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CHAT-RT研究:放射肿瘤学中的ChatGPT——一项关于DEGRO成员使用情况、认知及影响的调查

CHAT-RT study: ChatGPT in radiation oncology-a survey on usage, perception, and impact among DEGRO members.

作者信息

Konnerth Dinah, Altay-Langguth Alev, Dehelean Diana-Coralia, Maier Sebastian H, Pazos Montserrat, Rogowski Paul, Schönecker Stephan, Eze Chukwuka, Corradini Stefanie, Belka Claus, Marschner Sebastian N

机构信息

Department of Radiation Oncology, LMU University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany.

Bavarian Cancer Research Center (BZKF), Munich, Germany.

出版信息

Radiat Oncol. 2025 Sep 15;20(1):140. doi: 10.1186/s13014-025-02721-9.

Abstract

BACKGROUND

Radiation oncology is increasingly turning to Artificial Intelligence (AI) - and in particular Chat Generative pre-trained transformer (ChatGPT) - for decision support, patient education, and workflow efficiency. Despite promising gains, questions about accuracy, General Data Protection Regulation (GDPR)-compliance and ethical use persist, especially in high-stakes cancer care. To clarify real-world attitudes and practices, we surveyed members of the German Society of Radiation Oncology (DEGRO) on their use, perceptions, and concerns regarding ChatGPT across clinical, research, communication, and administrative tasks.

METHODS

An anonymous online survey was implemented via LimeSurvey platform and distributed to all members of the DEGRO in Germany, Austria, and Switzerland between April and June 2024. The 40-item questionnaire-covering demographics, radiotherapy experience, and ChatGPT's clinical, research, communication, and administrative applications-was developed through a narrative literature review, ChatGPT-assisted drafting, back-translation, expert validation, and pilot testing. Fully completed responses were used for descriptive statistics and analysis.

RESULTS

Of 213 respondents, 159 fully completed the survey. Participants were predominantly based in Germany (92.5%), worked in university hospitals (74.2%), and identified as radiation oncologists (54.7%), with a broad range of radiotherapy experience (< 1 year: 7.5%; >15 years: 24.5%). Awareness of ChatGPT was high (94.9%), yet actual use varied: 32.1% never used it, while 35.2% employed it regularly for administrative tasks and 30.2% for manuscript drafting. Mid-career clinicians (6-10 years' experience) showed the greatest enthusiasm-44% agreed it saves time and 72% planned further integration-though all career stages (71.7% overall) expressed strong interest in formal training. Satisfaction was highest for administrative (94.6%) and manuscript support (91.7%) but lower for technical queries (66.7%). Major concerns included misinformation (69.2%), erosion of critical thinking (57.9%), and data-privacy risks (57.2%).

CONCLUSION

Our survey demonstrates high awareness and adoption of ChatGPT for administrative and educational tasks, alongside more cautious use in clinical decision-making. Widespread concerns about misinformation, critical-thinking erosion, and data privacy-especially among early- and mid-career clinicians-underscore the need for targeted AI training, rigorous validation, and transparent governance to ensure safe, effective integration into patient care.

摘要

背景

放射肿瘤学越来越多地转向人工智能(AI),尤其是聊天生成预训练变换器(ChatGPT),以提供决策支持、患者教育并提高工作流程效率。尽管有望取得成效,但关于准确性、符合通用数据保护条例(GDPR)以及道德使用的问题依然存在,尤其是在高风险的癌症治疗中。为了阐明实际的态度和做法,我们对德国放射肿瘤学会(DEGRO)的成员进行了调查,了解他们在临床、研究、沟通和行政任务中对ChatGPT的使用、看法和担忧。

方法

通过LimeSurvey平台进行了一项匿名在线调查,并于2024年4月至6月期间分发给德国、奥地利和瑞士的所有DEGRO成员。这份包含40个条目的问卷涵盖了人口统计学、放射治疗经验以及ChatGPT在临床、研究、沟通和行政方面的应用,是通过叙述性文献综述、ChatGPT辅助起草、回译、专家验证和预测试编制而成的。完整填写的回复用于描述性统计和分析。

结果

在213名受访者中,159人完整完成了调查。参与者主要来自德国(92.5%),在大学医院工作(74.2%),并将自己认定为放射肿瘤学家(54.7%),具有广泛的放射治疗经验(<1年:7.5%;>15年:24.5%)。对ChatGPT的知晓度很高(94.9%),但实际使用情况各不相同:32.1%的人从未使用过,35.2%的人经常将其用于行政任务,30.2%的人用于手稿起草。职业生涯中期的临床医生(有6 - 10年经验)表现出最大的热情——44%的人认为它节省时间,72%的人计划进一步整合——尽管所有职业阶段(总体为71.7%)都表示对接受正规培训有浓厚兴趣。对行政方面(94.6%)和手稿支持(91.7%)的满意度最高,但对技术问题的满意度较低(66.7%)。主要担忧包括错误信息(69.2%)、批判性思维的削弱(57.9%)和数据隐私风险(57.2%)。

结论

我们的调查表明,ChatGPT在行政和教育任务方面的知晓度和采用率很高,而在临床决策中的使用则更为谨慎。对错误信息、批判性思维削弱和数据隐私的广泛担忧,尤其是在职业生涯早期和中期的临床医生中,凸显了进行有针对性的人工智能培训、严格验证和透明管理的必要性,以确保安全、有效地将其整合到患者护理中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c66/12439408/8ce6d54874c7/13014_2025_2721_Fig1_HTML.jpg

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