Does Patient Age Impact In-Office Tooth Bleaching Outcomes? A Parallel Clinical Trial
Bibliographic record
Abstract
OBJECTIVES: To assess the influence of patient age on tooth sensitivity, bleaching effectiveness, and the self-perception and psychosocial impact of dental esthetics following in-office tooth bleaching with 35% hydrogen peroxide. METHODS: This parallel study categorized 56 subjects by age into early adulthood (18-25 years) and middle-aged (40-65 years) groups. The bleaching agent was applied in a single 45-minute session, spanning two bleaching sessions at a 1-week interval. Bleaching effectiveness assessment used upper incisors and canines. A shade guide (VITA Bleachedguide 3D-MASTER) and a portable spectrophotometer evaluated color changes. A visual analog scale and verbal rating scale recorded tooth sensitivity during and up to 48 hours after the bleaching procedure. The Psychosocial Impact of Dental Aesthetics Questionnaire measured the self-perception and psychosocial impact of the bleaching protocol. Student t-test, Fisher exact test, Mann-Whitney, multivariate analysis of variance, chi-square, two-way repeated measures analysis of variance, and the Wilcoxon test (α=0.05) verified the data. RESULTS: Early adulthood subjects demonstrated a significant increase (17%) in the risk of tooth sensitivity (p=0.038), and the highest pain levels occurred 1 hour after the bleaching session (p<0.01). Nonetheless, early adulthood subjects showed improved bleaching effects 30 days after the procedure when compared to the middle-aged subjects, even though the overall perception of the psychosocial impact of dental esthetics was more evident in middle-aged subjects. CONCLUSIONS: Patient age influenced in-office bleaching outcomes. Both age groups reported esthetic satisfaction, but early adulthood subjects (18-25 years) experienced a more substantial whitening effect, greater dentin sensitivity, and higher psychological impact. Conversely, middle-aged subjects (40-65 years) had a better overall perception of the psychosocial impact of dental esthetics.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".