生成式人工智能聊天机器人用于儿科骨科家长指导:试点可行性研究。

IF 4.9 Q2 ORTHOPEDICS
JBJS Open Access Pub Date : 2026-06-09 eCollection Date: 2026-04-01 DOI:10.2106/JBJS.OA.26.00078
Wayne Yong Xiang Foo, Kenneth Pak Leung Wong, Arjandas Mahadev, Mohammad Ashik Bin Zainuddin, Andrew Chia Chen Chou
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引用次数: 0

摘要

背景:患有儿科骨科疾病的儿童的父母在他们的门诊就诊后经常有问题,并且缺乏可靠的咨询后资源来解决这些问题。在线资源的质量参差不齐,通用人工智能(AI)模型已经证明了安全性的局限性,包括未经提示的治疗建议和引文不准确。一个专门建造的、有监督的生成式人工智能解决方案可能会提供一个更安全、更可靠的替代方案。方法:采用检索增强生成技术开发了一个生成式AI聊天机器人,并在OrthoKids教材上进行训练,该教材涵盖了5种常见的儿童骨科疾病:内趾、扁平足、脊柱侧弯、弓腿和叩膝。经过2名接受过奖学金培训的儿科骨科医生的反复改进,18名多学科临床医生使用结构化的12项5分制李克特量表对聊天机器人进行了评估,评估准确性、安全性、可用性和临床可接受性。结果:12个领域中有11个的平均得分超过4.0分。解释的清晰性获得了一致的正面认可(100%),而方案一致性获得了最高的平均评分(4.50±0.62)。引文准确性是评分最低的领域(4.00±0.77)。没有发现幻觉,88.9%的评估者确认没有未经提示的治疗建议。逆向评分的安全项目(Q8)显示出最大的评分差异(平均3.11±1.57),骨科专家对感知伤害的评分明显低于护士(平均4.40)(平均1.33)。结论:专门构建的gen AI聊天机器人在多学科评估人员中具有较高的临床准确性和可接受性,有效避免了未经提示的治疗建议。这些试验结果支持了在儿童骨科实践中作为家长教育辅助手段的可行性。证据等级:三级。有关证据水平的完整描述,请参见作者说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generative Artificial Intelligence Chatbots for Parental Guidance in Pediatric Orthopaedics: A Pilot Feasibility Study.

Background: Parents of children with pediatric orthopaedic conditions frequently have questions after their clinic visit, and a reliable postconsultation resource to address these enquiries is lacking. Online resources are variable in quality, and general purpose artificial intelligence (AI) models have demonstrated safety limitations, including unprompted treatment recommendations and citation inaccuracies. A purpose-built, supervised generative AI solution may offer a safer and more reliable alternative.

Methods: A generative AI chatbot was developed using retrieval-augmented generation and trained on OrthoKids educational materials covering 5 common pediatric orthopaedic conditions: in-toeing, flatfoot, scoliosis, bow legs, and knock knees. After iterative refinement by 2 fellowship-trained pediatric orthopaedic surgeons, the chatbot was evaluated by 18 multidisciplinary clinicians using a structured 12-item 5-point Likert scale survey assessing accuracy, safety, usability, and clinical acceptability.

Results: Mean scores exceeded 4.0 of 5.0 on 11 of 12 domains. Clarity of explanation achieved unanimous positive endorsement (100%), while protocol alignment received the highest mean score (4.50 ± 0.62). Citation accuracy was the lowest-rated domain (4.00 ± 0.77). No hallucinations were identified, and 88.9% of evaluators confirmed the absence of unprompted treatment recommendations. The reverse-scored safety item (Q8) demonstrated the greatest inter-rater variability (mean 3.11 ± 1.57), with orthopaedic specialists rating perceived harm substantially lower (mean 1.33) than nurses (mean 4.40).

Conclusion: A purpose-built gen AI chatbot demonstrated high clinical accuracy and acceptability among multidisciplinary evaluators, with effective avoidance of unprompted treatment recommendations. These pilot findings support feasibility for use as a parental education adjunct in pediatric orthopaedic practice.

Level of evidence: Level III. See Instructions for Authors for a complete description of levels of evidence.

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来源期刊
JBJS Open Access
JBJS Open Access Medicine-Surgery
CiteScore
5.00
自引率
0.00%
发文量
77
审稿时长
6 weeks
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