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预防医学  2025, Vol. 37 Issue (3): 217-222    DOI: 10.19485/j.cnki.issn2096-5087.2025.03.001
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基于潜在剖面分析的慢性病住院患者服药依从性影响因素分析
王晓闪1,2, 叶丽香1,2, 陈莉1, 李敏香2, 王心语1, 蔡小霞1
1.海南医科大学国际护理学院,海南 海口 571199;
2.海南医科大学第二附属医院护理部,海南 海口 570216
Influencing factors for medication adherence among inpatients with chronic diseases based on latent profile analysis
WANG Xiaoshan1,2, YE Lixiang1,2, CHEN Li1, LI Minxiang2, WANG Xinyu1, CAI Xiaoxia1
1. School of International Nursing, Hainan Medical University, Haikou, Hainan 571199, China;
2. Department of Nursing, The Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570216, China
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摘要 目的 基于潜在剖面分析探讨慢性病住院患者服药依从性类型及影响因素,为提高慢性病患者服药依从性提供参考。方法 选择海南医科大学第二附属医院住院治疗的慢性病患者为研究对象,通过问卷调查收集人口学信息、慢性病患病和健康教育等资料;采用服药依从性量表调查服药依从性,根据该量表的8个条目得分,采用潜在剖面分析服药依从性分类;采用无序多分类logistic回归模型分析慢性病住院患者服药依从性的影响因素。结果 回收有效问卷290份,问卷有效率为97.64%。调查男性157例,占54.14%;女性133例,占45.86%。年龄MQR)为61(21)岁。慢性病住院患者服药依从性得分MQR)为4.75(4.50)分,经潜在剖面分析分为主观轻视型依从缺失、主观自信型依从波动和自省型依从良好3类,分别占38.97%、28.28%和32.76%。无序多分类logistic回归分析结果显示,相较于主观自信型依从波动患者,家庭月收入(5 000~10 000元,OR=2.981,95%CI:1.055~8.429)、慢性病共病(OR=3.478,95%CI:1.579~7.661)、近1年接受健康教育次数(≤1次,OR=0.329,95%CI:0.120~0.907;2次,OR=0.363,95%CI:0.138~0.950)、健康信息素养得分(<60分,OR=2.596,95%CI:1.209~5.573)与主观轻视型依从缺失有统计学关联(均P<0.05)。结论 慢性病住院患者主观轻视型依从缺失与家庭月收入、慢性病共病、接受健康教育次数及健康信息素养水平有关。
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王晓闪
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王心语
蔡小霞
关键词 慢性病住院患者服药依从性潜在剖面分析影响因素    
AbstractObjective To explore the types of medication adherence and their influencing factors among inpatients with chronic diseases based on latent profile analysis, so as to provide the basis for improving medication adherence among patients with chronic diseases. Methods The inpatients with chronic diseases admitted to the Second Affiliated Hospital of Hainan Medical University were selected as the study subjects. Demographic information, chronic disease status, and health education were collected through questionnaire surveys. Medication adherence was assessed using the Medication Adherence Scale and categorized based on the scores of its eight items through latent profile analysis. Factors affecting medication adherence among inpatients with chronic diseases were analyzed using a multinomial logistic regression model. Results Totally 290 valid questionnaires were recovered, with an effective recovery rate of 97.64%. There were 157 males (54.14%) and 133 females (45.86%), with a median age of 61 (interquartile range, 21) years. The median score of medication adherence was 4.75 (interquartile range, 4.50). Based on latent profile analysis, medication adherence was categorized into three types: subjective neglect with poor adherence (38.97%), subjective confidence with fluctuating adherence (28.28%), and self-reflective with good adherence (32.76%). Multinomial logistic regression analysis showed that compared to the subjective confidence with fluctuating adherence, family monthly income (5 000-10 000 yuan, OR=2.981, 95%CI: 1.055-8.429), comorbidity of chronic diseases (OR=3.478, 95%CI: 1.579-7.661), number of health education sessions received in the past year (≤1 session, OR=0.329, 95%CI: 0.120-0.907; 2 sessions, OR=0.363, 95%CI: 0.138-0.950), and health information literacy scores (<60 points, OR=2.596, 95%CI: 1.209-5.573) were statistically associated with subjective neglect with poor adherence (all P<0.05). Conclusion Subjective neglect with poor medication adherence among inpatients with chronic diseases is associated with family monthly income, comorbidity of chronic diseases, the number of health education sessions received, and health information literacy.
Key wordschronic diseases    inpatient    medication adherence    latent profile analysis    influencing factor
收稿日期: 2024-09-23      修回日期: 2025-01-09      出版日期: 2025-03-10
中图分类号:  R193  
基金资助:海南省哲学社会科学课题(HNSK(ZC)22-193)
作者简介: 王晓闪,硕士研究生在读,副主任护师,主要从事临床护理工作
通信作者: 蔡小霞,E-mail:896318445@qq.com   
引用本文:   
王晓闪, 叶丽香, 陈莉, 李敏香, 王心语, 蔡小霞. 基于潜在剖面分析的慢性病住院患者服药依从性影响因素分析[J]. 预防医学, 2025, 37(3): 217-222.
WANG Xiaoshan, YE Lixiang, CHEN Li, LI Minxiang, WANG Xinyu, CAI Xiaoxia. Influencing factors for medication adherence among inpatients with chronic diseases based on latent profile analysis. Preventive Medicine, 2025, 37(3): 217-222.
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http://www.zjyfyxzz.com/CN/10.19485/j.cnki.issn2096-5087.2025.03.001      或      http://www.zjyfyxzz.com/CN/Y2025/V37/I3/217
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