Published on in Vol 19, No 3 (2017): March

Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students

Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students

Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students

Journals

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  17. Xu X, Chikersal P, Doryab A, Villalba D, Dutcher J, Tumminia M, Althoff T, Cohen S, Creswell K, Creswell J, Mankoff J, Dey A. 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 View
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  20. Chow P, Showalter S, Gerber M, Kennedy E, Brenin D, Schroen A, Mohr D, Lattie E, Cohn W. Use of Mental Health Apps by Breast Cancer Patients and Their Caregivers in the United States: Protocol for a Pilot Pre-Post Study. JMIR Research Protocols 2019;8(1):e11452 View
  21. Rashid H, Mendu S, Daniel K, Beltzer M, Teachman B, Boukhechba M, Barnes L. 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 View
  22. Chan S, Godwin H, Gonzalez A, Yellowlees P, Hilty D. Review of Use and Integration of Mobile Apps Into Psychiatric Treatments. Current Psychiatry Reports 2017;19(12) View
  23. Nicholas J, Shilton K, Schueller S, Gray E, Kwasny M, Mohr D. 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 View
  24. Montag C, Baumeister H, Kannen C, Sariyska R, Meßner E, Brand M. Concept, Possibilities and Pilot-Testing of a New Smartphone Application for the Social and Life Sciences to Study Human Behavior Including Validation Data from Personality Psychology. J 2019;2(2):102 View
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  28. 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 View
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  33. Di Matteo D, Fotinos K, Lokuge S, Yu J, Sternat T, Katzman M, Rose J. The Relationship Between Smartphone-Recorded Environmental Audio and Symptomatology of Anxiety and Depression: Exploratory Study. JMIR Formative Research 2020;4(8):e18751 View
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  38. Chikersal P, Doryab A, Tumminia M, Villalba D, Dutcher J, Liu X, Cohen S, Creswell K, Mankoff J, Creswell J, Goel M, Dey A. Detecting Depression and Predicting its Onset Using Longitudinal Symptoms Captured by Passive Sensing. ACM Transactions on Computer-Human Interaction 2021;28(1):1 View
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  45. Xu X, Chikersal P, Dutcher J, Sefidgar Y, Seo W, Tumminia M, Villalba D, Cohen S, Creswell K, Creswell J, Doryab A, Nurius P, Riskin E, Dey A, Mankoff J. Leveraging Collaborative-Filtering for Personalized Behavior Modeling. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2021;5(1):1 View
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Books/Policy Documents

  1. Lee J, Lam M, Chiu C. Pervasive Computing Paradigms for Mental Health. View
  2. Hur J, Stockbridge M, Fox A, Shackman A. Emotion and Cognition. View
  3. Lee H, Cho A, Jo Y, Whang M. Advances in Computer Science and Ubiquitous Computing. View
  4. Seidl D. The Geographies of COVID-19. View
  5. Chemagosi M, Barongo S. Student Stress in Higher Education. View
  6. Zafeiridi E, Qirtas M, Bantry White E, Pesch D. Bridging the Gap Between AI and Reality. View