http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
trust, ethics, and community creation in a digital bereavement group during COVID-19
During the COVID-19 pandemic, many programs and services transitioned online to continue to provide care. This was true of a Medical Assistance in Dying (MAiD) grief and bereavement group situated in Ontario, Canada. Research was conducted on the impact and efficacy of this bereavement group with respect to how participants generate meaning following a psychosocial intervention such as this. This research implements a mixed-methods approach to data collection with an ethnographic focus due to the researcher's training and background in medical anthropology. As a result of the COVID-19 pandemic, this group made a rapid transition from an in-person group to an online environment, affecting the methods that had been initially considered for data collection. Many lessons were learned during the research process, most notably the challenges and successes associated with building trust, obtaining ongoing consent, and the similarities and differences between a virtual and "in the field" observational environment. The researcher determined that trust-building involves a complex system of transparency and sincerity, while technological supports such as the use of multiple computer monitors to view all participants simultaneously while recording detailed "in the moment" notes rather than retrospective note-taking create a unique observational environment for the researcher. Ongoing consent became a topic of significance due to the "invisible" nature of a virtual observer and involved novel ethical considerations as a result of COVID-19. These considerations provided insight into the research process during COVID-19, and how these methods can be implemented into the future in a way that is ethical and supports a sense of community between the participants and the researcher in a population that may be perceived as vulnerable.
SAGE research methods: doing research online