A. E. El Ayadi, Pushpendra Singh, Mona Duggal, Vijay Kumar, Jasmeet Kaur, Preetika Sharma, K. Vosburg, N. Diamond-Smith
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Methods We pilot-tested Saheli among pregnant and breastfeeding participants of pre-existing WhatsApp educational groups led by a community-based non-governmental organisation in Haryana, India from January to March 2022 using a pre/post design. Results 829 unique participants completed precommunity surveys or postcommunity surveys; 238 completed both. 829 individuals used Saheli, including 88% postintervention survey participants. Users reported Saheli was easy to engage with (79%), easy to understand (91%), quick (83%) and met their information needs (97%). 89% indicated it improved their COVID-19 knowledge a lot, 72% recommended it to others and 88% shared chatbot-derived information with others. Most participants received ≥1 COVID-19 vaccine (86% vs 88%, preintervention to postintervention); full vaccination was 55% and 61%, respectively. Vaccination over time increased marginally for ≥1 dose (OR 1.15, 95% CI 0.99 to 1.36) and significantly for 2 doses (OR 1.21, 95% CI 1.09 to 1.34), and increases were significant among pregnant (≥1 dose) and breastfeeding participants (2 doses). Vaccine hesitancy was low. Chatbot use was high, yet individual chatbot engagement did not alter COVID-19 vaccination. Conclusion Chatbots are a promising health education strategy due to high acceptability and deployment potential. Interpreting community chatbot impact must acknowledge the co-occurring constellation of multilevel interventions, community and pandemic factors.","PeriodicalId":53454,"journal":{"name":"BMJ Innovations","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Feasibility and acceptability of Saheli, a WhatsApp Chatbot, on COVID-19 vaccination among pregnant and breastfeeding women in rural North India\",\"authors\":\"A. E. El Ayadi, Pushpendra Singh, Mona Duggal, Vijay Kumar, Jasmeet Kaur, Preetika Sharma, K. Vosburg, N. 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Results 829 unique participants completed precommunity surveys or postcommunity surveys; 238 completed both. 829 individuals used Saheli, including 88% postintervention survey participants. Users reported Saheli was easy to engage with (79%), easy to understand (91%), quick (83%) and met their information needs (97%). 89% indicated it improved their COVID-19 knowledge a lot, 72% recommended it to others and 88% shared chatbot-derived information with others. Most participants received ≥1 COVID-19 vaccine (86% vs 88%, preintervention to postintervention); full vaccination was 55% and 61%, respectively. Vaccination over time increased marginally for ≥1 dose (OR 1.15, 95% CI 0.99 to 1.36) and significantly for 2 doses (OR 1.21, 95% CI 1.09 to 1.34), and increases were significant among pregnant (≥1 dose) and breastfeeding participants (2 doses). Vaccine hesitancy was low. Chatbot use was high, yet individual chatbot engagement did not alter COVID-19 vaccination. 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引用次数: 0
摘要
由于围产期COVID-19感染对孕产妇和胎儿的不良后果以及通过母体抗体保护婴儿的机会，孕妇和哺乳期妇女是COVID-19疫苗接种的优先目标。Saheli(“女性朋友”)是一个部署在whatsapp上的聊天机器人，为孕妇和哺乳期妇女提供关于COVID-19的循证指导。目的了解萨赫勒的可行性和可接受性及其对COVID-19疫苗接种的影响。方法:2022年1月至3月，我们在印度哈里亚纳邦一个社区非政府组织领导的已有WhatsApp教育小组的孕妇和哺乳期参与者中，采用前后设计对Saheli进行了试点测试。结果829名参与者完成了社区前调查和社区后调查;238人两者都完成了。829人使用Saheli，其中88%为干预后调查参与者。用户表示，Saheli易于参与(79%)，易于理解(91%)，快速(83%)，并满足他们的信息需求(97%)。89%的人表示这大大提高了他们对COVID-19的了解，72%的人向他人推荐，88%的人与他人分享聊天机器人衍生的信息。大多数参与者接种了1支以上的COVID-19疫苗(干预前和干预后分别为86%和88%);完全疫苗接种率分别为55%和61%。≥1剂的疫苗接种率随着时间的推移略有增加(OR 1.15, 95% CI 0.99至1.36)，2剂的疫苗接种率显著增加(OR 1.21, 95% CI 1.09至1.34)，孕妇(≥1剂)和母乳喂养参与者(2剂)的疫苗接种率显著增加。疫苗犹豫率低。聊天机器人的使用率很高，但个人聊天机器人的参与并没有改变COVID-19疫苗接种。结论聊天机器人具有较高的可接受性和部署潜力，是一种很有前途的健康教育策略。解释社区聊天机器人的影响必须承认多层干预、社区和流行病因素共同发生的星座。
Feasibility and acceptability of Saheli, a WhatsApp Chatbot, on COVID-19 vaccination among pregnant and breastfeeding women in rural North India
Introduction Pregnant and breastfeeding women are priority targets for COVID-19 vaccination due to adverse maternal and fetal consequences of perinatal COVID-19 infection and the opportunity for protecting infants through maternal antibodies. Saheli (‘female friend’) is a WhatsApp-deployed chatbot providing evidence-based guidance on COVID-19 for pregnant and breastfeeding women. Objectives To understand the feasibility and acceptability of Saheli and its impact on COVID-19 vaccination. Methods We pilot-tested Saheli among pregnant and breastfeeding participants of pre-existing WhatsApp educational groups led by a community-based non-governmental organisation in Haryana, India from January to March 2022 using a pre/post design. Results 829 unique participants completed precommunity surveys or postcommunity surveys; 238 completed both. 829 individuals used Saheli, including 88% postintervention survey participants. Users reported Saheli was easy to engage with (79%), easy to understand (91%), quick (83%) and met their information needs (97%). 89% indicated it improved their COVID-19 knowledge a lot, 72% recommended it to others and 88% shared chatbot-derived information with others. Most participants received ≥1 COVID-19 vaccine (86% vs 88%, preintervention to postintervention); full vaccination was 55% and 61%, respectively. Vaccination over time increased marginally for ≥1 dose (OR 1.15, 95% CI 0.99 to 1.36) and significantly for 2 doses (OR 1.21, 95% CI 1.09 to 1.34), and increases were significant among pregnant (≥1 dose) and breastfeeding participants (2 doses). Vaccine hesitancy was low. Chatbot use was high, yet individual chatbot engagement did not alter COVID-19 vaccination. Conclusion Chatbots are a promising health education strategy due to high acceptability and deployment potential. Interpreting community chatbot impact must acknowledge the co-occurring constellation of multilevel interventions, community and pandemic factors.
期刊介绍：
Healthcare is undergoing a revolution and novel medical technologies are being developed to treat patients in better and faster ways. Mobile revolution has put a handheld computer in pockets of billions and we are ushering in an era of mHealth. In developed and developing world alike healthcare costs are a concern and frugal innovations are being promoted for bringing down the costs of healthcare. BMJ Innovations aims to promote innovative research which creates new, cost-effective medical devices, technologies, processes and systems that improve patient care, with particular focus on the needs of patients, physicians, and the health care industry as a whole and act as a platform to catalyse and seed more innovations. Submissions to BMJ Innovations will be considered from all clinical areas of medicine along with business and process innovations that make healthcare accessible and affordable. Submissions from groups of investigators engaged in international collaborations are especially encouraged. The broad areas of innovations that this journal aims to chronicle include but are not limited to: Medical devices, mHealth and wearable health technologies, Assistive technologies, Diagnostics, Health IT, systems and process innovation.
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