Clinical and Translational Radiation Oncology (Nov 2022)
An impact model to understand and improve work-life balance in early-career researchers in radiation oncology
Abstract
Purpose: The COVID-19 pandemic had a substantial effect on mental health and work productivity of early-career researchers working in Radiation Oncology (RO). However, the underlying mechanisms of these effects are unclear. The aim of the current qualitative study was therefore to achieve a better understanding of how these effects arose and could be managed in the future. Methods: This study was conducted jointly by RO and qualitative health researchers. Data was collected in four online Focus Groups with 6–11 RO researchers (total N = 31) working in Europe. The transcripts were analysed through a qualitative cross-impact analysis. Results: Causal relations were identified between seventeen variables that depict the impact of disrupted working conditions. Mental health and work productivity were indeed the most important affected variables, but relations between variables towards these impacts were complex. Relations could either be positive or negative and direct or indirect, leading to a cascade of interrelated events which are highly personal and could change over time. We developed the model ‘impact of disrupted working conditions’ depicting the identified variables and their relations, to allow more individual assessment and personalised solutions. Conclusion: The impacts of disrupted working conditions on RO researchers varied due to the complexity of interrelated variables. Consequently, collective actions are not sufficient, and a more personal approach is needed. Our impact model is recommended to help guide conversations and reflections with the aim of improving work/life balance. The participants showed high levels of personal responsibility towards their own mental health and work productivity. Although being an individual issue, a collective responsibility in developing such approaches is key due to the dependency on organizational variables.