Identifying and preventing burnout in young oncologists, an overwhelming challenge in the COVID-19 era: a study of the Spanish Society of Medical Oncology (SEOM)

BACKGROUND

Young oncologists are at particular risk of professional burnout, and this could have a significant impact on their health and care of their patients. The coronavirus disease 2019 (COVID-19) pandemic has forced rapid changes in professionals' jobs and training, with the consequent physical and psychological effects. We aimed to characterize burnout levels and determinants in young oncologists, and the effects of the pandemic on their training and health.

METHODS

Two online surveys were conducted among oncology residents and young oncology specialists in Spain. The first addressed professional burnout and its determinants before the COVID-19 pandemic, while the second analyzed the impact of the pandemic on health care organization, training, and physical and psychological health in the same population.

RESULTS

In total, 243 respondents completed the first survey, and 263 the second; 25.1% reported significant levels of professional burnout. Burnout was more common among medical oncology residents (28.2%), mainly in their second year of training. It was significantly associated with a poor work-life balance, inadequate vacation time, and the burnout score. Nearly three-quarters of respondents (72%) were reassigned to COVID-19 care and 84.3% of residents missed part of their training rotations. Overall, 17.2% of this population reported that they had contracted COVID-19, 37.3% had scores indicating anxiety, and 30.4% moderate to severe depression. Almost a quarter of young oncologists (23.3%) had doubts about their medical vocation.

CONCLUSIONS

Burnout affects a considerable number of young oncologists. The COVID-19 pandemic has had a profound impact on causes of burnout, making it even more necessary to periodically monitor it to define appropriate detection and prevention strategies.

Linear age-dependent population growth with seasonal harvesting

A population growth is modelled by the Von Foerster PDE with accompanying Lotka-Volterra integral equation describing the birth rate; the age specific death and fertility rates are assumed to depend only on age and not time. A harvesting policy where a fraction of the population of age greater than a given age is harvested for a fraction of a given season. This introduces a time dependence, but this difficulty is circumvented by devising approximate time-independent models whose birthrates bracket the true birthrate--the standard renewal equation theory applies to the approximate models so quantitative results can be obtained.