Journal of Medical Internet Research

Malnutrition is prevalent among children with cancer and is often exacerbated by diminished appetite. To combat this, hospitalized children are increasingly adopting mukbang, a popular online eating show genre.

Health care is undergoing rapid change due to digitalization, artificial intelligence, data-driven decision-making, and shifting patient needs. These developments raise complex ethical, social, and organizational questions that cannot always be addressed by conventional research methods alone. There is a growing need for tools that help stakeholders imagine alternative futures to surface underlying values. Futures studies and speculative fiction respond to this need by presenting “what if” scenarios that make uncertain futures concrete and discussable, enabling dialogue among diverse stakeholders such as health care professionals, researchers, policy makers, and decision makers. This paper examines how speculative fiction can be used as a structured yet imaginative tool in health care research. It positions speculative fiction as a tool within futures studies and participatory research approaches, outlining its conceptual grounding and clarifying its role that stimulates interpretation and reflection within methods such as focus groups, workshops, and surveys. In this way, speculative fiction complements established approaches such as human-centered design, contextual inquiry, and value specification by addressing what does not yet exist and making abstract future issues tangible. The paper presents a case study, The Digital Data Divide, in which speculative fiction was used to explore the use of personal data in health care. Two contrasting short films were developed to stimulate dialogue and invite participants to reflect on associated values. Insights from this case are structured into a 6-step practical reporting guide: determining whether speculative fiction fits the research aim, choosing an appropriate form of speculative fiction, creating or selecting speculative scenarios, engaging participants, analyzing responses, and sharing and disseminating results. Across these steps, the paper discusses methodological and ethical considerations, including alignment between scenarios and study aims, balancing utopian and dystopian elements, questions of plausibility and interpretability, and the need for researcher reflexivity. Overall, this paper contributes to the growing discussion on future-oriented tools in health care research by showing how speculative fiction can help address complex and uncertain challenges in ways that are accessible to a wide range of stakeholders and that support dialogue across perspectives, provided that its use is ethically transparent, methodologically explicit, and carefully reported. The paper concludes with a call to other researchers to also experiment with speculative fiction and to share their experiences with the health care research community to learn and advance its use.

Regular moderate-to-vigorous physical activity (MVPA) reduces the risk of noncommunicable diseases, yet one-third of adults globally fail to meet MVPA recommendations. Office employees, among the least active groups, face heightened risks due to prolonged sedentary behavior and barriers like lack of time, fatigue, and low motivation. Although scalable, web-based interventions frequently face challenges, such as low engagement, high attrition, and limited personalization. Blended interventions, combining digital tools with interactive components, show promise but lack robust evidence among office employees.

Digital tools continue to evolve and have the potential to improve health care delivery. However, they are associated with challenges, including accessibility issues and health misinformation. Individuals need eHealth literacy (eHL) to reliably use these tools, and providers require appropriate eHL measurement approaches to offer targeted solutions. For around 2 decades, researchers have been operationalizing and measuring eHL.

Survivors of cardiac arrest often face multifaceted challenges—cognitive, emotional, physical, and existential—that extend beyond clinical recovery. Despite these long-term consequences, follow-up care is often insufficient, and access to reliable information and support remains limited. Broader initiatives to address post–cardiac arrest care are still lacking. This qualitative study represents the initial phase of a multiphase development process to cocreate, design, and later evaluate a web-based support and learning platform for cardiac arrest survivors. The platform is intended to complement existing health care services and support survivors in managing life after cardiac arrest.

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Applying digital health technologies (DHTs) for health promotion and disease prevention is recommended by official bodies such as the World Health Organization. User-centered co-design with systematic patient and public involvement is considered best practice for developing such complex interventions. Although well-established methodological guides and frameworks are available, an important gap is that they are either holistic but generic, offering minimal operational guidance, or context-specific and operational, but focusing only on subphases of establishing DHT-enhanced interventions.

Many inductive reviews exploring telehealth and its application in health care have identified missing or inconsistently reported implementation data, calling for a standardized approach to telehealth research.

Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. The complexity of guideline-concordant care and unstructured clinical data has driven demand for decision-support tools. Large language models (LLMs) show promise for processing clinical data and patient–provider communication, yet evidence is fragmented, and a CRC-specific synthesis across the full care continuum is lacking.

The transition from adolescence to young adulthood (age 10‐25 years) constitutes a sensitive developmental period marked by rapid biological, psychological, and social change, during which preventive health interventions can shape long-term outcomes. Mobile health tools offer accessible opportunities for tailored support for this population, but often adapt poorly to dynamic contexts, resulting in inconsistent engagement and effects. Just-in-time adaptive interventions (JITAIs), which tailor support in real time using ongoing data, are increasingly explored as precision health strategies. However, how these mechanisms are designed, implemented, and evaluated for adolescents and young adults (AYAs) has not been systematically reviewed.

The reliability of general-purpose large language models (LLMs) for complex clinical tasks in specialized domains such as microsatellite instability (MSI) cancers remains critically uncharacterized. The absence of a domain-specific benchmark to evaluate and guide the optimization of their capabilities across diverse clinical tasks poses unevaluated risks to patient safety.

Artificial intelligence (AI) is increasingly applied in medicine, including clinical decision-making. AI-based decision support systems (DSS) can enhance early risk detection and treatment optimization. However, the perspectives of patients and their support persons on AI-assisted DSS in clinical care, particularly regarding shared decision-making (SDM), remain underexplored.