Mixed methods research-methodologies that synthesize qualitative and quantitative approaches in the design, collection, analysis, and dissemination of research related to a specific topic or aim-is increasingly common, offering innovative empirical insight into families and relationships. We first elaborate on our definition of mixed methods research, emphasizing that there is significant heterogeneity within mixed methods approaches to studying families and relationships. Second, we discuss benefits of mixed methods projects within family and relationship research, including theory-building and innovation.
View Article and Find Full Text PDFObjective: Excess cholesterol loading on arterial macrophages is linked to foam cell formation, atherosclerosis and cardiovascular risk in rheumatoid arthritis (RA). However, the effect of changes in cholesterol loading on coronary plaque trajectory and the impact of RA therapies on this relationship are unknown. We investigated the association between variations in cholesterol loading capacity (CLC) over time and atherosclerosis progression.
View Article and Find Full Text PDFBackground: Because biologic and small molecule therapy is expensive, payors have mandated pre-authorizations for these medications, often resulting in a lengthy approval process. The aims of this study are to assess the frequency of and risk factors for delays in starting advanced therapies assessing insurance, care team, and patient-related factors.
Methods: Retrospective, multi-center study of adult inflammatory bowel disease patients with prescriptions for an advanced therapy in two geographically distinct academic gastroenterology practices; one with and the other without a dedicated pharmacist.
Purpose: In the adult literature, allograft reconstruction of gapped peripheral nerve injuries has gained popularity over autologous nerve grafting. Allografts have demonstrated similar recovery while eliminating donor site morbidity. There is no well-defined incidence or treatment of such injuries in children.
View Article and Find Full Text PDFIntroduction: The transformative feature of Artificial Intelligence (AI) is the massive capacity for interpreting and transforming unstructured data into a coherent and meaningful context. In general, the potential that AI will alter traditional approaches to student research and its evaluation appears to be significant. With regard to research in global health, it is important for students and research experts to assess strengths and limitations of GenAI within this space.
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