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Journal of Medical Internet Research

Citing this Article

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Published on 29.03.16 in Vol 18, No 3 (2016): March

This paper is in the following e-collection/theme issue:

Works citing "Mobile Phone-Based Unobtrusive Ecological Momentary Assessment of Day-to-Day Mood: An Explorative Study"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.5505):

(note that this is only a small subset of citations)

  1. Hallgren KA, Bauer AM, Atkins DC. Digital technology and clinical decision making in depression treatment: Current findings and future opportunities. Depression and Anxiety 2017;34(6):494
    CrossRef
  2. 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
  3. Kruger DJ, Duan A, Juhasz D, Phaneuf CV, Sreenivasa V, Saunders CM, Heyblom AM, Sonnega PA, Day ML, Misevich SL. Cell Phone Use Latency in a Midwestern USA University Population. Journal of Technology in Behavioral Science 2017;2(1):56
    CrossRef
  4. Luhmann M. Using Big Data to study subjective well-being. Current Opinion in Behavioral Sciences 2017;18:28
    CrossRef
  5. Van Ameringen M, Turna J, Khalesi Z, Pullia K, Patterson B. There is an app for that! The current state of mobile applications (apps) for DSM-5 obsessive-compulsive disorder, posttraumatic stress disorder, anxiety and mood disorders. Depression and Anxiety 2017;34(6):526
    CrossRef
  6. Attwood S, Parke H, Larsen J, Morton KL. Using a mobile health application to reduce alcohol consumption: a mixed-methods evaluation of the drinkaware track & calculate units application. BMC Public Health 2017;17(1)
    CrossRef
  7. 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
  8. van de Ven P, O’Brien H, Henriques R, Klein M, Msetfi R, Nelson J, Rocha A, Ruwaard J, O’Sullivan D, Riper H. ULTEMAT: A mobile framework for smart ecological momentary assessments and interventions. Internet Interventions 2017;9:74
    CrossRef
  9. Mikus A, Hoogendoorn M, Rocha A, Gama J, Ruwaard J, Riper H. Predicting short term mood developments among depressed patients using adherence and ecological momentary assessment data. Internet Interventions 2017;
    CrossRef
  10. 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
  11. 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
  12. Meinlschmidt G, Lee J, Stalujanis E, Belardi A, Oh M, Jung EK, Kim H, Alfano J, Yoo S, Tegethoff M. Smartphone-Based Psychotherapeutic Micro-Interventions to Improve Mood in a Real-World Setting. Frontiers in Psychology 2016;7
    CrossRef
  13. Gao Y, Li A, Zhu T, Liu X, Liu X. How smartphone usage correlates with social anxiety and loneliness. PeerJ 2016;4:e2197
    CrossRef
  14. 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
  15. 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