PDF(Pubmed)
Abstract：
BACKGROUND: Generative artificial intelligence has the potential to revolutionize health technology product development by improving coding quality, efficiency, documentation, quality assessment and review, and troubleshooting.
OBJECTIVE: This paper explores the application of a commercially available generative artificial intelligence tool (ChatGPT) to the development of a digital health behavior change intervention designed to support patient engagement in a commercial digital diabetes prevention program.
METHODS: We examined the capacity, advantages, and limitations of ChatGPT to support digital product idea conceptualization, intervention content development, and the software engineering process, including software requirement generation, software design, and code production. In total, 11 evaluators, each with at least 10 years of experience in fields of study ranging from medicine and implementation science to computer science, participated in the output review process (ChatGPT vs human-generated output). All had familiarity or prior exposure to the original personalized automatic messaging system intervention. The evaluators rated the ChatGPT-produced outputs in terms of understandability, usability, novelty, relevance, completeness, and efficiency.
RESULTS: Most metrics received positive scores. We identified that ChatGPT can (1) support developers to achieve high-quality products faster and (2) facilitate nontechnical communication and system understanding between technical and nontechnical team members around the development goal of rapid and easy-to-build computational solutions for medical technologies.
CONCLUSIONS: ChatGPT can serve as a usable facilitator for researchers engaging in the software development life cycle, from product conceptualization to feature identification and user story development to code generation.
BACKGROUND: ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500.
OBJECTIVE: This paper explores the application of a commercially available generative artificial intelligence tool (ChatGPT) to the development of a digital health behavior change intervention designed to support patient engagement in a commercial digital diabetes prevention program.
METHODS: We examined the capacity, advantages, and limitations of ChatGPT to support digital product idea conceptualization, intervention content development, and the software engineering process, including software requirement generation, software design, and code production. In total, 11 evaluators, each with at least 10 years of experience in fields of study ranging from medicine and implementation science to computer science, participated in the output review process (ChatGPT vs human-generated output). All had familiarity or prior exposure to the original personalized automatic messaging system intervention. The evaluators rated the ChatGPT-produced outputs in terms of understandability, usability, novelty, relevance, completeness, and efficiency.
RESULTS: Most metrics received positive scores. We identified that ChatGPT can (1) support developers to achieve high-quality products faster and (2) facilitate nontechnical communication and system understanding between technical and nontechnical team members around the development goal of rapid and easy-to-build computational solutions for medical technologies.
CONCLUSIONS: ChatGPT can serve as a usable facilitator for researchers engaging in the software development life cycle, from product conceptualization to feature identification and user story development to code generation.
BACKGROUND: ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500.
摘要：
背景：生成人工智能具有通过提高编码质量来彻底改变健康技术产品开发的潜力，效率,文档,质量评估和审查，和故障排除。
目的：本文探讨了商用生成人工智能工具（ChatGPT）在开发数字健康行为改变干预措施中的应用，旨在支持患者参与商业数字糖尿病预防计划。
方法：我们检查了容量，优势,以及ChatGPT在支持数字产品理念概念化方面的局限性，干预内容开发，和软件工程过程，包括软件需求生成，软件设计,和代码生产。总的来说,11名评估人员，每个人在从医学和实施科学到计算机科学的研究领域都有至少10年的经验，参与了输出审查过程(ChatGPT与人工产生的输出)。所有人都熟悉或事先接触过原始的个性化自动消息传递系统干预。评估人员根据可理解性对ChatGPT产生的产出进行了评级，可用性，新奇，相关性，完整性，和效率。
结果：大多数指标都获得了积极的评分。我们发现ChatGPT可以（1）支持开发人员更快地实现高质量的产品；（2）促进技术和非技术团队成员之间的非技术沟通和系统理解，围绕快速和易于构建的医疗技术计算解决方案的开发目标。
结论：ChatGPT可以作为参与软件开发生命周期的研究人员的有用推动者，从产品概念化到功能识别，从用户故事开发到代码生成。
背景：ClinicalTrials.govNCT04049500;https://clinicaltrials.gov/ct2/show/NCT04049500。
目的：本文探讨了商用生成人工智能工具（ChatGPT）在开发数字健康行为改变干预措施中的应用，旨在支持患者参与商业数字糖尿病预防计划。
方法：我们检查了容量，优势,以及ChatGPT在支持数字产品理念概念化方面的局限性，干预内容开发，和软件工程过程，包括软件需求生成，软件设计,和代码生产。总的来说,11名评估人员，每个人在从医学和实施科学到计算机科学的研究领域都有至少10年的经验，参与了输出审查过程(ChatGPT与人工产生的输出)。所有人都熟悉或事先接触过原始的个性化自动消息传递系统干预。评估人员根据可理解性对ChatGPT产生的产出进行了评级，可用性，新奇，相关性，完整性，和效率。
结果：大多数指标都获得了积极的评分。我们发现ChatGPT可以（1）支持开发人员更快地实现高质量的产品；（2）促进技术和非技术团队成员之间的非技术沟通和系统理解，围绕快速和易于构建的医疗技术计算解决方案的开发目标。
结论：ChatGPT可以作为参与软件开发生命周期的研究人员的有用推动者，从产品概念化到功能识别，从用户故事开发到代码生成。
背景：ClinicalTrials.govNCT04049500;https://clinicaltrials.gov/ct2/show/NCT04049500。
