GRACE, A Hybrid Rule- and LLM-based Embodied Voice Assistant for Cognitive Stimulation in Older Adults: A Pilot Study Assessing Technical Feasibility, Technology Acceptance, and Working Alliance (Preprint)
Journal
JMIR Aging
ISSN
2561-7605
Type
working paper
Date Issued
2025-05-09
Author(s)
Abstract
Background:
The health and economic burden of Dementia has led the WHO to recognize dementia as a public health priority. Although there currently does not exist a cure for dementia, there are multiple interventions aimed at preventing the risk for dementia and improving the quality of life of people with dementia. Voice assistants, particularly those using large language models (LLM), have emerged as promising tools to deliver these interventions to older adults due to their accessible and natural interface.
Objective:
This pilot study aimed to evaluate the technical feasibility and technology acceptance of the embodied rule-based and LLM voice assistant GRACE, as well as its working alliance with healthy older adults while delivering cognitive stimulation interventions.
Methods:
A pilot study was conducted with 21 healthy German-speaking adults over the age of 60. Participants interacted with GRACE in a laboratory setting for 10–15 minutes. The interaction involved a structured cognitive stimulation session using rule-based and LLM components. Data were collected using pre- and post-interaction questionnaires and semi-structured interviews. Quantitative analysis included descriptive statistics and Wilcoxon signed-rank tests. Qualitative data were analyzed thematically.
Results:
Participants rated GRACE positively, with statistically significant scores above neutral (p < .001 for perceived ease of use, usefulness, enjoyment, and working alliance; p < .01 for perceived control and intention to continue interacting). Thematic analysis revealed that GRACE was perceived as easy to understand and unambiguous, friendly, and supportive, with intervention components viewed as enjoyable and appropriately challenging. Areas for improvement included personalization, response delays, and voice quality.
Conclusions:
The results suggest that embodied rule-based and LLM voice assistants like GRACE are feasible and well-received tools for delivering cognitive interventions to older adults. Future iterations will incorporate feedback and extend testing to individuals at risk for dementia.
The health and economic burden of Dementia has led the WHO to recognize dementia as a public health priority. Although there currently does not exist a cure for dementia, there are multiple interventions aimed at preventing the risk for dementia and improving the quality of life of people with dementia. Voice assistants, particularly those using large language models (LLM), have emerged as promising tools to deliver these interventions to older adults due to their accessible and natural interface.
Objective:
This pilot study aimed to evaluate the technical feasibility and technology acceptance of the embodied rule-based and LLM voice assistant GRACE, as well as its working alliance with healthy older adults while delivering cognitive stimulation interventions.
Methods:
A pilot study was conducted with 21 healthy German-speaking adults over the age of 60. Participants interacted with GRACE in a laboratory setting for 10–15 minutes. The interaction involved a structured cognitive stimulation session using rule-based and LLM components. Data were collected using pre- and post-interaction questionnaires and semi-structured interviews. Quantitative analysis included descriptive statistics and Wilcoxon signed-rank tests. Qualitative data were analyzed thematically.
Results:
Participants rated GRACE positively, with statistically significant scores above neutral (p < .001 for perceived ease of use, usefulness, enjoyment, and working alliance; p < .01 for perceived control and intention to continue interacting). Thematic analysis revealed that GRACE was perceived as easy to understand and unambiguous, friendly, and supportive, with intervention components viewed as enjoyable and appropriately challenging. Areas for improvement included personalization, response delays, and voice quality.
Conclusions:
The results suggest that embodied rule-based and LLM voice assistants like GRACE are feasible and well-received tools for delivering cognitive interventions to older adults. Future iterations will incorporate feedback and extend testing to individuals at risk for dementia.
Publisher
JMIR Publications Inc.