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A Novel Mobile Health App to Educate and Empower Young Adults With Type 1 Diabetes to Exercise Safely: Prospective Single-Arm Pre-Post Noninferiority Clinical Trial

A Novel Mobile Health App to Educate and Empower Young Adults With Type 1 Diabetes to Exercise Safely: Prospective Single-Arm Pre-Post Noninferiority Clinical Trial

Means (pooled SDs) for exercise frequency, intensity, and duration across the respective study phases were analyzed, and the magnitude of change between phases for each of the exercise components was reported using Hedges g and interpreted as small (g=0.2), moderate (g=0.5), or large (g=0.8) [30].

Vinutha Beliyurguthu Shetty, Rachel Lim, Shaun Teo, Wayne H K Soon, Heather C Roby, Alison G Roberts, Grant J Smith, Paul A Fournier, Timothy W Jones, Elizabeth A Davis

JMIR Diabetes 2025;10:e68694

Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring Component

Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring Component

The Fit-COVID dataset provided HRV data from 20 healthy individuals who tested negative for COVID-19 via immunoglobulin M or immunoglobulin G antibody tests, as well as 20 individuals with post–COVID-19 condition who had a confirmed polymerase chain reaction positive COVID-19 diagnosis, exhibited mild to moderate symptoms, and were assessed 15 to 180 days after infection. All participants were aged 20 to 40 years [65].

Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

J Med Internet Res 2025;27:e76613