Adherence to behaviours associated with the test, trace, and isolate system: an analysis using the theoretical domains framework - Rachael J. Thorneloe; Elaine N. Clarke; Madelynne A. Arden (BMC, 2022)
Abstract Background The UK's test, trace, and isolate system are key measures to reduce the impact and spread of COVID-19. However, engagement with and adherence to guidance on testing, self-isolation, and providing details of contacts can be low and interventions are needed. This qualitative study aimed to identify the key factors affecting adherence to test, trace, and isolate behaviours using the Theoretical Domains Framework (TDF). Methods We conducted six online focus groups between October 2020 and February 2021 with people living in Sheffield who came into close contact with others in work or social settings (N = 30). The focus groups explored capability, opportunity, and motivational barriers to adherence to test, trace, and isolate behaviours. Framework analysis was used to code the data into TDF domains. Results There is a complex relationship between the factors affecting COVID-19 symptom identification, testing, and self-isolation. People who perceived significant barriers to testing and self-isolation were less likely to interpret potential symptoms as COVID-19, and perceiving barriers to self-isolation reduced the likelihood of requesting a test. Concerns about the negative consequences of self-isolation for themselves and others were common and also influenced willingness to pass on details of contacts. There was a lack of trust in the Test and Trace system, with people wanting further evidence of being at risk of infection. Conclusions Communications and interventions to increase adherence to test, trace, and isolate strategies need to consider the interplay of these behaviours and their influences and target them collectively. Efforts to promote testing should focus on the range of barriers to self-isolation, especially increasing financial and practical support, and include new messaging to promote symptom identification.