[HTML][HTML] Translation and validation of the Copenhagen Burnout Inventory amongst Greek doctors

E Papaefstathiou, A Tsounis, M Malliarou… - Health psychology …, 2019 - ncbi.nlm.nih.gov
E Papaefstathiou, A Tsounis, M Malliarou, P Sarafis
Health psychology research, 2019ncbi.nlm.nih.gov
Abstract The Copenhagen Burnout Inventory (CBI) is a tool for burnout measurement and
includes three different subscales:(i) personal,(ii) work-related and (iii) client-related
burnout. The aim of this study was the translation and validation of CBI into the Greek
Language. The forward-backward translation method was performed. Initially the
questionnaire was distributed to 35 medical students for face validity assessment. Then, 284
residents answered the Greek version of CBI so as for construct validity to be examined. The …
Abstract
The Copenhagen Burnout Inventory (CBI) is a tool for burnout measurement and includes three different subscales:(i) personal,(ii) work-related and (iii) client-related burnout. The aim of this study was the translation and validation of CBI into the Greek Language. The forward-backward translation method was performed. Initially the questionnaire was distributed to 35 medical students for face validity assessment. Then, 284 residents answered the Greek version of CBI so as for construct validity to be examined. The data analysis was performed by using SPSS and AMOS. Face validity was estimated above 0.8 for the Greek version of CBI. The three factors model of CBI-Greek, with 1 item removed, achieved not so well-defined inner structure in CFI. However, the 16-item model achieved good levels of goodness-of-fit indices (Cmin/df 2.52, RMSEA 0.074, GFI 0.901, CFI70. 938, NFI 0.901, TLI 0.923). The composite reliability values, also varied from 0.842 to 0.852. Cronbach’s alpha index values surpassed 0.844. The 16-item model of CBI-Gr is a valid tool with high internal consistency that can be used in the evaluation of burnout in Greek population. The original 3-items model is a possible alternative.
ncbi.nlm.nih.gov
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