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.

dc.contributor.author

Shepherd-Banigan, Megan

dc.contributor.author

Smith, Valerie A

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Lindquist, Jennifer H

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Cary, Michael Paul

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Miller, Katherine EM

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Chapman, Jennifer G

dc.contributor.author

Van Houtven, Courtney H

dc.date.accessioned

2022-11-01T13:57:33Z

dc.date.available

2022-11-01T13:57:33Z

dc.date.issued

2020-02

dc.date.updated

2022-11-01T13:57:32Z

dc.description.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.
dc.identifier

10.1186/s13063-020-4113-x

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1745-6215

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1745-6215

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https://hdl.handle.net/10161/26144

dc.language

eng

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Springer Science and Business Media LLC

dc.relation.ispartof

Trials

dc.relation.isversionof

10.1186/s13063-020-4113-x

dc.subject

Humans

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Treatment Outcome

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Institutionalization

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Long-Term Care

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Data Interpretation, Statistical

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Follow-Up Studies

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Depression

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Stress, Psychological

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Family

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Age Factors

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Quality of Life

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Aged

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Aged, 80 and over

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Middle Aged

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Caregivers

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Veterans

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Female

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Male

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Randomized Controlled Trials as Topic

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Machine Learning

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Cognitive Dysfunction

dc.title

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.

dc.type

Journal article

duke.contributor.orcid

Shepherd-Banigan, Megan|0000-0002-4020-8936

duke.contributor.orcid

Smith, Valerie A|0000-0001-5170-9819

duke.contributor.orcid

Cary, Michael Paul|0000-0002-7966-7515

duke.contributor.orcid

Van Houtven, Courtney H|0000-0002-0783-1611

pubs.begin-page

189

pubs.issue

1

pubs.organisational-group

Duke

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School of Medicine

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School of Nursing

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Basic Science Departments

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Clinical Science Departments

pubs.organisational-group

Medicine

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Medicine, General Internal Medicine

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Institutes and Provost's Academic Units

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University Institutes and Centers

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Social Science Research Institute

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Population Health Sciences

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Duke - Margolis Center for Health Policy

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Center on Health & Society

pubs.publication-status

Published

pubs.volume

21

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