[Developmental trajectories of medication adherence and predictors of latent classes in patients with ischemic stroke].

Authors

Xiao Li, Di Xie, Zhiying Shen, Keyi Zhou, Bo Li, Wanli Lin, Lina Gong, Pingping Yan

Published in

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences. Volume 51. Issue 5. Pages 881-893. May 28, 2026.

Abstract

The prevention and treatment of stroke in China remain challenging, and long-term standardized use of secondary prevention medications is of great significance. Overall medication adherence among patients with ischemic stroke is suboptimal and shows a gradual decline after discharge, indicating an urgent need for improvement. This study aims to identify the categories and predictors of developmental trajectories of medication adherence in patients with ischemic stroke, thereby providing a reference for developing precision intervention programs.
A total of 373 patients with ischemic stroke admitted to the Third Xiangya Hospital of Central South University from January to December 2024 were selected using purposive sampling. Baseline data were collected during hospitalization using a general information questionnaire, the Brief Illness Perception Questionnaire (BIPQ), the Self-efficacy for Appropriate Medication Use Scale (SEAMS), the Family Adaptability and Cohesion Scale Ⅱ-Chinese Version (FACES Ⅱ-CV), and the Connor-Davidson Resilience Scale (CD-RISC). Medication adherence was assessed at 2 weeks, 1 month, 3 months, and 6 months after discharge using the 8-item Morisky Medication Adherence Scale (MMAS-8). A latent growth mixture model (LGMM) was used to identify developmental trajectories of medication adherence in patients with ischemic stroke, and multivariate Logistic regression analysis was used to analyze predictors of different trajectory classes.
Four developmental trajectory classes of medication adherence were identified among patients with ischemic stroke: the sustained moderate-adherence group (22.8%), the low-adherence declining group (17.2%), the low-adherence improving group (26.2%), and the moderate-adherence declining group (33.8%). Multivariate Logistic regression analysis showed that, with the low-adherence declining group as the reference, each 1-point increase in SEAMS score increased the odds of being classified into the sustained moderate-adherence group, moderate-adherence declining group, and low-adherence improving group by 48.3%, 33.9%, and 36.5%, respectively (all P<0.05). Each 1-point increase in FACES Ⅱ-CV score increased these odds by 9.2%, 4.3%, and 5.6%, respectively (all P<0.05). Each 1-point increase in BIPQ score decreased these odds by 18.9%, 15.7%, and 16.3%, respectively (all P<0.05). Each 1-point increase in CD-RISC score increased the odds of being classified into the sustained moderate-adherence group and low-adherence improving group by 9.1% and 6.2%, respectively (both P<0.05). Patients aged 18-59 years were 3.537 and 4.032 times more likely than those aged ≥60 years to be classified into the sustained moderate-adherence group and low-adherence improving group, respectively (both P<0.05). Patients taking 1-5 medications were 5.405 and 3.010 times more likely than those taking >5 medications to be classified into the sustained moderate-adherence group and low-adherence improving group, respectively (both P<0.05). With the sustained moderate-adherence group as the reference, each 1-point increase in SEAMS, FACES Ⅱ-CV, and CD-RISC scores, taking 1-5 medications, and being aged 18-59 years reduced the odds of being classified into the moderate-adherence declining group by 9.7%, 4.5%, 9.1%, 77.5%, and 55.8%, respectively (all P<0.05).
The developmental trajectories of medication adherence in patients with ischemic stroke show significant population heterogeneity. Healthcare professionals should actively identify the trajectory types of medication adherence in patients with ischemic stroke and implement stratified intervention strategies based on predictive factors to reverse unfavorable adherence trends.

PMID:
42565566
Bibliographic data and abstract were imported from PubMed on 07 Aug 2026.

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