JMIR Formative Research

Eye tracking is recognized as a gold standard for measuring visual attention and cognitive engagement. In this study, it offers a useful lens for understanding how primary care providers balance patient communication with navigation of electronic health records (EHRs). We used wearable eye tracking to collect visual information processing behavior and conducted a retrospective think-aloud protocol to examine how primary care clinicians processed suiciderelated information (CAT-MH(R)) embedded in...

BackgroundTyping in the electronic health record (EHR) takes up healthcare providers time and cognitive space and constitutes a substantial administrative burden contributing to high burnout rates in healthcare. Ambient digital scribes may improve this problem. ObjectiveTo investigate the effect of the use of Autoscriber, an ambient digital scribe, on healthcare providers administrative workload and the quality of medical notes in the EHR. MethodsA study period of 26 weeks was randomized into ...

Wearable devices can collect changes in human behaviors related to mental health including depression and anxiety. Here, we examined whether and how digital metrics from a consumer-grade wearable smart ring (Oura Ring) differed by severity of depression and anxiety symptoms using data from a large-scale population-based sample of young adults (n=1,290, age range: 33-35). Participants wore the ring for two weeks, assessing sleep architecture, nocturnal heart rate (HR), heart rate variability (HRV...

BackgroundTinnitus affects a substantial proportion of the global population and can severely disrupt sleep, mood, and daily functioning, yet the quality of mobile health apps designed for tinnitus management remains highly variable. Traditional evaluation methods, including clinical trials, expert rating scales, and small-scale surveys, rarely capture large-scale, feature-level feedback from real-world users, leaving a gap in understanding which app characteristics drive sustained engagement an...

Digital therapeutics for mental health often face low patient engagement, which limits their clinical impact. Interventions that deliver treatment using a video game medium may improve engagement and therapeutic efficacy, but the putative emergence of gaming-related problems remains a concern among clinical stakeholders. We examined whether long-term engagement with Meliora, a video game therapeutic for adult major depressive disorder, was associated with changes in gaming-related problems in a ...

BackgroundGenerative artificial intelligence (GenAI) in healthcare may reduce administrative burden and enhance quality of care. Large language models (LLMs) can generate draft responses to patient messages using electronic health record (EHR) data. This could mitigate increased workload related to high message volumes. While effectiveness and feasibility of these GenAI tools have been studied in the United States, evidence from non-English contexts is scarce, particularly regarding user experie...

Artificial intelligence (AI) is increasingly integrated into healthcare delivery, yet patient acceptance in resource constrained settings remains incompletely characterized. This study assessed attitudes toward AI supported care among patients attending hospitals in three Jordanian governorates (Amman, Balqa, Irbid) and examined demographic and digital literacy correlates of acceptance. In a cross sectional survey (n = 500 complete questionnaires), participants rated exposure to AI in healthcare...

BackgroundAs digital communication becomes central to daily life, psychotherapy increasingly has access to patients electronic media data. While digital phenotyping has been widely studied, less is known about whether incorporating personal communication data, such as text messages, improves clinical outcomes in psychotherapy. ObjectiveTo determine whether integrating personalized text message data into psychotherapy improves depression, anxiety, health related quality of life, and therapeutic ...

Neurological health score (NHS), indicating the health of brain and nervous system, helps in identifying high risk individuals, and in recommending lifestyle modifications. In the present study, we developed NHS based on genetic, lifestyle and biochemical variables associated with eight neurological disorders - dementia, stroke, Parkinsons disease, amyotrophic lateral sclerosis, schizophrenia, bipolar disorder, multiple sclerosis and migraine. UK Biobank data from Caucasian individuals was used ...

BackgroundEHR documentation and chart review contribute to clinician workload and burnout. To alleviate pre-charting burden, Epic has released a new generative AI chart summarizer tool, which has become widely adopted; however, its impact has not been examined in randomized trials. ObjectiveTo evaluate whether access to an Epic generative AI chart summarization tool reduces cognitive task load among ambulatory providers compared with usual care. MethodsTwo-arm, parallel-group randomized contro...

