An investment bubble occurs when there is a surge in asset prices that is not warranted by asset fundamentals because of irrationally exuberant market behavior. When prices rise to a level where no additional investors are willing to buy at the elevated price, then a massive sell-off typically occurs. Digital health investments represent approximately 10% of venture capital-backed startup investments, and diabetes digital health startups represent 4% of digital health investments. Attributes of a bubble indicate evidence for and against the current time period being in an investment bubble for digital health startups. After analyzing these attributes as well as the overall economy and the demand for healthcare products, we conclude that digital health startups and particularly digital health startups for diabetes are not in a bubble.
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http://dx.doi.org/10.1177/1932296819867742 | DOI Listing |
J Med Internet Res
March 2025
Department of Pharmacology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Background: Acceptance and commitment therapy provides a psychobehavioral framework feasible for digital and hybrid weight loss interventions. In face-to-face studies, group-based interventions yield more favorable outcomes than individual interventions, but the effect of the intervention form has not been studied in combination with eHealth.
Objective: This study investigated whether a minimal, 3-session group or individual enhancement could provide additional benefits compared to an eHealth-only intervention when assessing weight, body composition, and laboratory metrics in a sample of occupational health patients with obesity.
J Med Internet Res
March 2025
Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia.
Background: Conversational artificial intelligence (AI) allows for engaging interactions, however, its acceptability, barriers, and enablers to support patients with atrial fibrillation (AF) are unknown.
Objective: This work stems from the Coordinating Health care with AI-supported Technology for patients with AF (CHAT-AF) trial and aims to explore patient perspectives on receiving support from a conversational AI support program.
Methods: Patients with AF recruited for a randomized controlled trial who received the intervention were approached for semistructured interviews using purposive sampling.
JMIR Form Res
March 2025
Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Background: Screening for cognitive impairment in primary care is important, yet primary care physicians (PCPs) report conducting routine cognitive assessments for less than half of patients older than 60 years of age. Linus Health's Core Cognitive Evaluation (CCE), a tablet-based digital cognitive assessment, has been used for the detection of cognitive impairment, but its application in primary care is not yet studied.
Objective: This study aimed to explore the integration of CCE implementation in a primary care setting.
Oncotarget
March 2025
Worldwide Innovative Network (WIN) Association - WIN Consortium, Chevilly-Larue, France.
The human genome project ushered in a genomic medicine era that was largely unimaginable three decades ago. Discoveries of druggable cancer drivers enabled biomarker-driven gene- and immune-targeted therapy and transformed cancer treatment. Minimizing treatment not expected to benefit, and toxicity-including financial and time-are important goals of modern oncology.
View Article and Find Full Text PDFEuropace
March 2025
Clinical Cardiac Academic Group, Genetic and Cardiovascular Sciences Institute, City-St George's University of London, London, UK.
Atrial fibrillation (AF) is one of the most common cardiac diseases and a complicating comorbidity for multiple associated diseases. Many clinical decisions regarding AF are currently based on the binary recognition of AF being present or absent with the categorical appraisal of AF as continued or intermittent. Assessment of AF in clinical trials is largely limited to the time to (first) detection of an AF episode.
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