the Eastern Economic Corridor of Thailand
. Journal of Multidisciplinary Healthcare 2020;Volume 13:1443
CrossRef -
Pedrelli P, Fedor S, Ghandeharioun A, Howe E, Ionescu DF, Bhathena D, Fisher LB, Cusin C, Nyer M, Yeung A, Sangermano L, Mischoulon D, Alpert JE, Picard RW. Monitoring Changes in Depression Severity Using Wearable and Mobile Sensors. Frontiers in Psychiatry 2020;11
CrossRef -
Mendu S, Baglione A, Baee S, Wu C, Ng B, Shaked A, Clore G, Boukhechba M, Barnes L. A Framework for Understanding the Relationship between Social Media Discourse and Mental Health. Proceedings of the ACM on Human-Computer Interaction 2020;4(CSCW2):1
CrossRef -
Chikersal P, Doryab A, Tumminia M, Villalba DK, Dutcher JM, Liu X, Cohen S, Creswell KG, Mankoff J, Creswell JD, Goel M, Dey AK. Detecting Depression and Predicting its Onset Using Longitudinal Symptoms Captured by Passive Sensing. ACM Transactions on Computer-Human Interaction 2021;28(1):1
CrossRef -
Wang Y, Ren X, Liu X, Zhu T. Examining the Correlation Between Depression and Social Behavior on Smartphones Through Usage Metadata: Empirical Study. JMIR mHealth and uHealth 2021;9(1):e19046
CrossRef -
Wen H, Sobolev M, Vitale R, Kizer J, Pollak JP, Muench F, Estrin D. mPulse Mobile Sensing Model for Passive Detection of Impulsive Behavior: Exploratory Prediction Study. JMIR Mental Health 2021;8(1):e25019
CrossRef -
Aubourg T, Demongeot J, Provost H, Vuillerme N. Exploitation of Outgoing and Incoming Telephone Calls in the Context of Circadian Rhythms of Social Activity Among Elderly People: Observational Descriptive Study. JMIR mHealth and uHealth 2020;8(11):e13535
CrossRef -
He-Yueya J, Buck B, Campbell A, Choudhury T, Kane JM, Ben-Zeev D, Althoff T. Assessing the relationship between routine and schizophrenia symptoms with passively sensed measures of behavioral stability. npj Schizophrenia 2020;6(1)
CrossRef -
Low CA. Harnessing consumer smartphone and wearable sensors for clinical cancer research. npj Digital Medicine 2020;3(1)
CrossRef -
Asuzu K, Rosenthal MZ. Mobile device use among inpatients on a psychiatric unit: A preliminary study. Psychiatry Research 2021;297:113720
CrossRef -
Hafiz P, Miskowiak KW, Maxhuni A, Kessing LV, Bardram JE. Wearable Computing Technology for Assessment of Cognitive Functioning of Bipolar Patients and Healthy Controls. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(4):1
CrossRef -
Martinez-Martin N, Dasgupta I, Carter A, Chandler JA, Kellmeyer P, Kreitmair K, Weiss A, Cabrera LY. Ethics of Digital Mental Health During COVID-19: Crisis and Opportunities. JMIR Mental Health 2020;7(12):e23776
CrossRef -
Gutierrez LJ, Rabbani K, Ajayi OJ, Gebresilassie SK, Rafferty J, Castro LA, Banos O. Internet of Things for Mental Health: Open Issues in Data Acquisition, Self-Organization, Service Level Agreement, and Identity Management. International Journal of Environmental Research and Public Health 2021;18(3):1327
CrossRef -
Elhai JD, Sapci O, Yang H, Amialchuk A, Rozgonjuk D, Montag C. Objectively‐measured and self‐reported smartphone use in relation to surface learning, procrastination, academic productivity, and psychopathology symptoms in college students. Human Behavior and Emerging Technologies 2021;
CrossRef
