Orthodontic Compliance Assessment: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: The aim of this review was to determine whether the type of removable appliance, as well as the age and sex of the patient, may affect the extension or reduction of wear time by assessing the correlation between the mean actual and orthodontist-recommended wear times. METHODS: Randomised case control trials, cohort studies, case series, observational studies, reviews, and retrospective analyses were identified. The quality of the studies was assessed using the Cochrane Collaboration Tool and modified Newcastle-Ottawa Scale. The electronic databases Embase, PubMed, Scopus, and Web of Science were reviewed, and 542 articles were obtained, of which 31 were qualified for qualitative synthesis. The data from 1674 participants were collected and a weighted average was determined for the mean wear time of each appliance. RESULTS: Regardless of the type of extra- or intraoral appliances, mean wear time was shorter than recommended, although patients using intraoral appliances cooperated more. The best compliance was noted for Schwarz appliances (73.70%) and plate retainers (85%). There was no evidence of an influence of patients' age and sex on compliance during treatment. CONCLUSIONS: The considerable inconsistency and imprecision of articles could affect the reliability of the results. Previous studies analysing the effectiveness of treatment with removable appliances based on an arbitrarily assumed average wear time need to be revised in order to verify the actual wear time with the use of microsensors.
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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 | 0.017 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".