Evidence map›Paper›PMID 39761547›Full record

ArticleJMIR aging2025

The PDC30 Chatbot-Development of a Psychoeducational Resource on Dementia Caregiving Among Family Caregivers: Mixed Methods Acceptability Study.

Sheung-Tak Cheng, Peter H F Ng

Abstract read
In one paragraph

Article in JMIR aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. A comprehensive survey of AI agents in healthcare.Journal of biomedical informatics · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Large language model-driven agents in nursing practice: A scoping review.International journal of nursing sciences · 2025
    Review
  9. Article
  10. 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

2 authors.

Sheung-Tak ChengDepartment of Health and Physical Education, The Education University of Hong Kong, Tai Po, China (Hong Kong).ORCID 0000-0003-2923-4217
Peter H F NgDepartment of Computing, Faculty of Computer and Mathematical Sciences, Hong Kong Polytechnic University, Hung Hom, China (Hong Kong).ORCID 0000-0002-9671-896X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProviding ongoing support to the increasing number of caregivers as their needs change in the long-term course of dementia is a severe challenge to any health care system. Conversational artificial intelligence (AI) operating 24/7 may help to tackle this problem.

objectiveThis study describes the development of a generative AI chatbot-the PDC30 Chatbot-and evaluates its acceptability in a mixed methods study.

methodsThe PDC30 Chatbot was developed using the GPT-4o large language model, with a personality agent to constrain its behavior to provide advice on dementia caregiving based on the Positive Dementia Caregiving in 30 Days Guidebook-a laypeople's resource based on a validated training manual for dementia caregivers. The PDC30 Chatbot's responses to 21 common questions were compared with those of ChatGPT and another chatbot (called Chatbot-B) as standards of reference. Chatbot-B was constructed using PDC30 Chatbot's architecture but replaced the latter's knowledge base with a collection of authoritative sources, including the World Health Organization's iSupport, By Us For Us Guides, and 185 web pages or manuals by Alzheimer's Association, National Institute on Aging, and UK Alzheimer's Society. In the next phase, to assess the acceptability of the PDC30 Chatbot, 21 family caregivers used the PDC30 Chatbot for two weeks and provided ratings and comments on its acceptability.

resultsAmong the three chatbots, ChatGPT's responses tended to be repetitive and not specific enough. PDC30 Chatbot and Chatbot-B, by virtue of their design, produced highly context-sensitive advice, with the former performing slightly better when the questions conveyed significant psychological distress on the part of the caregiver. In the acceptability study, caregivers found the PDC30 Chatbot highly user-friendly, and its responses quite helpful and easy to understand. They were rather satisfied with it and would strongly recommend it to other caregivers. During the 2-week trial period, the majority used the chatbot more than once per day. Thematic analysis of their written feedback revealed three major themes: helpfulness, accessibility, and improved attitude toward AI.

conclusionsThe PDC30 Chatbot provides quality responses to caregiver questions, which are well-received by caregivers. Conversational AI is a viable approach to improve the support of caregivers.

Indexed as

CaregiversDementiaAdultAgedArtificial IntelligenceFemaleHumansMaleMiddle AgedSurveys and QuestionnairesAlzheimercaregivingchatbotconversational artificial intelligencedementiadigital healthhealth care technologylanguage modelsmedical innovationsmobile phonepsychoeducational

Identifiers

PMID39761547
PMCPMC11758934

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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.