Tebianian Mohammad A, Jahromi Soodeh Razeghi
Department of Computer Software Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.
Department of Clinical Nutrition, School of Nutrition Sciences and Food Technology, Shahid Beheshti University of Medical Sciences, Iran.
Int J Prev Med. 2024 Jul 17;15:20. doi: 10.4103/ijpvm.ijpvm_268_23. eCollection 2024.
We developed and evaluated an intelligent diabetes assistant application (Diabetter) for the self-management of diabetes. It suggested that increasing the patient's interest and participation in using smartphone apps is important for the effectiveness of diabetes management apps.
After evaluating all-encompassing features for diabetes management, we divided the selected factors into sub-factors for use in the application. Then, we created the first high-fidelity prototype using related programs and conducted early user testing to validate and improve Diabetter. To handle the user transaction time and keep them motivated, we designed and implemented a scoring system based on the nudge theory rules within the app.
To evaluate Diabetter's impact on diabetes self-management, we measured HbA1c levels after a prolonged period. The Diabetter prototype was developed and modified in a revised version for better user interaction with the app. The scoring system increased the input of users' information, which resulted in more analysis and recommendations to users. Clinical studies showed that as a result of continuous input of information from users who had been using the application for a longer period of time, their HbA1c levels were within the healthy range.
The results demonstrate that the Diabetter application has been able to play an effective role in diabetes self-management by increasing users' app usage time. However, future study is needed to provide a better interpretation.
我们开发并评估了一款用于糖尿病自我管理的智能糖尿病助手应用程序(Diabetter)。结果表明,提高患者对使用智能手机应用程序的兴趣和参与度对于糖尿病管理应用程序的有效性至关重要。
在评估了糖尿病管理的全面功能后,我们将选定的因素细分为子因素以用于该应用程序。然后,我们使用相关程序创建了第一个高保真原型,并进行了早期用户测试以验证和改进Diabetter。为了处理用户交互时间并保持他们的积极性,我们在应用程序中基于助推理论规则设计并实施了一个评分系统。
为了评估Diabetter对糖尿病自我管理的影响,我们在一段较长时间后测量了糖化血红蛋白(HbA1c)水平。Diabetter原型经过开发并修改为修订版,以实现用户与应用程序更好的交互。评分系统增加了用户信息的输入量,从而为用户带来了更多的分析和建议。临床研究表明,由于长期使用该应用程序的用户持续输入信息,他们的HbA1c水平处于健康范围内。
结果表明,Diabetter应用程序通过增加用户的应用程序使用时间,已能够在糖尿病自我管理中发挥有效作用。然而,需要未来的研究来提供更好的解释。