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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jan 17, 2023
Open Peer Review Period: Jan 17, 2023 - Mar 14, 2023
Date Accepted: Aug 25, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

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

Leng M, Sun Y, Li C, Han S, Wang Z

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

J Med Internet Res 2023;25:e45788

DOI: 10.2196/45788

PMID: 37751241

PMCID: 10565620

Usability evaluation of a knowledge graph-based dementia care intelligent recommender system: A mixed-methods study

  • Minmin Leng; 
  • Yue Sun; 
  • Ce Li; 
  • Shuyu Han; 
  • Zhiwen Wang

ABSTRACT

Background:

Knowledge graph-based recommender system offers the possibility of meeting the personalized needs of people with dementia and their caregivers. However, the usability of the developed recommender system is still unknown.

Objective:

This study aimed to evaluate the usability of a knowledge graph-based dementia care intelligent recommender system.

Methods:

A mixed-methods approach was employed to conduct the usability evaluation, including the collection of quantitative and qualitative data. Participants were recruited to use the recommender system via advertisements displayed on social media. After two weeks of use, feedback was provided through the Computer System Usability Questionnaire and semi-structured interviews. Descriptive statistics were used to describe sociodemographic characteristics and questionnaire scores. Qualitative data were analyzed systematically using inductive thematic analysis.

Results:

A total of 56 caregivers were recruited. Quantitative data suggested that the recommender system was easy for caregivers to use, with a mean questionnaire score of 2.14. Qualitative data showed that caregivers generally believed that the content of the recommender system was professional, easy to understand and instructive and could meet users’ personalized needs, and they were willing to continue to use it. However, the system also has shortcomings. Functions that provide interactions between professionals and caregivers, caregiver support, and resource recommendations might be added to improve the system’s usability.

Conclusions:

The recommender system provides a solution to meet the personalized needs of people with dementia and their caregivers and has the potential to substantially improve health outcomes. The next step will be to optimize and upgrade the recommender system based on the caregivers' suggestions and evaluate the effect of the application. Clinical Trial: Not applicable.


 Citation

Please cite as:

Leng M, Sun Y, Li C, Han S, Wang Z

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

J Med Internet Res 2023;25:e45788

DOI: 10.2196/45788

PMID: 37751241

PMCID: 10565620

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