Developmental trajectory and influencing factors of self-management behavior among stroke patients
10.3760/cma.j.cn371468-20241017-00491
- VernacularTitle:脑卒中患者自我管理行为发展轨迹及影响因素
- Author:
Lulu LI
1
;
Hui ZHANG
;
Xuan WANG
;
Yue LI
;
Yuanli GUO
;
Lina GUO
;
Qilan TANG
;
Aixia WANG
Author Information
1. 郑州大学第一附属医院神经内科，郑州 450052
- Publication Type:Journal Article
- Keywords:
Stroke;
Self-management behavior;
Developmental trajectory;
Growth mixture model;
Logistic regression model;
Influencing factor
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2025;34(3):215-222
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the developmental trajectory and influencing factors of self-management behavior among stroke patients.Methods:A total of 478 ischemic stroke patients admitted to the department of neurology of a grade-Ⅲ hospital in Henan Province from July 2023 to June 2024 were selected as the investigation objects. Baseline data of patients were collected using the general situation questionnaire, stroke knowledge questionnaire, stroke health belief scale, stroke self-management behavior scale and self-rating depression scale. The self-management behavior level of patients was assessed at discharge, 1 month, 3 months and 6 months after discharge. Mplus 7.0 software was used to conduct trajectory analysis of stroke patients' self-management behaviors, and multiple Logistic regression analysis was used to analyze the influencing factors associated with the development trajectory types of different stroke self-management behaviors.Results:The self-management behavior scores of stroke patients at discharge, 1 month, 3 months and 6 months after discharge were 206.59(167.59, 230.57), 169.59(129.73, 196.73), 149.82(120.89, 171.48), and 147.14(123.02, 181.64), respectively. Four trajectory categories were described. Category 1 was low-level pattern of initial decrease followed by stabilization, accounting for 16.95%(81/478)( P<0.001, intercept=2.701). Category 2 was low-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept =2.696). Category 3 was medium-level pattern of initial decrease followed by stabilization, accounting for 57.11%(273/478)( P<0.001, intercept =3.829). Category 4 was high-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept=4.366). The self-management behavior of stroke patients with low level of stroke knowledge, low level of health belief, aged 60 to 70 years old, residence in rural areas and middle school and below education level were more likely to belong to the low level group(all P<0.05). Patients with low depression in the low level group were more likely to be classified as low-level pattern of initial decrease followed by increase( P<0.05). Conclusion:The trajectory category of self-management behavior could be predicted by stroke knowledge level, health belief level, age, place of residence, educational background and depression. Their self-management behavior level may be improved through targeted interventions according to the characteristics of different trajectory categories.
