JMIR Research Protocols

Problematic digital media use (PDMU) among young people has been on the rise. PDMU is defined as excessive use of digital media, the internet, or electronic communication leading to user dysfunction and harm to other individuals. Evidence links excessive use of media with various mental health disorders, behavioral problems, substance abuse, poor sleep hygiene, and social dysfunction. This maladaptive behavior is pervasive among young people, yet there is a paucity of studies that comprehensively examine the phenomenon in this specific population.

A comprehensive understanding of organizations is fundamental for implementing successful change measures. However, to date, there is no empirically testable, operationalized systems-psychodynamic organizational diagnostic method that can capture the deeper, more complex dynamics that are crucial for sustainable transformation. To address this gap, we developed the Systematic Multidimensional Organizational Assessment (SyMOA), a qualitative instrument based on an evidence-based clinical diagnostic framework, the Operationalized Psychodynamic Diagnostics III. SyMOA integrates clinical, organizational, and systemic psychodynamic theory and analyzes an organization’s challenges based on invisible and unconscious aspects, that is, those lurking beneath the surface. It hypothesizes 3 organizational dimensions: (1) current challenges based on the sociotechnical integration and organizational internal functioning level, (2) internal relationship dynamics, and (3) unconscious organizational conflicts. The SyMOA dimensions are operationalized into a semistructured interview guide and coding protocols for the analysis of the content. By capturing the underlying dynamics, SyMOA aims to provide a deeper understanding of an organization’s challenges and establish a solid foundation for targeted interventions.

Multiple myeloma (MM) is characterized by kidney deficiency, phlegm, and blood stasis as core findings, specifically in Traditional Chinese Medicine (TCM), and the kidney-tonifying, phlegm-resolving, and blood stasis–removing (KPR) method is a fundamental therapeutic approach for MM in TCM. Western medicine primarily focuses on targeted immunotherapy or chemotherapy for MM treatment, whereas TCM characterizes MM through distinct pathological patterns that directly correspond to immune microenvironment dysregulation. Emerging evidence implicates the PHD finger protein 19 (PHF19)/enhancer of zeste homolog 2 (EZH2)/trimethylated histone H3 at lysine 27 (H3K27me3) epigenetic axis in immune microenvironment dysregulation and MM progression. Notably, TCM “blood stasis” correlates with hypoxia-induced immune gene silencing in MM bone marrow, and KPR (a clinically validated TCM decoction with 16 herbs) acts on this axis via its active components that regulate EZH2 and epigenetic function, merging TCM syndrome differentiation with modern epigenetics. We have designed a randomized controlled trial (RCT) to investigate the mechanism of action and safety of the KPR method in MM.

The infusion of vasopressors is a standard treatment for shock, and international guidelines recommend administering these medications through central venous catheters (CVCs) due to concerns about potential extravasation and local tissue injury with peripheral intravenous (PIV) administration. However, CVCs are often unavailable in resource-variable settings due to lack of human and material resources. Previous studies have assessed the safety of vasopressor infusion through PIV catheters but have considered only limited patient populations or a short infusion time or have used retrospective designs that may have failed to capture mild complications.

Recognizing the bidirectional relationship between oral health and diabetes mellitus (DM) and integrating DM screening and referrals to primary care into routine dental hygiene visits has strong potential to expand access to diabetes prevention and early detection services.

Type 1 diabetes (T1D) requires repeated self-management behaviors and ongoing problem-solving to maintain optimal glucose levels and prevent complications. Despite increasing adoption of continuous glucose monitoring (CGM), which can alleviate some of the constant self-management burden, adolescents struggle to achieve glycemic recommendations and report low engagement with diabetes device data. Previous studies have used retrospective or quantitative approaches to describe adolescent self-management; however, it is unclear how psychosocial influences (eg, mood and distress) and contexts impact adolescent self-management behaviors and engagement with their diabetes devices in everyday life. Exploration of real-time experiences will help to identify potential targets and strategies for future interventions to improve glycemic outcomes in adolescents with T1D using advanced diabetes technologies.

Tetraplegia, often resulting from cervical spinal cord injury, may lead to significant motor and sensory loss, severely impacting independence and quality of life (QoL). Assistive technologies, such as wheelchair-mounted robotic arms (WMRAs), offer potential to enhance autonomy in daily living. However, adoption remains limited due to high costs, complex controls, and insufficient end user involvement. Robust evidence on their real-world effectiveness, particularly post hospitalization, is still lacking.

The early detection of cognitive impairments in individuals with psychosis offers a means to support clinical and functional recovery. However, there are significant barriers to assessing cognition in clinical services, including lack of staff time, training, and confidence in administering assessments. We have developed the Cardiff Online Cognitive Assessment (CONCA), aiming to address these barriers, and here present the protocol to assess its acceptability as a clinical tool.

Affect plays a pivotal role in capturing people’s attention with health messages that influence audiences’ perceptions, attitudes, and, ultimately, health-related behavior. Adolescents are notably sensitive to affective cues in communication. However, there is a lack of reviews synthesizing the evidence examining the role of affect in health messaging targeted at adolescents.

Cardiorespiratory fitness (CRF) is a key predictor of cardiovascular and other health-related diseases in individuals with obesity. CRF is most accurately assessed through maximal exercise testing with advanced gas-analysis equipment (maximum volume of oxygen [VO]); however, this approach is time-consuming, costly, and requires specialized expertise. Therefore, submaximal tests and self-reported physical activity levels have been used to develop predictive algorithms to estimate CRF, yet they often performed poorly in individuals with low CRF levels, such as patients with obesity, because they are predominantly developed using data from healthy populations. Studies using machine learning (ML) models based on VO data from patients with obesity appear to be lacking in the literature. ML models based on routinely collected clinical measures may offer a more practical and potentially accurate way to estimate CRF, reducing time, costs, and clinical burden.

Visual impairment (VI) affects more than 600 million people globally and significantly reduces quality of life. In Singapore, 20% of adults aged 60 years and older (~180,000 people) have VI, a figure expected to double by 2030 due to population aging. While about half of VI cases are due to uncorrected refractive errors, the rest are caused by age-related diseases. The current traditional screening model is a 2-visit, labor-intensive approach with low follow-up rates and frequent unnecessary referrals. Although AI for Disease-related Visual Impairment Screening Using Retinal Imaging, the deep learning model in this study, has demonstrated strong diagnostic performance in retrospective datasets (area under the curve=0.942), key aspects of real-world implementation such as operational efficiency, patient acceptability, workflow feasibility, and cost remain insufficiently studied. As a result, real-world evidence directly comparing artificial intelligence (AI)–assisted and traditional screening pathways is limited.

Systems psychodynamics provide valuable insights into organizational development. However, to date, instruments that can reliably assess organizations based on systems psychodynamic theories are scarce. The Systematic Multidimensional Organizational Assessment (SyMOA) is a qualitative instrument that provides an in-depth systems psychodynamic analysis of organizational dynamics using a semistructured interview guide. To complement the method, a standardized, quantitative self-assessment questionnaire will be developed and validated.