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The effect of an app-based dietary education on dietary intake and cardiometabolic risk markers in people with type 2 diabetes: results from a randomized controlled trial.
Nutr J
January 2025
Division of Clinical Epidemiology, Department of Medicine Solna, Karolinska Institutet, Eugeniahemmet T2:02, Stockholm, SE-171 76, Sweden.
Background: mHealth, i.e. mobile-health, strategies may be used as a complement to regular care to support healthy dietary habits in primary care patients.
View Article and Find Full Text PDFAssociation of 30-s Sit-to-Stand Power Test Outcome With Body Balance in Physically Active Older Adults.
J Aging Phys Act
January 2025
Human Motor Systems Laboratory, School of Physical Education and Sport, University of São Paulo, São Paulo, SP, Brazil.
Amount of serial sitting and standing movements has been employed in clinical and research settings to assess legs' muscular strength. In this cross-sectional study, we aimed to test the correlation between the 30-s sit-to-stand power test (30STSp) outcome and body balance in older adults. We evaluated physically active male and female (n = 51) individuals with an age range of 60-80 years (M = 69.
View Article and Find Full Text PDFA smartphone-based application to improve breastfeeding duration and self-efficacy: a randomized controlled clinical trial.
Women Health
January 2025
Medical College of Georgia, Augusta University, Augusta, Georgia, USA.
A novel breastfeeding mobile app was created. We aim to determine if patients who utilize the app will have longer breastfeeding duration, improved breastfeeding self-efficacy scores at 1-year follow-up, and higher exclusive breastfeeding rates at 6 months postpartum. Participants were randomized, with 45 to the intervention and 48 to the control groups.
View Article and Find Full Text PDFEnhancing Interpretable, Transparent, and Unobtrusive Detection of Acute Marijuana Intoxication in Natural Environments: Harnessing Smart Devices and Explainable AI to Empower Just-In-Time Adaptive Interventions: Longitudinal Observational Study.
JMIR AI
January 2025
Human-Computer Interaction and Human-Centered AI Systems Lab, AI for Healthcare Lab, Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology, Hoboken, NJ, United States.
Background: Acute marijuana intoxication can impair motor skills and cognitive functions such as attention and information processing. However, traditional tests, like blood, urine, and saliva, fail to accurately detect acute marijuana intoxication in real time.
Objective: This study aims to explore whether integrating smartphone-based sensors with readily accessible wearable activity trackers, like Fitbit, can enhance the detection of acute marijuana intoxication in naturalistic settings.
A cross-language speech model for detection of Parkinson's disease.
J Neural Transm (Vienna)
December 2024
Department of Neurology, Seoul National University Hospital and Seoul National University College of Medicine, Seoul, Korea.
Speech change is a biometric marker for Parkinson's disease (PD). However, evaluating speech variability across diverse languages is challenging. We aimed to develop a cross-language algorithm differentiating between PD patients and healthy controls using a Taiwanese and Korean speech data set.
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