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A family-based behavioral group obesity randomized control feasibility trial across a clinical trials network: a focus on contact hours.
J Pediatr Psychol
January 2025
Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, United States.
Objective: This ancillary study's purpose is to describe the relationship between dose of treatment and body mass index (BMI) outcomes in a tele-behavioral health program delivered in the IDeA States Pediatric Clinical Trials Network to children and their families living in rural communities.
Methods: Participants randomized to the intervention were able to receive 26 contact hours (15 hr of group sessions and 11 hr of individual sessions) of material focused on nutrition, physical activity, and behavioral caregiver training delivered via interactive televideo. Dose of the intervention received by child/caregiver dyads (n = 52) from rural areas was measured as contact hours.
The natural history of cytologically low-risk indeterminate thyroid nodules.
J Clin Endocrinol Metab
January 2025
Department of Internal Medicine and Therapeutics, University of Pavia, 27100 Pavia, Italy.
Background: Thyroid nodules classified cytologically as low-risk indeterminate lesions (TIR3A) on fine-needle aspiration biopsy (FNAB) present a clinical challenge due to their uncertain malignancy risk. This single-center study aimed to evaluate the natural history of TIR3A nodules.
Materials And Methods: FNABs performed between July 2017 and December 2019 were retrospectively retrieved and patients with TIR3A nodules were evaluated at baseline and throughout a follow-up based on ultrasound (US) parameters and clinical data.
Transformers for Neuroimage Segmentation: Scoping Review.
J Med Internet Res
January 2025
Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.
Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.
View Article and Find Full Text PDFTesting the Feasibility, Acceptability, and Potential Efficacy of an Innovative Digital Mental Health Care Delivery Model Designed to Increase Access to Care: Open Trial of the Digital Clinic.
JMIR Ment Health
January 2025
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.
Background: Mental health concerns have become increasingly prevalent; however, care remains inaccessible to many. While digital mental health interventions offer a promising solution, self-help and even coached apps have not fully addressed the challenge. There is now a growing interest in hybrid, or blended, care approaches that use apps as tools to augment, rather than to entirely guide, care.
View Article and Find Full Text PDFHarnessing Human-Centered Design for Evidence-Based Psychosocial Interventions and Implementation Strategies in Community Settings: Protocol for Redesign to Improve Usability, Engagement, and Appropriateness.
JMIR Res Protoc
January 2025
Division of Services and Interventions Research, National Institute of Mental Health, Bethesda, MD, United States.
Background: Although substantial progress has been made in establishing evidence-based psychosocial clinical interventions and implementation strategies for mental health, translating research into practice-particularly in more accessible, community settings-has been slow.
Objective: This protocol outlines the renewal of the National Institute of Mental Health-funded University of Washington Advanced Laboratories for Accelerating the Reach and Impact of Treatments for Youth and Adults with Mental Illness Center, which draws from human-centered design (HCD) and implementation science to improve clinical interventions and implementation strategies. The Center's second round of funding (2023-2028) focuses on using the Discover, Design and Build, and Test (DDBT) framework to address 3 priority clinical intervention and implementation strategy mechanisms (ie, usability, engagement, and appropriateness), which we identified as challenges to implementation and scalability during the first iteration of the center.
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