Journal of Medical Internet Research
The leading peer-reviewed journal for digital medicine and health and health care in the internet age.
Editor-in-Chief:
Gunther Eysenbach, MD, MPH, FACMI, Founding Editor and Publisher; Adjunct Professor, School of Health Information Science, University of Victoria, Canada
Impact Factor 5.8 CiteScore 14.4
Recent Articles

The digital landscape has become a vital platform for public health discourse, particularly concerning important topics like organ donation. With a global rise in organ transplant needs, fostering public understanding and positive attitudes toward organ donation is critical. Social media platforms, such as X, contain conversations from the public, and key stakeholders maintain an active presence on the platform.

Many digital interventions for unhealthy alcohol use are based on personalized normative feedback (PNF) and personalized feedback on risks for health (PFR). The hypothesis is that PNF and PFR affect drinkers’ perceptions of drinking norms and risks, resulting in changes in drinking behaviors. This study is a follow-up mediation analysis of the primary and secondary outcomes of a randomized controlled trial testing the effect of a smartphone-based intervention to reduce alcohol use.


The integration of artificial intelligence (AI) systems for automating medical history taking and triage can significantly enhance patient flow in health care systems. Despite the promising performance of numerous AI studies, only a limited number of these systems have been successfully integrated into routine health care practice. To elucidate how AI systems can create value in this context, it is crucial to identify the current state of knowledge, including the readiness of these systems, the facilitators of and barriers to their implementation, and the perspectives of various stakeholders involved in their development and deployment.

Mumps is a viral respiratory disease characterized by facial swelling and transmitted through respiratory secretions. Despite the availability of an effective vaccine, mumps outbreaks have reemerged globally, including in China, where it remains a significant public health issue. In Yunnan province, China, the incidence of mumps has fluctuated markedly and is higher than that in mainland China, underscoring the need for improved outbreak prediction methods. Traditional surveillance methods, however, may not be sufficient for timely and accurate outbreak prediction.

Mobile health (mHealth) tools have the potential to reduce the burden of chronic conditions that disproportionately affect Hispanic and Latinx communities; however, digital divides in the access to and use of health technology suggest that mHealth has the potential to exacerbate, rather than reduce, these disparities.

Artificial intelligence (AI) has the potential to revolutionize health care by enhancing both clinical outcomes and operational efficiency. However, its clinical adoption has been slower than anticipated, largely due to the absence of comprehensive evaluation frameworks. Existing frameworks remain insufficient and tend to emphasize technical metrics such as accuracy and validation, while overlooking critical real-world factors such as clinical impact, integration, and economic sustainability. This narrow focus prevents AI tools from being effectively implemented, limiting their broader impact and long-term viability in clinical practice.

Medication-related harm, including adverse drug events (ADEs) and medication errors, represents a significant iatrogenic burden in clinical care. Digital health technology (DHT) interventions can significantly enhance medication safety outcomes. Although the clinical effectiveness of DHT for medication safety has been relatively well studied, much less is known about the cost-effectiveness of these interventions.

Health care is experiencing new opportunities in the emerging digital landscape. The metaverse, a shared virtual space, integrates technologies such as augmented reality, virtual reality, blockchain, and artificial intelligence. It allows users to interact with immersive digital worlds, connect with others, and explore unknowns. While the metaverse is gaining traction across various medical disciplines, its application in thyroid diseases remains unexplored. Subclinical hypothyroidism (SCH) is the most common thyroid disorder during pregnancy and is frequently associated with adverse pregnancy outcomes.

Cervical cancer remains the fourth leading cause of death among women globally, with a particularly severe burden in low-resource settings. A comprehensive approach—from screening to diagnosis and treatment—is essential for effective prevention and management. Large language models (LLMs) have emerged as potential tools to support health care, though their specific role in cervical cancer management remains underexplored.

Implementation of patient-reported outcome measures (PROMs) in clinical practice is challenging. We believe effective communication is key to realizing the clinical benefits of PROMs. Communication processes for PROMs in clinical practice typically involve (1) health care professionals (HCPs) inviting patients to complete PROMs, (2) patients completing PROMs, (3) HCPs and patients interpreting the resulting patient-reported outcomes (PROs), and (4) HCPs and patients using PROs for health management. Yet, communication around PROMs remains underexplored. Importantly, patients differ in their skills, knowledge, preferences, and motivations for completing PROMs, as well as in their ability and willingness to interpret and apply PROs in managing their health. Despite this, current communication practices often fail to account for these differences. This paper highlights the importance of personalized communication to make PROMs accessible to diverse populations. Personalizing communication manually is highly labor-intensive, but several digital technologies can offer a feasible solution to accommodate various patients. Despite their potential, these technologies have not yet been applied to PROMs. We explore how existing principles and tools, such as automatic data-to-text generation (including multimodal outputs like text combined with data visualizations) and conversational agents, can enable personalized communication of PROMs in practice.
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