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

Mobile Health (mhealth) (2984) Depression and Mood Disorders; Suicide Prevention (1393) Natural Language Processing (708) mHealth for Data Collection and Research (982) Diagnostic Tools in Mental Health (249) Decision Support for Health Professionals (1211) Generative Language Models Including ChatGPT (328) mHealth for Diagnosis (63)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54617, first published .
Using Large Language Models to Detect Depression From User-Generated Diary Text Data as a Novel Approach in Digital Mental Health Screening: Instrument Validation Study

Using Large Language Models to Detect Depression From User-Generated Diary Text Data as a Novel Approach in Digital Mental Health Screening: Instrument Validation Study

Using Large Language Models to Detect Depression From User-Generated Diary Text Data as a Novel Approach in Digital Mental Health Screening: Instrument Validation Study

Authors of this article:

Daun Shin1, 2 Author Orcid Image ;   Hyoseung Kim3 Author Orcid Image ;   Seunghwan Lee3 Author Orcid Image ;   Younhee Cho2, 4 Author Orcid Image ;   Whanbo Jung2 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics

Daun Shin   1, 2 , MD, PhD ;   Hyoseung Kim   3 , BS ;   Seunghwan Lee   3 , BS ;   Younhee Cho   2, 4 , DA ;   Whanbo Jung   2 , MD

1 Department of Psychiatry, Anam Hospital, Korea University, Seoul, Republic of Korea

2 Doctorpresso, Seoul, Republic of Korea

3 VOLTWIN, Seoul, Republic of Korea

4 Department of Design, Seoul National University, Seoul, Republic of Korea

Corresponding Author:

  • Daun Shin, MD, PhD
  • Department of Psychiatry
  • Anam Hospital
  • Korea University
  • 73 Goryeodae-ro
  • Seongbuk-gu
  • Seoul, 02841
  • Republic of Korea
  • Phone: 82 1093649735
  • Fax: 82 2-920-5185
  • Email: rune1018@gmail.com