Assessing a cut-off point for the diagnosis of abnormal uterine bleeding using the Menstrual Bleeding Questionnaire (MBQ): a validation and cultural translation study with Brazilian women
Keywords:
Metrorrhagia, Translations, Validation study [publication type], Abnormal uterine bleeding, Menstrual bleeding questionnaire, Prospective cohort studyAbstract
BACKGROUND: Abnormal uterine bleeding (AUB) is a common condition, and the Menstrual Bleeding Questionnaire (MBQ) is used for its assessment.
OBJECTIVES: To translate, assess the cut-off point for diagnosis, and explore psychometric properties of the MBQ for use in Brazilian Portuguese.
DESIGN AND SETTING: Prospective cohort study including 200 women (100 with and 100 without AUB) at a tertiary referral center.
METHODS: MBQ translation involved a pilot-testing phase, instrument adjustment, data collection, and back-translation. Cut-off point was obtained using receiver operating curve analysis. Menstrual patterns, impact on quality of life due to AUB, internal consistency, test-retest, responsiveness, and discriminant validity were assessed. For construct validity, the Pictorial Blood Assessment Chart (PBAC) and World Health Organization Quality of Life – abbreviated version (WHOQOL-BREF) were applied.
RESULTS: Women with AUB were older, had higher body mass indices, and had a worse quality of life during menstruation. Regarding the MBQ’s psychometric variables, Cronbach’s alpha coefficient was > 0.70 in all analyses, high intraclass correlation coefficient was found in both groups; no ceiling and floor effects were observed, and construct validity was demonstrated (correlation between MBQ score, PBAC score, and clinical menstrual cycle data). No difference between MBQ and PBAC scores were perceived after the test-retest. Significant differences were found between MBQ and PBAC scores before and after treatment. An MBQ score ≥ 24 was associated with a high probability of AUB; accuracy of 98%.
CONCLUSION: The MBQ is a reliable questionnaire for Brazilian women. The cut-off ≥ 24 shows high accuracy to discriminate AUB.
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