According to Crossref, the following books are citing this article (DOI 10.2196/jmir.4273):
-
Dagum P, Montag C. Digital Phenotyping and Mobile Sensing. 2019. Chapter 2:13
CrossRef -
Derksen JJL. Preventie psychische aandoeningen. 2018. Chapter 2:31
CrossRef -
Lee H, Cho A, Jo Y, Whang M. Advances in Computer Science and Ubiquitous Computing. 2018. Chapter 212:1332
CrossRef -
Vayena E, Gasser U. The Ethics of Biomedical Big Data. 2016. Chapter 2:17
CrossRef -
Lee H, Jo Y, Kim H, Whang M. Advances in Computer Science and Ubiquitous Computing. 2018. Chapter 219:1377
CrossRef -
. The Cambridge Handbook of Research Methods in Clinical Psychology. 2020. Part VI:299
CrossRef -
Losada DE, Crestani F. Experimental IR Meets Multilinguality, Multimodality, and Interaction. 2016. Chapter 3:28
CrossRef -
Ferguson SG, Jahnel T, Elliston K, Shiffman S. The Cambridge Handbook of Research Methods in Clinical Psychology. 2020. 23:301
CrossRef -
Chanchaichujit J, Tan A, Meng F, Eaimkhong S. Healthcare 4.0. 2019. Chapter 2:17
CrossRef -
Fang Y, Mao R. Depressive Disorders: Mechanisms, Measurement and Management. 2019. Chapter 1:1
CrossRef -
Maglogiannis I, Zlatintsi A, Menychtas A, Papadimatos D, Filntisis PP, Efthymiou N, Retsinas G, Tsanakas P, Maragos P. Artificial Intelligence Applications and Innovations. 2020. Chapter 25:293
CrossRef -
Cho A, Lee H, Hwang H, Jo Y, Whang M. Advances in Computer Science and Ubiquitous Computing. 2018. Chapter 218:1371
CrossRef -
Klaas VC, Calatroni A, Hardegger M, Guckenberger M, Theile G, Tröster G. Wireless Mobile Communication and Healthcare. 2017. Chapter 28:207
CrossRef -
Thakur SS, Roy RB. Computational Intelligence: Theories, Applications and Future Directions - Volume I. 2019. Chapter 10:119
CrossRef -
Rozgonjuk D, Elhai JD, Hall BJ. Digital Phenotyping and Mobile Sensing. 2019. Chapter 11:185
CrossRef -
Rabbi M. Encyclopedia of Behavioral Medicine. 2020. Chapter 102004-1:1
CrossRef -
Cummins N, Matcham F, Klapper J, Schuller B. Artificial Intelligence in Precision Health. 2020. :231
CrossRef -
Duke , Montag C. Internet Addiction. 2017. Chapter 21:359
CrossRef -
Pérez-Vereda A, Flores-Martín D, Canal C, Murillo JM. Gerontechnology. 2019. Chapter 1:3
CrossRef -
Theilig M, Blankenhagel KJ, Zarnekow R. Information Systems and Neuroscience. 2019. Chapter 20:163
CrossRef -
Wolfer J. Online Engineering & Internet of Things. 2018. Chapter 63:672
CrossRef -
Rabbi M, Hane Aung M, Choudhury T. Mobile Health. 2017. Chapter 26:519
CrossRef -
Singh VK, Ghosh I. Encyclopedia of Behavioral Medicine. 2018. Chapter 102005-1:1
CrossRef -
Rustagi A, Manchanda C, Sharma N, Kaushik I. International Conference on Innovative Computing and Communications. 2021. Chapter 3:19
CrossRef -
Castro LA, Rodríguez MD, Martínez F, Rodríguez L, Andrade G, Cornejo R. Intelligent Data Sensing and Processing for Health and Well-Being Applications. 2018. :3
CrossRef -
Singh VK, Ghosh I. Encyclopedia of Behavioral Medicine. 2020. Chapter 102005:218
CrossRef -
Rabbi M. Encyclopedia of Behavioral Medicine. 2020. Chapter 102004:1632
CrossRef -
Harari GM, Stachl C, Müller SR, Gosling SD. The Handbook of Personality Dynamics and Processes. 2021. :763
CrossRef -
Tushar AK, Kabir MA, Ahmed SI. Signal Processing Techniques for Computational Health Informatics. 2021. Chapter 11:247
CrossRef