The Impact of Gross Motor Function on the Oral Health-Related Quality of Life in Young Adults with Cerebral Palsy in Saudi Arabia
Bibliographic record
Abstract
Background. There is evidence that gross motor function impacts the health-related quality of life of young adults with cerebral palsy. This study aimed to assess gross motor function, oral health and oral health-related quality of life (OHRQoL), and the relationship between them in young adults with cerebral palsy. Methods. The sample comprised 46 individuals aged between 13 and 17 years with Gross Motor Function Classification Scores (GMFCS) ranging from level I to level III. The individuals and their parents were administered an Arabic version of the child perception questionnaire for adolescents. Parental and child perception scores, DMFT, and gingival index were compared across GMFCS levels using the one-way ANOVA and Scheffe’s post hoc test. Results. Children with level III GMFCS had a significantly higher child perception score (CPQ) and parental perception score (PPQ) than those with level I or level II scores. There was a significant association between function (GMFCS) and the CPQ score in children ( p=0.016 ). No significant associations were found between the CPQ score and either dental caries (DMFT) or gingival bleeding (GI) scores. Children with GMFCS level III had a significantly higher DMFT ( p=0.002 ) and GI ( p=0.001 ) scores. Conclusion. Motor function has a significant impact on both the oral health and the OHRQoL of adolescents and young adults with spastic cerebral palsy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".