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. 2022 Apr 18;12(4):e052329. doi: 10.1136/bmjopen-2021-052329

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© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Flow chart of the data analysis related to the first secondary aim: ‘to investigate which factors are influencing the presence of probable awake/sleep bruxism, temporomandibular disorders (TMD) pain and the frequency of definite awake/sleep bruxism’. All variables will be tested individually to see whether an association with the dependent variable (awake and sleep bruxism and TMD pain) exists, and to see how strong this association is (step 1). This dataset will be analysed for both probable bruxism and TMD pain with the use of logistic regression analyses. For definite bruxism, a linear regression analysis will be used (step 2). The forward selection procedure will be used for the (strongest) independent variables until all variables in this regression model show a p value <0.05 (step 2). In both step 1 and step 2, a distinction will be made between sleep and awake bruxism.