Factors associated with respite care use among veteran caregivers: a machine learning analysis.
Background and Objectives Respite care provides temporary relief to family caregivers yet remains underused, and the factors shaping its utilization among Veteran caregivers are not well understood. This evaluation examined caregiver‑ and Veteran‑specific characteristics associated with respite care...
| Publicado en: | Gerontologist Vol. 66; no. 7; pp. 1 - 14 |
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| Autores principales: | , , , , , , , , , |
| Formato: | Artículo |
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Oxford University Press / USA
Jul2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=195281427&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 195281427 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00169013 GET jtl: Gerontologist issn: 00169013 maglogo: N pubinfo: dt: Jul2026 vid: 66 iid: 7 pid: 622 pub: Oxford University Press / USA artinfo: ui: 195281427 10.1093/geront/gnag098 ppf: 1 ppct: 13 formats: tig: atl: Factors associated with respite care use among veteran caregivers: a machine learning analysis. aug: au: Harris-Gersten, Melissa Li, Zhen Patel, Pujan Lo, Jeanie Shepherd-Banigan, Megan Miller, Katherine Jacobs, Josephine Hastings, Susan N Majette, Nadya Dictus, Cassandra affil: Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Healthcare System, Veterans Health Administration, Durham, North Carolina, United StatesDepartment of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, United States Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Healthcare System, Veterans Health Administration, Durham, North Carolina, United States Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, United States Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Healthcare System, Veterans Health Administration, Durham, North Carolina, United StatesDepartment of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, United StatesMid-Atlantic MIRECC, Durham VA Health Care System, Durham, North Carolina, United StatesDuke-Margolis Health Policy Institute, Duke University, Durham, North Carolina, United States VA Partnered Evidence-based Policy Resource Center, Boston VA Health Care System, Boston, Massachusetts, United StatesHealth Policy and Management Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, United StatesDepartment of Health Policy, Stanford University School of Medicine, Stanford, California, United States Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Healthcare System, Veterans Health Administration, Durham, North Carolina, United StatesDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, United States Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Healthcare System, Veterans Health Administration, Durham, North Carolina, United StatesSchool of Nursing, Duke University, Durham, North Carolina, United States su: United States. Dept. of Veterans Affairs Health services accessibility Psychological well-being Psychology of veterans Psychology of caregivers Respite care Random forest algorithms Research funding Questionnaires Scientific observation Services for caregivers Descriptive statistics Longitudinal method Machine learning Data analysis software Caregiver attitudes sug: subj: Health services accessibility Psychological well-being Psychology of veterans Psychology of caregivers United States. Dept. of Veterans Affairs Administration of Veterans' Affairs Respite care Random forest algorithms Research funding Questionnaires Scientific observation Services for caregivers Descriptive statistics Longitudinal method Machine learning Data analysis software Caregiver attitudes keyword: Andersen's Behavioral Model Caregiver burden caregivers copyrightHolder:The Gerontological Society of America copyrightYear:2026 dementia depressive disorders frailty Health services utilization https://dx.doi.org/10.1093/geront/gnag098 inLanguage:en machine learning Predictive modeling publisher:Oxford University Press random forest respite care of patient sameAs:https://pubmed.ncbi.nlm.nih.gov/42090474/ VA health system veterans Andersen's Behavioral Model Caregiver burden caregivers copyrightHolder:The Gerontological Society of America copyrightYear:2026 dementia depressive disorders frailty Health services utilization https://dx.doi.org/10.1093/geront/gnag098 inLanguage:en machine learning Predictive modeling publisher:Oxford University Press random forest respite care of patient sameAs:https://pubmed.ncbi.nlm.nih.gov/42090474/ VA health system veterans ab: Background and Objectives Respite care provides temporary relief to family caregivers yet remains underused, and the factors shaping its utilization among Veteran caregivers are not well understood. This evaluation examined caregiver‑ and Veteran‑specific characteristics associated with respite care use within the Department of Veterans Affairs (VA) Caregiver Support Program's Program of General Caregiver Support Services (PGCSS). Research Design and Methods We analyzed survey and administrative data from 1,727 caregivers of Veterans enrolled in PGCSS who completed baseline surveys between 2018 and 2021. Caregivers were predominantly female (96%) with a mean age of 62 years; Veterans averaged 70 years. Respite use within 2 years of survey completion was identified through linked VA data. Guided by Andersen's Healthcare Utilization Model, 34 caregiver and Veteran variables were evaluated with random forest models to identify characteristics that most strongly differentiated respite users from non‑users. Results Respite care was used by 23.5% of caregivers. Use was more common among older caregivers and Veterans (predisposing factors), among caregivers reporting greater burden, depression, or financial strain and Veterans with higher frailty, functional limitation, or dementia (need factors), and among caregivers perceiving stronger communication and collaboration with the clinical team (enabling factors). Model performance was strong (testing accuracy = 0.79 with all variables; 0.77 with the top 15), and results remained consistent in a sensitivity analysis limited to caregivers of Veterans who survived the 2‑year follow‑up period. Discussion and Implications Both caregiving intensity and care‑recipient complexity characterize respite use even within a system of broad service availability. Findings provide a foundation for future hypothesis‑driven studies and inform efforts to align respite programs more closely with caregiver–Veteran needs. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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