Self-reported medication nonadherence predicts cholesterol levels over time.

Loading...

Date

2019-03

Journal Title

Journal ISSN

Volume Title

Citation Stats

Attention Stats

Abstract

Objective

Self-report measures of medication nonadherence are frequently adapted to new clinical populations without evidence of validity. We evaluated the predictive validity of a medication nonadherence measure previously validated in patients with hypertension among patients taking cholesterol-reducing medications.

Method

This secondary analysis involves data from a randomized trial (VA HSR&D IIR 08-297) conducted at the Durham Veterans Affairs Medical Center. At baseline, 6-months, and 12-months, serum cholesterol was obtained and participants (n = 236) completed a 3-item measure of extent of nonadherence to cholesterol-reducing medications. Two cross-lagged panel models with covariates, in addition to growth curve analysis, were used to examine the predictive utility of self-reported nonadherence on concurrent and future cholesterol levels, while accounting for potential reverse-causation.

Results

Extent of nonadherence items produced reliable scores across time and fit a single-factor model (CFI = 0.99). Nonadherence, and changes in nonadherence, moderately predicted future cholesterol values, and changes in cholesterol values (7 of 9 longitudinal associations were significant at p < .05; B's ranged from 0.16 to 0.35). Evidence for reverse associations was weaker (3 of 9 longitudinal associations were significant at p < .05; B's ranged from 0.16 to 0.36).

Conclusion

Analyses support the predictive validity of this medication nonadherence measure over the competing reverse-causation hypothesis.

Department

Description

Provenance

Subjects

Humans, Cholesterol, Middle Aged, Female, Male, Medication Adherence, Self Report

Citation

Published Version (Please cite this version)

10.1016/j.jpsychores.2019.01.010

Publication Info

Blalock, Dan V, Leah L Zullig, Hayden B Bosworth, Shannon S Taylor and Corrine I Voils (2019). Self-reported medication nonadherence predicts cholesterol levels over time. Journal of psychosomatic research, 118. pp. 49–55. 10.1016/j.jpsychores.2019.01.010 Retrieved from https://hdl.handle.net/10161/29868.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Blalock

Daniel Blalock

Medical Associate Professor in the Department of Psychiatry and Behavioral Sciences

I am a research scientist and Licensed Clinical Psychologist with a background in health services research, clinical psychology, and experimental psychology. My research interests include 1) the evaluation of current integrated behavioral health settings in health care systems to optimize future implementation efforts, 2) the development of novel integrated behavioral health strategies tailored to specific populations and healthcare system needs, 3) broad processes of behavior change and self-regulation, and 4) psychometric measurement of patient reported outcomes and research methods/statistics.

 

These interests have taken the form of specific research endeavors involving: a) large nonrandomized investigations of electronic health records data, b) development and evaluation of telehealth interventions to improve self-management of mental and physical health behaviors, and c) evaluation of patient-reported outcomes through telehealth modalities and in primary care, specialty care, and higher level of care settings.

 

To date, the content domains of most of my research have involved substance use (specifically alcohol, opioids, and tobacco), health behaviors (specifically medication adherence), mental health (specifically anxiety, depression, PTSD, and eating disorders), and health services utilization.

Zullig

Leah L Zullig

Professor in Population Health Sciences

Leah L. Zullig, PhD, MPH is a health services researcher and implementation scientist whose work focuses on accelerating the adoption of evidence-based practices to improve healthcare delivery and population health. She is a Professor in the Duke University Department of Population Health Sciences and an investigator with the Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT) at the Durham Veterans Affairs Health Care System.


Dr. Zullig is a recognized leader in implementation science. She directs INTERACT, the Implementation Science Research Collaborative, which fosters interdisciplinary collaborations across Duke University and with external partners to accelerate the translation of research into practice. She also leads the Dissemination and Implementation Catalyst within Duke's Clinical and Translational Science Award (CTSA) program and serves as Co-Leader of the Duke Cancer Institute's Cancer Prevention and Control Research Program.


Dr. Zullig's research spans three interconnected areas: improving the quality and delivery of cancer care; advancing cancer survivorship and chronic disease management; and enhancing medication adherence. Across these domains, she applies implementation science methods to develop, evaluate, and scale evidence-based interventions that promote equitable, high-quality care across diverse healthcare settings. Her research is characterized by strong partnerships with healthcare systems, ensuring that findings extend beyond publication to inform clinical practice, health system transformation, and policy.


Dr. Zullig has authored more than 200 peer-reviewed publications and has established a national reputation for leading pragmatic, health system-embedded research that improves patient outcomes and advances the science of implementation.


Dr. Zullig earned her Bachelor of Science in Health Promotion, Master of Public Health in Public Health Administration, and PhD in Health Policy.

Bosworth

Hayden Barry Bosworth

Professor in Population Health Sciences

Dr. Bosworth is a health services researcher and Deputy Director of the Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT)  at the Durham VA Medical Center. He is also Vice Chair of Education and Professor of Population Health Sciences. He is also a Professor of Medicine, Psychiatry, and Nursing at Duke University Medical Center and Adjunct Professor in Health Policy and Administration at the School of Public Health at the University of North Carolina at Chapel Hill. His research interests comprise three overarching areas of research: 1) clinical research that provides knowledge for improving patients’ treatment adherence and self-management in chronic care; 2) translation research to improve access to quality of care; and 3) eliminate health care disparities. 

 

Dr. Bosworth is the recipient of an American Heart Association established investigator award, the 2013 VA Undersecretary Award for Outstanding Achievement in Health Services Research (The annual award is the highest honor for VA health services researchers), and a VA Senior Career Scientist Award. In terms of self-management, Dr. Bosworth has expertise developing interventions to improve health behaviors related to hypertension, coronary artery disease, and depression, and has been developing and implementing tailored patient interventions to reduce the burden of other chronic diseases. These trials focus on motivating individuals to initiate health behaviors and sustaining them long term and use members of the healthcare team, particularly pharmacists and nurses. He has been the Principal Investigator of over 30 trials resulting in over 400 peer reviewed publications and four books. This work has been or is being implemented in multiple arenas including Medicaid of North Carolina, private payers, The United Kingdom National Health System Direct, Kaiser Health care system, and the Veterans Affairs.

Areas of Expertise: Health Behavior, Health Services Research, Implementation Science, Health Measurement, and Health Policy


Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.