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...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
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| Series: | BMC Pulmonary Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12890-025-03859-8 |
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| Summary: | 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. |
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| ISSN: | 1471-2466 |