JMIR Formative Research

Wrong-site surgery (WSS) is a critical but preventable medical error, often resulting in severe patient harm and substantial financial costs. While protocols exist to reduce wrong-site surgery, underreporting and inconsistent documentation continue to contribute to its persistence. Machine learning (ML) models, which have shown success in detecting medication errors, may offer a solution by identifying unusual procedure-diagnosis combinations. This study investigated whether an ML approach can effectively adapt to detect surgical errors.

Patient satisfaction surveys can offer crucial information on the quality of care but are rarely conducted in low-income settings. In contrast with in-person exit interviews, phone-based interactive voice response (IVR) surveys may offer benefits including standardization, patient privacy, reduced social desirability bias, and cost and time efficiency. IVR surveys have rarely been tested in low-income settings, particularly for patient satisfaction surveys.

The use of unsupervised digital cognitive assessments provides considerable opportunities for early and comprehensive testing for Alzheimer’s disease, minimizing the demand on time and personnel resources in medical practices. However, the acceptance within health care has yet to be assessed.

Accumulating evidence supports the use of virtual reality (VR) in mental health care, with one potential application being its use to assist individuals with relaxation exercises. Despite studies finding support for the potential of VR to effectively aid in relaxation, its implementation remains limited outside of specialized clinics. Known barriers are insufficient knowledge regarding VR operation, lack of availability of VR relaxation apps tailored to local health care systems, and cost concerns. Unfortunately, many VR relaxation apps are designed exclusively for stand-alone headsets, limiting accessibility for a broad audience.

Public deliberation is an approach used to engage persons with diverse perspectives in discussions and decision-making about issues affecting the public that are controversial or value laden. Because experts have identified the need to evaluate facilitator performance, our research team developed a framework to assess the fidelity of facilitator remarks to key principles of public deliberation.

Decreasing aggression through stress reduction is an important part of forensic psychiatric treatment. DEEP is an experience-based virtual reality intervention that uses biofeedback to train diaphragmatic breathing and increase relaxation. Although DEEP has shown promising results in reducing stress and anxiety in students and adolescents in special education, it has not been examined in forensic psychiatric populations.

Emergency departments (EDs) are high-pressure environments where clinicians diagnose patients under significant constraints, including limited medical histories, severe time pressures, and frequent interruptions. Current ED care practices often inadequately support meaningful patient participation. Most interventions prioritize clinical workflow and health care provider communication, inadvertently overlooking patients’ needs. Additionally, patient-facing technologies in EDs are typically developed without meaningful patient input, leading to solutions that may not effectively address patients’ specific challenges. To enhance both patient-centered care practices and the diagnosis process in EDs, patient involvement in technology design is essential to ensure their needs during emergency care are understood and addressed.

In the Netherlands, 545,900 people suffered from COPD in 2022. Physical therapy following the Royal Dutch Society for Physiotherapy (KNGF) guidelines, for COPD treatment is a proven effective treatment for people with COPD. The revised guidelines includes a new recommendation: a patient’s physical activity level should be assessed with an activity tracker (AT). Literature shows that the implementation of eHealth in clinical practice, in this case, activity trackers, is challenging.

Geospatial data science can be a powerful tool to aid the design, reach, efficiency, and impact of community-based intervention trials. The project titled Take Care Texas aims to develop and test an adaptive, multilevel, community-based intervention to increase COVID-19 testing and vaccination uptake among vulnerable populations in three Texas regions: Harris County, Cameron County, and Northeast Texas.

The Otago Program (OP) is evidence-based and focuses on fall prevention in older people. The feasibility and usability of a short-term digital program modeled after the principles of the OP in the setting of early geriatric rehabilitation (EGR) is unclear.

Technology is more likely to be used when it is designed to meet the needs of end-users. To supplement the [PROGRAM] diabetes prevention program, a smartphone application was developed in partnership with past [PROGRAM] clientele. Usability testing is critical for the ongoing use and adoption of mHealth applications by providing insight on where appropriate adjustemnts and improvements need to be made to ensure user satisfaction.

Despite the growing interest in smart glasses, it is striking that they are not widespread among health care professionals. Previous research has identified issues related to social interactions involving the use of smart glasses in public settings, which may differ from those associated with their application in health care contexts.