Publication Name	World Journal of Psychiatry
Manuscript ID	119455
DOI	10.5498/wjp.119455
Country	China

Category	Psychology
Manuscript Type	Retrospective Study
Article Title	Efficacy of a machine learning model integrating clinical-psychosocial factors in predicting posttraumatic bone nonunion and bone defects
Manuscript Source	Unsolicited Manuscript
All Author List	Fei-Fan Luan, Jia-Yi Chen, Yu-Zhong Zheng, Min-Hua Hu, Feng Huang and Chen-Xiao Zheng
Funding Agency and Grant Number
Corresponding Author	Chen-Xiao Zheng, PhD, Zhongshan Hospital of Traditional Chinese Medicine Affliated to Guangzhou University of Traditional Chinese Medicine, The Tenth Clinical Medical College of Guangzhou University of Traditional Chinese Medicine, No.3 Kangxin Road, West District, Zhongshan 528400, Guangdong Province, China. cuokoo1973@163.com
Key Words	Bone nonunion; Machine learning; Psychosocial factors; Risk prediction; Decision curve analysis
Core Tip	In summary, the integrated model developed in this study demonstrates favorable discriminative ability (operating characteristic curve = 0.888 in external validation) and potential clinical utility for nonunion risk prediction, although further validation is needed. Importantly, our findings highlight the significant contribution of psychosocial factors - particularly anxiety, depression, and social support - to bone healing. These results provide strong evidence for promoting the deep integration of the “bio‑psycho‑social” medical model into routine orthopedic clinical practice, thereby facilitating more individualized and holistic patient management.
Citation	Luan FF, Chen JY, Zheng YZ, Hu MH, Huang F, Zheng CX. Efficacy of a machine learning model integrating clinical-psychosocial factors in predicting posttraumatic bone nonunion and bone defects. World J Psychiatry 2026; In press DOI: https://doi.org/10.5498/wjp.119455
PDF	119455-in-press.pdf

Received	2026-04-17 10:06
Peer-Review Started	2026-04-17 10:06
First Decision by Editorial Office Director	2026-05-07 09:22
Return for Revision	2026-05-07 09:22
Revised	2026-05-22 04:03
Publication Fee Transferred
Second Decision by Editor	2026-06-15 02:42
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-06-15 06:03
Articles in Press	2026-06-15 06:03
Edit the Manuscript by Language Editor
Typeset the Manuscript

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: http://creativecommons.org/Licenses/by-nc/4.0/
Copyright	©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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