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Kazakh version of the beck depression inventory: Validation study in female cancer patients.


ABSTRACT: This study aimed to evaluate the validity of the Beck Depression Inventory (BDI-II) as a screening tool for depression among Kazakh-speaking female cancer patients. A cross-sectional study design with random sampling was used to collect and analyze data from 115 female cancer patients. Means, sensitivity, specificity, and positive and negative predictive values were calculated. An analysis of receiver operating characteristic (ROC) curves was conducted to determine the optimal cut-off score for the BDI-II in this population as a screening tool for depression. Test-retest reliability and internal consistency were also tested. Results showed that using a BDI-II cut score of 15 retained high sensitivity (82.7%), increased specificity (75.0%), and improved positive (86.1%) and negative predictive values (69.8%) of the BDI-II compared to a cut score of 14. Kazakh BDI-II indicated excellent consistency (Cronbach's alpha of 0.86) and reliability (intraclass correlation coefficient (ICC) of 0.92 (95% CI [0.89-0.94])). The use of this valid screening tool can facilitate the diagnosis of depression in female cancer patients.

SUBMITTER: Karibayeva I 

PROVIDER: S-EPMC10372230 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Kazakh version of the beck depression inventory: Validation study in female cancer patients.

Karibayeva Indira I   Turdaliyeva Botagoz B   Zainal Nor Zuraida NZ   Bagiyarova Fatima F   Kussainova Dinara D  

Heliyon 20230710 7


This study aimed to evaluate the validity of the Beck Depression Inventory (BDI-II) as a screening tool for depression among Kazakh-speaking female cancer patients. A cross-sectional study design with random sampling was used to collect and analyze data from 115 female cancer patients. Means, sensitivity, specificity, and positive and negative predictive values were calculated. An analysis of receiver operating characteristic (ROC) curves was conducted to determine the optimal cut-off score for  ...[more]

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