Structured AbstractO_ST_ABSObjectiveC_ST_ABSThe use of ambient AI documentation tools is rapidly growing in US hospitals and clinics. Such tools generate the first draft of clinical notes from scribed patient-provider conversations, which clinicians can then review and edit before signing into electronic health records (EHR). Understanding how and why clinicians make modifications to AI-generated drafts is critical to improving AI design and clinical efficiency, yet it has been under-studied. Th...

BackgroundPost-marketing surveillance is essential for complementing the safety profiles of medicinal products, especially for populations generally excluded from clinical trials such as pregnant individuals. However, the absence of a standardised pregnancy indicator in the electronic transmissions of adverse event reports hampers their correct identification in pharmacovigilance databases and complicates the study of safety concerns related to pregnancy exposures. Three recently developed rule-...

ObjectivesGiven the widespread use of period-tracking applications and evidence that some users rely on fertile-window predictions for pregnancy prevention, we aimed to quantify pregnancy risk arising from misclassification of biologically fertile days by period-tracking applications, and to compare this risk across calendar-based and basal body temperature (BBT)-supported period tracking and a digital contraceptive regulated as a medical device. MethodsWe conducted an observational analysis of...

BackgroundArtificial intelligence is increasingly embedded in healthcare delivery. Its legitimacy depends on institutional governance, not technical performance alone. Prior research has centered on clinicians and patients. Less attention has been given to cybersecurity professionals who sustain the digital infrastructures that support health AI. This study examines how cybersecurity professionals conceptualize AI as clinical infrastructure and how these interpretations shape understandings of t...

BackgroundMental well-being encompasses positive psychological functioning, life satisfaction, and engagement with daily activities. It is influenced by multiple interrelated factors, including symptoms of stress, anxiety, depression, and psychological inflexibility. Network analysis provides a data-driven framework for examining the complex interconnections between these components and for identifying elements that may play a central role in the mental well-being system. The present study aimed...

IntroductionClinicians and patients are likely to increasingly use Large Language Models (LLMs) for diagnostic support. Use of LLMs mostly created in North America and Europe, could lead to a High-Income Country bias if used in Low- and Middle-Income Country (LMIC) healthcare settings. We aimed to explore if diagnostic suggestions made by LLMs are relevant in LMIC settings. MethodsFive short respiratory clinical vignettes were produced. For each vignette, a group of doctors from one of 5 countr...

Objective: Evaluating and monitoring patients with cervical spondylotic myelopathy (CSM) remains a challenge due to limited tools for assessing objective neurological disability longitudinally and in the home environment. Given their prevalence and low cost, mobile health (mHealth), and specifically smartphone technologies offer a promising approach to fill this gap. This study explored stakeholder perspectives on the role of mHealth in CSM monitoring to inform development of a smartphone-based ...

Ambient intelligence-based systems are increasingly used for clinical documentation. To quantify linguistic differences associated with ambient documentation, we conducted a matched pre-post analysis of 6,026 outpatient clinical notes from Mass General Brigham following implementation of two ambient AI documentation systems (Nuance Dragon Ambient eXperience [DAX] and Abridge). Within-clinician comparisons focused on the History of Present Illness (HPI) and Assessment and Plan (A&P) sections and ...

AbstractAccurate health information is ineffective if patients cannot understand it. Large Language Model (LLM) health research values veridical precision; however, linguistic accessibility remains an under-examined component of output quality and usability. This study investigated two sources of variability in readability classification: differences across LLM systems and across readability metrics. The analysis tested 1,120 data points from seven systems in English and Portuguese, comparing ba...

Large language models (LLMs) are increasingly used by the public to seek health information, yet their reliability in addressing common vaccine myths remains unclear. We conducted an exploratory multi-vendor evaluation of three LLMs (GPT-5, Gemini 2.5 Flash, Claude Sonnet 4) using officially curated vaccination myths from Germanys public health institution and two realistic user framings as prompts: a curious skeptic and a convinced believer. All model responses were independently evaluated by t...