Journal of Medical Internet Research

Engagement with suicide-related content online is often assumed to be harmful, yet many individuals with lived experience describe such content as supportive or even life-preserving. Despite policy and clinical concerns, little is known about how people intentionally or unintentionally encounter this content, how they interpret it, and how these experiences shape perceived harm or benefit.

Patients with cancer frequently experience complex and multidimensional symptom burdens. Standardized patient-reported outcome measures provide structured approaches to symptom assessment but may not capture the full range of symptom-related and psychosocial concerns expressed in patients’ narratives. Patient-generated social media data offer a complementary source for examining how these concerns are expressed online.

Unemployment has economic consequences and is associated with emotional distress and impairment. Joblessness is often associated with depression, leading to a vicious cycle of reduced drive to seek work, deepening financial stress, and worsening depression. Few scalable interventions exist that integrate job-search strategies with cognitive behavioral techniques.

Clinical practice guidelines are central instruments of evidence-based care; yet, in many domains, particularly rare or complex diseases, multiple guidelines coexist and frequently offer conflicting advice. Existing strategies for resolving such divergences are often labor-intensive, opaque, and insufficiently reproducible.

Pediatric health care systems face increasing uncertainty driven by rapid technological change, workforce shifts and shortages, environmental threats, and evolving family and community needs. Pediatrics requires future-focused considerations that go beyond adult systems, including family-centered care, developmental trajectories, and long-term societal impacts on child well-being. While the future cannot be predicted, futures medicine methods offer structured approaches to anticipate change and support proactive, values-driven planning. This Viewpoint describes the application of pediatric futures methods within an academic, independent nonprofit pediatric health system and proposes a practical framework that connects future readiness to strategic decision-making and daily care delivery. Futures medicine methods are not new in pediatric health care but may not be visible from the front line of care delivery, which provides an opportunity for clinical, operational, administrative, and enterprise leaders to implement these methods in their workflows. This paper introduces the discover to deliver pediatric futures framework, a continuum that links long-range futures discovery to near-term strategic planning, operational design, implementation, and outcome demonstration, emphasizing future methods and activities for applicable use.

Voice disorders are common, yet access to timely specialist assessment is often limited. Automated analysis of short voice recordings may support early screening, but achieving robust performance on heterogeneous clinical datasets remains challenging.

AI-based clinical decision support systems (AI-CDSSs) can help primary care clinicians provide higher quality care amid rising case complexity and resource constraints. However, evidence regarding their effectiveness and safety in primary care practice is lacking.

Conventional triage relies on clinician judgment and limited information available at first contact. AI and machine learning (ML) may improve early risk stratification, whereas tele-triage and patient-facing tools primarily support remote assessment, access, and care routing.

The rise of video-based social media platforms and the shift toward a video-first content strategy by social media companies have altered how people consume and engage with food-related content. However, little is known about how young adults experience, interpret, and are influenced by food-related videos on social media across different national and cultural contexts.