基于聊天机器人的家庭健康史数据收集的可用性,参与度和报告有用性:混合方法分析分析
Michelle Hoang Nguyen1,2, João Sedoc3, Casey Overby Taylor1,2,4
1Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.
Journal of medical Internet research
|September 30, 2024
概括
收集家庭健康史 (FHx) 的聊天机器人方法比传统形式更易于使用和更具吸引力. 需要对聊天机器人个性,报告和个性化进行改进,以改善遗传风险评估.
科学领域:
- 基因组医学是基因组医学.
- 医疗信息学 医疗信息学
- 人与计算机的交互
背景情况:
- 家庭病史 (FHx) 对于评估遗传风险至关重要.
- 目前收集FHx的方法在许多成年人中未得到充分利用.
- 需要创新的数字工具来改善FHx数据收集.
研究的目的:
- 为了比较两个基于网络的FHx收集方法的可用性,参与度和报告实用性.
- 评估基于流程的聊天机器人 (KIT) 与传统的基于表格的方法.
- 确定优化基于聊天机器人的FHx数据收集的设计考虑因素.
主要方法:
- 一个混合方法的研究随机选择参与者进行聊天机器人 (KIT) 或基于表单的FHx收集方法.
- 用户可用性使用系统可用性量表 (SUS) 和定性反来评估.
- 参与度是通过所花费的时间和报告的条件来衡量,并补充了日志数据和用户评论.
主要成果:
- 使用KIT的参与者报告了明显更高的可用性 (SUS得分为80.2比61.9) 和参与度.
- 与表单用户相比,KIT用户花费的时间更少,报告的情况更多.
- 这两种方法都产生了一些有用的报告,用户希望更多的个性化和信息.
结论:
- 聊天机器人方法 (KIT) 提供了一种更易于使用和更有吸引力的方法来收集家庭健康史.
- 未来的聊天机器人设计应该专注于个性化,改进报告和谨慎的登陆.
- 过渡到大型语言模型可能会进一步增强基于聊天机器人的FHx数据收集.
关键词:
聊天机器人聊天机器人聊天机器人交谈代理人 交谈代理人众包 (crowdsourcing) 是一种众包方式.数字健康工具 数字健康工具参与 参与 参与 参与评价 评价 评价 评价家庭健康史 家庭健康史混合方法混合方法.报告的有用性 报告的有用性可用性可用性可用性更多相关视频
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