The relationship between mobile phone location sensor data and depressive symptom severity

Saeb, Sohrab, Lattie, Emily G., Schueller, Stephen M., Kording, Konrad P., Mohr, David C.·2016·PeerJ
DOI 10.7717/peerj.2537

Cited by (311)

Items 101–200 of 311

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  4. Smartphone Sensor Data for Identifying and Monitoring Symptoms of Mood Disorders: A Longitudinal Observational Study
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  6. Screening for Depression in Mobile Devices Using Patient Health Questionnaire-9 (PHQ-9) Data: A Diagnostic Meta-Analysis via Machine Learning Methods
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  7. Applied Affective Computing
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  8. Towards the use of commercial wrist wearables in education
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  9. Ethical Dimensions of Digital Phenotyping Within the Context of Mental Healthcare
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  10. The Relation Between Passively Collected GPS Mobility Metrics and Depressive Symptoms: Systematic Review and Meta-Analysis
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  11. The potential of digital phenotyping to advance the contributions of mobile health to self-management science
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  12. Digital Phenotyping in Child and Adolescent Psychiatry: A Perspective
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  13. Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment
    Hart, Alexander, Reis, Dorota, Prestele, Elisabeth, Jacobson, Nicholas C · 2022 · Journal of Medical Internet Research
  14. Multimodal Digital Phenotyping Study in Patients With Major Depressive Episodes and Healthy Controls (Mobile Monitoring of Mood): Observational Longitudinal Study
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  15. Google Trends as a Method to Predict New COVID-19 Cases and Socio-Psychological Consequences of the Pandemic
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  16. Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping
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  17. Use of Mobile Sensing Data for Longitudinal Monitoring and Prediction of Depression Severity: Systematic Review
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  18. Depression Detection Through Smartphone Sensing: A Federated Learning Approach
    Nawrin Tabassum, Mustofa Ahmed, Nushrat Jahan Shorna, MD Mejbah Ur Rahman Sowad Sowad, H M Zabir Haque · 2023 · International Journal of Interactive Mobile Technologies (iJIM)
  19. An Ensemble Classification Model for Depression Based on Wearable Device Sleep Data
    Yuzhu Hu, Jian Chen, Junxin Chen, Wei William Wang, Shen Zhao, Xiping Hu · 2023 · IEEE Journal of Biomedical and Health Informatics
  20. Beyond Detection: Towards Actionable Sensing Research in Clinical Mental Healthcare
    Daniel A. Adler, Yuewen Yang, Thalia Viranda, Xuhai Xu, David C. Mohr, Anna Van Meter, Julia Tartaglia, Nicholas C. Jacobson, Fei Wang, Deborah L. Estrin et al. · 2024 · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  21. Comparing self reported and physiological sleep quality from consumer devices to depression and neurocognitive performance
    Samir Akre, Zachary Daniel Cohen, Amelia Welborn, Tomislav D. Zbozinek, Brunilda Balliu, Michelle Genevieve Craske, Alex A. T. Bui · 2025 · npj Digital Medicine
  22. Physiological Stress Level Estimation Based on Smartphone Logs
    Naoki Yamamoto, Keiichi Ochiai, Akiya Inagaki, Yusuke Fukazawa, Masatoshi Kimoto, Kazuki Kiriu, Kouhei Kaminishi, Jun Ota, Tsukasa Okimura, Yuri Terasawa et al. · 2018 · International Conference on Mobile Computing and Ubiquitous Network (ICMU)
  23. Clinician perspectives on how digital phenotyping can inform client treatment
    Simone Schmidt, Simon D’Alfonso · 2023 · Acta Psychologica
  24. Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment
    Anastasia C. Bryan, Michael V. Heinz, Abigail J. Salzhauer, George D. Price, ML Tlachac, Nicholas C. Jacobson · 2024 · Biomedical Materials & Devices
  25. Sensing everyday activity: Parent perceptions and feasibility
    Hannah I. Levin, Dominique Egger, Lara Andres, Mckensey Johnson, Sarah Kate Bearman, Kaya de Barbaro · 2021 · Infant Behavior and Development
  26. You're Making Me Depressed: Leveraging Texts from Contact Subsets to Predict Depression
    ML Tlachac, Ermal Toto, Elke Angelika Rundensteiner · 2019 · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...)
