Objective: Weight bias is pervasive in healthcare and leads to worse patient outcomes. A uniquely designed 4-h continuing medical education (CME) intervention was assessed for changing healthcare professionals' (HCPs') weight biases and clinical practice behaviors.
Design: The intervention used a (1) pre/post design examining CME attendees' self-reported weight bias at baseline, after, and 4- and 12-month follow-up, and (2) post/post design examining obesity practice behaviors 12 months after intervention in attendees and non-attendees.
Reproductive toxicity is of special concern among the harmful effects induced by environmental pollutants; consequently, further studies on such a topic are required. To avoid the use of mammalians, lower eukaryotes like are viable alternatives. This study addresses the gap in understanding the link between reproductive adverse outcomes and the presence of pollutants in reproductive organs by using Silver nanoparticles (AgNPs) were selected for their ease of internalization, detection, and widespread environmental presence.
View Article and Find Full Text PDFIntroduction: Among older adults with cancer receiving chemotherapy, frailty indices predict OS and toxicity. Given the increased use of immunotherapy and targeted therapy for advanced non-small cell lung cancer (aNSCLC), we evaluated frailty and Karnofsky Performance Status (KPS) among older adults with aNSCLC receiving chemotherapy, immunotherapy, and/or targeted therapy.
Methods: Patients aged ≥ 65 with aNSCLC starting systemic therapy with non-curative intent underwent geriatric assessments over 6 months.
Artificial light at night (ALAN) changes animal behavior in multiple invertebrates and vertebrates and can result in decreased fitness. However, ALAN effects have not been studied in European honey bees (Apis mellifera), an important pollinator in which foragers show strong circadian rhythmicity. Colonies can be exposed to ALAN in swarm clusters, when bees cluster outside the nest on hot days and evenings, and, in limited cases, when they build nests in the open.
View Article and Find Full Text PDFIntroduction: The Implementation Research Logic Model (IRLM) aids users in combining, organizing, and specifying the relationships between important constructs in implementation research. The goal of the IRLM is to improve the rigor, reproducibility, and transparency of implementation research projects. The article describing the IRLM was published September 25, 2020 (, Vol 15); it has since been highly cited and included as a required element in multiple funding opportunity announcements from federal agencies.
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