AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (614.8 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Review | Open Access

From Amyotrophic Lateral Sclerosis to Neurodegenerative Diseases: A Scoping Review of Artificial Intelligence‐Powered Chatbots for Addressing Patients' and Caregivers' Information Needs

Julie Desgroseilliers1 ( )Christine Hamel1Kathy Ogundokun2Karine Latulippe3
Faculty of Education, Laval University, Quebec City, Canada
Centre for Research on Children and Families (CRCF), McGill University, Montreal, Canada
Department of Education, Educational Technology and Distance Learning, TÉLUQ University, Quebec City, Canada
Show Author Information

Abstract

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that profoundly impacts patients and caregivers. Given its rapid progression and the absence of a cure, effective disease management depends on timely and reliable information. Although artificial intelligence (AI)‐powered chatbots have emerged as promising tools to support health‐related information needs, their effectiveness in addressing the specific concerns of individuals with ALS remains unclear. This scoping review aimed to identify the specific and evolving information needs of individuals with ALS and their caregivers when using chatbot technology. A systematic search was conducted across six databases—Medline (PubMed), CINAHL, Embase, PsycINFO, ACM Digital Library, and Scopus—identifying 24 studies published between 2019 and 2024. Study selection followed a dual‐reviewer approach, and methodological quality was assessed using the Mixed Methods Appraisal Tool. Data were extracted and thematically analyzed using an inductive approach. Data were extracted from all selected articles and organized thematically using an inductive approach aligned with the objectives of the scoping review. The final themes were: (1) accessibility, (2) empowerment, (3) efficiency, (4) personalization, (5) lack of empathy and nuanced understanding, (6) linguistic and technical barriers, and (7) ethical responsibility. AI‐powered chatbots offer significant potential as complementary tools to support ALS patients and caregivers. However, their design and implementation must prioritize ethical considerations, inclusivity, and user‐centered development to ensure equitable and effective support. Future research should focus on rigorous, user‐centered evaluations to optimize AI‐powered chatbot effectiveness and mitigate risks associated with misinformation, accessibility gaps, and user trust.

Graphical Abstract

This scoping review synthesizes evidence from 24 studies (2019–2024) to examine how AI‐powered chatbots address patients' and caregivers' health information needs across diseases. Findings highlight key benefits such as accessibility, empowerment, efficiency, and personalization, alongside important limitations related to empathy, language and technical barriers, and ethical responsibility. AI‐powered chatbots show promise as complementary information tools, but their effectiveness depends on ethical, inclusive, and user‐centered design.

Electronic Supplementary Material

Download File(s)
med-4-2-125_ESM.docx (43 KB)

References

【1】
【1】
 
 
Medicine Advances
Pages 125-135

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Desgroseilliers J, Hamel C, Ogundokun K, et al. From Amyotrophic Lateral Sclerosis to Neurodegenerative Diseases: A Scoping Review of Artificial Intelligence‐Powered Chatbots for Addressing Patients' and Caregivers' Information Needs. Medicine Advances, 2026, 4(2): 125-135. https://doi.org/10.1002/med4.70065

14

Views

0

Downloads

0

Crossref

Received: 21 July 2025
Revised: 08 September 2025
Accepted: 01 December 2025
Published: 06 May 2026
© 2026 The Author(s). Tsinghua University Press.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.