四川精神卫生2026，Vol.39Issue(1)：36-43,8.DOI:10.11886/scjsws20251029003
基于XGBoost模型的珠海市严重精神障碍患者服药依从性影响因素研究
Study on medication adherence factors among patients with severe mental disorders in Zhuhai city based on XGBoost model
摘要
Abstract
Background Low medication compliance among patients with severe mental disorders increases the disease burden on both the patients'families and the society.Medication adherence is influenced by numerous factors.Traditional methods such as Logistic regression struggle to quantify the importance of these factors.By introducing Extreme Gradient Boosting(XGBoost)combined with Shapley Additive Explanations(SHAP),enables the quantification of the relative contribution weights of each factor,providing support for identifying the core influencing factors.Objective To explore the influencing factors of medication adherence among patients with severe mental disorders in Zhuhai,aiming to provide references for optimizing patient management strategies.Methods Extract the data of patients with severe mental disorders who were registered on the mental health system platform in Zhuhai City from January 1,2023 to March 31,2025.A total of 9 329 patients were finally included for analysis.Influencing factors were screened using univariate analysis and multivariate logistic regression analysis,and an XGBoost model combined with the SHAP algorithm was constructed to quantify the importance of each influencing factor.Results Among 9 329 patients,8 446 demonstrated medication adherence,yielding an adherence rate of 90.53%.Multivariable analysis identified several risk factors significantly associated with medication non-adherence,being unmarried(OR=1.237,95%CI:1.019-1.502)or divorced(OR=1.389,95%CI:1.038-1.832),a diagnosis of mental retardation with psychiatric disorders(OR=3.025,95%CI:2.402-3.796)or paranoid psychosis(OR=5.117,95%CI:3.086-8.299),a disease duration of 2-4 years(OR=1.355,95%CI:1.085-1.696),4-6 years(OR=2.143,95%CI:1.671-2.747),or>6 years(OR=1.681,95%CI:1.365-2.079),lack of guardian subsidies(OR=1.412,95%CI:1.099-1.801),absence of a disability certificate(OR=1.900,95%CI:1.588-2.282),not being enrolled in care and support groups(OR=1.384,95%CI:1.183-1.617)or community services(OR=1.313,95%CI:1.042-1.645),and not cohabiting with a guardian(OR=1.257,95%CI:1.048-1.501).Conversely,the enrollment in special outpatient disease programs(OR=0.716,95%CI:0.609-0.842)and a family history of mental illness(OR=0.713,95%CI:0.503-0.982)were identified as protective factors.The XGBoost model exhibited robust predictive performance,with a sensitivity of 0.433,specificity of 0.944,accuracy of 0.891,Area Under the Curve(AUC)of 0.837,and F1 value of 0.449.Feature importance ranking indicated that the top three factors were disease duration,diagnosis,and the acquisition of disability certificates.Conclusion Policy-based support(acquisition of disability certificates,special outpatient disease enrollment)and clinical disease characteristics(disease duration,diagnosis type)are key factors affecting medication adherence among patients with severe mental disorders in Zhuhai City.关键词
严重精神障碍/服药依从性/影响因素/XGBoost模型Key words
Severe mental disorders/Medication adherence/Influencing factors/XGBoost model分类
医药卫生引用本文复制引用
叶仲书,滕勇勇,权京菊,孙亚军,黄家驹,吴逸璇,韩昌霖,张广川..基于XGBoost模型的珠海市严重精神障碍患者服药依从性影响因素研究[J].四川精神卫生,2026,39(1):36-43,8.基金项目
珠海市医学科研项目(项目名称:珠海市严重精神障碍患者不规律服药相关因素分析,项目编号:2220009000281) Funded by Zhuhai Medical Research Project(number,2220009000281) （项目名称:珠海市严重精神障碍患者不规律服药相关因素分析,项目编号:2220009000281）
