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| 药物理解与使用自我效能量表 (MUSE-S)× | 药物依从性评定量表 (MARS)× | |
|---|---|---|
| 领域 | 药理学 | 药理学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2009 | 2000 |
| 提出者≠ | Sunil Kripalani, Jill Risser, Monica E. Gatti, and Thomas A. Jacobson | Kathryn Thompson, Jayashri Kulkarni, and Anthony A. Sergejew |
| 类型 | Self-report | Self-report |
| 开创性文献≠ | Kripalani, S., Risser, J., Gatti, M. E., & Jacobson, T. A. (2009). Development and validation of a simple questionnaire to measure medication understanding. Medical Care, 47(3), 340-348. link ↗ | Thompson, K., Kulkarni, J., & Sergejew, A. A. (2000). Reliability and validity of a new Medication Adherence Rating Scale (MARS) for the psychoses. Schizophrenia Research, 42(3), 241-247. DOI ↗ |
| 别名 | MUSE-S | MARS |
| 相关 | 4 | 4 |
| 摘要≠ | The Medication Understanding and Use Self-Efficacy Scale (MUSE-S) is a brief, patient-centered self-report measure assessing both knowledge and confidence regarding medication use. Developed by Kripalani and colleagues at Emory University in 2009, the MUSE-S evaluates whether patients understand their medications (what they are for, how to take them, important side effects) and feel confident managing them in daily life. This dual focus on knowledge and self-efficacy makes the MUSE-S particularly valuable for identifying education gaps, assessing health literacy barriers to medication adherence, and evaluating outcomes of medication counseling or education interventions. | The Medication Adherence Rating Scale (MARS) is a 10-item self-report measure developed by Thompson, Kulkarni, and Sergejew in 2000 to assess medication adherence behaviors and attitudes in psychiatric populations, particularly antipsychotic medication use. Although originally validated in schizophrenia, it has been successfully applied across diverse medical conditions including hypertension, diabetes, and chronic disease management, providing a quick, sensitive assessment of actual adherence frequency and admission of problematic medication-taking behaviors. |
| ScholarGate数据集 ↗ |
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