Is Exhaustion More Sensitive Than Disengagement to Burnout in Academic Anesthesia? A Study Using the Oldenburg Burnout Inventory

Abstract

Reportedly, clinicians of all kinds are experiencing alarming rates of burnout, and its prevalence among anesthesia providers is high. We examined burnout in a large academic anesthesia department with a commonly used questionnaire, the Oldenburg Burnout Inventory, which provides scores on two scales, “exhaustion” and “disengagement.” We examined differences in scores between exhaustion and disengagement and their prevalences. All N = 415 staff members of the department were requested to complete the Oldenburg Burnout Inventory and N = 130 (31%) did so. The mean ± standard deviation was 2.52 ± 0.51 (range, 1.13 to 3.75) for exhaustion and 2.27 ± 0.52 (range, 1.13 to 3.63) for disengagement. The mean for exhaustion exceeded that for disengagement by 0.25 ± 0.42 (range, −1.25 to 1.25), t(129)=6.68, p < 0.0001 by paired t test. Mean ratings exceeded the midpoint (2.5) between the “burned out” and “not burned out” ends of the rating scale for 49% of respondents for exhaustion, but only 30% for disengagement. More respondents (N = 87, 67%) had a higher mean for exhaustion than disengagement than the opposite pattern (N = 28, 22%), M = 29.5, p < 0.0001 by sign test. Thus, burnout symptoms were common but reflected more in exhaustion than disengagement. Literature review suggested that the difference between the exhaustion and disengagement means that we found was larger than typical, but not unusual, for health-care-related groups, and typical for other groups. Future studies should clarify circumstances under which exhaustion exceeds disengagement and vice versa, both in anesthesia and other fields.

Burnout among German oncologists: A cross-sectional study in cooperation with the Arbeitsgemeinschaft Internistische Onkologie Quality of Life Working Group

“…Since there is no standard cutoff for burnout in the OLBI, we rst used M OLBI ≥ 2.18 as the mean value of the disengagement and exhaustion scales (Peter Chernoff, Adedokun, O'Sullivan, McManus, & Payne, 2019). Further analyses are limited to the more sensitive cutoff of M Exh ≥ 2.5 (Block, Bair, & Carillo, 2020) for the exhaustion subscale as a "burnout measure." Furthermore, sociodemographic data, profession, medical eld, professional experience, workplace, and employment status, board certi cation, work on inpatient palliative care unit (PCU) and participation in an outpatient palliative care team (Spezialisierte Ambulante Palliativversorgung (SAPV)) were assessed, including the estimated proportion of total working time, proportion of inpatient work, working hours with tumor patients and the estimated proportion of working time with palliative patients.…”

<p>Response to Burnout as a State: Random-Intercept Cross-Lagged Relationship Between Exhaustion and Disengagement in a 10-Day Study [Letter]</p>

“…In a study not cited in their article, we recently examined the relationship between exhaustion and disengagement in an academic anesthesia department. 3 Our study involved a one-time administration of the OLBI. We noted that the mean for exhaustion exceeded that for disengagement, ie, burnout symptoms were reflected more in exhaustion than disengagement.…”

Within- and between-person factor structure of the Oldenburg Burnout Inventory: Analysis of a diary study using multilevel confirmatory factor analysis

“…In line with the processual nature of “burning out,” exhaustion is assumed to develop first, as a response to excessive job demands and work overload [ 22 ]. In this light, the common opinion that exhaustion is a critical component of burnout is unsurprising [ 20 – 22 ]. Another argument supporting this view was provided in a study by Schonfeld et al [ 23 ] using exploratory structural equation modelling bifactor analysis.…”