Evidence map›Paper›PMID 40751486›Full record

ArticleJournal of the American Geriatrics Society2025

Development and Pilot Testing of an Artificial Intelligence and Care Coach Intervention for Cognitively Impaired Older Adults.

Cameron J Gettel, Chitra Dorai, James Galske, Tonya Chera, Edith Stern, Kate Keefe, Erica DeFrancesco, Sreeranjini Seetharam, Sandeep Nagaraj, Vaishnavi Raveendranathan and 1 more

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Cameron J GettelDepartment of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0002-6249-1023
Chitra DoraiAmicus Brain Innovations, Inc., Chappaqua, New York, USA.
James GalskeDepartment of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0002-1328-0131
Tonya CheraDepartment of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Edith SternAmicus Brain Innovations, Inc., Chappaqua, New York, USA.
Kate KeefeLiveWell Dementia Specialists, Plantsville, Connecticut, USA.
Erica DeFrancescoLiveWell Dementia Specialists, Plantsville, Connecticut, USA.
Sreeranjini SeetharamAmicus Brain Innovations, Inc., Chappaqua, New York, USA.
Sandeep NagarajAmicus Brain Innovations, Inc., Chappaqua, New York, USA.
Vaishnavi RaveendranathanAmicus Brain Innovations, Inc., Chappaqua, New York, USA.
Heidi GilLiveWell Dementia Specialists, Plantsville, Connecticut, USA.

Funding

Geriatric Emergency care Applied Research network 2.0 - Advancing Dementia Care (GEAR 2.0 ADC)R61AG069822 · NIA · YALE UNIVERSITY · PI HWANG, ULA Y, SHAH, MANISH N · 2020 to 2021
$3.0M
Alzheimer's Association ARCOM-22-878456Emergency Medicine FoundationNIA NIH HHS R61 AG069822NIA NIH HHS R61AG069822
6 · The paper itself

Abstract

backgroundCare transitions from the emergency department (ED) to community settings are particularly challenging for persons living with cognitive impairment (PLWCI) and their caregivers. The chaotic ED environment and limited post-discharge support contribute to poor outcomes and high caregiver burden. This study aimed to develop and pilot test an intervention integrating artificial intelligence (AI) technology and care coaching to enhance post-ED support among PLWCI and their caregivers.

methodsWe conducted a three-phase study using a user-centered approach. Phase 1 involved focus groups with key informants to explore care transition experiences. Phase 2 included a design thinking workshop with PLWCI, caregivers, clinicians, and technology experts to co-create the intervention. The final intervention combined a 5-part AI technology application (termed NeuViCare)-planner, task support, resource advisor, care advisor, and community hub-with access to a care coach trained in occupational therapy or nursing. In Phase 3, we pilot tested the intervention in four EDs, measuring caregiver self-efficacy (Fortinsky Caregiver Self-Efficacy scale) and burden (4-item Zarit Caregiver Burden scale).

resultsFocus groups including 15 participants highlighted major ED and transition challenges, emphasizing the need for better communication and support. Workshop participants (n = 23) identified key intervention components. In the pilot, 40 participants enrolled, with 34 completing the 7-day follow-up and 29 completing the 30-day follow-up. Engagement with NeuViCare was high, with caregiver self-efficacy improving from 52.0 at Day 0 to 65.8 at Day 30, and caregiver burden decreasing from 9.2 to 8.2.

conclusionIntegrating AI-driven support with human care coaching shows promise in improving ED care transitions for PLWCI and their caregivers. The intervention enhanced caregiver self-efficacy and modestly reduced burden, suggesting potential for broader implementation.

Indexed as

Artificial IntelligenceCaregiversCognitive DysfunctionMentoringAgedAged, 80 and overEmergency Service, HospitalFemaleFocus GroupsHumansMalePilot ProjectsSelf Efficacyartificial intelligencecare coachcare transitioncognitive impairmentdementiaemergency department

Identifiers

PMID40751486
PMCPMC13030919

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.