Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí hóa học đề tài : Towards a brief definition of burnout syndrome by subtypes: Development of the “Burnout Clinical Subtypes Questionnaire” (BCSQ-12) | Montero-Marín et al. Health and Quality of Life Outcomes 2011 9 74 http content 9 1 74 HEALTH AND QUALITY OF LIFE OUTCOMES RESEARCH Open Access Towards a brief definition of burnout syndrome by subtypes Development of the Burnout Clinical Subtypes Questionnaire BCSQ-12 ị r i i r l A f l A r t 1 2 z r c 1 f I zz lz I r 3 4 D t r A I 115 zl I n zv z- Ỉ r 1 Jesus Montero-Marin Petros Skapinakis Ricardo Araya Margarita Gill and Javier Garcia-Campayo Abstract Background Burnout has traditionally been described by means of the dimensions of exhaustion cynicism and lack of eficacy from the Maslach Burnout Inventory-General Survey MBI-GS . The Burnout Clinical Subtype Questionnaire BCSQ-12 comprising the dimensions of overload lack of development and neglect is proposed as a brief means of identifying the different ways this disorder is manifested. The aim of the study is to test the construct and criterial validity of the BCSQ-12. Method A cross-sectional design was used on a multi-occupational sample of randomly selected university employees n 826 . An exploratory factor analysis EFA was performed on half of the sample using the maximum likelihood ML method with varimax orthogonal rotation while confirmatory factor analysis CFA was performed on the other half by means of the ML method. ROC curve analysis was preformed in order to assess the discriminatory capacity of BCSQ-12 when compared to MBI-GS. Cut-off points were proposed for the BCSQ-12 that optimized sensitivity and specificity. Multivariate binary logistic regression models were used to estimate effect size as an odds ratio OR adjusted for sociodemographic and occupational variables. Contrasts for sex and occupation were made using Mann-Whitney U and KrusKall-Wallis tests on the dimensions of both models. Results EFA offered a solution containing 3 factors with eigenvalues 1 explaining of variance. CFA presented the following indices c2 p c2 gl GFI AGFI RMSEA .
