Journal of Medical Internet Research

Sub-Saharan Africa has been a technological hothouse when it comes to mobile phone technology adoption. However, evidence on the role played by mobile technology on infectious disease prevention has been mostly limited to experimental studies.

The prevalence of knee osteoarthritis (KOA) in the adult population is high and patients profit from individualized therapy approaches. Just-in-time adaptive interventions (JITAIs) are upcoming digital interventions for behavior change.

Over the past quarter-century, mobile health (mHealth) technologies have experienced significant changes in adoption rates, adaptation strategies, and instances of abandonment. Understanding the underlying factors driving these trends is essential for optimizing the design, implementation, and sustainability of interventions using these technologies. The evolution of mHealth adoption has followed a progressive trajectory, starting with cautious exploration and later accelerating due to technological advancements, increased smartphone penetration, and growing acceptance of digital health solutions by both health care providers and patients. However, alongside widespread adoption, challenges related to usability, interoperability, privacy concerns, and socioeconomic disparities have emerged, necessitating ongoing adaptation efforts. While many mHealth initiatives have successfully adapted to address these challenges, technology abandonment remains common, often due to unsustainable business models, inadequate user engagement, and insufficient evidence of effectiveness. This paper utilizes the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework to examine the interplay between the academic and industry sectors in patterns of adoption, adaptation, and abandonment, using 3 major mHealth innovations as examples: health-related SMS text messaging, mobile apps and wearables, and social media for health communication. Health SMS text messaging has demonstrated significant potential as a tool for health promotion, disease management, and patient engagement. The proliferation of mobile apps and devices has facilitated a shift from in-person and in-clinic practices to mobile- and wearable-centric solutions, encompassing everything from simple activity trackers to advanced health monitoring devices. Social media, initially characterized by basic text-based interactions in chat rooms and online forums, underwent a paradigm shift with the emergence of platforms such as MySpace and Facebook. This transition ushered in an era of mass communication through social media. The rise of microblogging and visually focused platforms such as Twitter(now X), Instagram, Snapchat, and TikTok, along with the integration of live streaming and augmented reality features, exemplifies the ongoing innovation within the social media landscape. Over the past 25 years, there have been remarkable strides in the adoption and adaptation of mHealth technologies, driven by technological innovation and a growing recognition of their potential to revolutionize health care delivery. Each mobile technology uniquely enhances public health and health care by catering to different user needs. SMS text messaging offers wide accessibility and proven effectiveness, while mobile apps and wearables provide comprehensive functionalities for more in-depth health management. Social media platforms amplify these efforts with their vast reach and community-building potential, making it essential to select the right tool for specific health interventions to maximize impact and engagement. Nevertheless, continued efforts are needed to address persistent challenges and mitigate instances of abandonment, ensuring that mHealth interventions reach their full potential in improving health outcomes and advancing equitable access to care.

Cannabis consumption has increased in recent years, as has cannabis use disorder. While researchers have explored public online community discussions of active cannabis use, less is known about the popularity and content of publicly available online communities intended to support cannabis cessation.

Cerebral hemorrhage is a critical medical condition that necessitates a rapid and precise diagnosis for timely medical intervention, including emergency operation. Computed tomography (CT) is essential for identifying cerebral hemorrhage, but its effectiveness is limited by the availability of experienced radiologists, especially in resource-constrained regions or when shorthanded during holidays or at night. Despite advancements in artificial intelligence–driven diagnostic tools, most require technical expertise. This poses a challenge for widespread adoption in radiological imaging. The introduction of advanced natural language processing (NLP) models such as GPT-4, which can annotate and analyze images without extensive algorithmic training, offers a potential solution.

Undernutrition is an underlying factor in nearly 50% of 1 million estimated annual deaths among Nigerian children aged <5 years. Inappropriate maternal infant and young child feeding (IYCF) practices are basic contributors to child undernutrition. Teenage motherhood exacerbates the problem of inadequate child feeding. One possible intervention method to improve IYCF knowledge and practices of teenage mothers is the use of mobile gaming technologies. Despite extreme poverty in low- and middle-income countries, a ubiquity of mobile phone networks exists.

Clinical narratives are essential components of electronic health records. The adoption of electronic health records has increased documentation time for hospital staff, leading to the use of abbreviations and acronyms more frequently. This brevity can potentially hinder comprehension for both professionals and patients.

In the complex and multidimensional field of medicine, multimodal data are prevalent and crucial for informed clinical decisions. Multimodal data span a broad spectrum of data types, including medical images (eg, MRI and CT scans), time-series data (eg, sensor data from wearable devices and electronic health records), audio recordings (eg, heart and respiratory sounds and patient interviews), text (eg, clinical notes and research articles), videos (eg, surgical procedures), and omics data (eg, genomics and proteomics). While advancements in large language models (LLMs) have enabled new applications for knowledge retrieval and processing in the medical field, most LLMs remain limited to processing unimodal data, typically text-based content, and often overlook the importance of integrating the diverse data modalities encountered in clinical practice. This paper aims to present a detailed, practical, and solution-oriented perspective on the use of multimodal LLMs (M-LLMs) in the medical field. Our investigation spanned M-LLM foundational principles, current and potential applications, technical and ethical challenges, and future research directions. By connecting these elements, we aimed to provide a comprehensive framework that links diverse aspects of M-LLMs, offering a unified vision for their future in health care. This approach aims to guide both future research and practical implementations of M-LLMs in health care, positioning them as a paradigm shift toward integrated, multimodal data–driven medical practice. We anticipate that this work will spark further discussion and inspire the development of innovative approaches in the next generation of medical M-LLM systems.

Approximately 4.5 million people live with type 2 diabetes mellitus (T2DM) in the United Kingdom. Evidence shows that structured education programs can improve glycemic control and reduce the risk of complications from T2DM, but they have low attendance rates. To widen access to T2DM structured education, National Health Service England commissioned a national rollout of Healthy Living, a digital self-management program.

In recent years, there has been an increase in the use of conversational agents for health promotion and service delivery. To date, health professionals’ views on the use of this technology have received limited attention in the literature.

Telehealth played a critical role during the COVID-19 pandemic and continues to function as an essential component of health care. Existing platforms cannot ensure privacy and prevent cyberattacks.

Regular physical activity is associated with improved quality of life in patients with inflammatory bowel diseases (IBDs), although much of the existing research is based on self-reported data. Wearable devices provide objective data on many rich physical activity dimensions including steps, duration, distance, and intensity. Little is known about how patients with IBDs engage in these varying dimensions of exercise and how it may influence their symptom and disease-specific patient-reported outcomes (PROs).