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

  • Practice and Public Health Policies
  • Published:
Translational Behavioral Medicine

Abstract

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.

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Acknowledgments

The paper is based in part on an NIH Adherence Network meeting on “Advancing the Science of Adherence Assessment: A Working Meeting on Self-Report Measures,” sponsored by the NIH Office of Behavioral and Social Sciences (OBSSR) and held 17 October 2011. We are grateful to Shoshana Kahana for her contributions, to Janet de Moor, Martha Hare, Donna McCloskey, and Anne Trontell for their paper feedback, and to all members of the NIH Adherence Network for their support.

Source of funding

This paper was supported by the National Institutes of Health (NIH) Office of Behavioral and Social Sciences Research (OBSSR) and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) through award number U01AR057954 (Crane). Additional support was provided through National Institute of Nursing Research (NINR) grant PO1NR010949 (Dunbar-Jacob), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grant K12DK097696 (Hilliard), National Heart, Lung, and Blood Institute (NHLBI) grant K24HL111315 (Ogedegbe), and National Institute of Mental Health (NIMH) grants K24MH093243 (Simoni) and R01MH084759 (Crane). Further support (for Simoni and Crane) was provided by the University of Washington Center for AIDS Research (CFAR), an NIH-funded centers program (P30AI27757) which is collaboratively supported by NIAID, NCI, NIMH, NIDA, NICHD, NHLBI, and NIA.

Authors’ statement of conflict of interest and adherence to ethical standards

The authors declare that they have no conflict of interest. All procedures were conducted in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000.

Disclaimer

The views expressed in this article are those of the authors and should not be interpreted as the official recommendations or policy of the NIH, its constituent institutes, or other author-affiliated organizations.

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Authors and Affiliations

  1. NIH/National Institute of Mental Health Division of AIDS Research, Bethesda, MD, USA

    Michael J. Stirratt PhD

  2. School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA

    Jacqueline Dunbar-Jacob PhD

  3. Division of Infectious Diseases, University of Washington, Seattle, WA, USA

    Heidi M. Crane MD

  4. Department of Psychology, University of Washington, Seattle, WA, USA

    Jane M. Simoni PhD

  5. NIH/National Heart, Lung and Blood Institute, Bethesda, MD, USA

    Susan Czajkowski PhD

  6. Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA

    Marisa E. Hilliard PhD

  7. Department of Family Medicine, University of Michigan, Ann Arbor, MI, USA

    James E. Aikens PhD

  8. NIH/National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA

    Christine M. Hunter PhD

  9. Health Science Center, University of Texas, San Antonio, TX, USA

    Dawn I. Velligan PhD

  10. NIH/National Institute on Drug Abuse, Bethesda, MD, USA

    Kristen Huntley PhD

  11. School of Medicine, New York University, New York, NY, USA

    Gbenga Ogedegbe MD

  12. School of Medicine, Johns Hopkins University, Baltimore, MD, USA

    Cynthia S. Rand PhD

  13. NIH/National Eye Institute, Bethesda, MD, USA

    Eleanor Schron PhD

  14. National Science Foundation, Arlington, VA, USA

    Wendy J. Nilsen PhD

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  1. Michael J. Stirratt PhD
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  2. Jacqueline Dunbar-Jacob PhD
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  3. Heidi M. Crane MD
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Corresponding author

Correspondence to Michael J. Stirratt PhD.

Additional information

Implications

Practice: Routine assessment of medication adherence in clinical settings through brief, validated self-report measures can provide actionable information to medical providers about patient nonadherence.

Policy: Clinical guidelines should recommend routine assessment of medication adherence in clinical settings through validated self-report measures, and healthcare policies should support integration of this patient-reported outcome into electronic health records.

Research: The validity 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; further research to strengthen self-report adherence measures is needed.

Appendix

Appendix

Table 2 Selected Adherence Self-Report Measures in Chronic Disease Reporting Validity Data
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Stirratt, M.J., Dunbar-Jacob, J., Crane, H.M. et al. Self-report measures of medication adherence behavior: recommendations on optimal use. Behav. Med. Pract. Policy Res. 5, 470–482 (2015). https://doi.org/10.1007/s13142-015-0315-2

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