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Psychometric properties of the Breast Cancer Awareness Measurement among Chinese women: a cross-sectional study

Na Liu, Ping Li, Jie Wang, Dandan Chen, Weijia Sun, Pingping Guo, Xuehui Zhang, Wei Zhang

2020BMJ Open17 citationsDOIOpen Access PDF

Abstract

Objectives To perform the cross-cultural adaption of the Breast Cancer Awareness Measurement (BCAM) and to test its psychometric properties among Chinese women. Design This is a cross-sectional study. Settings This study was conducted in communities, schools and institutions in Changchun, Jilin Province, China. Participants A total of 328 women voluntarily participated in and completed the Chinese version of the BCAM (C-BCAM), resulting in an effective response rate of 91.1%. Primary and secondary outcome measures Psychometric properties, including item analysis (the extreme group comparison and item-total correlations), content validity (item-level content validity index (I-CVI) and scale-level content validity index (S-CVI)), construct validity (exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)) and internal consistency (Cronbach’s α and test–retest reliability), were measured. Results The C-BCAM has excellent internal consistency (Cronbach’s α=0.90), with alpha coefficients of 0.88, 0.84 and 0.94 for its three domains. The test–retest reliability coefficient was 0.72. The I-CVI ranged from 0.86 to 1.00, and the S-CVI was 0.92. CFA showed that the three-factor model explained 51.56% of the total variance, with a good model fit (likelihood ratio χ 2 /df=1.86, incremental fit index=0.94, comparative fit index=0.94, goodness-of-fit index=0.84, adjusted goodness-of-fit index=0.80, standardised root mean square error of approximation=0.06 and root mean square residual=0.05). Conclusions The C-BCAM has satisfactory validity and reliability and is a culturally appropriate and reliable tool for evaluating breast cancer awareness among Chinese women. This reliable instrument can help researchers and health professionals evaluate women’s knowledge about the symptoms and risk factors of breast cancer and identify their barriers to seeking medical help. It also helps healthcare providers identify women with poor breast cancer awareness and encourage them to perform screening practice.

Topics & Concepts

Cronbach's alphaConfirmatory factor analysisConstruct validityMedicineBreast cancer awarenessExploratory factor analysisContent validityGoodness of fitStatisticsReliability (semiconductor)Index (typography)Clinical psychologyPsychometricsBreast cancerStructural equation modelingCancerInternal medicineMathematicsWorld Wide WebQuantum mechanicsComputer sciencePhysicsPower (physics)Global Cancer Incidence and ScreeningCancer survivorship and careHealth Education and Validation
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