Evidence map›Paper›PMID 42307353›Full record

ArticleRevista da Associacao Medica Brasileira (1992)2026

A comparative evaluation of ChatGPT and Gemini for stroke caregiver support: accuracy, safety, and response characteristics.

Osman Karaca, Mustafa Savaş Torlak, Ayşe Nur Tekin

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In one paragraph

Article in Revista da Associacao Medica Brasileira (1992), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Osman KaracaKTO Karatay University, Department of Physiotherapy and Rehabilitation - Konya, Türkiye.ORCID http://orcid.org/0000-0003-4552-410X
Mustafa Savaş TorlakKTO Karatay University, Vocational School of Health Sciences, Departments of Therapy and Rehabilitation - Konya, Türkiye.ORCID http://orcid.org/0000-0002-8084-6203
Ayşe Nur TekinBaskent University Hospital Konya, Department of Physical Therapy and Rehabilitation - Konya, Türkiye.ORCID http://orcid.org/0000-0001-6852-4335

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe use of large language models is increasing in healthcare. The aim of this study was to evaluate and compare the responses provided by ChatGPT (OpenAI) and Gemini (Google) to frequently asked questions about stroke and its treatment by caregivers, in terms of clarity, empathy/tone, actionability, information risk/safety, and accuracy.

methodsThis study used a qualitative content analysis to evaluate responses generated by large language models to stroke-related caregiving questions. Ten frequently asked questions were identified through a review of the literature on stroke caregiving. These questions were presented to the free versions of ChatGPT and Gemini, and responses from each model were recorded. The recorded responses were independently evaluated by 10 experts from neurology, physiatry, and physiotherapy using a structured Likert-scale instrument across five predefined categories: clarity, empathy/tone, actionability, information risk/safety, and accuracy.

resultsGeneralized estimating equation analyses indicated that the overall trends in response scores did not differ significantly between ChatGPT and Gemini across all evaluated categories (p>0.05). In contrast, response score trends varied primarily in clarity and empathy/tone, with limited variation in actionability (p<0.05). Intraclass correlation coefficient values were below 0.50 for both ChatGPT and Gemini.

conclusionAlthough both models generally performed well, question-level variations and low inter-rater reliability limit generalizability, and even small shortcomings in information risk may have important implications for stroke caregivers and, indirectly, for patients with stroke.

Indexed as

CaregiversStrokeGenerative Artificial IntelligenceHumansLarge Language ModelsQualitative ResearchReproducibility of ResultsSurveys and Questionnaires

Identifiers

PMID42307353
PMCPMC13268627

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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.