Trajectories and predictors of self-care from pre-discharge to 12 months after discharge in people with spinal cord injury: a longitudinal study using growth mixture modeling

Front Neurosci. 2026 Jun 9;20:1817190. doi: 10.3389/fnins.2026.1817190. eCollection 2026.

ABSTRACT

INTRODUCTION: Self-care is essential for preventing secondary complications and supporting community reintegration after spinal cord injury (SCI). However, evidence is limited on how self-care changes over time after discharge and whether distinct subgroups exhibit different trajectories.

METHODS: Using convenience sampling, 220 patients with SCI were recruited from a tertiary hospital in northern China between August 2023 and December 2024. Self-care was measured with the Self-Care in Spinal Cord Injuries Inventory (SC-SCII) at pre-discharge baseline and at 1, 3, 6, and 12 months after discharge. Baseline mental health literacy and perceived social support were assessed using the Multicomponent Mental Health Literacy Scale (MMHL) and the Perceived Social Support Scale (PSSS). Repeated-measures ANOVA was used to describe the population-average time trend, and growth mixture modeling (GMM) was used as the primary person-centered analysis to identify latent trajectory classes. Multinomial logistic regression examined predictors of class membership.

RESULTS: A total of 209 patients completed all assessments (attrition rate: 5.0%). Mean SC-SCII scores peaked at 1 month post-discharge and then declined gradually over 12 months (F = 25.965, p < 0.001). GMM identified three distinct self-care trajectories: low-level decreasing (31.1%), moderate-level stable (39.7%), and high-level increasing (29.2%), with high classification accuracy (entropy = 0.965). Sex, educational level, mental health literacy, and perceived social support were associated with trajectory membership.

CONCLUSION: Self-care trajectories after SCI are heterogeneous, and early post-discharge improvements may be transient for many individuals. The identified trajectories provide preliminary evidence for developing future prediction tools and trajectory-informed transitional nursing interventions.

PMID:42344283 | PMC:PMC13286920 | DOI:10.3389/fnins.2026.1817190