ORIGINAL RESEARCH article
Front. Neurol.
Sec. Neurorehabilitation
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1627893
The heterogeneous life space trajectories and predictors in stroke patients: a cohort study
Provisionally accepted- 1School of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- 2Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Objective: This study aimed to identify heterogeneous trajectories of life space among stroke patients and explore the predictors for different classes of life space. Methods: This prospective cohort study assessed 210 stroke patients' life space at baseline and 1, 3, 6 months post-discharge. We elucidated heterogeneous trajectories of life space by latent class growth model and explored the predictors of trajectories by multinomial logistic regression analysis. Results: Among 173 participants completing the 6-month follow-up, three distinct life space trajectories were identified: the "high-level recovery flat class" (8%), the "medium-level recovery good class" (72%), and the "low-level recovery poor class" (20%). Multinomial logistic regression, using the low-level recovery poor class as the reference, indicated that age <60, absence of limb sensory deficit, and positive environmental experiences were predictors of the medium-level recovery good class, whereas employment status and positive environmental experiences were predictors of the high-level recovery flat class. Conclusion: The three trajectories of life space indicated that the 1 month post-discharge is the most vulnerable phase for stroke patients. Age and employment status significantly influence life space trajectories. Patients in the low-level recovery poor class should receive special attention. Strategies to improve sensory deficits and environmental experiences should be developed to expand life space, promoting stroke patients' rehabilitation.
Keywords: Life space, Stroke, trajectories, predictors, latent class growth model
Received: 17 Jun 2025; Accepted: 16 Sep 2025.
Copyright: © 2025 Yang, Xie, Ge, Tang, Cheng and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Kangyao Cheng, chengkangyao@163.com
Yin Wang, wangyin1977@126.com
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