Zixin Wang, Siyu Chen, Josiah Poon, Soyeon Caren Han, Danhua Ye, Fuk-Yuen Yu, Yuan Fang, Zhao Ni, Martin C S Wong, Phoenix K H Mo
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引用次数: 0
摘要
重要性:很少有可靠的评估评估聊天机器人对提高65岁或以上成年人肺炎球菌疫苗(PV)摄取的功效。目的:评估混合聊天机器人在增加65岁或以上香港居民光伏吸收方面的相对功效。设计、环境和参与者:这项部分隐蔽性、平行组随机临床试验于2023年5月1日至2024年11月30日在中国香港进行。参与者年龄在65岁或以上,持有香港身份证,能说并理解广东话,是智能手机和WhatsApp用户,之前没有使用过PV。参与者是通过随机电话招募的,并被随机分为改变阶段组和标准干预组。干预措施:在变化阶段组中,混合聊天机器人的基于规则的组件评估参与者在PV吸收方面的变化阶段,然后在第0、1、2和3个月提供针对变化阶段的干预措施。混合聊天机器人的自然语言处理组件为参与者的pv相关问题提供实时答案。在标准干预组,聊天机器人在第0个月、第1个月、第2个月和第3个月向参与者发送一个访问涵盖PV信息的标准在线视频的链接。主要结果和测量方法:主要结果是12个月时自我报告的PV吸收,研究小组验证了这一点。次要结果是参与者在第0个月和第12个月的变化阶段,通过使用有效的问题来测量,得分为1 =预思考,2 =沉思,3 =准备,4 =行动。结果:共有374名参与者(女性213名[57.0%],平均[SD]年龄69.6[3.1]岁)被随机分为改变阶段组(n = 187)和标准干预组(n = 187)。意向治疗分析显示,改变期组有效PV摄取率高于标准干预组(29.4% vs 18.7%; P = 0.01)。变化阶段组的SD平均评分高于标准干预组(2.2 [1.3]vs 1.9 [1.1]; P = .02)。结论和相关性:在这项随机临床试验中,混合聊天机器人在增加香港老年人PV摄取方面比标准干预更有效。对于老年人来说,混合聊天机器人可能是一种可持续的PV推广。试验注册:ClinicalTrials.gov标识符:NCT05772117。
A Hybrid Chatbot to Promote Pneumococcal Vaccination Among Older Adults: A Randomized Clinical Trial.
Importance: There are few robust evaluations assessing the efficacy of chatbots to improve pneumococcal vaccination (PV) uptake among adults 65 years of age or older.
Objective: To evaluate the relative efficacy of a hybrid chatbot in increasing PV uptake among Hong Kong residents aged 65 years or older.
Design, setting, and participants: This partially masked, parallel-group randomized clinical trial was conducted between May 1, 2023, and November 30, 2024 in Hong Kong, China. Participants were aged 65 years or older, had a Hong Kong identity card, could speak and comprehend Cantonese, were smartphone and WhatsApp users, and had no prior PV uptake. Participants were recruited through random telephone calls and were randomized to either the stage of change group or the standard intervention group.
Interventions: In the stage of change group, the rule-based component of the hybrid chatbot assessed participants' stage of change regarding PV uptake and then delivered stage of change-tailored interventions at months 0, 1, 2, and 3. The natural language processing component of the hybrid chatbot provided real-time answers to participants' PV-related questions. In the standard intervention group, the chatbot sent participants a link to access a standard online video covering PV information at months 0, 1, 2, and 3.
Main outcomes and measures: The primary outcome was self-reported PV uptake at month 12, which was validated by the research team. The secondary outcome was participants' stage of change measured at month 0 and month 12 by using validated questions, with a score of 1 = precontemplation, 2 = contemplation, 3 = preparation, and 4 = action.
Results: A total of 374 participants (213 female [57.0%]; mean [SD] age, 69.6 [3.1] years) were randomized to either the stage of change group (n = 187) or the standard intervention group (n = 187). The intention-to-treat analysis showed that the validated PV uptake rate was higher in the stage of change group than in the standard intervention group (29.4% vs 18.7%; P = .01). The mean (SD) stage of change score was higher in the stage of change group than in the standard intervention group (2.2 [1.3] vs 1.9 [1.1]; P = .02). More participants in the stage of change group than in the standard intervention group completed at least 1 intervention session (79.7% vs 57.8%; P < .001).
Conclusions and relevance: In this randomized clinical trial, the hybrid chatbot was more efficacious than the standard intervention in increasing PV uptake among older adults in Hong Kong. A hybrid chatbot may be a sustainable PV promotion for older adults.
期刊介绍:
JAMA Network Open, a member of the esteemed JAMA Network, stands as an international, peer-reviewed, open-access general medical journal.The publication is dedicated to disseminating research across various health disciplines and countries, encompassing clinical care, innovation in health care, health policy, and global health.
JAMA Network Open caters to clinicians, investigators, and policymakers, providing a platform for valuable insights and advancements in the medical field. As part of the JAMA Network, a consortium of peer-reviewed general medical and specialty publications, JAMA Network Open contributes to the collective knowledge and understanding within the medical community.