Non-communicable diseases (NCDs) are a leading cause of global deaths, necessitating a focus on primary prevention and lifestyle behavior change. Health coaching, coupled with Question Answering (QA) systems, has the potential to transform preventive healthcare. This paper presents a human-Artificial Intelligence (AI) health coaching model incorporating a domain-specific extractive QA system. A sleep-focused dataset, SleepQA, was manually assembled and used to fine-tune domain-specific BERT models. The QA system was evaluated using automatic and human methods. A data-centric framework enhanced the system's performance by improving passage retrieval and question reformulation. Although the system did not outperform the baseline in automatic evaluation, it excelled in the human evaluation of real-world questions. Integration into a Human-AI health coaching model was tested in a pilot Randomized Controlled Trial (RCT).

翻译：非传染性疾病是全球死亡的主要原因，这要求我们重点关注初级预防和生活方式行为改变。健康辅导与问答系统相结合，有望变革预防性医疗保健。本文提出了一种结合领域特异性抽取式问答系统的人机健康辅导模型。我们手动构建了专注于睡眠的数据集SleepQA，并用于微调领域特异性BERT模型。该问答系统通过自动化和人工方法进行了评估。一种以数据为中心的框架通过改进段落检索和问题重述提升了系统性能。尽管该系统在自动评估中未超越基线，但在真实世界问题的人工评估中表现优异。该系统已集成到人机健康辅导模型中，并通过一项试点随机对照试验进行了测试。