The knowledge and use of population-based methods for caries detection

了解并运用基于人群的龋齿检测方法

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Abstract

BACKGROUND: Since the 1980s, a wide variety of methods have been proposed to measure dental caries in the population, demonstrating a lack of consensus regarding the procedure that should be used for this purpose. The current study investigated the methods that are known and used by public oral health researchers and professors as well as the reasons that lead to the choice of a particular method. METHOD: In the context of an interview, a questionnaire was administered to public oral health researchers and professors who used caries indices and worked in Salvador and Feira de Santana, Bahia, Brazil from 2005 to 2015. A quantitative and descriptive approach was applied that adopted the multiple correspondence analysis (MCA) technique to assess the associations among responses. RESULTS: The decayed, missing, and filled index (DMF) was the only measurement known by all respondents, and although 45 of the 47 professors/researchers were dissatisfied with this index, only six had used other methods. This index was chosen because of its comparability and ease of application. The MCA revealed response associations among older, male participants who graduated from the Federal University of Bahia (UFBA) and who continued to use this index because of its comparability and because it is the index recommended by the World Health Organization (WHO) and the Brazilian Ministry of Health (MS). Another group was also observed that consisted of younger females who graduated from the State University of Feira de Santana (UEFS) or another university and who used the DMF because it is well-known, simple, and easy to apply. CONCLUSIONS: The DMF index was the most known and used method. Many respondents demonstrated a desire for change and were critical of the DMF; however, they did not know of and had not used newer methods for measuring dental caries. Greater importance should be placed on the problem of dental caries assessment in the population.

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