Journal of Medical Internet Research

Web-based surveys involving self-reported questionnaires are vulnerable to fraudulent responses. Advancements in artificial intelligence and bots have introduced additional challenges to preventing and identifying fraudulent responses to online questionnaires.

SMS text message reminders have been used to promote many health behaviors, such as improving diet and physical activity, managing chronic health conditions, reminding patients about medical appointments, and supporting medication adherence across a range of health conditions. Despite their promise, developing effective reminders tailored to specific patient populations is resource-intensive. AI may facilitate item development, and online research panels may provide an efficient way to test message content with target users prior to implementing large-scale trials.

Children with inattentive attention-deficit/hyperactivity disorder (ADHD) often present with impairments in executive functions and fine motor skills in addition to core inattentive symptoms. However, evidence remains limited regarding structured telerehabilitation-based fine motor training for these outcomes.

Motivation to quit smoking and decisions to smoke or forgo smoking vary throughout the day. However, little is known about how within-day patterns of psychological states such as self-efficacy and attitudes toward smoking relate to these determinants of smoking cessation attempts. Identifying these dynamic processes can inform the development of more precisely timed and tailored digital interventions.

Molecular Tumor Boards (MTBs) generate highly technical recommendations. The language used in their protocols is rarely accessible to patients. Lay-language patient protocols could support patient-clinician communication, yet manual production is difficult to sustain in high-volume oncology settings. Large language models (LLMs) may offer scalable drafting assistance, yet clinical usability remains largely uninvestigated under real-world deployment constraints. Existing evaluations rely predominantly on synthetic data or closed-source models that are incompatible with strict data protection requirements.

Cancer survivors often experience declining engagement in digital health interventions (DHIs). However, predictors of engagement with provider-guided DHIs remain unclear. Nurse WRITE (Nurse Written Representational Intervention To Ease Symptoms), an effective 8-week nurse-directed symptom management DHI, offers an opportunity to identify factors influencing engagement and enhance intervention efficacy evaluation.

AI is increasingly used to support clinical diagnosis, but the appropriate allocation of responsibility between clinicians and AI remains unclear. Different responsibility structures may influence how clinicians evaluate AI recommendations and revise their diagnostic judgments.

Delays in access to ambulatory care are associated with adverse health outcomes, diminished patient experience, and increased system inefficiencies. US health systems have adopted automated waitlists, a technology-enabled tool that notifies patients of earlier appointment availability. Existing case reports suggest benefits. However, there is limited evidence on the efficacy of adopting, implementing, and sustaining an automated waitlist to improve access.

Insomnia burdens patients with breast cancer, exceeding its prevalence in other malignancies. While excessive screen time is known to disrupt sleep in children and adolescents, its impact on patients with breast cancer remains underexplored, particularly regarding how perceived stigma may modify screen-related sleep disruption.

Men’s health urology faces growing challenges driven by workforce shortages, rising disease burden, and persistent disparities in care. Despite an increasing prevalence of conditions like benign prostatic hyperplasia, prostate cancer, and urinary tract infections, more than half of U.S. counties lack a practicing urologist. Stigma, access, and uncertainty lead men to delay care further, resulting in higher morbidity, late-stage diagnoses, and unsustainable costs. To meet these challenges, this paper explores the transformative potential of agentic AI systems to drive Healthcare 5.0 in urology to create a more equitable, efficient, and proactive care system. We examine how AI can advance the quintuple aim of health care: enhancing patient experience, improving population health, reducing costs, increasing provider satisfaction, and promoting health equity. The paper introduces the concept of a suite of specialized AI agents, rooted in both currently in use and developing AI applications, that work collaboratively to support providers, patients, and health care administrators across the continuum of care. These agents not only improve efficiency, streamline workflows, and augment clinical reasoning, but also enable scalable, virtual-first care delivery systems. We articulate our view of the future urology patient journey, illustrating how AI agents can transform each step of the process to provide an improved, seamless experience for patients and providers while maintaining human-centered, personalized care. Finally, we outline critical future directions, such as data interoperability, regulatory frameworks, and inclusive design principles, to ensure that AI technologies are deployed safely, equitably, and in line with ethical regulations. Through the strategic implementation of agentic AI, we view the future of men’s health urology as a model for innovation, driving better outcomes for patients and sustainable, meaningful care for providers.

Delirium is a serious condition characterized by an acute change in attention, arousal, and sleep disturbance. It is common in inpatients with Parkinson disease (PD) but is frequently missed or misidentified due to overlapping symptoms, such as cognitive impairment, hallucinations, and sleep disturbances. While clinical tools often measure only a snapshot of delirium, wearable devices could facilitate the identification and ongoing monitoring of delirium, including continuous assessment of activity and sleep patterns, which are frequently disrupted. Establishing feasibility is essential before wearable technologies can be implemented in routine clinical care.

In addition to core behavioral symptoms, children and adolescents with autism spectrum disorder (ASD) frequently exhibit impairments in executive function and motor performance. Although virtual reality (VR)–based physical exercise interventions are increasingly used in ASD rehabilitation, evidence regarding their multidimensional effects remains limited.