van Dam Arno
GGZ WNB Mental Health Institute, Research and InnovationHalsteren, Netherlands; Tranzo Scientific Center for Care and Welfare, Tilburg UniversityTilburg, Netherlands.
Front Psychol. 2016 Feb 4;7:90. doi: 10.3389/fpsyg.2016.00090. eCollection 2016.
Several authors have suggested that burned out patients do not form a homogeneous group and that subgroups should be considered. The identification of these subgroups may contribute to a better understanding of the burnout construct and lead to more specific therapeutic interventions. Subgroup analysis may also help clarify whether burnout is a distinct entity and whether subgroups of burnout overlap with other disorders such as depression and chronic fatigue syndrome. In a group of 113 clinically diagnosed burned out patients, levels of fatigue, depression, and anxiety were assessed. In order to identify possible subgroups, we performed a two-step cluster analysis. The analysis revealed two clusters that differed from one another in terms of symptom severity on the three aforementioned measures. Depression appeared to be the strongest predictor of group membership. These results are considered in the light of the scientific debate on whether burnout can be distinguished from depression and whether burnout subtyping is useful. Finally, implications for clinical practice and future research are discussed.
几位作者指出，职业倦怠患者并非一个同质化群体，应考虑区分亚组。识别这些亚组可能有助于更好地理解职业倦怠的构成，并带来更具针对性的治疗干预措施。亚组分析还可能有助于阐明职业倦怠是否是一个独特的实体，以及职业倦怠的亚组是否与其他疾病（如抑郁症和慢性疲劳综合征）重叠。在一组113名临床诊断为职业倦怠的患者中，对疲劳、抑郁和焦虑水平进行了评估。为了识别可能的亚组，我们进行了两步聚类分析。分析揭示了两个在上述三项指标的症状严重程度上彼此不同的聚类。抑郁似乎是分组的最强预测因素。结合关于职业倦怠是否可与抑郁症区分以及职业倦怠亚型划分是否有用的科学辩论来考虑这些结果。最后，讨论了对临床实践和未来研究的启示。