  27. Disturbed sleep as a clinical marker of wish to die: A smartphone monitoring study over three months of observation
    Alejandro Porras‐Segovia, Aurora Cobo Aguilera, Isaac Díaz-Oliván, Antonio Artés-Rodrı́guez, Sofian Berrouiguet, Jorge López‐Castromán, Philippe Courtet, María Luisa Barrigón, María A. Oquendo, Enrique Baca‐García · 2021 · Journal of Affective Disorders
  28. Role of AI/ML in the study of mental health problems of the students: a bibliometric study
    S. S. Rajkishan, A. Jiran Meitei, Abha Singh · 2023 · International Journal of Systems Assurance Engineering and Management
  29. A commentary on the potential of smartphones and other wearable devices to be used in the identification and monitoring of mental illness
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  30. Improving Depression Severity Prediction from Passive Sensing: Symptom-Profiling Approach
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  32. Smartphones within Psychological Science
    David A. Ellis · 2020 · Cambridge University Press eBooks
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  34. Ecological Momentary Assessment for Monitoring Risk of Suicide Behavior
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  35. Trusting the bot: Addressing the ethical challenges of consumer digital mental health therapy
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  36. Wearable Computing Technology for Assessment of Cognitive Functioning of Bipolar Patients and Healthy Controls
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  37. Considerations for Designing Context-Aware Mobile Apps for Mental Health Interventions
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  38. The CARP Mobile Sensing Framework -- A Cross-platform, Reactive, Programming Framework and Runtime Environment for Digital Phenotyping
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  39. Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation
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  40. The comfort of adolescent patients and their parents with mobile sensing and digital phenotyping
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  41. Automated Time Manager: Effectiveness of Self-Regulation on Time Management Through a Smartphone Application
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  42. Tracking and Modeling Subjective Well-Being Using Smartphone-Based Digital Phenotype
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  46. Technology in the Assessment, Treatment, and Management of Depression
    Caroline S. Bader, Miranda D. Skurla, Ipsit Vihang Vahia · 2020 · Harvard Review of Psychiatry
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  48. Smartphone-based Mental State Estimation: A Survey from a Machine Learning Perspective
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  49. ARGUS: Interactive visual analysis of disruptions in smartphone-detected Bio-Behavioral Rhythms
    Hamid Mansoor, Walter Gerych, Abdulaziz Saleh Alajaji, Luke Buquicchio, Kavin Chandrasekaran, Emmanuel Agu, Elke Angelika Rundensteiner · 2021 · Visual Informatics
  50. Acceptance of smart sensing: a barrier to implementation—results from a randomized controlled trial
    Terhorst, Yannik, Weilbacher, Nadine, Suda, Carolin, Simon, Laura, Messner, Eva-Maria, Sander, Lasse Bosse, Baumeister, Harald · 2023 · Frontiers in Digital Health
  51. Mental Health Monitoring and Detection Based on Machine Learning and IoT Data
    Belal Mohsen, Osama D. Al-Khaleel, Abdullah Alfadhly · 2022 · International Journal of Information Technology & Decision Making
  52. Investigating Smartphone-Based Sensing Features for Depression Severity Prediction: Observation Study
    Yannik Terhorst, Eva-Maria Meßner, Kennedy Opoku Asare, Christian Montag, Christopher Kannen, Harald Baumeister · 2024 · Journal of Medical Internet Research
  53. The CAMS eSense Framework
    Jakob E. Bardram · 2019
  54. Mobile sensing in psychological and educational research: Examples from two application fields
    Efsun Birtwistle, Ramona Schoedel, Florian Bemmann, Astrid Wirth, Christoph Sürig, Clemens Stachl, Markus Bühner, Frank Niklas · 2022 · International Journal of Testing
  55. Technology-Based Ecological Momentary Assessment in Clinical Psychology
    Desirée Colombo, Carlos Suso‐Ribera, Javier Fernández‐Álvarez, Pietro Cipresso, Azucena García‐Palacios, Giuseppe Riva, Cristina Botella · 2020 · Elsevier eBooks
  56. A survey of autonomous monitoring systems in mental health
