JMIR Formative Research
Process evaluations, early results, and feasibility/pilot studies of digital and non-digital interventions
Editor-in-Chief:
Amaryllis Mavragani, PhD, Scientific Editor at JMIR Publications, Canada
Impact Factor 2.4 More information about Impact Factor CiteScore 4.2 More information about CiteScore
Recent Articles


Heart failure is a chronic condition that significantly impacts patients’ quality of life and increases health care burden. Effective self-monitoring and lifestyle modification are essential components of heart failure management and can support improved health outcomes. Mobile health technologies, such as smartphone apps, are increasingly used to assist patients with heart failure in self-management. However, evidence regarding patient engagement, user experience, and the effectiveness of these mobile health tools remains limited and continues to evolve.

The current level of insulin knowledge, attitudes, and practices of patients self-administering their first insulin injection needs to be improved. There is an emerging need to develop a program for patients self-administering their first insulin injection based on the e-coach model derived from the temporal self-regulation theory.

Understanding how medical students learn is critical for improving teaching strategies in clinical education. Despite the widespread use of learning style frameworks, such as visual, aural, read/write, and kinesthetic (VARK), evidence from sub-Saharan Africa remains limited, and the use of learning style approaches is debated in the literature. In clinical and health sciences education, aligning teaching with learners’ preferences can enhance knowledge retention, procedural competence, and ultimately the quality of patient care.

Sleep disturbances and low physical activity are common among breast cancer (BC) survivors and are associated with increased morbidity and mortality. Given the increased access to technological devices and the growing popularity of SMS text messaging–based mobile health interventions, these tools have the potential to both address sleep disturbances and promote physical activity in a scalable and cost-effective way. To understand and make effective use of these tools, it is important to consider the preferences of BC survivors with sleep disturbances, including how SMS text messaging–based mobile health interventions could deliver interventions involving physical activity and sleep hygiene.

Optimizing recovery following breast cancer surgery is critical for restoring usual function, minimizing complications, and enabling timely initiation of adjuvant therapies. Enhanced Recovery After Surgery protocols are internationally endorsed recommendations and include patient-led behaviors such as early mobilization, early oral intake of fluids and food, postoperative rehabilitation exercises, and multimodal pain management. However, adherence to these behaviors is often suboptimal, and strategies to support patients are limited. Digital health interventions (DHIs) may offer scalable solutions.

Out-of-pocket (OOP) costs pose a significant barrier to participating in cancer clinical trials (CCTs). Financial reimbursement programs (FRPs) that reduce the burden of OOP costs can support participation in CCTs if the information is readily available to participants at the time of enrollment. Prior studies have shown the importance and impact of FRPs, but despite improvements, significant barriers still remain.


Ecological momentary assessment (EMA) enables repeated, real-time measurement of emotional states, behaviors, and contextual exposures in individuals’ daily lives. Although EMA has been increasingly used in health and behavioral research, evidence regarding the feasibility, compliance, and acceptability of smartphone-based EMA among older adults in Asian settings remains limited.

Tuberculosis is a leading cause of death in South Africa, with poor adherence undermining treatment success. Findings from recent research on the impact of mHealth (mobile health) interventions on tuberculosis treatment outcomes show promise, yet many interventions remain untested in African contexts. Rising smartphone ownership in South Africa enables more complex mHealth interventions, offering an opportunity to deploy behavioral tools within high-burden, resource-constrained settings.


Acute kidney injury (AKI) is a frequent and serious complication among hospitalized patients, particularly in critical care settings, where its incidence can exceed 50%. AKI is associated with increased mortality, prolonged hospitalization, dialysis dependence, and higher health care costs. Although the KDIGO (Kidney Disease: Improving Global Outcomes) guidelines emphasize supportive care, hemodynamic optimization, and avoidance of nephrotoxins, their implementation remains inconsistent, partly due to the lack of timely risk stratification. Recent advances in artificial intelligence have enhanced early prediction and detection of AKI, offering new opportunities to improve patient outcomes and intensive care unit (ICU) efficiency. The U-Care Renal Platform (UCRP; U-Care Medical S.r.l), a Conformité Européenne (CE)–marked artificial intelligence–powered medical device, integrates directly with the ICU electronic health record to continuously analyze patient data and predict the risk of moderate or severe AKI within 24 hours, providing actionable, guideline-based recommendations. While the predictive performance of UCRP has been validated previously, its real-world impact on clinical and operational outcomes in the ICU remains underexplored.
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