"Trust people you've never worked with" - A social network visualization of teamwork, cohesion, social support, and mental health in NHS Covid personnel

Abstract

Background: The unprecedented rapid re-deployment of healthcare workers from different care pathways into newly created and fluid COVID-19 teams provides a unique opportunity to examine the interaction of many of the established non-technical factors for successful delivery of clinical care and teamwork in healthcare settings. This research paper therefore aims to address these gaps by qualitatively exploring the impact of COVID work throughout the pandemic on permanent and deployed personnel's experiences, their ability to effectively work together, and the effect of social dynamics (e.g., cohesion, social support) on teamwork and mental health.

Methods: Seventy-five interviews were conducted across the UK between March and December 2021 during wave 2 and 3 of COVID-19 with 75 healthcare workers who were either permanent staff on Intensive Care/High Dependency Units used as COVID wards, had been rapidly deployed to such a ward, or had managed such wards. Work Life Balance was measured using the WLB Scale. Interview transcripts were qualitatively coded and thematic codes were compared using network graph modeling.

Results: Using thematic network analysis, four overarching thematic clusters were found, (1) teamwork, (2) organizational support and management, (3) cohesion and social support, and (4) psychological strain. The study has three main findings. First, the importance of social factors for teamwork and mental health, whereby team identity may influence perceptions of preparedness, collaboration and communication, and impact on the collective appraisal of stressful events and work stressors. Secondly, it demonstrates the positive and negative impact of professional roles and skills on the development of teamwork and team identity. Lastly the study identifies the more pronounced negative impact of COVID work on deployed personnel's workload, mental health, and career intentions, exacerbated by reduced levels of social support during, and after, their deployment.

Conclusion: The thematic network analysis was able to highlight that many of the traditional factors associated with the successful delivery of patient care were impeded by pandemic constraints, markedly influencing personnel's ability to work together and cope with pandemic work stressors. In this environment teamwork, delivery of care and staff well-being appear to depend on relational and organizational context, social group membership, and psycho-social skills related to managing team identity. While results hold lessons for personnel selection, training, co-location, and organizational support during and after a pandemic, further research is needed into the differential impact of pandemic deployment on HCWs mental health and teamwork.

Keywords: COVID-19; healthcare; inter-disciplinary; inter-professional; leadership; mental health; preparedness; teamwork.

Figure 1

Graph of connections between codes in all personnel, showing 62 codes, with 4 community clusters: (1) teamwork (teal 24%), (2) psychological strain (green, 37%), (3) organization support and management (purple 13%), and (4) cohesion and social support (khaki, 26%). Lift >5, edge weight > 10, graph density: 0.271, size average weighted degree (722.58), and communities by modularity (Modularity: 0.295).

Figure 2

Graph of connections between codes in deployed personnel, showing 62 codes, with 4 community clusters: (1) teamwork (teal 26%), (2) psychological strain (green, 42%), (3) organization support and management (purple 11%), and (4) cohesion and social support (khaki, 21%). Lift >5, edge weight > 10, graph density: 0.241, size average weighted degree (414.6), and communities by modularity (Modularity: 0.384).

Figure 3

Graph of connections between codes permanent personnel, showing 62 codes, with 4 community clusters: (1) teamwork (teal 27%), (2) psychological strain (green, 27%), (3) organization support and management (purple 19%), and (4) cohesion and social support (khaki, 27%). Lift >8, edge weight > 4, graph density: 0.235, size average weighted degree (141.09), and communities by modularity (Modularity: 0.331).

Figure 4

Teamwork in deployed personnel: this graph displays the codes most connected to Teamwork in deployed personnel, by filtering Figure 2 using an ego network to only display codes connected to Teamwork. Additionally, a Fruchterman Reingold layout algorithm was applied to further highlight, through adjacency to the code teamwork, which codes share the most references with teamwork in this group.

Figure 5

Teamwork in permanent personnel: this graph displays the codes most connected to Teamwork in deployed personnel, by filtering Figure 3 using an ego network to only display codes connected to Teamwork. Additionally, a Fruchterman Reingold layout algorithm was applied to further highlight, through adjacency to the code teamwork, which codes share the most references with teamwork in this group.