Research related to the developmental disability (DD) community should include collaboration with individuals with DD. Unfortunately, people with DD are infrequently involved in research projects in meaningful ways, and there is little guidance about how to collaborate equitably with researchers with DD. The purpose of this article is to share lessons learned from a collaborative research study among researchers with and without DD using both qualitative and quantitative methods to develop and examine the effectiveness of a civic engagement intervention for transition-aged youth with disabilities. It includes how our research team compensated researchers with DD, clarified team member roles, leveraged the expertise of researchers with DD in using both qualitative and quantitative methods, and integrated technology throughout the research process.
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http://dx.doi.org/10.1352/1934-9556-60.5.405 | DOI Listing |
Aim: To discuss inter-organisational collaboration in the context of the successful COVID-19 vaccination programme in North Central London (NCL).
Design: An action research study in 2023-2024.
Methods: Six action research cycles used mixed qualitative methods.
JMIR Form Res
January 2025
College of Nursing, The Ohio State University, Columbus, OH, United States.
Background: Researchers have encountered challenges in recruiting unpaid caregivers of people living with Alzheimer disease and related dementias for intervention studies. However, little is known about the reasons for nonparticipation in in-home smart health interventions in community-based settings.
Objective: This study aimed to (1) assess recruitment rates in a smart health technology intervention for caregivers of people living with Alzheimer disease and related dementias and reasons for nonparticipation among them and (2) discuss lessons learned from recruitment challenges and strategies to improve recruitment.
Heart Rhythm
January 2025
Geisinger Heart Institute, Geisinger Wyoming Valley Medical Center, MC 36-10, 1000 E Mountain Blvd, Wilkes-Barre, PA 18711.
Int J Mol Sci
January 2025
IRCAD (Interdisciplinary Research Center of Autoimmune Diseases), Università del Piemonte Orientale (UPO), 28100 Novara, Italy.
SARS-CoV-2 virus, the etiological agent of the novel coronavirus disease 19 (COVID-19), was first identified in late 2019, following the sudden appearance of a cluster of pneumonia cases of unknown origin in China [...
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.
We test here the prediction capabilities of the new generation of deep learning predictors in the more challenging situation of multistate multidomain proteins by using as a case study a coiled-coil family of Nucleotide-binding Oligomerization Domain-like (NOD-like) receptors from and a few extra examples for reference. Results reveal a truly remarkable ability of these platforms to correctly predict the 3D structure of modules that fold in well-established topologies. A lower performance is noticed in modeling morphing regions of these proteins, such as the coiled coils.
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