(Journal of Medical Internet Research[TA])
11,403 results
  • User Acceptability and Adoption of AI-Generated Lifestyle Intervention Recommendations: Scoping Review and Theoretical Integration. [Review]
    J Med Internet Res. 2026 Jul 14; 28:e93573.Ma M, Sui T, … Lau PWCJM
  • CONCLUSIONS: This review extends prior AI and digital health reviews by shifting attention toward how users perceive, intend to follow, and enact AI-generated lifestyle recommendations. Acceptability and adoption appear to depend on systems eliciting and adapting to context, content being actionable and credible, users having the capacity to interpret, trust, and engage with recommendations while retaining control, and resources, routines, and social contexts allowing enactment. The framework can guide theory-driven evaluation, outcome selection, and system design by identifying where recommendation processes may succeed or fail, but should be interpreted as preliminary and evidence-informed rather than causal. By integrating implementation, behavioral, and human-AI perspectives, this review provides a foundation for moving AI-generated lifestyle recommendations from technically plausible outputs toward user-centered, context-sensitive, and behaviorally actionable support.
  • Concentration and Specialty Pair Patterns of Interdepartmental Consultations in Hospitalized Patients Using Real-World Data: Retrospective Cohort Study. [Journal Article]
    J Med Internet Res. 2026 Jul 14; 28:e81670.Zhang L, Liu S, … Qiu LJM
  • CONCLUSIONS: This study provides a novel, hospital-wide, network-based mapping of interdepartmental consultations using real-world data. Unlike prior work limited to single departments or diseases, it reveals that collaboration is concentrated, Pareto-like, and disease-driven. The identification of stable, disease-specific consultation pairs offers a data-driven framework for understanding multidisciplinary collaboration. These findings offer a data-driven framework for understanding multidisciplinary collaboration as a networked system. In practice, administrators and clinicians can use this evidence to prioritize resources, design standardized multidisciplinary team pathways, and implement spatial or digital interventions to reduce delays and improve patient flow and outcomes.
  • Factors Shaping Trust and Satisfaction With AI Medical Chatbots: A Mixed Methods Vignette Survey of Caregivers Seeking Guidance on Pediatric Infectious Diseases. [Journal Article]
    J Med Internet Res. 2026 Jul 14; 28:e88126.Huang R, Cecil J, … Chattopadhyay SJM
  • CONCLUSIONS: Existing evaluation frameworks only partially capture how caregivers assess medical chatbots. Caregivers valued actionable guidance, credible references, and clear reasoning over lengthy, exhaustive detail. Rather than passively receiving dense information, they preferred an interactive style in which the chatbot proactively proposed follow-up suggestions, helping them steer the conversation toward their specific needs. Reactions to empathetic language and medical disclaimers were context-dependent: features that built trust in some situations could seem insincere, excessive, or unnecessary in others. These findings suggest that future medical chatbots should move beyond one-size-fits-all communication and adapt to individual users' situations, preferences, and information needs. Evaluation protocols should likewise assess not only whether chatbot responses are accurate and comprehensive but also whether they are actionable, appropriately toned, and responsive to users' evolving needs over the course of a conversation.
  • Menopause Apps Offer Empowerment, but Pose Risks. [News]
    J Med Internet Res. 2026 Jul 13; 28:e106205.Glauser WJM
  • Increased health care and research attention to menopause, along with growing industry investment, has fueled a commercial boom in menopause-related products, services, and apps. In this News and Perspectives article, JMIR Correspondent Wendy Glauser reports on the benefits and risks associated with menopause apps.
  • Digital Outpatient Care for Patients With Type 1 Diabetes (DigiDiaS): Pragmatic Observational Pre-Post Study. [Journal Article]
    J Med Internet Res. 2026 Jul 13; 28:e94782.Spildo I, Holmen H, … Torbjørnsen AJM
  • CONCLUSIONS: This real-world pragmatic observational comparison under routine conditions demonstrates that reorganizing outpatient care for patients with type 1 diabetes into a flexible digital model, DigiDiaS care, did not result in statistically significant between-group differences in health outcomes, including self-management, glycemic control, and well-being, compared with usual care. Over 80% of participants in DigiDiaS care utilized the digital solution, with patient-initiated asynchronous messaging as the most frequently used feature.
  • AI Model Improves Interpretation of Cardiac Magnetic Resonance Imaging Scans. [News]
    J Med Internet Res. 2026 Jul 13; 28:e106121.Narang SKJM
  • Interpreting cardiac magnetic resonance imaging scans takes significant time and specialist expertise. In this News and Perspectives article, JMIR Correspondent Shalini Kathuria Narang reports on new research introducing an AI tool that may enhance accuracy and efficiency.
  • On the Road Again: Virtual Reality for Poststroke Rehabilitation. [News]
    J Med Internet Res. 2026 Jul 13; 28:e106124.Congdon JJM
  • Virtual reality (VR) has a long history in stroke rehabilitation. In this News and Perspectives article, JMIR Correspondent Jenna Congdon reports on one person's journey back to driving after a stroke, highlighting the strengths, limitations, and future of VR in rehabilitation.
  • Family Size and Longitudinal Outcomes of a Digital-Human Parenting Intervention in Chinese Preschool Families: Secondary Analysis. [Randomized Controlled Trial]
    J Med Internet Res. 2026 Jul 10; 28:e101388.Fang Z, He X, … Lachman JMJM
  • CONCLUSIONS: Family size might not always be associated with short-term intervention effectiveness but was associated with divergence in longer-term trajectories. These findings suggest that caregiving demands are relevant for the sustainability of intervention effects. By integrating baseline differences, short-term effects, and longitudinal trajectories within a single framework, this study highlights the importance of moving beyond average treatment effects to more dynamic, context-sensitive evaluations. Designing parenting interventions, particularly scalable digital-human programs, that incorporate sustained and context-responsive support may be critical for addressing variation in family structure and enhancing long-term effectiveness.
  • Artificial Intelligence for Evidence Synthesis of Emerging Biologics to Improve Skeletal Health in Osteogenesis Imperfecta: Systematic Review and Meta-Analysis. [Systematic Review]
    J Med Internet Res. 2026 Jul 10; 28:e85840.Li C, Dai Z, … Li XJM
  • CONCLUSIONS: This review is the first to synthesize and quantitatively compare skeletal outcomes across multiple biologics in OI with an AI-assisted review workflow. Denosumab and setrusumab demonstrate promising efficacy in improving lumbar spine aBMD across ages, although current evidence does not support superior fracture reduction over bisphosphonates. GPT-4o can substantially accelerate evidence synthesis but should be deployed with explicit human oversight in tasks requiring contextual understanding and clinical reasoning. These findings should be interpreted cautiously given the small and heterogeneous trial base. Taken together, our workflow presented how evidence synthesis may be scaled and operationalized in real-world rare disease research.