It was adopted as a second tool to measure burnout because it enabled the direct comparison of results between this study to the many other studies of anesthesiology residents which used the aMBI. The abbreviated version of the MBI-HSS (aMBI) contains 12 of the 22 questions from the MBI-HSS but utilizes different cut-offs to define burnout. It is the most commonly used and validated tool to detect burnout in clinicians so it was considered as the gold standard. The 22-question Maslach Burnout Inventory for healthcare professionals (MBI-HSS) contains three subscales, which assess emotional exhaustion (EE), depersonalization (DP), and a sense of low personal achievement (LPA). Of these, the SingHealth Anesthesiology Residency Program (SHARP) is the largest training program spanning three hospitals, therefore, establishing the prevalence of burnout in SHARP would be a good indication of the prevalence of burnout among anesthesiology residents in Singapore. There are three anesthesiology residency training programs in Singapore that come under the purview of the Accreditation Council of Graduate Medical Education International (ACGME-I). Addressing burnout in anesthesiology residents early, reduces the detrimental effects on long-term physical and mental health, thereby prolonging the longevity and well being of a skilled workforce. In a national US study, the prevalence of burnout, distress and depression in 5295 anesthesiology residents were reported as 51%, 32% and 12%, respectively. Indeed, recent studies have suggested that burnout is common in anesthesiology residents and trainees. Īnesthesiology is a stressful specialty and a self-perceived lack of personal accomplishment may be more common because efforts for safe anesthesia are often not acknowledged. Furthermore, clinicians experiencing burnout may develop depression, sleep disturbances, alcoholism, musculoskeletal disorders, hypertension and ischemic heart disease.
MASLACH BURNOUT INVENTORY TEST PROFESSIONAL
Nonetheless, undetected and unaddressed, clinician burnout can result in poorer patient satisfaction, impaired professionalism and communication, depression and suicidal ideations, professional errors and near misses, which may impact patient outcomes. Globally, it is estimated that 30–50% of clinicians experience symptoms of burnout, but it is unclear whether these symptoms translate into burnout syndrome. Since May 2019, burnout has been recognized as an “occupational phenomenon” in the 11th revision of the International Classification of Disease published by the World Health Organization.
Although there was a good correlation between the MBI-HSS and aMBI subscale scores, the positive predictive value of the aMBI was poor 33.3% (95% CI:27.5–39.8%), therefore caution and clinical correlation are advised when using the aMBI tool because of the high rates of false-positives.īurnout is a work-related syndrome characterized by depersonalization, emotional exhaustion, and low personal accomplishment, leading to detrimental professional and personal consequences. Compared to the actual prevalence of burnout in our cohort, the MBI-HSS detected burnout most accurately area under receiver operating characteristic of 0.99 (95% confidence interval (CI): 0.92–1.0).
Burnout proportions reported by the MBI-HSS and aMBI were found to be significantly different 22.4% vs. Maslach-recommended cut-offs for the MBI-HSS and the aMBI with standard cut-offs were used to estimate burnout prevalence, and actual prevalence was established clinically by a thorough review of multiple data sources.
The MBI-HSS and aMBI were distributed amongst 86 residents across three hospitals, with a total of 58 residents completing the survey (67.4% response rate 17 male and 41 female). A wide range in burnout prevalence is reported in anesthesiology, so this study aimed to ascertain which of these two tools most accurately detected burnout in our anesthesiology residents.
The Maslach Burnout Inventory for healthcare professionals (MBI-HSS) and its abbreviated version (aMBI), are the most common tools to detect burnout in clinicians.
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