Effects of Dental Rehabilitation under General Anesthesia on Children’s Oral-Health-Related Quality of Life: Saudi Arabian Parents’ Perspectives
Bibliographic record
Abstract
Aim: To determine whether dental treatment under general anesthesia (GA) would improve quality of life for children as reported by Saudi Arabian parents using a Parental-Caregivers Perceptions Questionnaire (P-CPQ) and a Family Impact Scale (FIS). Methods: Sixty-six parents completed P-CPQ and FIS scales four to eight weeks after their children (ages three to ten years) underwent comprehensive dental treatment under GA. Postoperative data were compared with baseline data gathered before GA using paired t-test at the 0.05 level of significance. The responsiveness of the P-CPQ and the FIS and the magnitude of changes in children’s quality of life as a result of dental treatment were determined by calculating the effect size (ES). Cross-sectional construct validity and internal consistency were also examined using the pretreatment scores of the P-CPQ and the FIS scores. Results: The overall P-CPQ and FIS scores showed a significant decrease following treatment, concomitant with large ES in both scales and all their subscales with the exception of social wellbeing, which showed moderate ES (ES 0.59). The greatest relative changes were seen in the oral symptoms (ES 1.81) and the family activity (ES 1.57) subscales. Conclusion: Dental treatment under GA is associated with considerable improvement in children’s quality of life as perceived by Saudi parents. The P-CPQ and the FIS scales are valid and responsive to changes resulting from dental treatment of young children affected by severe childhood caries.
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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 | 0.001 | 0.002 |
| 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".