Background: Bruxism is when a person habitually clenches or grinds their teeth. It is a form of parafunctional activity that occurs during sleep and during periods of alertness. This activity can be heard as a grinding or clicking sound and cause facial and/or jaw pain. Bruxism is classified into two categories: sleep bruxism, which occurs during sleep, and awake bruxism, which occurs during periods of alertness. The exact cause of bruxism is unknown. However, there are many potential contributing factors. STAB is a new tool to diagnose bruxism and evaluate possible comorbidities. It has two Axis. Subjectrelated reports on bruxism conditions and possible outcomes are part of Axis A and include clinical (researcher reports) and instrumental assessments (technical reports). Axis B contains self-reported data (subject-based reports) on variables and conditions that may be causal or ancillary in bruxism. This review aims to evaluate the possible use of STAB in the diagnosis of bruxism; Methods: PubMed, Web of Science and Lilacs were systematically searched until 31/01/2023. In addition, amanual search was performed using the bibliography of selected articles and a Google Scholar search. It was completed, and the papers were read to assess their eligibility. Results: The STAB will assist in gathering data on various elements, conditions, and circumstances presently understudied in bruxism. It is split into two axes for this reason. Conclusion: Subject-based reports on bruxism status and possible consequences are part of Axis A, along with clinical (examiner reports) and instrumental assessments (technology report). Self-reported data (subject-based report) on variables and conditions that may play a causal or concomitant part in bruxism are included in axis B. Building predictive models for use in clinical and research settings will be possible thanks to this complete multidimensional assessment system.

Standardized Tool for the Assessment of Bruxism (STAB): A New Method to Assess the Temporomandibular Disorder Patients

Minervini, Giuseppe
;
2024

Abstract

Background: Bruxism is when a person habitually clenches or grinds their teeth. It is a form of parafunctional activity that occurs during sleep and during periods of alertness. This activity can be heard as a grinding or clicking sound and cause facial and/or jaw pain. Bruxism is classified into two categories: sleep bruxism, which occurs during sleep, and awake bruxism, which occurs during periods of alertness. The exact cause of bruxism is unknown. However, there are many potential contributing factors. STAB is a new tool to diagnose bruxism and evaluate possible comorbidities. It has two Axis. Subjectrelated reports on bruxism conditions and possible outcomes are part of Axis A and include clinical (researcher reports) and instrumental assessments (technical reports). Axis B contains self-reported data (subject-based reports) on variables and conditions that may be causal or ancillary in bruxism. This review aims to evaluate the possible use of STAB in the diagnosis of bruxism; Methods: PubMed, Web of Science and Lilacs were systematically searched until 31/01/2023. In addition, amanual search was performed using the bibliography of selected articles and a Google Scholar search. It was completed, and the papers were read to assess their eligibility. Results: The STAB will assist in gathering data on various elements, conditions, and circumstances presently understudied in bruxism. It is split into two axes for this reason. Conclusion: Subject-based reports on bruxism status and possible consequences are part of Axis A, along with clinical (examiner reports) and instrumental assessments (technology report). Self-reported data (subject-based report) on variables and conditions that may play a causal or concomitant part in bruxism are included in axis B. Building predictive models for use in clinical and research settings will be possible thanks to this complete multidimensional assessment system.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/546360
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