Effectiveness of orofacial myofunctional therapy in improving orofacial function and oral habits: a scoping review.
Bibliographic record
Abstract
Background: The effectiveness of orofacial myofunctional therapy (OMT) has yet to be confirmed in the literature. This scoping review aimed to answer the question, "What evidence exists to support the effectiveness of OMT in treating/managing orofacial myofunctional disorders (OMDs) affecting orofacial structures' function and oral habits?" Methods: A librarian at the University of Alberta, Canada, developed a comprehensive search strategy and applied it to 6 databases and grey literature. The reference lists of included studies were cross-checked. Two independent reviewers screened the retrieved records in 2 phases; 1 extracted data. The evidence level of each article was assessed using the Oxford CEBM Levels of Evidence. A third reviewer solved conflicts. Results: After screening 11,518 records, 58 were included (50 primary studies and 8 reviews). The addressed OMDs were ankyloglossia (8 studies), atypical swallowing (9 studies), lip incompetence (13 studies), mouth breathing (10 studies), non-nutritive sucking habit (10 studies), low tongue position at rest (2 studies), and simultaneous OMDs (9 studies). Only 11 studies (19%) were randomized controlled trials. Most presented no proper randomization process and no allocation concealment description; half were open-label studies. Although 86% of primary studies reported positive results using OMT, of 12 comparisons found, only 9 were considered plausible (6 at level of evidence 3, 2 at level 2, and 1 at level 1). None was deemed to have confirmed the effectiveness of OMT. Discussion: Conducting methodologically sound clinical trials with larger samples and longer follow-ups is crucial to answering the research question. Conclusion: In some scenarios, OMT produces clinical changes. However, insufficient high-level evidence exists to fully confirm OMT's effectiveness.
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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 | 0.032 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".