December 31, 2020
1 min read
Disclosures: One study author reports receiving personal fees from Shire/Takeda outside the submitted work. The other authors report no relevant financial disclosures.
Burnout and clinical symptoms of anxiety and depression were empirically distinct among ICU clinicians, according to results of a cross-sectional study published in JAMA Network Open.
“There is currently a significant level of discussion and debate about the associations and distinctiveness of burnout with other mental health problems, including depression and anxiety,” Ronald Fischer, PhD, of the Institute D’Or for Research and Teaching in Brazil, and colleagues wrote. “A 2018 systematic review indicated that the heterogeneity of published research does not allow a reliable examination of comorbidities, raising questions about whether it is possible to clearly distinguish burnout as an occupational syndrome from potentially underlying comorbidities. Similarly, studies in non-health sectors come to conflicting conclusions about the burnout-depression association.”
The researchers aimed to assess the correlations and distinctiveness of burnout, depression and anxiety among 715 ICU clinicians whose data were available in the ICU Visits Study, a cluster-randomized crossover clinical trial conducted between April 2017 and July 2018 among 36 mixed public and private nonprofit ICUs in Brazil. Participants included dayshift physicians, nurses, nurse technicians and physiotherapists who worked in an ICU 20 hours or more per week. Main outcome measures included burnout, depression and anxiety according to the Maslach Burnout Inventory (MBI) and the Hospital Depression and Anxiety Scale (HADS).
Results showed low levels of emotional exhaustion and personal accomplishment on the MBI and similarly low levels of anxiety and depression on the HADS. According to confirmatory factor analyses, there was consistent evidence of improved fit separating latent burnout dimensions from anxiety and depression. The researchers noted reported results of an exploratory graph analysis that combined gaussian graphical model with clustering algorithms for weighted networks and suggested three clusters, with distinctions for burnout, anxiety and depression. A bootstrap with 1,000 random samples, in which the three-cluster solution was apparent among 625 samples, confirmed this structure. Network statistics and latent variable loadings suggested three key indicators that can be used for short screening instruments. These were feeling burned out from work, worrying thoughts and reverse-scored reporting feeling cheerful.
“Practitioners should screen for burnout as a work-related stress syndrome and for clinical syndromes, such as depression and anxiety, to provide appropriate diagnosis and offer appropriate treatment,” Fischer and colleagues wrote. “Our analysis offers options for measuring core constructs for screening purposes.”