Right Information, Right Care, Right Patient, Right Time: Community Preferences to Inform a Self-Management Support Tool for Upper Respiratory Symptoms.

Introduction: During and after the COVID-19 pandemic, communities must cope with several conditions that cause similar upper-respiratory symptoms but are managed differently. We describe community reactions to a self-management toolkit for patients with upper respiratory symptoms to inform mobile e-health app development. The toolkit is based on the '4R' (Right Information, Right Care, Right Patient, Right Time) care planning and management model.

Self-Reported Financial Difficulties Among Patients with Multiple Myeloma and Chronic Lymphocytic Leukemia Treated at U.S. Community Oncology Clinics (Alliance A231602CD).

Objectives: To estimate the proportion and correlates of self-reported financial difficulty among patients with multiple myeloma (MM) or chronic lymphocytic leukemia (CLL).

Setting: 23 U.S.

Research protocol for bridging research, accurate information and dialogue (BRAID)-clinical trials: a mixed-methods study of a community-based intervention to improve trust and diversify participation in clinical trials.

Cultural beliefs, personal experiences, and historic abuses within the healthcare system-rooted in structural racism-all contribute to community distrust in science and medicine. This lack of trust, particularly within underserved communities, contributes to decreased participation in clinical trials and a lack of representation in the data. Open dialogue about community concerns and experiences related to research participation and medical care processes can help build trust and change attitudes and behaviors that affect community health.

The faces of Long-COVID: interplay of symptom burden with socioeconomic, behavioral and healthcare factors.

Aims: The long-term effects of COVID-19 (Long COVID) include 19 symptoms ranging from mild to debilitating. We examined multidimensional correlates of Long COVID symptom burden.

Methods: This study focused on participants who reported having had COVID in Spring 2023 (n = 656; 85% female, mean age = 55, 59% college).