Standardised Tool for the Assessment of Bruxism
Bibliographic record
Abstract
OBJECTIVE: This paper aims to present and describe the Standardised Tool for the Assessment of Bruxism (STAB), an instrument that was developed to provide a multidimensional evaluation of bruxism status, comorbid conditions, aetiology and consequences. METHODS: The rationale for creating the tool and the road map that led to the selection of items included in the STAB has been discussed in previous publications. RESULTS: The tool consists of two axes, specifically dedicated to the evaluation of bruxism status and consequences (Axis A) and of bruxism risk and etiological factors and comorbid conditions (Axis B). The tool includes 14 domains, accounting for a total of 66 items. Axis A includes the self-reported information on bruxism status and possible consequences (subject-based report) together with the clinical (examiner report) and instrumental (technology report) assessment. The Subject-Based Assessment (SBA) includes domains on Sleep Bruxism (A1), Awake Bruxism (A2) and Patient's Complaints (A3), with information based on patients' self-report. The Clinically Based Assessment (CBA) includes domains on Joints and Muscles (A4), Intra- and Extra-Oral Tissues (A5) and Teeth and Restorations (A6), based on information collected by an examiner. The Instrumentally Based Assessment (IBA) includes domains on Sleep Bruxism (A7), Awake Bruxism (A8) and the use of Additional Instruments (A9), based on the information gathered with the use of technological devices. Axis B includes the self-reported information (subject-based report) on factors and conditions that may have an etiological or comorbid association with bruxism. It includes domains on Psychosocial Assessment (B1), Concurrent Sleep-related Conditions Assessment (B2), Concurrent Non-Sleep Conditions Assessment (B3), Prescribed Medications and Use of Substances Assessment (B4) and Additional Factors Assessment (B5). As a rule, whenever possible, existing instruments, either in full or partial form (i.e. specific subscales), are included. A user's guide for scoring the different items is also provided to ease administration. CONCLUSIONS: The instrument is now ready for on-field testing and further refinement. It can be anticipated that it will help in collecting data on bruxism in such a comprehensive way to have an impact on several clinical and research fields.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".