Publication Name	World Journal of Psychiatry
Manuscript ID	76033
Country	China

Category	Public, Environmental & Occupational Health
Manuscript Type	Review
Article Title	Influencing factors, prediction and prevention of depression in college students: A literature review
Manuscript Source	Invited Manuscript
All Author List	Xin-Qiao Liu, Yu-Xin Guo, Wen-Jie Zhang and Wen-Juan Gao
Funding Agency and Grant Number
Corresponding Author	Xin-Qiao Liu, PhD, Associate Professor, School of Education, Tianjin University, No. 135 Tongyan Road, Jinnan District, Tianjin 300350, China. xinqiaoliu@pku.edu.cn
Key Words	Depression; Prediction; Prevention; Artificial intelligence; Big data; Machine learning
Core Tip	This study reviewed the extant literature by identifying nonpathological factors related to college students' depression, investigating the methods of predicting depression, and exploring nonpharmaceutical interventions for depression among college students. The influencing factors can be categorized into students’ demographic characteristics, college experience, lifestyle, and social support. For the prediction of depression, methods such as machine algorithms and artificial intelligence have been employed together with the traditional psychological scales. This study summarizes general and professional measures that can be taken for the prevention and treatment of college students' depression.
Citation	Liu XQ, Guo YX, Zhang WJ, Gao WJ. Influencing factors, prediction and prevention of depression in college students: A literature review. World J Psychiatry 2022; 12(7): 860-873

Received	2022-02-27 04:58
Peer-Review Started	2022-02-27 04:59
To Make the First Decision
Return for Revision	2022-04-18 07:03
Revised	2022-04-29 15:31
Second Decision	2022-06-20 03:01
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2022-06-27 00:06
Articles in Press	2022-06-27 00:06
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2022-06-29 03:14

ISSN	2220-3206 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Copyright	© The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
Permissions	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher	Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website	http://www.wjgnet.com