PDF(Pubmed)
Abstract：
Chatbots have become ubiquitous in our daily lives, enabling natural language conversations with users through various modes of communication. Chatbots have the potential to play a significant role in promoting health and well-being. As the number of studies and available products related to chatbots continues to rise, there is a critical need to assess product features to enhance the design of chatbots that effectively promote health and behavioral change.
This scoping review aims to provide a comprehensive assessment of the current state of health-related chatbots, including the chatbots\' characteristics and features, user backgrounds, communication models, relational building capacity, personalization, interaction, responses to suicidal thoughts, and users\' in-app experiences during chatbot use. Through this analysis, we seek to identify gaps in the current research, guide future directions, and enhance the design of health-focused chatbots.
Following the scoping review methodology by Arksey and O\'Malley and guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist, this study used a two-pronged approach to identify relevant chatbots: (1) searching the iOS and Android App Stores and (2) reviewing scientific literature through a search strategy designed by a librarian. Overall, 36 chatbots were selected based on predefined criteria from both sources. These chatbots were systematically evaluated using a comprehensive framework developed for this study, including chatbot characteristics, user backgrounds, building relational capacity, personalization, interaction models, responses to critical situations, and user experiences. Ten coauthors were responsible for downloading and testing the chatbots, coding their features, and evaluating their performance in simulated conversations. The testing of all chatbot apps was limited to their free-to-use features.
This review provides an overview of the diversity of health-related chatbots, encompassing categories such as mental health support, physical activity promotion, and behavior change interventions. Chatbots use text, animations, speech, images, and emojis for communication. The findings highlight variations in conversational capabilities, including empathy, humor, and personalization. Notably, concerns regarding safety, particularly in addressing suicidal thoughts, were evident. Approximately 44% (16/36) of the chatbots effectively addressed suicidal thoughts. User experiences and behavioral outcomes demonstrated the potential of chatbots in health interventions, but evidence remains limited.
This scoping review underscores the significance of chatbots in health-related applications and offers insights into their features, functionalities, and user experiences. This study contributes to advancing the understanding of chatbots\' role in digital health interventions, thus paving the way for more effective and user-centric health promotion strategies. This study informs future research directions, emphasizing the need for rigorous randomized control trials, standardized evaluation metrics, and user-centered design to unlock the full potential of chatbots in enhancing health and well-being. Future research should focus on addressing limitations, exploring real-world user experiences, and implementing robust data security and privacy measures.
This scoping review aims to provide a comprehensive assessment of the current state of health-related chatbots, including the chatbots\' characteristics and features, user backgrounds, communication models, relational building capacity, personalization, interaction, responses to suicidal thoughts, and users\' in-app experiences during chatbot use. Through this analysis, we seek to identify gaps in the current research, guide future directions, and enhance the design of health-focused chatbots.
Following the scoping review methodology by Arksey and O\'Malley and guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist, this study used a two-pronged approach to identify relevant chatbots: (1) searching the iOS and Android App Stores and (2) reviewing scientific literature through a search strategy designed by a librarian. Overall, 36 chatbots were selected based on predefined criteria from both sources. These chatbots were systematically evaluated using a comprehensive framework developed for this study, including chatbot characteristics, user backgrounds, building relational capacity, personalization, interaction models, responses to critical situations, and user experiences. Ten coauthors were responsible for downloading and testing the chatbots, coding their features, and evaluating their performance in simulated conversations. The testing of all chatbot apps was limited to their free-to-use features.
This review provides an overview of the diversity of health-related chatbots, encompassing categories such as mental health support, physical activity promotion, and behavior change interventions. Chatbots use text, animations, speech, images, and emojis for communication. The findings highlight variations in conversational capabilities, including empathy, humor, and personalization. Notably, concerns regarding safety, particularly in addressing suicidal thoughts, were evident. Approximately 44% (16/36) of the chatbots effectively addressed suicidal thoughts. User experiences and behavioral outcomes demonstrated the potential of chatbots in health interventions, but evidence remains limited.
This scoping review underscores the significance of chatbots in health-related applications and offers insights into their features, functionalities, and user experiences. This study contributes to advancing the understanding of chatbots\' role in digital health interventions, thus paving the way for more effective and user-centric health promotion strategies. This study informs future research directions, emphasizing the need for rigorous randomized control trials, standardized evaluation metrics, and user-centered design to unlock the full potential of chatbots in enhancing health and well-being. Future research should focus on addressing limitations, exploring real-world user experiences, and implementing robust data security and privacy measures.
