Evidence map›Paper›PMID 32955452›Full record

ArticleJournal of medical Internet research2020

A Personalized Voice-Based Diet Assistant for Caregivers of Alzheimer Disease and Related Dementias: System Development and Validation.

Juan Li, Bikesh Maharjan, Bo Xie, Cui Tao

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
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

13 citing papers in PubMed, 60 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Frontiers in dementia · 2024
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  6. Article
  7. Article
  8. Article
  9. Informal Dementia Caregivers: Current Technology Use and Acceptance of Technology in Care.International journal of environmental research and public health · 2021
    Article
  10. Virtual Home Assistant Use and Perceptions of Usefulness by Older Adults and Support Person Dyads.International journal of environmental research and public health · 2021
    Article
  11. Article
  12. Voice Assistants to Deliver Cognitive Stimulation Therapy for Persons Living with Dementia.Extended abstracts on Human factors in computing systems. CHI Conference
    Article
  13. Article
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

4 authors at 3 institutions in 1 country.

Juan LiNorth Dakota State University, Fargo, ND, United States.ORCID 0000-0002-7668-5996
Bikesh MaharjanNorth Dakota State University, Fargo, ND, United States.ORCID 0000-0002-7284-1808
Bo XieUniversity of Texas, Austin, TX, United States.ORCID 0000-0002-6016-6008
Cui TaoUniversity of Texas Health Science Center at Houston, Houston, TX, United States.ORCID 0000-0002-4267-1924
North Dakota State University · USThe University of Texas at Austin · USThe University of Texas Health Science Center at Houston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe world's aging population is increasing, with an expected increase in the prevalence of Alzheimer disease and related dementias (ADRD). Proper nutrition and good eating behavior show promise for preventing and slowing the progression of ADRD and consequently improving patients with ADRD's health status and quality of life. Most ADRD care is provided by informal caregivers, so assisting caregivers to manage patients with ADRD's diet is important.

objectiveThis study aims to design, develop, and test an artificial intelligence-powered voice assistant to help informal caregivers manage the daily diet of patients with ADRD and learn food and nutrition-related knowledge.

methodsThe voice assistant is being implemented in several steps: construction of a comprehensive knowledge base with ontologies that define ADRD diet care and user profiles, and is extended with external knowledge graphs; management of conversation between users and the voice assistant; personalized ADRD diet services provided through a semantics-based knowledge graph search and reasoning engine; and system evaluation in use cases with additional qualitative evaluations.

resultsA prototype voice assistant was evaluated in the lab using various use cases. Preliminary qualitative test results demonstrate reasonable rates of dialogue success and recommendation correctness.

conclusionsThe voice assistant provides a natural, interactive interface for users, and it does not require the user to have a technical background, which may facilitate senior caregivers' use in their daily care tasks. This study suggests the feasibility of using the intelligent voice assistant to help caregivers manage patients with ADRD's diet.

Indexed as

AgedAlzheimer DiseaseCaregiversDementiaDietDiet TherapyFemaleHumansMaleQuality of LifeReproducibility of ResultsVoice RecognitionAlzheimer diseasedementiadietknowledgeontologyvoice assistant

Identifiers

PMID32955452
PMCPMC7536606
OpenAlexW3044764387

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.