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  57. Smartphone and Wearable Device-Based Digital Phenotyping to Understand Substance use and its Syndemics
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  58. Emotion-Aware Systems for Promoting Human Well-being
    Elena Di Lascio · 2018 · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp)
  59. Making the MOST out of smartphone opportunities for mental health
    Simon D’Alfonso, Nathaniel Carpenter, Mario Álvarez‐Jiménez · 2018 · Australian Conference on Computer-Human Interaction (OzCHI)
  60. Conversational agents on smartphones and the web
    Timothy Bickmore, Teresa K. O’Leary · 2022 · Elsevier eBooks
  61. Dynamic Bidirectional Associations Between Global Positioning System Mobility and Ecological Momentary Assessment of Mood Symptoms in Mood Disorders: Prospective Cohort Study
    Ting-Yi Lee, Ching‐Hsuan Chen, I‐Ming Chen, Hsi‐Chung Chen, Chih‐Min Liu, Shu‐I Wu, Chuhsing Kate Hsiao, Po‐Hsiu Kuo · 2024 · Journal of Medical Internet Research
  62. Mobile sensing for studying personality dynamics in daily life
    Gabriella M. Harari, Clemens Stachl, Sandrine R. Müller, Samuel D. Gosling · 2021 · Elsevier eBooks
  63. On the Transition of Social Interaction from In-Person to Online: Predicting Changes in Social Media Usage of College Students during the COVID-19 Pandemic based on Pre-COVID-19 On-Campus Colocation
    Weichen Wang, Jialing Wu, Subigya Kumar Nepal, Alex W DaSilva, Elin L. Hedlund, Eilis I Murphy, Courtney Rogers, Jeremy F. Huckins · 2021 · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION
  64. Data-Driven Learning in High-Resolution Activity Sampling From Patients With Bipolar Depression: Mixed-Methods Study
    Darius A. Rohani, Nanna Tuxen, Andrea Quemada Lopategui, Lars Vedel Kessing, Jakob E. Bardram · 2018 · JMIR Mental Health
  65. Medical brain drain from Western Balkan and Croatia to Germany and Austria – an approach to the digital demography
    Tado Jurić · 2021 · medRxiv
  66. Integration of Sensor-Based Technology in Mental Healthcare: A Systematic Scoping Review
    R. Bosch, Matthijs Leendert Noordzij, Gerben J. Westerhof, Ernst Thomas Bohlmeijer · 2024 · Journal of Technology in Behavioral Science
  67. Digital phenotyping for mental health conditions: a systematic review of implementation and application
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  68. An exploration in remote blood pressure management: Application of daily routine pattern based on mobile data in health management
    Yidan Xiang, Shaochun Li, Pengzhu Zhang · 2021 · Fundamental Research
  69. Predicting Stress in Older Adults with RNN and LSTM from Time Series Sensor Data and Cortisol
    Md. Saif Hassan Onim, Himanshu Thapliyal · 2024 · IEEE Computer Society Annual Symposium on VLSI
  70. Machine Learning Prediction of TBI from Mobility, Gait and Balance Patterns
    Bhoomi Kalpesh Patel, Srinarayan Srikanthan, Florina Asani, Emmanuel Agu · 2021 · IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies
  71. Smartphone-Based Digital Phenotyping Across Health Conditions: Scoping Review
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  77. Individual-level Anxiety Detection and Prediction from Longitudinal YouTube and Google Search Engagement Logs
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  78. Underlying dimensions of depression and negative affect are equally related to problematic smartphone and social media use severity
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    Morgan Quinn Ross, Sandrine R. Müller, Joseph Bayer · 2022 · American Psychological Association eBooks
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  82. Integrated behavioral health treatments: innovations to achieve population impact
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  83. Technological Advances in Clinical Assessment
    Michael V. Heinz, Natalie Thomas, Nhi D. Nguyen, Tess Z. Griffin, Nicholas C. Jacobson · 2021 · Elsevier eBooks
  84. Predicting future sedentary behaviour using wearable and mobile devices
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  85. Towards a Framework for Assessing Daily Mobility Using GPS Data
    Michelle Pasquale Fillekes, Eleftheria Giannouli, Wiebren Zijlstra, Robert Weibel · 2018 · GI_Forum
  86. Measures of Behavior and Life Dynamics from Commonly Available GPS Data (DPLocate): Algorithm Development and Validation
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