手法を比較

	Hill-Bone Compliance Scale (HBCS)	Beliefs about Medicines Questionnaire (BMQ)
分野	薬理学	薬理学
系統	Process / pipeline	Process / pipeline
提唱年	1999	1999
提唱者	Marjorie T. Kim, Mozella N. Hill, Lisa R. Bone, and Debra M. Levine	Rob Horne, John Weinman, and Michelle Hankins
種類	Self-report	Self-report
原典	Kim, M. T., Hill, M. N., Bone, L. R., & Levine, D. M. (1999). Development and Testing of the Hill-Bone Compliance Scale. Journal of Cardiovascular Nursing, 4(1), 54-59. (Also: Hill, M. N., Bone, L. R., & Kim, M. T. (1996). Perspective on compliance research in hypertension. Journal of Clinical Hypertension, 8(1), 12-17.)	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.
別名	HBCS	BMQ
関連	4	4
概要	The Hill-Bone Compliance Scale (HBCS) is a brief, disease-specific self-report measure designed to assess medication and lifestyle adherence in hypertension management. Developed by Kim, Hill, Bone, and Levine at Johns Hopkins University in 1999, the HBCS measures three dimensions of hypertension adherence: medication-taking, dietary sodium restriction, and appointment keeping. Unlike generic adherence measures, the HBCS captures the multifaceted nature of hypertension self-management, recognizing that many hypertensive patients struggle equally with medication adherence and behavioral changes (diet, exercise, weight management, stress management). The scale has demonstrated strong reliability and validity in diverse hypertensive populations and remains widely used in hypertension research and clinical management.	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.