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| Škála hodnocení adherence k medikaci (MARS)× | Inventář postojů k lékům (DAI)× | |
|---|---|---|
| Obor | Farmakologie | Farmakologie |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 2000 | 1983 |
| Tvůrce≠ | Kathryn Thompson, Jayashri Kulkarni, and Anthony A. Sergejew | Thomas P. Hogan, Ahmed G. Awad, and Robert Eastwood |
| Typ | Self-report | Self-report |
| Původní zdroj≠ | 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 ↗ | Hogan, T. P., Awad, A. G., & Eastwood, R. (1983). A self-report scale predictive of drug compliance in schizophrenics: Reliability and discriminative validity. Psychological Medicine, 13(1), 177-183. DOI ↗ |
| Další názvy≠ | MARS | DAI, DAI-10, DAI-30 |
| Příbuzné | 4 | 4 |
| Shrnutí≠ | 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. | The Drug Attitude Inventory (DAI) is a brief self-report measure developed by Hogan, Awad, and Eastwood in 1983 to assess attitudes toward medication and predicted medication compliance in schizophrenia and other psychiatric conditions. The original 30-item version (DAI-30) and the widely used 10-item short form (DAI-10) capture patients' subjective experience of medication benefit, side effects, and overall willingness to take medication as a predictor of adherence. The DAI is particularly valuable in psychiatric care, where attitudes toward antipsychotic and antidepressant medications strongly predict adherence and clinical outcomes. |
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