How to conduct research on burnout: advantages and disadvantages of a unidimensional approach in burnout research

• Published in: Occupational and environmental medicine (London, England) Vol. 60; no. suppl 1; pp. i16 - i20
• Main Authors: Brenninkmeijer, V, VanYperen, N
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group Ltd 01-06-2003; BMJ Publishing Group; BMJ Publishing Group LTD; BMJ Group
• Subjects: Adult; Burnout; Burnout, Professional - diagnosis; Continuous variables; Decision trees; Exhaustion; False positive errors; Female; Humans; Logistic regression; Male; methodology; Middle Aged; Occupational Diseases - diagnosis; occupational stress; Psychological stress; Psychometrics; Research Design; Researchers; Social comparison; Statistical variance; Surveys and Questionnaires
• ISSN: 1351-0711; 1470-7926
• DOI: 10.1136/oem.60.suppl_1.i16

When conducting research on burnout, it may be difficult to decide whether one should report results separately for each burnout dimension or whether one should combine the dimensions. Although the multidimensionality of the burnout concept is widely acknowledged, for research purposes it is sometimes convenient to regard burnout as a unidimensional construct. This article deals with the question of whether and when it may be appropriate to treat burnout as a unidimensional variable, and presents a decision rule to distinguish between people high and low in burnout. To develop a guideline for obtaining a dichotomous measure of burnout, the scores on the Utrecht Burnout Scale (UBOS) of 44 well functioning individuals were compared with the scores of 29 individuals diagnosed as suffering from burnout. Based on these data, the authors recommend the “exhaustion + 1” criterion for research in non-clinical populations. Following this criterion, individuals can be considered as burnt out when they report, compared to a norm group, high emotional exhaustion, in combination with high depersonalisation or low personal accomplishment. The criterion may be used to estimate the percentage in a sample of individuals in a state of burnout.