Published on in Vol 4, No 1 (2017): Jan-Mar

Using Real-Time Social Media Technologies to Monitor Levels of Perceived Stress and Emotional State in College Students: A Web-Based Questionnaire Study

Using Real-Time Social Media Technologies to Monitor Levels of Perceived Stress and Emotional State in College Students: A Web-Based Questionnaire Study

Using Real-Time Social Media Technologies to Monitor Levels of Perceived Stress and Emotional State in College Students: A Web-Based Questionnaire Study

Journals

  1. Wang W, Xu H, Wang B, Zhu E. The Mediating Effects of Learning Motivation on the Association between Perceived Stress and Positive-Deactivating Academic Emotions in Nursing Students Undergoing Skills Training. Journal of Korean Academy of Nursing 2019;49(4):495 View
  2. Young S, Garett R. Ethical Issues in Addressing Social Media Posts About Suicidal Intentions During an Online Study Among Youth: Case Study. JMIR Mental Health 2018;5(2):e33 View
  3. Day J, Freiberg K, Hayes A, Homel R. Towards Scalable, Integrative Assessment of Children’s Self-Regulatory Capabilities: New Applications of Digital Technology. Clinical Child and Family Psychology Review 2019;22(1):90 View
  4. Liu S, Chen B, Kuo A. Monitoring Physical Activity Levels Using Twitter Data: Infodemiology Study. Journal of Medical Internet Research 2019;21(6):e12394 View
  5. Hartnup B, Dong L, Eisingerich A. How an Environment of Stress and Social Risk Shapes Student Engagement With Social Media as Potential Digital Learning Platforms: Qualitative Study. JMIR Medical Education 2018;4(2):e10069 View
  6. Edo-Osagie O, De La Iglesia B, Lake I, Edeghere O. A scoping review of the use of Twitter for public health research. Computers in Biology and Medicine 2020;122:103770 View
  7. DaSilva A, Huckins J, Wang R, Wang W, Wagner D, Campbell A. Correlates of Stress in the College Environment Uncovered by the Application of Penalized Generalized Estimating Equations to Mobile Sensing Data. JMIR mHealth and uHealth 2019;7(3):e12084 View
  8. Taylor J, Pagliari C. Mining social media data: How are research sponsors and researchers addressing the ethical challenges?. Research Ethics 2018;14(2):1 View
  9. Young S, Mercer N, Weiss R, Torrone E, Aral S. Using social media as a tool to predict syphilis. Preventive Medicine 2018;109:58 View
  10. Hwang Y, Kim H, Choi H, Lee J. Exploring Abnormal Behavior Patterns of Online Users With Emotional Eating Behavior: Topic Modeling Study. Journal of Medical Internet Research 2020;22(3):e15700 View
  11. Campisi J, May J, Burch K, Larson K, Doscher J, Doherty S, Isaacson K, Sebring K, Gahan A. Anxiety-inducing Facebook behavior is associated with higher rates of upper respiratory infection in college-aged users. Computers in Human Behavior 2017;76:211 View
  12. Schmidt S, Kaess M. Fortschritte und Herausforderungen für die Analyse von Big Data in sozialen Medien im Jugendalter. Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie 2020;48(1):47 View
  13. Mohino-Herranz I, Gil-Pita R, García-Gómez J, Rosa-Zurera M, Seoane F. A Wrapper Feature Selection Algorithm: An Emotional Assessment Using Physiological Recordings from Wearable Sensors. Sensors 2020;20(1):309 View
  14. Huckins J, DaSilva A, Hedlund E, Murphy E, Rogers C, Wang W, Obuchi M, Holtzheimer P, Wagner D, Campbell A. Causal Factors of Anxiety and Depression in College Students: Longitudinal Ecological Momentary Assessment and Causal Analysis Using Peter and Clark Momentary Conditional Independence. JMIR Mental Health 2020;7(6):e16684 View
  15. van Draanen J, Tao H, Gupta S, Liu S. Geographic Differences in Cannabis Conversations on Twitter: Infodemiology Study. JMIR Public Health and Surveillance 2020;6(4):e18540 View
  16. Wang Y, Yu W, Liu S, Young S. The Relationship Between Social Media Data and Crime Rates in the United States. Social Media + Society 2019;5(1):205630511983458 View
  17. Khasawneh A, Chalil Madathil K, Zinzow H, Rosopa P, Natarajan G, Achuthan K, Narasimhan M. Factors Contributing to Adolescents’ and Young Adults’ Participation in Web-Based Challenges: Survey Study. JMIR Pediatrics and Parenting 2021;4(1):e24988 View
  18. Rouvinen H, Jokiniemi K, Sormunen M, Turunen H. Internet use and health in higher education students: a scoping review. Health Promotion International 2021;36(6):1610 View
  19. Garett R, Young S. Digital Public Health Surveillance Tools for Alcohol Use and HIV Risk Behaviors. AIDS and Behavior 2021;25(S3):333 View
  20. Timmerman J, Volpe V. Aspects of campus climate and mental health threats: The role of hypervigilance. Journal of American College Health 2023;71(3):695 View
  21. Zhu Y, Cao L, Xie J, Yu Y, Chen A, Huang F. Using social media data to assess the impact of COVID-19 on mental health in China. Psychological Medicine 2021:1 View
  22. Liu S, Perdew M, Lithopoulos A, Rhodes R. The Feasibility of Using Instagram Data to Predict Exercise Identity and Physical Activity Levels: Cross-sectional Observational Study. Journal of Medical Internet Research 2021;23(4):e20954 View
  23. Paligu F, Varol C. Browser Forensic Investigations of Instagram Utilizing IndexedDB Persistent Storage. Future Internet 2022;14(6):188 View
  24. Li L, Schiffman J, Martin E. Affect-Dynamic Signatures of Psychosis Risk Across Multiple Time Scales and Contexts. Clinical Psychological Science 2022;10(5):960 View
  25. Moawad R. Using WhatsApp During the COVID-19 Pandemic and the Emotions and Perceptions of Users. Psychology Research and Behavior Management 2022;Volume 15:2369 View
  26. Deng T, Barman-Adhikari A, Lee Y, Dewri R, Bender K. Substance use and sentiment and topical tendencies: a study using social media conversations of youth experiencing homelessness. Information Technology & People 2023;36(6):2515 View
  27. Fan M, Cai W. How does a creative learning environment foster student creativity? An examination on multiple explanatory mechanisms. Current Psychology 2022;41(7):4667 View