Burnout syndrome in medical oncologists during the COVID-19 pandemic: Argentinian national survey.

Abstract

Burnout (BO) syndrome is a condition that results in physical and mental distress. The current COVID-19 pandemic is strongly affecting the mental health of the general population. We aimed to assess the incidence of BO among medical oncologists and determine factors associated with burnout levels during the current pandemic.MethodsA digital survey was created for this study. The Spanish-validated version of Maslach BO Inventory was incorporated to define BO. Social and demographic information was analysed to remove duplicated answers.ResultsA total of 188 Argentinian medical oncologists from 16 cities participated in the survey. The median age of the participants was 43 years (IQR 38-50) and a similar distribution between male and female was observed. At the time of the survey, Argentina was in the third month of strict lockdown. Most of the participants practiced in both public and private practice facilities (55.3%) and the majority reported more than 10 years of experience (53.2%). Twenty-five percent (43) of subjects reported high levels of DP, 39.9% (75) reported high levels of EE and 53.7% (101) reported low levels of PA. BO Maslach criteria were fulfilled by 14.9% (28). We compared this result with other burnout assessment tools. Using the Gil-Monte and Neira tool, BO-associated domains were altered in 77.1%, 42% and 42% for EE, DP, and PA domains, respectively. Concomitantly, under Neira assessment a domain impairment was appreciated in 77.1%, 76% and 54% respectively. BO criteria were met by 30.3% (57) according to Gil-Monte and 47.9% (90) to Neira.ConclusionBO is a multifaceted issue with a negative impact on physicians, patients, and institutions. During the COVID-19 pandemic, BO criteria was met in a considerable proportion of survey respondents using MBI, and Peiro and Neiro tools and younger age, use of antidepressants and psychological medications and income reduction arose as statistically significant factors after multivariate analysis.