JMIR Research Protocols

Older patients with metastatic colorectal cancer (mCRC) are a heterogeneous population with wide variability in functional status, frailty, cognition, nutritional reserve, and comorbidity burden. Treatment decisions are often guided primarily by chronological age and performance status, which may not adequately capture vulnerability or patient-centered outcomes in this population.

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder characterized by impairments in social communication, restricted and repetitive behaviors, and deficits across multiple developmental domains. Although conventional interventions, including speech, behavioral, and occupational therapies, improve functional outcomes, many children continue to experience persistent cognitive and adaptive impairments. Ayurvedic formulations such as and possess neuroprotective, anti-inflammatory, antioxidant, and cognition-enhancing properties, but robust clinical evidence supporting their adjunctive use in ASD is limited.

Standardized metrics such as the numeric rating scale (NRS) provide essential quantitative pain benchmarks but can be augmented by capturing the functional and emotional context of a patient’s lived experience. Adding surveys creates a “contextual disconnect” (increasing data yield with diminishing insights) and adds patient burden. The CONNECT (Collecting Communication Data to Enhance Patient-Physician Interaction) study proposes a structured, multimodal framework integrating patient narratives, drawings, and mobility assessments to capture each patient’s holistic “pain story” and create a comprehensive ground truth dataset for developing digital health tools.

Existing adolescent pregnancy prevention programs have demonstrated modest effects. Evaluation is needed for interventions aimed at improving intermediary outcomes linked to behaviors associated with adolescent pregnancy prevention, including intentions, communication skills, decision-making skills, access to information, and supportive adult relationships. These intermediary outcomes often serve as mechanisms that decrease sexual behaviors associated with unintended pregnancy and sexually transmitted infection risk and enhance understanding of how interventions influence behavior. The US federal government announced a funding cycle aimed at assessing innovative programs for underserved youth. As 1 of the 12 grantees, we will evaluate Using the Connect (UTC), a novel game-based learning intervention offering opportunities to improve participants’ intention to delay sex, skills related to communication, decision-making, and accessing information, and strengthen their connection to a trusted adult.

Antimicrobial resistance poses a growing threat to patient safety worldwide. Nurses are central to antimicrobial management; however, their contribution to formal antimicrobial stewardship (AMS) programs remains poorly characterized. To our knowledge, no previous review has combined evidence on the effectiveness and implementation of nurse-led and nurse-involved AMS interventions, including Gulf Cooperation Council and Middle East and North Africa (GCC/MENA) subgroup analysis.

Stroke is the second leading cause of death worldwide. Cerebrovascular diseases (CVDs), including strokes and transient ischemic attacks (TIAs), cause long-term disabilities and economic burdens. Strokes can be ischemic, caused by blood clots; or hemorrhagic, caused by bleeding in the brain. Immediate diagnosis and treatment are crucial. Proper management of TIAs is essential due to the high risk of subsequent strokes. Currently, wearable sensors, AI-based prediction, and automatic video analysis are not used in CVD diagnosis and recovery estimation.

Chronic pain is a leading cause of disability and requires multidimensional assessment of pain intensity and functioning, yet electronic health records rarely capture these measures systematically. By contrast, surveys collecting patient-reported outcomes can assess pain over multiple dimensions but remain resource-intensive and difficult to scale for continuous population-level monitoring.

Attention-deficit/hyperactivity disorder (ADHD) affects over 366 million adults and 139 million children worldwide, yet diagnosis remains fundamentally subjective, relying on clinical interviews, behavioral observations, and rating scales that yield inconsistent results across practitioners and settings. Artificial intelligence (AI), machine learning (ML), and deep learning (DL) offer a paradigm shift toward objective, data-driven diagnosis by detecting complex patterns across neuroimaging, electrophysiology, and digital biomarkers that elude conventional assessment. Although AI-based ADHD research has grown exponentially, no comprehensive synthesis examines the full spectrum of data modalities, validation practices, and clinical translation readiness. This gap limits our understanding of which approaches are most promising for real-world implementation.

Despite advances in HIV treatment, many people living with HIV fail to achieve or maintain viral suppression. Individuals who experience interruptions in HIV care, adherence challenges, and viral nonsuppression are often underrepresented in clinic-based cohort studies. Virtual cohort methodologies offer opportunities to recruit, engage, and retain these populations while integrating longitudinal behavioral, biomarker, and digital engagement data needed to characterize dynamic changes in HIV care engagement and viral suppression.

Despite several efforts to expand tobacco cessation services through tobacco cessation centers (TCCs) and quit lines, key operational challenges still persist. Recently, AI-based digital interventions have shown promise globally for smoking cessation; however, they remain underused in tobacco cessation strategy in the Indian context.

Simulation-based learning constitutes a valuable component of medical training, with immersive 3D simulations and physical simulations being commonly used. Immersive 3D simulation training has been proven to enhance procedural skills and their transfer, whereas physical simulators allow for haptic feedback. However, direct comparative evidence between these 2 simulation modalities is scarce and often does not address cognitive, motivational, and perceived learning outcomes, which also have an effect on actual learning outcomes.

Emotional disorders—primarily anxiety and unipolar depressive disorders—are highly prevalent, disabling, and frequently comorbid. Disorder‑specific cognitive behavioral therapy (DS‑CBT) is considered a gold standard treatment, yet it can be inefficient in the context of high comorbidity and service constraints. Transdiagnostic psychotherapies that target shared maintaining mechanisms (eg, emotion dysregulation and neuroticism) have been developed, including the Unified Protocol, transdiagnostic behavior therapy, emotion regulation therapy, and various transdiagnostic internet-delivered cognitive behavioral therapy protocols. Recent meta-analyses suggest that transdiagnostic interventions are effective or likely effective, but a comprehensive comparative evaluation across different transdiagnostic protocols, DS‑CBT, other evidence‑based psychotherapies, and control conditions is lacking.