Identifying treatment effects of an informal caregiver education intervention to increase days in the community and decrease caregiver distress: a machine-learning secondary analysis of subgroup effects in the HI-FIVES randomized clinical trial.
Date
2020-02
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Citation Stats
Attention Stats
Abstract
Background
Informal caregivers report substantial burden and depressive symptoms which predict higher rates of patient institutionalization. While caregiver education interventions may reduce caregiver distress and decrease the use of long-term institutional care, evidence is mixed. Inconsistent findings across studies may be the result of reporting average treatment effects which do not account for how effects differ by participant characteristics. We apply a machine-learning approach to randomized clinical trial (RCT) data of the Helping Invested Family Members Improve Veteran's Experiences Study (HI-FIVES) intervention to explore how intervention effects vary by caregiver and patient characteristics.Methods
We used model-based recursive partitioning models. Caregivers of community-residing older adult US veterans with functional or cognitive impairment at a single VA Medical Center site were randomized to receive HI-FIVES (n = 118) vs. usual care (n = 123). The outcomes included cumulative days not in the community and caregiver depressive symptoms assessed at 12 months post intervention. Potential moderating characteristics were: veteran age, caregiver age, caregiver ethnicity and race, relationship satisfaction, caregiver burden, perceived financial strain, caregiver depressive symptoms, and patient risk score.Results
The effect of HI-FIVES on days not at home was moderated by caregiver burden (p < 0.001); treatment effects were higher for caregivers with a Zarit Burden Scale score ≤ 28. Caregivers with lower baseline Center for Epidemiologic Studies Depression Scale (CESD-10) scores (≤ 8) had slightly lower CESD-10 scores at follow-up (p < 0.001).Conclusions
Family caregiver education interventions may be less beneficial for highly burdened and distressed caregivers; these caregivers may require a more tailored approach that involves assessing caregiver needs and developing personalized approaches.Trial registration
ClinicalTrials.gov, ID:NCT01777490. Registered on 28 January 2013.Type
Department
Description
Provenance
Subjects
Citation
Permalink
Published Version (Please cite this version)
Publication Info
Shepherd-Banigan, Megan, Valerie A Smith, Jennifer H Lindquist, Michael Paul Cary, Katherine EM Miller, Jennifer G Chapman and Courtney H Van Houtven (2020). Identifying treatment effects of an informal caregiver education intervention to increase days in the community and decrease caregiver distress: a machine-learning secondary analysis of subgroup effects in the HI-FIVES randomized clinical trial. Trials, 21(1). p. 189. 10.1186/s13063-020-4113-x Retrieved from https://hdl.handle.net/10161/26144.
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.
Collections
Scholars@Duke
Michael Paul Cary
Dr. Cary is an Associate Professor and Elizabeth C. Clipp Term Chair of Nursing in the Duke University School of Nursing. Dually trained as a health services researcher and applied data scientist, Dr. Cary uses AI and machine learning to study health disparities related to aging and develop strategies to advance health equity and improve healthcare delivery to older adults in diverse populations. His research has been supported by the National Library of Medicine, National Institute of Nursing Research, and the Duke Clinical and Translational Science Institute. He has published more than 50 manuscripts, book chapters, and editorials and has mentored numerous students and faculty members. In 2022, he was inducted as a Fellow of the American Academy of Nursing for his significant contributions to improve health and healthcare.
Most recently, he was selected by Duke Health to be the inaugural AI Health Equity Scholar. In this health system leadership position, he leads an interdisciplinary team in identifying clinical algorithms that perpetuate racial and ethnic health and health care disparities and implementing system-wide standards for mitigating their harmful discriminatory effects on patients. These meaningful contributions are vital to addressing health disparities and promoting equitable health outcomes for all patients at Duke and beyond.
Dr. Cary received a bachelor’s degree in health services administration from James Madison University. He also earned a bachelors, masters, and doctoral degree in nursing from the University of Virginia.
Courtney Harold Van Houtven
Dr. Courtney Van Houtven is a Professor in The Department of Population Health Science, Duke University School of Medicine and Duke-Margolis Center for Health Policy. She is also a Research Career Scientist in The Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System. Dr. Van Houtven’s aging and economics research interests encompass long-term care financing, intra-household decision-making, unpaid family and friend care, and home- and community-based services. She examines how family caregiving affects health care utilization, expenditures, health and work outcomes of care recipients and caregivers. She is also interested in understanding how best to support family caregivers to optimize caregiver and care recipient outcomes.
Dr. Van Houtven is co-PI on the QUERI Program Project, “Optimizing Function and Independence”, in which her caregiver skills training program developed as an RCT in VA, now called Caregivers FIRST, has been implemented at 125 VA sites nationally. The team will evaluate how intensification of an implementation strategy changes adoption. She directs the VA-CARES Evaluation Center, which evaluates the VA’s Caregiver Support Program. She leads a mixed methods R01 study as PI from the National Institute on Aging that will assess the value of "home time" for persons living with dementia and their caregivers (RF1 AG072364).
Areas of expertise: Health Services Research and Health Economics
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.