Latent profile analysis for medication adherence in patients with chronic obstructive pulmonary disease
Abstract Objective This study examined the latent profile of medication adherence in patients with chronic obstructive pulmonary disease (COPD) and explored the influencing factors. Methods From October 2023 to January 2024, a quantitative cross-sectional study was conducted with 567 Chinese patient...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | BMC Pulmonary Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12890-025-03859-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849767053835108352 |
|---|---|
| author | Xiao-Qin Wang Yu-Lin Lu Juan Liu Ping Zhang Shu-Yu Shi Yuan-Yuan Yi Ping Wu Xue-mei Li Kai Sun Qing-Jie Chen |
| author_facet | Xiao-Qin Wang Yu-Lin Lu Juan Liu Ping Zhang Shu-Yu Shi Yuan-Yuan Yi Ping Wu Xue-mei Li Kai Sun Qing-Jie Chen |
| author_sort | Xiao-Qin Wang |
| collection | DOAJ |
| description | Abstract Objective This study examined the latent profile of medication adherence in patients with chronic obstructive pulmonary disease (COPD) and explored the influencing factors. Methods From October 2023 to January 2024, a quantitative cross-sectional study was conducted with 567 Chinese patients with COPD from 6 tertiary hospitals in Yunnan Province, Sichuan Province, Hubei Province, Shanghai and Chongqing, China, using demographic information and the medication compliance scale for COPD patients. Latent profile analyses were performed using Mplus 8.3 software. Pearson’s chi-square test and logistic regression analysis were performed with SPSS 26.0 software. Results Two profiles of medication adherence were identified on the basis of patients’ responses to the medication compliance scale for COPD:“healthcare provider-supervised (n = 315,55.56%)” and “self-compliant (n = 252,44.44%)”. The medication adherence score for “healthcare provider-supervised” patients (47.60 ± 8.17) was lower than the score for “self-compliant” patients (50.36 ± 8.71) with a significant difference between the two groups (P < 0.001). Multinational logistic regression analysis indicated that education level, monthly income and place of residence significantly predicted profile membership. Conclusion Our results show that medication adherence in patients with COPD can be classified into two unique profiles. Monthly income, education level and place of residence significantly predicted profile membership. Healthcare workers should conduct scientific and comprehensive evaluations of patients’ medication adherence and influencing factors, strengthen health education, and provide family support to improve medication compliance and ensure treatment effectiveness. |
| format | Article |
| id | doaj-art-4617a3dcc23c4c5abf8b7287d85adf79 |
| institution | DOAJ |
| issn | 1471-2466 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pulmonary Medicine |
| spelling | doaj-art-4617a3dcc23c4c5abf8b7287d85adf792025-08-20T03:04:21ZengBMCBMC Pulmonary Medicine1471-24662025-07-012511910.1186/s12890-025-03859-8Latent profile analysis for medication adherence in patients with chronic obstructive pulmonary diseaseXiao-Qin Wang0Yu-Lin Lu1Juan Liu2Ping Zhang3Shu-Yu Shi4Yuan-Yuan Yi5Ping Wu6Xue-mei Li7Kai Sun8Qing-Jie Chen9Department of Pulmonary and Critical Care Medicine, Chongqing University Three Gorges HospitalSchool of Nursing, Kunming Medical UniversityDepartment of Pulmonary and Critical Care Medicine, Chongqing University Three Gorges HospitalDepartment of Pulmonary and Critical Care Medicine, Chongqing University Three Gorges HospitalLinfen Central HospitalDepartment of Pulmonary and Critical Care Medicine, Chongqing University Three Gorges HospitalDepartment of Pulmonary and Critical Care Medicine, Chongqing University Three Gorges HospitalDepartment of Pulmonary and Critical Care Medicine, Chongqing University Three Gorges HospitalDepartment of Pulmonary and Critical Care Medicine, Chongqing University Three Gorges HospitalDepartment of Pharmacy, Ruikang Hospital affiliated to Guangxi University of Traditional Chinese MedicineAbstract Objective This study examined the latent profile of medication adherence in patients with chronic obstructive pulmonary disease (COPD) and explored the influencing factors. Methods From October 2023 to January 2024, a quantitative cross-sectional study was conducted with 567 Chinese patients with COPD from 6 tertiary hospitals in Yunnan Province, Sichuan Province, Hubei Province, Shanghai and Chongqing, China, using demographic information and the medication compliance scale for COPD patients. Latent profile analyses were performed using Mplus 8.3 software. Pearson’s chi-square test and logistic regression analysis were performed with SPSS 26.0 software. Results Two profiles of medication adherence were identified on the basis of patients’ responses to the medication compliance scale for COPD:“healthcare provider-supervised (n = 315,55.56%)” and “self-compliant (n = 252,44.44%)”. The medication adherence score for “healthcare provider-supervised” patients (47.60 ± 8.17) was lower than the score for “self-compliant” patients (50.36 ± 8.71) with a significant difference between the two groups (P < 0.001). Multinational logistic regression analysis indicated that education level, monthly income and place of residence significantly predicted profile membership. Conclusion Our results show that medication adherence in patients with COPD can be classified into two unique profiles. Monthly income, education level and place of residence significantly predicted profile membership. Healthcare workers should conduct scientific and comprehensive evaluations of patients’ medication adherence and influencing factors, strengthen health education, and provide family support to improve medication compliance and ensure treatment effectiveness.https://doi.org/10.1186/s12890-025-03859-8Chronic obstructive pulmonary diseaseLatent profile analysisMedication adherenceInfluencing factors |
| spellingShingle | Xiao-Qin Wang Yu-Lin Lu Juan Liu Ping Zhang Shu-Yu Shi Yuan-Yuan Yi Ping Wu Xue-mei Li Kai Sun Qing-Jie Chen Latent profile analysis for medication adherence in patients with chronic obstructive pulmonary disease BMC Pulmonary Medicine Chronic obstructive pulmonary disease Latent profile analysis Medication adherence Influencing factors |
| title | Latent profile analysis for medication adherence in patients with chronic obstructive pulmonary disease |
| title_full | Latent profile analysis for medication adherence in patients with chronic obstructive pulmonary disease |
| title_fullStr | Latent profile analysis for medication adherence in patients with chronic obstructive pulmonary disease |
| title_full_unstemmed | Latent profile analysis for medication adherence in patients with chronic obstructive pulmonary disease |
| title_short | Latent profile analysis for medication adherence in patients with chronic obstructive pulmonary disease |
| title_sort | latent profile analysis for medication adherence in patients with chronic obstructive pulmonary disease |
| topic | Chronic obstructive pulmonary disease Latent profile analysis Medication adherence Influencing factors |
| url | https://doi.org/10.1186/s12890-025-03859-8 |
| work_keys_str_mv | AT xiaoqinwang latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT yulinlu latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT juanliu latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT pingzhang latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT shuyushi latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT yuanyuanyi latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT pingwu latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT xuemeili latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT kaisun latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease AT qingjiechen latentprofileanalysisformedicationadherenceinpatientswithchronicobstructivepulmonarydisease |