Background: Digital health technologies are widely used for disease management, with their computing platforms, software, and sensors being used for health care. These technologies are developed to manage chronic diseases and infectious bacterial diseases, including tuberculosis (TB). Objective: This study aims to comprehensively review the literature on the use of digital health interventions (DHIs) for enhancing TB treatment adherence and identify major strategies for their adoption. Methods: We conducted a literature search in the PubMed, Cochrane Library, Ovid Embase, and Scopus databases for relevant studies published between January 2012 and March 2022. Studies that focused on web-based or mobile phone–based interventions, medication adherence, digital health, randomized controlled trials, digital interventions, or mobile health and ubiquitous health technology for TB treatment and related health outcomes were included. Results: We identified 27 relevant studies and classified them according to the intervention method, a significant difference in treatment success, and health outcomes. The following interventions were emphasized: SMS text messaging interventions (8/27, 30%), medicine reminders (6/27, 22%), and web-based direct observation therapy (9/27, 33%). Digital health technology significantly promoted disease management among individuals and health care professionals. However, only a few studies addressed 2-way communication therapies, such as interactive SMS text messaging and feedback systems. Conclusions: This scoping review classified studies on DHIs for patients with TB and demonstrated their potential for the self-management of TB. DHIs are still being developed, and evidence on the impact of digital technologies on enhancing TB treatment adherence remains limited. However, it is necessary to encourage patients’ participation in TB treatment and self-management through bidirectional communication. We emphasize the importance of developing a communication system.

Background: Tuberculosis (TB) is a highly infectious disease. Negative perceptions and insufficient knowledge have made its eradication difficult. Recently, mobile health care interventions, such as an anti-TB chatbot developed by the research team, have emerged in support of TB eradication programs. However, before the anti-TB chatbot is deployed, it is important to understand the factors that predict its acceptance by the population. Objective: This study aims to explore the acceptance of an anti-TB chatbot that provides information about the disease and its treatment to people vulnerable to TB in South Korea. Thus, we are investigating the factors that predict technology acceptance through qualitative research based on the interviews of patients with TB and homeless facility personnel. We are then verifying the extended Technology Acceptance Model (TAM) and predicting the factors associated with the acceptance of the chatbot. Methods: In study 1, we conducted interviews with potential chatbot users to extract the factors that predict user acceptance and constructed a conceptual framework based on the TAM. In total, 16 interviews with patients with TB and one focus group interview with 10 experts on TB were conducted. In study 2, we conducted surveys of potential chatbot users to validate the extended TAM. Survey participants were recruited among late-stage patients in TB facilities and members of web-based communities sharing TB information. A total of 123 responses were collected. Results: The results indicate that perceived ease of use and social influence were significantly predictive of perceived usefulness (P=.04 and P<.001, respectively). Perceived usefulness was predictive of the attitude toward the chatbot (P<.001), whereas perceived ease of use (P=.88) was not. Behavioral intention was positively predicted by attitude toward the chatbot and facilitating conditions (P<.001 and P=.03, respectively). The research model explained 55.4% of the variance in the use of anti-TB chatbots. The moderating effect of TB history was found in the relationship between attitude toward the chatbot and behavioral intention (P=.01) and between facilitating conditions and behavioral intention (P=.02). Conclusions: This study can be used to inform future design of anti-TB chatbots and highlight the importance of services and the environment that empower people to use the technology.

A design process that involves the participation of children should effectively elicit the needs of child users by considering characteristics such as their age-appropriate levels of cognitive ability, shyness, language skills, and motor-sensory capabilities. Since the 1960s, a variety of methods and guidelines have emerged specialising in children. Participatory design deals with the problem of enabling users to participate in the design process and with the task of generating ideas by means of generative toolkits and workshops. Hence, participatory design enables designers to look at problems from a child's standpoint and, simultaneously, deal with childhood traits such as shyness and immature language skills. This paper introduces two participatory design toolkits: namely Info Block and Info Tree. These toolkits enable users to build information architecture (IA) that can, firstly, reflect their cognitive characteristics and, secondly, elicit user needs with respect to the information architecture design of children's websites. In a case study, the toolkits were used to evaluate the usability of the Yahoo!® Kids (Korea) directory. The results show that the information architecture of children differs from that of adults in depth, breadth, and clarity of contents and logicality. Finally, suggestions are made to improve the usability of children's websites.

Smart homes are a strong match for the characteristics of product-service systems (PSSs), but practitioners lack the knowledge necessary to approach their designs from a systemic perspective. Positing that smart home appliances (SHAs) are the building blocks of smart homes as competitive PSSs, this article investigates the attributes of SHAs as design elements and the advantages of PSSs as design goals. Based on systematic literature reviews and interviews with SHA experts in South Korea, the authors propose a revised set of SHA attributes and discuss the two focal areas for developing competitive PSSs with SHAs: smartness for personalized user experiences and smartness for expanded cooperation. The article contributes to the fast-changing smart home industry by capturing the attributes that define today’s SHAs, demonstrating that these attributes can contribute to the development of smart homes as a competitive PSS, and identifying areas of focus for those who develop SHAs and systems.