Published on in Vol 7, No 9 (2019): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14657, first published .
Response Time as an Implicit Self-Schema Indicator for Depression Among Undergraduate Students: Preliminary Findings From a Mobile App–Based Depression Assessment

Response Time as an Implicit Self-Schema Indicator for Depression Among Undergraduate Students: Preliminary Findings From a Mobile App–Based Depression Assessment

Response Time as an Implicit Self-Schema Indicator for Depression Among Undergraduate Students: Preliminary Findings From a Mobile App–Based Depression Assessment

Journals

  1. Kim B, Kwon K, Hwang S, Ryoo H, Chung U, Lee S, Lee J, Park H, Shin J, Bae S. Psychological Effects of COVID-19 Patient Management Experience among Paramedics and Emergency Medical Technicians: A Nationwide Survey in Korea. Infection & Chemotherapy 2022;54(2):316 View
  2. Choudhury A, Kuehn A, Shamszare H, Shahsavar Y. Analysis of Mobile App-Based Mental Health Solutions for College Students: A Rapid Review. Healthcare 2023;11(2):272 View
  3. Leong Q, Sridhar S, Blasiak A, Tadeo X, Yeo G, Remus A, Ho D. Characteristics of Mobile Health Platforms for Depression and Anxiety: Content Analysis Through a Systematic Review of the Literature and Systematic Search of Two App Stores. Journal of Medical Internet Research 2022;24(2):e27388 View
  4. Moulaei K, Bahaadinbeigy K, Mashoof E, Dinari F. Design and development of a mobile-based self-care application for patients with depression and anxiety disorders. BMC Medical Informatics and Decision Making 2023;23(1) View
  5. Bera S, Bhattacharya S. Exploring the importance of mobile app attributes based on consumers' voices using structured and unstructured data. IIM Ranchi Journal of Management Studies 2024;3(1):4 View
  6. Su Z, Liu R, Zhou K, Wei X, Wang N, Lin Z, Xie Y, Wang J, Wang F, Zhang S, Zhang X. Exploring the relationship between response time sequence in scale answering process and severity of insomnia: A machine learning approach. Heliyon 2024;10(13):e33485 View