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To determine the impact of tethered personal health record (PHR) use on patient engagement and intermediate health outcomes among patients with coronary artery disease (CAD).

To investigate subjective experiences and patterns of engagement with a novel electronic tool for facilitating reflection and problem solving for individuals with type 2 diabetes, Mobile Diabetes Detective (MoDD).

Prior studies of computing applications that support patients' medication knowledge and self-management offer valuable insights into effective application design, but do not address inpatient settings. This study is the first to explore the design and usefulness of patient-facing tools supporting inpatient medication management and tracking.

This article examines engagement with a mobile application ("mCare") for wounded Service Members rehabilitating in their communities. Many had behavioral health problems, Traumatic Brain Injury (TBI), and/or post-traumatic stress disorder (PTS). The article also examines associations between Service Members' background characteristics and their engagement with mCare.

We implemented a web-based, patient-centered toolkit that engages patients/caregivers in the hospital plan of care by facilitating education and patient-provider communication. Of the 585 eligible patients approached on medical intensive care and oncology units, 239 were enrolled (119 patients, 120 caregivers). The most common reason for not approaching the patient was our inability to identify a health care proxy when a patient was incapacitated. Significantly more caregivers were enrolled in [...]

Mobile health (mHealth) interventions may improve diabetes outcomes, but require engagement. Little is known about what factors impede engagement, so the authors examined the relationship between patient factors and engagement in an mHealth medication adherence promotion intervention for low-income adults with type 2 diabetes (T2DM).

The high prevalence of limited health literacy among patients threatens the success of secure electronic messaging between patients from diverse populations and their providers.

To develop and evaluate RobotReviewer, a machine learning (ML) system that automatically assesses bias in clinical trials. From a (PDF-formatted) trial report, the system should determine risks of bias for the domains defined by the Cochrane Risk of Bias (RoB) tool, and extract supporting text for these judgments.