Self-report measures of medication adherence behavior: recommendations on optimal use

Michael J. Stirratt, Jacqueline Dunbar-Jacob, Heidi M. Crane, Jane M. Simoni, Susan Czajkowski, Marisa E. Hilliard, James E. Aikens, Christine M. Hunter, Dawn I. Velligan, Kristen Huntley, Gbenga Ogedegbe, Cynthia S. Rand, Eleanor Schron, Wendy J. Nilsen

Resultado de la investigación: Review articlerevisión exhaustiva

397 Citas (Scopus)

Resumen

Medication adherence plays an important role in optimizing the outcomes of many treatment and preventive regimens in chronic illness. Self-report is the most common method for assessing adherence behavior in research and clinical care, but there are questions about its validity and precision. The NIH Adherence Network assembled a panel of adherence research experts working across various chronic illnesses to review self-report medication adherence measures and research on their validity. Self-report medication adherence measures vary substantially in their question phrasing, recall periods, and response items. Self-reports tend to overestimate adherence behavior compared with other assessment methods and generally have high specificity but low sensitivity. Most evidence indicates that self-report adherence measures show moderate correspondence to other adherence measures and can significantly predict clinical outcomes. The quality of self-report adherence measures may be enhanced through efforts to use validated scales, assess the proper construct, improve estimation, facilitate recall, reduce social desirability bias, and employ technologic delivery. Self-report medication adherence measures can provide actionable information despite their limitations. They are preferred when speed, efficiency, and low-cost measures are required, as is often the case in clinical care.

Idioma originalEnglish (US)
Páginas (desde-hasta)470-482
Número de páginas13
PublicaciónTranslational Behavioral Medicine
Volumen5
N.º4
DOI
EstadoPublished - dic 1 2015

ASJC Scopus subject areas

  • Applied Psychology
  • Behavioral Neuroscience

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