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Articles Published Processes
8/24/2026 6:01:19 AM | Browse: 0 | Download: 0
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Received |
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2026-01-26 06:30 |
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Peer-Review Started |
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2026-01-26 06:32 |
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First Decision by Editorial Office Director |
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2026-02-10 09:16 |
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Return for Revision |
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2026-02-10 09:16 |
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Revised |
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2026-03-05 22:56 |
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Publication Fee Transferred |
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2026-03-25 19:04 |
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Second Decision by Editor |
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2026-06-29 02:21 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-06-29 03:44 |
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Articles in Press |
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2026-06-29 03:44 |
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Edit the Manuscript by Language Editor |
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2026-07-06 00:35 |
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Typeset the Manuscript |
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2026-08-13 03:09 |
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Publish the Manuscript Online |
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2026-08-24 06:01 |
| ISSN |
2220-3206 (online) |
| Open Access |
Open-Access: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Psychiatry |
| Manuscript Type |
Observational Study |
| Article Title |
Gamified video-based affective computing framework for adolescent depression screening
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Qi-Zhou Li, Li-Yuan-Ke Wang, Ming-Hao Wang, Jing-Yun Li, Xin-Xi Chen, Wei Fang, Zi-Xu Wang, Pei-Dong Chen, Qing-Shu Bai, Pei Sun, Xi-Wang Fan, Rui Zhong and Hua Shi |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Hua Shi, Department of Mental Health and Health Promotion, Chinese PLA Center for Disease Control and Prevention, No. 20 Dongjie Street, Fengtai District, Beijing 100071, China. placdc@139.com |
| Key Words |
Depressive disorder; Facial expression; Machine learning; Affective computing |
| Core Tip |
This study introduces a gamified, video-based affective computing approach for adolescent depression screening that captures spontaneous behavioural cues during an interactive game task. By extracting facial action units, gaze behaviour, head pose, and valence-arousal features from short video recordings recorded within the game, we trained a machine learning classifier that reliably distinguished depressed adolescents from healthy controls with strong external generalization. The findings demonstrate that visual behavioural signals alone can support accurate, low-cost, and non-invasive depression screening, highlighting the potential of gamified paradigms for scalable mental health screening in addition to traditional clinical interviews. |
| Publish Date |
2026-08-24 06:01 |
| Citation |
Li QZ, Wang LYK, Wang MH, Li JY, Chen XX, Fang W, Wang ZX, Chen PD, Bai QS, Sun P, Fan XW, Zhong R, Shi H. Gamified video-based affective computing framework for adolescent depression screening. World J Psychiatry 2026; 16(9): 119308
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| URL |
https://www.wjgnet.com/2220-3206/full/v16/i9/119308.htm |
| DOI |
https://doi.org/10.5498/wjp.119308 |
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