Copyright: ©Author(s) 2026. 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.
World J Psychiatry. Nov 19, 2026; 16(11): 122686
Published online Nov 19, 2026. doi: 10.5498/wjp.122686
Published online Nov 19, 2026. doi: 10.5498/wjp.122686
Development and validation of a risk assessment model for fear of falling in elderly stroke patients
Yi-Mei Zhao, Department of Hepatobiliary Surgery, Hejiang People’s Hospital, Luzhou 646200, Sichuan Province, China
Yi-Mei Zhao, School of Nursing, Southwest Medical University, Luzhou 646000, Sichuan Province, China
Xue-Mei Sun, Department of Neurology and Department of Geriatrics, Hejiang People’s Hospital, Luzhou 646200, Sichuan Province, China
Jing Huang, Department of Neurology and Department of Endocrinology, Luxian People’s Hospital, Luzhou 646100, Sichuan Province, China
Xian-Rong Li, Department of General Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China
Co-first authors: Yi-Mei Zhao and Xue-Mei Sun.
Author contributions: Li XR designed the research; Zhao YM performed the research; Sun XM and Huang J collected the data; Zhao YM and Sun XM analyzed the data; Zhao YM wrote the paper; Sun XM and Huang J reviewed and revised the paper. Zhao YM and Sun XM contributed equally to this work as co-first authors.
AI contribution statement: No AI tools were used in the preparation of this manuscript.
Institutional review board statement: The Hejiang People’s Hospital Ethics Committee approved the study (Ethics No. 202536). Every procedure was carried out in compliance with the Declaration of Helsinki’s ethical standards.
Informed consent statement: This study was a retrospective observational study based on existing medical records. The study protocol was approved by the Ethics Committee of Hejiang People’s Hospital (Ethics No. 202536). Due to the retrospective design and the anonymization of all patient data, the requirement for written informed consent was waived by the institutional review board. No additional patient contact was required, and all procedures were conducted in accordance with the ethical standards of the Declaration of Helsinki.
Conflict-of-interest statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: Technical appendix, statistical code, and dataset are available from the corresponding author at lx18982475619@163.com upon reasonable request. Informed consent was waived due to the retrospective nature of the study, and the presented data are anonymized to minimize the risk of identification.
Corresponding author: Xian-Rong Li, Department of General Surgery, The Affiliated Hospital of Southwest Medical University, No. 25 Taiping Street, Jiangyang District, Luzhou 646000, Sichuan Province, China. lx18982475619@163.com
Received: April 27, 2026
Revised: June 11, 2026
Accepted: October 8, 2026
Published online: November 19, 2026
Processing time: 187 Days and 20.4 Hours
Revised: June 11, 2026
Accepted: October 8, 2026
Published online: November 19, 2026
Processing time: 187 Days and 20.4 Hours
Core Tip
Core Tip: This cross-sectional study constructed and validated a risk assessment nomogram for fear of falling in elderly stroke patients based on seven readily available clinical variables including history of falls, walking aid use, Fall Risk Questionnaire score, National Institutes of Health Stroke Scale score, Barthel Index, Five-Times Sit-to-Stand Test, and Four-Stage Balance Test. The model demonstrated good discrimination ability with a training area under the curve (AUC) of 0.880 and a validation AUC of 0.889, and a 10-fold cross-validated AUC of 0.848 ± 0.077. It provides a practical tool for early identification of high-risk individuals.