# Developing, Implementing, and Evaluating a Caregiver and Elder Abuse Screening, Risk Assessment and Treatment to Improve Outcomes for Older and Vulnerable Adults with MCI/ADRD

> **NIH NIH R61** · UNIVERSITY OF TEXAS MED BR GALVESTON · 2022 · $526,064

## Abstract

ABSTRACT
Elder abuse (EA) is chronically undetected and underreported in primary care settings, especially in older and
vulnerable adults with mild cognitive impairment (MCI), such as those with traumatic brain injury and those with
Alzheimer’s Disease and Related Dementias (ADRD). Elder abuse increases risks for hospitalization and
mortality among older and vulnerable adults. To aid screening and provision of a brief educational intervention
with adults experiencing cognitive decline, the Screening, Brief Intervention, Referral to Treatment (SBIRT)
model may be an effective model to guide primary prevention of elder abuse. Following a SBIRT model, the
proposed CAPA-OV (Caregiver and Patient Abuse assessment For Older and Vulnerable populations) will
build on research from the EA and intimate partner violence (IPV) fields. The long-term goal of this project is to
establish and test 1) a valid primary care-based EA screening tool with an embedded caregiver risk
assessment and 2) a two-part effective brief intervention focused on both patients and caregivers to mitigate
EA among older and vulnerable adults with MCI/ADRD. Using primary care clinics in a racially, ethnically, and
socioeconomically diverse area of southeast Texas, specific aims during the R61 phase are to:
Aim 1: Explore dynamic risks and protective factors of EA with older and vulnerable adults with MCI/ADRD
based on qualitative interviews with adults with MCI/ADRD and caregivers and develop and validate an EA risk
assessment model using 20% Medicare claims data. Aim 2: Develop a SBIRT-type intervention, the CAPA-OV,
with an adapted caregiver risk assessment, for use with patients with MCI/ADRD and caregivers in primary
care settings. Aim 3: Pilot test the feasibility, fidelity, barriers, and effects of implementing CAPA-OV in three
primary care clinics. Based on results from the R61, minor adaption of CAPA-OV will be completed prior to
implementation across primary care settings. Specific aims during the R33 phase include: Aim 4: use a
pragmatic trial to test the hypothesis that patient-caregiver dyads randomized to receive CAPA-OV will show
reductions in exposure to EA, improvements in physical and mental health, and enhancements in quality of life,
relative to patient-caregiver dyads receiving standard of care at 6-, 12-, and 18-month follow-up. Aim 5:
Evaluate the process and outcomes of implementing CAPA-OV using mixed-methods approaches guided by
the Consolidated Framework for Implementation Research (CFIR) and the Reach, Effectiveness, Adoption,
Implementation, and Maintenance (RE-AIM) theoretical frameworks. In developing the first efficacious
asymptomatic screening and intervention in English and Spanish that improves EA detection and reduces
harms for older adults with MCI/ADRD, we will reduce the public health burden of EA. Our study innovatively
addresses both vulnerable and older adults and their caregivers, addressing major risk factors for EA and
subsequent health prob...

## Key facts

- **NIH application ID:** 10512890
- **Project number:** 1R61AG078519-01
- **Recipient organization:** UNIVERSITY OF TEXAS MED BR GALVESTON
- **Principal Investigator:** Monique Renae Pappadis
- **Activity code:** R61 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $526,064
- **Award type:** 1
- **Project period:** 2022-09-15 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10512890

## Citation

> US National Institutes of Health, RePORTER application 10512890, Developing, Implementing, and Evaluating a Caregiver and Elder Abuse Screening, Risk Assessment and Treatment to Improve Outcomes for Older and Vulnerable Adults with MCI/ADRD (1R61AG078519-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10512890. Licensed CC0.

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