手法を比較

	Drug Attitude Inventory (DAI)	自己効力感（適切な服薬管理尺度）（SEAMS）
分野	薬理学	薬理学
系統	Process / pipeline	Process / pipeline
提唱年	1983	2007
提唱者	Thomas P. Hogan, Ahmed G. Awad, and Robert Eastwood	Gbenga Ogedegbe, Antoinette Schoenthaler, and colleagues
種類	Self-report	Self-report
原典	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.	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.)
別名	DAI, DAI-10, DAI-30	SEAMS
関連	4	4
概要	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.	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.