To implement a chatbot on the Facebook platform to establish connections with health care professionals who had subscribed to the chatbot, provide medical and pharmaceutical educational content, and collect data for online pharmacy research projects. Facebook was chosen because it has billions of daily active users, which offers a massive potential audience for research projects.
The chatbot was successfully implemented on the Facebook platform following 3 consecutive steps. Firstly, the ChatPion script was installed on the Pharmind website to establish the chatbot system. Secondly, the PharmindBot application was developed on Facebook. Finally, the PharmindBot app was integrated with the chatbot system.
The chatbot responds automatically to public comments and sends subscribers private responses using AI. The chatbot collected quantitative and qualitative data with minimal costs.
The chatbot\'s auto-reply function was tested using a post published on a specific page on Facebook. Testers were asked to leave predefined keywords to test its functionality. The chatbot\'s ability to collect and save data was tested by asking testers to fill out an online survey within Facebook Messenger for quantitative data and answer predefined questions for qualitative data.
The chatbot was tested on 1000 subscribers who interacted with it. Almost all testers (n = 990, 99%) obtained a successful private reply from the chatbot after sending a predefined keyword. Also, the chatbot replied privately to almost all public comments (n = 985, 98.5%) which helped to increase the organic reach and to establish a connection with the chatbot subscribers. No missing data were found when the chatbot was used to collect quantitative and qualitative data.
The chatbot reached thousands of health care professionals and provided them with automated responses. At a low cost, the chatbot was able to gather both qualitative and quantitative data without relying on Facebook ads to reach the intended audience. The data collection was efficient and effective. Using chatbots by pharmacy and medical researchers will help do more feasible online studies using AI to advance health care research.
目标:要在Facebook®平台上实施聊天机器人,以与订阅聊天机器人的医疗保健专业人员建立联系,提供医学和药学教育内容,并为在线药学研究项目收集数据。Facebook®之所以被选中,是因为它每天有数十亿的活跃用户,为研究项目提供了大量的潜在受众。
方法:聊天机器人是在Facebook®平台上成功实现的,遵循三个连续步骤。首先,在Pharmind网站上安装了ChatPion脚本,以建立聊天机器人系统。其次,PharmindBot应用程序是在Facebook®上开发的。最后,PharmindBot应用程序与聊天机器人系统集成。
方法:聊天机器人自动响应公众评论,并使用人工智能向订阅者发送私人响应。聊天机器人以最小的成本收集定量和定性数据。
方法:使用Facebook®特定页面上发布的帖子测试了聊天机器人的自动回复功能。要求测试人员留下预定义的关键字来测试其功能。通过要求测试人员在FacebookMessenger®中填写定量数据的在线调查并回答定性数据的预定义问题,测试了聊天机器人收集和保存数据的能力。
结果:聊天机器人在与之互动的1000个订阅者上进行了测试。几乎所有测试人员(n=990,99%)在发送预定义的关键字后,从聊天机器人那里获得了成功的私人回复。此外,聊天机器人私下回复了几乎所有的公众意见(n=985,98.5%),这有助于增加有机覆盖,并与聊天机器人用户建立连接。当使用聊天机器人收集定量和定性数据时,没有发现缺失的数据。
结论:聊天机器人覆盖了数千名医疗保健专业人员,并为他们提供了自动响应。以低成本,聊天机器人能够收集定性和定量数据,而无需依赖Facebook®广告来接触目标受众。数据收集是高效和有效的。药学和医学研究人员使用聊天机器人将有助于使用AI进行更可行的在线研究,以推进医疗保健研究。