Ye Zhongshu,Teng Yongyong,Quan Jingju,Sun Yajun,Huang Jiaju,Wu Yixuan,Han Changlin,Zhang Guangchuan,Study on medication adherence factors among patients with severe mental disorders in Zhuhai city based on XGBoost model[J].SICHUAN MENTAL HEALTH,2026,39(1):36-43

Study on medication adherence factors among patients with severe mental disorders in Zhuhai city based on XGBoost model

DOI：10.11886/scjsws20251029003

English keywords:Severe mental disorders Medication adherence Influencing factors XGBoost model

Fund projects: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）

Author Name	Affiliation	Postcode
Ye Zhongshu	1The Third People's Hospital of Zhuhai, Zhuhai 519000, China 2Zhuhai Engineering Technology Research Center of Occupational and Mental Health, Zhuhai 519000, China	519000
Teng Yongyong	1The Third People's Hospital of Zhuhai, Zhuhai 519000, China 2Zhuhai Engineering Technology Research Center of Occupational and Mental Health, Zhuhai 519000, China	519000
Quan Jingju	1The Third People's Hospital of Zhuhai, Zhuhai 519000, China 2Zhuhai Engineering Technology Research Center of Occupational and Mental Health, Zhuhai 519000, China	519000
Sun Yajun	1The Third People's Hospital of Zhuhai, Zhuhai 519000, China 2Zhuhai Engineering Technology Research Center of Occupational and Mental Health, Zhuhai 519000, China	519000
Huang Jiaju	1The Third People's Hospital of Zhuhai, Zhuhai 519000, China 2Zhuhai Engineering Technology Research Center of Occupational and Mental Health, Zhuhai 519000, China	519000
Wu Yixuan	1The Third People's Hospital of Zhuhai, Zhuhai 519000, China 2Zhuhai Engineering Technology Research Center of Occupational and Mental Health, Zhuhai 519000, China	519000
Han Changlin	1The Third People's Hospital of Zhuhai, Zhuhai 519000, China 2Zhuhai Engineering Technology Research Center of Occupational and Mental Health, Zhuhai 519000, China	519000
Zhang Guangchuan^*	1The Third People's Hospital of Zhuhai, Zhuhai 519000, China 2Zhuhai Engineering Technology Research Center of Occupational and Mental Health, Zhuhai 519000, China	519000

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English 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. ［Funded by Zhuhai Medical Research Project （number， 2220009000281）］

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