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BackgroundChronic kidney disease (CKD) is a global health problem with a high economic burden, which is particularly prevalent in Taiwan. Mobile health apps have been widely used to maintain continuity of patient care for various chronic diseases. To slow the progression of CKD, continuity of care is vital for patients’ self-management and cooperation with health care professionals. However, the literature provides a limited understanding of the use of mobile health apps to maintain continuity of patient-centered care for CKD. ObjectiveThis study identified apps related to the continuity of patient-centered care for CKD on the App Store, Google Play, and 360 Mobile Assistant, and explored the information and frequency of changes in these apps available to the public on different platforms. App functionalities, like patient self-management and patient management support for health care professionals, were also examined. MethodsWe used the CKD-related keywords “kidney,” “renal,” “nephro,” “chronic kidney disease,” “CKD,” and “kidney disease” in traditional Chinese, simplified Chinese, and English to search 3 app platforms: App Store, Google Play, and 360 Mobile Assistant. A total of 2 reviewers reached consensus on coding guidelines and coded the contents and functionalities of the apps through content analysis. After coding, Microsoft Office Excel 2016 was used to calculate Cohen kappa coefficients and analyze the contents and functionalities of the apps. ResultsA total of 177 apps related to patient-centered care for CKD in any language were included. On the basis of their functionality and content, 67 apps were recommended for patients. Among them, the most common functionalities were CKD information and CKD self-management (38/67, 57%), e-consultation (17/67, 25%), CKD nutrition education (16/67, 24%), and estimated glomerular filtration rate (eGFR) calculators (13/67, 19%). In addition, 67 apps were recommended for health care professionals. The most common functionalities of these apps were comprehensive clinical calculators (including eGFR; 30/67; 45%), CKD medical professional information (16/67, 24%), stand-alone eGFR calculators (14/67, 21%), and CKD clinical decision support (14/67, 21%). A total of 43 apps with single- or multiple-indicator calculators were found to be suitable for health care professionals and patients. The aspects of patient care apps intended to support self-management of CKD patients were encouraging patients to actively participate in health care (92/110, 83.6%), recognizing and effectively responding to symptoms (56/110, 50.9%), and disease-specific knowledge (53/110, 48.2%). Only 13 apps contained consulting management functions, patient management functions or teleconsultation functions designed to support health care professionals in CKD patient management. ConclusionsThis study revealed that the continuity of patient-centered care for CKD provided by mobile health apps is inadequate for both CKD self-management by patients and patient care support for health care professionals. More comprehensive solutions are required to enhance the continuity of patient-centered care for CKD.

The purpose of this study is to explore the classroom management effectiveness enhancement by using social networking apps through electronic devices such as smartphones, tablet computers, and personal computers, as well as the role of parental involvement. Quantitative research was conducted, and the Structural Equation Modelling (SEM) statistical technique applied. From 15 different Changhua County primary schools in Taiwan, 411 teachers were chosen using stratified random sampling in proportion to the size and location of schools. Each teacher was invited to fill out a questionnaire. A total of 403 (98.05%) questionnaires were returned, with 382 (92.94%) considered valid. In order to confirm the statistical results, a focused group interview was also conducted. The effects of the behaviour intention of using Line, parental involvement, and classroom management effectiveness were all found to be positively associated with one another. Moreover, the mediating role of parents in the relationship between the behaviour intention of using Line and classroom management effectiveness enhancement was also supported and confirmed.

In a smart city, IoT devices are required to support monitoring of normal operations such as traffic, infrastructure, and the crowd of people. IoT‐enabled systems offered by many IoT devices are expected to achieve sustainable developments from the information collected by the smart city. Indeed, artificial intelligence (AI) and machine learning (ML) are well‐known methods for achieving this goal as long as the system framework and problem statement are well prepared. However, to better use AI/ML, the training data should be as global as possible, which can prevent the model from working only on local data. Such data can be obtained from different sources, but this induces the privacy issue where at least one party collects all data in the plain. The main focus of this article is on support vector machines (SVM). We aim to present a solution to the privacy issue and provide confidentiality to protect the data. We build a privacy‐preserving scheme for SVM (SecretSVM) based on the framework of federated learning and distributed consensus. In this scheme, data providers self‐organize and obtain training parameters of SVM without revealing their own models. Finally, experiments with real data analysis show the feasibility of potential applications in smart cities. This article is the extended version of that of Hsu et al. (Proceedings of the 15th ACM Asia Conference on Computer and Communications Security. ACM; 2020:904‐906). [ABSTRACT FROM AUTHOR]