JMIR Human Factors

Symptom checkers are applications that assist medical laypeople in diagnosing their symptoms and determining which course of action to take. When evaluating these tools, previous studies primarily used an approach introduced a decade ago that lacked any type of quality control. Numerous studies have criticized this approach, and several empirical studies have sought to improve specific aspects of evaluations. However, even after a decade, a high-quality methodological framework for standardizing the evaluation of symptom checkers remains missing. This article synthesizes empirical studies to outline a Symptom Checker Accuracy Reporting Framework (SCARF) and a corresponding checklist for standardizing evaluations based on representative case selection, an externally and internally valid evaluation design, and metrics that increase cross-study comparability. This approach is backed up by several open-access resources to facilitate implementation. Ultimately, this approach should enhance the quality and comparability of future evaluations of online and AI-based symptom checkers, diagnostic decision support systems, and large language models to enable meta-analyses and help stakeholders make more informed decisions.

Discrimination can greatly impact both physical and mental health due to frequent stressors. Younger individuals, particularly those under 17 years old, are more adversely affected by victimization. Within the European Union, Romania exhibits poor rankings concerning LGBTQ+ inclusion, with large numbers of LGBTQ+ teenagers experiencing bullying due to their sexual orientation. Given that much of this discrimination and harassment occurs within schools, teachers and counselors are vital in affecting institutional change.

Stroke often leads to persistent impairments that limit daily functioning and psychosocial well-being. Virtual reality (VR) has emerged as a promising adjunct in stroke rehabilitation, although research has largely focused on clinical outcomes, with limited attention to user involvement and the experiences of multiple stakeholders in the design process.

Overdose Fatality Review (OFR) is a public health process in which cases of fatal overdose are carefully reviewed to identify prevention strategies. Current OFR requires review of multiple unconnected data sources, which is a manually intensive process. The Substance Misuse Data Commons (SMDC) was created to link Electronic Health Record (EHR) data with data from local and state agencies into a single, cloud-based e-platform, but does not currently have a data visualization tool.

The German electronic health record (EHR) aims to enhance patient care and reduce costs, but users often worry about data privacy and security. To mitigate disease-related privacy concerns, for instance, surrounding stigmatized diseases, we test the effect of privacy fact sheets (PFS) - a concise but comprehensive transparency feature designed to increase users’ perceived control over their data - on increasing EHR usage in a simulated online study.

Women with cardiovascular disease (CVD) remain underserved due to gaps in recognition, diagnosis, and care tailored to sex-specific risks. Digital health tools have the potential to address these inequities, but many fail to reflect the distinct needs of women. In a prior review, we assessed 20 CVD apps and 22 wearables and found that only 25% (5/20) of apps and 40% (9/22) of wearables included any sex-specific content, such as hormone cycle tracking and life-stage considerations related to pregnancy or menopause. These findings confirm that current digital tools largely mirror the gender gaps seen in traditional care.

Diabetic foot ulceration (DFU) is the leading cause of non-traumatic amputations in people with diabetes. Research shows that improving patient awareness can result in short-term improvements, but Cochrane reviews report insufficient high-quality evidence.

The emergence of Artificial Intelligence (AI) is driving digital transformation and reshaping medical education in China. Numerous medical schools and institutions are actively implementing AI tools for case-based learning, literature analysis, and lecture support. This expanding application is accelerating the adoption of localized AI platforms, which are poised to become integral components in the coming years.

Entrapment of sickled red blood cells in the microvasculature leads to sudden painful vaso-occlusive crises (VOC) in sickle cell disease (SCD). This is potentially triggered by autonomic nervous system mediated vasoconstriction in peripheral vasculature and resultant decrease in microvascular blood flow. Indeed, vasoconstriction biomarkers derived from a single night of laboratory-based fingertip photoplethysmography (PPG) recording were predictive of higher frequency of future VOC in SCD. Non-invasive, remote and longitudinal monitoring of autonomic vasoreactivity will facilitate development of predictive biomarkers of imminent VOC.

South Asian communities in Canada face significant disparities in access to healthcare and experience higher rates of chronic conditions such as cardiovascular disease, diabetes, and hypertension. Hospital-at-home services have the potential to improve access and outcomes, yet little is known about how these services are perceived and experienced by South Asian patients and caregivers. Understanding both barriers and facilitators is critical for culturally responsive implementation.

Technology-assisted 24-hour dietary recall (24HR) methods offer the potential for scalable population dietary assessment, but current challenges include balancing accuracy and cost against participant burden and acceptability of these methods. Qualitative methods present a novel approach to understanding potential barriers and enablers to the acceptability of 24HR methods, but remain relatively unexplored.

Dementia increases the risk of individuals getting lost due to cognitive decline, impacting daily functioning and heightening caregiver worry. Traditional search methods are often time-consuming and stressful, while GPS-based technologies face limitations like battery dependency. A crowdsourcing Internet of Things (IoT) technology using energy-efficient Bluetooth Low Energy (BLE) offers a potential solution to locate missing individuals with dementia more effectively by harnessing the power of the crowd and fostering a caring and inclusive community.