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

JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (383) JMIR Theme Issue: COVID-19 Special Issue (2452) Anxiety and Stress Disorders (1053) Ecological Momentary Assessment (EMA) (311) Outbreak and Pandemic Preparedness and Management (1727) Infectious Diseases (non-STD/STI) (1575) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1515) Mass Media/Social Media Communication and Campaigns (461) Machine Learning (1465) mHealth for Data Collection and Research (955)

Published on in Vol 8, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30833, first published .
Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning–Based Ecological Momentary Assessment Study

Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning–Based Ecological Momentary Assessment Study

Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning–Based Ecological Momentary Assessment Study

Authors of this article:

Jihan Ryu1 Author Orcid Image ;   Emese Sükei2 Author Orcid Image ;   Agnes Norbury1 Author Orcid Image ;   Shelley H Liu1 Author Orcid Image ;   Juan José Campaña-Montes3 Author Orcid Image ;   Enrique Baca-Garcia3, 4 Author Orcid Image ;   Antonio Artés2, 3, 5 Author Orcid Image ;   M Mercedes Perez-Rodriguez1 Author Orcid Image
Article Authors Cited by (10) Tweetations (8) Metrics

Journals

  1. Sutherland Charvis J, Schulz C, Drohan M, Rafiee P, Stamates A, Yang M. A daily examination of perceived stress and coping strategies used among college students during COVID-19. Journal of American College Health 2023:1 View
  2. Rosen A, Holmes A, Balluerka N, Hidalgo M, Gorostiaga A, Gómez-Benito J, Huedo-Medina T. Is Social Media a New Type of Social Support? Social Media Use in Spain during the COVID-19 Pandemic: A Mixed Methods Study. International Journal of Environmental Research and Public Health 2022;19(7):3952 View
  3. Rezapour M, Elmshaeuser S, Vellido A. Artificial intelligence-based analytics for impacts of COVID-19 and online learning on college students’ mental health. PLOS ONE 2022;17(11):e0276767 View
  4. Mulinari S. Short-circuiting biology: Digital phenotypes, digital biomarkers, and shifting gazes in psychiatry. Big Data & Society 2023;10(1) View
  5. Chemnad K, Alshakhsi S, Almourad M, Altuwairiqi M, Phalp K, Ali R. Smartphone Usage before and during COVID-19: A Comparative Study Based on Objective Recording of Usage Data. Informatics 2022;9(4):98 View
  6. Liu H, Tao T, Chan S, Ma J, Lau A, Yeung E, Hobfoll S, Hou W. Daily routine disruptions and psychiatric symptoms amid COVID-19: a systematic review and meta-analysis of data from 0.9 million individuals in 32 countries. BMC Medicine 2024;22(1) View
  7. dos Santos M, Heckler W, Bavaresco R, Barbosa J. Machine learning applied to digital phenotyping: A systematic literature review and taxonomy. Computers in Human Behavior 2024;161:108422 View
  8. Gyorda J, Lekkas D, Jacobson N. Detecting Longitudinal Trends between Passively Collected Phone Use and Anxiety among College Students. Digital Biomarkers 2024;8(1):181 View
  9. Welch S, Bagheri K, Bethell M, Anastasio A, Tabarestani T, Bolognesi M. Evaluating the Quality and Reliability of Total Knee Arthroplasty Rehabilitation Exercises on the Social Media Platform TikTok. Arthroplasty Today 2024;30:101486 View