Evaluating the Implementation of the GREAT4Diabetes WhatsApp Chatbot to Educate People With Type 2 Diabetes During the COVID-19 Pandemic: Convergent Mixed Methods Study.

Q2 Medicine JMIR Diabetes Pub Date : 2022-06-24 DOI:10.2196/37882
Robert Mash, Darcelle Schouw, Alex Emilio Fischer
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引用次数: 0

Abstract

Background: In South Africa, diabetes is a leading cause of morbidity and mortality, which was exacerbated during the COVID-19 pandemic. Most education and counseling activities were stopped during the lockdown, and the GREAT4Diabetes WhatsApp Chatbot was innovated to fill this gap.

Objective: This study aimed to evaluate the implementation of the chatbot in Cape Town, South Africa, between May and October 2021.

Methods: Convergent mixed methods were used to evaluate the implementation outcomes: acceptability, adoption, appropriateness, feasibility, fidelity, cost, coverage, effects, and sustainability. Quantitative data were derived from the chatbot and analyzed using the SPSS. Qualitative data were collected from key informants and analyzed using the framework method assisted by Atlas-ti. The chatbot provided users with 16 voice messages and graphics in English, Afrikaans, or Xhosa. Messages focused on COVID-19 infection and self-management of type 2 diabetes.

Results: The chatbot was adopted by the Metro Health Services to assist people with diabetes who had restricted health care during the lockdown and were at a higher risk of hospitalization and death from COVID-19 infection. The chatbot was disseminated via health care workers in primary care facilities and local nonprofit organizations and via local media and television. Two technical glitches interrupted the dissemination but did not substantially affect user behavior. Minor changes were made to the chatbot to improve its utility. Many patients had access to smartphones and were able to use the chatbot via WhatsApp. Overall, 8158 people connected with the chatbot and 4577 (56.1%) proceeded to listen to the messages, with 12.56% (575/4577) of them listening to all 16 messages, mostly within 32 days. The incremental setup costs were ZAR 255,000 (US $16,876) and operational costs over 6 months were ZAR 462,473 (US $30,607). More than 90% of the users who listened to each message found them useful. Of the 533 who completed the whole program, 351 (71.1%) said they changed their self-management a lot and 87.6% (369/421) were more confident. Most users changed their lifestyles in terms of diet (315/414, 76.1%) and physical activity (222/414, 53.6%). Health care workers also saw benefits to patients and recommended that the service continues. Sustainability of the chatbot will depend on the future policy of the provincial Department of Health toward mobile health and the willingness to contract with Aviro Health. There is the potential to go to scale and include other languages and chronic conditions.

Conclusions: The chatbot shows great potential to complement traditional health care approaches for people with diabetes and assist with more comprehensive patient education. Further research is needed to fully explore the patient's experience of the chatbot and evaluate its effectiveness in our context.

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评估GREAT4Diabetes WhatsApp聊天机器人在新冠肺炎大流行期间教育2型糖尿病患者的实施:融合混合方法研究
在南非,糖尿病是发病和死亡的主要原因,在2019冠状病毒病大流行期间,这一情况进一步恶化。在封锁期间,大多数教育和咨询活动都停止了,GREAT4Diabetes WhatsApp聊天机器人的创新填补了这一空白。本研究旨在评估2021年5月至10月期间聊天机器人在南非开普敦的实施情况。方法采用融合混合方法对实施结果进行评价:可接受性、采用性、适宜性、可行性、保真度、成本、覆盖率、效果和可持续性。定量数据来自聊天机器人,并使用SPSS进行分析。从关键举报人处收集定性数据,并使用Atlas-ti辅助的框架方法进行分析。这个聊天机器人用英语、南非荷兰语或科萨语为用户提供16条语音信息和图形。信息侧重于COVID-19感染和2型糖尿病的自我管理。结果该聊天机器人被地铁卫生服务中心采用,以帮助在封锁期间医疗保健受限、因COVID-19感染住院和死亡风险较高的糖尿病患者。聊天机器人通过初级保健机构和当地非营利组织的医护人员以及当地媒体和电视传播。两个技术故障中断了传播,但并未对用户行为产生实质性影响。对聊天机器人做了一些小改动,以提高其实用性。许多患者都有智能手机,可以通过WhatsApp使用聊天机器人。总体而言,8158人与聊天机器人连接,4577人(56.1%)继续收听消息,其中12.56%(575/4577)的人收听了所有16条消息,大部分在32天内。增量安装成本为255,000兰特(16,876美元),6个月的运营成本为462,473兰特(30,607美元)。超过90%的用户听了每条消息后都觉得很有用。在完成整个项目的533人中,351人(71.1%)表示他们在自我管理方面改变了很多,87.6%(369/421)表示他们更有信心。大多数用户在饮食(315/414,76.1%)和体育锻炼(222/414,53.6%)方面改变了生活方式。卫生保健工作者也看到了病人的好处,并建议继续提供这项服务。聊天机器人的可持续性将取决于省卫生厅对移动医疗的未来政策以及与Aviro Health签订合同的意愿。有可能扩大规模,包括其他语言和慢性病。结论该聊天机器人在糖尿病患者传统医疗保健方式的补充方面具有很大的潜力,并有助于更全面的患者教育。需要进一步的研究来充分探索患者对聊天机器人的体验,并评估其在我们环境中的有效性。
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来源期刊
JMIR Diabetes
JMIR Diabetes Computer Science-Computer Science Applications
CiteScore
4.00
自引率
0.00%
发文量
35
审稿时长
16 weeks
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