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RESEARCH ARTICLE

Trajectories of Fear of Falling and Associated Factors among Stroke Patients

The Open Nursing Journal 19 June 2026 RESEARCH ARTICLE DOI: 10.2174/0118744346464359260614203126

Abstract

Introduction

To explore latent classes and developmental trajectories of fear of falling (FOF) within 1 to 6 months after stroke onset and to examine factors associated with latent class membership.

Methods

Through convenience sampling, 203 stroke patients receiving rehabilitation treatment at the Neurology Department in Hebei Province were recruited between May 2023 and December 2023. Data were collected at 1, 2, 3, 4, and 6 months after stroke onset using a general questionnaire and the Falls Efficacy Scale International (FES-I). Growth Mixture Modeling (GMM) was used to explore the latent classes and corresponding development trajectories of FOF. Univariate analysis and logistic regression were used to examine factors associated with latent class membership.

Results

The model fit results showed that a two-class latent-basis growth mixture model (allowing non-linear change over time) was the optimal model. The Class 1 (60.0%) was characterized by a higher initial level of FOF followed by a gradual decline over time, whereas the Class 2 (40.0%) showed a relatively lower initial level of FOF with a gradual increase over time. The logistic regression analysis indicated that education level, fall history, type of stroke, and any chronic illness were independently associated with latent class membership.

Discussion

The two distinct trajectories of FOF suggest that FOF changes dynamically among stroke patients during recovery. Patients with elementary school education or below, prior falls, hemorrhagic stroke, and three or more chronic illnesses were more likely to belong to the lower-FOF increasing group, comprising 40% of the sample.

Conclusion

These findings highlight the importance of early recognition of patients who may be more likely to follow an increasing FOF trajectory and may inform more attentive and individualized rehabilitation planning.

Keywords: Stroke, Fear of falling, Rehabilitation, Growth mixture modeling, Latent class, Associated factors.
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