Evidence map›Paper›PMID 41212582›Full record

ArticleCancer medicine2025

Artificial Intelligence Chatbots and Their Responses to Most Searched Spanish Cancer Questions.

En Cheng, Jesus D Anampa, Carolina Bernabe-Ramirez, Juan Lin, Xiaonan Xue, Carmen R Isasi, Alyson B Moadel-Robblee, Edward Chu

Abstract read
In one paragraph

Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

8 authors.

En ChengDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
Jesus D AnampaCancer Therapeutics Program, Montefiore Einstein Comprehensive Cancer Center, Bronx, New York, USA.ORCID https://orcid.org/0000-0002-1898-180X
Carolina Bernabe-RamirezCancer Therapeutics Program, Montefiore Einstein Comprehensive Cancer Center, Bronx, New York, USA.
Juan LinDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
Xiaonan XueDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
Carmen R IsasiDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
Alyson B Moadel-RobbleeDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
Edward ChuCancer Therapeutics Program, Montefiore Einstein Comprehensive Cancer Center, Bronx, New York, USA.

Funding

WORD PROCESSORP30CA013330 · NCI · YESHIVA UNIVERSITY · PI STEVEN C. ALMO · 1985 to 2026
$111.2M
Einstein-Montefiore Clinical and Translational Science Award HubUM1TR004400 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI Jessica Kahn, Mimi Y Kim · 2023 to 2026
$17.3M
Albert Einstein College of MedicineMontefiore Einstein Comprehensive Cancer CenterNCATS NIH HHS UM1 TR004400NCATS NIH HHS UM1TR004400NCI NIH HHS P30 CA013330NCI NIH HHS P30CA013330
6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) chatbots perform well in answering English cancer questions. For Spanish, their performance is unknown and may differ by free vs. paywall versions.

methodsWe evaluated the quality (range: 1-5 points), actionability (range: 0-100%), and readability (range: 1-13 grades) of six popular AI chatbots in responding to the 15 most searched Spanish questions regarding breast, prostate, and colon cancer.

resultsThe quality of overall AI chatbot responses was good (mean [95% CI]: 3.5 [3.4-3.6] points), while the actionability was low (mean [95% CI]: 35.6% [30.8%-40.3%]). The readability was high-school-level (mean [95% CI]: 9.2 [8.8-9.6] grades), not concordant with the American Medical Association recommendation (≤ 6th grade). The quality, actionability, and readability did not differ by free and paywall versions (p > 0.05).

conclusionOur findings suggested AI chatbots may generate good-quality responses to Spanish cancer questions, regardless of free or paywall versions. However, further improvement in actionability and readability is needed to benefit Spanish-speaking patients.

Indexed as

Artificial IntelligenceNeoplasmsComprehensionFemaleGenerative Artificial IntelligenceHumansLanguageMaleSpainSurveys and Questionnairesartificial intelligencehealth literacyHispanic Americansnatural language processingneoplasmspatient education

Identifiers

PMID41212582
PMCPMC12599334

What OpenQuestion holds

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LicenceCC BY
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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.