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Background The COVID-19 pandemic has expanded the use of mobile health (mHealth) technologies in contact tracing, communicating COVID-19–related information, and monitoring the health conditions of the general population in the Philippines. However, the limited end-user engagement in the features and feedback along the development cycle of mHealth technologies results in risks in adoption. The World Health Organization (WHO) recommends user-centric design and development of mHealth technologies to ensure responsiveness to the needs of the end users. Objective The goal of the study is to understand, using end users’ perspectives, the design and quality of mHealth technology implementations in the Philippines during the COVID-19 pandemic, with a focus on the areas identified by stakeholders: (1) utility, (2) technology readiness level, (3) design, (4) information, (5) usability, (6) features, and (7) security and privacy. Methods Using a descriptive qualitative design, we conducted 5 interviews and 3 focus group discussions (FGDs) with a total of 16 participants (6, 37.5%, males and 10, 62.5%, females). Questions were based on the Mobile App Rating Scale (MARS). Using the cyclical coding approach, transcripts were analyzed with NVivo 12. Themes were identified. Results The qualitative analysis identified 18 themes that were organized under the 7 focus areas: (1) utility: use of mHealth technologies and motivations in using mHealth; (2) technology readiness: mobile technology literacy and user segmentation; (3) design: user interface design, language and content accessibility, and technology design; (4) information: accuracy of information and use of information; (5) usability: design factors, dependency on human processes, and technical issues; (6) features: interoperability and data integration, other feature and design recommendations, and technology features and upgrades; and (7) privacy and security: trust that mHealth can secure data, lack of information, and policies. To highlight, accessibility, privacy and security, a simple interface, and integration are some of the design and quality areas that end users find important and consider in using mHealth tools. Conclusions Engaging end users in the development and design of mHealth technologies ensures adoption and accessibility, making it a valuable tool in curbing the pandemic. The 6 principles for developers, researchers, and implementers to consider when scaling up or developing a new mHealth solution in a low-resource setting are that it should (1) be driven by value in its implementation, (2) be inclusive, (3) address users’ physical and cognitive restrictions, (4) ensure privacy and security, (5) be designed in accordance with digital health systems’ standards, and (6) be trusted by end users.

Background In the Philippines, various mobile health apps were implemented during the COVID-19 pandemic with very little knowledge in terms of their quality. The aims of this paper were 1) to systemically search for mobile apps with COVID-19 pandemic use case that are implemented in the Philippines; 2) to assess the apps using Mobile App Rating Scale (MARS); and 3) to identify the critical points for future improvements of these apps. Methods To identify existing mobile applications with COVID-19 pandemic use case employed in the Philippines, Google Play and Apple App Stores were systematically searched. Further search was conducted using the Google Search. Data were extracted from the app web store profile and apps were categorized according to use cases. Mobile apps that met the inclusion criteria were independently assessed and scored by two researchers using the MARS—a 23-item, expert-based rating scale for assessing the quality of mHealth applications. Results A total of 27 apps were identified and assessed using MARS. The majority of the apps are designed for managing exposure to COVID-19 and for promoting health monitoring. The overall MARS score of all the apps is 3.62 points (SD 0.7), with a maximum score of 4.7 for an app used for telehealth and a minimum of 2.3 for a COVID-19 health declaration app. The majority (n = 19, 70%) of the apps are equal to or exceeded the minimum “acceptable” MARS score of 3.0. Looking at the categories, the apps for raising awareness received the highest MARS score of 4.58 (SD 0.03) while those designed for managing exposure to COVID-19 received the lowest mean score of 3.06 (SD 0.6). Conclusions There is a heterogenous quality of mHealth apps implemented during the COVID-19 pandemic in the Philippines. The study also identified areas to better improve the tools. Considering that mHealth is expected to be an integral part of the healthcare system post-pandemic, the results warrant better policies and guidance in the development and implementation to ensure quality across the board and as a result, positively impact health outcomes.

Background A conversational agent powered by artificial intelligence, commonly known as a chatbot, is one of the most recent innovations used to provide information and services during the COVID-19 pandemic. However, the multitude of conversational agents explicitly designed during the COVID-19 pandemic calls for characterization and analysis using rigorous technological frameworks and extensive systematic reviews. Objective This study aims to describe the general characteristics of COVID-19 chatbots and examine their system designs using a modified adapted design taxonomy framework. Methods We conducted a systematic review of the general characteristics and design taxonomy of COVID-19 chatbots, with 56 studies included in the final analysis. This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to select papers published between March 2020 and April 2022 from various databases and search engines. Results Results showed that most studies on COVID-19 chatbot design and development worldwide are implemented in Asia and Europe. Most chatbots are also accessible on websites, internet messaging apps, and Android devices. The COVID-19 chatbots are further classified according to their temporal profiles, appearance, intelligence, interaction, and context for system design trends. From the temporal profile perspective, almost half of the COVID-19 chatbots interact with users for several weeks for >1 time and can remember information from previous user interactions. From the appearance perspective, most COVID-19 chatbots assume the expert role, are task oriented, and have no visual or avatar representation. From the intelligence perspective, almost half of the COVID-19 chatbots are artificially intelligent and can respond to textual inputs and a set of rules. In addition, more than half of these chatbots operate on a structured flow and do not portray any socioemotional behavior. Most chatbots can also process external data and broadcast resources. Regarding their interaction with users, most COVID-19 chatbots are adaptive, can communicate through text, can react to user input, are not gamified, and do not require additional human support. From the context perspective, all COVID-19 chatbots are goal oriented, although most fall under the health care application domain and are designed to provide information to the user. Conclusions The conceptualization, development, implementation, and use of COVID-19 chatbots emerged to mitigate the effects of a global pandemic in societies worldwide. This study summarized the current system design trends of COVID-19 chatbots based on 5 design perspectives, which may help developers conveniently choose a future-proof chatbot archetype that will meet the needs of the public in the face of growing demand for a better pandemic response.