Comparer des méthodes

	Échelle d'auto-efficacité pour l'utilisation appropriée des médicaments (SEAMS)	Questionnaire sur les croyances relatives aux médicaments (BMQ)
Domaine	Pharmacologie	Pharmacologie
Famille	Process / pipeline	Process / pipeline
Année d'origine	2007	1999
Auteur d'origine	Gbenga Ogedegbe, Antoinette Schoenthaler, and colleagues	Rob Horne, John Weinman, and Michelle Hankins
Type	Self-report	Self-report
Source fondatrice	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.)	Horne, R., Weinman, J., & Hankins, M. (1999). The Beliefs about Medicines Questionnaire: The development and evaluation of a new method for assessing the cognitive representation of medication. Psychology & Health, 14(1), 1-24.
Alias	SEAMS	BMQ
Apparentées	4	4
Résumé	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.	The Beliefs about Medicines Questionnaire (BMQ) is an 18-item self-report measure developed by Horne, Weinman, and Hankins in 1999 to assess patients' cognitive beliefs about necessity of medications and concerns about potential adverse effects. It is widely used in clinical research to predict medication adherence, particularly in chronic disease management, and has demonstrated strong predictive validity across diverse populations and disease contexts.