JMIR Formative Research

Children undergoing cancer treatment experience a range of treatment-related toxicities that significantly affect quality of life and adherence to therapy. Current methods for symptom reporting rely heavily on clinician interpretation of caregiver or child verbal reports, which can result in incomplete or inaccurate records. The Pediatric Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (Pediatric PRO-CTCAE; National Cancer Institute) provides a validated mechanism for direct symptom reporting by children and caregivers, yet its traditional administration and preselection of questions limit the breadth of symptom capture.

Marijuana initiation among adults aged 50 years and older has increased substantially. Although acute tetrahydrocannabinol exposure can impair psychomotor function, less is known about how real-world medical marijuana initiation relates to functional tasks such as driving in mid-to-late life.

Childhood obesity constitutes a complex medical and psychosocial challenge that requires both nutritional knowledge and sensitive, relationship-oriented doctor-patient communication. The Planetary Health Diet links individual health promotion with environmental sustainability and represents a relevant framework for contemporary medical education.

Environmental exposures such as heat and air pollution are critical determinants of health, yet traditional assessment methods rely on stationary monitors or residential address proxies that fail to capture the exposures that individuals experience throughout the day.

Management of contacts to medical communication centers relies heavily on clinical judgment, contextual understanding, and communication skills. Decision support systems, intended to complement medical expertise, may, due to their rigidity, impede effective caller interaction and may, together with the obligatory documentation of calls, contribute to a workflow that draws attention away from the communication. Recommender systems have demonstrated potential in supporting decision-making across various domains by nudging individuals toward better choices without undermining autonomy. We built a prototype that combined artificial intelligence–based question recommendations with structured documentation (hereafter: the prototype) and conducted a feasibility study to test its influence on operators’ performance.

The European General Data Protection Regulation (GDPR) strictly regulates the processing of personal and health-related data, posing challenges for digital health research, especially when data are collected using participants’ own devices. Although scientific data can theoretically be anonymized, standard internet communication protocols inevitably expose transmission metadata, preventing true anonymization. Existing solutions, including virtual private networks, reverse proxies, and trust centers, improve confidentiality but do not technically or legally enable fully anonymized data collection. Consequently, large-scale digital health research often requires extensive organizational measures, complex consent procedures, and high regulatory overhead.

Breast cancer is the most commonly diagnosed cancer among women and is the leading cause of cancer death among Latina individuals. Breast cancer survivors are at increased risk of obesity. Mobile health interventions have been shown to be an effective way of reducing the risk of weight gain. Less studied but also important is the extent to which social networks play a role in supporting or undermining weight loss efforts.

Substance use disorders (SUDs) are a major public health concern, contributing to significant individual and societal costs. Despite this, the uptake of evidence-based pharmacologic and behavioral interventions remains limited. The digital delivery of SUD treatment has emerged as a potentially scalable way to reduce access barriers and increase treatment use. Existing digital therapeutic interventions are often created without clinician involvement, evidence-based materials, interdisciplinary input, or content review. The implementation of a structured and methodologically rigorous development process is needed across digital health interventions to help ensure patient-facing materials are validated, understandable, and actionable for the end user.

Society faces multiple challenges, including lifestyle diseases and global climate change. Framing health education within sustainable development may enhance motivation for behavior change because proenvironmental behaviors, as well as healthy behaviors, often rely on the same behavior change principles. Combining these perspectives may therefore reinforce health behaviors and climate-friendly choices.

In a retrospective study of 40 individuals with Parkinson disease, lower visual equilibrium scores (as measured by the sensory organization test, condition 2) were significantly associated with a higher frequency of falls.

The application of artificial intelligence (AI) is increasingly valuable as a tool and assistant in many areas of clinical and academic medicine. Generative AI (GenAI) creates new content used by large language models, which can generate language that strongly resembles or even improves on that of humans. Learners and educators in many areas of education are using GenAI for essays and assessments, raising issues regarding learning and assessment. GenAI is also raising new concerns in health professions education (HPE), an area of health professions training that sometimes has different aims and assessment methods compared to its clinical counterparts. HPE needs to assess levels of knowledge and understanding of pedagogy, and the use of GenAI presents challenges to its current assessments, which are predominantly written.

Major depressive disorder (MDD) affects millions of Americans each year and is often diagnosed and treated in primary care. Evidence shows that self-management techniques, shared decision-making (SDM), and goal setting are effective strategies for managing MDD, but the required collaboration between patients and primary care clinicians can be difficult. Primary Care Path is a program for supporting depression management in primary care that includes a patient-facing mobile app and an accompanying care team–facing web interface. Leveraging programs that provide clinician-facing software with companion patient-facing mobile technology may help patients and physicians align depression treatment and management goals, support effective SDM, alleviate barriers, and improve both clinical care and patient outcomes.