超重
心理干预
冲程(发动机)
医学
老年学
潜在类模型
比例(比率)
公共卫生
肥胖
环境卫生
护理部
物理
工程类
内科学
统计
机械工程
量子力学
数学
作者
Chenxi Zhou,Shanshan Wang,Beilei Lin,Bowen Liu,Lanlan Zhang,Yunjing Qiu,Jingfeng Chen,Haoran Wang,Zhenxiang Zhang
摘要
The primary prevention of stroke high-risk groups is contingent upon health behavior intervention, and the key to such interventions is health behavioral decision-making. The present study aims to explore the potential classification of the health behavior decision-making of high-risk stroke groups using latent profile analysis (LPA) and the key influencing factors of the LPA classes. A cross-sectional study was conducted from January to May 2023 with 264 high-risk individuals of stroke in Henan Province, China. Data were collected using the Behavioral Decision Assessment Scale of Stroke Patients, the Revised Health Promoting Lifestyle Profile-II and the Social Support Rating Scale. LPA showed that a three-profile model of health behavior decision-making best fit this study. Health behavior decision-making of stroke high-risk groups were divided into three latent classes: high-output behavior type (23.1%), influence-impervious type (60.6%), and influence-sensitive type (16.3%). Comparisons between the three LPA classes showed that living situation, per capita monthly household income, hypertension, overweight/obesity, health promoting lifestyle behavior were significantly different between the participants' latent classes of behavior decision-making. Clinical staff can develop targeted interventions according to different problems existing in the decision-making processes, and improve and implement the screening content and process among community high-risk stroke groups, which has practical significance for promoting their healthy behaviors. Patient or Public Contribution: In our study, survey questionnaires were completed by participants at high risk of stroke.
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