JMIR Research Protocols

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental condition affecting approximately 7% to 8% of children and adolescents, characterized by persistent inattention, hyperactivity, and impulsivity. Adolescence represents a period of heightened vulnerability, during which pharmacological treatments are frequently limited by adverse effects, suboptimal adherence, and partial response. Physical exercise, particularly high-intensity interval training (HIIT), has demonstrated superior effects on inhibitory control and inattention compared with moderate-intensity continuous exercise. However, the repetitive nature and high perceived exertion of traditional HIIT protocols result in poor adherence, especially in individuals with ADHD. Virtual reality (VR)–based exergames have been proposed as a strategy to sustain vigorous physiological demands while maintaining intrinsic motivation. Despite this potential, the existing literature is predominantly limited by passive control conditions, which prevent adequate control for the effects of VR immersion and cognitive engagement, limiting causal inference regarding the specific contribution of physiological exertion.

Intensive care unit–acquired weakness (ICU-AW) research focuses predominantly on intrinsic muscle pathology rather than integrated systemic interactions, which are commonly studied in exercise science. Peak oxygen uptake (), on/off kinetics, and skeletal muscle oxygenation provide a quantitative evaluation of exercise capacity and are infrequently measured in intensive care unit (ICU) survivors. Routine cardiopulmonary exercise test (CPET) research separates and kinetics assessments into multiple sessions. Yet, a combined experimental approach may enhance diagnosis, follow-up retention, and mechanistic insight for patients with ICU-AW.

Type 1 diabetes mellitus (T1DM) in children requires sustained self-management to achieve glycemic targets. Continuous glucose monitoring (CGM) has transformed pediatric diabetes care; yet, adherence to device wear remains inconsistent. In May 2024, Oman launched a national initiative distributing CGMs to children with T1DM across all governorates, creating a real-world opportunity to study adherence determinants and to develop a locally validated AI-assisted predictive tool.

Artificial intelligence (AI) has the potential to transform chest radiography interpretation by enhancing diagnostic accuracy, identifying subtle findings, reducing errors, and helping prioritize patient care. Although chest radiography remains a cost-effective and widely used imaging tool, its effectiveness is limited by overlapping anatomy and variability in clinical expertise. Integrating AI can help overcome some of these challenges, especially in resource-constrained settings. However, robust validation in real-world clinical contexts is essential before widespread implementation. This study protocol evaluates whether AI assistance improves general practitioners’ ability to detect radiographic findings on chest radiography in adults with respiratory complaints or those undergoing treatment for respiratory diseases compared with unaided interpretation. Potential benefits include increased diagnostic safety, higher physician confidence, more efficient workflows, and expanded access to expert support in underserved areas.

Head and neck squamous cell carcinomas (HNSCCs) cause considerable morbidity and mortality. Multimodal treatment strategies can cause significant toxicity, and therapy options are limited for recurrent disease. Immunotherapy has emerged as a promising approach. However, patient response variability underscores the need for better predictive markers.

Patients with Alzheimer disease commonly rely on family caregivers for daily functioning. Research shows that relationships between caregivers and persons with memory loss have important effects on the health and well-being of both caregivers and persons with memory loss. However, most studies rely on a single caregiver–person with memory loss dyad as the unit of analysis, thereby neglecting the broader network of caregivers who collectively shape care experiences and outcomes.

Diabetes mellitus encompasses disorders characterized by hyperglycemia due to pancreatic β-cell dysfunction. Type 2 diabetes (T2D) constitutes over 90% of cases, with a background of genetic, metabolic, and environmental risk factors. Knowing that sex differences impact insulin resistance and glycemic control, this review aims to identify differences in adherence to dietary patterns between women and men with T2D.

Zimbabwe currently faces a rapidly escalating burden of noncommunicable diseases (NCDs) concurrently with persistent communicable disease challenges, resulting in profound epidemiological differences between rural and urban populations. To effectively address this evolving epidemiological landscape and guide evidence-based public health interventions, reliable and high-quality longitudinal data are essential for capturing temporal shifts and contextual determinants often overlooked by conventional health information systems.

Cigarettes are a global public health concern, as cigarette smoking is the leading cause of death in the United States and throughout most high-income countries. Exposure to tobacco retail has been linked to adverse smoking outcomes, but research using naturalistic and causal approaches to quantify these effects in the real world remains relatively sparse. To address these gaps, this study used geolocation tracking, ecological momentary assessment, and neuroimaging to assess smoking outcomes in daily life and conducted a randomized controlled trial focused on the effects of exposure to tobacco retail.

Kidney transplant recipients present reduced physical function and a high prevalence of cardiometabolic complications, which increase cardiovascular risk and compromise long-term graft outcomes. Resistance training has demonstrated beneficial effects in this population; however, previous interventions have shown heterogeneity in load prescription and have not incorporated objective monitoring of movement velocity. Velocity-based resistance training (VBT) allows precise regulation of exercise intensity and fatigue, potentially improving the safety and individualization of exercise prescription in clinical populations.

Ovarian cancer (OC) is a highly fatal gynecologic malignancy with complex management challenges and limited long-term survival for advanced stages. Large language models (LLMs)—including systems such as GPT-4, Claude, Google Gemini, and others—are emerging artificial intelligence (AI) tools capable of performing health care–related tasks such as diagnostic support, treatment planning, report generation, and patient communication. However, their applications in OC care have not yet been comprehensively assessed.

Advances in antiretroviral therapy have transformed HIV into a chronic condition, leading to a growing population of adults aged 50 years and older living with HIV in Canada and globally. These individuals experience higher rates of multimorbidity, frailty, cognitive changes, and polypharmacy than their HIV-negative peers, and many rely on caregivers for emotional and practical support. Caregiving often occurs within chosen families of partners, friends, and community members, yet these caregivers remain largely unrecognized in policies that prioritize bio-legal family structures. Existing person- and family-centered care (PFCC) models in HIV focus mainly on pediatric and adolescent populations, leaving a critical gap in guidance for older adults and their diverse caregivers.