Evidence map›Paper›PMID 42876766›Full record

ArticleFrontiers in public health2026

Performance of large language models in postoperative hip fracture rehabilitation counseling for older adults: a comparative evaluation of safety, accuracy, reliability, readability, and empathy.

Genrong Hu, Qiuju Lai, Shuqiong Liu, Baoyuan Xie, Zhishui Wu, Qiongxia Zhuang, Haiyan Tang, Jing Xu

Abstract readComparative Study
In one paragraph

Article in Frontiers in public health, 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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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Genrong HuLower Limb Department I, Quanzhou Orthopedic-traumatological Hospital, Quanzhou, Fujian, China.
Qiuju LaiLower Limb Department I, Quanzhou Orthopedic-traumatological Hospital, Quanzhou, Fujian, China.
Shuqiong LiuLower Limb Department I, Quanzhou Orthopedic-traumatological Hospital, Quanzhou, Fujian, China.
Baoyuan XieNursing Department, The Second Affiliated Hospital of Fujian Medical University (Donghai Campus), Quanzhou, Fujian, China.
Zhishui WuSpine Surgery Department, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China.
Qiongxia ZhuangLower Limb Department I, Quanzhou Orthopedic-traumatological Hospital, Quanzhou, Fujian, China.
Haiyan TangLower Limb Department I, Quanzhou Orthopedic-traumatological Hospital, Quanzhou, Fujian, China.
Jing XuLower Limb Department I, Quanzhou Orthopedic-traumatological Hospital, Quanzhou, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To compare the performance of five widely used large language models in answering public questions about postoperative rehabilitation after hip fracture in older adults, focusing on safety, accuracy, reliability, readability, empathy, and overall information quality. Methods: This cross-sectional comparative evaluation used a 42-question bank addressing general postoperative rehabilitation after proximal femoral fracture treated with internal fixation or hip arthroplasty. All questions and the standardized safety-oriented prompt were submitted in English, and all responses were returned and analyzed in their original English form without translation. Between May 1 and May 10, 2026, each question was submitted once to five generative artificial intelligence-driven chatbots through their official public interfaces, yielding 210 responses. Three independent raters evaluated each response using DISCERN, EQIP, JAMA benchmark criteria, Global Quality Score, and anchored 5-point accuracy and empathy scales. Safety was classified using prespecified binary criteria and summarized descriptively; readability was assessed using six established indices applied to the original English responses. Paired inferential analyses were used for non-binary outcomes. Results: Inter-rater agreement was excellent (Fleiss' kappa 0.855; ICC 0.829-0.884). Under the standardized safety-oriented prompt, 199 of 210 responses (94.8%) met the study's prespecified binary safety criterion; the 11 responses that did not meet the criterion were concentrated in three questions and were summarized descriptively. Accuracy ratings were high across models, with no statistically detectable difference ( Conclusions: Under a standardized safety-oriented prompt, most responses met the study's prespecified binary safety criterion and received high accuracy ratings; however, models differed in empathy, reliability, information quality, and readability. These prompt-conditioned findings do not establish unguided LLM responses as generally safe. LLMs may serve only as supervised adjunctive educational tools, with outputs framed as complementary to procedure-specific professional care.

Indexed as

ComprehensionHip FracturesLarge Language ModelsAgedCross-Sectional StudiesEmpathyFemaleHumansMaleReproducibility of ResultsSurveys and Questionnairesgenerative artificial intelligencehip fracturelarge language modelsolder adultspatient educationreadabilityrehabilitationsafety

Identifiers

PMID42876766
PMCPMC13662073

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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.