Residency training programs to support residents working in First Nations, Inuit, and Métis communities.

Background: To gain culturally appropriate awareness of First Nations, Inuit and/or Métis Health, research suggests that programs focus on sending more trainees to First Nations, Inuit and/or Métis communities Working within this context provides experiences and knowledge that build upon classroom education and support trainees' acquisition of skills to engage in culturally safe healthcare provision. This study examines residents' and faculty members' perceptions of how residency training programs can optimize First Nations, Inuit and/or Métis health training and support residents in gaining the knowledge, skills, and experiences for working in and with First Nations, Inuit and/or Métis communities.

Methods: A qualitative approach was used, guided by a relational lens for collecting data and a constructivist grounded theory for data interpretation.

Erratum: Publisher Correction: The protective effect of endurance running against the pro-invasive effects of ageing in breast cancer cells and mesenchymal stem cells in vitro.

[This corrects the article DOI: 10.1007/s44164-023-00055-y.].

Systemic inequities and sources of resilience: challenges faced by Indigenous women living with HIV during COVID-19 in the Canadian prairies.

This study explored the challenges faced by, and resilience of First Nations, Métis, and Inuit women living with HIV in Manitoba and Saskatchewan during the COVID-19 pandemic. Through a decolonizing, community-based research approach, guided by a Community Guiding Circle (CGC), interviews were conducted with 45 Indigenous women living with HIV. Participants were recruited via community outreach, peer networks, and social media.

Understanding Data Differences across the ENACT Federated Research Network.

Objective: Federated research networks, like Evolve to Next-Gen Accrual of patients to Clinical Trials (ENACT), aim to facilitate medical research by exchanging electronic health record (EHR) data. However, poor data quality can hinder this goal. While networks typically set guidelines and standards to address this problem, we developed an organically evolving, data-centric method using patient counts to identify data quality issues, applicable even to sites not yet in the network.