ABSTRACT

Using diabetes mobile apps for self-management of diabetes is one of the emerging strategies for controlling blood sugar levels and maintaining the wellness of patients with diabetes. This study aims to develop a strategy for thematically extracting user comments from diabetes mobile apps to understand the concern of patients with diabetes. Hence, 2678 user comments obtained from the Google Play Store are thematically analyzed with Non-negative Matrix Factorization (NMF) to identify the themes for describing positive, neutral, and negative sentiments. These themes are used as the ground truth for developing a 10-fold cross-validation ensemble Multilayer Artificial Neural Network (ANN) model following the Bag of Word (BOW) analysis of lemmatized user comments. The result shows that a total of 41.24% of positive sentimental users identified the diabetes mobile apps as Effective for Blood Sugar Monitoring (EBSM), 32.36% with neutral sentiments are mostly impressed by the Information Quality (IQ), whereas 40.81% of unhappy users are worried about the Poor Information Quality (PIQ). The prediction accuracy of the ANN model is 89%–97%, which is 5%–48% better than other predominant algorithms. It can be concluded from this study that diabetes mobile apps with a simple user interface, effective data storage and security, medication adherence, and doctor appointment scheduling are preferred by patients with diabetes.

摘要

使用糖尿病移动应用程序进行糖尿病自我管理是控制血糖水平和维持糖尿病患者健康的新兴策略之一。本研究旨在制定一种策略，从糖尿病移动应用程序中主题提取用户评论，以了解糖尿病患者的担忧。因此，使用非负矩阵分解 (NMF) 对从 Google Play 商店获得的 2678 条用户评论进行主题分析，以确定描述积极、中性和消极情绪的主题。这些主题被用作开发 10 倍交叉验证集成多层人工神经网络 (ANN) 模型的基本事实，并对词形还原的用户评论进行词袋 (BOW) 分析。结果显示，共有41个。24%的积极情绪用户认为糖尿病移动应用程序对血糖监测（EBSM）有效，32.36%的中性情绪用户主要对信息质量（IQ）印象深刻，而40.81%的不满意用户则担心信息质量（PIQ）较差。ANN模型的预测精度为89%~97%，比其他主流算法提高5%~48%。从这项研究可以得出结论，具有简单用户界面、有效的数据存储和安全性、药物依从性和医生预约安排的糖尿病移动应用程序是糖尿病患者的首选。ANN模型的预测精度为89%~97%，比其他主流算法提高5%~48%。从这项研究可以得出结论，具有简单用户界面、有效的数据存储和安全性、药物依从性和医生预约安排的糖尿病移动应用程序是糖尿病患者的首选。ANN模型的预测精度为89%~97%，比其他主流算法提高5%~48%。从这项研究可以得出结论，具有简单用户界面、有效的数据存储和安全性、药物依从性和医生预约安排的糖尿病移动应用程序是糖尿病患者的首选。