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Updated: Jul 15, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Usability Evaluation of a Knowledge Graph-Based Dementia Care Intelligent Recommender System: Mixed Methods Study.

Minmin Leng^1,2, Yue Sun², Ce Li³

¹Department of Nursing, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.

Journal of Medical Internet Research

|September 26, 2023

Summary

This study found that the dementia care intelligent recommender system (DCIRS) is usable and meets personalized needs for dementia patients and caregivers. Future updates will focus on caregiver suggestions to further enhance the system.

Keywords:

DCIRS caregivers dementia dementia care intelligent recommender system knowledge graph recommender system usability evaluation

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Last Updated: Jul 15, 2025

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Published on: June 13, 2025

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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Area of Science:

Artificial Intelligence in Healthcare
Human-Computer Interaction
Gerontology

Background:

Knowledge graph-based recommender systems show promise for personalized dementia care.
The usability of such systems for dementia patients and caregivers is not well-established.

Purpose of the Study:

To evaluate the usability of a knowledge graph-based dementia care intelligent recommender system (DCIRS).

Main Methods:

A convergent mixed methods design was employed, collecting quantitative and qualitative data from 56 caregivers.
Usability was assessed using the Computer System Usability Questionnaire and semistructured interviews after a 2-week trial.
Quantitative data were analyzed using descriptive statistics, and qualitative data underwent inductive thematic analysis.

Main Results:

The DCIRS was found to be easy to use, with a mean usability score of 2.14.
Caregivers perceived the system's content as professional, understandable, and instructive, meeting personalized needs.
Identified areas for improvement include enhanced professional-caregiver interaction and additional support/resource recommendations.

Conclusions:

The DCIRS offers a viable solution for personalized dementia care, with potential to improve health outcomes.
System optimization based on caregiver feedback is recommended for future iterations.
Further evaluation of the updated system's application impact is warranted.