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http://dx.doi.org/10.1097/JS9.0000000000003402 | DOI Listing |
J Med Internet Res
September 2025
Center for Healthy Minds and Department of Counseling Psychology, University of Wisconsin-Madison, Madison, WI, United States.
Background: Ecological momentary assessment (EMA) is increasingly being incorporated into intervention studies to acquire a more fine-grained and ecologically valid assessment of change. The added utility of including relatively burdensome EMA measures in a clinical trial hinges on several psychometric assumptions, including that these measure are (1) reliable, (2) related to but not redundant with conventional self-report measures (convergent and discriminant validity), (3) sensitive to intervention-related change, and (4) associated with a clinically relevant criterion of improvement (criterion validity) above conventional self-report measures (incremental validity).
Objective: This study aimed to evaluate the reliability, validity, and sensitivity to change of conventional self-report versus EMA measures of rumination improvement.
Prog Mol Biol Transl Sci
September 2025
Institute of Intelligent Machines, Chinese Academy of Science, Hefei, Anhui, P.R. China. Electronic address:
The convergence of artificial intelligence (AI) and wearable biosensors is revolutionizing personalized healthcare, enabling continuous monitoring, early detection of health issues, which enhances the efficiency of data processing and real-time decision-making. Multimodal Large Language Models (MLLMs) play a pivotal role in this ecosystem by offering advanced capabilities in analyzing complex health data, understanding nuanced health contexts, and generating tailored health recommendations instantaneously. This study provides insights into how machine learning, deep learning algorithms, and MLLM can work together to facilitate the analysis of physiologic data for real-time monitoring and early warning systems as well as complex decision support mechanisms.
View Article and Find Full Text PDFArch Psychiatr Nurs
October 2025
Inserm U1094, IRD UMR270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of chronic diseases in tropical zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, France; Département Universitaire de Sciences Infirmières, Faculté de Médecine et Pharmacie, Université de L
Background: Smartphones, first introduced in 1992 in the United States, have evolved into essential communication tools due to their convenience and increasing functionalities. Their widespread use has significantly impacted daily life, leading to various psychological and physical consequences, particularly among young adults. In France, Interministerial Mission to Combat Drugs and Addictive Behavior (MILDECA) reports a high prevalence of intensive smartphone usage among individuals aged 15-24, with many acknowledging their inability to control their screen time.
View Article and Find Full Text PDFJMIR Res Protoc
September 2025
Department of Health Services Research & Administration, College of Public Health, University of Nebraska Medical Center, Omaha, NE, United States.
Background: With the availability of more advanced and effective treatments, life expectancy has improved among patients with metastatic breast cancer (MBC), but this makes communication with their medical oncologist more complex. Some patients struggle to learn about their therapeutic options and to understand and articulate their preferences. Mobile health (mHealth) apps can enhance patient-provider communication, playing a crucial role in the diagnosis, treatment, quality of life, and outcomes for patients living with MBC.
View Article and Find Full Text PDFJ Ultrasound Med
September 2025
Department of Clinical Analysis, Federal University of Santa Catarina (UFSC), Florianópolis, Brazil.
Objectives: To evaluate the performance of artificial intelligence (AI)-based models in predicting elevated neonatal insulin levels through fetal hepatic echotexture analysis.
Methods: This diagnostic accuracy study analyzed ultrasound images of fetal livers from pregnancies between 37 and 42 weeks, including cases with and without gestational diabetes mellitus (GDM). Images were stored in Digital Imaging and Communications in Medicine (DICOM) format, annotated by experts, and converted to segmented masks after quality checks.