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Testing 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.
Revolutionizing colorectal cancer detection: A breakthrough in microbiome data analysis.
PLoS One
January 2025
Department of Computer Science, Faculty of Computing, Federal University of Lafia, Lafia, Nasarawa State, Nigeria.
Article Synopsis
- The emergence of Next Generation Sequencing (NGS) technology has transformed clinical diagnostics, providing extensive microbiome data for personalized medicine.
- Despite its potential, microbiome data's complexity and variability pose challenges for traditional statistical and machine learning approaches, including deep learning.
- The paper presents a novel feature engineering technique that combines two data feature sets, significantly improving the Deep Neural Network's performance in colorectal cancer detection, raising the Area Under the Curve (AUC) from 0.800 to 0.923, thus enhancing microbiome data analysis and disease detection capabilities.
Do global health networks facilitate innovation, learning and sharing? A qualitative analysis of the Quality-of-Care Network in Bangladesh, Ethiopia, Malawi, and Uganda.
PLOS Glob Public Health
January 2025
Bloomberg School of Public Health, Johns Hopkins University, Baltimore, United States of America.
The Quality-of-Care Network (QCN), launched by WHO and partners, links global and national actors across several countries to improve maternal and newborn health. We conducted a prospective qualitative study to examine how QCN in Bangladesh, Ethiopia, Malawi and Uganda facilitated learning, sharing, and innovation within and between network countries. We conducted 227 key informant interviews with QCN actors at global, national, and facility levels iteratively in two to four rounds from June 2019 to March 2022.
View Article and Find Full Text PDFThe landscape of family medicine in India - A cross-sectional survey study.
PLOS Glob Public Health
January 2025
Department of Family and Community Medicine, University of Toronto, Toronto, Canada.
Family medicine was recognized as a distinct specialty in India in the early 1980s, but it is at an early stage of implementation. There are few training programs, and little is known about family physicians' training, perceptions, and current practices. This paper describes the findings from the first national survey of family medicine in India.
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