Cited by 74Artificial Intelligence in Healthcare and EducationMobile Health and mHealth ApplicationsAI in Service Interactions

The Use of Chatbots in Oncological Care: A Narrative Review

Open access
Wang, Alexander, Qian, Zhiyu, Briggs, Logan, Cole, Alexander P, Reis, Leonardo O, Trinh, Quoc-Dien·2023·International Journal of General Medicine

Abstract

Background: Few reports have investigated chatbots in patient care. We aimed to assess the current applications, limitations, and challenges in the literature on chatbots employed in oncological care. Methods: We queried the PubMed database through April 2022 and included studies that investigated the use of chatbots in different phases of oncological care. The search used five different combinations of the specific terms "chatbot", "cancer", "oncology", and "conversational agent". Inclusion criteria were chatbot use in any aspect of oncological care-prevention, patient education, treatment, and surveillance. Results: The initial search yielded 196 records, 21 of which met inclusion criteria. The identified chatbots mostly focused on breast and ovarian cancer (n=8), with the second most common being cervical cancer (n=3). Good patient satisfaction was reported among 14 of 21 chatbots. The most reported chatbot applications were cancer screening, prevention, risk stratification, treatment, monitoring, and management. Of 12 studies examining efficacy of care via chatbot, 9 demonstrated improvements compared to standard care. Conclusion: Chatbots used for oncological care to date demonstrate high user satisfaction, and many have shown efficacy in improving patient-centered communication, accessibility to cancer-related information, and access to care. Currently, chatbots are primarily limited by the need for extensive user-testing and iterative improvement before widespread implementation.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2147/ijgm.s408208

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

1 of the 44 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

  1. [2]Shawar BA, Atwell E. Chatbots: are they really useful? 2007. Available from: https://www.researchgate.net/publication/220046725_Chatbots_Are_they_Really_Useful. Accessed April 23, 2022.
  2. [30]Amith M, Lin R, Cunningham R, et al. Examining potential usability and health beliefs among young adults using a conversational agent for HPV vaccine counseling - PubMed. AMIA Summits Transl Sci Proc. 2020; 2020: 7– 16. doi: 10.1145/3380991.3383937 PMC7233050 32477622 · DOI

Cited by

Sorted by citations

Authors
Wang, A., Qian, Z., Briggs, L., Cole, A. P., Reis, L. O., & Trinh, Q.-D.
Affiliations
Brigham and Women's Hospital (US)
Corresponding author
Trinh, Quoc-Dien
Venue
International Journal of General Medicine
Published
2023-05
Volume
Volume 16
Pages
1591-1602
ISSN
1178-7074 (ISSN-L)
OpenAlex
W4367557603
Cited by
73
References
44
Citations by year
2026: 17 · 2025: 27 · 2024: 23 · 2023: 6
FWCI
0.86
Type
journal article
Language
en
Open access
Locations
  • International Journal of General Medicine (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Dove Medical Press (Taylor and Francis Group) (submittedVersion, cc-by-nc)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
Keywords
chatbots, cancer care, cancer screening, cancer prevention, risk stratification, cancer surveillance, patient education, breast cancer, ovarian cancer, cervical cancer, patient satisfaction, health care access, patient-centered communication

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review