Σύγκριση μεθόδων

	Κλίμακα Αξιολόγησης Συμμόρφωσης στη Φαρμακευτική Αγωγή (MARS)	Κλίμακα Αυτο-αποτελεσματικότητας για την Κατάλληλη Χρήση Φαρμάκων (SEAMS)
Πεδίο	Φαρμακολογία	Φαρμακολογία
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	2000	2007
Δημιουργός	Kathryn Thompson, Jayashri Kulkarni, and Anthony A. Sergejew	Gbenga Ogedegbe, Antoinette Schoenthaler, and colleagues
Τύπος	Self-report	Self-report
Θεμελιώδης πηγή	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.	Ogedegbe, G., Schoenthaler, A., & Richardson, T. (2007). An Exploration of Contextual Factors and Antihypertensive Medication Adherence in Hypertensive African Americans. American Journal of Health-System Pharmacy, 64(23), 2510-2516. (SEAMS adapted from original research on self-efficacy in medication adherence.)
Εναλλακτικές ονομασίες	MARS	SEAMS
Συναφείς	4	4
Σύνοψη	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 Self-Efficacy for Appropriate Medication Use Scale (SEAMS) is a brief self-report measure designed to assess patients' confidence in their ability to manage medications appropriately across diverse contexts and challenges. Grounded in Bandura's self-efficacy theory, the SEAMS evaluates patients' perceived capacity to adhere to medication regimens despite potential barriers—forgetfulness, side effects, cost constraints, complexity, or changes in routine. The scale has demonstrated strong predictive validity for medication adherence and clinical outcomes in hypertension, diabetes, asthma, and other chronic diseases, making it valuable for identifying patients with low medication management confidence who need additional support.