JMIR Human Factors

Although chronic pain (CP) is highly prevalent, current modalities are not sufficient to address the needs of people living with this condition. Pharmacological treatments for CP can have severe side effects and increased likelihood of patients overdosing or developing addiction. Behavioral treatments are often indicated for the treatment of CP, but barriers to treatment are common. Virtual reality (VR)–based interventions have shown promise as an effective and potentially accessible form of treatment for CP. However, previous research on VR interventions for people living with CP has not often included diverse populations, including racial and ethnic minority groups and people with low socioeconomic status.

The widespread use of digital technologies has raised growing concerns about their impact on mental health. While self-regulation has been proposed as a protective factor, little is known about how distinct psychological profiles based on self-regulatory and technology use patterns relate to psychological distress. Person-centered approaches such as Latent Profile Analysis may offer deeper insights, particularly in underrepresented populations.

Patient autonomy through informed consent is a foundational ethical principle for health care practitioners. Online consent processes risk producing “consent in name only,” using manipulative or confusing user interfaces to extract consent artificially. This presents a significant danger for safe and ethical remote consultations for primary care providers, which often extract significant amounts of sensitive personal data.

Over 1 million Dutch people have diabetes, of whom 90% have type 2 diabetes. Studies show that lifestyle plays an important role in the course of type 2 diabetes. MiGuide (MiGuide Ltd) is an online platform that helps people adopt and sustain lifestyle changes. The platform is integrated into existing diabetes care within primary care. Previous research has shown that implementing new (eHealth) interventions is challenging and may reduce effectiveness. Mapping out the barriers and success factors in the implementation process is essential so that eHealth interventions such as MiGuide can be used effectively in regular health care.

Pain drawing (PD) body charts are widely used in back pain research, but the representation of sex in these charts has not been systematically evaluated.

Central venous catheters (CVCs) are indispensable to contemporary critical care, perioperative management, and emergency resuscitation, yet their insertion remains fraught with preventable harm and inefficiency.

Early rehabilitation in neurocritical care is often underutilized due to fragmented workflows, interdisciplinary coordination challenges, and the absence of structured digital decision support. Traditional clinical decision support systems (CDSS) often address single domains and lack adaptability to the dynamic, multi-professional workflows of intensive care units (ICUs).

Human factors (HF) or ergonomics, which explores the interaction between humans and systems, has been used to support design in safety critical industries such as aviation, transportation, nuclear power and manufacturing. HF methods have the potential to support the safe design of health information technology (HIT) however the evaluation of HF methods to determine their effectiveness and feasibility in this context has been limited.

Irritable bowel syndrome (IBS) is a common chronic gastrointestinal disorder that impairs bowel functions and patients’ overall quality of life. IBS-focused digital health technologies (DHTs), including online health resources and mobile health (mHealth) apps, have recently proliferated for patient use. However, research exploring patients’ experiences with navigating, adopting, or using commercial or publicly available DHTs for IBS self-management is limited.

Refugees and asylum-seekers commonly experience numerous adverse and traumatic events and are therefore at increased risk of mental health problems. Despite the high need for mental health interventions, services tend to be underused by refugees and asylum-seekers, and various barriers compromise access. Digital, efficient screening, adapted for these groups, could facilitate initial assessment and increase accessibility to mental health services. We developed an internet-based tiered screening procedure (i-TAP) aiming to identify clinically relevant symptoms of major depressive disorder (MDD), anxiety disorder, posttraumatic stress disorder, and insomnia disorder among individuals with a refugee background. The i-TAP is an adaptive procedure with 3 tiers aiming to identify general mental distress in Tier 1, differentiate between symptoms in Tier 2, and assess the severity of symptoms in Tier 3. Each tier additionally functions as a gateway to further assessment, as a negative outcome terminates the procedure.

Despite growing evidence demonstrating the connection between oral and systemic health, medical and dental care remain institutionally divided. A significant consequence of this division is the lack of information sharing, which is particularly problematic in dental care, where knowing patients’ medical information is crucial for providing safe and effective treatments. This separation poses additional challenges in Swedish regions with limited resources, such as Dalarna, where dental care practices would benefit from improved access to relevant medical information in their Electronic Dental Record systems.

Over the years, the nursing home regulatory landscape has undergone considerable transformation. The Five-Star Quality Rating System for Nursing Homes plays a central role in evaluating Quality of Care (QoC), though it carries both strengths and limitations. This system relies heavily on the Minimum Data Set (MDS) and derives several Quality Measures (QMs) from it. In this study, we validated the effectiveness of the Five-Star Nursing Homes Quality Rating System and its underlying quality measures in estimating nursing home quality of care. We constructed a panel dataset from three major sources: 1) COVID-19 nursing home data, 2) Payroll-Based Journal (PBJ) data, and 3) nursing home quality measure snapshots. The outcome variables included resident and staff cases, as well as death counts during the period May 2020–June 2023. The predictor variables were the Five-Star Quality Rating System for Nursing Home and its underlying QMs classified as either Structure, Process, or Outcome (SPO) QMs. The dataset included all nursing homes that completed at least one week of COVID-19 reporting at the facility level (N = 15,416) during the study period.