A Joint LLM-KG System for Disease Q&A.

Medical question answer (QA) assistants respond to lay users' health-related queries by synthesizing information from multiple sources using natural language processing and related techniques. They can serve as vital tools to alleviate issues of misinformation, information overload, and complexity of medical language, thus addressing lay users' information needs while reducing the burden on healthcare professionals. QA systems, the engines of such assistants, have often used large language models (LLMs) or knowledge graphs (KG), though the approaches could be complementary.

Determining containment policy impacts on public sentiment during the pandemic using social media data.

Stringent containment and closure policies have been widely implemented by governments to prevent the transmission of COVID-19. Yet, such policies have significant impacts on people’s emotions and mental well-being. Here, we study the effects of pandemic containment policies on public sentiment in Singapore.

Personalization of Intervention Timing for Physical Activity: Scoping Review.

Background: The use of sensors in smartphones, smartwatches, and wearable devices has facilitated the personalization of interventions to increase users' physical activity (PA). Recent research has focused on evaluating the effects of personalized interventions in improving PA among users. However, it is critical to deliver the intervention at an appropriate time to each user to increase the likelihood of adoption of the intervention.

Factors influencing user's adherence to physical activity applications: A scoping literature review and future directions.

Background: Although mobile app-delivered physical activity (PA) interventions have the potential to promote exercise, poor adherence to these apps is a common issue impeding their effectiveness. Gaining insights into the factors that influence PA app adherence is an important priority for app developers and intervention designers.

Objective: The objective of this study is to perform a literature review to synthesize the factors influencing PA app adherence and to identify directions for future research in this area.

Mobile-Based Interventions for Dietary Behavior Change and Health Outcomes: Scoping Review.

Background: Mobile apps are being widely used for delivering health interventions, with their ubiquitous access and sensing capabilities. One such use is the delivery of interventions for healthy eating behavior.

Objective: The aim of this study was to provide a comprehensive view of the literature on the use of mobile interventions for eating behavior change.

Combined interventions for physical activity, sleep, and diet using smartphone apps: A scoping literature review.

Background: The use of smartphone apps to track and manage physical activity (PA), diet, and sleep is growing rapidly. Many apps aim to change individual behavior on these three key health dimensions (PA, sleep, diet) by using various interventions. Earlier reviews have examined interventions using smartphone apps for one or two of these dimensions.