摘要：
背景：聊天机器人在我们的日常生活中无处不在，通过各种通信模式与用户进行自然语言对话。聊天机器人有可能在促进健康和福祉方面发挥重要作用。随着与聊天机器人相关的研究和可用产品的数量不断增加，非常需要评估产品功能，以增强聊天机器人的设计，从而有效地促进健康和行为改变。
目的：本范围审查旨在全面评估与健康相关的聊天机器人的现状，包括聊天机器人的特性和特点，用户背景,通信模型,关系建设能力，个性化,互动,对自杀想法的反应，和用户在使用聊天机器人期间的应用内体验。通过这种分析,我们试图找出当前研究中的差距，指导未来方向，并加强以健康为中心的聊天机器人的设计。
方法：遵循Arksey和O\'Malley的范围审查方法，并在PRISMA-ScR（系统审查的首选报告项目和范围审查的荟萃分析扩展）清单的指导下，这项研究采用了双管齐下的方法来识别相关的聊天机器人：（1）搜索iOS和Android应用程序商店；（2）通过图书馆员设计的搜索策略来审查科学文献。总的来说,根据两个来源的预定义标准选择了36个聊天机器人。使用为这项研究开发的综合框架对这些聊天机器人进行了系统评估，包括聊天机器人的特点，用户背景,建立关系能力，个性化,交互模型，对危急情况的反应，和用户体验。十个共同作者负责下载和测试聊天机器人，编码它们的特征，并评估他们在模拟对话中的表现。所有聊天机器人应用程序的测试仅限于其免费使用的功能。
结果：这篇综述概述了与健康相关的聊天机器人的多样性，包括心理健康支持等类别，促进身体活动，和行为改变干预措施。聊天机器人使用文本，动画,演讲,images,和用于交流的表情符号。这些发现突出了对话能力的变化，包括同理心，幽默,和个性化。值得注意的是,对安全的关注，特别是在解决自杀想法方面，很明显。大约44％（16/36）的聊天机器人有效地解决了自杀念头。用户体验和行为结果证明了聊天机器人在健康干预中的潜力，但证据仍然有限。
结论：本范围审查强调了聊天机器人在健康相关应用中的重要性，并提供了对其功能的见解。功能,和用户体验。这项研究有助于提高对聊天机器人在数字健康干预中的作用的理解。从而为更有效和以用户为中心的健康促进策略铺平道路。这项研究为未来的研究方向指明了方向，强调需要严格的随机对照试验，标准化评价指标，和以用户为中心的设计，以释放聊天机器人在增强健康和福祉方面的全部潜力。未来的研究应该集中在解决局限性上，探索现实世界的用户体验，并实施强大的数据安全和隐私措施。
目的：本范围审查旨在全面评估与健康相关的聊天机器人的现状，包括聊天机器人的特性和特点，用户背景,通信模型,关系建设能力，个性化,互动,对自杀想法的反应，和用户在使用聊天机器人期间的应用内体验。通过这种分析,我们试图找出当前研究中的差距，指导未来方向，并加强以健康为中心的聊天机器人的设计。
方法：遵循Arksey和O\'Malley的范围审查方法，并在PRISMA-ScR（系统审查的首选报告项目和范围审查的荟萃分析扩展）清单的指导下，这项研究采用了双管齐下的方法来识别相关的聊天机器人：（1）搜索iOS和Android应用程序商店；（2）通过图书馆员设计的搜索策略来审查科学文献。总的来说,根据两个来源的预定义标准选择了36个聊天机器人。使用为这项研究开发的综合框架对这些聊天机器人进行了系统评估，包括聊天机器人的特点，用户背景,建立关系能力，个性化,交互模型，对危急情况的反应，和用户体验。十个共同作者负责下载和测试聊天机器人，编码它们的特征，并评估他们在模拟对话中的表现。所有聊天机器人应用程序的测试仅限于其免费使用的功能。
结果：这篇综述概述了与健康相关的聊天机器人的多样性，包括心理健康支持等类别，促进身体活动，和行为改变干预措施。聊天机器人使用文本，动画,演讲,images,和用于交流的表情符号。这些发现突出了对话能力的变化，包括同理心，幽默,和个性化。值得注意的是,对安全的关注，特别是在解决自杀想法方面，很明显。大约44％（16/36）的聊天机器人有效地解决了自杀念头。用户体验和行为结果证明了聊天机器人在健康干预中的潜力，但证据仍然有限。
结论：本范围审查强调了聊天机器人在健康相关应用中的重要性，并提供了对其功能的见解。功能,和用户体验。这项研究有助于提高对聊天机器人在数字健康干预中的作用的理解。从而为更有效和以用户为中心的健康促进策略铺平道路。这项研究为未来的研究方向指明了方向，强调需要严格的随机对照试验，标准化评价指标，和以用户为中心的设计，以释放聊天机器人在增强健康和福祉方面的全部潜力。未来的研究应该集中在解决局限性上，探索现实世界的用户体验，并实施强大的数据安全和隐私措施。
